TY  - JOUR
AB  - Here we report the results from exploratory analysis using a Bayesian network approach of data originally derived from a large North European study of type 2 diabetes (T2D) conducted by the IMI DIRECT consortium. 3029 individuals (795 with T2D and 2234 without) within 7 different study centres provided data comprising genotypes, proteins, metabolites, gene expression measurements and many different clinical variables. The main aim of the current study was to demonstrate the utility of our previously developed method to fit Bayesian networks by performing exploratory analysis of this dataset to identify possible causal relationships between these variables. The data was analysed using the BayesNetty software package, which can handle mixed discrete/continuous data with missing values. The original dataset consisted of over 16,000 variables, which were filtered down to 260 variables for analysis. Even with this reduction, no individual had complete data for all variables, making it impossible to analyse using standard Bayesian network methodology. However, using the recently proposed novel imputation method implemented in BayesNetty we computed a large average Bayesian network from which we could infer possible associations and causal relationships between variables of interest. Our results confirmed many previous findings in connection with T2D, including possible mediating proteins and genes, some of which have not been widely reported. We also confirmed potential causal relationships with liver fat that were identified in an earlier study that used the IMI DIRECT dataset but was limited to a smaller subset of individuals and variables (namely individuals with complete data at pre-defined variables of interest). In addition to providing valuable confirmation, our analyses thus demonstrate a proof-of-principle of the utility of the method implemented within BayesNetty. The full final average Bayesian network generated from our analysis is freely available and can be easily interrogated further to address specific focussed scientific questions of interest.
AU  - Howey, R.*
AU  - Adam, J.
AU  - Adamski, J.
AU  - Atabaki, N.N.*
AU  - Brunak, S.*
AU  - Chmura, P.J.*
AU  - De Masi, F.*
AU  - Dermitzakis, E.T.*
AU  - Fernandez-Tajes, J.J.*
AU  - Forgie, I.M.*
AU  - Franks, P.W.*
AU  - Giordano, G.N.*
AU  - Haid, M.
AU  - Hansen, T.*
AU  - Hansen, T.H.*
AU  - Harms, P.P.*
AU  - Hattersley, A.T.*
AU  - Hong, M.G.*
AU  - Jacobsen, U.P.*
AU  - Jones, A.G.*
AU  - Koivula, R.W.*
AU  - Kokkola, T.*
AU  - Mahajan, A.*
AU  - Mari, A.*
AU  - McCarthy, M.I.*
AU  - McDonald, T.J.*
AU  - Musholt, P.B.*
AU  - Pavo, I.*
AU  - Pearson, E.R.*
AU  - Pedersen, O.*
AU  - Ruetten, H.*
AU  - Rutters, F.*
AU  - Schwenk, J.M.*
AU  - Sharma, S.
AU  - 't Hart, L.M.*
AU  - Vestergaard, H.*
AU  - Walker, M.*
AU  - Viñuela, A.*
AU  - Cordell, H.J.*
C1  - 75142
C2  - 57823
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Bayesian network imputation methods applied to multi-omics data identify putative causal relationships in a type 2 diabetes dataset containing incomplete data: An IMI DIRECT Study.
JO  - PLoS Genet.
VL  - 21
IS  - 7
PB  - Public Library Science
PY  - 2025
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Circulating metabolite levels have been associated with type 2 diabetes (T2D), but the extent to which T2D affects metabolite levels and their genetic regulation remains to be elucidated. In this study, we investigate the interplay between genetics, metabolomics, and T2D risk in the UK Biobank dataset using the Nightingale panel composed of 249 metabolites, 92% of which correspond to lipids (HDL, IDL, LDL, VLDL) and lipoproteins. By integrating these data with large-scale T2D GWAS from the DIAMANTE meta-analysis through Mendelian randomization analyses, we find 79 metabolites with a causal association to T2D, all spanning lipid-related classes except for Glucose and Tyrosine. Twice as many metabolites are causally affected by T2D liability, spanning almost all tested classes, including branched-chain amino acids. Secondly, using an interaction quantitative trait locus (QTL) analysis, we describe four metabolites consistently replicated in an independent dataset from the Estonian Biobank, for which genetic loci in two different genomic regions show attenuated regulation in T2D cases compared to controls. The significant variants from the interaction QTL analysis are significant QTLs for the corresponding metabolites in the general population but are not associated with T2D risk, pointing towards consequences of T2D on the genetic regulation of metabolite levels. Finally, through differential level analyses, we find 165 metabolites associated with microvascular, macrovascular, or both types of T2D complications, with only a few discriminating between complication classes. Of the 165 metabolites, 40 are not causally linked to T2D in either direction, suggesting biological mechanisms specific to the occurrence of complications. Overall, this work provides a map of the consequences of T2D on Nightingale targeted metabolite levels and on their genetic regulation, enabling a better understanding of the T2D trajectory leading to complications.
AU  - Bocher, O.
AU  - Singh, A.
AU  - Huang, Y.
AU  - Võsa, U.*
AU  - Reimann, E.
AU  - Arruda, A.L.
AU  - Barysenska, A.
AU  - Kolde, A.*
AU  - Rayner, N.W.
AU  - Esko, T.*
AU  - Mägi, R.*
AU  - Zeggini, E.
C1  - 72603
C2  - 56671
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Disentangling the consequences of type 2 diabetes on targeted metabolite profiles using causal inference and interaction QTL analyses.
JO  - PLoS Genet.
VL  - 20
IS  - 12
PB  - Public Library Science
PY  - 2024
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.
AU  - Kerimov, N.*
AU  - Tambets, R.*
AU  - Hayhurst, J.D.*
AU  - Rahu, I.*
AU  - Kolberg, P.*
AU  - Raudvere, U.*
AU  - Kuzmin, I.*
AU  - Chowdhary A.
AU  - Vija, A.*
AU  - Teras, H.J.*
AU  - Kanai, M.*
AU  - Ulirsch, J.*
AU  - Ryten, M.*
AU  - Hardy, J.*
AU  - Guelfi, S.*
AU  - Trabzuni, D.*
AU  - Kim-Hellmuth, S.
AU  - Rayner, N.W.
AU  - Finucane, H.*
AU  - Peterson, H.*
AU  - Mosaku, A.*
AU  - Parkinson, H.*
AU  - Alasoo, K.*
C1  - 68241
C2  - 54789
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs.
JO  - PLoS Genet.
VL  - 19
IS  - 9
PB  - Public Library Science
PY  - 2023
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.
AU  - Bocher, O.
AU  - Ludwig, T.E.*
AU  - Oglobinsky, M.S.*
AU  - Marenne, G.*
AU  - Deleuze, J.F.*
AU  - Suryakant, S.*
AU  - Odeberg, J.*
AU  - Morange, P.E.*
AU  - Tregouet, D.A.*
AU  - Perdry, H.*
AU  - Genin, E.*
C1  - 66391
C2  - 53164
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score.
JO  - PLoS Genet.
VL  - 18
IS  - 9
PB  - Public Library Science
PY  - 2022
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.
AU  - Butler-Laporte, G.*
AU  - Povysil, G.*
AU  - Kosmicki, J.A.*
AU  - Cirulli, E.T.*
AU  - Drivas, T.*
AU  - Furini, S.*
AU  - Saad, C.*
AU  - Schmidt, A.*
AU  - Olszewski, P.K.*
AU  - Korotko, U.*
AU  - Quinodoz, M.*
AU  - Çelik, E.*
AU  - Kundu, K.*
AU  - Walter, K.*
AU  - Jung, J.*
AU  - Stockwell, A.D.*
AU  - Sloofman, L.G.*
AU  - Jordan, D.M.*
AU  - Thompson, R.C.*
AU  - Del Valle, D.*
AU  - Simons, N.*
AU  - Cheng, E.*
AU  - Sebra, R.*
AU  - Schadt, E.E.*
AU  - Kim-Schulze, S.*
AU  - Gnjatic, S.*
AU  - Merad, M.*
AU  - Buxbaum, J.D.*
AU  - Beckmann, N.D.*
AU  - Charney, A.W.*
AU  - Przychodzen, B.*
AU  - Chang, T.*
AU  - Pottinger, T.D.*
AU  - Shang, N.*
AU  - Brand, F.*
AU  - Fava, F.*
AU  - Mari, F.*
AU  - Chwialkowska, K.*
AU  - Niemira, M.*
AU  - Pula, S.*
AU  - Baillie, J.K.*
AU  - Stuckey, A.*
AU  - Salas, A.*
AU  - Bello, X.*
AU  - Pardo-Seco, J.*
AU  - Gómez-Carballa, A.*
AU  - Rivero-Calle, I.*
AU  - Martinón-Torres, F.*
AU  - Ganna, A.*
AU  - Karczewski, K.J.*
AU  - Veerapen, K.*
AU  - Bourgey, M.*
AU  - Bourque, G.*
AU  - Eveleigh, R.J.*
AU  - Forgetta, V.*
AU  - Morrison, D.*
AU  - Langlais, D.*
AU  - Lathrop, M.*
AU  - Mooser, V.*
AU  - Nakanishi, T.*
AU  - Frithiof, R.*
AU  - Hultström, M.*
AU  - Lipcsey, M.*
AU  - Marincevic-Zuniga, Y.*
AU  - Nordlund, J.*
AU  - Schiabor Barrett, K.M.*
AU  - Lee, W.*
AU  - Bolze, A.*
AU  - White, S.*
AU  - Riffle, S.*
AU  - Tanudjaja, F.*
AU  - Sandoval, E.*
AU  - Neveux, I.*
AU  - Dabe, S.*
AU  - Casadei, N.*
AU  - Motameny, S.*
AU  - Alaamery, M.*
AU  - Massadeh, S.*
AU  - Aljawini, N.*
AU  - Almutairi, M.S.*
AU  - Arabi, Y.M.*
AU  - Alqahtani, S.A.*
AU  - Al Harthi, F.S.*
AU  - Almutairi, A.*
AU  - Alqubaishi, F.*
AU  - Alotaibi, S.*
AU  - Binowayn, A.*
AU  - Alsolm, E.A.*
AU  - El Bardisy, H.*
AU  - Fawzy, M.*
AU  - Cai, F.*
AU  - Soranzo, N.*
AU  - Butterworth, A.*
AU  - COVID-19 Host Genetics Initiative*
AU  - DeCOI Host Genetics Group*
AU  - GEN-COVID Multicenter Study (Italy)*
AU  - Mount Sinai Clinical Intelligence Center*
AU  - GEN-COVID consortium (Spain)*
AU  - GenOMICC Consortium*
AU  - Japan COVID-19 Task Force*
AU  - Regeneron Genetics Center*
AU  - Geschwind, D.H.*
AU  - Arteaga, S.*
AU  - Stephens, A.E.*
AU  - Butte, M.J.*
AU  - Boutros, P.C.*
AU  - Yamaguchi, T.N.*
AU  - Tao, S.*
AU  - Eng, S.*
AU  - Sanders, T.*
AU  - Tung, P.J.*
AU  - Broudy, M.E.*
AU  - Pan, Y.*
AU  - González, A.J.*
AU  - Chavan, N.*
AU  - Johnson, R.*
AU  - Pasaniuc, B.*
AU  - Yaspan, B.L.*
AU  - Smieszek, S.*
AU  - Rivolta, C.*
AU  - Bibert, S.*
AU  - Bochud, P.Y.*
AU  - Dabrowski, M.*
AU  - Zawadzki, P.*
AU  - Sypniewski, M.*
AU  - Kaja, E.*
AU  - Chariyavilaskul, P.*
AU  - Nilaratanakul, V.*
AU  - Hirankarn, N.*
AU  - Shotelersuk, V.*
AU  - Pongpanich, M.*
AU  - Phokaew, C.*
AU  - Chetruengchai, W.*
AU  - Tokunaga, K.*
AU  - Sugiyama, M.*
AU  - Kawai, Y.*
AU  - Hasegawa, T.*
AU  - Naito, T.*
AU  - Namkoong, H.*
AU  - Edahiro, R.*
AU  - Kimura, A.*
AU  - Ogawa, S.*
AU  - Kanai, T.*
AU  - Fukunaga, K.*
AU  - Imoto, S.*
AU  - Miyano, S.*
AU  - Mangul, S.*
AU  - Abedalthagafi, M.S.*
AU  - Zeberg, H.*
AU  - Grzymski, J.J.*
AU  - Washington, N.L.*
AU  - Ossowski, S.*
AU  - Ludwig, K.U.*
AU  - Schulte, E.C.
AU  - Riess, O.*
AU  - Moniuszko, M.*
AU  - Kwasniewski, M.*
AU  - Mbarek, H.*
AU  - Ismail, S.I.*
AU  - Verma, A.*
AU  - Goldstein, D.B.*
AU  - Kiryluk, K.*
AU  - Renieri, A.*
AU  - Richards, J.B.*
C1  - 66617
C2  - 53254
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.
JO  - PLoS Genet.
VL  - 18
IS  - 11
PB  - Public Library Science
PY  - 2022
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Mitochondrial DNA (mtDNA) maintenance disorders are caused by mutations in ubiquitously expressed nuclear genes and lead to syndromes with variable disease severity and tissue-specific phenotypes. Loss of function mutations in the gene encoding the mitochondrial genome and maintenance exonuclease 1 (MGME1) result in deletions and depletion of mtDNA leading to adult-onset multisystem mitochondrial disease in humans. To better understand the in vivo function of MGME1 and the associated disease pathophysiology, we characterized a Mgme1 mouse knockout model by extensive phenotyping of ageing knockout animals. We show that loss of MGME1 leads to de novo formation of linear deleted mtDNA fragments that are constantly made and degraded. These findings contradict previous proposal that MGME1 is essential for degradation of linear mtDNA fragments and instead support a model where MGME1 has a critical role in completion of mtDNA replication. We report that Mgme1 knockout mice develop a dramatic phenotype as they age and display progressive weight loss, cataract and retinopathy. Surprisingly, aged animals also develop kidney inflammation, glomerular changes and severe chronic progressive nephropathy, consistent with nephrotic syndrome. These findings link the faulty mtDNA synthesis to severe inflammatory disease and thus show that defective mtDNA replication can trigger an immune response that causes age-associated progressive pathology in the kidney.
AU  - Milenkovic, D.*
AU  - Sanz-Moreno, A.
AU  - Calzada-Wack, J.
AU  - Rathkolb, B.
AU  - Amarie, O.V.
AU  - Gerlini, R.
AU  - Aguilar-Pimentel, J.A.
AU  - Misic, J.*
AU  - Simard, M.L.*
AU  - Wolf, E.*
AU  - Fuchs, H.
AU  - Gailus-Durner, V.
AU  - Hrabě de Angelis, M.
AU  - Larsson, N.-G.*
C1  - 65015
C2  - 52032
TI  - Mice lacking the mitochondrial exonuclease MGME1 develop inflammatory kidney disease with glomerular dysfunction.
JO  - PLoS Genet.
VL  - 18
IS  - 5
PY  - 2022
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Mammalian cells release different types of vesicles, collectively termed extracellular vesicles (EVs). EVs contain cellular microRNAs (miRNAs) with an apparent potential to deliver their miRNA cargo to recipient cells to affect the stability of individual mRNAs and the cells' transcriptome. The extent to which miRNAs are exported via the EV route and whether they contribute to cell-cell communication are controversial. To address these issues, we defined multiple properties of EVs and analyzed their capacity to deliver packaged miRNAs into target cells to exert biological functions. We applied well-defined approaches to produce and characterize purified EVs with or without specific viral miRNAs. We found that only a small fraction of EVs carried miRNAs. EVs readily bound to different target cell types, but EVs did not fuse detectably with cellular membranes to deliver their cargo. We engineered EVs to be fusogenic and document their capacity to deliver functional messenger RNAs. Engineered fusogenic EVs, however, did not detectably alter the functionality of cells exposed to miRNA-carrying EVs. These results suggest that EV-borne miRNAs do not act as effectors of cell-to-cell communication.
AU  - Albanese, M.
AU  - Chen, Y.-F. A.
AU  - Hüls, C.
AU  - Gärtner, K.
AU  - Tagawa, T.
AU  - Mejias-Perez, E.*
AU  - Keppler, O.T.*
AU  - Göbel,C.
AU  - Zeidler, R.
AU  - Shein, M.*
AU  - Schütz, A.K.
AU  - Hammerschmidt, W.
C1  - 63708
C2  - 51744
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - MicroRNAs are minor constituents of extracellular vesicles that are rarely delivered to target cells.
JO  - PLoS Genet.
VL  - 17
IS  - 12
PB  - Public Library Science
PY  - 2021
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The endo-lysosomal two-pore channel (TPC2) has been established as an intracellular cation channel of significant physiological and pathophysiological relevance in recent years. For example, TPC2-/- mice show defects in cholesterol degradation, leading to hypercholesterinemia; TPC2 absence also results in mature-onset obesity, and a role in glucagon secretion and diabetes has been proposed. Infections with bacterial toxins or viruses e.g., cholera toxin or Ebola virus result in reduced infectivity rates in the absence of TPC2 or after pharmacological blockage, and TPC2-/- cancer cells lose their ability to migrate and metastasize efficiently. Finally, melanin production is affected by changes in hTPC2 activity, resulting in pigmentation defects and hair color variation. Here, we analyzed several publicly available genome variation data sets and identified multiple variations in the TPC2 protein in distinct human populations. Surprisingly, one variation, L564P, was found to be the predominant TPC2 isoform on a global scale. By applying endo-lysosomal patch-clamp electrophysiology, we found that L564P is a prerequisite for the previously described M484L gain-of-function effect that is associated with blond hair. Additionally, other gain-of-function variants with distinct geographical and ethnic distribution were discovered and functionally characterized. A meta-analysis of genome-wide association studies was performed, finding the polymorphisms to be associated with both distinct and overlapping traits. In sum, we present the first systematic analysis of variations in TPC2. We functionally characterized the most common variations and assessed their association with various disease traits. With TPC2 emerging as a novel drug target for the treatment of various diseases, this study provides valuable insights into ethnic and geographical distribution of TPC2 polymorphisms and their effects on channel activity.
AU  - Böck, J.*
AU  - Krogsaeter, E.*
AU  - Passon, M.*
AU  - Chao, Y.K.*
AU  - Sharma, S.
AU  - Grallert, H.
AU  - Peters, A.
AU  - Grimm, C.*
C1  - 61087
C2  - 49815
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Human genome diversity data reveal that L564P is the predominant TPC2 variant and a prerequisite for the blond hair associated M484L gain-of-function effect.
JO  - PLoS Genet.
VL  - 17
IS  - 1
PB  - Public Library Science
PY  - 2021
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Epigenetic mechanisms are gatekeepers for the gene expression patterns that establish and maintain cellular identity in mammalian development, stem cells and adult homeostasis. Amongst many epigenetic marks, methylation of histone 3 lysine 4 (H3K4) is one of the most widely conserved and occupies a central position in gene expression. Mixed lineage leukemia 1 (MLL1/KMT2A) is the founding mammalian H3K4 methyltransferase. It was discovered as the causative mutation in early onset leukemia and subsequently found to be required for the establishment of definitive hematopoiesis and the maintenance of adult hematopoietic stem cells. Despite wide expression, the roles of MLL1 in non-hematopoietic tissues remain largely unexplored. To bypass hematopoietic lethality, we used bone marrow transplantation and conditional mutagenesis to discover that the most overt phenotype in adult Mll1-mutant mice is intestinal failure. MLL1 is expressed in intestinal stem cells (ISCs) and transit amplifying (TA) cells but not in the villus. Loss of MLL1 is accompanied by loss of ISCs and a differentiation bias towards the secretory lineage with increased numbers and enlargement of goblet cells. Expression profiling of sorted ISCs revealed that MLL1 is required to promote expression of several definitive intestinal transcription factors including Pitx1, Pitx2, Foxa1, Gata4, Zfp503 and Onecut2, as well as the H3K27me3 binder, Bahcc1. These results were recapitulated using conditional mutagenesis in intestinal organoids. The stem cell niche in the crypt includes ISCs in close association with Paneth cells. Loss of MLL1 from ISCs promoted transcriptional changes in Paneth cells involving metabolic and stress responses. Here we add ISCs to the MLL1 repertoire and observe that all known functions of MLL1 relate to the properties of somatic stem cells, thereby highlighting the suggestion that MLL1 is a master somatic stem cell regulator.
AU  - Goveas, N.*
AU  - Waskow, C.*
AU  - Arndt, K.*
AU  - Heuberger, J.*
AU  - Zhang, Q.*
AU  - Alexopoulou, D.
AU  - Dahl, A.*
AU  - Birchmeier, W.*
AU  - Anastassiadis, K.*
AU  - Stewart, A.F.*
AU  - Kranz, A.*
C1  - 63723
C2  - 51757
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - MLL1 is required for maintenance of intestinal stem cells.
JO  - PLoS Genet.
VL  - 17
IS  - 12
PB  - Public Library Science
PY  - 2021
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The genetic landscape of diseases associated with changes in bone mineral density (BMD), such as osteoporosis, is only partially understood. Here, we explored data from 3,823 mutant mouse strains for BMD, a measure that is frequently altered in a range of bone pathologies, including osteoporosis. A total of 200 genes were found to significantly affect BMD. This pool of BMD genes comprised 141 genes with previously unknown functions in bone biology and was complementary to pools derived from recent human studies. Nineteen of the 141 genes also caused skeletal abnormalities. Examination of the BMD genes in osteoclasts and osteoblasts underscored BMD pathways, including vesicle transport, in these cells and together with in silico bone turnover studies resulted in the prioritization of candidate genes for further investigation. Overall, the results add novel pathophysiological and molecular insight into bone health and disease.
AU  - Swan, A.L.*
AU  - Schütt, C.
AU  - Rozman, J.
AU  - Del Mar Muñiz Moreno, M.*
AU  - Brandmaier, S.
AU  - Simon, M.*
AU  - Leuchtenberger, S.
AU  - Griffiths, M.*
AU  - Brommage, R.
AU  - Keskivali-Bond, P.*
AU  - Grallert, H.
AU  - Werner, T.*
AU  - Teperino, R.
AU  - Becker, L.
AU  - Miller, G.
AU  - Moshiri, A.*
AU  - Seavitt, J.R.*
AU  - Cissell, D.D.*
AU  - Meehan, T.F.*
AU  - Acar, E.F.*
AU  - Lelliott, C.J.*
AU  - Flenniken, A.M.*
AU  - Champy, M.F.*
AU  - Sorg, T.*
AU  - Ayadi, A.*
AU  - Braun, R.E.*
AU  - Cater, H.*
AU  - Dickinson, M.E.*
AU  - Flicek, P.*
AU  - Gallegos, J.*
AU  - Ghirardello, E.J.*
AU  - Heaney, J.D.*
AU  - Jacquot, S.*
AU  - Lally, C.*
AU  - Logan, J.G.*
AU  - Teboul, L.*
AU  - Mason, J.*
AU  - Spielmann, N.
AU  - McKerlie, C.*
AU  - Murray, S.A.*
AU  - Nutter, L.M.J.*
AU  - Odfalk, K.F.*
AU  - Parkinson, H.*
AU  - Prochazka, J.*
AU  - Reynolds, C.L.*
AU  - Selloum, M.*
AU  - Spoutil, F.*
AU  - Svenson, K.L.*
AU  - Vales, T.S.*
AU  - Wells, S.E.*
AU  - White, J.K.*
AU  - Sedlacek, R.*
AU  - Wurst, W.
AU  - Lloyd, K.K.C.*
AU  - Croucher, P.I.*
AU  - Fuchs, H.
AU  - Williams, G.R.*
AU  - Bassett, D.*
AU  - Gailus-Durner, V.
AU  - Herault, Y.*
AU  - Mallon, A.M.*
AU  - Brown, S.D.M.*
AU  - Mayer-Kuckuk, P.
AU  - Hrabě de Angelis, M.
AU  - IMPC Consortium (Aguilar-Pimentel, J.A.
AU  - Amarie, O.V.
AU  - Bürger, A.
AU  - Calzada-Wack, J.
AU  - Cho, Y.-L.
AU  - Giesert, F.
AU  - Garrett, L.
AU  - Graw, J.
AU  - Hörlein, A.
AU  - Hölter, S.M.
AU  - Klein-Rodewald, T.
AU  - Kühn, R.
AU  - Lengger, C.
AU  - Marschall, S.
AU  - Rathkolb, B.
AU  - Sanz-Moreno, A.
AU  - Seisenberger, C.
AU  - Steinkamp, R.
AU  - Stoeger, C.
AU  - Treise, I.
AU  - Zimprich, A.)
AU  - Beckers, J.
C1  - 60963
C2  - 49605
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density.
JO  - PLoS Genet.
VL  - 16
IS  - 12
PB  - Public Library Science
PY  - 2021
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Compromising mitochondrial fusion or fission disrupts cellular homeostasis; however, the underlying mechanism(s) are not fully understood. The loss of C. elegans fzo-1MFN results in mitochondrial fragmentation, decreased mitochondrial membrane potential and the induction of the mitochondrial unfolded protein response (UPRmt). We performed a genome-wide RNAi screen for genes that when knocked-down suppress fzo-1MFN(lf)-induced UPRmt. Of the 299 genes identified, 143 encode negative regulators of autophagy, many of which have previously not been implicated in this cellular quality control mechanism. We present evidence that increased autophagic flux suppresses fzo-1MFN(lf)-induced UPRmt by increasing mitochondrial membrane potential rather than restoring mitochondrial morphology. Furthermore, we demonstrate that increased autophagic flux also suppresses UPRmt induction in response to a block in mitochondrial fission, but not in response to the loss of spg-7AFG3L2, which encodes a mitochondrial metalloprotease. Finally, we found that blocking mitochondrial fusion or fission leads to increased levels of certain types of triacylglycerols and that this is at least partially reverted by the induction of autophagy. We propose that the breakdown of these triacylglycerols through autophagy leads to elevated metabolic activity, thereby increasing mitochondrial membrane potential and restoring mitochondrial and cellular homeostasis.
AU  - Haeussler, S.*
AU  - Köhler, F.*
AU  - Witting, M.
AU  - Premm, M.F.*
AU  - Rolland, S.G.*
AU  - Fischer, C.*
AU  - Chauve, L.*
AU  - Casanueva, O.*
AU  - Conradt, B.*
C1  - 58636
C2  - 48287
TI  - Autophagy compensates for defects in mitochondrial dynamics.
JO  - PLoS Genet.
VL  - 16
IS  - 3
PY  - 2020
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Author summary Essential tremor (ET) is the most common adult-onset movement disorder and in most affected families it appears to be inherited in an autosomal dominant pattern. The causes of essential tremor are unknown. Although many genetic studies in affected families and sporadic cases of ET have shown that genes may play a role, it has proven quite challenging to identify the specific genetic variants involved. Here, we use state-of-the-art technologies to identify the role of genetic variants on ET through exome sequencing of a large affected ET family and subsequent validation in a large population of cases and controls. We show that rare nonsynonymous variants of theTUBgene are significantly enriched in ET cases versus healthy controls. Further studies of biological pathways regulated by TUB in the mouse brain reveal key pathways related to ET. Our work expands our knowledge of the genetic basis of ET.Essential tremor (ET) is the most common adult-onset movement disorder. In the present study, we performed whole exome sequencing of a large ET-affected family (10 affected and 6 un-affected family members) and identified aTUBp.V431I variant (rs75594955) segregating in a manner consistent with autosomal-dominant inheritance. Subsequent targeted re-sequencing ofTUBin 820 unrelated individuals with sporadic ET and 630 controls revealed significant enrichment of rare nonsynonymousTUBvariants (e.g. rs75594955: p.V431I, rs1241709665: p.Ile20Phe, rs55648406: p.Arg49Gln) in the ET cohort (SKAT-O test p-value = 6.20e-08).TUBencodes a transcription factor predominantly expressed in neuronal cells and has been previously implicated in obesity. ChIP-seq analyses of the TUB transcription factor across different regions of the mouse brain revealed that TUB regulates the pathways responsible for neurotransmitter production as well thyroid hormone signaling. Together, these results support the association of rare variants inTUBwith ET.
AU  - Reza Sailani, M.*
AU  - Jahanbani, F.*
AU  - Abbott, C.W.*
AU  - Lee, H.*
AU  - Zia, A.*
AU  - Rego, S.*
AU  - Winkelmann, J.
AU  - Hopfner, F.*
AU  - Khan, T.N.*
AU  - Katsanis, N.*
AU  - Müller, S.H.*
AU  - Berg, D.*
AU  - Lyman, K.M.*
AU  - Mychajliw, C.*
AU  - Deuschl, G.*
AU  - Bernstein, J.A.*
AU  - Kuhlenbäumer, G.*
AU  - Snyder, M.P.*
C1  - 60291
C2  - 49135
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Candidate variants in TUB are associated with familial tremor.
JO  - PLoS Genet.
VL  - 16
IS  - 9
PB  - Public Library Science
PY  - 2020
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Author summaryCardiovascular diseases (CVD) are the number one cause of death globally. Various metabolic biomarkers including lipid and lipoprotein particles have been implicated as risk factors for the development of CVD. Understanding how these biomarkers are regulated can lead to increased understanding of CVD aetiology and the potential identification of drug targets. Here we take advantage of high resolution measurements on a large cohort of 7,142 healthy blood donors with whole-exome and whole-genome sequencing data to explore the influence of rare variation on circulating metabolic biomarker levels. Using a novel approach leveraging the information gained from various measurements on the same participants we are able to identify a novel biological pathway involved in the regulation of intermediate-density and low-density lipoproteins as well as circulating cholesterol, confirm various established gene associations and identify potential novel gene associations that merit further replication. This work highlights the advantages that can be gained by combining high resolution genotypic and phenotypic measurements in one large cohort.Circulating metabolite levels are biomarkers for cardiovascular disease (CVD). Here we studied, association of rare variants and 226 serum lipoproteins, lipids and amino acids in 7,142 (discovery plus follow-up) healthy participants. We leveraged the information from multiple metabolite measurements on the same participants to improve discovery in rare variant association analyses for gene-based and gene-set tests by incorporating correlated metabolites as covariates in the validation stage. Gene-based analysis corrected for the effective number of tests performed, confirmed established associations at APOB, APOC3, PAH, HAL and PCSK (p<1.32x10(-7)) and identified novel gene-trait associations at a lower stringency threshold with ACSL1, MYCN, FBXO36 and B4GALNT3 (p<2.5x10(-6)). Regulation of the pyruvate dehydrogenase (PDH) complex was associated for the first time, in gene-set analyses also corrected for effective number of tests, with IDL and LDL parameters, as well as circulating cholesterol (p(METASKAT)<2.41x10(-6)). In conclusion, using an approach that leverages metabolite measurements obtained in the same participants, we identified novel loci and pathways involved in the regulation of these important metabolic biomarkers. As large-scale biobanks continue to amass sequencing and phenotypic information, analytical approaches such as ours will be useful to fully exploit the copious amounts of biological data generated in these efforts.
AU  - Riveros-McKay, F.*
AU  - Oliver-Williams, C.*
AU  - Karthikeyan, S.*
AU  - Walter, K.*
AU  - Kundu, K.*
AU  - Ouwehand, W.H.*
AU  - Roberts, D.*
AU  - Soranzo, N.*
AU  - Wheeler, E.*
AU  - Zeggini, E.
AU  - Barroso, I.*
C1  - 58544
C2  - 48316
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - The influence of rare variants in circulating metabolic biomarkers.
JO  - PLoS Genet.
VL  - 16
IS  - 3
PB  - Public Library Science
PY  - 2020
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located nearNEDD4LandSLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (R(g)ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.Author summary Although twin studies have shown that body mass index (BMI) is highly heritable, many common genetic variants involved in the development of BMI have not yet been identified, especially in children. We studied associations of more than 40 million genetic variants with childhood BMI in 61,111 children aged between 2 and 10 years. We identified 25 genetic variants that were associated with childhood BMI. Two of these have not been implicated for BMI previously, located close to the genesNEDD4LandSLC45A3. We also show that the genetic background of childhood BMI overlaps with that of birth weight, adult BMI, waist-to-hip-ratio, diastolic blood pressure, type 2 diabetes, and age at menarche. Our results suggest that the biological processes underlying childhood BMI largely overlap with those underlying adult BMI. However, the overlap is not complete. Additionally, the genetic backgrounds of childhood BMI and other cardio-metabolic phenotypes are overlapping. This may mean that the associations of childhood BMI and later cardio-metabolic outcomes are partially explained by shared genetics, but it could also be explained by the strong association of childhood BMI with adult BMI.
AU  - Vogelezang, S.*
AU  - Bradfield, J.P.*
AU  - Ahluwalia, T.S.*
AU  - Curtin, J.A.*
AU  - Lakka, T.A.*
AU  - Grarup, N.*
AU  - Scholz, M.*
AU  - van der Most, P.J.*
AU  - Monnereau, C.*
AU  - Stergiakouli, E.*
AU  - Heiskala, A.*
AU  - Horikoshi, M.*
AU  - Fedko, I.O.*
AU  - Vilor-Tejedor, N.*
AU  - Cousminer, D.L.*
AU  - Standl, M.
AU  - Wang, C.A.*
AU  - Viikari, J.*
AU  - Geller, F.*
AU  - Iñiguez, C.*
AU  - Pitkänen, N.*
AU  - Chesi, A.*
AU  - Bacelis, J.*
AU  - Yengo, L.*
AU  - Torrent, M.*
AU  - Ntalla, I.*
AU  - Helgeland, Ø.*
AU  - Selzam, S.*
AU  - Vonk, J.M.*
AU  - Zafarmand, M.H.*
AU  - Heude, B.*
AU  - Farooqi, I.S.*
AU  - Alyass, A.*
AU  - Beaumont, R.N.*
AU  - Have, C.T.*
AU  - Rzehak, P.*
AU  - Bilbao, J.R.*
AU  - Schnurr, T.M.*
AU  - Barroso, I.*
AU  - Bønnelykke, K.*
AU  - Beilin, L.J.*
AU  - Carstensen, L.*
AU  - Charles, M.A.*
AU  - Chawes, B.*
AU  - Clément, K.*
AU  - Closa-Monasterolo, R.*
AU  - Custovic, A.*
AU  - Eriksson, J.G.*
AU  - Escribano, J.*
AU  - Groen-Blokhuis, M.*
AU  - Grote, V.*
AU  - Gruszfeld, D.*
AU  - Hakonarson, H.*
AU  - Hansen, T.*
AU  - Hattersley, A.T.*
AU  - Hollensted, M.*
AU  - Hottenga, J.J.*
AU  - Hyppönen, E.*
AU  - Johansson, S.*
AU  - Joro, R.*
AU  - Kähönen, M.*
AU  - Karhunen, V.*
AU  - Kiess, W.*
AU  - Knight, B.A.*
AU  - Koletzko, B.*
AU  - Kühnapfel, A.*
AU  - Landgraf, K.*
AU  - Langhendries, J.P.*
AU  - Lehtimäki, T.*
AU  - Leinonen, J.T.*
AU  - Li, A.*
AU  - Lindi, V.*
AU  - Lowry, E.*
AU  - Bustamante, M.*
AU  - Medina-Gomez, C.*
AU  - Melbye, M.*
AU  - Michaelsen, K.F.*
AU  - Morgen, C.S.*
AU  - Mori, T.A.*
AU  - Nielsen, T.R.H.*
AU  - Niinikoski, H.*
AU  - Oldehinkel, A.J.*
AU  - Pahkala, K.*
AU  - Panoutsopoulou, K.*
AU  - Pedersen, O.*
AU  - Pennell, C.E.*
AU  - Power, C.*
AU  - Reijneveld, S.A.*
AU  - Rivadeneira, F.*
AU  - Simpson, A.*
AU  - Sly, P.D.*
AU  - Stokholm, J.*
AU  - Teo, K.K.*
AU  - Thiering, E.
AU  - Timpson, N.J.*
AU  - Uitterlinden, A.G.*
AU  - Zeggini, E.
AU  - van Beijsterveldt, C.E.M.*
AU  - van Schaik, B.D.C.*
AU  - Vaudel, M.*
AU  - Verduci, E.*
C1  - 60367
C2  - 49390
CY  - 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
TI  - Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits.
JO  - PLoS Genet.
VL  - 16
IS  - 10
PB  - Public Library Science
PY  - 2020
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Circadian systems provide a fitness advantage to organisms by allowing them to adapt to daily changes of environmental cues, such as light/dark cycles. The molecular mechanism underlying the circadian clock has been well characterized. However, how internal circadian clocks are entrained with regular daily light/dark cycles remains unclear. By collecting and analyzing indirect calorimetry (IC) data from more than 2000 wild-type mice available from the International Mouse Phenotyping Consortium (IMPC), we show that the onset time and peak phase of activity and food intake rhythms are reliable parameters for screening defects of circadian misalignment. We developed a machine learning algorithm to quantify these two parameters in our misalignment screen (SyncScreener) with existing datasets and used it to screen 750 mutant mouse lines from five IMPC phenotyping centres. Mutants of five genes (Slc7a11, Rhbdl1, Spop, Ctc1 and Oxtr) were found to be associated with altered patterns of activity or food intake. By further studying the Slc7a11tm1a/tm1a mice, we confirmed its advanced activity phase phenotype in response to a simulated jetlag and skeleton photoperiod stimuli. Disruption of Slc7a11 affected the intercellular communication in the suprachiasmatic nucleus, suggesting a defect in synchronization of clock neurons. Our study has established a systematic phenotype analysis approach that can be used to uncover the mechanism of circadian entrainment in mice.
AU  - Zhang, T.*
AU  - Xie, P.*
AU  - Dong, Y.*
AU  - Liu, Z.*
AU  - Zhou, F.*
AU  - Pan, D.*
AU  - Huang, Z.*
AU  - Zhai, Q.*
AU  - Gu, Y.*
AU  - Wu, Q.*
AU  - Tanaka, N.*
AU  - Obata, Y.*
AU  - Bradley, A.*
AU  - Lelliott, C.J.*
AU  - Sanger Institute Mouse Genetics Project*
AU  - Nutter, L.M.J.*
AU  - McKerlie, C.*
AU  - Flenniken, A.M.*
AU  - Champy, M.-F.*
AU  - Sorg, T.*
AU  - Herault, Y.*
AU  - Hrabě de Angelis, M.
AU  - Gailus-Durner, V.
AU  - Mallon, A.-M.*
AU  - Brown, S.D.M.*
AU  - Meehan, T.*
AU  - Parkinson, H.E.*
AU  - Smedley, D.*
AU  - Lloyd, K.C.K.*
AU  - Yan, J.*
AU  - Gao, X.*
AU  - Seong, J.K.*
AU  - Wang, C.-K.L.*
AU  - Sedlacek, R.*
AU  - Liu, Y.*
AU  - Rozman, J.
AU  - Yang, L.*
AU  - Xu, Y.*
C1  - 57813
C2  - 48128
TI  - High-throughput discovery of genetic determinants of circadian misalignment.
JO  - PLoS Genet.
VL  - 16
IS  - 1
PY  - 2020
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p<10-16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC (sites VCF available via FTP at ftp.broadinstitute.org/pub/ExAC_release/release0.3/) to pinpoint genetic variation that contributes to variable disease predisposition across populations.
AU  - Rivas, M.A.*
AU  - Avila, B.E.*
AU  - Koskela, J.*
AU  - Huang, H.*
AU  - Stevens, C.F.*
AU  - Pirinen, M.*
AU  - Haritunians, T.*
AU  - Neale, B.M.*
AU  - Kurki, M.*
AU  - Ganna, A.*
AU  - Graham, D.*
AU  - Glaser, B.*
AU  - Peter, I.*
AU  - Atzmon, G.*
AU  - Barzilai, N.*
AU  - Levine, A.P.*
AU  - Schiff, E.*
AU  - Pontikos, N.*
AU  - Weisburd, B.*
AU  - Lek, M.*
AU  - Karczewski, K.J.*
AU  - Bloom, J.*
AU  - Minikel, E.V.*
AU  - Petersen, B.-S.*
AU  - Beaugerie, L.*
AU  - Seksik, P.*
AU  - Cosnes, J.*
AU  - Schreiber, S.*
AU  - Bokemeyer, B.*
AU  - Bethge, J.*
AU  - Heap, G.*
AU  - Ahmad, T.*
AU  - Plagnol, V.*
AU  - Segal, A.W.*
AU  - Targan, S.*
AU  - Turner, D.*
AU  - Saavalainen, P.*
AU  - Farkkila, M.*
AU  - Kontula, K.*
AU  - Palotie, A.*
AU  - Brant, S.R.*
AU  - Duerr, R.H.*
AU  - Silverberg, M.S.*
AU  - Rioux, J.D.*
AU  - Weersma, R.K.*
AU  - Franke, A.*
AU  - Jostins, L.*
AU  - Anderson, C.A.*
AU  - Barrett, J.C.*
AU  - MacArthur, D.G.*
AU  - Jalas, C.*
AU  - Sokol, H.*
AU  - Xavier, R.J.*
AU  - Pulver, A.*
AU  - Cho, J.H.*
AU  - McGovern, D.P.B.*
AU  - Daly, M.J.*
AU  - International IBD Genetics Consortium (IIBDGC) (Gieger, C.
