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Iotchkova, V.* ; Huang, J.* ; Morris, J.A.* ; Jain, D.* ; Barbieri, C.* ; Walter, K.* ; Min, J.L.* ; Chen, L.* ; Astle, W.* ; Cocca, M.* ; Deelen, P.* ; Elding, H.* ; Farmaki, A.E.* ; Franklin, C.S.* ; Frånberg, M.* ; Gaunt, T.R.* ; Hofman, A.* ; Jiang, T.* ; Kleber, M.E.* ; Lachance, G.* ; Luan, J.* ; Malerba, G.* ; Matchan, A.* ; Mead, D.* ; Memari, Y.* ; Ntalla, I.* ; Panoutsopoulou, K.* ; Pazoki, R.* ; Perry, J.R.B.* ; Rivadeneira, F.* ; Sabater-Lleal, M.* ; Sennblad, B.* ; Shin, S.Y.* ; Southam, L.* ; Traglia, M.* ; van Dijk, F.* ; van Leeuwen, E.M.* ; Zaza, G.* ; Zhang, W.* ; Amin, N.* ; Butterworth, A.S.* ; Chambers, J.C.* ; Dedoussis, G.* ; Dehghan, A.* ; Franco, O.H.* ; Franke, L.* ; Frontini, M.* ; Gambaro, G.* ; Gasparini, P.* ; Hamsten, A.* ; Issacs, A.* ; Kooner, J.S.* ; Kooperberg, C.* ; Langenberg, C.* ; Marz, W.* ; Scott, R.A.* ; Swertz, M.A.* ; Toniolo, D.* ; Uitterlinden, A.G.* ; van Duijn, C.M.* ; Watkins, H.* ; Zeggini, E. ; Maurano, M.T.* ; Timpson, N.J.* ; Reiner, A.P.* ; Auer, P.L.* ; Soranzo, N.*

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps.

Nat. Genet. 48, 1303-1312 (2016)

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Open Access Green as soon as Postprint is submitted to ZB.

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Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

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Publication type Article: Journal article

Document type Scientific Article

Corresponding Author

ISSN (print) / ISBN 1061-4036

e-ISSN 1546-1718

Journal Nature Genetics

Quellenangaben Volume: 48, Issue: 11, Pages: 1303-1312

Publisher Nature Publishing Group

Publishing Place New York, NY

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Institute of Translational Genomics (ITG)