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Nature Research, Communications Biology, 1(5), 2022

DOI: 10.1038/s42003-022-03702-4

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Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program

Journal article published in 2022 by Sheila M. Gaynor, Daniel DiCorpo, Emily M. Russell, Kenneth E. Westerman ORCID, Paul S. de Vries, Laura M. Raffield ORCID, Timothy D. Majarian, Heather M. Highland ORCID, Natalie R. Hasbani, Jennifer A. Brody, Lisa R. Yanek ORCID, Bertha Hidalgo, Gaynor Sm, Xiuqing Guo, James A. Perry ORCID and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

AbstractThe genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.