Nature CommunicationsGenomicsPeer-reviewed journal article
Deep-coverage whole genome sequences and blood lipids among 16,324 individuals
Pradeep NatarajaniD, Gina Marie PelosoiD, Seyedeh Maryam ZekavatiD, May E. MontasseriD, Andrea GannaiD, Mark D. ChaffiniD, Amit V. KheraiD, Wei ZhouiD, Jonathan M. BloomiD, J EngreitziD, Jason ErnstiD, Jeffrey R. O’ConnelliD, Sanni RuotsalaineniD, Maris AlveriD, Ani W ManichaikuliD, W. Craig JohnsoniD, James A. PerryiD, Timothy PoterbaiD, Cotton Seed, Ida L. SurakkaiD, Tõnu EskoiD, Samuli RipattiiD, Veikko V SalomaaiD, Adolfo CorreaiD, Ramachandran Srini VasaniD, , Sayantan DasiD
Abstract
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).
- organism: human
- assay: whole-genome sequencing
- research focus: variant effect prediction
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 184
- FWCI
- 15.89
- Field percentile
- top 1%
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