Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 67,655 bioRxiv papers from 298,484 authors.
Deep-coverage whole genome sequences and blood lipids among 16,324 individuals
Gina M Peloso,
S. Maryam Zekavat,
Amit V Khera,
Jonathan M Bloom,
Jesse M. Engreitz,
Jeffrey R. O’Connell,
Sanni E Ruotsalainen,
W Craig Johnson,
James A Perry,
Ida L Surakka,
Ramachandran S Vasan,
Benjamin M Neale,
Eric S Lander,
Stephen S. Rich,
James G Wilson,
L Adrienne Cupples,
Jerome I Rotter,
NHLBI TOPMed Lipids Working Group,
Cristen J. Willer,
Posted 24 Nov 2017
bioRxiv DOI: 10.1101/224378 (published DOI: 10.1038/s41467-018-05747-8)
Posted 24 Nov 2017
Deep-coverage whole genome sequencing at the population level is now feasible and offers potential advantages for locus discovery, particularly in the analysis rare mutations in non-coding regions. Here, we performed whole genome sequencing in 16,324 participants from four ancestries at mean depth >29X and analyzed correlations of genotypes with four quantitative traits - plasma levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. We conducted a discovery analysis including common or rare variants in coding as well as non-coding regions and developed a framework to interpret genome sequence for dyslipidemia risk. Common variant association yielded loci previously described with the exception of a few variants not captured earlier by arrays or imputation. In coding sequence, rare variant association yielded known Mendelian dyslipidemia genes and, in non-coding sequence, we detected no rare variant association signals after application of four approaches to aggregate variants in non-coding regions. We developed a new, genome-wide polygenic score for LDL-C and observed that a high polygenic score conferred similar effect size to a monogenic mutation (~30 mg/dl higher LDL-C for each); however, among those with extremely high LDL-C, a high polygenic score was considerably more prevalent than a monogenic mutation (23% versus 2% of participants, respectively).
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