AU  - Winkelmann, J.)
AU  - T2D-GENES Consortium (Schwarzmayr, T.
AU  - Hrabě de Angelis, M.
AU  - Thorand, B.
AU  - Meisinger, C.
AU  - Peters, A.
AU  - Grallert, H.
AU  - Strauch, K.
AU  - Strom, T.M.
AU  - Meitinger, T.)
C1  - 53597
C2  - 44671
TI  - Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population.
JO  - PLoS Genet.
VL  - 14
IS  - 5
PY  - 2018
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
AU  - Graff, M.*
AU  - Scott, R.A.*
AU  - Justice, A.E.*
AU  - Young, K.L.*
AU  - Feitosa, M.F.*
AU  - Barata, L.*
AU  - Winkler, T.W.*
AU  - Chu, A.Y.*
AU  - Mahajan, A.*
AU  - Hadley, D.*
AU  - Xue, L.*
AU  - Workalemahu, T.*
AU  - Heard-Costa, N.L.*
AU  - den Hoed, M.*
AU  - Ahluwalia, T.S.*
AU  - Qi, Q.*
AU  - Ngwa, J.S.*
AU  - Renström, F.*
AU  - Quaye, L.*
AU  - Eicher, J.D.*
AU  - Hayes, J.E.*
AU  - Cornelis, M.*
AU  - Kutalik, Z.*
AU  - Lim, E.*
AU  - Luan, J.*
AU  - Huffman, J.E.*
AU  - Zhang, W.*
AU  - Zhao, W.*
AU  - Griffin, P.J.*
AU  - Haller, T.*
AU  - Ahmad, S.*
AU  - Marques-Vidal, P.M.*
AU  - Bien, S.A.*
AU  - Yengo, L.*
AU  - Teumer, A.*
AU  - Smith, A.V.*
AU  - Kumari, M.*
AU  - Harder, M.N.*
AU  - Justesen, J.M.*
AU  - Kleber, M.E.*
AU  - Hollensted, M.*
AU  - Lohman, K.*
AU  - Rivera, N.V.*
AU  - Whitfield, J.B.*
AU  - Zhao, J.H.*
AU  - Stringham, H.M.*
AU  - Lyytikäinen, L.-P.*
AU  - Huppertz, C.*
AU  - Willemsen, G.*
AU  - Peyrot, W.J.*
AU  - Wu, Y.*
AU  - Kristiansson, K.*
AU  - Demirkan, A.*
AU  - Grallert, H.
AU  - Rawal, R.
AU  - Huth, C.
AU  - Peters, A.
AU  - Thorand, B.
AU  - Müller-Nurasyid, M.
AU  - Strauch, K.
AU  - Kilpeläinen, T.O.*
AU  - Bragg-Gresham, J.L.*
AU  - Vitart, V.*
AU  - Marten, J.*
AU  - Navarro, P.*
AU  - Bellis, C.*
AU  - Pasko, D.*
AU  - Johansson, Å.*
AU  - Snitker, S.*
AU  - Cheng, Y.C.*
AU  - Eriksson, J.*
AU  - Lim, U.*
AU  - Aadahl, M.*
AU  - Adair, L.S.*
AU  - Gieger, C.
AU  - Holzapfel, C.
C1  - 51114
C2  - 42740
CY  - San Francisco
TI  - Genome-wide physical activity interactions in adiposity ― A meta-analysis of 200,452 adults.
JO  - PLoS Genet.
VL  - 13
IS  - 4
PB  - Public Library Science
PY  - 2017
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Progress in mapping loci associated with common complex diseases or quantitative inherited traits has been expedited by large-scale meta-analyses combining information across multiple studies, assembled through collaborative networks of researchers. Participating studies will usually have been independently designed and implemented in unique settings that are potential sources of phenotype, ancestry or other variability that could introduce between-study heterogeneity into a meta-analysis. Heterogeneity tests based on individual genetic variants (e.g. Q, I-2) are not suited to identifying locus-specific from more systematic multi-locus or genome-wide patterns of heterogeneity. We have developed and evaluated an aggregate heterogeneity M statistic that combines between-study heterogeneity information across multiple genetic variants, to reveal systematic patterns of heterogeneity that elude conventional single variant analysis. Application to a GWAS meta-analysis of coronary disease with 48 contributing studies uncovered substantial systematic between-study heterogeneity, which could be partly explained by age-of-disease onset, family-history of disease and ancestry. Future meta-analyses of diseases and traits with multiple known genetic associations can use this approach to identify outlier studies and thereby optimize power to detect novel genetic associations.
AU  - Magosi, L.E.*
AU  - Goel, A.*
AU  - Hopewell, J.C.*
AU  - Farrall, M.*
AU  - CARDIoGRAMplusC4D Consortium (Gieger, C.
AU  - Peters, A.
AU  - Meitinger, T.)
C1  - 51438
C2  - 43071
CY  - San Francisco
TI  - Identifying systematic heterogeneity patterns in genetic association meta-analysis studies.
JO  - PLoS Genet.
VL  - 13
IS  - 5
PB  - Public Library Science
PY  - 2017
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - KDM2A is a histone demethylase associated with transcriptional silencing, however very little is known about its in vivo role in development and disease. Here we demonstrate that loss of the orthologue kdm2aa in zebrafish causes widespread transcriptional disruption and leads to spontaneous melanomas at a high frequency. Fish homozygous for two independent premature stop codon alleles show reduced growth and survival, a strong male sex bias, and homozygous females exhibit a progressive oogenesis defect. kdm2aa mutant fish also develop melanomas from early adulthood onwards which are independent from mutations in braf and other common oncogenes and tumour suppressors as revealed by deep whole exome sequencing. In addition to effects on translation and DNA replication gene expression, high-replicate RNA-seq in morphologically normal individuals demonstrates a stable regulatory response of epigenetic modifiers and the specific de-repression of a group of zinc finger genes residing in constitutive heterochromatin. Together our data reveal a complex role for Kdm2aa in regulating normal mRNA levels and carcinogenesis. These findings establish kdm2aa mutants as the first single gene knockout model of melanoma biology.
AU  - Scahill, C.M.*
AU  - Digby, Z.*
AU  - Sealy, I.M.*
AU  - Wojciechowska, S.*
AU  - White, R.J.*
AU  - Collins, J.E.*
AU  - Stemple, D.L.*
AU  - Bartke, T.
AU  - Mathers, M.E.*
AU  - Patton, E.E.*
AU  - Busch-Nentwich, E.M.*
C1  - 51870
C2  - 43542
CY  - San Francisco
TI  - Loss of the chromatin modifier Kdm2aa causes BrafV-600E -independent spontaneous melanoma in zebrafish.
JO  - PLoS Genet.
VL  - 13
IS  - 8
PB  - Public Library Science
PY  - 2017
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (GxE) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (P-v), GxE interaction effects (with smoking and physical activity), and marginal genetic effects (P-m). Correlations between P-v and P-m were stronger for SNPs with established marginal effects (Spearman's rho = 0.401 for triglycerides, and rho = 0.236 for BMI) compared to all SNPs. When P-v and P-m were compared for all pruned SNPs, only BMI was statistically significant (Spearman's rho = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the P-v distribution (P-binomial < 0.05). SNPs from the top 1% of the P-m distribution for BMI had more significant P-v values (Pmann-Whitney = 1.46x10(-5)), and the odds ratio of SNPs with nominally significant (< 0.05) P-m and P-v was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant GxE interaction P-values (Pint < 0.05) were enriched with nominally significant P-v values (P-binomial = 8.63x10(-9) and 8.52x10(-7) for SNP x smoking and SNP x physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for GxE, and variance-based prioritization can be used to identify them.
AU  - Shungin, D.*
AU  - Deng, W.Q.*
AU  - Varga, T.V.*
AU  - Luan, J.*
AU  - Mihailov, E.*
AU  - Metspalu, A.*
AU  - Morris, A.P.*
AU  - Forouhi, N.G.*
AU  - Lindgren, C.*
AU  - Magnusson, P.K.E.*
AU  - Pedersen, N.L.*
AU  - Hallmans, G.*
AU  - Chu, A.Y.*
AU  - Justice, A.E.*
AU  - Graff, M.*
AU  - Winkler, T.W.*
AU  - Rose, L.M.*
AU  - Langenberg, C.*
AU  - Cupples, L.A.*
AU  - Ridker, P.M.*
AU  - Wareham, N.J.*
AU  - Ong, K.K.*
AU  - Loos, R.J.F.*
AU  - Chasman, D.I.*
AU  - Ingelsson, E.*
AU  - Kilpeläinen, T.O.*
AU  - Scott, R.A.*
AU  - Mägi, R.*
AU  - Paré, G.*
AU  - Franks, P.W.*
AU  - GIANT Consortium (Gieger, C.
AU  - Grallert, H.
AU  - Holzapfel, C.
AU  - Rawal, R.
AU  - Huth, C.
AU  - Peters, A.
AU  - Thorand, B.
AU  - Müller-Nurasyid, M.
AU  - Strauch, K.)
C1  - 51555
C2  - 43216
CY  - San Francisco
TI  - Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions.
JO  - PLoS Genet.
VL  - 13
IS  - 6
PB  - Public Library Science
PY  - 2017
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Zygotic gene expression programs control cell differentiation in vertebrate development. In Xenopus, these programs are initiated by local induction of regulatory genes through maternal signaling activities in the wake of zygotic genome activation (ZGA) at the midblastula transition (MBT). These programs lay down the vertebrate body plan through gastrulation and neurulation, and are accompanied by massive changes in chromatin structure, which increasingly constrain cellular plasticity. Here we report on developmental functions for Brahma related gene 1 (Brg1), a key component of embyronic SWI/SNF chromatin remodeling complexes. Carefully controlled, global Brg1 protein depletion in X. tropicalis and X. laevis causes embryonic lethality or developmental arrest from gastrulation on. Transcriptome analysis at late blastula, before development becomes arrested, indicates predominantly a role for Brg1 in transcriptional activation of a limited set of genes involved in pattern specification processes and nervous system development. Mosaic analysis by targeted microinjection defines Brg1 as an essential amplifier of gene expression in dorsal (BCNE/Nieuwkoop Center) and ventral (BMP/Vent) signaling centers. Moreover, Brg1 is required and sufficient for initiating axial patterning in cooperation with maternal Wnt signaling. In search for a common denominator of Brg1 impact on development, we have quantitatively filtered global mRNA fluctuations at MBT. The results indicate that Brg1 is predominantly required for genes with the highest burst of transcriptional activity. Since this group contains many key developmental regulators, we propose Brg1 to be responsible for raising their expression above threshold levels in preparation for embryonic patterning.
AU  - Wagner, G.*
AU  - Singhal, N.*
AU  - Nicetto, D.*
AU  - Straub, T.*
AU  - Kremmer, E.
AU  - Rupp, R.A.W.*
C1  - 51109
C2  - 43082
CY  - San Francisco
TI  - Brg1 chromatin remodeling ATPase balances germ layer patterning by amplifying the transcriptional burst at midblastula transition.
JO  - PLoS Genet.
VL  - 13
IS  - 5
PB  - Public Library Science
PY  - 2017
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Insulin resistance (IR) and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR) analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or β-cell responsiveness (disposition index) during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613) followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330), we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining “gold standard” measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development.
AU  - Nowak, C.*
AU  - Salihovic, S.*
AU  - Ganna, A.*
AU  - Brandmaier, S.
AU  - Tukiainen, T.*
AU  - Broeckling, C.D.*
AU  - Magnusson, P.K.*
AU  - Prenni, J.E.*
AU  - Wang-Sattler, R.
AU  - Peters, A.
AU  - Strauch, K.
AU  - Meitinger, T.
AU  - Giedraitis, V.*
AU  - Ärnlöv, J.*
AU  - Berne, C.*
AU  - Gieger, C.
AU  - Ripatti, S*
AU  - Lind, L.*
AU  - Pedersen, N.L.*
AU  - Sundström, J.*
AU  - Ingelsson, E.*
AU  - Fall, T.*
C1  - 49877
C2  - 41849
CY  - San Francisco
TI  - Effect of insulin resistance on monounsaturated fatty acid levels: A multi-cohort non-targeted metabolomics and mendelian randomization study.
JO  - PLoS Genet.
VL  - 12
IS  - 10
PB  - Public Library Science
PY  - 2016
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Failure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinants of mortality in patients with new-onset heart failure, we performed a meta-analysis of genome-wide association studies and follow-up genotyping in independent populations. We identified and replicated an association for a genetic variant on chromosome 5q22 with 36% increased risk of death in subjects with heart failure (rs9885413, P = 2.7x10-9). We provide evidence from reporter gene assays, computational predictions and epigenomic marks that this polymorphism increases activity of an enhancer region active in multiple human tissues. The polymorphism was further reproducibly associated with a DNA methylation signature in whole blood (P = 4.5x10-40) that also associated with allergic sensitization and expression in blood of the cytokine TSLP (P = 1.1x10-4). Knockdown of the transcription factor predicted to bind the enhancer region (NHLH1) in a human cell line (HEK293) expressing NHLH1 resulted in lower TSLP expression. In addition, we observed evidence of recent positive selection acting on the risk allele in populations of African descent. Our findings provide novel genetic leads to factors that influence mortality in patients with heart failure.
AU  - Smith, J.G.*
AU  - Felix, J.F.*
AU  - Morrison, A.C.*
AU  - Kalogeropoulos, A.*
AU  - Trompet, S.*
AU  - Wilk, J.B.*
AU  - Gidlöf, O.*
AU  - Wang, X.*
AU  - Morley, M.*
AU  - Mendelson, M.*
AU  - Joehanes, R.*
AU  - Ligthart, S.*
AU  - Shan, X.*
AU  - Bis, J.C.*
AU  - Wang, Y.A.*
AU  - Sjögren, M.*
AU  - Ngwa, J.S.*
AU  - Brandimarto, J.*
AU  - Stott, D.J.*
AU  - Aguilar, D.*
AU  - Rice, K.M.*
AU  - Sesso, H.D.*
AU  - Demissie, S.*
AU  - Buckley, B.M.*
AU  - Taylor, K.D.*
AU  - Ford, I.*
AU  - Yao, C.*
AU  - Liu, C.*
AU  - CHARGE-SCD Consortium (Butler, J.)
AU  - EchoGen Consortium (Vasan, R.S.
AU  - Cappola, T.P.)
AU  - QT-IGC Consortium (Smith, N.L.
AU  - Gieger, C.
AU  - Perz, S.
AU  - Peters, A.
AU  - Pfeufer, A.
AU  - Waldenberger, M.
AU  - Crotti, L.)
AU  - CHARGE-QRS Consortium (Klopp, N.
AU  - Müller-Nurasyid, M.
AU  - Perz, S.
AU  - Wichmann, H.-E.
AU  - Meitinger, T.)
AU  - Sotoodehnia, N.*
AU  - van der Harst, P.*
AU  - Stricker, B.H.*
AU  - Kritchevsky, S.B.*
AU  - Liu, Y.*
AU  - Gaziano, J.M.*
AU  - Hofman, A.*
AU  - Moravec, C.S.*
AU  - Uitterlinden, A.G.*
AU  - Kellis, M.*
AU  - van Meurs, J.B.*
AU  - Margulies, K.B.*
AU  - Dehghan, A.*
AU  - Levy, D.*
AU  - Olde, B.*
AU  - Psaty, B.M.*
AU  - Cupples, L.A.*
AU  - Jukema, J.W.*
AU  - Djousse, L.*
AU  - Franco, O.H.*
AU  - Boerwinkle, E.*
AU  - Boyer, L.A.*
AU  - Newton-Cheh, C.*
C1  - 48659
C2  - 41252
TI  - Discovery of genetic variation on chromosome 5q22 associated with mortality in heart failure.
JO  - PLoS Genet.
VL  - 12
IS  - 5
PY  - 2016
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The tripeptide glutathione is the most abundant cellular antioxidant with high medical relevance, and it is also required as a co-factor for various enzymes involved in the detoxification of reactive oxygen species and toxic compounds. However, its cell-type specific functions and its interaction with other cytoprotective molecules are largely unknown. Using a combination of mouse genetics, functional cell biology and pharmacology, we unraveled the function of glutathione in keratinocytes and its cross-talk with other antioxidant defense systems. Mice with keratinocyte-specific deficiency in glutamate cysteine ligase, which catalyzes the rate-limiting step in glutathione biosynthesis, showed a strong reduction in keratinocyte viability in vitro and in the skin in vivo. The cells died predominantly by apoptosis, but also showed features of ferroptosis and necroptosis. The increased cell death was associated with increased levels of reactive oxygen and nitrogen species, which caused DNA and mitochondrial damage. However, epidermal architecture, and even healing of excisional skin wounds were only mildly affected in the mutant mice. The cytoprotective transcription factor Nrf2 was strongly activated in glutathione-deficient keratinocytes, but additional loss of Nrf2 did not aggravate the phenotype, demonstrating that the cytoprotective effect of Nrf2 is glutathione dependent. However, we show that deficiency in glutathione biosynthesis is efficiently compensated in keratinocytes by the cysteine/cystine and thioredoxin systems. Therefore, our study highlights a remarkable antioxidant capacity of the epidermis that ensures skin integrity and efficient wound healing.
AU  - Telorack, M.*
AU  - Meyer, M.*
AU  - Ingold, I.
AU  - Conrad, M.
AU  - Bloch, W.*
AU  - Werner, S.*
C1  - 47756
C2  - 39474
CY  - San Francisco
TI  - A glutathione-Nrf2-thioredoxin cross-talk ensures keratinocyte survival and efficient wound repair.
JO  - PLoS Genet.
VL  - 12
IS  - 1
PB  - Public Library Science
PY  - 2016
SN  - 1553-7390
ER  - 

TY  - JOUR
AU  - Winkler, T.W.*
AU  - Justice, A.E.*
AU  - Graff, M.*
AU  - Barata, L.*
AU  - Feitosa, M.F.*
AU  - Chu, S.*
AU  - Czajkowski, J.*
AU  - Esko, T.*
AU  - Fall, T.*
AU  - Kilpeläinen, T.O.*
AU  - Lu, Y.*
AU  - Mägi, R.*
AU  - Mihailov, E.*
AU  - Pers, T.H.*
AU  - Rüeger, S.*
AU  - Teumer, A.*
AU  - Ehret, G.B.*
AU  - Ferreira, T.*
AU  - Heard-Costa, N.L.*
AU  - Karjalainen, J.*
AU  - Lagou, V.*
AU  - Mahajan, A.*
AU  - Neinast, M.D.*
AU  - Prokopenko, I.*
AU  - Simino, J.*
AU  - Teslovich, T.M.*
AU  - Jansen, R.*
AU  - Westra, H.J.*
AU  - White, C.C.*
AU  - Absher, D.*
AU  - Ahluwalia, T.S.*
AU  - Ahmad, S.*
AU  - Albrecht, E.
AU  - Alves, A.C.*
AU  - Bragg-Gresham, J.L.*
AU  - de Craen, A.J.M.*
AU  - Bis, J.C.*
AU  - Bonnefond, A.*
AU  - Boucher, G.*
AU  - Cadby, G.*
AU  - Cheng, Y.C.*
AU  - Chiang, C.W.K.*
AU  - Delgado, G.*
AU  - Demirkan, A.*
AU  - Dueker, N.*
AU  - Eklund, N.*
AU  - Eiriksdottir, G.*
AU  - Eriksson, J.*
AU  - Feenstra, B.*
AU  - Fischer, K.*
AU  - Frau, F.*
AU  - Galesloot, T.E.*
AU  - Geller, F.*
AU  - Goel, A.*
AU  - Gorski, M.*
AU  - Grammer, T.B.*
AU  - Gustafsson, S.*
AU  - Haitjema, S.*
AU  - Hottenga, J.J.*
AU  - Huffman, J.E.*
AU  - Jackson, A.U.*
AU  - Jacobs, K.B.*
AU  - Johansson, A.*
AU  - Kaakinen, M.*
AU  - Kleber, M.E.*
AU  - Lahti, J.*
AU  - Leach, I.M.*
AU  - Lehne, B.*
AU  - Liu, Y.*
AU  - Lo, K.S.*
AU  - Lorentzon, M.*
AU  - Luan, J.*
AU  - Madden, P.A.F.*
AU  - Mangino, M.*
AU  - McKnight, B.*
AU  - Medina-Gomez, C.*
AU  - Monda, K.L.*
AU  - Montasser, M.E.*
AU  - Müller, G.*
AU  - Müller-Nurasyid, M.
AU  - Nolte, I.M.*
AU  - Panoutsopoulou, K.*
AU  - Pascoe, L.*
AU  - Paternoster, L.*
AU  - Rayner, N.W.*
AU  - Renström, F.*
AU  - Rizzi, F.*
AU  - Rose, L.M.*
AU  - Ryan, K.A.*
AU  - Salo, P.*
AU  - Sanna, S.*
AU  - Scharnagl, H.*
AU  - Shi, J.*
AU  - Smith, A.V.*
AU  - Southam, L.*
AU  - Stancáková, A.*
AU  - Steinthorsdottir, V.*
AU  - Strawbridge, R.J.*
AU  - Sung, Y.J.*
AU  - Tachmazidou, I.*
AU  - Tanaka, T.*
AU  - Thorleifsson, G.*
AU  - Trompet, S.*
AU  - Pervjakova, N.*
AU  - Tyrer, J.P.*
AU  - Vandenput, L.*
AU  - van der Laan, S.W.*
AU  - van der Velde, N.*
AU  - van Setten, J.*
AU  - van Vliet-Ostaptchouk, J.V.*
AU  - Verweij, N.*
AU  - Vlachopoulou, E.*
AU  - Waite, L.L.*
AU  - Wang, S.R.*
AU  - Wang, Z.*
AU  - Wild, S.H.*
AU  - Willenborg, C.*
AU  - Wilson, J.F.*
AU  - Wong, A.*
AU  - Yang, J.*
AU  - Yengo, L.*
AU  - Yerges-Armstrong, L.M.*
AU  - Yu, L.*
AU  - Zhang, W.*
AU  - Zhao, J.H.*
AU  - Andersson, E.A.*
AU  - Bakker, S.J.L.*
AU  - Baldassarre, D.*
AU  - Banasik, K.*
AU  - Barcella, M.*
AU  - Barlassina, C.*
AU  - Bellis, C.*
AU  - Benaglio, P.*
AU  - Blangero, J.*
AU  - Blüher, M.*
AU  - Bonnet, F.*
AU  - Bonnycastle, L.L.*
AU  - Boyd, H.A.*
AU  - Bruinenberg, M.*
AU  - Buchman, A.S.*
AU  - Campbell, H.*
AU  - Chen, Y.I.*
AU  - Chines, P.S.*
AU  - Claudi-Boehm, S.*
AU  - Cole, J.*
AU  - Collins, F.S.*
AU  - de Geus, E.J.C.*
AU  - de Groot, L.C.P.G.M.*
AU  - Dimitriou, M.*
AU  - Duan, J.*
AU  - Enroth, S.*
AU  - Eury, E.*
AU  - Farmaki, A.-E.*
AU  - Forouhi, N.G.*
AU  - Friedrich, N.*
AU  - Gejman, P.V.*
AU  - Gigante, B.*
AU  - Glorioso, N.*
AU  - Go, A.S.*
AU  - Gottesman, O.*
AU  - Grässler, J.*
AU  - Grallert, H.
AU  - Grarup, N.*
AU  - Gu, Y.*
AU  - Broer, L.*
AU  - Ham, A.C.*
AU  - Hansen, T.*
AU  - Harris, T.B.*
AU  - Hartman, C.A.*
AU  - Hassinen, M.*
AU  - Hastie, N.*
AU  - Hattersley, A.T.*
AU  - Heath, A.C.*
AU  - Henders, A.K.*
AU  - Hernandez, D.*
AU  - Hillege, H.*
AU  - Holmen, O.L.*
AU  - Hovingh, K.G.*
AU  - Hui, J.*
AU  - Husemoen, L.L.*
AU  - Hutri-Kähönen, N.*
AU  - Hysi, P.G.*
AU  - Illig, T.
AU  - de Jager, P.L.*
AU  - Jalilzadeh, S.*
AU  - Jorgensen, T.*
AU  - Jukema, J.W.*
AU  - Juonala, M.*
AU  - Kanoni, S.*
AU  - Karaleftheri, M.*
AU  - Khaw, K.T.*
AU  - Kinnunen, L.*
AU  - Kittner, S.J.*
AU  - Koenig, W.*
AU  - Kolcic, I.*
AU  - Kovacs, P.*
AU  - Krarup, N.T.*
AU  - Kratzer, W.*
AU  - Krüger, J.*
AU  - Kuh, D.*
AU  - Kumari, M.*
AU  - Kyriakou, T.*
AU  - Langenberg, C.*
AU  - Lannfelt, L.*
AU  - Lanzani, C.*
AU  - Lotay, V.*
AU  - Launer, L.J.*
AU  - Leander, K.*
AU  - Lindstrom, J.*
AU  - Linneberg, A.*
AU  - Lobbens, S.*
AU  - Luben, R.*
AU  - Lyssenko, V.*
AU  - Männistö, S.*
AU  - Magnusson, P.K.*
AU  - McArdle, W.L.*
AU  - Menni, C.*
AU  - Merger, S.*
AU  - Milani, L.*
AU  - Montgomery, G.W.*
AU  - Morris, A.P.*
AU  - Narisu, N.*
AU  - Nelis, M.*
AU  - Ong, K.K.*
AU  - Palotie, A.*
AU  - Perusse, L.*
AU  - Pichler, I.*
AU  - Pilia, M.G.*
AU  - Pouta, A.*
AU  - Rheinberger, M.*
AU  - Ribel-Madsen, R.*
AU  - Richards, M.*
AU  - Rice, K.M.*
AU  - Rice, T.K.*
AU  - Rivolta, C.*
AU  - Salomaa, V.*
AU  - Sanders, A.R.*
AU  - Sarzynski, M.A.*
AU  - Scholtens, S.*
AU  - Scott, R.A.*
AU  - Scott, W.R.*
AU  - Sebert, S.*
AU  - Sengupta, S.*
AU  - Sennblad, B.*
AU  - Seufferlein, T.*
AU  - Silveira, A.*
AU  - Slagboom, P.E.*
AU  - Smit, J.H.*
AU  - Sparso, T.H.*
AU  - Stirrups, K.*
AU  - Stolk, R.P.*
AU  - Stringham, H.M.*
AU  - Swertz, M.A.*
AU  - Swift, A.J.*
AU  - Syvanen, A.C.*
AU  - Tan, S.*
AU  - Thorand, B.
AU  - Tönjes, A.*
AU  - Tremblay, A.*
AU  - Tsafantakis, E.*
AU  - van der Most, P.J.*
AU  - Völker, U.*
AU  - Vohl, M.C.*
AU  - Vonk, J.M.*
AU  - Waldenberger, M.
AU  - Walker, R.W.*
AU  - Wennauer, R.*
AU  - Widen, E.*
AU  - Willemsen, G.*
AU  - Wilsgaard, T.*
AU  - Wright, A.F.*
AU  - Zillikens, M.C.*
AU  - van Dijk, S.C.*
AU  - van Schoor, N.M.*
AU  - Asselbergs, F.W.*
AU  - de Bakker, P.I.W.*
AU  - Beckmann, J.S.*
AU  - Beilby, J.*
AU  - Bennett, D.A.*
AU  - Bergman, R.N.*
AU  - Bergmann, S.*
AU  - Böger, C.A.*
AU  - Boehm, B.O.*
AU  - Boerwinkle, E.*
AU  - Boomsma, D.I.*
AU  - Bornstein, S.R.*
AU  - Bottinger, E.P.*
AU  - Bouchard, C.*
AU  - Chambers, J.C.*
AU  - Chanock, S.J.*
AU  - Chasman, D.I.*
AU  - Cucca, F.*
AU  - Cusi, D.*
AU  - Dedoussis, G.*
AU  - Erdmann, J.*
AU  - Eriksson, J.G.*
AU  - Evans, D.A.*
AU  - de Faire, U.*
AU  - Farrall, M.*
AU  - Ferrucci, L.*
AU  - Ford, I.*
AU  - Franke, L.*
AU  - Franks, P.W.*
AU  - Froguel, P.*
AU  - Gansevoort, R.T.*
AU  - CHARGE Consortium (Gieger, C.
AU  - Meisinger, C.
AU  - Prokisch, H.
AU  - Wichmann, H.-E.)
AU  - Grönberg, H.*
AU  - Gudnason, V.*
AU  - Gyllensten, U.*
AU  - Hall, P.*
AU  - Hamsten, A.*
AU  - van der Harst, P.*
AU  - Hayward, C.*
AU  - Heliövaara, M.*
AU  - Hengstenberg, C.*
AU  - Hicks, A.A.*
AU  - Hingorani, A.*
AU  - Hofman, A.*
AU  - Hu, F.*
AU  - Huikuri, H.V.*
AU  - Hveem, K.*
AU  - James, A.L.*
AU  - Jordan, J.M.*
AU  - Jula, A.*
AU  - Kähönen, M.*
AU  - Kajantie, E.*
AU  - Kathiresan, S.*
AU  - Kiemeney, L.A.L.M.*
AU  - Kivimaki, M.*
AU  - Knekt, P.B.*
AU  - Koistinen, H.A.*
AU  - Kooner, J.S.*
AU  - Koskinen, S.*
AU  - Kuusisto, J.*
AU  - Maerz, W.*
AU  - Martin, N.G.*
AU  - Laakso, M.*
AU  - Lakka, T.A.*
AU  - Lehtimäki, T.*
AU  - Lettre, G.*
AU  - Levinson, D.F.*
AU  - Lind, L.*
AU  - Lokki, M.L.*
AU  - Mäntyselkä, P.*
AU  - Melbye, M.*
AU  - Metspalu, A.*
AU  - Mitchell, B.D.*
AU  - Moll, F.L.*
AU  - Murray, J.C.*
AU  - Musk, A.W.*
AU  - Nieminen, M.S.*
AU  - Njolstad, I.*
AU  - Ohlsson, C.*
AU  - Oldehinkel, A.J.*
AU  - Oostra, B.A.*
AU  - Palmer, L.J.*
AU  - Pankow, J.S.*
AU  - Pasterkamp, G.*
AU  - Pedersen, N.L.*
AU  - Pedersen, O.*
AU  - Penninx, B.W.*
AU  - Perola, M.*
AU  - Peters, A.
AU  - Polasek, O.*
AU  - Pramstaller, P.P.*
AU  - Psaty, B.M.*
AU  - Qi, L.*
AU  - Quertermous, T.*
AU  - Raitakari, O.T.*
AU  - Rankinen, T.*
AU  - Rauramaa, R.*
AU  - Ridker, P.M.*
AU  - Rioux, J.D.*
AU  - Rivadeneira, F.*
AU  - Rotter, J.I.*
AU  - Rudan, I.*
AU  - den Ruijter, H.M.*
AU  - Saltevo, J.*
AU  - Sattar, N.*
AU  - Schunkert, H.*
AU  - Schwarz, P.E.H.*
AU  - Shuldiner, A.R.*
AU  - Sinisalo, J.*
AU  - Snieder, H.*
AU  - Sörensen, T.I.A.*
AU  - Spector, T.D.*
AU  - Staessen, J.A.*
AU  - Stefania, B.*
AU  - Thorsteinsdottir, U.*
AU  - Stumvoll, M.*
AU  - Tardif, J.-C.*
AU  - Tremoli, E.*
AU  - Tuomilehto, J.*
AU  - Uitterlinden, A.G.*
AU  - Uusitupa, M.*
AU  - Verbeek, A.L.M.*
AU  - Vermeulen, S.H.*
AU  - Viikari, J.S.*
AU  - Vitart, V.*
AU  - Völzke, H.*
AU  - Vollenweider, P.*
AU  - Waeber, G.*
AU  - Walker, M.*
AU  - Wallaschofski, H.*
AU  - Wareham, N.J.*
AU  - Watkins, H.*
AU  - Zeggini, E.*
AU  - Chakravarti, A.*
AU  - Clegg, D.J.*
AU  - Cupples, L.A.*
AU  - Gordon-Larsen, P.*
AU  - Jaquish, C.E.*
AU  - Rao, D.C.*
AU  - Abecasis, G.R.*
AU  - Assimes, T.L.*
AU  - Barroso, I.*
AU  - Berndt, S.I.*
AU  - Boehnke, M.*
AU  - Deloukas, P.*
AU  - Fox, C.S.*
AU  - Groop, L.C.*
AU  - Hunter, D.J.*
AU  - Ingelsson, E.*
AU  - Kaplan, R.C.*
AU  - McCarthy, M.I.*
AU  - Mohlke, K.L.*
AU  - O'Connell, J.R.*
AU  - Schlessinger, D.*
AU  - Strachan, D.P.*
AU  - Stefansson, K.*
AU  - van Duijn, C.M.*
AU  - Hirschhorn, J.N.*
AU  - Lindgren, C.M.*
AU  - Heid, I.M.
AU  - North, K.E.*
AU  - Borecki, I.B.*
AU  - Kutalik, Z.*
AU  - Loos, R.J.F.*
AU  - DIAGRAM Consortium (Klopp, N.
AU  - Meyer, J.)
AU  - Global BPgen Consortium (Döring, A.)
AU  - ICBP Consortium (Meitinger, T.)
C1  - 50586
C2  - 42432
CY  - San Francisco
TI  - Correction: The influence of age and sex on genetic associations with adult body size and shape: A large-scale genome-wide interaction study.
JO  - PLoS Genet.
VL  - 12
IS  - 6
PB  - Public Library Science
PY  - 2016
SN  - 1553-7390
ER  - 

TY  - JOUR
AU  - Wurst, W.
C1  - 48755
C2  - 41330
CY  - San Francisco
TI  - Animal models are valid to uncover disease mechanisms.
JO  - PLoS Genet.
VL  - 12
IS  - 5
PB  - Public Library Science
PY  - 2016
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the 'human blood metabolome-transcriptome interface' (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease.
AU  - Bartel, J.
AU  - Krumsiek, J.
AU  - Schramm, K.
AU  - Adamski, J.
AU  - Gieger, C.
AU  - Herder, C.*
AU  - Carstensen, M.*
AU  - Peters, A.
AU  - Rathmann, W.*
AU  - Roden, M.*
AU  - Strauch, K.
AU  - Suhre, K.
AU  - Kastenmüller, G.
AU  - Prokisch, H.
AU  - Theis, F.J.
C1  - 45348
C2  - 37306
CY  - San Francisco
TI  - The human blood metabolome-transcriptome interface.
JO  - PLoS Genet.
VL  - 11
IS  - 6
PB  - Public Library Science
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Cysteine-rich receptor-like kinases (CRKs) are transmembrane proteins characterized by the presence of two domains of unknown function 26 (DUF26) in their ectodomain. The CRKs form one of the largest groups of receptor-like protein kinases in plants, but their biological functions have so far remained largely uncharacterized. We conducted a large-scale phenotyping approach of a nearly complete crk T-DNA insertion line collection showing that CRKs control important aspects of plant development and stress adaptation in response to biotic and abiotic stimuli in a non-redundant fashion. In particular, the analysis of reactive oxygen species (ROS)-related stress responses, such as regulation of the stomatal aperture, suggests that CRKs participate in ROS/redox signalling and sensing. CRKs play general and fine-tuning roles in the regulation of stomatal closure induced by microbial and abiotic cues. Despite their great number and high similarity, large-scale phenotyping identified specific functions in diverse processes for many CRKs and indicated that CRK2 and CRK5 play predominant roles in growth regulation and stress adaptation, respectively. As a whole, the CRKs contribute to specificity in ROS signalling. Individual CRKs control distinct responses in an antagonistic fashion suggesting future potential for using CRKs in genetic approaches to improve plant performance and stress tolerance.
AU  - Bourdais, G.*
AU  - Burdiak, P.*
AU  - Gauthier, A.*
AU  - Nitsch, L.*
AU  - Salojärvi, J.*
AU  - Rayapuram, C.*
AU  - Idänheimo, N.*
AU  - Hunter, K.*
AU  - Kimura, S.*
AU  - Merilo, E.*
AU  - Vaattovaara, A.*
AU  - Oracz, K.*
AU  - Kaufholdt, D.*
AU  - Pallon, A.*
AU  - Anggoro, D.T.*
AU  - Glow, D.*
AU  - Lowe, J.*
AU  - Zhou, J.*
AU  - Mohammadi, O.*
AU  - Puukko, T.*
AU  - Albert, A.
AU  - Lang, H.
AU  - Ernst, D.
AU  - Kollist, H.*
AU  - Brosché, M.*
AU  - Durner, J.
AU  - Borst, J.W.*
AU  - Collinge, D.B.*
AU  - Karpiński, S.*
AU  - Lyngkjær, M.F.*
AU  - Robatzek, S.*
AU  - Wrzaczek, M.*
AU  - Kangasjärvi, J.*
C1  - 46398
C2  - 37533
CY  - San Francisco
TI  - Large-scale phenomics identifies primary and fine-tuning roles for CRKs in responses related to oxidative stress.
JO  - PLoS Genet.
VL  - 11
IS  - 7
PB  - Public Library Science
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - In mammals, the liver plays a central role in maintaining carbohydrate and lipid homeostasis by acting both as a major source and a major sink of glucose and lipids. In particular, when dietary carbohydrates are in excess, the liver converts them to lipids via de novo lipogenesis. The molecular checkpoints regulating the balance between carbohydrate and lipid homeostasis, however, are not fully understood. Here we identify PPP2R5C, a regulatory subunit of PP2A, as a novel modulator of liver metabolism in postprandial physiology. Inactivation of PPP2R5C in isolated hepatocytes leads to increased glucose uptake and increased de novo lipogenesis. These phenotypes are reiterated in vivo, where hepatocyte specific PPP2R5C knockdown yields mice with improved systemic glucose tolerance and insulin sensitivity, but elevated circulating triglyceride levels. We show that modulation of PPP2R5C levels leads to alterations in AMPK and SREBP-1 activity. We find that hepatic levels of PPP2R5C are elevated in human diabetic patients, and correlate with obesity and insulin resistance in these subjects. In sum, our data suggest that hepatic PPP2R5C represents an important factor in the functional wiring of energy metabolism and the maintenance of a metabolically healthy state.
AU  - Cheng, Y.S.*
AU  - Seibert, O.*
AU  - Klöting, N.*
AU  - Dietrich, A.*
AU  - Straßburger, K.*
AU  - Fernández-Veledo, S.*
AU  - Vendrell, J.J.*
AU  - Zorzano, A.*
AU  - Blüher, M.*
AU  - Herzig, S.
AU  - Berriel Diaz, M.
AU  - Teleman, A.A.*
C1  - 47255
C2  - 39245
TI  - PPP2R5C couples hepatic glucose and lipid homeostasis.
JO  - PLoS Genet.
VL  - 11
IS  - 10
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.
AU  - Horikoshi, M.*
AU  - Mägi, R.*
AU  - van de Bunt, M.*
AU  - Surakka, I.*
AU  - Sarin, A.P.*
AU  - Mahajan, A.*
AU  - Marullo, L.*
AU  - Thorleifsson, G.*
AU  - Hägg, S.*
AU  - Hottenga, J.J.*
AU  - Ladenvall, C.*
AU  - Ried, J.S.
