Whole Genome Sequence Association Analysis of Fasting Glucose and Fasting Insulin Levels in Diverse Cohorts from the NHLBI TOPMed Program

dc.contributor.authorDiCorpo, Daniel
dc.contributor.authorGaynor, Sheila M.
dc.contributor.authorRussell, Emily M.
dc.contributor.authorWesterman, Kenneth E.
dc.contributor.authorRaffield, Laura M.
dc.contributor.authorMajarian, Timothy D.
dc.contributor.authorWu, Peitao
dc.contributor.authorSarnowski, Chloé
dc.contributor.authorHighland, Heather M.
dc.contributor.authorJackson, Anne
dc.contributor.authorHasbani, Natalie R.
dc.contributor.authorde Vries, Paul S.
dc.contributor.authorBrody, Jennifer A.
dc.contributor.authorHidalgo, Bertha
dc.contributor.authorGuo, Xiuqing
dc.contributor.authorPerry, James A.
dc.contributor.authorO’Connell, Jeffrey R.
dc.contributor.authorLent, Samantha
dc.contributor.authorMontasser, May E.
dc.contributor.authorCade, Brian E.
dc.contributor.authorJain, Deepti
dc.contributor.authorWang, Heming
dc.contributor.authorD’Oliveira Albanus, Ricardo
dc.contributor.authorVarshney, Arushi
dc.contributor.authorYanek, Lisa R.
dc.contributor.authorLange, Leslie
dc.contributor.authorPalmer, Nicholette D.
dc.contributor.authorAlmeida, Marcio
dc.contributor.authorPeralta, Juan M.
dc.contributor.authorAslibekyan, Stella
dc.contributor.authorBaldridge, Abigail S.
dc.contributor.authorBertoni, Alain G.
dc.contributor.authorBielak, Lawrence F.
dc.contributor.authorChen, Chung-Shiuan
dc.contributor.authorChen, Yii-Der Ida
dc.contributor.authorChoi, Won Jung
dc.contributor.authorGoodarzi, Mark O.
dc.contributor.authorFloyd, James S.
dc.contributor.authorIrvin, Marguerite R.
dc.contributor.authorKalyani, Rita R.
dc.contributor.authorKelly, Tanika N.
dc.contributor.authorLee, Seonwook
dc.contributor.authorLiu, Ching-Ti
dc.contributor.authorLoesch, Douglas
dc.contributor.authorManson, JoAnn E.
dc.contributor.authorMinster, Ryan L.
dc.contributor.authorNaseri, Take
dc.contributor.authorPankow, James S.
dc.contributor.authorRasmussen-Torvik, Laura J.
dc.contributor.authorReiner, Alexander P.
dc.contributor.authorReupena, Muagututi’a Sefuiva
dc.contributor.authorSelvin, Elizabeth
dc.contributor.authorSmith, Jennifer A.
dc.contributor.authorWeeks, Daniel E.
dc.contributor.authorXu, Huichun
dc.contributor.authorYao, Jie
dc.contributor.authorZhao, Wei
dc.contributor.authorParker, Stephen
dc.contributor.authorAlonso, Alvaro
dc.contributor.authorArnett, Donna K.
dc.contributor.authorBlangero, John
dc.contributor.authorBoerwinkle, Eric
dc.contributor.authorCorrea, Adolfo
dc.contributor.authorCupples, L. Adrienne
dc.contributor.authorCurran, Joanne E.
dc.contributor.authorDuggirala, Ravindranath
dc.contributor.authorHe, Jiang
dc.contributor.authorHeckbert, Susan R.
dc.contributor.authorKardia, Sharon L.R.
dc.contributor.authorKim, Ryan W.
dc.contributor.authorKooperberg, Charles
dc.contributor.authorLiu, Simin
dc.contributor.authorMathias, Rasika A.
dc.contributor.authorMcGarvey, Stephen T.
dc.contributor.authorMitchell, Braxton D.
dc.contributor.authorMorrison, Alanna C.
dc.contributor.authorPeyser, Patricia A.
dc.contributor.authorPsaty, Bruce M.
dc.contributor.authorRedline, Susan
dc.contributor.authorShuldiner, Alan R.
dc.contributor.authorTaylor, Kent D.
dc.contributor.authorVasan, Ramachandran S.
dc.contributor.authorViaud-Martinez, Karine A.
dc.contributor.authorFlorez, Jose C.
dc.contributor.authorWilson, James G.
dc.contributor.authorSladek, Robert
dc.contributor.authorRich, Stephen S.
dc.contributor.authorRotter, Jerome I.
dc.contributor.authorLin, Xihong
dc.contributor.authorDupuis, Josée
dc.contributor.authorMeigs, James B.
dc.contributor.authorWessel, Jennifer
dc.contributor.authorManning, Alisa K.
dc.contributor.departmentEpidemiology, School of Public Health
dc.date.accessioned2023-07-21T16:37:51Z
dc.date.available2023-07-21T16:37:51Z
dc.date.issued2022-07-28
dc.description.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.
dc.eprint.versionFinal published version
dc.identifier.citationDiCorpo D, Gaynor SM, Russell EM, et al. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program. Commun Biol. 2022;5(1):756. Published 2022 Jul 28. doi:10.1038/s42003-022-03702-4
dc.identifier.urihttps://hdl.handle.net/1805/34535
dc.language.isoen_US
dc.publisherSpringer Nature
dc.relation.isversionof10.1038/s42003-022-03702-4
dc.relation.journalCommunications Biology
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMC
dc.subjectSequencing
dc.subjectGenetics research
dc.subjectDiabetes
dc.subjectQuantitative trait
dc.titleWhole Genome Sequence Association Analysis of Fasting Glucose and Fasting Insulin Levels in Diverse Cohorts from the NHLBI TOPMed Program
dc.typeArticle
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