TY  - JOUR
AB  - Wilson's disease is an autosomal recessive disorder resulting from copper excess. Some patients with clinical Wilson's disease symptoms exhibit no or only heterozygous pathogenic variants in the coding region of the disease-causing ATP7B gene. Therefore, the ATP7B promoter region is of special interest. Metal-responsive elements (MREs) located in the ATP7B promoter are promising motifs in modulating the ATP7B expression. We studied protein interaction of MREe, MREc, and MREd by electrophoretic mobility shift assays and revealed specific interactions for all MREs. We further narrowed down the specific binding site. Proteins potentially binding to the three MREs were identified by MatInspector analyses. Metal regulatory transcription factor 1 (MTF1) could be validated to bind to MREe by electrophoretic mobility shift assays. ATP7B promoter-driven reporter gene expression was significantly increased because of this interaction. MTF1 is a strong candidate in regulating the ATP7B expression through MREe binding.
AU  - Stalke, A.*
AU  - Prister, E.*
AU  - Baumann, U.*
AU  - Illig, T.*
AU  - Reischl, E.
AU  - Sandbothe, M.*
AU  - Vajen, B.*
AU  - Huge, N.*
AU  - Schlegelberger, B.*
AU  - von Neuhoff, N.*
AU  - Skawran, B.*
C1  - 57131
C2  - 47564
CY  - 111 River St, Hoboken 07030-5774, Nj Usa
SP  - 195-200
TI  - MTF1 binds to metal-responsive element e within the ATP7B promoter and is a strong candidate in regulating the ATP7B expression.
JO  - Ann. Hum. Genet.
VL  - 84
PB  - Wiley
PY  - 2020
SN  - 0003-4800
ER  - 

TY  - JOUR
AU  - Prokopenko, I.*
AU  - Ma, C.*
AU  - Mägi, R.*
AU  - Chen, H.*
AU  - Voight, B.F.*
AU  - Qi, L.U.*
AU  - van Zuydam, N.*
AU  - Grallert, H.
AU  - Yengo, L.*
AU  - Dina, C.*
AU  - Thorleifsson, G.*
AU  - Fucshberger, C.*
AU  - Liang, L.M.*
AU  - Müller-Nurasyid, M.
AU  - Willems, S.M.*
AU  - Kao, L.D.*
AU  - Navarro, P.*
AU  - Steinthorsdottir, V.*
AU  - Boehnke, M.*
AU  - Dupuis, J.*
AU  - McCarthy, M.I.*
AU  - Scott, L.J.*
C1  - 60135
C2  - 0
SP  - 429-430
TI  - Search for novel type 2 diabetes susceptibility loci using genome-wide association studies imputed from a 1000 Genomes references panel.
JO  - Ann. Hum. Genet.
VL  - 76
PY  - 2012
SN  - 0003-4800
ER  - 

TY  - JOUR
AB  - Haplotypes are an important concept for genetic association studies, but involve uncertainty due to statistical reconstruction from single nucleotide polymorphism (SNP) genotypes and genotype error. We developed a re-sampling approach to quantify haplotype misclassification probabilities and implemented the MC-SIMEX approach to tackle this as a 3 x 3 misclassification problem. Using a previously published approach as a benchmark for comparison, we evaluated the performance of our approach by simulations and exemplified it on real data from 15 SNPs of the APM1 gene. Misclassification due to reconstruction error was small for most, but notable for some, especially rarer haplotypes. Genotype error added misclassification to all haplotypes resulting in a non-negligible drop in sensitivity. In our real data example, the bias of association estimates due to reconstruction error alone reached -48.2% for a 1% genotype error, indicating that haplotype misclassification should not be ignored if high genotype error can be expected. Our 3 x 3 misclassification view of haplotype error adds a novel perspective to currently used methods based on genotype intensities and expected number of haplotype copies. Our findings give a sense of the impact of haplotype error under realistic scenarios and underscore the importance of high-quality genotyping, in which case the bias in haplotype association estimates is negligible.
AU  - Lamina, C.
AU  - Küchenhoff, H.*
AU  - Chang-Claude, J.*
AU  - Paulweber, B.*
AU  - Wichmann, H.-E.
AU  - Illig, T.
AU  - Hoehe, M.R.*
AU  - Kronenberg, F.*
AU  - Heid, I.M.
C1  - 5580
C2  - 27554
SP  - 452-462
TI  - Haplotype misclassification resulting from statistical reconstruction and genotype error, and its impact on association estimates.
JO  - Ann. Hum. Genet.
VL  - 74
IS  - 5
PB  - Wiley-Blackwell Publishing, Inc.
PY  - 2010
SN  - 0003-4800
ER  - 

TY  - JOUR
AB  - This paper proposes family based Hotelling's T2 tests for high resolution linkage disequilibrium (LD) mapping or association studies of complex diseases. Assume that genotype data of multiple markers or haplotype blocks are available for a sample of nuclear families, in which some offspring are affected. Paired Hotelling's T2 test statistics are proposed for a high resolution association study using parents as controls for affected offspring, based on two coding methods: haplotype/allele coding and genotype coding. The paired Hotelling's T2 tests take not only the correlation between the haplotype blocks or markers into account, but also take the correlation within each parent-offspring pair into account. The method extends two sample Hotelling's T2 test statistics for population case control association studies, which are not valid for family data due to correlation of genetic data among family members. The validity of the proposed method is justified by rigorous mathematical and statistical proof under the large sample theory. The non-centrality parameter approximations of the test statistics are calculated for power and sample size calculations. From power comparison and type I error calculations, it is shown that the test statistic based on haplotype/allele coding is advantageous over the test statistic of genotype coding. Analysis using multiple markers may provide higher power than single marker analysis. If only one marker is utilized the power of the test statistic based on haplotype/allele coding is nearly identical to that of 1-TDT. Moreover, a permutation procedure is provided for data analysis. The method is applied to data from a German asthma family study. The results based on the paired Hotelling's T2 statistic tests confirm the previous findings. However, the paired Hotelling's T2 tests produce much smaller P-values than those of the previous study. The permutation tests produce similar results to those of the previous study; moreover, additional marker combinations are shown to be significant by permutation tests. The proposed paired Hotelling's T2 statistic tests are potentially powerful in mapping complex diseases. A SAS Macro, Hotel_fam.sas, has been written to implement the method for data analysis.
AU  - Fan, R.*
AU  - Knapp, M.*
AU  - Wjst, M.
AU  - Zhao, C.*
AU  - Xiong, M.*
C1  - 4546
C2  - 22618
SP  - 187-208
TI  - High resolution T² association tests of complex diseases based on family data.
JO  - Ann. Hum. Genet.
VL  - 69
IS  - 2
PY  - 2005
SN  - 0003-4800
ER  -