AU  - Winkler, T.W.*
AU  - Willems, S.M.*
AU  - Pervjakova, N.*
AU  - Esko, T.*
AU  - Beekman, M.*
AU  - Nelson, C.P.*
AU  - Willenborg, C.*
AU  - Wiltshire, S.*
AU  - Ferreira, T.*
AU  - Fernández, J.*
AU  - Gaulton, K.J.*
AU  - Steinthorsdottir, V.*
AU  - Hamsten, A.*
AU  - Magnusson, P.K.*
AU  - Willemsen, G.*
AU  - Milaneschi, Y.*
AU  - Robertson, N.R.*
AU  - Groves, C.J.*
AU  - Bennett, A.J.*
AU  - Lehtimäki, T.*
AU  - Viikari, J.S.*
AU  - Rung, J.*
AU  - Lyssenko, V.*
AU  - Perola, M.*
AU  - Heid, I.M.*
AU  - Herder, C.*
AU  - Grallert, H.
AU  - Müller-Nurasyid, M.
AU  - Roden, M.*
AU  - Hyppönen, E.*
AU  - Isaacs, A.*
AU  - van Leeuwen, E.M.*
AU  - Karssen, L.C.*
AU  - Mihailov, E.*
AU  - Houwing-Duistermaat, J.J.*
AU  - de Craen, A.J.*
AU  - Deelen, J.*
AU  - Havulinna, A.S.*
AU  - Blades, M.*
AU  - Hengstenberg, C.*
AU  - Erdmann, J.*
AU  - Schunkert, H.*
AU  - Kaprio, J.*
AU  - Tobin, M.D.*
AU  - Samani, N.J.*
AU  - Lind, L.*
AU  - Salomaa, V.*
AU  - Lindgren, C.M.*
AU  - Slagboom, P.E.*
AU  - Metspalu, A.*
AU  - van Duijn, C.M.*
AU  - Eriksson, J.G.*
AU  - Peters, A.
AU  - Gieger, C.
AU  - Jula, A.*
AU  - Groop, L.*
AU  - Raitakari, O.T.*
AU  - Power, C.*
AU  - Penninx, B.W.*
AU  - de Geus, E.*
AU  - Smit, J.H.*
AU  - Boomsma, D.I.*
AU  - Pedersen, N.L.*
AU  - Ingelsson, E.*
AU  - Thorsteinsdottir, U.*
AU  - Stefansson, K.*
AU  - Ripatti, S.*
AU  - Prokopenko, I.*
AU  - McCarthy, M.I.*
AU  - Morris, A.P.*
AU  - ENGAGE Consortium (Döring, A.
AU  - Nitz, B.
AU  - Rawal, R.
AU  - Wichmann, H.-E.)
C1  - 45670
C2  - 37416
CY  - San Francisco
TI  - Discovery and fine-mapping of glycaemic and obesity-related trait loci using high-density imputation.
JO  - PLoS Genet.
VL  - 11
IS  - 7
PB  - Public Library Science
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.
AU  - Huan, T.*
AU  - Esko, T.*
AU  - Peters, M.J.*
AU  - Pilling, L.C.*
AU  - Schramm, K.
AU  - Schurmann, C.*
AU  - Chen, B.H.*
AU  - Liu, C.*
AU  - Joehanes, R.*
AU  - Johnson, A.D.*
AU  - Yao, C.*
AU  - Ying, S.X.*
AU  - Courchesne, P.*
AU  - Milani, L.*
AU  - Raghavachari, N.*
AU  - Wang, R.*
AU  - Liu, P.*
AU  - Reinmaa, E.*
AU  - Dehghan, A.*
AU  - Hofman, A.*
AU  - Uitterlinden, A.G.*
AU  - Hernandez, D.G.*
AU  - Bandinelli, S.*
AU  - Singleton, A.*
AU  - Melzer, D.*
AU  - Metspalu, A.*
AU  - Carstensen, M.*
AU  - Grallert, H.
AU  - Herder, C.*
AU  - Meitinger, T.
AU  - Peters, A.
AU  - Roden, M.*
AU  - Waldenberger, M.
AU  - Dörr, M.*
AU  - Felix, S.B.*
AU  - Zeller, T.*
AU  - ICBP Consortium (Levy, D.*)
AU  - Vasan, R.S.*
AU  - O'Donnell, C.J.*
AU  - Munson, P.J.*
AU  - Yang, X.*
AU  - Prokisch, H.
AU  - Völker, U.*
AU  - van Meurs, J.B.*
AU  - Ferrucci, L.*
C1  - 43872
C2  - 36617
CY  - San Francisco
TI  - A meta-analysis of gene expression signatures of blood pressure and hypertension.
JO  - PLoS Genet.
VL  - 11
IS  - 3
PB  - Public Library Science
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Beta-cell apoptosis and failure to induce beta-cell regeneration are hallmarks of type 2-like diabetes in mouse models. Here we show that islets from obese, diabetes-susceptible New Zealand Obese (NZO) mice, in contrast to diabetes-resistant C57BL/6J (B6)-ob/ob mice, do not proliferate in response to an in-vivo glucose challenge but lose their beta-cells. Genome-wide RNAseq based transcriptomics indicated an induction of 22 cell cycle-associated genes in B6-ob/ob islets that did not respond in NZO islets. Of all genes differentially expressed in islets of the two strains, seven mapped to the diabesity QTL Nob3, and were hypomorphic in either NZO (Lefty1, Apoa2, Pcp4l1, Mndal, Slamf7, Pydc3) or B6 (Ifi202b). Adenoviral overexpression of Lefty1, Apoa2, and Pcp4l1 in primary islet cells increased proliferation, whereas overexpression of Ifi202b suppressed it. We conclude that the identified genes in synergy with obesity and insulin resistance participate in adaptive islet hyperplasia and prevention from severe diabetes in B6-ob/ob mice.
AU  - Kluth, O.*
AU  - Matzke, D.*
AU  - Kamitz, A.*
AU  - Jähnert, M.*
AU  - Vogel, H.*
AU  - Scherneck, S.*
AU  - Schulze, M.*
AU  - Staiger, H.
AU  - Machicao, F.
AU  - Häring, H.-U.
AU  - Joost, H.G.*
AU  - Schürmann, A.*
C1  - 46760
C2  - 37793
TI  - Identification of four mouse diabetes candidate genes altering β-cell proliferation.
JO  - PLoS Genet.
VL  - 11
IS  - 9
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - We have studied the in vivo role of SLIRP in regulation of mitochondrial DNA (mtDNA) gene expression and show here that it stabilizes its interacting partner protein LRPPRC by protecting it from degradation. Although SLIRP is completely dependent on LRPPRC for its stability, reduced levels of LRPPRC persist in the absence of SLIRP in vivo. Surprisingly, Slirp knockout mice are apparently healthy and only display a minor weight loss, despite a 50-70% reduction in the steady-state levels of mtDNA-encoded mRNAs. In contrast to LRPPRC, SLIRP is dispensable for polyadenylation of mtDNA-encoded mRNAs. Instead, deep RNA sequencing (RNAseq) of mitochondrial ribosomal fractions and additional molecular analyses show that SLIRP is required for proper association of mRNAs to the mitochondrial ribosome and efficient translation. Our findings thus establish distinct functions for SLIRP and LRPPRC within the LRPPRC-SLIRP complex, with a novel role for SLIRP in mitochondrial translation. Very surprisingly, our results also demonstrate that mammalian mitochondria have a great excess of transcripts under basal physiological conditions in vivo.
AU  - Lagouge, M.*
AU  - Mourier, A.*
AU  - Lee, H.J.*
AU  - Spåhr, H.*
AU  - Wai, T.*
AU  - Kukat, C.*
AU  - Silva Ramos, E.*
AU  - Motori, E.*
AU  - Busch, J.D.*
AU  - Siira, S.*
AU  - German Mouse Clinic Consortium (Larsson, N.G.*
AU  - Aguilar-Pimentel, J.A.
AU  - Amarie, O.V.
AU  - Becker, L.
AU  - Beckers, J.
AU  - Brachthäuser, L.
AU  - Calzada-Wack, J.
AU  - Eickelberg, O.
AU  - Gailus-Durner, V.
AU  - Garrett, L.
AU  - Graw, J.
AU  - Hans, W.
AU  - Hölter, S.M.
AU  - Horsch, M.
AU  - Hrabě de Angelis, M.
AU  - Janik, D.
AU  - Klein-Rodewald, T.
AU  - Lengger, C.
AU  - Leuchtenberger, S.
AU  - Maier, H.
AU  - Moreth, K.
AU  - Neff, F.
AU  - Östereicher, M.A.
AU  - Puk, O.
AU  - Rácz, I.
AU  - Rathkolb, B.
AU  - Rozman, J.
AU  - Steinkamp, R.
AU  - Stoeger, C.
AU  - Stöger, T.
AU  - Vernaleken, A.
AU  - Wurst, W.
AU  - Yildirim, A.Ö.
AU  - Zimprich, A.)
AU  - Kremmer, E.
AU  - Filipovska, A.*
C1  - 46547
C2  - 37638
TI  - SLIRP regulates the rate of mitochondrial protein synthesis and protects LRPPRC from degradation.
JO  - PLoS Genet.
VL  - 11
IS  - 8
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genetic generalised epilepsy (GGE) is the most common form of genetic epilepsy, accounting for 20% of all epilepsies. Genomic copy number variations (CNVs) constitute important genetic risk factors of common GGE syndromes. In our present genome-wide burden analysis, large (≥ 400 kb) and rare (< 1%) autosomal microdeletions with high calling confidence (≥ 200 markers) were assessed by the Affymetrix SNP 6.0 array in European case-control cohorts of 1,366 GGE patients and 5,234 ancestry-matched controls. We aimed to: 1) assess the microdeletion burden in common GGE syndromes, 2) estimate the relative contribution of recurrent microdeletions at genomic rearrangement hotspots and non-recurrent microdeletions, and 3) identify potential candidate genes for GGE. We found a significant excess of microdeletions in 7.3% of GGE patients compared to 4.0% in controls (P = 1.8 x 10-7; OR = 1.9). Recurrent microdeletions at seven known genomic hotspots accounted for 36.9% of all microdeletions identified in the GGE cohort and showed a 7.5-fold increased burden (P = 2.6 x 10-17) relative to controls. Microdeletions affecting either a gene previously implicated in neurodevelopmental disorders (P = 8.0 x 10-18, OR = 4.6) or an evolutionarily conserved brain-expressed gene related to autism spectrum disorder (P = 1.3 x 10-12, OR = 4.1) were significantly enriched in the GGE patients. Microdeletions found only in GGE patients harboured a high proportion of genes previously associated with epilepsy and neuropsychiatric disorders (NRXN1, RBFOX1, PCDH7, KCNA2, EPM2A, RORB, PLCB1). Our results demonstrate that the significantly increased burden of large and rare microdeletions in GGE patients is largely confined to recurrent hotspot microdeletions and microdeletions affecting neurodevelopmental genes, suggesting a strong impact of fundamental neurodevelopmental processes in the pathogenesis of common GGE syndromes.
AU  - Lal, D.*
AU  - Ruppert, A.K.*
AU  - Trucks, H.*
AU  - Schulz, H.*
AU  - de Kovel, C.G.F.*
AU  - Kasteleijn-Nolst Trenité, D.*
AU  - Sonsma, A.C.*
AU  - Koeleman, B.P.*
AU  - Lindhout, D.*
AU  - Weber, Y.G.*
AU  - Lerche, H.*
AU  - Kapser, C.*
AU  - Schankin, C.J.*
AU  - Kunz, W.S.*
AU  - Surges, R.*
AU  - Elger, C.E.*
AU  - Gaus, V.*
AU  - Schmitz, B.*
AU  - Helbig, I.*
AU  - Muhle, H.*
AU  - Stephani, U.*
AU  - Klein, K.M.*
AU  - Rosenow, F.*
AU  - Neubauer, B.A.*
AU  - Reinthaler, E.M.*
AU  - Zimprich, F.*
AU  - Feucht, M.*
AU  - Møller, R.S.*
AU  - Hjalgrim, H.*
AU  - de Jonghe, P.*
AU  - Suls, A.*
AU  - Lieb, W.*
AU  - Franke, A.*
AU  - Strauch, K.
AU  - Gieger, C.
AU  - Schurmann, C.*
AU  - Schminke, U.*
AU  - Nürnberg, P.*
AU  - Sander, T.*
C1  - 44797
C2  - 37027
CY  - San Francisco
TI  - Burden analysis of rare microdeletions suggests a strong impact of neurodevelopmental genes in genetic generalised epilepsies.
JO  - PLoS Genet.
VL  - 11
IS  - 5
PB  - Public Library Science
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Plants integrate seasonal cues such as temperature and day length to optimally adjust their flowering time to the environment. Compared to the control of flowering before and after winter by the vernalization and day length pathways, mechanisms that delay or promote flowering during a transient cool or warm period, especially during spring, are less well understood. Due to global warming, understanding this ambient temperature pathway has gained increasing importance. In Arabidopsis thaliana, FLOWERING LOCUS M (FLM) is a critical flowering regulator of the ambient temperature pathway. FLM is alternatively spliced in a temperature-dependent manner and the two predominant splice variants, FLM-ß and FLM-δ, can repress and activate flowering in the genetic background of the A. thaliana reference accession Columbia-0. The relevance of this regulatory mechanism for the environmental adaptation across the entire range of the species is, however, unknown. Here, we identify insertion polymorphisms in the first intron of FLM as causative for accelerated flowering in many natural A. thaliana accessions, especially in cool (15°C) temperatures. We present evidence for a potential adaptive role of this structural variation and link it specifically to changes in the abundance of FLM-ß. Our results may allow predicting flowering in response to ambient temperatures in the Brassicaceae.
AU  - Lutz, U.*
AU  - Posé, D.*
AU  - Pfeifer, M.
AU  - Gundlach, H.
AU  - Hagmann, J.*
AU  - Wang, C.*
AU  - Weigel, D.*
AU  - Mayer, K.F.X.
AU  - Schmid, M.*
AU  - Schwechheimer, C.*
C1  - 47240
C2  - 39301
TI  - Modulation of ambient temperature-dependent flowering in Arabidopsis thaliana by natural variation of FLOWERING LOCUS M.
JO  - PLoS Genet.
VL  - 11
IS  - 10
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.
AU  - Mahajan, A.*
AU  - Sim, X.*
AU  - Ng, H.J.*
AU  - Manning, A.*
AU  - Rivas, M.A.*
AU  - Highland, H.M.*
AU  - Locke, A.E.*
AU  - Grarup, N.*
AU  - Im, H.K.*
AU  - Cingolani, P.*
AU  - Flannick, J.*
AU  - Fontanillas, P.*
AU  - Fuchsberger, C.*
AU  - Gaulton, K.J.*
AU  - Teslovich, T.M.*
AU  - Rayner, N.W.*
AU  - Robertson, N.R.*
AU  - Beer, N.L.*
AU  - Rundle, J.K.*
AU  - Bork-Jensen, J.*
AU  - Ladenvall, C.*
AU  - Blancher, C.*
AU  - Buck, D.*
AU  - Buck, G.*
AU  - Burtt, N.P.*
AU  - Gabriel, S.*
AU  - Gjesing, A.P.*
AU  - Groves, C.J.*
AU  - Hollensted, M.*
AU  - Huyghe, J.R.*
AU  - Jackson, A.U.*
AU  - Jun, G.*
AU  - Justesen, J.M.*
AU  - Mangino, M.*
AU  - Murphy, J.*
AU  - Neville, M.*
AU  - Onofrio, R.*
AU  - Small, K.S.*
AU  - Stringham, H.M.*
AU  - Syvanen, A.C.*
AU  - Trakalo, J.*
AU  - Abecasis, G.*
AU  - Bell, G.I.*
AU  - Blangero, J.*
AU  - Cox, N.J.*
AU  - Duggirala, R.*
AU  - Hanis, C.L.*
AU  - Seielstad, M.*
AU  - Wilson, J.G.*
AU  - Christensen, C.*
AU  - Brandslund, I.*
AU  - Rauramaa, R.*
AU  - Surdulescu, G.L.*
AU  - Doney, A.S.*
AU  - Lannfelt, L.*
AU  - Linneberg, A.*
AU  - Isomaa, B.*
AU  - Tuomi, T.*
AU  - Jørgensen, M.E.*
AU  - Jørgensen, T.*
AU  - Kuusisto, J.*
AU  - Uusitupa, M.*
AU  - Salomaa, V.*
AU  - Spector, T.D.*
AU  - Morris, A.D.*
AU  - Palmer, C.N.*
AU  - Collins, F.S.*
AU  - Mohlke, K.L.*
AU  - Bergman, R.N.*
AU  - Ingelsson, E.*
AU  - Lind, L.*
AU  - Tuomilehto, J.*
AU  - Hansen, T.*
AU  - Watanabe, R.M.*
AU  - Prokopenko, I.*
AU  - Dupuis, J.*
AU  - Karpe, F.*
AU  - Groop, L.*
AU  - Laakso, M.*
AU  - Pedersen, O.*
AU  - Florez, J.C*
AU  - Morris, A.P.*
AU  - Altshuler, D.*
AU  - Meigs, J.B.*
AU  - Boehnke, M.*
AU  - McCarthy, M.I.*
AU  - Lindgren, C.M.*
AU  - Gloyn, A.L.*
AU  - T2D-GENES Consortium (*)
AU  - GoT2D Consortium (Hrabě de Angelis, M.
AU  - Gieger, C.
AU  - Grallert, H.
AU  - Huth, C.
AU  - Kriebel, J.
AU  - Meisinger, C.
AU  - Meitinger, T.
AU  - Müller-Nurasyid, M.
AU  - Peters, A.
AU  - Ried, J.S.
AU  - Strauch, K.
AU  - Strom, T.M.)
C1  - 43424
C2  - 36365
TI  - Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.
JO  - PLoS Genet.
VL  - 11
IS  - 1
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome and exome sequencing in large cohorts enables characterization of the role of rare variation in complex diseases. Success in this endeavor, however, requires investigators to test a diverse array of genetic hypotheses which differ in the number, frequency and effect sizes of underlying causal variants. In this study, we evaluated the power of gene-based association methods to interrogate such hypotheses, and examined the implications for study design. We developed a flexible simulation approach, using 1000 Genomes data, to (a) generate sequence variation at human genes in up to 10K case-control samples, and (b) quantify the statistical power of a panel of widely used gene-based association tests under a variety of allelic architectures, locus effect sizes, and significance thresholds. For loci explaining ~1% of phenotypic variance underlying a common dichotomous trait, we find that all methods have low absolute power to achieve exome-wide significance (~5-20% power at α=2.5×10-6) in 3K individuals; even in 10K samples, power is modest (~60%). The combined application of multiple methods increases sensitivity, but does so at the expense of a higher false positive rate. MiST, SKAT-O, and KBAC have the highest individual mean power across simulated datasets, but we observe wide architecture-dependent variability in the individual loci detected by each test, suggesting that inferences about disease architecture from analysis of sequencing studies can differ depending on which methods are used. Our results imply that tens of thousands of individuals, extensive functional annotation, or highly targeted hypothesis testing will be required to confidently detect or exclude rare variant signals at complex disease loci.
AU  - Moutsianas, L.*
AU  - Agarwala, V.*
AU  - Fuchsberger, C.*
AU  - Flannick, J.*
AU  - Rivas, M.A.*
AU  - Gaulton, K.J.*
AU  - Albers, P.K.*
AU  - GoT2D Consortium (McCarthy, M.I.*
AU  - Gieger, C.
AU  - Grallert, H.
AU  - Hrabě de Angelis, M.
AU  - Huth, C.
AU  - Kriebel, J.
AU  - Meisinger, C.
AU  - Meitinger, T.
AU  - Müller-Nurasyid, M.
AU  - Peters, A.
AU  - Ried, J.S.
AU  - Strauch, K.
AU  - Strom, T.M.)
AU  - McVean, G.*
AU  - Boehnke, M.*
AU  - Altshuler, D.*
C1  - 44739
C2  - 36985
TI  - The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease.
JO  - PLoS Genet.
VL  - 11
IS  - 4
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies with metabolic traits (mGWAS) uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs) contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted 1H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3). Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13), pulmonary hypertension (CPS1), and ischemic stroke (XYLB). By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular mechanisms involved in the etiology of diseases.
AU  - Raffler, J.
AU  - Friedrich, N.*
AU  - Arnold, M.
AU  - Kacprowski, T.*
AU  - Rueedi, R.*
AU  - Altmaier, E.
AU  - Bergmann, S.*
AU  - Budde, K.*
AU  - Gieger, C.
AU  - Homuth, G.*
AU  - Pietzner, M.*
AU  - Römisch-Margl, W.
AU  - Strauch, K.
AU  - Völzke, H.*
AU  - Waldenberger, M.
AU  - Wallaschofski, H.*
AU  - Nauck, M.*
AU  - Völker, U.*
AU  - Kastenmüller, G.
AU  - Suhre, K.
C1  - 46783
C2  - 37797
TI  - Genome-wide association study with targeted and non-targeted NMR metabolomics identifies 15 novel loci of urinary human metabolic individuality.
JO  - PLoS Genet.
VL  - 11
IS  - 9
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Chemerin is an adipokine proposed to link obesity and chronic inflammation of adipose tissue. Genetic factors determining chemerin release from adipose tissue are yet unknown. We conducted a meta-analysis of genome-wide association studies (GWAS) for serum chemerin in three independent cohorts from Europe: Sorbs and KORA from Germany and PPP-Botnia from Finland (total N = 2,791). In addition, we measured mRNA expression of genes within the associated loci in peripheral mononuclear cells by micro-arrays, and within adipose tissue by quantitative RT-PCR and performed mRNA expression quantitative trait and expression-chemerin association studies to functionally substantiate our loci. Heritability estimate of circulating chemerin levels was 16.2% in the Sorbs cohort. Thirty single nucleotide polymorphisms (SNPs) at chromosome 7 within the retinoic acid receptor responder 2 (RARRES2)/Leucine Rich Repeat Containing (LRRC61) locus reached genome-wide significance (p<5.0×10−8) in the meta-analysis (the strongest evidence for association at rs7806429 with p = 7.8×10−14, beta = −0.067, explained variance 2.0%). All other SNPs within the cluster were in linkage disequilibrium with rs7806429 (minimum r2= 0.43 in the Sorbs cohort). The results of the subgroup analyses of males and females were consistent with the results found in the total cohort. No significant SNP-sex interaction was observed. rs7806429 was associated with mRNA expression of RARRES2 in visceral adipose tissue in women (p<0.05 after adjusting for age and body mass index). In conclusion, the present meta-GWAS combined with mRNA expression studies highlights the role of genetic variation in the RARRES2 locus in the regulation of circulating chemerin concentrations.
AU  - Tönjes, A.*
AU  - Scholz, M.*
AU  - Breitfeld, J.*
AU  - Marzi, C.
AU  - Grallert, H.
AU  - Gross, A.*
AU  - Ladenvall, C.*
AU  - Schleinitz, D.*
AU  - Krause, K.P.*
AU  - Kirsten, H.*
AU  - Laurila, E.*
AU  - Kriebel, J.
AU  - Thorand, B.
AU  - Rathmann, W.*
AU  - Groop, L.C.*
AU  - Prokopenko, I.*
AU  - Isomaa, B.*
AU  - Beutner, F.*
AU  - Kratzsch, J.K.*
AU  - Thiery, J.J.*
AU  - Faßhauer, M.*
AU  - Klöting, N.*
AU  - Gieger, C.
AU  - Blüher, M.*
AU  - Stumvoll, M.W.*
AU  - Kovacs, P.*
C1  - 43013
C2  - 35971
TI  - Genome wide meta-analysis highlights the role of genetic variation in RARRES2 in the regulation of circulating serum chemerin.
JO  - PLoS Genet.
VL  - 10
IS  - 12
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.
AU  - Westra, H.J.*
AU  - Arends, D.*
AU  - Esko, T.*
AU  - Peters, M.J.*
AU  - Schurmann, C.*
AU  - Schramm, K.
AU  - Kettunen, J.*
AU  - Yaghootkar, H.*
AU  - Fairfax, B.P.*
AU  - Andiappan, A.K.*
AU  - Li, Y.*
AU  - Fu, J.*
AU  - Karjalainen, J.*
AU  - Platteel, M.*
AU  - Visschedijk, M.*
AU  - Weersma, R.K.*
AU  - Kasela, S.*
AU  - Milani, L.*
AU  - Tserel, L.*
AU  - Peterson, P.*
AU  - Reinmaa, E.*
AU  - Hofman, A.*
AU  - Uitterlinden, A.G.*
AU  - Rivadeneira, F.*
AU  - Homuth, G.*
AU  - Petersmann, A.*
AU  - Lorbeer, R.*
AU  - Prokisch, H.
AU  - Meitinger, T.
AU  - Herder, C.*
AU  - Roden, M.*
AU  - Grallert, H.
AU  - Ripatti, S.*
AU  - Perola, M.*
AU  - Wood, A.R.*
AU  - Melzer, D.*
AU  - Ferrucci, L.*
AU  - Singleton, A.B.*
AU  - Hernandez, D.G.*
AU  - Knight, J.C.*
AU  - Melchiotti, R.*
AU  - Lee, B.*
AU  - Poidinger, M.*
AU  - Zolezzi, F.*
AU  - Larbi, A.*
AU  - Wang, Y.*
AU  - van den Berg, L.H.*
AU  - Veldink, J.H.*
AU  - Rotzschke, O.*
AU  - Makino, S.*
AU  - Salomaa, V.*
AU  - Strauch, K.
AU  - Völker, U.*
AU  - van Meurs, J.B.*
AU  - Metspalu, A.*
AU  - Wijmenga, C.*
AU  - Jansen, R.C.*
AU  - Franke, L.*
C1  - 44803
C2  - 37030
CY  - San Francisco
TI  - Cell specific eQTL analysis without sorting cells.
JO  - PLoS Genet.
VL  - 11
IS  - 5
PB  - Public Library Science
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
AU  - Winkler, T.W.*
AU  - Justice, A.E.*
AU  - Graff, M.*
AU  - Barata, L.*
AU  - Feitosa, M.F.*
AU  - Chu, S.*
AU  - Czajkowski, J.*
AU  - Esko, T.*
AU  - Fall, T.*
AU  - Kilpeläinen, T.O.*
AU  - Lu, Y.*
AU  - Mägi, R.*
AU  - Mihailov, E.*
AU  - Pers, T.H.*
AU  - Rüeger, S.*
AU  - Teumer, A.*
AU  - Ehret, G.B.*
AU  - Ferreira, T.*
AU  - Heard-Costa, N.L.*
AU  - Karjalainen, J.*
AU  - Lagou, V.*
AU  - Mahajan, A.*
AU  - Neinast, M.D.*
AU  - Prokopenko, I.*
AU  - Simino, J.*
AU  - Teslovich, T.M.*
AU  - Jansen, R.*
AU  - Westra, H.J.*
AU  - White, C.C.*
AU  - Absher, D.*
AU  - Ahluwalia, T.S.*
AU  - Ahmad, S.*
AU  - Albrecht, E.
AU  - Alves, A.C.*
AU  - Bragg-Gresham, J.L.*
AU  - de Craen, A.J.*
AU  - Bis, J.C.*
AU  - Bonnefond, A.*
AU  - Boucher, G.*
AU  - Cadby, G.*
AU  - Cheng, Y.C.*
AU  - Chiang, C.W.*
AU  - Delgado, G.*
AU  - Demirkan, A.*
AU  - Dueker, N.*
AU  - Eklund, N.*
AU  - Eiriksdottir, G.*
AU  - Eriksson, J.*
AU  - Feenstra, B.*
AU  - Fischer, K.*
AU  - Frau, F.*
AU  - Galesloot, T.E.*
AU  - Geller, F.*
AU  - Goel, A.*
AU  - Gorski, M.*
AU  - Grammer, T.B.*
AU  - Gustafsson, S.*
AU  - Haitjema, S.*
AU  - Hottenga, J.J.*
AU  - Huffman, J.E.*
AU  - Jackson, A.U.*
AU  - Jacobs, K.B.*
AU  - Johansson, A.*
AU  - Kaakinen, M.*
AU  - Kleber, M.E.*
AU  - Lahti, J.*
AU  - Mateo Leach, I.*
AU  - Lehne, B.*
AU  - Liu, Y.*
AU  - Lo, K.S.*
AU  - Lorentzon, M.*
AU  - Luan, J.*
AU  - Madden, P.A.*
AU  - Mangino, M.*
AU  - McKnight, B.*
AU  - Medina-Gomez, C.*
AU  - Monda, K.L.*
AU  - Montasser, M.E.*
AU  - Müller, G.*
AU  - Müller-Nurasyid, M.
AU  - Nolte, I.M.*
AU  - Panoutsopoulou, K.*
AU  - Pascoe, L.*
AU  - Paternoster, L.*
AU  - Rayner, N.W.*
AU  - Renström, F.*
AU  - Rizzi, F.*
AU  - Rose, L.M.*
AU  - Ryan, K.A.*
AU  - Salo, P.*
AU  - Sanna, S.*
AU  - Scharnagl, H.*
AU  - Shi, J.*
AU  - Smith, A.V.*
AU  - Southam, L.*
AU  - Stancáková, A.*
AU  - Steinthorsdottir, V.*
AU  - Strawbridge, R.J.*
AU  - Sung, Y.J.*
AU  - Tachmazidou, I.*
AU  - Tanaka, T.*
AU  - Thorleifsson, G.*
AU  - Trompet, S.*
AU  - Pervjakova, N.*
AU  - Tyrer, J.P.*
AU  - Vandenput, L.*
AU  - van der Laan, S.W.*
AU  - van der Velde, N.*
AU  - van Setten, J.*
AU  - van Vliet-Ostaptchouk, J.V.*
AU  - Verweij, N.*
AU  - Vlachopoulou, E.*
AU  - Waite, L.L.*
AU  - Wang, S.R.*
AU  - Wang, Z.*
AU  - Wild, S.H.*
AU  - Willenborg, C.*
AU  - Wilson, J.F.*
AU  - Wong, A.*
AU  - Yang, J.*
AU  - Yengo, L.*
AU  - Yerges-Armstrong, L.M.*
AU  - Yu, L.*
AU  - Zhang, W.*
AU  - Zhao, J.H.*
AU  - Andersson, E.A.*
AU  - Bakker, S.J.*
AU  - Baldassarre, D.*
AU  - Banasik, K.*
AU  - Barcella, M.*
AU  - Barlassina, C.*
AU  - Bellis, C.*
AU  - Benaglio, P.*
AU  - Blangero, J.*
AU  - Blüher, M.*
AU  - Bonnet, F.*
AU  - Bonnycastle, L.L.*
AU  - Boyd, H.A.*
AU  - Bruinenberg, M.*
AU  - Buchman, A.S.*
AU  - Campbell, H.*
AU  - Chen, Y.D.*
AU  - Chines, P.S.*
AU  - Claudi-Boehm, S.*
AU  - Cole, J.*
AU  - Collins, F.S.*
AU  - de Geus, E.J.*
AU  - de Groot, L.C.*
AU  - Dimitriou, M.*
AU  - Duan, J.*
AU  - Enroth, S.*
AU  - Eury, E.*
AU  - Farmaki, A.-E.*
AU  - Forouhi, N.G.*
AU  - Friedrich, N.*
AU  - Gejman, P.V.*
AU  - Gigante, B.*
AU  - Glorioso, N.*
AU  - Go, A.S.*
AU  - Gottesman, O.*
AU  - Gräßler, J.*
AU  - Grallert, H.
AU  - Grarup, N.*
AU  - Gu, Y.M.*
AU  - Broer, L.*
AU  - Ham, A.C.*
AU  - Hansen, T.*
AU  - Harris, T.B.*
AU  - Hartman, C.A.*
AU  - Hassinen, M.*
AU  - Hastie, N.*
AU  - Hattersley, A.T.*
AU  - Heath, A.C.*
AU  - Henders, A.K.*
AU  - Hernandez, D.*
AU  - Hillege, H.*
AU  - Holmen, O.L.*
AU  - Hovingh, K.G.*
AU  - Hui, J.*
AU  - Husemoen, L.L.*
AU  - Hutri-Kähönen, N.*
AU  - Hysi, P.G.*
AU  - Illig, T.
AU  - de Jager, P.L.*
AU  - Jalilzadeh, S.*
AU  - Jørgensen, T.*
AU  - Jukema, J.W.*
AU  - Juonala, M.*
AU  - Kanoni, S.*
AU  - Karaleftheri, M.*
AU  - Khaw, K.T.*
AU  - Kinnunen, L.*
AU  - Kittner, S.J.*
AU  - Koenig, W.*
AU  - Kolcic, I.*
AU  - Kovacs, P.*
AU  - Krarup, N.T.*
AU  - Kratzer, W.*
AU  - Krüger, J.*
AU  - Kuh, D.*
AU  - Kumari, M.*
AU  - Kyriakou, T.*
AU  - Langenberg, C.*
AU  - Lannfelt, L.*
AU  - Lanzani, C.*
AU  - Lotay, V.*
AU  - Launer, L.J.*
AU  - Leander, K.*
AU  - Lindstrom, J.*
AU  - Linneberg, A.*
AU  - Liu, Y.P.*
AU  - Lobbens, S.*
AU  - Luben, R.*
AU  - Lyssenko, V.*
AU  - Männistö, S.*
AU  - Magnusson, P.K.*
AU  - McArdle, W.L.*
AU  - Menni, C.*
AU  - Merger, S.*
AU  - Milani, L.*
AU  - Montgomery, G.W.*
AU  - Morris, A.P.*
AU  - Narisu, N.*
AU  - Nelis, M.*
AU  - Ong, K.K.*
AU  - Palotie, A.*
AU  - Perusse, L.*
AU  - Pichler, I.*
AU  - Pilia, M.G.*
AU  - Pouta, A.*
AU  - Rheinberger, M.*
AU  - Ribel-Madsen, R.*
AU  - Richards, M.*
AU  - Rice, K.M.*
AU  - Rice, T.K.*
AU  - Rivolta, C.*
AU  - Salomaa, V.*
AU  - Sanders, A.R.*
AU  - Sarzynski, M.A.*
AU  - Scholtens, S.*
AU  - Scott, R.A.*
AU  - Scott, W.R.*
AU  - Sebert, S.*
AU  - Sengupta, S.*
AU  - Sennblad, B.*
AU  - Seufferlein, T.*
AU  - Silveira, A.*
AU  - Slagboom, P.E.*
AU  - Smit, J.H.*
AU  - Sparsø, T.H.*
AU  - Stirrups, K.*
AU  - Stolk, R.P.*
AU  - Stringham, H.M.*
AU  - Swertz, M.A.*
AU  - Swift, A.J.*
AU  - Syvanen, A.C.*
AU  - Tan, S.T.*
AU  - Thorand, B.
AU  - Tönjes, A.*
AU  - Tremblay, A.*
AU  - Tsafantakis, E.*
AU  - van der Most, P.J.*
AU  - Völker, U.*
AU  - Vohl, M.C.*
AU  - Vonk, J.M.*
AU  - Waldenberger, M.
AU  - Walker, R.W.*
AU  - Wennauer, R.*
AU  - Widen, E.*
AU  - Willemsen, G.*
AU  - Wilsgaard, T.*
AU  - Wright, A.F.*
AU  - Zillikens, M.C.*
AU  - van Dijk, S.C.*
AU  - van Schoor, N.M.*
AU  - Asselbergs, F.W.*
AU  - de Bakker, P.I.*
AU  - Beckmann, J.S.*
AU  - Beilby, J.*
AU  - Bennett, D.A.*
AU  - Bergman, R.N.*
AU  - Bergmann, S.*
AU  - Böger, C.A.*
AU  - Boehm, B.O.*
AU  - Boerwinkle, E.*
AU  - Boomsma, D.I.*
AU  - Bornstein, S.R.*
AU  - Bottinger, E.P.*
AU  - Bouchard, C.*
AU  - Chambers, J.C.*
AU  - Chanock, S.J.*
AU  - Chasman, D.I.*
AU  - Cucca, F.*
AU  - Cusi, D.*
AU  - Dedoussis, G.*
AU  - Erdmann, J.*
AU  - Eriksson, J.G.*
AU  - Evans, D.A.*
AU  - de Faire, U.*
AU  - Farrall, M.*
AU  - Ferrucci, L.*
AU  - Ford, I.*
AU  - Franke, L.*
AU  - Franks, P.W.*
AU  - Froguel, P.*
AU  - Gansevoort, R.T.*
AU  - Gieger, C.
AU  - Grönberg, H.*
AU  - Gudnason, V.*
AU  - Gyllensten, U.*
AU  - Hall, P.*
AU  - Hamsten, A.*
AU  - van der Harst, P.*
AU  - Hayward, C.*
AU  - Heliövaara, M.*
AU  - Hengstenberg, C.*
AU  - Hicks, A.A.*
AU  - Hingorani, A.*
AU  - Hofman, A.*
AU  - Hu, F.*
AU  - Huikuri, H.V.*
AU  - Hveem, K.*
AU  - James, A.L.*
AU  - Jordan, J.M.*
AU  - Jula, A.*
AU  - Kähönen, M.*
AU  - Kajantie, E.*
AU  - Kathiresan, S.*
AU  - Kiemeney, L.A.*
AU  - Kivimaki, M.*
AU  - Knekt, P.B.*
AU  - Koistinen, H.A.*
AU  - Kooner, J.S.*
AU  - Koskinen, S.*
AU  - Kuusisto, J.*
AU  - Maerz, W.*
AU  - Martin, N.G.*
AU  - Laakso, M.*
AU  - Lakka, T.A.*
AU  - Lehtimäki, T.*
AU  - Lettre, G.*
AU  - Levinson, D.F.*
AU  - Lind, L.*
AU  - Lokki, M.L.*
AU  - Mäntyselkä, P.*
AU  - Melbye, M.*
AU  - Metspalu, A.*
AU  - Mitchell, B.D.*
AU  - Moll, F.L.*
AU  - Murray, J.C.*
AU  - Musk, A.W.*
AU  - Nieminen, M.S.*
AU  - Njølstad, I.*
AU  - Ohlsson, C.*
AU  - Oldehinkel, A.J.*
AU  - Oostra, B.A.*
AU  - Palmer, L.J.*
AU  - Pankow, J.S.*
AU  - Pasterkamp, G.*
AU  - Pedersen, N.L.*
AU  - Pedersen, O.*
AU  - Penninx, B.W.*
AU  - Perola, M.*
AU  - Peters, A.
AU  - Polasek, O.*
AU  - Pramstaller, P.P.*
AU  - Psaty, B.M.*
AU  - Qi, L.*
AU  - Quertermous, T.*
AU  - Raitakari, O.T.*
AU  - Rankinen, T.*
AU  - Rauramaa, R.*
AU  - Ridker, P.M.*
AU  - Rioux, J.D.*
AU  - Rivadeneira, F.*
AU  - Rotter, J.I.*
AU  - Rudan, I.*
AU  - den Ruijter, H.M.*
AU  - Saltevo, J.*
AU  - Sattar, N.*
AU  - Schunkert, H.*
AU  - Schwarz, P.E.*
AU  - Shuldiner, A.R.*
AU  - Sinisalo, J.*
AU  - Snieder, H.*
AU  - Sørensen, T.I.*
AU  - Spector, T.D.*
AU  - Staessen, J.A.*
AU  - Stefania, B.*
AU  - Thorsteinsdottir, U.*
AU  - Stumvoll, M.*
AU  - Tardif, J.-C.*
AU  - Tremoli, E.*
AU  - Tuomilehto, J.*
AU  - Uitterlinden, A.G.*
AU  - Uusitupa, M.*
AU  - Verbeek, A.L.*
AU  - Vermeulen, S.H.*
AU  - Viikari, J.S.*
AU  - Vitart, V.*
AU  - Völzke, H.*
AU  - Vollenweider, P.*
AU  - Waeber, G.*
AU  - Walker, M.*
AU  - Wallaschofski, H.*
AU  - Wareham, N.J.*
AU  - Watkins, H.*
AU  - Zeggini, E.*
AU  - CHARGE Consortium (Gieger, C.
AU  - Meisinger, C.
AU  - Prokisch, H.
AU  - Wichmann, H.-E.)
AU  - DIAGRAM Consortium (Klopp, N.
AU  - Meyer, J.)
AU  - GLGC Consortium (*)
AU  - Global BPgen Consortium (Döring, A.)
AU  - ICBP Consortium (Meitinger, T.)
