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Characterizing common and rare variations in non-traditional glycemic biomarkers using multivariate approaches on multi-ancestry ARIC study.
Ray, Debashree; Loomis, Stephanie J; Venkataraghavan, Sowmya; Zhang, Jiachen; Tin, Adrienne; Yu, Bing; Chatterjee, Nilanjan; Selvin, Elizabeth; Duggal, Priya.
Afiliação
  • Ray D; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
  • Loomis SJ; Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
  • Venkataraghavan S; Biogen Inc, Cambridge, MA.
  • Zhang J; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
  • Tin A; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
  • Yu B; School of Medicine, University of Mississippi Medical Center, Jackson, MS.
  • Chatterjee N; Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX.
  • Selvin E; Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
  • Duggal P; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD.
Diabetes ; 2024 Jun 13.
Article em En | MEDLINE | ID: mdl-38869630
ABSTRACT
Genetic studies of non-traditional glycemic biomarkers, glycated albumin and fructosamine, can shed light on unknown aspects of type 2 diabetes genetics and biology. We performed a multi-phenotype GWAS of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on common variants from genotyped/imputed data. We discovered 2 genome-wide significant loci, one mapping to known type 2 diabetes gene (ARAP1/STARD10) and another mapping to a novel region (UGT1A complex of genes) using multi-omics gene-mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry- and sex-specific (e.g., PRKCA in African ancestry, FCGRT in European ancestry, TEX29 in males). Further, we implemented multi-phenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Ten variant sets annotated to genes across different variant aggregation strategies were exome-wide significant only in multi-ancestry analysis, of which CD1D, EGFL7/AGPAT2 and MIR126 had notable enrichment of rare predicted loss of function variants in African ancestry despite smaller sample sizes. Overall, 8 out of 14 discovered loci and genes were implicated to influence these biomarkers via glycemic pathways, and most of them were not previously implicated in studies of type 2 diabetes. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across the entire allele frequency spectrum in multi-ancestry analysis. Future investigation of the loci and genes potentially acting through glycemic pathways may help us better understand risk of developing type 2 diabetes.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Diabetes Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Moldávia

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Diabetes Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Moldávia