Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes

Ng, Maggie; Shriner, Daniel; Chen, Brian H.; Jiang, Li; Chen, Weimin; Guo, Xiuqing; Liu, Jiankang; Bielinski, Suzette J.; Yanek, Lisa R.; Nalls, Michael A.; Comeau, Mary E.; Rasmussen‐Torvik, Laura J.; Jensen, Richard A.; Evans, Daniel S.; Sun, Yan V.; An, Ping; Patel, Sanjay R.; Lu, Yingchang; Long, Jirong; Armstrong, Loren L.; Wagenknecht, Lynne E.; Yang, Lingyao; Snively, Beverly M.; Palmer, Colin N.A.; Mudgal, Poorva; Langefeld, Carl D.; Keene, Keith L.; Freedman, Barry I.; Mychaleckyj, Josyf C.; Nayak, Uma; Raffel, Leslie J.; Goodarzi, Mark O.; Chen, Y-D Ida; Taylor, Herman A.; Correa, Adolfo; Sims, Mario; Couper, David J.; Pankow, James S.; Boerwinkle, Eric; Adeyemo, Adebowale; Doumatey, Ayo P.; Chen, Guanjie; Mathias, Rasika A.; Vaidya, Dhananjay; Singleton, Andrew B.; Zonderman, Alan B.; Igo, Robert P.; Sedor, John R.; Kabagambe, Edmond K.; Siscovick, David S.; McKnight, Barbara; Rice, Kenneth; Liu, Yongmei; Hsueh, Wen-Chi; Zhao, Wei; Bielak, Lawrence F.; Kraja, Aldi T.; Province, Michael A.; Böttinger, Erwin P.; Gottesman, Omri; Cai, Qiuyin; Wang, Zheng; Blot, William J.; Lowe, William L.; Pacheco, Jennifer A.; Crawford, Dana C.; Grundberg, Elin; Rich, Stephen S.; Hayes, M. Geoffrey; Shu, Xiao‐Ou; Loos, Ruth J.F.; Borecki, Ingrid B.; Peyser, Patricia A.; Cummings, Steven R.; Psaty, Bruce M.; Fornage, Myriam; Iyengar, Sudha K.; Evans, Michele K.; Becker, Diane M.; Kao, W. H. Linda; Wilson, James G.; Rotter, Jerome I.; Sale, Michèle M.; Liu, Simin; Rotimi, Charles N.; Bowden, Donald W.

doi:10.1371/journal.pgen.1004517

Cited by 196 publications

(165 citation statements)

References 64 publications

(84 reference statements)

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“…More than 100 gene loci associated with diabetes or diabetes-related phenotypes have been identified through genome-wide association (GWA) studies (MORRIS et al 2012;NG et al 2014;REPLICATION et al 2014;FLANNICK AND FLOREZ 2016;FUCHSBERGER et al 2016;JASON et al 2017). However, the effect size of each locus is small; their odds ratios are typically ~1.05 -1.10, and most of the heritability of T2D in human populations remains to be elucidated.…”

Section: Introductionmentioning

confidence: 99%

Genetic Drivers of Pancreatic Islet Function

et al. 2018

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The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we sensitized a genetically diverse mouse population with a Western diet high in fat (45%-kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression quantitative trait loci. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes (PDX1 and HNF4A), as well as three genes with nominal association with diabetes-related traits in humans (FAM83E, IL6ST, and SAT2). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse with those found in human populations and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping.4

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Section: Introductionmentioning

confidence: 99%

Genetic Drivers of Pancreatic Islet Function

et al. 2018

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“…Previous findings suggest that TCF7L2 and MTNR1B genes may also be involved with the development of T2DM [32]. As genetic markers of T2DM, three established loci (HMGA2, KCNQ1, and TCF7L2) and two novel loci (INS-IGF2, HLA-B) were identified at genome-wide significance [33]. As genetic testing advances, more genetic markers are being discovered.…”