AU  - MAGIC Consortium (*)
AU  - Chakravarti, A.*
AU  - Clegg, D.J.*
AU  - Cupples, L.A.*
AU  - Gordon-Larsen, P.*
AU  - Jaquish, C.E.*
AU  - Rao, D.C.*
AU  - Abecasis, G.R.*
AU  - Assimes, T.L.*
AU  - Barroso, I.*
AU  - Berndt, S.I.*
AU  - Boehnke, M.*
AU  - Deloukas, P.*
AU  - Fox, C.S.*
AU  - Groop, L.C.*
AU  - Hunter, D.J.*
AU  - Ingelsson, E.*
AU  - Kaplan, R.C.*
AU  - McCarthy, M.I.*
AU  - Mohlke, K.L.*
AU  - O'Connell, J.R.*
AU  - Schlessinger, D.*
AU  - Strachan, D.P.*
AU  - Stefansson, K.*
AU  - van Duijn, C.M.*
AU  - Hirschhorn, J.N.*
AU  - Lindgren, C.M.*
AU  - Heid, I.M.
AU  - North, K.E.*
AU  - Borecki, I.B.*
AU  - Kutalik, Z.*
AU  - Loos, R.J.*
C1  - 46950
C2  - 39079
TI  - The influence of age and sex on genetic associations with adult body size and shape: A large-scale genome-wide interaction study.
JO  - PLoS Genet.
VL  - 11
IS  - 10
PY  - 2015
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.
AU  - Hoggart, C.J.*
AU  - Venturini, G.*
AU  - Mangino, M.*
AU  - Gomez, F.*
AU  - Ascari, G.*
AU  - Zhao, J.H.*
AU  - Teumer, A.*
AU  - Winkler, T.W.*
AU  - Tsernikova, N.*
AU  - Luan, J.*
AU  - Mihailov, E.*
AU  - Ehret, G.B.*
AU  - Zhang, W.*
AU  - Lamparter, D.*
AU  - Esko, T.*
AU  - Mace, A.*
AU  - Rüeger, S.*
AU  - Bochud, P.Y.*
AU  - Barcella, M.*
AU  - Dauvilliers, Y.*
AU  - Benyamin, B.*
AU  - Evans, D.M*
AU  - Hayward, C.*
AU  - Lopez, M.F.*
AU  - Franke, L.*
AU  - Russo, A.*
AU  - Heid, I.M.*
AU  - Salvi, E.*
AU  - Vendantam, S.*
AU  - Arking, D.E.*
AU  - Boerwinkle, E.*
AU  - Chambers, J.C.*
AU  - Fiorito, G.*
AU  - Grallert, H.
AU  - Guarrera, S.*
AU  - Homuth, G.*
AU  - Huffman, J.E.*
AU  - Porteous, D.J.*
AU  - Generation Scotland Consortium (Loos, R.J.*)
AU  - LifeLines Cohort Study (Rivolta, C.*)
AU  - GIANT Consortium (Albrecht, E.
AU  - Gieger, C.
AU  - Heid, I.M.
AU  - Illig, T.
AU  - Kutalik, Z.*
AU  - Müller-Nurasyid, M.
AU  - Thorand, B.
AU  - Wichmann, H.-E.)
AU  - Moradpour, D.*
AU  - Iranzo, A.*
AU  - Hebebrand, J.*
AU  - Kemp, J.P.*
AU  - Lammers, G.J.*
AU  - Aubert, V.*
AU  - Heim, M.H.*
AU  - Martin, N.G.*
AU  - Montgomery, G.W.*
AU  - Peraita-Adrados, R.*
AU  - Santamaría, J.*
AU  - Negro, F.*
AU  - Schmidt, C.O.*
AU  - Scott, R.A.*
AU  - Spector, T.D.*
AU  - Strauch, K.
AU  - Völzke, H.*
AU  - Wareham, N.J.*
AU  - Yuan, W.*
AU  - Bell, J.T.*
AU  - Chakravarti, A.*
AU  - Kooner, J.S.*
AU  - Peters, A.
AU  - Matullo, G.*
AU  - Wallaschofski, H.*
AU  - Whitfield, J.B.*
AU  - Paccaud, F.*
AU  - Vollenweider, P.*
AU  - Bergmann, S.*
AU  - Beckmann, J.S.*
AU  - Tafti, M.*
AU  - Hastie, N.D.*
AU  - Cusi, D.*
AU  - Bochud, M.*
AU  - Frayling, T.M.*
AU  - Metspalu, A.*
AU  - Jarvelin, M.R.*
AU  - Scherag, A.*
AU  - Smith, G.D.*
AU  - Borecki, I.B.*
AU  - Rousson, V.*
AU  - Hirschhorn, J.N.*
C1  - 31858
C2  - 34829
CY  - San Francisco
SP  - 1-12
TI  - Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on Body Mass Index.
JO  - PLoS Genet.
VL  - 10
IS  - 7
PB  - Public Library Science
PY  - 2014
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Autoimmune thyroid diseases (AITD) are common, affecting 2-5% of the general population. Individuals with positive thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune hypothyroidism (Hashimoto's thyroiditis), as well as autoimmune hyperthyroidism (Graves' disease). As the possible causative genes of TPOAbs and AITD remain largely unknown, we performed GWAS meta-analyses in 18,297 individuals for TPOAb-positivity (1769 TPOAb-positives and 16,528 TPOAb-negatives) and in 12,353 individuals for TPOAb serum levels, with replication in 8,990 individuals. Significant associations (P<5×10(-8)) were detected at TPO-rs11675434, ATXN2-rs653178, and BACH2-rs10944479 for TPOAb-positivity, and at TPO-rs11675434, MAGI3-rs1230666, and KALRN-rs2010099 for TPOAb levels. Individual and combined effects (genetic risk scores) of these variants on (subclinical) hypo- and hyperthyroidism, goiter and thyroid cancer were studied. Individuals with a high genetic risk score had, besides an increased risk of TPOAb-positivity (OR: 2.18, 95% CI 1.68-2.81, P = 8.1×10(-8)), a higher risk of increased thyroid-stimulating hormone levels (OR: 1.51, 95% CI 1.26-1.82, P = 2.9×10(-6)), as well as a decreased risk of goiter (OR: 0.77, 95% CI 0.66-0.89, P = 6.5×10(-4)). The MAGI3 and BACH2 variants were associated with an increased risk of hyperthyroidism, which was replicated in an independent cohort of patients with Graves' disease (OR: 1.37, 95% CI 1.22-1.54, P = 1.2×10(-7) and OR: 1.25, 95% CI 1.12-1.39, P = 6.2×10(-5)). The MAGI3 variant was also associated with an increased risk of hypothyroidism (OR: 1.57, 95% CI 1.18-2.10, P = 1.9×10(-3)). This first GWAS meta-analysis for TPOAbs identified five newly associated loci, three of which were also associated with clinical thyroid disease. With these markers we identified a large subgroup in the general population with a substantially increased risk of TPOAbs. The results provide insight into why individuals with thyroid autoimmunity do or do not eventually develop thyroid disease, and these markers may therefore predict which TPOAb-positives are particularly at risk of developing clinical thyroid dysfunction.
AU  - Medici, M.*
AU  - Porcu, E.*
AU  - Pistis, G.*
AU  - Teumer, A.*
AU  - Brown, S.J.*
AU  - Jensen, R.A.*
AU  - Rawal, R.
AU  - Roef, G.L.*
AU  - Plantinga, T.S.*
AU  - Vermeulen, S.H.*
AU  - Lahti, J.*
AU  - Simmonds, M.J.*
AU  - Husemoen, L.L.*
AU  - Freathy, R.M.*
AU  - Shields, B.M.*
AU  - Pietzner, D.*
AU  - Nagy, R.*
AU  - Broer, L.*
AU  - Chaker, L.*
AU  - Korevaar, T.I.*
AU  - Plia, M.G.*
AU  - Sala, C.*
AU  - Völker, U.*
AU  - Richards, J.B.*
AU  - Sweep, F.C.*
AU  - Gieger, C.
AU  - Corre, T.*
AU  - Kajantie, E.*
AU  - Thuesen, B.*
AU  - Taes, Y.E.*
AU  - Visser, W.E.*
AU  - Hattersley, A.T.*
AU  - Kratzsch, J.*
AU  - Hamilton, A.*
AU  - Li, W.*
AU  - Homuth, G.*
AU  - Lobina, M.*
AU  - Mariotti, S.*
AU  - Soranzo, N.*
AU  - Cocca, M.*
AU  - Nauck, M.*
AU  - Spielhagen, C.*
AU  - Ross, A.*
AU  - Arnold, A.*
AU  - van de Bunt, M.*
AU  - Liyanarachchi, S.*
AU  - Heier, M.
AU  - Grabe, H.J.*
AU  - Masciullo, C.*
AU  - Galesloot, T.E.*
AU  - Lim, E.M.*
AU  - Reischl, E.
AU  - Leedman, P.J.*
AU  - Lai, S.*
AU  - Delitala, A.*
AU  - Bremner, A.P.*
AU  - Philips, D.I.*
AU  - Beilby, J.P.*
AU  - Mulas, A.*
AU  - Vocale, M.*
AU  - Abecasis, G.*
AU  - Forsen, T.*
AU  - James, A.*
AU  - Widen, E.*
AU  - Hui, J.*
AU  - Prokisch, H.
AU  - Rietzschel, E.E.*
AU  - Palotie, A.*
AU  - Feddema, P.*
AU  - Fletcher, S.J.*
AU  - Schramm, K.
AU  - Rotter, J.I.*
AU  - Kluttig, A.*
AU  - Radke, D.*
AU  - Traglia, M.*
AU  - Surdulescu, G.L.*
AU  - He, H.*
AU  - Franklyn, J.A.*
AU  - Tiller, D.*
AU  - Vaidya, B.*
AU  - de Meyer, T.*
AU  - Jørgensen, T.*
AU  - Eriksson, J.G.*
AU  - O'Leary, P.C.*
AU  - Wichmann, H.-E.
AU  - Hermus, A.R.*
AU  - Psaty, B.M.*
AU  - Ittermann, T.*
AU  - Hofman, A.*
AU  - Bosi, E.*
AU  - Schlessinger, D.*
AU  - Wallaschofski, H.*
AU  - Pirastu, N.*
AU  - Aulchenko, Y.S.*
AU  - de la Chapelle, A.*
AU  - Netea-Maier, R.T.*
AU  - Gough, S.C.*
AU  - Meyer zu Schwabedissen, H.E.*
AU  - Frayling, T.M.*
AU  - Kaufman, J.M.*
AU  - Linneberg, A.*
AU  - Räikkönen, K.*
AU  - Smit, J.W.A.*
AU  - Kiemeney, L.A.*
AU  - Rivadeneira, F.*
AU  - Uitterlinden, A.G.*
AU  - Walsh, J.P.*
AU  - Meisinger, C.
AU  - den Heijer, M.*
AU  - Visser, T.J.*
AU  - Spector, T.D.*
AU  - Wilson, S.G.*
AU  - Völzke, H.*
AU  - Cappola, A.*
AU  - Toniolo, D.*
AU  - Sanna, S.*
AU  - Naitza, S.*
AU  - Peeters, R.P.*
C1  - 30774
C2  - 33852
CY  - San Francisco
TI  - Identification of novel genetic loci associated with thyroid peroxidase antibodies and clinical thyroid disease.
JO  - PLoS Genet.
VL  - 10
IS  - 2
PB  - Public Library Science
PY  - 2014
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15x10(-94) < P < 5x10(-8), odds ratio (OR) = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2x10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.
AU  - Ng, M.C.Y.*
AU  - Shriner, D.*
AU  - Chen, B.H.*
AU  - Li, J.*
AU  - Chen, W.*
AU  - Guo, X.*
AU  - Liu, J.*
AU  - Bielinski, S.J.*
AU  - Yanek, L.R.*
AU  - Nalls, M.A.*
AU  - Comeau, M.E.*
AU  - Rasmussen-Torvik, L.J.*
AU  - Jensen, R.A.*
AU  - Evans, D.S.*
AU  - Sun, Y.V.*
AU  - An, P.*
AU  - Patel, S.R.*
AU  - Lu, Y.*
AU  - Long, J.*
AU  - Armstrong, L.L.*
AU  - Wagenknecht, L.*
AU  - Yang, L.*
AU  - Snively, B.M.*
AU  - Palmer, N.D.*
AU  - Mudgal, P.*
AU  - Langefeld, C.D.*
AU  - Keene, K.L.*
AU  - Freedman, B.I.*
AU  - Mychaleckyj, J.C.*
AU  - Nayak, U.*
AU  - Raffel, L.J.*
AU  - Goodarzi, M.O.*
AU  - Chen, Y.I.*
AU  - Taylor, H.A.*
AU  - Correa, A.*
AU  - Sims, M.*
AU  - Couper, D.*
AU  - Pankow, J.S.*
AU  - Boerwinkle, E.*
AU  - Adeyemo, A.*
AU  - Doumatey, A.*
AU  - Chen, G.*
AU  - Mathias, R.A.*
AU  - Vaidya, D.*
AU  - Singleton, A.B.*
AU  - Zonderman, A.B.*
AU  - Igo, R.P.*
AU  - Sedor, J.R.*
AU  - FIND Consortium (*)
AU  - Kabagambe, E.K.*
AU  - Siscovick, D.S.*
AU  - McKnight, B.*
AU  - Rice, K.*
AU  - Liu, Y.*
AU  - Hsueh, W.C.*
AU  - Zhao, W.*
AU  - Bielak, L.F.*
AU  - Kraja, A.*
AU  - Province, M.A.*
AU  - Bottinger, E.P.*
AU  - Gottesman, O.*
AU  - Cai, Q.*
AU  - Zheng, W.*
AU  - Blot, W.J.*
AU  - Lowe, W.L.*
AU  - Pacheco, J.A.*
AU  - Crawford, D.C.*
AU  - eMERGE Consortium (*)
AU  - DIAGRAM Consortium (Gieger, C.
AU  - Grallert, H.
AU  - Illig, T.
AU  - Klopp, N.
AU  - Müller-Nurasyid, M.
AU  - Peters, A.)
AU  - Grundberg, E.*
AU  - MuTHER Consortium (*)
AU  - Rich, S.S.*
AU  - Hayes, M.G.*
AU  - Shu, X.*
AU  - Loos, R.J.F.*
AU  - Borecki, I.B.*
AU  - Peyser, P.A.*
AU  - Cummings, S.R.*
AU  - Psaty, B.M.*
AU  - Fornage, M.*
AU  - Iyengar, S.K.*
AU  - Evans, M.K.*
AU  - Becker, D.M.*
AU  - Kao, W.H.L.*
AU  - Wilson, J.G.*
AU  - Rotter, J.I.*
AU  - Sale, M.M.*
AU  - Liu, S.*
AU  - Rotimi, C.N.*
AU  - Bowden, D.W.*
AU  - MEDIA Consortium (*)
C1  - 32529
C2  - 35119
CY  - San Francisco
TI  - Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes.
JO  - PLoS Genet.
VL  - 10
IS  - 8
PB  - Public Library Science
PY  - 2014
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Human driven selection during domestication and subsequent breed formation has likely left detectable signatures within the genome of modern cattle. The elucidation of these signatures of selection is of interest from the perspective of evolutionary biology, and for identifying domestication-related genes that ultimately may help to further genetically improve this economically important animal. To this end, we employed a panel of more than 15 million autosomal SNPs identified from re-sequencing of 43 Fleckvieh animals. We mainly applied two somewhat complementary statistics, the integrated Haplotype Homozygosity Score (iHS) reflecting primarily ongoing selection, and the Composite of Likelihood Ratio (CLR) having the most power to detect completed selection after fixation of the advantageous allele. We find 106 candidate selection regions, many of which are harboring genes related to phenotypes relevant in domestication, such as coat coloring pattern, neurobehavioral functioning and sensory perception including KIT, MITF, MC1R, NRG4, Erbb4, TMEM132D and TAS2R16, among others. To further investigate the relationship between genes with signatures of selection and genes identified in QTL mapping studies, we use a sample of 3062 animals to perform four genome-wide association analyses using appearance traits, body size and somatic cell count. We show that regions associated with coat coloring significantly (P<0.0001) overlap with the candidate selection regions, suggesting that the selection signals we identify are associated with traits known to be affected by selection during domestication. Results also provide further evidence regarding the complexity of the genetics underlying coat coloring in cattle. This study illustrates the potential of population genetic approaches for identifying genomic regions affecting domestication-related phenotypes and further helps to identify specific regions targeted by selection during speciation, domestication and breed formation of cattle. We also show that Linkage Disequilibrium (LD) decays in cattle at a much faster rate than previously thought.
AU  - Qanbari, S.*
AU  - Pausch, H.*
AU  - Jansen, S.*
AU  - Somel, M.*
AU  - Strom, T.M.
AU  - Fries, R.*
AU  - Nielsen, R.*
AU  - Simianer, H.*
C1  - 30772
C2  - 33850
CY  - San Francisco
TI  - Classic selective sweeps revealed by massive sequencing in cattle.
JO  - PLoS Genet.
VL  - 10
IS  - 2
PB  - Public Library Science
PY  - 2014
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Cilia are microtubule-based cell appendages, serving motility, chemo-/mechano-/photo- sensation, and developmental signaling functions. Cilia are comprised of distinct structural and functional subregions including the basal body, transition zone (TZ) and inversin (Inv) compartments, and defects in this organelle are associated with an expanding spectrum of inherited disorders including Bardet-Biedl syndrome (BBS), Meckel-Gruber Syndrome (MKS), Joubert Syndrome (JS) and Nephronophthisis (NPHP). Despite major advances in understanding ciliary trafficking pathways such as intraflagellar transport (IFT), how proteins are transported to subciliary membranes remains poorly understood. Using Caenorhabditis elegans and mammalian cells, we investigated the transport mechanisms underlying compartmentalization of JS-associated ARL13B/ARL-13, which we previously found is restricted at proximal ciliary membranes. We now show evolutionary conservation of ARL13B/ARL-13 localisation to an Inv-like subciliary membrane compartment, excluding the TZ, in many C. elegans ciliated neurons and in a subset of mammalian ciliary subtypes. Compartmentalisation of C. elegans ARL-13 requires a C-terminal RVVP motif and membrane anchoring to prevent distal cilium and nuclear targeting, respectively. Quantitative imaging in more than 20 mutants revealed differential contributions for IFT and ciliopathy modules in defining the ARL-13 compartment; IFT-A/B, IFT-dynein and BBS genes prevent ARL-13 accumulation at periciliary membranes, whereas MKS/NPHP modules additionally inhibit ARL-13 association with TZ membranes. Furthermore, in vivo FRAP analyses revealed distinct roles for IFT and MKS/NPHP genes in regulating a TZ barrier to ARL-13 diffusion, and intraciliary ARL-13 diffusion. Finally, C. elegans ARL-13 undergoes IFT-like motility and quantitative protein complex analysis of human ARL13B identified functional associations with IFT-B complexes, mapped to IFT46 and IFT74 interactions. Together, these findings reveal distinct requirements for sequence motifs, IFT and ciliopathy modules in defining an ARL-13 subciliary membrane compartment. We conclude that MKS/NPHP modules comprise a TZ barrier to ARL-13 diffusion, whereas IFT genes predominantly facilitate ARL-13 ciliary entry and/or retention via active transport mechanisms.
AU  - Cevik, S.*
AU  - Sanders, A.A.W.M.*
AU  - van Wijk, E.*
AU  - Boldt, K.*
AU  - Clarke, L.*
AU  - van Reeuwijk, J.*
AU  - Hori, Y.*
AU  - Horn, N.*
AU  - Hetterschijt, L.*
AU  - Wdowicz, A.*
AU  - Mullins, A.*
AU  - Kida, K.*
AU  - Kaplan, O.I.*
AU  - van Beersum, S.E.C.*
AU  - Wu, K.M.*
AU  - Letteboer, S.J.F.*
AU  - Mans, D.A.*
AU  - Katada, T.*
AU  - Kontani, K.*
AU  - Ueffing, M.
AU  - Roepman, R.*
AU  - Kremer, H.*
AU  - Blacque, O.E.*
C1  - 30680
C2  - 33868
CY  - San Francisco
TI  - Active transport and diffusion barriers restrict Joubert Syndrome-associated ARL13B/ARL-13 to an Inv-like ciliary membrane subdomain.
JO  - PLoS Genet.
VL  - 9
IS  - 12
PB  - Public Library Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.
AU  - Evans, D.M*
AU  - Brion, M.J.*
AU  - Paternoster, L.*
AU  - Kemp, J.P.*
AU  - McMahon, G.*
AU  - Munafò, M.*
AU  - Whitfield, J.B.*
AU  - Medland, S.E.*
AU  - Montgomery, G.W.*
AU  - GIANT Consortium (Gieger, C.
AU  - Grallert, H.
AU  - Heid, I.M.
AU  - Heinrich, J.
AU  - Illig, T.
AU  - Peters, A.
AU  - Wichmann, H.-E.)
AU  - CRP Consortium (Baumert, J.J.)
AU  - TAG Consortium (*)
AU  - Timpson, N.J.*
AU  - St. Pourcain, B.*
AU  - Lawlor, D.A.*
AU  - Martin, N.G.*
AU  - Dehghan, A.*
AU  - Hirschhorn, J.*
AU  - Davey Smith, G.*
C1  - 28955
C2  - 33592
CY  - San Francisco
TI  - Mining the human phenome using allelic scores that index biological intermediates.
JO  - PLoS Genet.
VL  - 9
IS  - 10
PB  - Public Library Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Recent advances in the identification of susceptibility genes and environmental exposures provide broad support for a post-infectious autoimmune basis for narcolepsy/hypocretin (orexin) deficiency. We genotyped loci associated with other autoimmune and inflammatory diseases in 1,886 individuals with hypocretin-deficient narcolepsy and 10,421 controls, all of European ancestry, using a custom genotyping array (ImmunoChip). Three loci located outside the Human Leukocyte Antigen (HLA) region on chromosome 6 were significantly associated with disease risk. In addition to a strong signal in the T cell receptor alpha (TRA@), variants in two additional narcolepsy loci, Cathepsin H (CTSH) and Tumor necrosis factor (ligand) superfamily member 4 (TNFSF4, also called OX40L), attained genome-wide significance. These findings underline the importance of antigen presentation by HLA Class II to T cells in the pathophysiology of this autoimmune disease.
AU  - Faraco, J.*
AU  - Lin, L.*
AU  - Kornum, B.R.*
AU  - Kenny, E.E.*
AU  - Trynka, G.*
AU  - Einen, M.*
AU  - Rico, T.J.*
AU  - Lichtner, P.
AU  - Dauvilliers, Y.*
AU  - Arnulf, I.*
AU  - Lecendreux, M.*
AU  - Javidi, S.*
AU  - Geisler, P.*
AU  - Mayer, G.*
AU  - Pizza, F.*
AU  - Poli, F.*
AU  - Plazzi, G.*
AU  - Overeem, S.*
AU  - Lammers, G.J.*
AU  - Kemlink, D.*
AU  - Sonka, K.*
AU  - Nevsimalova, S.*
AU  - Rouleau, G.*
AU  - Desautels, A.*
AU  - Montplaisir, J.*
AU  - Frauscher, B.*
AU  - Ehrmann, L.*
AU  - Högl, B.*
AU  - Jennum, P.*
AU  - Bourgin, P.*
AU  - Peraita-Adrados, R.*
AU  - Iranzo, A.*
AU  - Bassetti, C.*
AU  - Chen, W.M.*
AU  - Concannon, P.*
AU  - Thompson, S.D.*
AU  - Damotte, V.*
AU  - Fontaine, B.*
AU  - Breban, M.*
AU  - Gieger, C.
AU  - Klopp, N.
AU  - Deloukas, P.*
AU  - Wijmenga, C.*
AU  - Hallmayer, J.*
AU  - Onengut-Gumuscu, S.*
AU  - Rich, S.S.*
AU  - Winkelmann, J.
AU  - Mignot, E.*
C1  - 23655
C2  - 31243
TI  - ImmunoChip study implicates antigen presentation to T cells in narcolepsy.
JO  - PLoS Genet.
VL  - 9
IS  - 2
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1)), and its ratio to forced vital capacity (FEV(1)/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV(1) and FEV(1)/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = )5.00×10(-11)), HLA-DQB1 and HLA-DQA2 (smallest P(JMA = )4.35×10(-9)), and KCNJ2 and SOX9 (smallest P(JMA = )1.28×10(-8)) were associated with FEV(1)/FVC or FEV(1) in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.
AU  - Hancock, D.B.*
AU  - Artigas, M.S.*
AU  - Gharib, S.A.*
AU  - Henry, A.*
AU  - Manichaikul, A.*
AU  - Ramasamy, A.*
AU  - Loth, D.W.*
AU  - Imboden, M.*
AU  - Koch, B.*
AU  - McArdle, W.L.*
AU  - Smith, A.V.*
AU  - Smolonska, J.*
AU  - Sood, A.*
AU  - Tang, W.*
AU  - Wilk, J.B.*
AU  - Zhai, G.*
AU  - Zhao, J.H.*
AU  - Aschard, H.*
AU  - Burkart, K.M.*
AU  - Curjuric, I.*
AU  - Eijgelsheim, M.*
AU  - Elliott, P.*
AU  - Gu, X.*
AU  - Harris, T.B.*
AU  - Janson, C.*
AU  - Homuth, G.*
AU  - Hysi, P.G.*
AU  - Liu, J.Z.*
AU  - Loehr, L.R.*
AU  - Lohman, K.*
AU  - Loos, R.J.*
AU  - Manning, A.K.*
AU  - Marciante, K.D.*
AU  - Obeidat, M.*
AU  - Postma, D.S.*
AU  - Aldrich, M.C.*
AU  - Brusselle, G.G.*
AU  - Chen, T.H.*
AU  - Eiriksdottir, G.*
AU  - Franceschini, N.*
AU  - Heinrich, J.
AU  - Rotter, J.I.*
AU  - Wijmenga, C.*
AU  - Williams, O.D.*
AU  - Bentley, A.R.*
AU  - Hofman, A.*
AU  - Laurie, C.C.*
AU  - Lumley, T.*
AU  - Morrison, A.C.*
AU  - Joubert, B.R.*
AU  - Rivadeneira, F.*
AU  - Couper, D.J.*
AU  - Kritchevsky, S.B.*
AU  - Liu, Y.*
AU  - Wjst, M.
AU  - Wain, L.V.*
AU  - Vonk, J.M.*
AU  - Uitterlinden, A.G.*
AU  - Rochat, T.*
AU  - Rich, S.S.*
AU  - Psaty, B.M.*
AU  - O'Connor, G.T.*
AU  - North, K.E.*
AU  - Mirel, D.B.*
AU  - Meibohm, B.*
AU  - Launer, L.J.*
AU  - Khaw, K.T.*
AU  - Hartikainen, A.L.*
AU  - Hammond, C.J.*
AU  - Gläser, S.*
AU  - Marchini, J.*
AU  - Kraft, P.*
AU  - Wareham, N.J.*
AU  - Völzke, H.*
AU  - Stricker, B.H.*
AU  - Spector, T.D.*
AU  - Probst-Hensch, N.M.*
AU  - Jarvis, D.*
AU  - Jarvelin, M.R.*
AU  - Heckbert, S.R.*
AU  - Gudnason, V.*
AU  - Boezen, H.M.*
AU  - Barr, R.G.*
AU  - Cassano, P.A.*
AU  - Strachan, D.P.*
AU  - Fornage, M.*
AU  - Hall, I.P.*
AU  - Dupuis, J.*
AU  - Tobin, M.D.*
AU  - London, S.J.*
C1  - 11841
C2  - 30828
TI  - Genome-wide joint meta-analysis of SNP and SNP-by-smoking interaction identifies novel loci for pulmonary function.
JO  - PLoS Genet.
VL  - 8
IS  - 12
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The second messengers cAMP and cGMP activate their target proteins by binding to a conserved cyclic nucleotide-binding domain (CNBD). Here, we identify and characterize an entirely novel CNBD-containing protein called CRIS (cyclic nucleotide receptor involved in sperm function) that is unrelated to any of the other members of this protein family. CRIS is exclusively expressed in sperm precursor cells. Cris-deficient male mice are either infertile due to a lack of sperm resulting from spermatogenic arrest, or subfertile due to impaired sperm motility. The motility defect is caused by altered Ca(2+) regulation of flagellar beat asymmetry, leading to a beating pattern that is reminiscent of sperm hyperactivation. Our results suggest that CRIS interacts during spermiogenesis with Ca(2+)-regulated proteins that-in mature sperm-are involved in flagellar bending.
AU  - Krähling, A.M.*
AU  - Alvarez, L.*
AU  - Debowski, K.*
AU  - Van, Q.*
AU  - Gunkel, M.*
AU  - Irsen, S.*
AU  - Al-Amoudi, A.*
AU  - Strünker, T.*
AU  - Kremmer, E.
AU  - Krause, E.*
AU  - Voigt, I.*
AU  - Wörtge, S.*
AU  - Waisman, A.*
AU  - Weyand, I.*
AU  - Seifert, R.*
AU  - Kaupp, U.B.*
AU  - Wachten, D.*
C1  - 28882
C2  - 33561
CY  - San Francisco
TI  - CRIS - a novel cAMP-binding protein controlling spermiogenesis and the development of flagellar bending.
JO  - PLoS Genet.
VL  - 9
IS  - 12
PB  - Public Library Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies (GWAS) are a laborious but powerful tool to identify genetic risk factors associated with complex polygenic traits such as obesity [1], diabetes [2], or coronary artery disease [3]. The link between genetic variation in FTO and obesity was first described in a GWAS for type 2 diabetes [1] and was later independently confirmed in different populations all over the world. First described in 2007, genetic variation in FTO has since become one of the most solidly confirmed risk factor for polygenic obesity in humans; yet, information about how FTO affects metabolism is still scarce. Bioinformatic analyses suggest FTO codes for a Fe(II)- and 2-oxoglutarate–dependent nucleic acid demethylase [4], [5] that catalyzes demethylation of 3-methylthymine in single-stranded DNA [5]. However, how this proposed function of FTO is integrated into the complex network of energy metabolism control remains the object of intense scientific investigation.
AU  - Müller, T.D.
AU  - Tschöp, M.H.
AU  - Hofmann, S.M.
C1  - 11671
C2  - 30742
TI  - Emerging function of fat mass and obesity-associated protein (FTO).
JO  - PLoS Genet.
VL  - 9
IS  - 1
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Calcium is vital to the normal functioning of multiple organ systems and its serum concentration is tightly regulated. Apart from CASR, the genes associated with serum calcium are largely unknown. We conducted a genome-wide association meta-analysis of 39,400 individuals from 17 population-based cohorts and investigated the 14 most strongly associated loci in ≤21,679 additional individuals. Seven loci (six new regions) in association with serum calcium were identified and replicated. Rs1570669 near CYP24A1 (P = 9.1E-12), rs10491003 upstream of GATA3 (P = 4.8E-09) and rs7481584 in CARS (P = 1.2E-10) implicate regions involved in Mendelian calcemic disorders: Rs1550532 in DGKD (P = 8.2E-11), also associated with bone density, and rs7336933 near DGKH/KIAA0564 (P = 9.1E-10) are near genes that encode distinct isoforms of diacylglycerol kinase. Rs780094 is in GCKR. We characterized the expression of these genes in gut, kidney, and bone, and demonstrate modulation of gene expression in bone in response to dietary calcium in mice. Our results shed new light on the genetics of calcium homeostasis.
AU  - O'Seaghdha, C.M.*
AU  - Wu, H.*
AU  - Yang, Q.*
AU  - Kapur, K.*
AU  - Guessous, I.*
AU  - Zuber, A.M.*
AU  - Köttgen, A.*
AU  - Stoudmann, C.*
AU  - Teumer, A.*
AU  - Kutalik, Z.*
AU  - Mangino, M.*
AU  - Dehghan, A.*
AU  - Zhang, W.*
AU  - Eiriksdottir, G.*
AU  - Li, G.*
AU  - Tanaka, T.*
AU  - Portas, L.*
AU  - Lopez, L.M.*
AU  - Hayward, C.*
AU  - Lohman, K.*
AU  - Matsuda, K.*
AU  - Padmanabhan, S.*
AU  - Firsov, D.*
AU  - Sorice, R.*
AU  - Ulivi, S.*
AU  - Brockhaus, A.C.
AU  - Kleber, M.E.*
AU  - Mahajan, A.*
AU  - Ernst, F.D.*
AU  - Gudnason, V.*
AU  - Launer, L.J.*
AU  - Mace, A.*
AU  - Boerwinckle, E.*
AU  - Arking, D.E.*
AU  - Tanikawa, C.*
AU  - Nakamura, Y.*
AU  - Brown, M.J.*
AU  - Gaspoz, J.M.*
AU  - Theler, J.M.*
AU  - Siscovick, D.S.*
AU  - Psaty, B.M.*
AU  - Bergmann, S.*
AU  - Vollenweider, P.*
AU  - Vitart, V.*
AU  - Wright, A.F.*
AU  - Zemunik, T.*
AU  - Boban, M.*
AU  - Kolcic, I.*
AU  - Navarro, P.*
AU  - Brown, E.M.*
AU  - Estrada, K.*
AU  - Ding, J.*
AU  - Harris, T.B.*
AU  - Bandinelli, S.*
AU  - Hernandez, D.*
AU  - Singleton, A.B.*
AU  - Girotto, G.*
AU  - Ruggiero, D.*
AU  - d'Adamo, A.P.*
AU  - Robino, A.*
AU  - Meitinger, T.
AU  - Meisinger, C.
AU  - Davies, G.*
AU  - Starr, J.M.*
AU  - Chambers, J.C.*
AU  - Boehm, B.O.*
AU  - Winkelmann, B.R.*
AU  - Huang, J.*
AU  - Murgia, F.*
AU  - Wild, S.H.*
AU  - Campbell, H.*
AU  - Morris, A.P.*
AU  - Franco, O.H.*
AU  - Hofman, A.*
AU  - Uitterlinden, A.G.*
AU  - Rivadeneira, F.*
AU  - Völker, U.*
AU  - Hannemann, A.*
AU  - Biffar, R.*
AU  - Hoffmann, W.*
AU  - Shin, S.Y.*
AU  - Lescuyer, P.*
AU  - Henry, H.*
AU  - Schurmann, C.*
AU  - SUNLIGHT Consortium (*)
AU  - GEFOS Consortium (*)
AU  - Munroe, P.B.*
AU  - Gasparini, P.*
AU  - Pirastu, N.*
AU  - Ciullo, M.*
AU  - Gieger, C.
AU  - Marz, W.*
AU  - Lind, L.*
AU  - Spector, T.D.*
AU  - Smith, A.V.*
AU  - Rudan, I.*
AU  - Wilson, J.F.*
AU  - Polasek, O.*
AU  - Deary, I.J.*
AU  - Pirastu, M.*
AU  - Ferrucci, L.*
AU  - Liu, Y.*
AU  - Kestenbaum, B.*
AU  - Kooner, J.S.*
AU  - Witteman, J.C.*
AU  - Nauck, M.*
AU  - Kao, W.H.*
AU  - Wallaschofski, H.*
AU  - Bonny, O.*
AU  - Fox, C.S.*
AU  - Bochud, M.*
C1  - 27835
C2  - 32834
TI  - Meta-analysis of genome-wide association studies identifies six new Loci for serum calcium concentrations.
JO  - PLoS Genet.
VL  - 9
IS  - 9
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The CDKN1B gene encodes the cyclin-dependent kinase inhibitor p27(KIP1), an atypical tumor suppressor playing a key role in cell cycle regulation, cell proliferation, and differentiation. Impaired p27(KIP1) expression and/or localization are often observed in tumor cells, further confirming its central role in regulating the cell cycle. Recently, germline mutations in CDKN1B have been associated with the inherited multiple endocrine neoplasia syndrome type 4, an autosomal dominant syndrome characterized by varying combinations of tumors affecting at least two endocrine organs. In this study we identified a 4-bp deletion in a highly conserved regulatory upstream ORF (uORF) in the 5'UTR of the CDKN1B gene in a patient with a pituitary adenoma and a well-differentiated pancreatic neoplasm. This deletion causes the shift of the uORF termination codon with the consequent lengthening of the uORF-encoded peptide and the drastic shortening of the intercistronic space. Our data on the immunohistochemical analysis of the patient's pancreatic lesion, functional studies based on dual-luciferase assays, site-directed mutagenesis, and on polysome profiling show a negative influence of this deletion on the translation reinitiation at the CDKN1B starting site, with a consequent reduction in p27(KIP1) expression. Our findings demonstrate that, in addition to the previously described mechanisms leading to reduced p27(KIP1) activity, such as degradation via the ubiquitin/proteasome pathway or non-covalent sequestration, p27(KIP1) activity can also be modulated by an uORF and mutations affecting uORF could change p27(KIP1) expression. This study adds the CDKN1B gene to the short list of genes for which mutations that either create, delete, or severely modify their regulatory uORFs have been associated with human diseases.
AU  - Occhi, G.*
AU  - Regazzo, D.*
AU  - Trivellin, G.*
AU  - Boaretto, F.*
AU  - Ciato, D.*
AU  - Bobisse, S.*
AU  - Ferasin, S.*
AU  - Cetani, F.*
AU  - Pardi, E.*
AU  - Korbonits, M.*
AU  - Pellegata, N.S.
AU  - Sidarovich, V.*
AU  - Quattrone, A.*
AU  - Opocher, G.*
AU  - Mantero, F.*
AU  - Scaroni, C.*
C1  - 23723
C2  - 31257
TI  - A novel mutation in the upstream open reading frame of the CDKN1B gene causes a MEN4 phenotype.
JO  - PLoS Genet.
VL  - 9
IS  - 3
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
AU  - Randall, J.C.*
AU  - Winkler, T.W.*
AU  - Kutalik, Z.*
AU  - Berndt, S.I.*
AU  - Jackson, A.U.*
AU  - Monda, K.L.*
AU  - Kilpeläinen, T.O.*
AU  - Esko, T.*
AU  - Mägi, R.*
AU  - Li, S.*
AU  - Workalemahu, T.*
AU  - Feitosa, M.F.*
AU  - Croteau-Chonka, D.C.*
AU  - Day, F.R.*
AU  - Fall, T.*
AU  - Ferreira, T.*
AU  - Gustafsson, S.*
AU  - Locke, A.E.*
AU  - Mathieson, I.*
AU  - Scherag, A.*
AU  - Vedantam, S.*
AU  - Wood, A.R.*
AU  - Liang, L.*
AU  - Steinthorsdottir, V.*
AU  - Thorleifsson, G.*
AU  - Dermitzakis, E.T.*
AU  - Dimas, A.S.*
AU  - Karpe, F.*
AU  - Min, J.L.*
AU  - Nicholson, G.*
AU  - Clegg, D.J.*
AU  - Person, T.*
AU  - Krohn, J.P.*
AU  - Bauer, S.*
AU  - Buechler, C.*
AU  - Eisinger, K.*
AU  - DIAGRAM Consortium (Grallert, H.
AU  - Thorand, B.
AU  - Klopp, N.
AU  - Petersen, A.-K.
AU  - Huth, C.
AU  - Gieger, C.
AU  - Illig, T.
AU  - Wichmann, H.-E.
AU  - Meitinger, T.)
AU  - Bonnefond, A.*
AU  - Froguel, P.*
AU  - MAGIC Investigators (Illig, T.
AU  - Grallert, H.
AU  - Thorand, B.
AU  - Wichmann, H.-E.
AU  - Gieger, C.
AU  - Meisinger, C.)
AU  - Hottenga, J.J.*
AU  - Prokopenko, I.*
AU  - Waite, L.L.*
AU  - Harris, T.B.*
AU  - Smith, A.V.*
AU  - Shuldiner, A.R.*
AU  - McArdle, W.L.*
AU  - Caulfield, M.J.*
AU  - Munroe, P.B.*
AU  - Grönberg, H.*
AU  - Chen, Y.D.*
AU  - Li, G.*
AU  - Beckmann, J.S.*
AU  - Johnson, T.*
AU  - Thorsteinsdottir, U.*
AU  - Teder-Laving, M.*
AU  - Khaw, K.T.*
AU  - Wareham, N.J.*
AU  - Zhao, J.H.*
AU  - Amin, N.*
AU  - Oostra, B.A.*
AU  - Kraja, A.T.*
AU  - Province, M.A.*
AU  - Cupples, L.A.*
AU  - Heard-Costa, N.L.*
AU  - Kaprio, J.*
AU  - Ripatti, S.*
AU  - Surakka, I.*
AU  - Collins, F.S.*
AU  - Saramies, J.*
AU  - Tuomilehto, J.*
AU  - Jula, A.*
AU  - Salomaa, V.*
AU  - Erdmann, J.*
AU  - Hengstenberg, C.*
AU  - Loley, C.*
AU  - Schunkert, H.*
AU  - Lamina, C.*
AU  - Wichmann, H.-E.
