Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease.pdf (811.79 kB)
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Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease.

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posted on 17.05.2018, 08:38 by Connor A. Emdin, Amit V. Khera, Mark Chaffin, Derek Klarin, Pradeep Natarajan, Krishna Aragam, Mary Haas, Alexander Bick, Seyedeh M. Zekavat, Akihiro Nomura, Diego Ardissino, James G. Wilson, Heribert Schunkert, Ruth McPherson, Hugh Watkins, Roberto Elosua, Matthew J. Bown, Nilesh J. Samani, Usman Baber, Jeanette Erdmann, Namrata Gupta, John Danesh, Daniel Chasman, Paul Ridker, Joshua Denny, Lisa Bastarache, Judith H. Lichtman, Gail D'Onofrio, Jennifer Mattera, John A. Spertus, Wayne H.-H. Sheu, Kent D. Taylor, Bruce M. Psaty, Stephen S. Rich, Wendy Post, Jerome I. Rotter, Yii-Der Ida Chen, Harlan Krumholz, Danish Saleheen, Stacey Gabriel, Sekar Kathiresan
Less than 3% of protein-coding genetic variants are predicted to result in loss of protein function through the introduction of a stop codon, frameshift, or the disruption of an essential splice site; however, such predicted loss-of-function (pLOF) variants provide insight into effector transcript and direction of biological effect. In >400,000 UK Biobank participants, we conduct association analyses of 3759 pLOF variants with six metabolic traits, six cardiometabolic diseases, and twelve additional diseases. We identified 18 new low-frequency or rare (allele frequency < 5%) pLOF variant-phenotype associations. pLOF variants in the gene GPR151 protect against obesity and type 2 diabetes, in the gene IL33 against asthma and allergic disease, and in the gene IFIH1 against hypothyroidism. In the gene PDE3B, pLOF variants associate with elevated height, improved body fat distribution and protection from coronary artery disease. Our findings prioritize genes for which pharmacologic mimics of pLOF variants may lower risk for disease.


This research has been conducted using the UK Biobank resource, application 7089. The WGHS is supported by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913) with funding for genotyping provided by Amgen. The VIRGO study was supported by grant R01 HL081153-01A1K from the National Heart, Lung, and Blood Institute. The TAICHI study was supported by the National Health Research Institutes, Taiwan (PH-099-PP-03, PH-100-PP-03, PH-101-PP-03), the National Science Council, Taiwan (Grant Nos NSC 101-2314-B-075A-006-MY3, MOST 104-2314-B-075A-006-MY3, MOST 104-2314-B-075A-007, MOST 105-2314-B-075A-003), the Taichung Veterans General Hospital, Taiwan (TCVGH-1020101C, TCVGH-1020102D, TCVGH-1023102B, TCVGH-1023107D, TCVGH-1030101C, TCVGH-1030105D, TCVGH-1033503C, TCVGH-1033102B, TCVGH-1033108D, TCVGH-1040101C, TCVGH-1040102D, TCVGH-1043504C, TCVGH-1043104B), and the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881. The MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, and DK063491. Whole genome sequencing of the VIRGO and TAICHI cohorts was funded by grant 5UM1HG008895-02 from the National Human Genome Research Institute’s Center for Common Disease Genomics. Whole genome sequencing of the MESA cohort was funded through the Trans-Omics for Precision Medicine (TOPMed) Program of the National Heart, Lung, and Blood Institute. General study coordination was provided by the TOPMed Data Coordinating Center (3R01HL-12393-02S1). The contributions of the investigators of the NHLBI TOPMed Consortium (htt



Nature Communications, 2018, 9, 1613

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