A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains

Abstract

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

Figure 1. Variables used to characterize six metabolic syndrome domains.

Figure 2. Multivariate association scan of the metabolic syndrome in n = 19,468 European American participants from five cohorts. Y-axis P–values are truncated at 1×10⁻²⁰.

Figure 3. Multivariate GWAS of metabolic syndrome in n = 6,287 African American participants from four cohorts. Y-axis P–values are truncated at 1×10⁻²⁰.

Figure 4. Regional association plots for metabolic syndrome trait dimensions associated with APOC1, BRAP, and PLCG1.

Positions are from NCBI build 36 and recombination rates are estimated from HapMap phase II CEU data. SNPs are represented by circles, and the large blue diamond is the SNP with the lowest P-value. Circle color represents correlation with the top SNP: blue indicates weak correlation and red indicates strong correlation. Recombination rate is plotted in the background and known genes in the region are shown at the bottom of the plot.