AU  - Albrecht, E.
AU  - Gieger, C.
AU  - Hicks, A.A.*
AU  - Johansson, A.*
AU  - Pramstaller, P.P.*
AU  - Kathiresan, S.*
AU  - Speliotes, E.K.*
AU  - Penninx, B.*
AU  - Hartikainen, A.L.*
AU  - Jarvelin, M.R.*
AU  - Gyllensten, U.*
AU  - Boomsma, D.I.*
AU  - Campbell, H.*
AU  - Wilson, J.F.*
AU  - Chanock, S.J.*
AU  - Farrall, M.*
AU  - Goel, A.*
AU  - Medina-Gomez, C.*
AU  - Rivadeneira, F.*
AU  - Estrada, K.*
AU  - Uitterlinden, A.G.*
AU  - Hofman, A.*
AU  - Zillikens, M.C.*
AU  - den Heijer, M.*
AU  - Kiemeney, L.A.*
AU  - Maschio, A.*
AU  - Hall, P.*
AU  - Tyrer, J.*
AU  - Teumer, A.*
AU  - Völzke, H.*
AU  - Kovacs, P.*
AU  - Tönjes, A.*
AU  - Mangino, M.*
AU  - Spector, T.D.*
AU  - Hayward, C.*
AU  - Rudan, I.*
AU  - Hall, A.S.*
AU  - Samani, N.J.*
AU  - Attwood, A.P.*
AU  - Sambrook, J.G.*
AU  - Hung, J.*
AU  - Palmer, L.J.*
AU  - Lokki, M.L.*
AU  - Sinisalo, J.*
AU  - Boucher, G.*
AU  - Huikuri, H.*
AU  - Lorentzon, M.*
AU  - Ohlsson, C.*
AU  - Eklund, N.*
AU  - Eriksson, J.G.*
AU  - Barlassina, C.*
AU  - Rivolta, C.*
AU  - Nolte, I.M.*
AU  - Snieder, H.*
AU  - van der Klauw, M.M.*
AU  - van Vliet-Ostaptchouk, J.V.*
AU  - Gejman, P.V.*
AU  - Shi, J.*
AU  - Jacobs, K.B.*
AU  - Wang, Z.*
AU  - Bakker, S.J.*
AU  - Mateo Leach, I.*
AU  - Navis, G.*
AU  - van der Harst, P.*
AU  - Martin, N.G.*
AU  - Medland, S.E.*
AU  - Montgomery, G.W.*
AU  - Yang, J.*
AU  - Chasman, D.I.*
AU  - Ridker, P.M.*
AU  - Rose, L.M.*
AU  - Lehtimäki, T.*
AU  - Raitakari, O.*
AU  - Absher, D.*
AU  - Iribarren, C.*
AU  - Basart, H.*
AU  - Hovingh, K.G.*
AU  - Hyppönen, E.*
AU  - Power, C.*
AU  - Anderson, D.*
AU  - Beilby, J.P.*
AU  - Hui, J.*
AU  - Jolley, J.*
AU  - Sager, H.*
AU  - Bornstein, S.R.*
AU  - Schwarz, P.E.*
AU  - Kristiansson, K.*
AU  - Perola, M.*
AU  - Lindstrom, J.*
AU  - Swift, A.J.*
AU  - Uusitupa, M.*
AU  - Atalay, M.*
AU  - Lakka, T.A.*
AU  - Rauramaa, R.*
AU  - Bolton, J.L.*
AU  - Fowkes, G.*
AU  - Fraser, R.M.*
AU  - Price, J.F.*
AU  - Fischer, K.*
AU  - Krjutå Kov, K.*
AU  - Metspalu, A.*
AU  - Mihailov, E.*
AU  - Langenberg, C.*
AU  - Luan, J.*
AU  - Ong, K.K.*
AU  - Chines, P.S.*
AU  - Keinanen-Kiukaanniemi, S.M.*
AU  - Saaristo, T.E.*
AU  - Edkins, S.*
AU  - Franks, P.W.*
AU  - Hallmans, G.*
AU  - Shungin, D.*
AU  - Morris, A.D.*
AU  - Palmer, C.N.*
AU  - Erbel, R.*
AU  - Moebus, S.*
AU  - Nöthen, M.M.*
AU  - Pechlivanis, S.*
AU  - Hveem, K.*
AU  - Narisu, N.*
AU  - Hamsten, A.*
AU  - Humphries, S.E.*
AU  - Strawbridge, R.J.*
AU  - Tremoli, E.*
AU  - Grallert, H.
AU  - Thorand, B.
AU  - Illig, T.
AU  - Koenig, W.*
AU  - Müller-Nurasyid, M.
AU  - Peters, A.
AU  - Boehm, B.O.*
AU  - Kleber, M.E.*
AU  - Marz, W.*
AU  - Winkelmann, B.R.*
AU  - Kuusisto, J.*
AU  - Laakso, M.*
AU  - Arveiler, D.*
AU  - Cesana, G.*
AU  - Kuulasmaa, K.*
AU  - Virtamo, J.*
AU  - Yarnell, J.W.*
AU  - Kuh, D.*
AU  - Wong, A.*
AU  - Lind, L.*
AU  - de Faire, U.*
AU  - Gigante, B.*
AU  - Magnusson, P.K.*
AU  - Pedersen, N.L.*
AU  - Dedoussis, G.*
AU  - Dimitriou, M.*
AU  - Kolovou, G.*
AU  - Kanoni, S.*
AU  - Stirrups, K.*
AU  - Bonnycastle, L.L.*
AU  - Njølstad, I.*
AU  - Wilsgaard, T.*
AU  - Ganna, A.*
AU  - Rehnberg, E.*
AU  - Hingorani, A.*
AU  - Kivimaki, M.*
AU  - Kumari, M.*
AU  - Assimes, T.L.*
AU  - Barroso, I.*
AU  - Boehnke, M.*
AU  - Borecki, I.B.*
AU  - Deloukas, P.*
AU  - Fox, C.S.*
AU  - Frayling, T.*
AU  - Groop, L.C.*
AU  - Haritunians, T.*
AU  - Hunter, D.*
AU  - Ingelsson, E.*
AU  - Kaplan, R.*
AU  - Mohlke, K.L.*
AU  - O'Connell, J.R.*
AU  - Schlessinger, D.*
AU  - Strachan, D.P.*
AU  - Stefansson, K.*
AU  - van Duijn, C.M.*
AU  - Abecasis, G.R.*
AU  - McCarthy, M.I.*
AU  - Hirschhorn, J.N.*
AU  - Qi, L.*
AU  - Loos, R.J.*
AU  - Lindgren, C.M.*
AU  - North, K.E.*
AU  - Heid, I.M.
C1  - 25486
C2  - 31859
TI  - Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits.
JO  - PLoS Genet.
VL  - 9
IS  - 6
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The fungal family Clavicipitaceae includes plant symbionts and parasites that produce several psychoactive and bioprotective alkaloids. The family includes grass symbionts in the epichloae clade ( and species), which are extraordinarily diverse both in their host interactions and in their alkaloid profiles. Epichloae produce alkaloids of four distinct classes, all of which deter insects, and some-including the infamous ergot alkaloids-have potent effects on mammals. The exceptional chemotypic diversity of the epichloae may relate to their broad range of host interactions, whereby some are pathogenic and contagious, others are mutualistic and vertically transmitted (seed-borne), and still others vary in pathogenic or mutualistic behavior. We profiled the alkaloids and sequenced the genomes of 10 epichloae, three ergot fungi ( species), a morning-glory symbiont (), and a bamboo pathogen (), and compared the gene clusters for four classes of alkaloids. Results indicated a strong tendency for alkaloid loci to have conserved cores that specify the skeleton structures and peripheral genes that determine chemical variations that are known to affect their pharmacological specificities. Generally, gene locations in cluster peripheries positioned them near to transposon-derived, AT-rich repeat blocks, which were probably involved in gene losses, duplications, and neofunctionalizations. The alkaloid loci in the epichloae had unusual structures riddled with large, complex, and dynamic repeat blocks. This feature was not reflective of overall differences in repeat contents in the genomes, nor was it characteristic of most other specialized metabolism loci. The organization and dynamics of alkaloid loci and abundant repeat blocks in the epichloae suggested that these fungi are under selection for alkaloid diversification. We suggest that such selection is related to the variable life histories of the epichloae, their protective roles as symbionts, and their associations with the highly speciose and ecologically diverse cool-season grasses.
AU  - Schardl, C.L.*
AU  - Young, C.A.*
AU  - Hesse, U.*
AU  - Amyotte, S.G.*
AU  - Andreeva, K.*
AU  - Calie, P.J.*
AU  - Fleetwood, D.J.*
AU  - Haws, D.C.*
AU  - Moore, N.*
AU  - Oeser, B.*
AU  - Panaccione, D.G.*
AU  - Schweri, K.K.*
AU  - Voisey, C.R.*
AU  - Farman, M.L.*
AU  - Jaromczyk, J.W.*
AU  - Roe, B.A.
AU  - O'Sullivan, D.M.*
AU  - Scott, B.*
AU  - Tudzynski, P.*
AU  - An, Z.*
AU  - Arnaoudova, E.G.*
AU  - Bullock, C.T.*
AU  - Charlton, N.D.*
AU  - Chen, L.*
AU  - Cox, M.*
AU  - Dinkins, R.D.*
AU  - Florea, S.*
AU  - Glenn, A.E.*
AU  - Gordon, A.*
AU  - Güldener, U.
AU  - Harris, D.R.*
AU  - Hollin, W.*
AU  - Jaromczyk, J.*
AU  - Johnson, R.D.*
AU  - Khan, A.K.*
AU  - Leistner, E.*
AU  - Leuchtmann, A.*
AU  - Li, C.*
AU  - Liu, J.*
AU  - Liu, M.*
AU  - Mace, W.*
AU  - Machado, C.*
AU  - Nagabhyru, P.*
AU  - Pan, J.*
AU  - Schmid, J.*
AU  - Sugawara, K.*
AU  - Steiner, U.*
AU  - Takach, J.E.*
AU  - Tanaka, E.*
AU  - Webb, J.S.*
AU  - Wilson, E.V.*
AU  - Wiseman, J.L.*
AU  - Yoshida, R.*
AU  - Zeng, Z.*
C1  - 23485
C2  - 31201
TI  - Plant-symbiotic fungi as chemical engineers: Multi-genome analysis of the clavicipitaceae reveals dynamics of alkaloid loci.
JO  - PLoS Genet.
VL  - 9
IS  - 2
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Several infrequent genetic polymorphisms in the SERPINA1 gene are known to substantially reduce concentration of alpha1-antitrypsin (AAT) in the blood. Since low AAT serum levels fail to protect pulmonary tissue from enzymatic degradation, these polymorphisms also increase the risk for early onset chronic obstructive pulmonary disease (COPD). The role of more common SERPINA1 single nucleotide polymorphisms (SNPs) in respiratory health remains poorly understood. We present here an agnostic investigation of genetic determinants of circulating AAT levels in a general population sample by performing a genome-wide association study (GWAS) in 1392 individuals of the SAPALDIA cohort. Five common SNPs, defined by showing minor allele frequencies (MAFs) >5%, reached genome-wide significance, all located in the SERPINA gene cluster at 14q32.13. The top-ranking genotyped SNP rs4905179 was associated with an estimated effect of β = -0.068 g/L per minor allele (P = 1.20*10(-12)). But denser SERPINA1 locus genotyping in 5569 participants with subsequent stepwise conditional analysis, as well as exon-sequencing in a subsample (N = 410), suggested that AAT serum level is causally determined at this locus by rare (MAF<1%) and low-frequent (MAF 1-5%) variants only, in particular by the well-documented protein inhibitor S and Z (PI S, PI Z) variants. Replication of the association of rs4905179 with AAT serum levels in the Copenhagen City Heart Study (N = 8273) was successful (P<0.0001), as was the replication of its synthetic nature (the effect disappeared after adjusting for PI S and Z, P = 0.57). Extending the analysis to lung function revealed a more complex situation. Only in individuals with severely compromised pulmonary health (N = 397), associations of common SNPs at this locus with lung function were driven by rarer PI S or Z variants. Overall, our meta-analysis of lung function in ever-smokers does not support a functional role of common SNPs in the SERPINA gene cluster in the general population.
AU  - Thun, G.A.*
AU  - Imboden, M.*
AU  - Ferrarotti, I.*
AU  - Kumar, A.*
AU  - Obeidat, M.*
AU  - Zorzetto, M.*
AU  - Haun, M.*
AU  - Curjuric, I.*
AU  - Couto Alves, A.*
AU  - Jackson, V.E.*
AU  - Albrecht, E.
AU  - Ried, J.S.
AU  - Teumer, A.*
AU  - Lopez, L.M.*
AU  - Huffman, J.E.*
AU  - Enroth, S.*
AU  - Bossé, Y.*
AU  - Hao, K.*
AU  - Timens, W.*
AU  - Gyllensten, U.*
AU  - Polasek, O.*
AU  - Wilson, J.F.*
AU  - Rudan, I.*
AU  - Hayward, C.*
AU  - Sandford, A.J.*
AU  - Deary, I.J.*
AU  - Koch, B.*
AU  - Reischl, E.
AU  - Schulz, H.
AU  - Hui, J.*
AU  - James, A.L.*
AU  - Rochat, T.*
AU  - Russi, E.W.*
AU  - Jarvelin, M.R.*
AU  - Strachan, D.P.*
AU  - Hall, I.P.*
AU  - Tobin, M.D.*
AU  - Dahl, M.*
AU  - Fallgaard Nielsen, S.*
AU  - Nørdestgaard, B.G.*
AU  - Kronenberg, F.*
AU  - Luisetti, M.*
AU  - Probst-Hensch, N.M.*
C1  - 27491
C2  - 32696
TI  - Causal and synthetic associations of variants in the SERPINA gene cluster with alpha1-antitrypsin serum levels.
JO  - PLoS Genet.
VL  - 9
IS  - 8
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Regulation of mitochondrial DNA (mtDNA) expression is critical for the control of oxidative phosphorylation in response to physiological demand, and this regulation is often impaired in disease and aging. We have previously shown that mitochondrial transcription termination factor 3 (MTERF3) is a key regulator that represses mtDNA transcription in the mouse, but its molecular mode of action has remained elusive. Based on the hypothesis that key regulatory mechanisms for mtDNA expression are conserved in metazoans, we analyzed Mterf3 knockout and knockdown flies. We demonstrate here that decreased expression of MTERF3 not only leads to activation of mtDNA transcription, but also impairs assembly of the large mitochondrial ribosomal subunit. This novel function of MTERF3 in mitochondrial ribosomal biogenesis is conserved in the mouse, thus we identify a novel and unexpected role for MTERF3 in coordinating the crosstalk between transcription and translation for the regulation of mammalian mtDNA gene expression.
AU  - Wredenberg, A.*
AU  - Lagouge, M.*
AU  - Bratic, A.*
AU  - Metodiev, M.D.*
AU  - Spåhr, H.*
AU  - Mourier, A.*
AU  - Freyer, C.*
AU  - Ruzzenente, B.*
AU  - Tain, L.*
AU  - Grönke, S.*
AU  - Baggio, F.*
AU  - Kukat, C.*
AU  - Kremmer, E.
AU  - Wibom, R.*
AU  - Polosa, P.L.*
AU  - Habermann, B.*
AU  - Partridge, L.*
AU  - Park, C.B.*
AU  - Larsson, N.G.*
C1  - 26260
C2  - 32149
TI  - MTERF3 regulates mitochondrial ribosome biogenesis in invertebrates and mammals.
JO  - PLoS Genet.
VL  - 9
IS  - 1
PB  - Public Library of Science
PY  - 2013
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4×10(-11)), GCKR (rs780093, 2p23.3, p = 2.2×10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4×10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1×10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3×10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5×10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1×10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3×10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
AU  - Coviello, A.D.*
AU  - Haring, R.*
AU  - Wellons, M.*
AU  - Vaidya, D.*
AU  - Lehtimäki, T.*
AU  - Keildson, S.*
AU  - Lunetta, K.L.*
AU  - He, C.*
AU  - Fornage, M.*
AU  - Lagou, V.*
AU  - Mangino, M.*
AU  - Onland-Moret, N.C.*
AU  - Chen, B.*
AU  - Eriksson, J.*
AU  - Garcia, M.*
AU  - Liu, Y.M.*
AU  - Koster, A.*
AU  - Lohman, K.*
AU  - Lyytikäinen, L.-P.*
AU  - Petersen, A.-K.
AU  - Prescott, J.*
AU  - Stolk, L.*
AU  - Vandenput, L.*
AU  - Wood, A.R.*
AU  - Zhuang, W.V.*
AU  - Ruokonen, A.*
AU  - Hartikainen, A.L.*
AU  - Pouta, A.*
AU  - Bandinelli, S.*
AU  - Biffar, R.*
AU  - Brabant, G.*
AU  - Cox, D.G.*
AU  - Chen, Y.*
AU  - Cummings, S.*
AU  - Ferrucci, L.*
AU  - Gunter, M.J.*
AU  - Hankinson, S.E.*
AU  - Martikainen, H.*
AU  - Hofman, A.*
AU  - Homuth, G.*
AU  - Illig, T.
AU  - Jansson, J.O.*
AU  - Johnson, A.D.*
AU  - Karasik, D.*
AU  - Karlsson, M.*
AU  - Kettunen, J.*
AU  - Kiel, D.P.*
AU  - Kraft, P.*
AU  - Liu, J.*
AU  - Ljunggren, O.*
AU  - Lorentzon, M.*
AU  - Maggio, M.*
AU  - Markus, M.R.*
AU  - Mellström, D.*
AU  - Miljkovic, I.*
AU  - Mirel, D.*
AU  - Nelson, S.*
AU  - Morin Papunen, L.*
AU  - Peeters, P.H.*
AU  - Prokopenko, I.*
AU  - Raffel, L.*
AU  - Reincke, M.*
AU  - Reiner, A.P.*
AU  - Rexrode, K.*
AU  - Rivadeneira, F.*
AU  - Schwartz, S.M.*
AU  - Siscovick, D.*
AU  - Soranzo, N.*
AU  - Stöckl, D.
AU  - Tworoger, S.*
AU  - Uitterlinden, A.G.*
AU  - van Gils, C.H.*
AU  - Vasan, R.S.*
AU  - Wichmann, H.-E.
AU  - Zhai, G.*
AU  - Bhasin, S.*
AU  - Bidlingmaier, M.*
AU  - Chanock, S.J.*
AU  - de Vivo, I.*
AU  - Harris, T.B.*
AU  - Hunter, D.J.*
AU  - Kähönen, M.*
AU  - Liu, S.*
AU  - Ouyang, P.*
AU  - Spector, T.D.*
AU  - van der Schouw, Y.T.*
AU  - Viikari, J.*
AU  - Wallaschofski, H.*
AU  - McCarthy, M.I.*
AU  - Frayling, T.M.*
AU  - Murray, A.*
AU  - Franks, S.*
AU  - Jarvelin, M.R.*
AU  - de Jong, F.H.*
AU  - Raitakari, O.*
AU  - Teumer, A.*
AU  - Ohlsson, C.*
AU  - Murabito, J.M.*
AU  - Perry, J.R.*
C1  - 8454
C2  - 30118
TI  - A genome-wide association meta-analysis of circulating sex hormone-binding globulin reveals multiple loci implicated in sex steroid hormone regulation.
JO  - PLoS Genet.
VL  - 8
IS  - 7
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
AU  - Dastani, Z.*
AU  - Hivert, M.F.*
AU  - Timpson, N.*
AU  - Perry, J.R.*
AU  - Yuan, X.*
AU  - Scott, R.A.*
AU  - Henneman, P.*
AU  - Heid, I.M.*
AU  - Kizer, J.R.*
AU  - Lyytikäinen, L.-P.*
AU  - Fuchsberger, C.*
AU  - Tanaka, T.*
AU  - Morris, A.P.*
AU  - Small, K.*
AU  - Isaacs, A.*
AU  - Beekman, M.*
AU  - Coassin, S.*
AU  - Lohman, K.*
AU  - Qi, L.*
AU  - Kanoni, S.*
AU  - Pankow, J.S.*
AU  - Uh, H.W.*
AU  - Wu, Y.*
AU  - Bidulescu, A.*
AU  - Rasmussen-Torvik, L.J.*
AU  - Greenwood, C.M.*
AU  - Ladouceur, M.*
AU  - Grimsby, J.*
AU  - Manning, A.K.*
AU  - Liu, C.-T.*
AU  - Kooner, J.*
AU  - Mooser, V.E.*
AU  - Vollenweider, P.*
AU  - Kapur, K.A.*
AU  - Chambers, J.*
AU  - Wareham, N.J.*
AU  - Langenberg, C.*
AU  - Frants, R.*
AU  - Willems-Vandijk, K.*
AU  - Oostra, B.A.*
AU  - Willems, S.M.*
AU  - Lamina, C.*
AU  - Winkler, T.W.*
AU  - Psaty, B.M.*
AU  - Tracy, R.P.*
AU  - Brody, J.*
AU  - Chen, I.*
AU  - Viikari, J.*
AU  - Kähönen, M.*
AU  - Pramstaller, P.P.*
AU  - Evans, D.M*
AU  - St Pourcain, B.*
AU  - Sattar, N.*
AU  - Wood, A.R.*
AU  - Bandinelli, S.*
AU  - Carlson, O.D.*
AU  - Egan, J.M.*
AU  - Böhringer, S.*
AU  - van Heemst, D.*
AU  - Kedenko, L.*
AU  - Kristiansson, K.*
AU  - Nuotio, M.L.*
AU  - Loo, B.M.*
AU  - Harris, T.*
AU  - Garcia, M.*
AU  - Kanaya, A.*
AU  - Haun, M.*
AU  - Klopp, N.
AU  - Wichmann, H.-E.
AU  - Deloukas, P.*
AU  - Katsareli, E.*
AU  - Couper, D.J.*
AU  - Duncan, B.B.*
AU  - Kloppenburg, M.*
AU  - Adair, L.S.*
AU  - Borja, J.B.*
AU  - DIAGRAM Consortium (Klopp, N.
AU  - Gieger, C.
AU  - Grallert, H.
AU  - Illig, T.
AU  - Huth, C.
AU  - Meitinger, T.
AU  - Petersen, A.-K.
AU  - Wichmann, H.-E.
AU  - Thorand, B.)
AU  - MAGIC Investigators (Grallert, H.
AU  - Meisinger, C.
AU  - Thorand, B.
AU  - Wichmann, H.-E.
AU  - Illig, T.
AU  - Gieger, C.)
AU  - Global Lipids Genetics Consortium (*)
AU  - MuTHER Consortium (*)
AU  - Wilson, J.G.*
AU  - Musani, S.*
AU  - Guo, X.*
AU  - Johnson, T.*
AU  - Semple, R.*
AU  - Teslovich, T.M.*
AU  - Allison, M.A.*
AU  - Redline, S.*
AU  - Buxbaum, S.G.*
AU  - Mohlke, K.L.*
AU  - Meulenbelt, I.*
AU  - Ballantyne, C.M.*
AU  - Dedoussis, G.V.*
AU  - Hu, F.B.*
AU  - Liu, Y.*
AU  - Paulweber, B.*
AU  - Spector, T.D.*
AU  - Slagboom, P.E.*
AU  - Ferrucci, L.*
AU  - Jula, A.*
AU  - Perola, M.*
AU  - Raitakari, O.*
AU  - Florez, J.C*
AU  - Salomaa, V.*
AU  - Eriksson, J.G.*
AU  - Frayling, T.M.*
AU  - Hicks, A.A.*
AU  - Lehtimäki, T.*
AU  - Smith, G.D.*
AU  - Siscovick, D.S.*
AU  - Kronenberg, F.*
AU  - van Duijn, C.M.*
AU  - Loos, R.J.*
AU  - Waterworth, D.M.*
AU  - Meigs, J.B.*
AU  - Dupuis, J.*
AU  - Richards, J.B.*
C1  - 7513
C2  - 29789
TI  - Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: A multi-ethnic meta-analysis of 45,891 individuals.
JO  - PLoS Genet.
VL  - 8
IS  - 3
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10(-204)) and 10 loci for sphingolipids (smallest P-value = 3.10×10(-57)). After a correction for multiple comparisons (P-value<2.2×10(-9)), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits.
AU  - Demirkan, A.*
AU  - van Duijn, C.M.*
AU  - Ugocsai, P.*
AU  - Isaacs, A.*
AU  - Pramstaller, P.P.*
AU  - Liebisch, G.*
AU  - Wilson, J.F.*
AU  - Johansson, A.*
AU  - Rudan, I.*
AU  - Aulchenko, Y.S.*
AU  - Kirichenko, A.V.*
AU  - Janssens, A.C.*
AU  - Jansen, R.C.*
AU  - Gnewuch, C.*
AU  - Domingues, F.S.*
AU  - Pattaro, C.*
AU  - Wild, S.H.*
AU  - Jonasson, I.*
AU  - Polasek, O.*
AU  - Zorkoltseva, I.V.*
AU  - Hofman, A.*
AU  - Karssen, L.C.*
AU  - Struchalin, M.*
AU  - Floyd, J.*
AU  - Igl, W.*
AU  - Biloglav, Z.*
AU  - Broer, L.*
AU  - Pfeufer, A.*
AU  - Pichler, I.*
AU  - Campbell, S.*
AU  - Zaboli, G.*
AU  - Kolcic, I.*
AU  - Rivadeneira, F.*
AU  - Huffman, J.*
AU  - Hastie, N.D.*
AU  - Uitterlinden, A.*
AU  - Franke, L.*
AU  - Franklin, C.S.*
AU  - Vitart, V.*
AU  - DIAGRAM Consortium (Huth, C.
AU  - Gieger, C.
AU  - Klopp, N.
AU  - Petersen, A.-K.
AU  - Thorand, B.
AU  - Wichmann, H.-E.
AU  - Illig, T.)
AU  - Nelson, C.P.*
AU  - Preuss, M*
AU  - CARDIoGRAM Consortium (Döring, A.
AU  - Meisinger, C.
AU  - Peters, A.
AU  - Illig, T.
AU  - Meitinger, T.
AU  - Klopp, N.
AU  - Wichmann, H.-E.)
AU  - Bis, J.C.*
AU  - O'Donnell, C.J.*
AU  - Franceschini, N*
AU  - CHARGE Consortium (*)
AU  - Witteman, J.C.*
AU  - Axenovich, T.*
AU  - Oostra, B.A.*
AU  - Meitinger, T.
AU  - Hicks, A.A.*
AU  - Hayward, C.*
AU  - Wright, A.F.*
AU  - Gyllensten, U.*
AU  - Campbell, H.*
AU  - Schmitz, G*
C1  - 7269
C2  - 29629
TI  - Genome-wide association study identifies novel loci associated with circulating phospho- and sphingolipid concentrations.
JO  - PLoS Genet.
VL  - 8
IS  - 2
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots quantified using computed tomography (CT) to uncover novel loci for body fat distribution among participants of European ancestry. Subcutaneous and visceral fat were quantified in 5,560 women and 4,997 men from 4 population-based studies. Genome-wide genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), VAT adjusted for body mass index, and VAT/SAT ratio (a metric of the propensity to store fat viscerally as compared to subcutaneously) in the overall sample and in women and men separately. A weighted z-score meta-analysis was conducted. For the VAT/SAT ratio, our most significant p-value was rs11118316 at LYPLAL1 gene (p = 3.1 × 10E-09), previously identified in association with waist-hip ratio. For SAT, the most significant SNP was in the FTO gene (p = 5.9 × 10E-08). Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, rs1659258 near THNSL2 (p = 1.6 × 10-08), but not men (p = 0.75). Validation of this SNP in the GIANT consortium data demonstrated a similar sex-specific pattern, with observed significance in women (p = 0.006) but not men (p = 0.24) for BMI and waist circumference (p = 0.04 [women], p = 0.49 [men]). Finally, we interrogated our data for the 14 recently published loci for body fat distribution (measured by waist-hip ratio adjusted for BMI); associations were observed at 7 of these loci. In contrast, we observed associations at only 7/32 loci previously identified in association with BMI; the majority of overlap was observed with SAT. Genome-wide association for visceral and subcutaneous fat revealed a SNP for VAT in women. More refined phenotypes for body composition and fat distribution can detect new loci not previously uncovered in large-scale GWAS of anthropometric traits.
AU  - Fox, C.S.*
AU  - Liu, Y.*
AU  - White, C.C.*
AU  - Feitosa, M.*
AU  - Smith, A.V.*
AU  - Heard-Costa, N.*
AU  - Lohman, K.*
AU  - GIANT Consortium (Heid, I.M.
AU  - Heinrich, J.
AU  - Peters, A.
AU  - Gieger, C.
AU  - Illig, T.
AU  - Grallert, H.
AU  - Wichmann, H.-E.
AU  - Thiering, E.)
AU  - MAGIC Investigators (Grallert, H.
AU  - Gieger, C.
AU  - Meisinger, C.
AU  - Thorand, B.
AU  - Illig, T.
AU  - Wichmann, H.-E.)
AU  - Global Lipids Genetics Consortium (*)
AU  - Johnson, A.D.*
AU  - Foster, M.C.*
AU  - Greenawalt, D.M.*
AU  - Griffin, P.*
AU  - Ding, J.*
AU  - Newman, A.B.*
AU  - Tylavsky, F.*
AU  - Miljkovic, I.*
AU  - Kritchevsky, S.B.*
AU  - Launer, L.*
AU  - Garcia, M.*
AU  - Eiriksdottir, G.*
AU  - Carr, J.J.*
AU  - Gudnason, V.*
AU  - Harris, T.B.*
AU  - Cupples, L.A.*
AU  - Borecki, I.B.*
C1  - 8204
C2  - 30080
TI  - Genome-wide association for abdominal subcutaneous and visceral adipose reveals a novel locus for visceral fat in women.
JO  - PLoS Genet.
VL  - 8
IS  - 5
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - PRDM family members are transcriptional regulators involved in tissue specific differentiation. PRDM5 has been reported to predominantly repress transcription, but a characterization of its molecular functions in a relevant biological context is lacking. We demonstrate here that Prdm5 is highly expressed in developing bones; and, by genome-wide mapping of Prdm5 occupancy in pre-osteoblastic cells, we uncover a novel and unique role for Prdm5 in targeting all mouse collagen genes as well as several SLRP proteoglycan genes. In particular, we show that Prdm5 controls both Collagen I transcription and fibrillogenesis by binding inside the Col1a1 gene body and maintaining RNA polymerase II occupancy. In vivo, Prdm5 loss results in delayed ossification involving a pronounced impairment in the assembly of fibrillar collagens. Collectively, our results define a novel role for Prdm5 in sustaining the transcriptional program necessary to the proper assembly of osteoblastic extracellular matrix.
AU  - Galli, G.G.*
AU  - Honnens de Lichtenberg, K.*
AU  - Carrara, M.*
AU  - Hans, W.
AU  - Wuelling, M.*
AU  - Mentz, B.*
AU  - Multhaupt, H.A.*
AU  - Fog, C.K.*
AU  - Jensen, K.T.*
AU  - Rappsilber, J.*
AU  - Vortkamp, A.*
AU  - Coulton, L.*
AU  - Fuchs, H.*
AU  - Gailus-Durner, V.
AU  - Hrabě de Angelis, M.
AU  - Calogero, R.A.*
AU  - Couchman, J.R.*
AU  - Lund, A.H.*
C1  - 7479
C2  - 29739
TI  - Prdm5 regulates collagen gene transcription by association with RNA polymerase II in developing bone.
JO  - PLoS Genet.
VL  - 8
IS  - 5
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Recent genome-wide association studies (GWAS) with metabolomics data linked genetic variation in the human genome to differences in individual metabolite levels. A strong relevance of this metabolic individuality for biomedical and pharmaceutical research has been reported. However, a considerable amount of the molecules currently quantified by modern metabolomics techniques are chemically unidentified. The identification of these "unknown metabolites" is still a demanding and intricate task, limiting their usability as functional markers of metabolic processes. As a consequence, previous GWAS largely ignored unknown metabolites as metabolic traits for the analysis. Here we present a systems-level approach that combines genome-wide association analysis and Gaussian graphical modeling with metabolomics to predict the identity of the unknown metabolites. We apply our method to original data of 517 metabolic traits, of which 225 are unknowns, and genotyping information on 655,658 genetic variants, measured in 1,768 human blood samples. We report previously undescribed genotype-metabotype associations for six distinct gene loci (SLC22A2, COMT, CYP3A5, CYP2C18, GBA3, UGT3A1) and one locus not related to any known gene (rs12413935). Overlaying the inferred genetic associations, metabolic networks, and knowledge-based pathway information, we derive testable hypotheses on the biochemical identities of 106 unknown metabolites. As a proof of principle, we experimentally confirm nine concrete predictions. We demonstrate the benefit of our method for the functional interpretation of previous metabolomics biomarker studies on liver detoxification, hypertension, and insulin resistance. Our approach is generic in nature and can be directly transferred to metabolomics data from different experimental platforms.
AU  - Krumsiek, J.
AU  - Suhre, K.
AU  - Evans, A.M.*
AU  - Mitchell, M.W.*
AU  - Mohney, R.P.*
AU  - Milburn, M.V.*
AU  - Wägele, B.
AU  - Römisch-Margl, W.
AU  - Illig, T.
AU  - Adamski, J.
AU  - Gieger, C.
AU  - Theis, F.J.
AU  - Kastenmüller, G.
C1  - 10677
C2  - 30412
TI  - Mining the unknown: A systems approach to metabolite identification combining genetic and metabolic information.
JO  - PLoS Genet.
VL  - 8
IS  - 10
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Type 2 Diabetes (T2D) is a highly prevalent chronic metabolic disease with strong co-morbidity with obesity and cardiovascular diseases. There is growing evidence supporting the notion that a crosstalk between mitochondria and the insulin signaling cascade could be involved in the etiology of T2D and insulin resistance. In this study we investigated the molecular basis of this crosstalk by using systems biology approaches. We combined, filtered, and interrogated different types of functional interaction data, such as direct protein-protein interactions, co-expression analyses, and metabolic and signaling dependencies. As a result, we constructed the mitochondria-insulin (MITIN) network, which highlights 286 genes as candidate functional linkers between these two systems. The results of internal gene expression analysis of three independent experimental models of mitochondria and insulin signaling perturbations further support the connecting roles of these genes. In addition, we further assessed whether these genes are involved in the etiology of T2D using the genome-wide association study meta-analysis from the DIAGRAM consortium, involving 8,130 T2D cases and 38,987 controls. We found modest enrichment of genes associated with T2D amongst our linker genes (p = 0.0549), including three already validated T2D SNPs and 15 additional SNPs, which, when combined, were collectively associated to increased fasting glucose levels according to MAGIC genome wide meta-analysis (p = 8.12×10(-5)). This study highlights the potential of combining systems biology, experimental, and genome-wide association data mining for identifying novel genes and related variants that increase vulnerability to complex diseases.
AU  - Mercader, J.M.*
AU  - Puiggros, M.*
AU  - Segrè, A.V.*
AU  - Planet, E.*
AU  - Sorianello, E.*
AU  - Sebastian, D.*
AU  - Rodriguez-Cuenca, S.*
AU  - Ribas, V.*
AU  - Bonàs-Guarch, S.*
AU  - Draghici, S.*
AU  - Yang, C.*
AU  - Mora, S.*
AU  - Vidal-Puig, A.*
AU  - Dupuis, J.*
AU  - DIAGRAM Consortium (Huth, C.
AU  - Grallert, H.
AU  - Gieger, C.
AU  - Klopp, N.
AU  - Meitinger, T.
AU  - Petersen, A.-K.
AU  - Thorand, B.
AU  - Wichmann, H.-E.
AU  - Illig, T.)
AU  - Florez, J.C*
AU  - MITIN Consortium (*)
AU  - Zorzano, A.*
AU  - Torrents, D.*
C1  - 11747
C2  - 30803
TI  - Identification of novel type 2 diabetes candidate genes involved in the crosstalk between the mitochondrial and the insulin signaling systems.
JO  - PLoS Genet.
VL  - 8
IS  - 12
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Metabolic Syndrome (MetS) is highly prevalent and has considerable public health impact, but its underlying genetic factors remain elusive. To identify gene networks involved in MetS, we conducted whole-genome expression and genotype profiling on abdominal (ABD) and gluteal (GLU) adipose tissue, and whole blood (WB), from 29 MetS cases and 44 controls. Co-expression network analysis for each tissue independently identified nine, six, and zero MetS-associated modules of coexpressed genes in ABD, GLU, and WB, respectively. Of 8,992 probesets expressed in ABD or GLU, 685 (7.6%) were expressed in ABD and 51 (0.6%) in GLU only. Differential eigengene network analysis of 8,256 shared probesets detected 22 shared modules with high preservation across adipose depots (D(ABD-GLU) = 0.89), seven of which were associated with MetS (FDR P<0.01). The strongest associated module, significantly enriched for immune response-related processes, contained 94/620 (15%) genes with inter-depot differences. In an independent cohort of 145/141 twins with ABD and WB longitudinal expression data, median variability in ABD due to familiality was greater for MetS-associated versus un-associated modules (ABD: 0.48 versus 0.18, P = 0.08; GLU: 0.54 versus 0.20, P = 7.8×10(-4)). Cis-eQTL analysis of probesets associated with MetS (FDR P<0.01) and/or inter-depot differences (FDR P<0.01) provided evidence for 32 eQTLs. Corresponding eSNPs were tested for association with MetS-related phenotypes in two GWAS of >100,000 individuals; rs10282458, affecting expression of RARRES2 (encoding chemerin), was associated with body mass index (BMI) (P = 6.0×10(-4)); and rs2395185, affecting inter-depot differences of HLA-DRB1 expression, was associated with high-density lipoprotein (P = 8.7×10(-4)) and BMI-adjusted waist-to-hip ratio (P = 2.4×10(-4)). Since many genes and their interactions influence complex traits such as MetS, integrated analysis of genotypes and coexpression networks across multiple tissues relevant to clinical traits is an efficient strategy to identify novel associations.
AU  - Min, J.L.*
AU  - Nicholson, G.*
AU  - Halgrimsdottir, I.*
AU  - Almstrup, K.*
AU  - Petri, A.*
AU  - Barrett, A.*
AU  - Travers, M.*
AU  - Rayner, N.W.*
AU  - Mägi, R.*
AU  - Pettersson, F.H.*
AU  - Broxholme, J.*
AU  - Neville, M.J.*
AU  - Wills, Q.F.*
AU  - Cheeseman, J.*
AU  - GIANT Consortium (Heid, I.M.
AU  - Thiering, E.
AU  - Gieger, C.
AU  - Grallert, H.
AU  - Wichmann, H.-E.
AU  - Illig, T.
AU  - Heinrich, J.
AU  - Peters, A.
AU  - *)
AU  - Allen, M.*
AU  - Holmes, C.C.*
AU  - Spector, T.D.*
AU  - Fleckner, J.*
AU  - McCarthy, M.I.*
AU  - Karpe, F.*
AU  - Lindgren, C.M.*
AU  - Zondervan, K.T.*
C1  - 28623
C2  - 33495
TI  - Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes.
JO  - PLoS Genet.
VL  - 8
IS  - 2
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - c-Myc (hereafter called Myc) belongs to a family of transcription factors that regulates cell growth, cell proliferation, and differentiation. Myc initiates the transcription of a large cast of genes involved in cell growth by stimulating metabolism and protein synthesis. Some of these, like those involved in glycolysis, may be part of the Warburg effect, which is defined as increased glucose uptake and lactate production in the presence of adequate oxygen supply. In this study, we have taken a mouse-genetics approach to challenge the role of select Myc-regulated metabolic enzymes in tumorigenesis in vivo. By breeding λ-Myc transgenic mice, Apc(Min) mice, and p53 knockout mice with mouse models carrying inactivating alleles of Lactate dehydrogenase A (Ldha), 3-Phosphoglycerate dehydrogenase (Phgdh) and Serine hydroxymethyltransferase 1 (Shmt1), we obtained offspring that were monitored for tumor development. Very surprisingly, we found that these genes are dispensable for tumorigenesis in these genetic settings. However, experiments in fibroblasts and colon carcinoma cells expressing oncogenic Ras show that these cells are sensitive to Ldha knockdown. Our genetic models reveal cell context dependency and a remarkable ability of tumor cells to adapt to alterations in critical metabolic pathways. Thus, to achieve clinical success, it will be of importance to correctly stratify patients and to find synthetic lethal combinations of inhibitors targeting metabolic enzymes.
