Deep-coverage whole genome sequences and blood lipids among 16,324 individuals
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Author(s)
Natarajan, Pradeep
Peloso, Gina M.
Zekavat, Seyedeh Maryam
Montasser, May
Ganna, Andrea
Chaffin, Mark
Khera, Amit V.
Zhou, Wei
Bloom, Jonathan M.
Engreitz, Jesse M.
Date Issued
August 2018
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Natarajan, Pradeep et al. “Deep-Coverage Whole Genome Sequences and Blood Lipids Among 16,324 Individuals.” Nature Communications 9, 1 (August 2018): 3391. © 2018 The Author(s)
Version
Final published version
Abstract
Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits—plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/s41467-018-05747-8
