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

Valentina Iotchkova, Jie Huang, John A. Morris, Deepti Jain, Caterina Barbieri, Klaudia Walter, Josine L. Min, Lu Chen, William Astle, Massimilian Cocca, Patrick Deelen, Heather Elding, Aliki Eleni Farmaki, Christopher S. Franklin, Mattias Franberg, Tom R. Gaunt, Albert Hofman, Tao Jiang, Marcus E. Kleber, Genevieve LachanceJian'An Luan, Giovanni Malerba, Angela Matchan, Daniel Mead, Yasin Memari, Ioanna Ntalla, Kalliope Panoutsopoulou, Raha Pazoki, John R B Perry, Fernando Rivadeneira, Maria Sabater-Lleal, Bengt Sennblad, So Youn Shin, Lorraine Southam, Michela Traglia, Freerk Van Dijk, Elisabeth M. Van Leeuwen, Gianluigi Zaza, Weihua Zhang, Najaf Amin, Adam Butterworth, John C. Chambers, George Dedoussis, Abbas Dehghan, Oscar H. Franco, Lude Franke, Mattia Frontini, Giovanni Gambaro, Paolo Gasparini, Daniela Toniolo, UK10K Consortium

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)1303-1312
Number of pages10
JournalNature Genetics
Volume48
Issue number11
DOIs
Publication statusPublished - Nov 1 2016

ASJC Scopus subject areas

  • Genetics

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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., Franberg, M., Gaunt, T. R., Hofman, A., Jiang, T., Kleber, M. E., ... UK10K Consortium (2016). Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps. Nature Genetics, 48(11), 1303-1312. https://doi.org/10.1038/ng.3668