AU  - Nilsson, L.M.*
AU  - Forshell, T.Z.P.*
AU  - Rimpi, S.*
AU  - Kreutzer, C.*
AU  - Pretsch, W.
AU  - Bornkamm, G.W.
AU  - Nilsson, J.A.*
C1  - 7502
C2  - 29762
TI  - Mouse genetics suggests cell-context dependency for Myc-regulated metabolic enzymes during tumorigenesis.
JO  - PLoS Genet.
VL  - 8
IS  - 3
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Neurobeachin (Nbea) regulates neuronal membrane protein trafficking and is required for the development and functioning of central and neuromuscular synapses. In homozygous knockout (KO) mice, Nbea deficiency causes perinatal death. Here, we report that heterozygous KO mice haploinsufficient for Nbea have higher body weight due to increased adipose tissue mass. In several feeding paradigms, heterozygous KO mice consumed more food than wild-type (WT) controls, and this consumption was primarily driven by calories rather than palatability. Expression analysis of feeding-related genes in the hypothalamus and brainstem with real-time PCR showed differential expression of a subset of neuropeptide or neuropeptide receptor mRNAs between WT and Nbea+/- mice in the sated state and in response to food deprivation, but not to feeding reward. In humans, we identified two intronic NBEA single-nucleotide polymorphisms (SNPs) that are significantly associated with body-mass index (BMI) in adult and juvenile cohorts. Overall, data obtained in mice and humans suggest that variation of Nbea abundance or activity critically affects body weight, presumably by influencing the activity of feeding-related neural circuits. Our study emphasizes the importance of neural mechanisms in body weight control and points out NBEA as a potential risk gene in human obesity.
AU  - Olszewski, P.K.*
AU  - Rozman, J.
AU  - Jacobsson, J.A.*
AU  - Rathkolb, B.
AU  - Strömberg, S.*
AU  - Hans, W.
AU  - Klockars, A.*
AU  - Alsiö, J.*
AU  - Risérus, U.*
AU  - Becker, L.
AU  - Hölter, S.M.
AU  - Elvert, R.
AU  - Ehrhardt, N.
AU  - Gailus-Durner, V.
AU  - Fuchs, H.
AU  - Fredriksson, R.*
AU  - Wolf, E.*
AU  - Klopstock, T.*
AU  - Wurst, W.
AU  - Levine, A.S.*
AU  - Marcus, C.*
AU  - Hrabě de Angelis, M.
AU  - Klingenspor, M.*
AU  - Schiöth, H.B.*
AU  - Kilimann, M.W.*
C1  - 7103
C2  - 29607
TI  - Neurobeachin, a regulator of synaptic protein targeting, is associated with body fat mass and feeding behavior in mice and body-mass index in humans.
JO  - PLoS Genet.
VL  - 8
IS  - 3
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD.
AU  - Pattaro, C.*
AU  - Köttgen, A.*
AU  - Teumer, A.*
AU  - Garnaas, M.*
AU  - Böger, C.A.*
AU  - Fuchsberger, C.*
AU  - Olden, M.*
AU  - Chen, M.H.*
AU  - Tin, A.*
AU  - Taliun, D.*
AU  - Li, M.*
AU  - Gao, X.*
AU  - Gorski, M.
AU  - Yang, Q.*
AU  - Hundertmark, C.*
AU  - Foster, M.C.*
AU  - O'Seaghdha, C.M.*
AU  - Glazer, N.*
AU  - Isaacs, A.*
AU  - Liu, C.-T.*
AU  - Smith, A.V.*
AU  - O'Connell, J.R.*
AU  - Struchalin, M.*
AU  - Tanaka, T.*
AU  - Li, G.*
AU  - Johnson, A.D.*
AU  - Gierman, H.J.*
AU  - Feitosa, M.*
AU  - Hwang, S.J.*
AU  - Atkinson, E.J.*
AU  - Lohman, K.*
AU  - Cornelis, M.C.*
AU  - Johansson, Å*
AU  - Tönjes, A.*
AU  - Dehghan, A.*
AU  - Chouraki, V.*
AU  - Holliday, E.G.*
AU  - Sorice, R.*
AU  - Kutalik, Z.*
AU  - Lehtimäki, T.*
AU  - Esko, T.*
AU  - Deshmukh, H.*
AU  - Ulivi, S.*
AU  - Chu, A.Y.*
AU  - Murgia, F.*
AU  - Trompet, S.*
AU  - Imboden, M.*
AU  - Kollerits, B.*
AU  - Pistis, G.*
AU  - CARDIoGRAM Consortium (Wichmann, H.-E.
AU  - Klopp, N.
AU  - Illig, T.
AU  - Meisinger, C.
AU  - Peters, A.
AU  - Meitinger, T.
AU  - Döring, A.)
AU  - ICBP Consortium (*)
AU  - CARE Consortium (*)
AU  - Wellcome Trust Case Control Consortium 2 (WTCCC2) (*)
AU  - Harris, T.B.*
AU  - Launer, L.J.*
AU  - Aspelund, T.*
AU  - Eiriksdottir, G.*
AU  - Mitchell, B.D.*
AU  - Boerwinkle, E.*
AU  - Schmidt, H.*
AU  - Cavalieri, M.*
AU  - Rao, M.*
AU  - Hu, F.B.*
AU  - Demirkan, A.*
AU  - Oostra, B.A.*
AU  - de Andrade, M.*
AU  - Turner, S.T.*
AU  - Ding, J.*
AU  - Andrews, J.S.*
AU  - Freedman, B.I.*
AU  - Koenig, W.*
AU  - Illig, T.
AU  - Döring, A.
AU  - Wichmann, H.-E.
AU  - Klopp, N.
AU  - Meisinger, C.
AU  - Peters, A.
AU  - Meitinger, T.
AU  - Kolcic, I.*
AU  - Zemunik, T.*
AU  - Boban, M.*
AU  - Minelli, C.*
AU  - Wheeler, H.E.*
AU  - Igl, W.*
AU  - Zaboli, G.*
AU  - Wild, S.H.*
AU  - Wright, A.F.*
AU  - Campbell, H.*
AU  - Ellinghaus, D.*
AU  - Nöthlings, U.*
AU  - Jacobs, G.*
AU  - Biffar, R.*
AU  - Endlich, K.*
AU  - Ernst, F.*
AU  - Homuth, G.*
AU  - Kroemer, H.K.*
AU  - Nauck, M.*
AU  - Stracke, S.*
AU  - Völker, U.*
AU  - Völzke, H.*
AU  - Kovacs, P.*
AU  - Stumvoll, M.*
AU  - Mägi, R.*
AU  - Hofman, A.*
AU  - Uitterlinden, A.G.*
AU  - Rivadeneira, F.*
AU  - Aulchenko, Y.S.*
AU  - Polasek, O.*
AU  - Hastie, N.*
AU  - Vitart, V.*
AU  - Helmer, C.*
AU  - Wang, J.J.*
AU  - Ruggiero, D.*
AU  - Bergmann, S.*
AU  - Kähönen, M.*
AU  - Viikari, J.*
AU  - Nikopensius, T.*
AU  - Province, M.*
AU  - Ketkar, S.*
AU  - Colhoun, H.*
AU  - Doney, A.*
AU  - Robino, A.*
AU  - Giulianini, F.*
AU  - Krämer, B.K.*
AU  - Portas, L.*
AU  - Ford, I.*
AU  - Buckley, B.M.*
AU  - Adam, M.*
AU  - Thun, G.A.*
AU  - Paulweber, B.*
AU  - Haun, M.*
AU  - Sala, C.*
AU  - Metzger, M.*
AU  - Mitchell, P.*
AU  - Ciullo, M.*
AU  - Kim, S.K.*
AU  - Vollenweider, P.*
AU  - Raitakari, O.*
AU  - Metspalu, A.*
AU  - Palmer, C.*
AU  - Gasparini, P.*
AU  - Pirastu, M.*
AU  - Jukema, J.W.*
AU  - Probst-Hensch, N.M.*
AU  - Kronenberg, F.*
AU  - Toniolo, D.*
AU  - Gudnason, V.*
AU  - Shuldiner, A.R.*
AU  - Coresh, J.*
AU  - Schmidt, R.*
AU  - Ferrucci, L.*
AU  - Siscovick, D.S.*
AU  - van Duijn, C.M.*
AU  - Borecki, I.*
AU  - Kardia, S.L.*
AU  - Liu, Y.*
AU  - Curhan, G.C.*
AU  - Rudan, I.*
AU  - Gyllensten, U.*
AU  - Wilson, J.F.*
AU  - Franke, A.*
AU  - Pramstaller, P.P.*
AU  - Rettig, R.*
AU  - Prokopenko, I.*
AU  - Witteman, J.C.*
AU  - Hayward, C.*
AU  - Ridker, P.*
AU  - Parsa, A.*
AU  - Bochud, M.*
AU  - Heid, I.M.*
AU  - Goessling, W.*
AU  - Chasman, D.I.*
AU  - Kao, W.H.*
AU  - Fox, C.S.*
C1  - 7487
C2  - 29747
TI  - Genome-wide association and functional follow-up reveals new loci for kidney function.
JO  - PLoS Genet.
VL  - 8
IS  - 3
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m(2)) compared to obese cases (BMI >= 30 Kg/m(2)). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m(2)) or 4,123 obese cases (BMI >= 30 kg/m(2)), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4610 29, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A-previously identified in South Asians but not Europeans-was associated with type 2 diabetes in obese cases (P = 1.3 x 10(-8), OR= 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2 x 10(-14). This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2 x 10(-16). This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.
AU  - Perry, J.R.*
AU  - Voight, B.F.*
AU  - Yengo, L.*
AU  - Amin, N.*
AU  - Dupuis, J.*
AU  - Ganser, M.*
AU  - Grallert, H.
AU  - Navarro, P.*
AU  - Li, M.*
AU  - Qi, L.*
AU  - Steinthorsdottir, V.*
AU  - Scott, R.A.*
AU  - Almgren, P.*
AU  - Arking, D.E.*
AU  - Aulchenko, Y.*
AU  - Balkau, B.*
AU  - Benediktsson, R.*
AU  - Bergman, R.N.*
AU  - Boerwinkle, E.*
AU  - Bonnycastle, L.*
AU  - Burtt, N.P.*
AU  - Campbell, H.*
AU  - Charpentier, G.*
AU  - Collins, F.S.*
AU  - Gieger, C.
AU  - Green, T.*
AU  - Hadjadj, S.*
AU  - Hattersley, A.T.*
AU  - Herder, C.*
AU  - Hofman, A.*
AU  - Johnson, A.D.*
AU  - Köttgen, A.*
AU  - Kraft, P.*
AU  - Labrune, Y.*
AU  - Langenberg, C.*
AU  - Manning, A.K.*
AU  - Mohlke, K.L.*
AU  - Morris, A.P.*
AU  - Oostra, B.*
AU  - Pankow, J.*
AU  - Petersen, A.-K.
AU  - Pramstaller, P.P.*
AU  - Prokopenko, I.*
AU  - Rathmann, W.*
AU  - Rayner, W.*
AU  - Roden, M.*
AU  - Rudan, I.*
AU  - Rybin, D.*
AU  - Scott, L.J.*
AU  - Sigurdsson, G.*
AU  - Sladek, R.*
AU  - Thorleifsson, G.*
AU  - Thorsteinsdottir, U.*
AU  - Tuomilehto, J.*
AU  - Uitterlinden, A.G.*
AU  - Vivequin, S.*
AU  - Weedon, M.N.*
AU  - Wright, A.F.*
AU  - Hu, F.B.*
AU  - Illig, T.
AU  - Kao, L.*
AU  - Meigs, J.B.*
AU  - Wilson, J.F.*
AU  - Stefansson, K.*
AU  - van Duijn, C.M.*
AU  - Altschuler, D.*
AU  - Morris, A.D.*
AU  - Boehnke, M.*
AU  - McCarthy, M.I.*
AU  - Froguel, P.*
AU  - Palmer, C.N.*
AU  - Wareham, N.J.*
AU  - Groop, L.*
AU  - Frayling, T.M.*
AU  - Cauchi, S.*
C1  - 7613
C2  - 30139
TI  - Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases.
JO  - PLoS Genet.
VL  - 8
IS  - 5
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the "Metabochip," a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.
AU  - Voight, B.F.*
AU  - Kang, H.M.*
AU  - Ding, J.*
AU  - Palmer, C.D.*
AU  - Sidore, C.*
AU  - Chines, P.S.*
AU  - Burtt, N.P.*
AU  - Fuchsberger, C.*
AU  - Li, Y.M.*
AU  - Erdmann, J.*
AU  - Frayling, T.M.*
AU  - Heid, I.M.
AU  - Jackson, A.U.*
AU  - Johnson, T.*
AU  - Kilpeläinen, T.O.*
AU  - Lindgren, C.M.*
AU  - Morris, A.P.*
AU  - Prokopenko, I.*
AU  - Randall, J.C.*
AU  - Saxena, R.*
AU  - Soranzo, N.*
AU  - Speliotes, E.K.*
AU  - Teslovich, T.M.*
AU  - Wheeler, E.*
AU  - Maguire, J.*
AU  - Parkin, M.*
AU  - Potter, S.*
AU  - Rayner, N.W.*
AU  - Robertson, N.*
AU  - Stirrups, K.*
AU  - Winckler, W.*
AU  - Sanna, S.*
AU  - Mulas, A.*
AU  - Nagaraja, R.*
AU  - Cucca, F.*
AU  - Barroso, I.*
AU  - Deloukas, P.*
AU  - Loos, R.J.F.*
AU  - Kathiresan, S.*
AU  - Munroe, P.B.*
AU  - Newton-Cheh, C.*
AU  - Pfeufer, A.
AU  - Samani, N.J.*
AU  - Schunkert, H.*
AU  - Hirschhorn, J.N.*
AU  - Altshuler, D.*
AU  - McCarthy, M.I.*
AU  - Abecasis, G.R.*
AU  - Boehnke, M.*
C1  - 10646
C2  - 30426
TI  - The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits.
JO  - PLoS Genet.
VL  - 8
IS  - 8
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low-BMI cases are larger than those estimated from high-BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1×10(-9)). The improvement varied across diseases with a 16% median increase in χ(2) test statistics and a commensurate increase in power. This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci.
AU  - Zaitlen, N.*
AU  - Lindström, S.*
AU  - Pasaniuc, B.*
AU  - Cornelis, M.*
AU  - Genovese, G.*
AU  - Pollack, S.*
AU  - Barton, A.*
AU  - Bickeböller, H.*
AU  - Bowden, D.W.*
AU  - Eyre, S.*
AU  - Freedman, B.I.*
AU  - Friedman, D.J.*
AU  - Field, J.K.*
AU  - Groop, L.*
AU  - Haugen, A.*
AU  - Heinrich, J.
AU  - Henderson, B.E.*
AU  - Hicks, P.J.*
AU  - Hocking, L.J.*
AU  - Kolonel, L.N.*
AU  - Landi, M.T.*
AU  - Langefeld, C.D.*
AU  - Le Marchand, L.*
AU  - Meister, M.*
AU  - Morgan, A.W.*
AU  - Raji, O.Y.*
AU  - Risch, A.*
AU  - Rosenberger, A.*
AU  - Scherf, D.*
AU  - Steer, S.*
AU  - Walshaw, M.*
AU  - Waters, K.M.*
AU  - Wilson, A.G.*
AU  - Wordsworth, P.*
AU  - Zienolddiny, S.*
AU  - Tchetgen, E.T.*
AU  - Haiman, C.*
AU  - Hunter, D.J.*
AU  - Plenge, R.M.*
AU  - Worthington, J.*
AU  - Christiani, D.C.*
AU  - Schaumberg, D.A.*
AU  - Chasman, D.I.*
AU  - Altshuler, D.*
AU  - Voight, B.*
AU  - Kraft, P.*
AU  - Patterson, N.*
AU  - Price, A.L.*
C1  - 11373
C2  - 30649
TI  - Informed conditioning on clinical covariates increases power in case-control association studies.
JO  - PLoS Genet.
VL  - 8
IS  - 11
PB  - Public Library of Science
PY  - 2012
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Systemic sclerosis (SSc) is an orphan, complex, inflammatory disease affecting the immune system and connective tissue. SSc stands out as a severely incapacitating and life-threatening inflammatory rheumatic disease, with a largely unknown pathogenesis. We have designed a two-stage genome-wide association study of SSc using case-control samples from France, Italy, Germany, and Northern Europe. The initial genome-wide scan was conducted in a French post quality-control sample of 564 cases and 1,776 controls, using almost 500 K SNPs. Two SNPs from the MHC region, together with the 6 loci outside MHC having at least one SNP with a P<10(-5) were selected for follow-up analysis. These markers were genotyped in a post-QC replication sample of 1,682 SSc cases and 3,926 controls. The three top SNPs are in strong linkage disequilibrium and located on 6p21, in the HLA-DQB1 gene: rs9275224, P = 9.18×10(-8), OR = 0.69, 95% CI [0.60-0.79]; rs6457617, P = 1.14×10(-7) and rs9275245, P = 1.39×10(-7). Within the MHC region, the next most associated SNP (rs3130573, P = 1.86×10(-5), OR = 1.36 [1.18-1.56]) is located in the PSORS1C1 gene. Outside the MHC region, our GWAS analysis revealed 7 top SNPs (P<10(-5)) that spanned 6 independent genomic regions. Follow-up of the 17 top SNPs in an independent sample of 1,682 SSc and 3,926 controls showed associations at PSORS1C1 (overall P = 5.70×10(-10), OR:1.25), TNIP1 (P = 4.68×10(-9), OR:1.31), and RHOB loci (P = 3.17×10(-6), OR:1.21). Because of its biological relevance, and previous reports of genetic association at this locus with connective tissue disorders, we investigated TNIP1 expression. A markedly reduced expression of the TNIP1 gene and also its protein product were observed both in lesional skin tissue and in cultured dermal fibroblasts from SSc patients. Furthermore, TNIP1 showed in vitro inhibitory effects on inflammatory cytokine-induced collagen production. The genetic signal of association with TNIP1 variants, together with tissular and cellular investigations, suggests that this pathway has a critical role in regulating autoimmunity and SSc pathogenesis.
AU  - Allanore, Y.*
AU  - Saad, M.*
AU  - Dieudé, P.*
AU  - Avouac, J.*
AU  - Distler, J.H.*
AU  - Amouyel, P.*
AU  - Matucci-Cerinic, M.*
AU  - Riemekasten, G.*
AU  - Airo, P.*
AU  - Melchers, I.*
AU  - Hachulla, E.*
AU  - Cusi, D.*
AU  - Wichmann, H.-E.
AU  - Wipff, J.*
AU  - Lambert, J.C.*
AU  - Hunzelmann, N.*
AU  - Tiev, K.*
AU  - Caramaschi, P.*
AU  - Diot, E.*
AU  - Kowal-Bielecka, O.*
AU  - Valentini, G.*
AU  - Mouthon, L.*
AU  - Czirják, L.*
AU  - Damjanov, N.*
AU  - Salvi, E.*
AU  - Conti, C.*
AU  - Müller, M.
AU  - Müller-Ladner, U.*
AU  - Riccieri, V.*
AU  - Ruiz, B.*
AU  - Cracowski, J.L.*
AU  - Letenneur, L.*
AU  - Dupuy, A.M.*
AU  - Meyer, O.*
AU  - Kahan, A.*
AU  - Munnich, A.*
AU  - Boileau, C.*
AU  - Martinez, M.*
C1  - 6471
C2  - 28747
TI  - Genome-wide scan identifies TNIP1, PSORS1C1, and RHOB as novel risk loci for systemic sclerosis.
JO  - PLoS Genet.
VL  - 7
IS  - 7
PB  - Public Library Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Sclerotinia sclerotiorum and Botrytis cinerea are closely related necrotrophic plant pathogenic fungi notable for their wide host ranges and environmental persistence. These attributes have made these species models for understanding the complexity of necrotrophic, broad host-range pathogenicity. Despite their similarities, the two species differ in mating behaviour and the ability to produce asexual spores. We have sequenced the genomes of one strain of S. sclerotiorum and two strains of B. cinerea. The comparative analysis of these genomes relative to one another and to other sequenced fungal genomes is provided here. Their 38-39 Mb genomes include 11,860-14,270 predicted genes, which share 83% amino acid identity on average between the two species. We have mapped the S. sclerotiorum assembly to 16 chromosomes and found large-scale co-linearity with the B. cinerea genomes. Seven percent of the S. sclerotiorum genome comprises transposable elements compared to <1% of B. cinerea. The arsenal of genes associated with necrotrophic processes is similar between the species, including genes involved in plant cell wall degradation and oxalic acid production. Analysis of secondary metabolism gene clusters revealed an expansion in number and diversity of B. cinerea-specific secondary metabolites relative to S. sclerotiorum. The potential diversity in secondary metabolism might be involved in adaptation to specific ecological niches. Comparative genome analysis revealed the basis of differing sexual mating compatibility systems between S. sclerotiorum and B. cinerea. The organization of the mating-type loci differs, and their structures provide evidence for the evolution of heterothallism from homothallism. These data shed light on the evolutionary and mechanistic bases of the genetically complex traits of necrotrophic pathogenicity and sexual mating. This resource should facilitate the functional studies designed to better understand what makes these fungi such successful and persistent pathogens of agronomic crops.
AU  - Amselem, J.*
AU  - Cuomo, C.A.*
AU  - van Kan, J.A.*
AU  - Viaud, M.*
AU  - Benito, E.P.*
AU  - Couloux, A.*
AU  - Coutinho, P.M.*
AU  - de Vries, R.P.*
AU  - Dyer, P.S.*
AU  - Fillinger, S.*
AU  - Fournier, E.*
AU  - Gout, L.*
AU  - Hahn, M.*
AU  - Kohn, L.*
AU  - Lapalu, N.*
AU  - Plummer, K.M.*
AU  - Pradier, J.M.*
AU  - Quévillon, E.*
AU  - Sharon, A.*
AU  - Simon, A.*
AU  - ten Have, A.*
AU  - Tudzynski, B.*
AU  - Tudzynski, P.*
AU  - Wincker, P.*
AU  - Andrew, M.*
AU  - Anthouard, V.*
AU  - Beever, R.E.*
AU  - Beffa, R.*
AU  - Benoit, I.*
AU  - Bouzid, O.*
AU  - Brault, B.*
AU  - Chen, Z.*
AU  - Choquer, M.*
AU  - Collémare, J.*
AU  - Cotton, P.*
AU  - Danchin, E.G.*
AU  - Da Silva, C.*
AU  - Gautier, A.*
AU  - Giraud, C.*
AU  - Giraud, T.*
AU  - Gonzalez, C.*
AU  - Grossetete, S.*
AU  - Güldener, U.
AU  - Henrissat, B.*
AU  - Howlett, BJ.*
AU  - Kodira, C.*
AU  - Kretschmer, M.*
AU  - Lappartient, A.*
AU  - Leroch, M.*
AU  - Levis, C.*
AU  - Mauceli, E.*
AU  - Neuvéglise, C.*
AU  - Oeser, B.*
AU  - Pearson, M.*
AU  - Poulain, J.*
AU  - Poussereau, N.*
AU  - Quesneville, H.*
AU  - Rascle, C.*
AU  - Schumacher, J.*
AU  - Segurens, B.*
AU  - Sexton, A.*
AU  - Silva, E.*
AU  - Sirven, C.*
AU  - Soanes, D.M.*
AU  - Talbot, N.J.*
AU  - Templeton, M.*
AU  - Yandava, C.*
AU  - Yarden, O.*
AU  - Zeng, Q.*
AU  - Rollins, J.A.*
AU  - Lebrun, M.H.*
AU  - Dickman, M.*
C1  - 6900
C2  - 29422
TI  - Genomic analysis of the necrotrophic fungal pathogens Sclerotinia sclerotiorum and Botrytis cinerea.
JO  - PLoS Genet.
VL  - 7
IS  - 8
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Family studies suggest a genetic component to the etiology of chronic kidney disease (CKD) and end stage renal disease (ESRD). Previously, we identified 16 loci for eGFR in genome-wide association studies, but the associations of these single nucleotide polymorphisms (SNPs) for incident CKD or ESRD are unknown. We thus investigated the association of these loci with incident CKD in 26,308 individuals of European ancestry free of CKD at baseline drawn from eight population-based cohorts followed for a median of 7.2 years (including 2,122 incident CKD cases defined as eGFR <60ml/min/1.73m(2) at follow-up) and with ESRD in four case-control studies in subjects of European ancestry (3,775 cases, 4,577 controls). SNPs at 11 of the 16 loci (UMOD, PRKAG2, ANXA9, DAB2, SHROOM3, DACH1, STC1, SLC34A1, ALMS1/NAT8, UBE2Q2, and GCKR) were associated with incident CKD; p-values ranged from p = 4.1e-9 in UMOD to p = 0.03 in GCKR. After adjusting for baseline eGFR, six of these loci remained significantly associated with incident CKD (UMOD, PRKAG2, ANXA9, DAB2, DACH1, and STC1). SNPs in UMOD (OR = 0.92, p = 0.04) and GCKR (OR = 0.93, p = 0.03) were nominally associated with ESRD. In summary, the majority of eGFR-related loci are either associated or show a strong trend towards association with incident CKD, but have modest associations with ESRD in individuals of European descent. Additional work is required to characterize the association of genetic determinants of CKD and ESRD at different stages of disease progression.
AU  - Böger, C.A.*
AU  - Gorski, M.
AU  - Li, M.*
AU  - Hoffmann, M.M.*
AU  - Huang, C.*
AU  - Yang, Q.*
AU  - Teumer, A.*
AU  - Krane, V.*
AU  - O'Seaghdha, C.M.*
AU  - Kutalik, Z.*
AU  - Wichmann, H.-E.
AU  - Haak, T.*
AU  - Boes, E.*
AU  - Coassin, S.*
AU  - Coresh, J.*
AU  - Kollerits, B.*
AU  - Haun, M.*
AU  - Paulweber, B.*
AU  - Köttgen, A.*
AU  - Li, G.*
AU  - Shlipak, M.G.*
AU  - Powe, N.*
AU  - Hwang, S.J.*
AU  - Dehghan, A.*
AU  - Rivadeneira, F.*
AU  - Uitterlinden, A.*
AU  - Hofman, A.*
AU  - Beckmann, JS.*
AU  - Krämer, B.K.*
AU  - Witteman, J.*
AU  - Bochud, M.*
AU  - Siscovick, D.*
AU  - Rettig, R.*
AU  - Kronenberg, F.*
AU  - Wanner, C.*
AU  - Thadhani, R.I.*
AU  - Heid, I.M.
AU  - Fox, C.S.*
AU  - Kao, W.H*
C1  - 5460
C2  - 29103
TI  - Association of eGFR-related loci identified by GWAS with incident CKD and ESRD.
JO  - PLoS Genet.
VL  - 7
IS  - 9
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - A previous genome-wide association (GWA) meta-analysis of 12,386 PD cases and 21,026 controls conducted by the International Parkinson's Disease Genomics Consortium (IPDGC) discovered or confirmed 11 Parkinson's disease (PD) loci. This first analysis of the two-stage IPDGC study focused on the set of loci that passed genome-wide significance in the first stage GWA scan. However, the second stage genotyping array, the ImmunoChip, included a larger set of 1,920 SNPs selected on the basis of the GWA analysis. Here, we analyzed this set of 1,920 SNPs, and we identified five additional PD risk loci (combined p<5×10(-10), PARK16/1q32, STX1B/16p11, FGF20/8p22, STBD1/4q21, and GPNMB/7p15). Two of these five loci have been suggested by previous association studies (PARK16/1q32, FGF20/8p22), and this study provides further support for these findings. Using a dataset of post-mortem brain samples assayed for gene expression (n = 399) and methylation (n = 292), we identified methylation and expression changes associated with PD risk variants in PARK16/1q32, GPNMB/7p15, and STX1B/16p11 loci, hence suggesting potential molecular mechanisms and candidate genes at these risk loci.
AU  - International Parkinson's Disease Genomics Consortium (IPDGC) (Illig, T.
AU  - Lichtner, P.)
AU  - Wellcome Trust Case Control Consortium 2 (WTCCC2) (*)
C1  - 6491
C2  - 28787
TI  - A two-stage meta-analysis identifies several new loci for Parkinson's disease.
JO  - PLoS Genet.
VL  - 7
IS  - 6
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ∼2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10(-33); LPA:p<10(-19); 1p13.3:p<10(-17)) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10(-7)). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06-1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ∼4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes.
AU  - IBC 50K CAD Consortium (Klopp, N.
AU  - Baumert, J.J.
AU  - Peters, A.
AU  - Meisinger, C.
AU  - Gieger, C.
AU  - Döring, A.
AU  - Illig, T.
AU  - Meitinger, T.
AU  - Wichmann, H.-E.)
C1  - 6172
C2  - 29240
TI  - Large-scale gene-centric analysis identifies novel variants for coronary artery disease.
JO  - PLoS Genet.
VL  - 7
IS  - 9
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies (GWAS) have been successful in identifying common genetic variation involved in susceptibility to etiologically complex disease. We conducted a GWAS to identify common genetic variation involved in susceptibility to upper aero-digestive tract (UADT) cancers. Genome-wide genotyping was carried out using the Illumina HumanHap300 beadchips in 2,091 UADT cancer cases and 3,513 controls from two large European multi-centre UADT cancer studies, as well as 4,821 generic controls. The 19 top-ranked variants were investigated further in an additional 6,514 UADT cancer cases and 7,892 controls of European descent from an additional 13 UADT cancer studies participating in the INHANCE consortium. Five common variants presented evidence for significant association in the combined analysis (p ≤ 5 × 10⁻⁷). Two novel variants were identified, a 4q21 variant (rs1494961, p = 1×10⁻⁸) located near DNA repair related genes HEL308 and FAM175A (or Abraxas) and a 12q24 variant (rs4767364, p =2 × 10⁻⁸) located in an extended linkage disequilibrium region that contains multiple genes including the aldehyde dehydrogenase 2 (ALDH2) gene. Three remaining variants are located in the ADH gene cluster and were identified previously in a candidate gene study involving some of these samples. The association between these three variants and UADT cancers was independently replicated in 5,092 UADT cancer cases and 6,794 controls non-overlapping samples presented here (rs1573496-ADH7, p = 5 × 10⁻⁸); rs1229984-ADH1B, p = 7 × 10⁻⁹; and rs698-ADH1C, p = 0.02). These results implicate two variants at 4q21 and 12q24 and further highlight three ADH variants in UADT cancer susceptibility.
AU  - McKay, J.D.*
AU  - Truong, T.*
AU  - Gaborieau, V.*
AU  - Chabrier, A.*
AU  - Chuang, S.C.*
AU  - Byrnes, G.*
AU  - Zaridze, D.*
AU  - Shangina, O.*
AU  - Szeszenia-Dabrowska, N.*
AU  - Lissowska, J.*
AU  - Rudnai, P.*
AU  - Fabianova, E.*
AU  - Bucur, A.*
AU  - Bencko, V.*
AU  - Holcatova, I.*
AU  - Janout, V.*
AU  - Foretova, L.*
AU  - Lagiou, P.*
AU  - Trichopoulos, D.*
AU  - Benhamou, S.*
AU  - Bouchardy, C.*
AU  - Ahrens, W.*
AU  - Merletti, F.*
AU  - Richiardi, L.*
AU  - Talamini, R.*
AU  - Barzan, L.*
AU  - Kjaerheim, K.*
AU  - Macfarlane, GJ.*
AU  - Macfarlane, TV.*
AU  - Simonato, L.*
AU  - Canova, C.*
AU  - Agudo, A.*
AU  - Castellsagué, X.*
AU  - Lowry, R.*
AU  - Conway, DI.*
AU  - McKinney, P.A.*
AU  - Healy, C.M.*
AU  - Toner, M.E.*
AU  - Znaor, A.*
AU  - Curado, M.P.*
AU  - Koifman, S.*
AU  - Menezes, A.*
AU  - Wünsch-Filho, V.*
AU  - Neto, J.E.*
AU  - Garrote, L.F.*
AU  - Boccia, S.*
AU  - Cadoni, G.*
AU  - Arzani, D.*
AU  - Olshan, A.F.*
AU  - Weissler, M.C.*
AU  - Funkhouser, W.K.*
AU  - Luo, J.*
AU  - Lubinski, J.*
AU  - Trubicka, J.*
AU  - Lener, M.*
AU  - Oszutowska, D.*
AU  - Schwartz, S.M.*
AU  - Chen, C.*
AU  - Fish, S.*
AU  - Doody, DR.*
AU  - Muscat, J.E.*
AU  - Lazarus, P.*
AU  - Gallagher, C.J.*
AU  - Chang, S.C.*
AU  - Zhang, Z.F.*
AU  - Wei, Q.*
AU  - Sturgis, E.M.*
AU  - Wang, L.E.*
AU  - Franceschi, S.*
AU  - Herrero, R.*
AU  - Kelsey, K.T.*
AU  - McClean, M.D.*
AU  - Marsit, C.J.*
AU  - Nelson, H.H.*
AU  - Romkes, M.*
AU  - Buch, S.*
AU  - Nukui, T.*
AU  - Zhong, S.*
AU  - Lacko, M.*
AU  - Manni, J.J.*
AU  - Peters, W.H.*
AU  - Hung, R.J.*
AU  - McLaughlin, J.*
AU  - Vatten, L.*
AU  - Njølstad, I.*
AU  - Goodman, G.E.*
AU  - Field, J.K.*
AU  - Liloglou, T.*
AU  - Vineis, P.*
AU  - Clavel-Chapelon, F.*
AU  - Palli, D.*
AU  - Tumino, R.*
AU  - Krogh, V.*
AU  - Panico, S.*
AU  - González, C.A.*
AU  - Quirós, J.R.*
AU  - Martinez, C.*
AU  - Navarro, C.*
AU  - Ardanaz, E.*
AU  - Larrañaga, N.*
AU  - Khaw, K.T.*
AU  - Key, T.*
AU  - Bueno-de-Mesquita, H.B.*
AU  - Peeters, P.H.*
AU  - Trichopoulou, A.*
AU  - Linseisen, J.
AU  - Boeing, H.*
AU  - Hallmans, G.*
AU  - Overvad, K.*
AU  - Tjønneland, A.*
AU  - Kumle, M.*
AU  - Riboli, E.*
AU  - Välk, K.*
AU  - Voodern, T.*
AU  - Metspalu, A.*
AU  - Zelenika, D.*
AU  - Boland, A.*
AU  - Delepine, M.*
AU  - Foglio, M.*
AU  - Lechner, D.*
AU  - Blanche, H.*
AU  - Gut, I.G.*
AU  - Galan, P.*
AU  - Heath, S.*
AU  - Hashibe, M.*
AU  - Hayes, RB.*
AU  - Boffetta, P.*
AU  - Lathrop, M*
AU  - Brennan, P.
C1  - 5944
C2  - 28422
TI  - A genome-wide association study of upper aerodigestive tract cancers conducted within the INHANCE consortium.
JO  - PLoS Genet.
VL  - 7
IS  - 3
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8×10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8×10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation.
AU  - Mittelstraß, K.
AU  - Ried, J.S.
AU  - Yu, Z.
AU  - Krumsiek, J.
AU  - Gieger, C.
AU  - Prehn, C.
AU  - Römisch-Margl, W.
AU  - Polonikov, A.*
AU  - Peters, A.
AU  - Theis, F.J.
AU  - Meitinger, T.
AU  - Kronenberg, F.*
AU  - Weidinger, S.*
AU  - Wichmann, H.-E.
AU  - Suhre, K.*
AU  - Wang-Sattler, R.
AU  - Adamski, J.
AU  - Illig, T.
C1  - 5444
C2  - 28779
TI  - Discovery of sexual dimorphisms in metabolic and genetic biomarkers.
JO  - PLoS Genet.
VL  - 7
IS  - 8
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - White blood cell (WBC) count is a common clinical measure from complete blood count assays, and it varies widely among healthy individuals. Total WBC count and its constituent subtypes have been shown to be moderately heritable, with the heritability estimates varying across cell types. We studied 19,509 subjects from seven cohorts in a discovery analysis, and 11,823 subjects from ten cohorts for replication analyses, to determine genetic factors influencing variability within the normal hematological range for total WBC count and five WBC subtype measures. Cohort specific data was supplied by the CHARGE, HeamGen, and INGI consortia, as well as independent collaborative studies. We identified and replicated ten associations with total WBC count and five WBC subtypes at seven different genomic loci (total WBC count-6p21 in the HLA region, 17q21 near ORMDL3, and CSF3; neutrophil count-17q21; basophil count- 3p21 near RPN1 and C3orf27; lymphocyte count-6p21, 19p13 at EPS15L1; monocyte count-2q31 at ITGA4, 3q21, 8q24 an intergenic region, 9q31 near EDG2), including three previously reported associations and seven novel associations. To investigate functional relationships among variants contributing to variability in the six WBC traits, we utilized gene expression- and pathways-based analyses. We implemented gene-clustering algorithms to evaluate functional connectivity among implicated loci and showed functional relationships across cell types. Gene expression data from whole blood was utilized to show that significant biological consequences can be extracted from our genome-wide analyses, with effect estimates for significant loci from the meta-analyses being highly corellated with the proximal gene expression. In addition, collaborative efforts between the groups contributing to this study and related studies conducted by the COGENT and RIKEN groups allowed for the examination of effect homogeneity for genome-wide significant associations across populations of diverse ancestral backgrounds.
AU  - Nalls, M.A.*
AU  - Couper, D.J.*
AU  - Tanaka, T.*
AU  - van Rooij, F.J.*
AU  - Chen, M.H.*
AU  - Smith, A.V.*
AU  - Toniolo, D.*
AU  - Zakai, N.A.*
AU  - Yang, Q.*
AU  - Greinacher, A.*
AU  - Wood, A.R.*
AU  - Garcia, M.*
AU  - Gasparini, P.*
AU  - Liu, Y.*
AU  - Lumley, T.*
AU  - Folsom, A.R.*
AU  - Reiner, A.P.*
AU  - Gieger, C.
AU  - Lagou, V.*
AU  - Felix, J.F.*
AU  - Völzke, H.*
AU  - Gouskova, N.A.*
AU  - Biffi, A.*
AU  - Döring, A.
AU  - Völker, U.*
AU  - Chong, S.*
AU  - Wiggins, K.L.*
AU  - Rendon, A.*
AU  - Dehghan, A.*
AU  - Moore, M.*
AU  - Taylor, K.*
AU  - Wilson, J.G.*
AU  - Lettre, G.*
AU  - Hofman, A.*
AU  - Bis, J.C.*
AU  - Pirastu, N.*
AU  - Fox, C.S.*
AU  - Meisinger, C.*
AU  - Sambrook, J.*
AU  - Arepalli, S.*
AU  - Nauck, M.*
AU  - Prokisch, H.
AU  - Stephens, J.*
AU  - Glazer, N.L.*
AU  - Cupples, L.A.*
AU  - Okada, Y.*
AU  - Takahashi, A.*
AU  - Kamatani, Y.*
AU  - Matsuda, K.*
AU  - Tsunoda, T.*
AU  - Kubo, M.*
AU  - Nakamura, Y.*
AU  - Yamamoto, K.*
AU  - Kamatani, N.*
AU  - Stumvoll, M.*
AU  - Tönjes, A.*
AU  - Prokopenko, I.*
AU  - Illig, T.
AU  - Patel, K.V.*
AU  - Garner, S.F.*
AU  - Kühnel, B.
AU  - Mangino, M.*
AU  - Oostra, B.A.*
AU  - Thein, S.L.*
AU  - Coresh, J.*
AU  - Wichmann, H.-E.
