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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Abstract
The genetics of type 2 diabetes (T2D) and dyslipidemia remain understudied in Hispanic/Latino populations despite worsening health disparities. Specifically, large-scale meta-analyses and functional interpretation have not previously been undertaken and represent an untapped resource for further discovery of metabolic disease etiology. In the most powerful genetic analysis of T2D and lipid traits in Hispanics to date, we present both single variant (~20M SNPs) and functionally oriented, gene-based (~7200 genes) findings in 13,152 T2D cases and 21,511 controls, and ~23,400 samples with measured HDL, LDL, triglycerides, and total cholesterol. Gene-based analyses revealed 34 novel lipid trait genes and one novel T2D gene, SLC22A18, located distally to known T2D gene KCNQ1. Gene ontology enrichment analysis of MetaXcan results identified very-low density lipoprotein remodeling, cholesterol homeostasis, and triglyceride homeostasis as the most significantly enriched biological pathways, lending further support to these novel association findings.
We then performed trans-ethnic meta-analysis of genome-wide association studies of type 2 diabetes (T2D) in 99,265 cases and 545,212 controls from diverse populations. We identified 110 loci at genome-wide significance (p<5x10-8), including 37 mapping outside regions previously implicated in the disease, with the strongest novel associations at/near INHBB (rs58884021, p=2.8x10-12), PLEKHA1 (rs2421016, p=3.2x10-12), and EIF5A2 (rs6804915, p=3.8x10-12). We identified 156 distinct association signals (p<10-5) across the 110 loci, including 11 at KCNQ1, 5 at INS-IGF2. Whilst allelic effects on T2D risk of index variants were predominantly consistent across populations, for the first time we observed strong evidence of heterogeneity that was correlated with ancestry. Fine-mapping analyses substantially improved localization of potential causal variants compared with previous efforts, highlighting 17 signals for which a single variant accounted for >99% of the posterior probability of driving the association. Integration of fine-mapping data and annotation revealed the posterior probability (π) to be significantly enriched in coding exons (p=1.4x10-5), for the first time including an index variant at the APOE-TOMM40 locus, APOE p.Cys130Arg (rs429358, π=99.2%). Via large-scale meta-analysis and analysis based on functional annotation, results highlight potential regulatory signatures that are predictive of metabolic health in Hispanic/Latino populations and demonstrate the utility of diverse populations for fine mapping.
