Rader, D. J. — Page 2 | bioRxiv Science

bioRxiv2018

Genetic regulatory mechanisms of smooth muscle cells map to coronary artery disease risk loci

Coronary artery disease (CAD) is the leading cause of death globally. Genome-wide association studies (GWAS) have identified more than 95 independent loci that influence CAD risk, most of which reside in non-coding regions of the genome. To interpret these loci, we generated transcriptome and whole-genome datasets using human coronary artery smooth muscle cells (HCASMC) from 52 unrelated donors, as well as epigenomic datasets using ATAC-seq on a subset of 8 donors. Through systematic comparison with publicly available datasets from GTEx and ENCODE projects, we identified transcriptomic, epigenetic, and genetic regulatory mechanisms specific to HCASMC. We assessed the relevance of HCASMC to CAD risk using transcriptomic and epigenomic level analyses. By jointly modeling eQTL and GWAS datasets, we identified five genes (SIPA1, TCF21, SMAD3, FES, and PDGFRA) that modulate CAD risk through HCASMC, all of which have relevant functional roles in vascular remodeling. Comparison with GTEx data suggests that SIPA1 and PDGFRA influence CAD risk predominantly through HCASMC, while other annotated genes may have multiple cell and tissue targets. Together, these results provide new tissue-specific and mechanistic insights into the regulation of a critical vascular cell type associated with CAD in human populations.

genomics↗

bioRxiv2017

Multiplexed targeted resequencing identifies coding and regulatory variation underlying phenotypic extremes of HDL-cholesterol in humans

Genome-wide association studies have uncovered common variants at many loci influencing human complex traits and diseases, such as high-density lipoprotein cholesterol (HDL-C). However, the contribution of the identified genes is difficult to ascertain from current efforts interrogating common variants with small effects. Thus, there is a pressing need for scalable, cost-effective strategies for uncovering causal variants, many of which may be rare and noncoding. Here, we used a multiplexed inversion probe (MIP) target capture approach to resequence both coding and regulatory regions at seven HDL-C associated loci in 797 individuals with extremely high HDL-C vs. 735 low-to-normal HDL-C controls. Our targets included protein-coding regions of GALNT2, APOA5, APOC3, SCARB1, CCDC92, ZNF664, CETP, and LIPG (>9 kb), and proximate noncoding regulatory features (>42 kb). Exome-wide genotyping in 1,114 of the 1,532 participants yielded a >90% genotyping concordance rate with MIP-identified variants in ~90% of participants. This approach rediscovered nearly all established GWAS associations in GALNT2, CETP, and LIPG loci with significant and concordant associations with HDL-C from our phenotypic-extremes design at 0.1% of the sample size of lipid GWAS studies. In addition, we identified a novel, rare, CETP noncoding variant enriched in the extreme high HDL-C group (P<0.01, Score Test). Our targeted resequencing of individuals at the HDL-C phenotypic extremes offers a novel, efficient, and cost-effective approach for identifying rare coding and noncoding variation differences in extreme phenotypes and supports the rationale for applying this methodology to uncover rare variation--particularly non-coding variation--underlying myriad complex traits.

genomics↗