AU  - Menzel, S.*
AU  - Lin, J.*
AU  - Pistis, G.*
AU  - Uitterlinden, A.G.*
AU  - Spector, T.D.*
AU  - Teumer, A.*
AU  - Eiriksdottir, G.*
AU  - Gudnason, V.*
AU  - Bandinelli, S.*
AU  - Frayling, T.M.*
AU  - Chakravarti, A.*
AU  - van Duijn, C.M.*
AU  - Melzer, D.*
AU  - Ouwehand, W.H.*
AU  - Levy, D.*
AU  - Boerwinkle, E.*
AU  - Singleton, A.B.*
AU  - Hernandez, D.G.*
AU  - Longo, D.L.*
AU  - Soranzo, N.*
AU  - Witteman, J.C.*
AU  - Psaty, B.M.*
AU  - Ferrucci, L.*
AU  - Harris, T.B.*
AU  - O'Donnell, C.J.*
AU  - Ganesh, S.K.*
C1  - 6440
C2  - 28694
TI  - Multiple loci are associated with white blood cell phenotypes.
JO  - PLoS Genet.
VL  - 7
IS  - 6
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - We have performed a metabolite quantitative trait locus (mQTL) study of the (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) metabolome in humans, building on recent targeted knowledge of genetic drivers of metabolic regulation. Urine and plasma samples were collected from two cohorts of individuals of European descent, with one cohort comprised of female twins donating samples longitudinally. Sample metabolite concentrations were quantified by (1)H NMR and tested for association with genome-wide single-nucleotide polymorphisms (SNPs). Four metabolites' concentrations exhibited significant, replicable association with SNP variation (8.6×10(-11)
AU  - Nicholson, G.*
AU  - Rantalainen, M.*
AU  - Li, J.V.*
AU  - Maher, AD.*
AU  - Malmodin, D.*
AU  - Ahmadi, K.R.*
AU  - Faber, J.H.*
AU  - Barrett, A.*
AU  - Min, J.L.*
AU  - Rayner, N.W.*
AU  - Toft, H.*
AU  - Krestyaninova, M.*
AU  - Viksna, J.*
AU  - Neogi, S.G.*
AU  - Dumas, M.E.*
AU  - Sarkans, U*
AU  - MolPAGE Consortium (*)
AU  - Donnelly, P.*
AU  - Illig, T.
AU  - Adamski, J.
AU  - Suhre, K.
AU  - Allen, M.*
AU  - Zondervan, K.T.*
AU  - Spector, T.D.*
AU  - Nicholson, J.K.*
AU  - Lindon, J.C.*
AU  - Baunsgaard, D.*
AU  - Holmes, E.*
AU  - McCarthy, M.I.*
AU  - Holmes, C.C.*
C1  - 6522
C2  - 28905
TI  - A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection.
JO  - PLoS Genet.
VL  - 7
IS  - 9
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Testosterone concentrations in men are associated with cardiovascular morbidity, osteoporosis, and mortality and are affected by age, smoking, and obesity. Because of serum testosterone's high heritability, we performed a meta-analysis of genome-wide association data in 8,938 men from seven cohorts and followed up the genome-wide significant findings in one in silico (n = 871) and two de novo replication cohorts (n = 4,620) to identify genetic loci significantly associated with serum testosterone concentration in men. All these loci were also associated with low serum testosterone concentration defined as <300 ng/dl. Two single-nucleotide polymorphisms at the sex hormone-binding globulin (SHBG) locus (17p13-p12) were identified as independently associated with serum testosterone concentration (rs12150660, p = 1.2×10(-41) and rs6258, p = 2.3×10(-22)). Subjects with ≥ 3 risk alleles of these variants had 6.5-fold higher risk of having low serum testosterone than subjects with no risk allele. The rs5934505 polymorphism near FAM9B on the X chromosome was also associated with testosterone concentrations (p = 5.6×10(-16)). The rs6258 polymorphism in exon 4 of SHBG affected SHBG's affinity for binding testosterone and the measured free testosterone fraction (p<0.01). Genetic variants in the SHBG locus and on the X chromosome are associated with a substantial variation in testosterone concentrations and increased risk of low testosterone. rs6258 is the first reported SHBG polymorphism, which affects testosterone binding to SHBG and the free testosterone fraction and could therefore influence the calculation of free testosterone using law-of-mass-action equation.
AU  - Ohlsson, C.*
AU  - Wallaschofski, H.*
AU  - Lunetta, K.L.*
AU  - Stolk, L.*
AU  - Perry, J.R.*
AU  - Koster, A.*
AU  - Petersen, A.-K.
AU  - Eriksson, J.*
AU  - Lehtimäki, T.*
AU  - Huhtaniemi, I.T.*
AU  - Hammond, G.L.*
AU  - Maggio, M.*
AU  - Coviello, A.D*
AU  - EMAS Study Group (*)
AU  - Ferrucci, L.*
AU  - Heier, M.
AU  - Hofman, A.*
AU  - Holliday, K.L.*
AU  - Jansson, J.O.*
AU  - Kähönen, M.*
AU  - Karasik, D.*
AU  - Karlsson, M.K.*
AU  - Kiel, D.P.*
AU  - Liu, Y.*
AU  - Ljunggren, O.*
AU  - Lorentzon, M.*
AU  - Lyytikäinen, L.-P.*
AU  - Meitinger, T.
AU  - Mellström, D.*
AU  - Melzer, D.*
AU  - Miljkovic, I.*
AU  - Nauck, M.*
AU  - Nilsson, M.*
AU  - Penninx, B.*
AU  - Pye, S.R.*
AU  - Vasan, R.S.*
AU  - Reincke, M.*
AU  - Rivadeneira, F.*
AU  - Tajar, A.*
AU  - Teumer, A.*
AU  - Uitterlinden, A.G.*
AU  - Ulloor, J.*
AU  - Viikari, J.*
AU  - Völker, U.*
AU  - Völzke, H.*
AU  - Wichmann, H.-E.
AU  - Wu, T.S.*
AU  - Zhuang, W.V.*
AU  - Ziv, E.*
AU  - Wu, F.C.*
AU  - Raitakari, O.*
AU  - Eriksson, A.*
AU  - Bidlingmaier, M.*
AU  - Harris, T.B.*
AU  - Murray, A.*
AU  - de Jong, F.H.*
AU  - Murabito, J.M.*
AU  - Bhasin, S.*
AU  - Vandenput, L.*
AU  - Haring, R.*
C1  - 6699
C2  - 29136
TI  - Genetic determinants of serum testosterone concentrations in men.
JO  - PLoS Genet.
VL  - 7
IS  - 10
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The PR interval on the electrocardiogram reflects atrial and atrioventricular nodal conduction time. The PR interval is heritable, provides important information about arrhythmia risk, and has been suggested to differ among human races. Genome-wide association (GWA) studies have identified common genetic determinants of the PR interval in individuals of European and Asian ancestry, but there is a general paucity of GWA studies in individuals of African ancestry. We performed GWA studies in African American individuals from four cohorts (n = 6,247) to identify genetic variants associated with PR interval duration. Genotyping was performed using the Affymetrix 6.0 microarray. Imputation was performed for 2.8 million single nucleotide polymorphisms (SNPs) using combined YRI and CEU HapMap phase II panels. We observed a strong signal (rs3922844) within the gene encoding the cardiac sodium channel (SCN5A) with genome-wide significant association (p<2.5 x 10⁻⁸) in two of the four cohorts and in the meta-analysis. The signal explained 2% of PR interval variability in African Americans (beta  = 5.1 msec per minor allele, 95% CI  = 4.1-6.1, p = 3 x 10⁻²³). This SNP was also associated with PR interval (beta = 2.4 msec per minor allele, 95% CI = 1.8-3.0, p = 3 x 10⁻¹⁶) in individuals of European ancestry (n = 14,042), but with a smaller effect size (p for heterogeneity <0.001) and variability explained (0.5%). Further meta-analysis of the four cohorts identified genome-wide significant associations with SNPs in SCN10A (rs6798015), MEIS1 (rs10865355), and TBX5 (rs7312625) that were highly correlated with SNPs identified in European and Asian GWA studies. African ancestry was associated with increased PR duration (13.3 msec, p = 0.009) in one but not the other three cohorts. Our findings demonstrate the relevance of common variants to African Americans at four loci previously associated with PR interval in European and Asian samples and identify an association signal at one of these loci that is more strongly associated with PR interval in African Americans than in Europeans.
AU  - Smith, J.G.*
AU  - Magnani, J.W.*
AU  - Palmer, C.*
AU  - Meng, Y.A.*
AU  - Soliman, E.Z.*
AU  - Musani, S.K.*
AU  - Kerr, K.F.*
AU  - Schnabel, R.B.*
AU  - Lubitz, S.A.*
AU  - Sotoodehnia, N.*
AU  - Redline, S.*
AU  - Pfeufer, A.
AU  - Müller, M.
AU  - Evans, D.S.*
AU  - Nalls, M.A.*
AU  - Liu, Y.*
AU  - Newman, A.B.*
AU  - Zonderman, A.B.*
AU  - Evans, M.K.*
AU  - Deo, R.*
AU  - Ellinor, P.T.*
AU  - Paltoo, D.N.*
AU  - Newton-Cheh, C.*
AU  - Benjamin, E.J.*
AU  - Mehra, R.*
AU  - Alonso, A.*
AU  - Heckbert, S.R.*
AU  - Fox, E.R.*
C1  - 4213
C2  - 28791
TI  - Genome-wide association studies of the PR interval in African Americans.
JO  - PLoS Genet.
VL  - 7
IS  - 2
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8)) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.
AU  - Speliotes, E.K.*
AU  - Yerges-Armstrong, L.M.*
AU  - Wu, J.*
AU  - Hernaez, R.*
AU  - Kim, L.J.*
AU  - Palmer, C.D.*
AU  - Gudnason, V.*
AU  - Eiriksdottir, G.*
AU  - Garcia, M.E.*
AU  - Launer, L.J.*
AU  - Nalls, M.A.*
AU  - Clark, J.M.*
AU  - Mitchell, B.D.*
AU  - Shuldiner, A.R.*
AU  - Butler, J.L.*
AU  - Tomas, M.*
AU  - Hoffmann, U.*
AU  - Hwang, S.J.*
AU  - Massaro, J.M.*
AU  - O'Donnell, C.J.*
AU  - Sahani, D.V.*
AU  - Salomaa, V.*
AU  - Schadt, E.E.*
AU  - Schwartz, S.M.*
AU  - Siscovick, D.S.*
AU  - NASH Clinical Research Network (*)
AU  - GIANT Consortium (Heid, I.M.
AU  - Thiering, E.
AU  - Gieger, C.
AU  - Grallert, H.
AU  - Meitinger, T.
AU  - Heinrich, J.
AU  - Illig, T.
AU  - Peters, A.
AU  - Wichmann, H.-E.)
AU  - MAGIC Investigators (Grallert, H.
AU  - Meisinger, C.
AU  - Thorand, B.
AU  - Wichmann, H.-E.
AU  - Gieger, C.
AU  - Illig, T.)
AU  - Voight, B.F.*
AU  - Carr, J.J.*
AU  - Feitosa, M.F.*
AU  - Harris, T.B.*
AU  - Fox, C.S.*
AU  - Smith, A.V.*
AU  - Kao, W.H.*
AU  - Hirschhorn, J.N.*
AU  - Borecki, I.B.*
AU  - GOLD Consortium (*)
C1  - 5049
C2  - 28814
TI  - Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits.
JO  - PLoS Genet.
VL  - 7
IS  - 3
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.
AU  - Surakka, I.*
AU  - Isaacs, A.*
AU  - Karssen, L.C.*
AU  - Laurila, P.P.*
AU  - Middelberg, R.P.*
AU  - Tikkanen, E.*
AU  - Ried, J.S.
AU  - Lamina, C.*
AU  - Mangino, M.*
AU  - Igl, W.*
AU  - Hottenga, J.J.*
AU  - Lagou, V.*
AU  - van der, Harst, P.*
AU  - Mateo, Leach, I.*
AU  - Esko, T.*
AU  - Kutalik, Z.*
AU  - Wainwright, N.W.*
AU  - Struchalin, M.V.*
AU  - Sarin, A.P.*
AU  - Kangas, A.J.*
AU  - Viikari, J.S.*
AU  - Perola, M.*
AU  - Rantanen, T.*
AU  - Petersen, A.-K.
AU  - Soininen, P.*
AU  - Johansson, A.*
AU  - Soranzo, N.*
AU  - Heath, A.C.*
AU  - Papamarkou, T.*
AU  - Prokopenko, I.*
AU  - Tönjes, A.*
AU  - Kronenberg, F.*
AU  - Döring, A.
AU  - Rivadeneira, F.*
AU  - Montgomery, G.W.*
AU  - Whitfield, JB.*
AU  - Kähönen, M.*
AU  - Lehtimäki, T.*
AU  - Freimer, N.B.*
AU  - Willemsen, G.*
AU  - de Geus, E.J.*
AU  - Palotie, A.*
AU  - Sandhu, M.S.*
AU  - Waterworth, D.M.*
AU  - Metspalu, A.*
AU  - Stumvoll, M.*
AU  - Uitterlinden, A.G.*
AU  - Jula, A.*
AU  - Navis, G.*
AU  - Wijmenga, C.*
AU  - Wolffenbuttel, B.H.*
AU  - Taskinen, M.R.*
AU  - Ala-Korpela, M.*
AU  - Kaprio, J.*
AU  - Kyvik, K.O.*
AU  - Boomsma, D.I.*
AU  - Pedersen, N.L.*
AU  - Gyllensten, U.*
AU  - Wilson, J.F.*
AU  - Rudan, I.*
AU  - Campbell, H.*
AU  - Pramstaller, P.P.*
AU  - Spector, T.D.*
AU  - Witteman, J.C.*
AU  - Eriksson, J.G.*
AU  - Salomaa, V.*
AU  - Oostra, B.A.*
AU  - Raitakari, O.T.*
AU  - Wichmann, H.-E.
AU  - Gieger, C.
AU  - Jarvelin, M.R.*
AU  - Martin, N.G.*
AU  - Hofman, A.*
AU  - McCarthy, M.I.*
AU  - Peltonen, L.*
AU  - van Duijn, C.M.*
AU  - Aulchenko, Y.S.*
AU  - Ripatti, S*
AU  - ENGAGE Consortium (*)
C1  - 6781
C2  - 29261
TI  - A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol.
JO  - PLoS Genet.
VL  - 7
IS  - 10
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Restless legs syndrome (RLS) is a sensorimotor disorder with an age-dependent prevalence of up to 10% in the general population above 65 years of age. Affected individuals suffer from uncomfortable sensations and an urge to move in the lower limbs that occurs mainly in resting situations during the evening or at night. Moving the legs or walking leads to an improvement of symptoms. Concomitantly, patients report sleep disturbances with consequences such as reduced daytime functioning. We conducted a genome-wide association study (GWA) for RLS in 922 cases and 1,526 controls (using 301,406 SNPs) followed by a replication of 76 candidate SNPs in 3,935 cases and 5,754 controls, all of European ancestry. Herein, we identified six RLS susceptibility loci of genome-wide significance, two of them novel: an intergenic region on chromosome 2p14 (rs6747972, P = 9.03 × 10(-11), OR = 1.23) and a locus on 16q12.1 (rs3104767, P = 9.4 × 10(-19), OR = 1.35) in a linkage disequilibrium block of 140 kb containing the 5'-end of TOX3 and the adjacent non-coding RNA BC034767.
AU  - Winkelmann, J.
AU  - Czamara, D.*
AU  - Schormair, B.
AU  - Knauf, F.
AU  - Schulte, E.C.*
AU  - Trenkwalder, C.*
AU  - Dauvilliers, Y.*
AU  - Polo, O.*
AU  - Högl, B.*
AU  - Berger, K.*
AU  - Fuhs, A.*
AU  - Gross, N.*
AU  - Stiasny-Kolster, K.*
AU  - Oertel, W.*
AU  - Bachmann, C.G.*
AU  - Paulus, W.*
AU  - Xiong, L.*
AU  - Montplaisir, J.*
AU  - Rouleau, G.A.*
AU  - Fietze, I.*
AU  - Vávrová, J.*
AU  - Kemlink, D.*
AU  - Sonka, K.*
AU  - Nevsimalova, S.*
AU  - Lin, S.C.*
AU  - Wszolek, Z.*
AU  - Vilariño-Güell, C.*
AU  - Farrer, M.J.*
AU  - Gschliesser, V.*
AU  - Frauscher, B.*
AU  - Falkenstetter, T.*
AU  - Poewe, W.*
AU  - Allen, R.P.*
AU  - Earley, C.J.*
AU  - Ondo, W.G.*
AU  - Le, W.D.*
AU  - Spieler, D.
AU  - Kaffe, M.
AU  - *
AU  - Kettunen, J.*
AU  - Perola, M.*
AU  - Silander, K.*
AU  - Cournu-Rebeix, I.*
AU  - Francavilla, M.*
AU  - Fontenille, C.*
AU  - Fontaine, B.*
AU  - Vodicka, P.*
AU  - Prokisch, H.
AU  - Lichtner, P.
AU  - Peppard, P.*
AU  - Faraco, J.*
AU  - Mignot, E.*
AU  - Gieger, C.
AU  - Illig, T.
AU  - Wichmann, H.-E.
AU  - Müller-Myhsok, B.*
AU  - Meitinger, T.
C1  - 6502
C2  - 28820
TI  - Genome-wide association study identifies novel restless legs syndrome susceptibility loci on 2p14 and 16q12.1.
JO  - PLoS Genet.
VL  - 7
IS  - 7
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Neuronal ceroid lipofuscinosis (NCL) is a progressive neurodegenerative disease characterized by brain and retinal atrophy and the intracellular accumulation of autofluorescent lysosomal storage bodies resembling lipofuscin in neurons and other cells. Tibetan terriers show a late-onset lethal form of NCL manifesting first visible signs at 5-7 years of age. Genome-wide association analyses for 12 Tibetan-terrier-NCL-cases and 7 Tibetan-terrier controls using the 127K canine Affymetrix SNP chip and mixed model analysis mapped NCL to dog chromosome (CFA) 2 at 83.71-84.72 Mb. Multipoint linkage and association analyses in 376 Tibetan terriers confirmed this genomic region on CFA2. A mutation analysis for 14 positional candidate genes in two NCL-cases and one control revealed a strongly associated single nucleotide polymorphism (SNP) in the MAPK PM20/PM21 gene and a perfectly with NCL associated single base pair deletion (c.1620delG) within exon 16 of the ATP13A2 gene. The c.1620delG mutation in ATP13A2 causes skipping of exon 16 presumably due to a broken exonic splicing enhancer motif. As a result of this mutation, ATP13A2 lacks 69 amino acids. All known 24 NCL cases were homozygous for this deletion and all obligate 35 NCL-carriers were heterozygous. In a sample of 144 dogs from eleven other breeds, the c.1620delG mutation could not be found. Knowledge of the causative mutation for late-onset NCL in Tibetan terrier allows genetic testing of these dogs to avoid matings of carrier animals. ATP13A2 mutations have been described in familial Parkinson syndrome (PARK9). Tibetan terriers with these mutations provide a valuable model for a PARK9-linked disease and possibly for manganese toxicity in synucleinopathies.
AU  - Wöhlke, A.
AU  - Philipp, U.
AU  - Bock, P.
AU  - Beineke, A.
AU  - Lichtner, P.*
AU  - Meitinger, T.*
AU  - Distl, O.
A2  - Barsh, G.S.*
C1  - 6709
C2  - 29146
TI  - A one base pair deletion in the canine ATP13A2 gene causes exon skipping and late-onset neuronal ceroid lipofuscinosis in the Tibetan terrier.
JO  - PLoS Genet.
VL  - 7
IS  - 10
PB  - Public Library of Science
PY  - 2011
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The most common Rhodopsin (Rh) mutation associated with autosomal dominant retinitis pigmentosa (ADRP) in North America is the substitution of proline 23 by histidine (Rh(P23H)). Unlike the wild-type Rh, mutant Rh(P23H) exhibits folding defects and forms intracellular aggregates. The mechanisms responsible for the recognition and clearance of misfolded Rh(P23H) and their relevance to photoreceptor neuron (PN) degeneration are poorly understood. Folding-deficient membrane proteins are subjected to Endoplasmic Reticulum (ER) quality control, and we have recently shown that Rh(P23H) is a substrate of the ER-associated degradation (ERAD) effector VCP/ter94, a chaperone that extracts misfolded proteins from the ER (a process called retrotranslocation) and facilitates their proteasomal degradation. Here, we used Drosophila, in which Rh1(P37H) (the equivalent of mammalian Rh(P23H)) is expressed in PNs, and found that the endogenous Rh1 is required for Rh1(P37H) toxicity. Genetic inactivation of VCP increased the levels of misfolded Rh1(P37H) and further activated the Ire1/Xbp1 ER stress pathway in the Rh1(P37H) retina. Despite this, Rh1(P37H) flies with decreased VCP function displayed a potent suppression of retinal degeneration and blindness, indicating that VCP activity promotes neurodegeneration in the Rh1(P37H) retina. Pharmacological treatment of Rh1(P37H) flies with the VCP/ERAD inhibitor Eeyarestatin I or with the proteasome inhibitor MG132 also led to a strong suppression of retinal degeneration. Collectively, our findings raise the possibility that excessive retrotranslocation and/or degradation of visual pigment is a primary cause of PN degeneration.
AU  - Griciuc, A.
AU  - Aron, L.*
AU  - Roux, M.J.*
AU  - Klein, R.*
AU  - Giangrande, A.*
AU  - Ueffing, M.
C1  - 5153
C2  - 27764
TI  - Inactivation of VCP/ter94 suppresses retinal pathology caused by misfolded rhodopsin in Drosophila.
JO  - PLoS Genet.
VL  - 6
IS  - 8
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Genome-wide association studies (GWAS) have identified 38 larger genetic regions affecting classical blood lipid levels without adjusting for important environmental influences. We modeled diet and physical activity in a GWAS in order to identify novel loci affecting total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels. The Swedish (SE) EUROSPAN cohort (N(SE) = 656) was screened for candidate genes and the non-Swedish (NS) EUROSPAN cohorts (N(NS) = 3,282) were used for replication. In total, 3 SNPs were associated in the Swedish sample and were replicated in the non-Swedish cohorts. While SNP rs1532624 was a replication of the previously published association between CETP and HDL cholesterol, the other two were novel findings. For the latter SNPs, the p-value for association was substantially improved by inclusion of environmental covariates: SNP rs5400 (p(SE,unadjusted) = 3.6 x 10(-5), p(SE,adjusted) = 2.2 x 10(-6), p(NS,unadjusted) = 0.047) in the SLC2A2 (Glucose transporter type 2) and rs2000999 (p(SE,unadjusted) = 1.1 x 10(-3), p(SE,adjusted) = 3.8 x 10(-4), p(NS,unadjusted) = 0.035) in the HP gene (Haptoglobin-related protein precursor). Both showed evidence of association with total cholesterol. These results demonstrate that inclusion of important environmental factors in the analysis model can reveal new genetic susceptibility loci.
AU  - Igl, W.*
AU  - Johansson, A.*
AU  - Wilson, J.F.*
AU  - Wild, S.H.*
AU  - Polasek, O.*
AU  - Hayward, C.*
AU  - Vitart, V.*
AU  - Hastie, N.*
AU  - Rudan, P.*
AU  - Gnewuch, C.*
AU  - Schmitz, G.*
AU  - Meitinger, T.
AU  - Pramstaller, P.P.*
AU  - Hicks, A.A.*
AU  - Oostra, B.A.*
AU  - van Duijn, C.M.*
AU  - Rudan, I.*
AU  - Wright, A.*
AU  - Campbell, H.*
AU  - Gyllensten, U.*
C1  - 878
C2  - 27160
TI  - Modeling of environmental effects in genome-wide association studies identifies SLC2A2 and HP as novel loci influencing serum cholesterol levels.
JO  - PLoS Genet.
VL  - 6
IS  - 1
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - There is increasing evidence that the microcirculation plays an important role in the pathogenesis of cardiovascular diseases. Changes in retinal vascular caliber reflect early microvascular disease and predict incident cardiovascular events. We performed a genome-wide association study to identify genetic variants associated with retinal vascular caliber. We analyzed data from four population-based discovery cohorts with 15,358 unrelated Caucasian individuals, who are members of the Cohort for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and replicated findings in four independent Caucasian cohorts (n  =  6,652). All participants had retinal photography and retinal arteriolar and venular caliber measured from computer software. In the discovery cohorts, 179 single nucleotide polymorphisms (SNP) spread across five loci were significantly associated (p<5.0×10(-8)) with retinal venular caliber, but none showed association with arteriolar caliber. Collectively, these five loci explain 1.0%-3.2% of the variation in retinal venular caliber. Four out of these five loci were confirmed in independent replication samples. In the combined analyses, the top SNPs at each locus were: rs2287921 (19q13; p  =  1.61×10(-25), within the RASIP1 locus), rs225717 (6q24; p = 1.25×10(-16), adjacent to the VTA1 and NMBR loci), rs10774625 (12q24; p  =  2.15×10(-13), in the region of ATXN2,SH2B3 and PTPN11 loci), and rs17421627 (5q14; p = 7.32×10(-16), adjacent to the MEF2C locus). In two independent samples, locus 12q24 was also associated with coronary heart disease and hypertension. Our population-based genome-wide association study demonstrates four novel loci associated with retinal venular caliber, an endophenotype of the microcirculation associated with clinical cardiovascular disease. These data provide further insights into the contribution and biological mechanisms of microcirculatory changes that underlie cardiovascular disease.
AU  - Ikram, M.K.*
AU  - Sim, X.*
AU  - Jensen, R.A.*
AU  - Cotch, M.F.*
AU  - Hewitt, A.W.*
AU  - Ikram, M.A.*
AU  - Wang, J.J.*
AU  - Klein, R.*
AU  - Klein, B.E.*
AU  - Breteler, M.M.*
AU  - Cheung, N.*
AU  - Liew, G.*
AU  - Mitchell, P.*
AU  - Uitterlinden, A.G.*
AU  - Rivadeneira, F.*
AU  - Hofman, A.*
AU  - de Jong, P.T.*
AU  - van Duijn, C.M.*
AU  - Kao, L.*
AU  - Cheng, C.Y.*
AU  - Smith, A.V.*
AU  - Glazer, N.L.*
AU  - Lumley, T.*
AU  - McKnight, B.*
AU  - Psaty, B.M.*
AU  - Jonasson, F.*
AU  - Eiriksdottir, G.*
AU  - Aspelund, T.*
AU  - Global BPgen Consortium (Döring, A.
AU  - Gieger, C.
AU  - Illig, T.
AU  - Meitinger, T.
AU  - Pfeufer, A.
AU  - Wichmann, H.-E.)
AU  - Harris, T.B.*
AU  - Launer, L.J.*
AU  - Taylor, K.D.*
AU  - Li, X.*
AU  - Iyengar, S.K.*
AU  - Xi, Q.*
AU  - Sivakumaran, T.A.*
AU  - Mackey, D.A.*
AU  - MacGregor, S.*
AU  - Martin, N.G.*
AU  - Young, T.L.*
AU  - Bis, J.C.*
AU  - Wiggins, K.L.*
AU  - Heckbert, S.R.*
AU  - Hammond, C.J.*
AU  - Andrew, T.*
AU  - Fahy, S.*
AU  - Attia, J.*
AU  - Holliday, E.G.*
AU  - Scott, R.J.*
AU  - Islam, F.M.*
AU  - Rotter, J.I.*
AU  - McAuley, A.K.*
AU  - Boerwinkle, E.*
AU  - Tai, E.S.*
AU  - Gudnason, V.*
AU  - Siscovick, D.S.*
AU  - Vingerling, J.R.*
AU  - Wong, T.Y.*
C1  - 4664
C2  - 28527
TI  - Four novel Loci (19q13, 6q24, 12q24, and 5q14) influence the microcirculation in vivo.
JO  - PLoS Genet.
VL  - 6
IS  - 10
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Elevated levels of acute-phase serum amyloid A (A-SAA) cause amyloidosis and are a risk factor for atherosclerosis and its clinical complications, type 2 diabetes, as well as various malignancies. To investigate the genetic basis of A-SAA levels, we conducted the first genome-wide association study on baseline A-SAA concentrations in three population-based studies (KORA, TwinsUK, Sorbs) and one prospective case cohort study (LURIC), including a total of 4,212 participants of European descent, and identified two novel genetic susceptibility regions at 11p15.5-p13 and 1p31. The region at 11p15.5-p13 (rs4150642; p = 3.20×10(-111)) contains serum amyloid A1 (SAA1) and the adjacent general transcription factor 2 H1 (GTF2H1), Hermansky-Pudlak Syndrome 5 (HPS5), lactate dehydrogenase A (LDHA), and lactate dehydrogenase C (LDHC). This region explains 10.84% of the total variation of A-SAA levels in our data, which makes up 18.37% of the total estimated heritability. The second region encloses the leptin receptor (LEPR) gene at 1p31 (rs12753193; p = 1.22×10(-11)) and has been found to be associated with CRP and fibrinogen in previous studies. Our findings demonstrate a key role of the 11p15.5-p13 region in the regulation of baseline A-SAA levels and provide confirmative evidence of the importance of the 1p31 region for inflammatory processes and the close interplay between A-SAA, leptin, and other acute-phase proteins.
AU  - Marzi, C.
AU  - Albrecht, E.
AU  - Hysi, P.G.*
AU  - Lagou, V.*
AU  - Waldenberger, M.
AU  - Tönjes, A.*
AU  - Prokopenko, I.*
AU  - Heim, K.
AU  - Blackburn, H.*
AU  - Ried, J.S.
AU  - Kleber, M.E.*
AU  - Mangino, M.*
AU  - Thorand, B.
AU  - Peters, A.
AU  - Hammond, C.J.*
AU  - Grallert, H.
AU  - Boehm, B.O.*
AU  - Kovacs, P.*
AU  - Geistlinger, L.
AU  - Prokisch, H.
AU  - Winkelmann, B.R.*
AU  - Spector, T.D.*
AU  - Wichmann, H.-E.
AU  - Stumvoll, M.*
AU  - Soranzo, N.*
AU  - Marz, W.*
AU  - Koenig, W.*
AU  - Illig, T.
AU  - Gieger, C.
C1  - 6090
C2  - 28052
TI  - Genome-wide association study identifies two novel regions at 11p15.5-p13 and 1p31 with major impact on acute-phase serum amyloid A.
JO  - PLoS Genet.
VL  - 6
IS  - 11
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Magnesium, potassium, and sodium, cations commonly measured in serum, are involved in many physiological processes including energy metabolism, nerve and muscle function, signal transduction, and fluid and blood pressure regulation. To evaluate the contribution of common genetic variation to normal physiologic variation in serum concentrations of these cations, we conducted genome-wide association studies of serum magnesium, potassium, and sodium concentrations using approximately 2.5 million genotyped and imputed common single nucleotide polymorphisms (SNPs) in 15,366 participants of European descent from the international CHARGE Consortium. Study-specific results were combined using fixed-effects inverse-variance weighted meta-analysis. SNPs demonstrating genome-wide significant (p<5 x 10(-8)) or suggestive associations (p<4 x 10(-7)) were evaluated for replication in an additional 8,463 subjects of European descent. The association of common variants at six genomic regions (in or near MUC1, ATP2B1, DCDC5, TRPM6, SHROOM3, and MDS1) with serum magnesium levels was genome-wide significant when meta-analyzed with the replication dataset. All initially significant SNPs from the CHARGE Consortium showed nominal association with clinically defined hypomagnesemia, two showed association with kidney function, two with bone mineral density, and one of these also associated with fasting glucose levels. Common variants in CNNM2, a magnesium transporter studied only in model systems to date, as well as in CNNM3 and CNNM4, were also associated with magnesium concentrations in this study. We observed no associations with serum sodium or potassium levels exceeding p<4 x 10(-7). Follow-up studies of newly implicated genomic loci may provide additional insights into the regulation and homeostasis of human serum magnesium levels.
AU  - Meyer, T.E.*
AU  - Verwoert, G.C.*
AU  - Hwang, S.J.*
AU  - Glazer, N.L.*
AU  - Smith, A.V.*
AU  - van Rooij, F.J.A.*
AU  - Ehret, G.B.*
AU  - Boerwinkle, E.*
AU  - Felix, J.F.*
AU  - Leak, T.S.*
AU  - Harris, T.B.*
AU  - Yang, Q.*
AU  - Dehghan, A.*
AU  - Aspelund, T.*
AU  - Katz, R.*
AU  - Homuth, G.*
AU  - Kocher, T.*
AU  - Rettig, R.*
AU  - Ried, J.S.
AU  - Gieger, C.
AU  - Prucha, H.*
AU  - Pfeufer, A.
AU  - Meitinger, T.
AU  - Coresh, J.*
AU  - Hofman, A.*
AU  - Sarnak, M.J.*
AU  - Chen, Y.D.I.*
AU  - Uitterlinden, A.G.*
AU  - Chakravarti, A.*
AU  - Psaty, B.M.*
AU  - van Duijn, C.M.*
AU  - Kao, W.H.L.*
AU  - Witteman, J.C.M.*
AU  - Gudnason, V.*
AU  - Siscovick, D.S.*
AU  - Fox, C.S.*
AU  - Köttgen, A.*
C1  - 4121
C2  - 27470
TI  - Genome-wide association studies of serum magnesium, potassium, and sodium concentrations identify six loci influencing serum magnesium levels.
JO  - PLoS Genet.
VL  - 6
IS  - 8
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - To get beyond the "low-hanging fruits" so far identified by genome-wide association (GWA) studies, new methods must be developed in order to discover the numerous remaining genes that estimates of heritability indicate should be contributing to complex human phenotypes, such as obesity. Here we describe a novel integrative method for complex disease gene identification utilizing both genome-wide transcript profiling of adipose tissue samples and consequent analysis of genome-wide association data generated in large SNP scans. We infer causality of genes with obesity by employing a unique set of monozygotic twin pairs discordant for BMI (n = 13 pairs, age 24-28 years, 15.4 kg mean weight difference) and contrast the transcript profiles with those from a larger sample of non-related adult individuals (N = 77). Using this approach, we were able to identify 27 genes with possibly causal roles in determining the degree of human adiposity. Testing for association of SNP variants in these 27 genes in the population samples of the large ENGAGE consortium (N = 21,000) revealed a significant deviation of P-values from the expected (P = 4x10(-4)). A total of 13 genes contained SNPs nominally associated with BMI. The top finding was blood coagulation factor F13A1 identified as a novel obesity gene also replicated in a second GWA set of approximately 2,000 individuals. This study presents a new approach to utilizing gene expression studies for informing choice of candidate genes for complex human phenotypes, such as obesity.
AU  - Naukkarinen, J.*
AU  - Surakka, I.*
AU  - Pietiläinen, K.H.*
AU  - Rissanen, A.*
AU  - Salomaa, V.*
AU  - Ripatti, S.*
AU  - Yki-Järvinen, H.*
AU  - van Duijn, C.M.*
AU  - Wichmann, H.-E.
AU  - Kaprio, J.*
AU  - Taskinen, M.R.*
AU  - Peltonen, L.*
C1  - 4661
C2  - 27464
SP  - 1-10
TI  - Use of genome-wide expression data to mine the 'Gray Zone' of GWA studies leads to novel candidate obesity genes.
JO  - PLoS Genet.
VL  - 6
IS  - 6
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Hypertension is a heritable and major contributor to the global burden of disease. The sum of rare and common genetic variants robustly identified so far explain only 1%-2% of the population variation in BP and hypertension. This suggests the existence of more undiscovered common variants. We conducted a genome-wide association study in 1,621 hypertensive cases and 1,699 controls and follow-up validation analyses in 19,845 cases and 16,541 controls using an extreme casecontrol design. We identified a locus on chromosome 16 in the 59 region of Uromodulin (UMOD; rs13333226, combined P value of 3.6610211). The minor G allele is associated with a lower risk of hypertension (OR [95%CI]: 0.87 [0.84-0.91]), reduced urinary uromodulin excretion, better renal function; and each copy of the G allele is associated with a 7.7% reduction in risk of CVD events after adjusting for age, sex, BMI, and smoking status (H.R. = 0.923, 95% CI 0.860-0.991; p = 0.027). In a subset of 13,446 individuals with estimated glomerular filtration rate (eGFR) measurements, we show that rs13333226 is independently associated with hypertension (unadjusted for eGFR: 0.89 [0.83-0.96], p = 0.004; after eGFR adjustment: 0.89 [0.83-0.96], p = 0.003). In clinical functional studies, we also consistently show the minor G allele is associated with lower urinary uromodulin excretion. The exclusive expression of uromodulin in the thick portion of the ascending limb of Henle suggests a putative role of this variant in hypertension through an effect on sodium homeostasis. The newly discovered UMOD locus for hypertension has the potential to give new insights into the role of uromodulin in BP regulation and to identify novel drugable targets for reducing cardiovascular risk.
AU  - Padmanabhan, S.*
AU  - Melander, O.*
AU  - Johnson, T.*
AU  - di Blasio, A.M.*
AU  - Lee, W.K.*
AU  - Gentilini, G.*
AU  - Hastie, C.E.*
AU  - Menni, C.*
AU  - Monti, M.C.*
AU  - Delles, C.*
AU  - Laing, S.*
AU  - Corso, B.*
AU  - Navis, G.*
AU  - Kwakernaak, A.J.*
AU  - van der Harst, P.*
AU  - Bochud, M.*
AU  - Maillard, M.*
AU  - Burnier, M.*
AU  - Hedner, T.*
AU  - Kjeldsen, S.*
AU  - Wahlstrand, B.*
AU  - Sjögren, M.*
AU  - Fava, C.*
AU  - Montagnana, M.*
AU  - Danese, E.*
AU  - Torffvit, O.*
AU  - Hedblad, B.*
AU  - Snieder, H.*
AU  - Conell, J.M.C.*
AU  - Brown, M.*
AU  - Samani, N.J.*
AU  - Farrall, M.*
AU  - Cesana, G.*
AU  - Mancia, G.*
AU  - Signorini, S.*
AU  - Grassi, G.*
AU  - Eyheramendy, S.*
AU  - Wichmann, H.-E.
AU  - Laan, M.*
AU  - Strachan, D.P.*
AU  - Sever, P.*
AU  - Shields, D.C.*
AU  - Stanton, A.*
AU  - Vollenweider, P.*
AU  - Teumer, A.*
AU  - Völzke, H.*
AU  - Rettig, R.*
AU  - Newton-Cheh, C.*
AU  - Arora, P.*
AU  - Zhang, F.*
AU  - Soranzo, N.*
AU  - Spector, T.D.*
AU  - Lucas, G.*
AU  - Kathiresan, S.*
AU  - Siscovick, D.S.*
AU  - Luan, J.*
AU  - Loos, R.J.F.*
AU  - Wareham, N.J.*
AU  - Penninx, B.W.*
AU  - Nolte, I.M.*
AU  - McBride, M.*
AU  - Miller, W.H.*
AU  - Nicklin, S.A.*
AU  - Baker, A.H.*
AU  - Graham, D.*
AU  - Mc Donald, R.A.*
AU  - Pell, J.P.*
AU  - Sattar, N.*
AU  - Welsh, P.*
AU  - Munroe, P.*
AU  - Caulfield, M.J.*
AU  - Zanchetti, A.*
AU  - Dominiczak, A.F.*
C1  - 2647
C2  - 27595
CY  - San Francisco
SP  - 1-11
TI  - Genome-wide association study of blood pressure extremes identifies variant near UMOD associated with hypertension.
JO  - PLoS Genet.
VL  - 6
IS  - 10
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Meta-analyses of population-based genome-wide association studies (GWAS) in adults have recently led to the detection of new genetic loci for obesity. Here we aimed to discover additional obesity loci in extremely obese children and adolescents. We also investigated if these results generalize by estimating the effects of these obesity loci in adults and in population-based samples including both children and adults. We jointly analysed two GWAS of 2,258 individuals and followed-up the best, according to lowest p-values, 44 single nucleotide polymorphisms (SNP) from 21 genomic regions in 3,141 individuals. After this DISCOVERY step, we explored if the findings derived from the extremely obese children and adolescents (10 SNPs from 5 genomic regions) generalized to (i) the population level and (ii) to adults by genotyping another 31,182 individuals (GENERALIZATION step). Apart from previously identified FTO, MC4R, and TMEM18, we detected two new loci for obesity: one in SDCCAG8 (serologically defined colon cancer antigen 8 gene; p = 1.85x10(-8) in the DISCOVERY step) and one between TNKS (tankyrase, TRF1-interacting ankyrin-related ADP-ribose polymerase gene) and MSRA (methionine sulfoxide reductase A gene; p = 4.84x10(-7)), the latter finding being limited to children and adolescents as demonstrated in the GENERALIZATION step. The odds ratios for early-onset obesity were estimated at approximately 1.10 per risk allele for both loci. Interestingly, the TNKS/MSRA locus has recently been found to be associated with adult waist circumference. In summary, we have completed a meta-analysis of two GWAS which both focus on extremely obese children and adolescents and replicated our findings in a large followed-up data set. We observed that genetic variants in or near FTO, MC4R, TMEM18, SDCCAG8, and TNKS/MSRA were robustly associated with early-onset obesity. We conclude that the currently known major common variants related to obesity overlap to a substantial degree between children and adults.