Section: Genetic Etiologymentioning

confidence: 99%

Type 2 Diabetes Mellitus in Children and Adolescents: Early Prevention and Non-Drug Therapy

Lu-nan¹,

Long²,

Hui³

et al. 2017

JDM

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The global rate of type 2 diabetes mellitus (T2DM) in youth has increased dramatically in the last 30 years. This increase mirrors the global epidemic of childhood obesity. Studies show that, compared to adults who develop T2DM, youth with T2DM ultimately suffer from more harmful symptoms. The prevalence of T2DM and obesity in youth signals a significant public health issue that financially burdens governments, families, and individuals. Since evidence suggests that T2DM in youth is different from both type 1 and type 2 diabetes in adults, researchers and clinicians face many difficulties in developing new treatments. Most treatment efforts have relied on drugs; however, recent studies suggest that non-drug therapy also effectively reduces obesity and diabetic symptoms. Healthier eating, increased physical exercise, and positive mental health, are often underappreciated factors towards managing obesity. Yet these lifestyle changes empower both young and older patients to independently fight diseases and attain better health. To manage the global health risk of obesity, further research addressing the prevention and nondrug early intervention of T2DM and obesity in youth is urgently needed. The present review focuses on the latest updates in the field.

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“…These trans-ethnic findings provided further evidence of the reliability and robustness of GWASs. Imputation was carried out using either HapMap dataset or the 1000 genome dataset and provided dense genotyping that led to the identification of six new T2D loci in Japanese, African Americans, and Mexican and Latin Americans [48][49][50][51]. The availability of imputed genetic data in different ancestry groups also enabled meta-analyses using multiple ancestry groups, including one trans-ethnic meta-analysis that analyzed data from European, East Asian, South Asian, Mexican, and Mexican American studies to identify seven new T2D loci [52].…”

Section: Gwas Imputation and Meta-analysis In Diverse Ethnic Groupsmentioning

confidence: 99%

Complex Genetics of Type 2 Diabetes and Effect Size: What have We Learned from Isolated Populations?

Nair

Baier

2015

Rev Diabet Stud

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■ AbstractGenetic studies in large outbred populations have documented a complex, highly polygenic basis for type 2 diabetes (T2D). Most of the variants currently known to be associated with T2D risk have been identified in large studies that included tens of thousands of individuals who are representative of a single major ethnic group such as European, Asian, or African. However, most of these variants have only modest effects on the risk for T2D; identification of definitive 'causal variant' or 'causative loci' is typically lacking. Studies in isolated populations offer several advantages over outbred populations despite being, on average, much smaller in sample size. For example, reduced genetic variability, enrichment of rare variants, and a more uniform environment and lifestyle, which are hallmarks of isolated populations, can reduce the complexity of identifying disease-associated genes. To date, studies in isolated populations have provided valuable insight into the genetic basis of T2D by providing both a deeper understanding of previously identified T2D-associated variants (e.g. demonstrating that variants in KCNQ1 have a strong parent-of-origin effect) or providing novel variants (e.g. ABCC8 in Pima Indians, TBC1D4 in the Greenlandic population, HNF1A in Canadian Oji-Cree). This review summarizes advancements in genetic studies of T2D in outbred and isolated populations, and provides information on whether the difference in the prevalence of T2D in different populations (Pima Indians vs. non-Hispanic Whites and non-Hispanic Whites vs. non-Hispanic Blacks) can be explained by the difference in risk allele frequencies of established T2D variants.

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Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes

Cited by 196 publications

References 64 publications

Genetic Drivers of Pancreatic Islet Function

Genetic Drivers of Pancreatic Islet Function

Type 2 Diabetes Mellitus in Children and Adolescents: Early Prevention and Non-Drug Therapy

Complex Genetics of Type 2 Diabetes and Effect Size: What have We Learned from Isolated Populations?

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