AU  - Scherag, A.*
AU  - Dina, C.*
AU  - Hinney, A.*
AU  - Vatin, V.*
AU  - Scherag, S.*
AU  - Vogel, C.I.G.*
AU  - Müller, T.D.*
AU  - Grallert, H.
AU  - Wichmann, H.-E.
AU  - Balkau, B.*
AU  - Heude, B.*
AU  - Jarvelin, M.R.*
AU  - Hartikainen, A.L.*
AU  - Lévy-Marchal, C.*
AU  - Weill, J.*
AU  - Delplanque, J.*
AU  - Körner, A.*
AU  - Kiess, W.*
AU  - Kovacs, P.*
AU  - Rayner, N.W.*
AU  - Prokopenko, I.*
AU  - McCarthy, M.I.*
AU  - Schäfer, H.*
AU  - Jarick, I.*
AU  - Boeing, H.*
AU  - Fisher, E.*
AU  - Reinehr, T.*
AU  - Heinrich, J.
AU  - Rzehak, P.
AU  - Berdel, D.*
AU  - Borte, M.*
AU  - Biebermann, H.*
AU  - Krude, H.*
AU  - Rosskopf, D.*
AU  - Rimmbach, C.*
AU  - Rief, W.*
AU  - Fromme, T.*
AU  - Klingenspor, M.*
AU  - Schürmann, A.*
AU  - Schulz, N.*
AU  - Nöthen, M.M.*
AU  - Mühleisen, T.W.*
AU  - Erbel, R.*
AU  - Jöckel, K.-H.*
AU  - Moebus, S.*
AU  - Boes, T.*
AU  - Illig, T.
AU  - Froguel, P.*
AU  - Hebebrand, J.*
AU  - Meyre, D.*
C1  - 1169
C2  - 27309
TI  - Two new loci for body-weight regulation identified in a joint analysis of genome-wide association studies for early-onset extreme obesity in French and German study groups.
JO  - PLoS Genet.
VL  - 6
IS  - 4
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Mitochondrial dysfunction has been observed in skeletal muscle of people with diabetes and insulin-resistant individuals. Furthermore, inherited mutations in mitochondrial DNA can cause a rare form of diabetes. However, it is unclear whether mitochondrial dysfunction is a primary cause of the common form of diabetes. To date, common genetic variants robustly associated with type 2 diabetes (T2D) are not known to affect mitochondrial function. One possibility is that multiple mitochondrial genes contain modest genetic effects that collectively influence T2D risk. To test this hypothesis we developed a method named Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA; http://www.broadinstitute.org/mpg/magenta). MAGENTA, in analogy to Gene Set Enrichment Analysis, tests whether sets of functionally related genes are enriched for associations with a polygenic disease or trait. MAGENTA was specifically designed to exploit the statistical power of large genome-wide association (GWA) study meta-analyses whose individual genotypes are not available. This is achieved by combining variant association p-values into gene scores and then correcting for confounders, such as gene size, variant number, and linkage disequilibrium properties. Using simulations, we determined the range of parameters for which MAGENTA can detect associations likely missed by single-marker analysis. We verified MAGENTA's performance on empirical data by identifying known relevant pathways in lipid and lipoprotein GWA meta-analyses. We then tested our mitochondrial hypothesis by applying MAGENTA to three gene sets: nuclear regulators of mitochondrial genes, oxidative phosphorylation genes, and approximately 1,000 nuclear-encoded mitochondrial genes. The analysis was performed using the most recent T2D GWA meta-analysis of 47,117 people and meta-analyses of seven diabetes-related glycemic traits (up to 46,186 non-diabetic individuals). This well-powered analysis found no significant enrichment of associations to T2D or any of the glycemic traits in any of the gene sets tested. These results suggest that common variants affecting nuclear-encoded mitochondrial genes have at most a small genetic contribution to T2D susceptibility.
AU  - Segrè, A.V.*
AU  - DIAGRAM Consortium (Huth, C.
AU  - Grallert, H.
AU  - Gieger, C.
AU  - Klopp, N.
AU  - Meitinger, T.
AU  - Petersen, A.-K.
AU  - Thorand, B.
AU  - Wichmann, H.-E.
AU  - Illig, T.)
AU  - MAGIC Investigators (Meisinger, C.
AU  - Grallert, H.
AU  - Gieger, C.
AU  - Thorand, B.
AU  - Wichmann, H.-E.
AU  - Illig, T.)
AU  - Groop, L.*
AU  - Mootha, V.K.*
AU  - Daly, M.J.*
AU  - Altshuler, D.*
C1  - 5127
C2  - 27914
TI  - Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits.
JO  - PLoS Genet.
VL  - 6
IS  - 8
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Dilated cardiomyopathy (DCM) is a structural heart disease with strong genetic background. Monogenic forms of DCM are observed in families with mutations located mostly in genes encoding structural and sarcomeric proteins. However, strong evidence suggests that genetic factors also affect the susceptibility to idiopathic DCM. To identify risk alleles for non-familial forms of DCM, we carried out a case-control association study, genotyping 664 DCM cases and 1,874 population-based healthy controls from Germany using a 50K human cardiovascular disease bead chip covering more than 2,000 genes pre-selected for cardiovascular relevance. After quality control, 30,920 single nucleotide polymorphisms (SNP) were tested for association with the disease by logistic regression adjusted for gender, and results were genomic-control corrected. The analysis revealed a significant association between a SNP in HSPB7 gene (rs1739843, minor allele frequency 39%) and idiopathic DCM (p = 1.06 × 10⁻⁶, OR  = 0.67 [95% CI 0.57-0.79] for the minor allele T). Three more SNPs showed p < 2.21 × 10⁻⁵. De novo genotyping of these four SNPs was done in three independent case-control studies of idiopathic DCM. Association between SNP rs1739843 and DCM was significant in all replication samples: Germany (n =564, n = 981 controls, p = 2.07 × 10⁻³, OR = 0.79 [95% CI 0.67-0.92]), France 1 (n = 433 cases, n = 395 controls, p =3.73 × 10⁻³, OR  = 0.74 [95% CI 0.60-0.91]), and France 2 (n = 249 cases, n = 380 controls, p = 2.26 × 10⁻⁴, OR  = 0.63 [95% CI 0.50-0.81]). The combined analysis of all four studies including a total of n = 1,910 cases and n = 3,630 controls showed highly significant evidence for association between rs1739843 and idiopathic DCM (p = 5.28 × 10⁻¹³, OR= 0.72 [95% CI 0.65-0.78]). None of the other three SNPs showed significant results in the replication stage.This finding of the HSPB7 gene from a genetic search for idiopathic DCM using a large SNP panel underscores the influence of common polymorphisms on DCM susceptibility.
AU  - Stark, K.*
AU  - Esslinger, U.B.*
AU  - Reinhard, W.*
AU  - Petrov, G.*
AU  - Winkler, T.*
AU  - Komajda, M.*
AU  - Isnard, R.*
AU  - Charron, P.*
AU  - Villard, E.*
AU  - Cambien, F.*
AU  - Tiret, L.*
AU  - Aumont, M.-C.*
AU  - Dubourg, O.*
AU  - Trochu, J.-N.*
AU  - Fauchier, L.*
AU  - Degroote, P.*
AU  - Richter, A.*
AU  - Maisch, B.*
AU  - Wichter, T.*
AU  - Zollbrecht, C.*
AU  - Grassl, M.*
AU  - Schunkert, H.*
AU  - Linsel-Nitschke, P.*
AU  - Erdmann, J.*
AU  - Baumert, J.J.
AU  - Illig, T.
AU  - Klopp, N.
AU  - Wichmann, H.-E.
AU  - Meisinger, C.
AU  - Koenig, W.*
AU  - Lichtner, P.
AU  - Meitinger, T.
AU  - Schillert, A.*
AU  - König, I.R.*
AU  - Hetzer, R.*
AU  - Heid, I.M.
AU  - Regitz-Zagrosek, V.*
AU  - Hengstenberg, C.*
C1  - 5977
C2  - 27722
TI  - Genetic association study identifies HSPB7 as a risk gene for idiopathic dilated cardiomyopathy.
JO  - PLoS Genet.
VL  - 6
IS  - 10
PB  - Public Library of Science
PY  - 2010
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Hypermutation of the immunoglobulin (Ig) genes requires Activation Induced cytidine Deaminase (AID) and transcription, but it remains unclear why other transcribed genes of B cells do not mutate. We describe a reporter transgene crippled by hypermutation when inserted into or near the Ig light chain (IgL) locus of the DT40 B cell line yet stably expressed when inserted into other chromosomal positions. Step-wise deletions of the IgL locus revealed that a sequence extending for 9.8 kilobases downstream of the IgL transcription start site confers the hypermutation activity. This sequence, named DIVAC for diversification activator, efficiently activates hypermutation when inserted at non-Ig loci. The results significantly extend previously reported findings on AID-mediated gene diversification. They show by both deletion and insertion analyses that cis-acting sequences predispose neighboring transcription units to hypermutation.
AU  - Blagodatski, A.*
AU  - Batrak, V.*
AU  - Schmidl, S.*
AU  - Schoetz, U.*
AU  - Caldwell, R.B.*
AU  - Arakawa, H.*
AU  - Buerstedde, J.M.
C1  - 509
C2  - 25970
TI  - A cis-acting diversification activator both necessary and sufficient for AID-mediated hypermutation.
JO  - PLoS Genet.
VL  - 5
IS  - 1
PB  - Public Library of Science
PY  - 2009
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The INSIG2 rs7566605 polymorphism was identified for obesity (BMI> or =30 kg/m(2)) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status ('healthy population', HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I(2) measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I(2) measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI> or =32.5, 35.0, 37.5, 40.0 kg/m(2) versus BMI<25 kg/m(2)) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far.
AU  - Heid, I.M.
AU  - Huth, C.
AU  - Loos, R.J.F.*
AU  - Kronenberg, F.*
AU  - Adamkova, V.*
AU  - Anand, S.S.*
AU  - Ardlie, K.*
AU  - Biebermann, H.*
AU  - Bjerregaard, P.*
AU  - Boeing, H.*
AU  - Bouchard, C.*
AU  - Ciullo, M.*
AU  - Cooper, J.A.*
AU  - Corella, D.*
AU  - Dina, C.*
AU  - Engert, J.C.*
AU  - Fisher, E.*
AU  - Francès, F.*
AU  - Froguel, P.*
AU  - Hebebrand, J.*
AU  - Hegele, R.A.*
AU  - Hinney, A.*
AU  - Hoehe, M.R.*
AU  - Hu, F.B.*
AU  - Hubácek, J.A.*
AU  - Humphries, S.E.*
AU  - Hunt, S.C.*
AU  - Illig, T.
AU  - Jarvelin, M.R.*
AU  - Kaakinen, M.*
AU  - Kollerits, B.*
AU  - Krude, H.*
AU  - Kumar, J.*
AU  - Lange, L.A.*
AU  - Langer, B.*
AU  - Li, S.*
AU  - Luchner, A.*
AU  - Lyon, H.N.*
AU  - Meyre, D.*
AU  - Mohlke, K.L.*
AU  - Mooser, V.*
AU  - Nebel, A.*
AU  - Nguyen, T.T.*
AU  - Paulweber, B.*
AU  - Perusse, L.*
AU  - Qi, L.*
AU  - Rankinen, T.*
AU  - Rosskopf, D.*
AU  - Schreiber, S.*
AU  - Sengupta, S.*
AU  - Sorice, R.*
AU  - Suk, A.*
AU  - Thorleifsson, G.*
AU  - Thorsteinsdottir, U.*
AU  - Völzke, H.*
AU  - Vimaleswaran, K.S.*
AU  - Wareham, N.J.*
AU  - Waterworth, D.*
AU  - Yusuf, S.*
AU  - Lindgren, C.*
AU  - McCarthy, M.I.*
AU  - Lange, C.*
AU  - Hirschhorn, J.N.*
AU  - Laird, N.*
AU  - Wichmann, H.-E.
C1  - 2080
C2  - 26474
TI  - Meta-analysis of the INSIG2 association with obesity including 74,345 individuals: Does heterogeneity of estimates relate to study design?
JO  - PLoS Genet.
VL  - 5
IS  - 10
PB  - Public Library of Science
PY  - 2009
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic beta-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08x10(-66). The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10(-4) or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested for a role in the development of common cardiovascular, metabolic, neurological, and psychiatric diseases.
AU  - Hicks, A.A.*
AU  - Pramstaller, P.P.*
AU  - Johansson, A.*
AU  - Vitart, V.*
AU  - Rudan, I.*
AU  - Ugocsai, P.*
AU  - Aulchenko, Y.*
AU  - Franklin, C.S.*
AU  - Liebisch, G.*
AU  - Erdmann, J.*
AU  - Jonasson, I.*
AU  - Zorkoltseva, I.V.*
AU  - Pattaro, C.*
AU  - Hayward, C.*
AU  - Isaacs, A.*
AU  - Hengstenberg, C.*
AU  - Campbell, S.*
AU  - Gnewuch, C.*
AU  - Janssens, A.C.*
AU  - Kirichenko, A.V.*
AU  - König, I.R.*
AU  - Marroni, F.*
AU  - Polasek, O.*
AU  - Demirkan, A.*
AU  - Kolcic, I.*
AU  - Schwienbacher, C.*
AU  - Igl, W.*
AU  - Biloglav, Z.*
AU  - Witteman, J.C.*
AU  - Pichler, I.*
AU  - Zaboli, G.*
AU  - Axenovich,T.I.*
AU  - Peters, A.
AU  - Schreiber, S.*
AU  - Wichmann, H.-E.
AU  - Schunkert, H.*
AU  - Hastie, N.*
AU  - Oostra, B.A.*
AU  - Wild, S.H.*
AU  - Meitinger, T.
AU  - Gyllensten, U.*
AU  - van Duijn, C.M.*
AU  - Wilson, J.F.*
AU  - Wright, A.*
AU  - Schmitz, G.*
AU  - Campbell, H.*
C1  - 142
C2  - 26477
TI  - Genetic determinants of circulating sphingolipid concentrations in European populations.
JO  - PLoS Genet.
VL  - 5
IS  - 10
PB  - Public Library of Science
PY  - 2009
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-9)). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-54), respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.
AU  - Kolz, M.
AU  - Johnson, T.*
AU  - Sanna, S.*
AU  - Teumer, A.*
AU  - Vitart, V.*
AU  - Perola, M.*
AU  - Mangino, M.*
AU  - Albrecht, E.
AU  - Wallace, C.*
AU  - Farrall, M.*
AU  - Johansson, A.*
AU  - Nyholt, D.R.*
AU  - Aulchenko, Y.*
AU  - Beckmann, J.S.*
AU  - Bergmann, S.*
AU  - Bochud, M.*
AU  - Brown, M.*
AU  - Campbell, H.*
AU  - Connell, J.*
AU  - Dominiczak, A.*
AU  - Homuth, G.*
AU  - Lamina, C.
AU  - McCarthy, M.I.*
AU  - Meitinger, T.
AU  - Mooser, V.*
AU  - Munroe, P.*
AU  - Nauck, M.*
AU  - Peden, J.*
AU  - Prokisch, H.*
AU  - Salo, P.*
AU  - Salomaa, V.*
AU  - Samani, N.J.*
AU  - Schlessinger, D.*
AU  - Uda, M.*
AU  - Völker, U.*
AU  - Waeber, G.*
AU  - Waterworth, D.*
AU  - Wang-Sattler, R.
AU  - Wright, A.F.*
AU  - Adamski, J.
AU  - Whitfield, J.B.*
AU  - Gyllensten, U.*
AU  - Wilson, J.F.*
AU  - Rudan, I.*
AU  - Pramstaller, P.*
AU  - Watkins, H.*
AU  - Döring, A.
AU  - Wichmann, H.-E.
AU  - Spector, T.D.*
AU  - Peltonen, L.*
AU  - Völzke, H.*
AU  - Nagaraja, R.*
AU  - Vollenweider, P.*
AU  - Caulfield, M.*
AU  - Illig, T.
AU  - Gieger, C.
C1  - 1041
C2  - 26277
TI  - Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations.
JO  - PLoS Genet.
VL  - 5
IS  - 6
PB  - Public Library of Science
PY  - 2009
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
AU  - Lindgren, C.M.*
AU  - Heid, I.M.
AU  - Randall, J.C.*
AU  - Lamina, C.
AU  - Steinthorsdottir, V.*
AU  - Qi, L.*
AU  - Speliotes, E.K.*
AU  - Thorleifsson, G.*
AU  - Willer, C.J.*
AU  - Herrera, B.M.*
AU  - Jackson, A.U.*
AU  - Lim, N.*
AU  - Scheet, P.*
AU  - Soranzo, N.*
AU  - Amin, N.*
AU  - Aulchenko, Y.S.*
AU  - Chambers, J.C.*
AU  - Drong, A.*
AU  - Luan, J.A.*
AU  - Lyon, H.N.*
AU  - Rivadeneira, F.*
AU  - Sanna, S.*
AU  - Timpson, N.J.*
AU  - Zillikens, M.C.*
AU  - Zhao, J.H.*
AU  - Almgren, P.*
AU  - Bandinelli, S.*
AU  - Bennett, A.J.*
AU  - Bergman, R.N.*
AU  - Bonnycastle, L.L.*
AU  - Bumpstead, S.J.*
AU  - Chanock, S.J.*
AU  - Cherkas, L.*
AU  - Chines, P.*
AU  - Coin, L.*
AU  - Cooper, C.*
AU  - Crawford, G.*
AU  - Döring, A.*
AU  - Dominiczak, A.*
AU  - Doney, A.S.*
AU  - Ebrahim, S.*
AU  - Elliott, P.*
AU  - Erdos, M.R.*
AU  - Estrada, K.*
AU  - Ferrucci, L.*
AU  - Fischer, G.
AU  - Forouhi, N.G.*
AU  - Gieger, C.
AU  - Grallert, H.
AU  - Groves, C.J.*
AU  - Grundy, S.*
AU  - Guiducci, C.*
AU  - Hadley, D.*
AU  - Hamsten, A.*
AU  - Havulinna, A.S.*
AU  - Hofman, A.*
AU  - Holle, R.
AU  - Holloway, J.W.*
AU  - Illig, T.
AU  - Isomaa, B.*
AU  - Jacobs, L.C.*
AU  - Jameson, K.*
AU  - Jousilahti, P.*
AU  - Karpe, F.*
AU  - Kuusisto, J.*
AU  - Laitinen, J.*
AU  - Lathrop, G.M.*
AU  - Lawlor, D.A.*
AU  - Mangino, M.*
AU  - McArdle, W.L.*
AU  - Meitinger, T.
AU  - Morken, M.A.*
AU  - Morris, A.P.*
AU  - Munroe, P.*
AU  - Narisu, N.*
AU  - Nordstrom, A.*
AU  - Nordstrom, P.*
AU  - Oostra, B.A.*
AU  - Palmer, C.N.A.*
AU  - Payne, F.*
AU  - Peden, J.F.*
AU  - Prokopenko, I.*
AU  - Renström, F.*
AU  - Ruokonen, A.*
AU  - Salomaa, V.*
AU  - Sandhu, M.S.*
AU  - Scott, L.J.*
AU  - Scuteri, A.*
AU  - Silander, K.*
AU  - Song, K.J.*
AU  - Yuan, X.*
AU  - Stringham, H.M.*
AU  - Swift, A.J.*
AU  - Tuomi, T.*
AU  - Uda, M.*
AU  - Vollenweider, P.*
AU  - Waeber, G.*
AU  - Wallace, C.*
AU  - Walters, G.B.*
AU  - Weedon, M.N.*
AU  - Witteman, J.C.M.*
AU  - Zhang, C.L.*
AU  - Zhang, W.H.*
AU  - Caulfield, M.J.*
AU  - Collins, F.S.*
AU  - Smith, G.D.*
AU  - Day, I.N.M.*
AU  - Franks, P.W.*
AU  - Hattersley, A.T.*
AU  - Hu, F.B.*
AU  - Jarvelin, M.R.*
AU  - Kong, A.*
AU  - Kooner, J.S.*
AU  - Laakso, M.*
AU  - Lakatta, E.*
AU  - Mooser, V.*
AU  - Morris, A.D.*
AU  - Peltonen, L.*
AU  - Samani, N.J.*
AU  - Spector, T.D.*
AU  - Strachan, D.P.*
AU  - Tanaka, T.*
AU  - Tuomilehto, J.*
AU  - Uitterlinden, A.G.*
AU  - van Duijn, C.M.*
AU  - Wareham, N.J.*
AU  - Watkins, H.*
AU  - Waterworth, D.M.*
AU  - Boehnke, M.*
AU  - Deloukas, P.*
AU  - Groop, L.*
AU  - Hunter, D.J.*
AU  - Thorsteinsdottir, U.*
AU  - Schlessinger, D.*
AU  - Wichmann, H.-E.
AU  - Frayling, T.M.*
AU  - Abecasis, G.R.*
AU  - Hirschhorn, J.N.*
AU  - Loos, R.J.F.*
AU  - Stefansson, K.*
AU  - Mohlke, K.L.*
AU  - Barroso, I.S.*
AU  - McCarthy, M.I.*
C1  - 2250
C2  - 26278
TI  - Genome-wide association scan meta-analysis identifies three loci influencing adiposity and fat distribution.
JO  - PLoS Genet.
VL  - 5
IS  - 6
PB  - Public Library of Science
PY  - 2009
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P< or =5x10(-8)). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P< or =0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2x10(-19) for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9x10(-8), n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5x10(-6), n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2x10(-3), n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk.
AU  - Richards, J.B.*
AU  - Waterworth, D.*
AU  - O'Rahilly, S.*
AU  - Hivert, M.F.*
AU  - Loos, R.J.F.*
AU  - Perry, J.R.B.*
AU  - Tanaka, T.*
AU  - Timpson, N.J.*
AU  - Semple, R.K.*
AU  - Soranzo, N.*
AU  - Song, K.*
AU  - Rocha, N.*
AU  - Grundberg, E.*
AU  - Dupuis, J.*
AU  - Florez, J.C*
AU  - Langenberg, C.*
AU  - Prokopenko, I.*
AU  - Saxena, R.*
AU  - Aulchenko, Y.*
AU  - Evans, D.*
AU  - Waeber, G.*
AU  - Erdmann, J.*
AU  - Burnett, M.S.*
AU  - Sattar, N.*
AU  - Devaney, J.*
AU  - Willenborg, C.*
AU  - Hingorani, A.*
AU  - Witteman, J.C.M.*
AU  - Vollenweider, P.*
AU  - Glaser, B.*
AU  - Hengstenberg, C.*
AU  - Ferrucci, L.*
AU  - Melzer, D.*
AU  - Stark, K.*
AU  - Deanfield, J.*
AU  - Winogradow, J.*
AU  - Grassl, M.*
AU  - Hall, A.S.*
AU  - Egan, J.M.*
AU  - Thompson, J.R.*
AU  - Ricketts, S.L.*
AU  - König, I.R.*
AU  - Reinhard, W.*
AU  - Grundy, S.*
AU  - Wichmann, H.-E.
AU  - Barter, P.*
AU  - Mahley, R.*
AU  - Kesaniemi, Y.A.*
AU  - Rader, D.J.*
AU  - Reilly, M.P.*
AU  - Epstein, S.E.*
AU  - Stewart, A.F.R.*
AU  - van Duijn, C.M.*
AU  - Schunkert, H.*
AU  - Burling, K.*
AU  - Deloukas, P.*
AU  - Pastinen, T.*
AU  - Samani, N.J.*
AU  - McPherson, R.*
AU  - Smith, G.D.*
AU  - Frayling, T.M.*
AU  - Wareham, N.J.*
AU  - Meigs, J.B.*
AU  - Mooser, V.*
AU  - Spector, T.D.*
C1  - 2958
C2  - 26734
TI  - A genome-wide association study reveals variants in ARL15 that influence adiponectin levels.
JO  - PLoS Genet.
VL  - 5
IS  - 12
PB  - Public Library of Science
PY  - 2009
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - The rapidly evolving field of metabolomics aims at a comprehensive measurement of ideally all endogenous metabolites in a cell or body fluid. It thereby provides a functional readout of the physiological state of the human body. Genetic variants that associate with changes in the homeostasis of key lipids, carbohydrates, or amino acids are not only expected to display much larger effect sizes due to their direct involvement in metabolite conversion modification, but should also provide access to the biochemical context of such variations, in particular when enzyme coding genes are concerned. To test this hypothesis, we conducted what is, to the best of our knowledge, the first GWA study with metabolomics based on the quantitative measurement of 363 metabolites in serum of 284 male participants of the KORA study. We found associations of frequent single nucleotide polymorphisms (SNPs) with considerable differences in the metabolic homeostasis of the human body, explaining up to 12% of the observed variance. Using ratios of certain metabolite concentrations as a proxy for enzymatic activity, up to 28% of the variance can be explained (p-values 10(-16) to 10(-21)). We identified four genetic variants in genes coding for enzymes (FADS1, LIPC, SCAD, MCAD) where the corresponding metabolic phenotype (metabotype) clearly matches the biochemical pathways in which these enzymes are active. Our results suggest that common genetic polymorphisms induce major differentiations in the metabolic make-up of the human population. This may lead to a novel approach to personalized health care based on a combination of genotyping and metabolic characterization. These genetically determined metabotypes may subscribe the risk for a certain medical phenotype, the response to a given drug treatment, or the reaction to a nutritional intervention or environmental challenge.
AU  - Gieger, C.
AU  - Geistlinger, L.
AU  - Altmaier, E.
AU  - Hrabě de Angelis, M.
AU  - Kronenberg, F.*
AU  - Meitinger, T.
AU  - Mewes, H.-W.
AU  - Wichmann, H.-E.
AU  - Weinberger, K.M.*
AU  - Adamski, J.
AU  - Illig, T.
AU  - Suhre, K.
C1  - 3319
C2  - 25816
TI  - Genetics meets metabolomics: A genome-wide association study of metabolite profiles in human serum.
JO  - PLoS Genet.
VL  - 4
IS  - 11
PB  - Public Library of Science
PY  - 2008
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Myosin VI, found in organisms from Caenorhabditis elegans to humans, is essential for auditory and vestibular function in mammals, since genetic mutations lead to hearing impairment and vestibular dysfunction in both humans and mice. Here, we show that a missense mutation in this molecular motor in an ENU-generated mouse model, Tailchaser, disrupts myosin VI function. Structural changes in the Tailchaser hair bundles include mislocalization of the kinocilia and branching of stereocilia. Transfection of GFP-labeled myosin VI into epithelial cells and delivery of endocytic vesicles to the early endosome revealed that the mutant phenotype displays disrupted motor function. The actin-activated ATPase rates measured for the D179Y mutation are decreased, and indicate loss of coordination of the myosin VI heads or 'gating' in the dimer form. Proper coordination is required for walking processively along, or anchoring to, actin filaments, and is apparently destroyed by the proximity of the mutation to the nucleotide-binding pocket. This loss of myosin VI function may not allow myosin VI to transport its cargoes appropriately at the base and within the stereocilia, or to anchor the membrane of stereocilia to actin filaments via its cargos, both of which lead to structural changes in the stereocilia of myosin VI-impaired hair cells, and ultimately leading to deafness.
AU  - Hertzano, R.*
AU  - Shalit, E.*
AU  - Rzadzinska, A.K.*
AU  - Song, L.*
AU  - Ron, U.*
AU  - Tan, J.T.*
AU  - Shitrit, A.S.*
AU  - Fuchs, H.
AU  - Hasson, T.*
AU  - Ben-Tal, N. Sweeney, H.L.*
AU  - Hrabě de Angelis, M.
AU  - Steel, K.P.*
AU  - Avraham, K.B.*
C1  - 653
C2  - 25600
TI  - A Myo6 mutation destroys coordination between the myosin heads, revealing new functions of myosin VI in the stereocilia of mammalian inner ear hair cells.
JO  - PLoS Genet.
VL  - 4
IS  - 10
PB  - Public Library of Science
PY  - 2008
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Osteogenesis imperfecta is an inherited disorder characterized by increased bone fragility, fractures, and osteoporosis, and most cases are caused by mutations affecting the type I collagen genes. Here, we describe a new mouse model for Osteogenesis imperfecta termed Aga2 (abnormal gait 2) that was isolated from the Munich N-ethyl-N-nitrosourea mutagenesis program and exhibited phenotypic variability, including reduced bone mass, multiple fractures, and early lethality. The causal gene was mapped to Chromosome 11 by linkage analysis, and a C-terminal frameshift mutation was identified in the Col1a1 (procollagen type I, alpha 1) gene as the cause of the disorder. Aga2 heterozygous animals had markedly increased bone turnover and a disrupted native collagen network. Further studies showed that abnormal proalpha1(I) chains accumulated intracellularly in Aga2/+ dermal fibroblasts and were poorly secreted extracellularly. This was associated with the induction of an endoplasmic reticulum stress-specific unfolded protein response involving upregulation of BiP, Hsp47, and Gadd153 with caspases-12 and -3 activation and apoptosis of osteoblasts both in vitro and in vivo. These studies resulted in the identification of a new model for Osteogenesis imperfecta, and identified a role for intracellular modulation of the endoplasmic reticulum stress-associated unfolded protein response machinery toward osteoblast apoptosis during the pathogenesis of disease.
AU  - Lisse, T.S.
AU  - Thiele, F.
AU  - Fuchs, H.
AU  - Hans, W.
AU  - Przemeck, G.K.H.
AU  - Abe, K.
AU  - Rathkolb, B.
AU  - Quintanilla-Martinez, L.
AU  - Hölzlwimmer, G.
AU  - Helfrich, M.*
AU  - Wolf, E.*
AU  - Ralston, S.H.*
AU  - Hrabě de Angelis, M.
C1  - 476
C2  - 25122
TI  - ER stress-mediated apoptosis in a new mouse model of Osteogenesis imperfecta.
JO  - PLoS Genet.
VL  - 4
IS  - 2
PB  - Public Library of Science
PY  - 2008
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Progressive hearing loss is common in the human population, but we have few clues to the molecular basis. Mouse mutants with progressive hearing loss offer valuable insights, and ENU (N-ethyl-N-nitrosourea) mutagenesis is a useful way of generating models. We have characterised a new ENU-induced mouse mutant, Oblivion (allele symbol Obl), showing semi-dominant inheritance of hearing impairment. Obl/+ mutants showed increasing hearing impairment from post-natal day (P)20 to P90, and loss of auditory function was followed by a corresponding base to apex progression of hair cell degeneration. Obl/Obl mutants were small, showed severe vestibular dysfunction by 2 weeks of age, and were completely deaf from birth; sensory hair cells were completely degenerate in the basal turn of the cochlea, although hair cells appeared normal in the apex. We mapped the mutation to Chromosome 6. Mutation analysis of Atp2b2 showed a missense mutation (2630C-->T) in exon 15, causing a serine to phenylalanine substitution (S877F) in transmembrane domain 6 of the PMCA2 pump, the resident Ca(2+) pump of hair cell stereocilia. Transmembrane domain mutations in these pumps generally are believed to be incompatible with normal targeting of the protein to the plasma membrane. However, analyses of hair cells in cultured utricular maculae of Obl/Obl mice and of the mutant Obl pump in model cells showed that the protein was correctly targeted to the plasma membrane. Biochemical and biophysical characterisation showed that the pump had lost a significant portion of its non-stimulated Ca(2+) exporting ability. These findings can explain the progressive loss of auditory function, and indicate the limits in our ability to predict mechanism from sequence alone.
AU  - Spiden, S.L.*
AU  - Bortolozzi, M.*
AU  - di Leva, F.*
AU  - Hrabě de Angelis, M.
AU  - Fuchs, H.
AU  - Lim, D.*
AU  - Ortolano, S.*
AU  - Ingham, N.J.*
AU  - Brini, M.*
AU  - Carafoli, E.*
AU  - Mammano, F.*
AU  - Steel, K.P.*
C1  - 654
C2  - 25682
TI  - The novel mouse mutation Oblivion inactivates the PMCA2 pump and causes progressive hearing loss.
JO  - PLoS Genet.
VL  - 4
IS  - 10
PB  - Public Library of Science
PY  - 2008
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - High levels of serum IgE are considered markers of parasite and helminth exposure. In addition, they are associated with allergic disorders, play a key role in anti-tumoral defence, and are crucial mediators of autoimmune diseases. Total IgE is a strongly heritable trait. In a genome-wide association study (GWAS), we tested 353,569 SNPs for association with serum IgE levels in 1,530 individuals from the population-based KORA S3/F3 study. Replication was performed in four independent population-based study samples (total n = 9,769 individuals). Functional variants in the gene encoding the alpha chain of the high affinity receptor for IgE (FCER1A) on chromosome 1q23 (rs2251746 and rs2427837) were strongly associated with total IgE levels in all cohorts with P values of 1.85 x 10(-20) and 7.08 x 10(-19) in a combined analysis, and in a post-hoc analysis showed additional associations with allergic sensitization (P = 7.78 x 10(-4) and P = 1.95 x 10(-3)). The "top" SNP significantly influenced the cell surface expression of FCER1A on basophils, and genome-wide expression profiles indicated an interesting novel regulatory mechanism of FCER1A expression via GATA-2. Polymorphisms within the RAD50 gene on chromosome 5q31 were consistently associated with IgE levels (P values 6.28 x 10(-7)-4.46 x 10(-8)) and increased the risk for atopic eczema and asthma. Furthermore, STAT6 was confirmed as susceptibility locus modulating IgE levels. In this first GWAS on total IgE FCER1A was identified and replicated as new susceptibility locus at which common genetic variation influences serum IgE levels. In addition, variants within the RAD50 gene might represent additional factors within cytokine gene cluster on chromosome 5q31, emphasizing the need for further investigations in this intriguing region. Our data furthermore confirm association of STAT6 variation with serum IgE levels.
AU  - Weidinger, S.
AU  - Gieger, C.
AU  - Rodriguez, E.
AU  - Baurecht, H.
AU  - Mempel, M.
AU  - Klopp, N.
AU  - Gohlke, H.
AU  - Wagenpfeil, S.*
AU  - Ollert, M.
AU  - Ring, J.*
AU  - Behrendt, H.
AU  - Heinrich, J.
AU  - Novak, N.*
AU  - Bieber, T.*
AU  - Krämer, U.*
AU  - Berdel, D.*
AU  - von Berg, A.*
AU  - Bauer, C.P.*
AU  - Herbarth, O.*
AU  - Koletzko, S.*
AU  - Prokisch, H.
AU  - Mehta, D.
AU  - Meitinger, T.
AU  - Depner, M.*
AU  - von Mutius, E.*
AU  - Liang, L.*
AU  - Moffatt, M.*
AU  - Cookson, W.*
AU  - Kabesch, M.*
AU  - Wichmann, H.-E.
AU  - Illig, T.
C1  - 2500
C2  - 25568
TI  - Genome-wide scan on total serum IgE levels identifies FCER1A as novel susceptibility locus.
JO  - PLoS Genet.
VL  - 4
IS  - 8
PB  - Public Library of Science
PY  - 2008
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - A SNP upstream of the INSIG2 gene, rs7566605, was recently found to be associated with obesity as measured by body mass index (BMI) by Herbert and colleagues. The association between increased BMI and homozygosity for the minor allele was first observed in data from a genome-wide association scan of 86,604 SNPs in 923 related individuals from the Framingham Heart Study offspring cohort. The association was reproduced in four additional cohorts, but was not seen in a fifth cohort. To further assess the general reproducibility of this association, we genotyped rs7566605 in nine large cohorts from eight populations across multiple ethnicities (total n = 16,969). We tested this variant for association with BMI in each sample under a recessive model using family-based, population-based, and case-control designs. We observed a significant (p < 0.05) association in five cohorts but saw no association in three other cohorts. There was variability in the strength of association evidence across examination cycles in longitudinal data from unrelated individuals in the Framingham Heart Study Offspring cohort. A combined analysis revealed significant independent validation of this association in both unrelated (p = 0.046) and family-based (p = 0.004) samples. The estimated risk conferred by this allele is small, and could easily be masked by small sample size, population stratification, or other confounders. These validation studies suggest that the original association is less likely to be spurious, but the failure to observe an association in every data set suggests that the effect of SNP rs7566605 on BMI may be heterogeneous across population samples.
AU  - Lyon, H.N.*
AU  - Emilsson, V.*
AU  - Hinney, A.*
AU  - Heid, I.M.
AU  - Lasky-Su, J.*
AU  - Zhu, X.*
AU  - Thorleifsson, G.*
AU  - Gunnarsdottir, S.*
AU  - Walters, G.B.*
AU  - Thorsteinsdottir, U.*
AU  - Kong, A.*
AU  - Gulcher, J.*
AU  - Nguyen, T.T.*
AU  - Scherag, A.*
AU  - Pfeufer, A.
AU  - Meitinger, T.
AU  - Brönner, G.*
AU  - Rief, W.*
AU  - Soto-Quiros, M.E.*
AU  - Avila, L.*
AU  - Klanderman, B.*
AU  - Raby, B.A.*
AU  - Silverman, E.K.*
AU  - Weiss, S.T.*
AU  - Laird, N.*
AU  - Ding, X.*
AU  - Groop, L.*
AU  - Tuomi, T.*
AU  - Isomaa, B.*
AU  - Bengtsson, K.*
AU  - Butler, J.L.*
AU  - Cooper, R.S.*
AU  - Fox, C.S.*
AU  - O'Donnell, C.J.*
AU  - Vollmert, C.
AU  - Celedón, J.C.*
AU  - Wichmann, H.-E.
AU  - Hebebrand, J.*
AU  - Stefansson, K.*
AU  - Lange, C.*
AU  - Hirschhorn, J.N.*
C1  - 5195
C2  - 24504
SP  - 0627-0633
TI  - The association of a SNP upstream of INSIG2 with body mass index is reproduced in several but not all cohorts.
JO  - PLoS Genet.
VL  - 3
IS  - 4
PB  - Public Library of Science
PY  - 2007
SN  - 1553-7390
ER  - 

TY  - JOUR
AB  - Mitochondria carry out specialized functions; compartmentalized, yet integrated into the metabolic and signaling processes of the cell. Although many mitochondrial proteins have been identified, understanding their functional interrelationships has been a challenge. Here we construct a comprehensive network of the mitochondrial system. We integrated genome-wide datasets to generate an accurate and inclusive mitochondrial parts list. Together with benchmarked measures of protein interactions, a network of mitochondria was constructed in their cellular context, including extra-mitochondrial proteins. This network also integrates data from different organisms to expand the known mitochondrial biology beyond the information in the existing databases. Our network brings together annotated and predicted functions into a single framework. This enabled, for the entire system, a survey of mutant phenotypes, gene regulation, evolution, and disease susceptibility. Furthermore, we experimentally validated the localization of several candidate proteins and derived novel functional contexts for hundreds of uncharacterized proteins. Our network thus advances the understanding of the mitochondrial system in yeast and identifies properties of genes underlying human mitochondrial disorders.
AU  - Perocchi, F.*
AU  - Jensen, L.L.*
AU  - Gagneur, J.*
AU  - Ahting, U.
AU  - von Mering, C.*
AU  - Bork, P.*
AU  - Prokisch, H.
AU  - Steinmetz, L.M.*
C1  - 5105
C2  - 24213
SP  - 1612-1624
TI  - Assessing systems properties of yeast mitochondria through an interaction map of the organelle.
JO  - PLoS Genet.
VL  - 2
IS  - 10
PB  - Public Library of Science
PY  - 2006
SN  - 1553-7390
ER  -