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Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis

Author

Listed:
  • Eleanor Wheeler
  • Aaron Leong
  • Ching-Ti Liu
  • Marie-France Hivert
  • Rona J Strawbridge
  • Clara Podmore
  • Man Li
  • Jie Yao
  • Xueling Sim
  • Jaeyoung Hong
  • Audrey Y Chu
  • Weihua Zhang
  • Xu Wang
  • Peng Chen
  • Nisa M Maruthur
  • Bianca C Porneala
  • Stephen J Sharp
  • Yucheng Jia
  • Edmond K Kabagambe
  • Li-Ching Chang
  • Wei-Min Chen
  • Cathy E Elks
  • Daniel S Evans
  • Qiao Fan
  • Franco Giulianini
  • Min Jin Go
  • Jouke-Jan Hottenga
  • Yao Hu
  • Anne U Jackson
  • Stavroula Kanoni
  • Young Jin Kim
  • Marcus E Kleber
  • Claes Ladenvall
  • Cecile Lecoeur
  • Sing-Hui Lim
  • Yingchang Lu
  • Anubha Mahajan
  • Carola Marzi
  • Mike A Nalls
  • Pau Navarro
  • Ilja M Nolte
  • Lynda M Rose
  • Denis V Rybin
  • Serena Sanna
  • Yuan Shi
  • Daniel O Stram
  • Fumihiko Takeuchi
  • Shu Pei Tan
  • Peter J van der Most
  • Jana V Van Vliet-Ostaptchouk
  • Andrew Wong
  • Loic Yengo
  • Wanting Zhao
  • Anuj Goel
  • Maria Teresa Martinez Larrad
  • Dörte Radke
  • Perttu Salo
  • Toshiko Tanaka
  • Erik P A van Iperen
  • Goncalo Abecasis
  • Saima Afaq
  • Behrooz Z Alizadeh
  • Alain G Bertoni
  • Amelie Bonnefond
  • Yvonne Böttcher
  • Erwin P Bottinger
  • Harry Campbell
  • Olga D Carlson
  • Chien-Hsiun Chen
  • Yoon Shin Cho
  • W Timothy Garvey
  • Christian Gieger
  • Mark O Goodarzi
  • Harald Grallert
  • Anders Hamsten
  • Catharina A Hartman
  • Christian Herder
  • Chao Agnes Hsiung
  • Jie Huang
  • Michiya Igase
  • Masato Isono
  • Tomohiro Katsuya
  • Chiea-Chuen Khor
  • Wieland Kiess
  • Katsuhiko Kohara
  • Peter Kovacs
  • Juyoung Lee
  • Wen-Jane Lee
  • Benjamin Lehne
  • Huaixing Li
  • Jianjun Liu
  • Stephane Lobbens
  • Jian'an Luan
  • Valeriya Lyssenko
  • Thomas Meitinger
  • Tetsuro Miki
  • Iva Miljkovic
  • Sanghoon Moon
  • Antonella Mulas
  • Gabriele Müller
  • Martina Müller-Nurasyid
  • Ramaiah Nagaraja
  • Matthias Nauck
  • James S Pankow
  • Ozren Polasek
  • Inga Prokopenko
  • Paula S Ramos
  • Laura Rasmussen-Torvik
  • Wolfgang Rathmann
  • Stephen S Rich
  • Neil R Robertson
  • Michael Roden
  • Ronan Roussel
  • Igor Rudan
  • Robert A Scott
  • William R Scott
  • Bengt Sennblad
  • David S Siscovick
  • Konstantin Strauch
  • Liang Sun
  • Morris Swertz
  • Salman M Tajuddin
  • Kent D Taylor
  • Yik-Ying Teo
  • Yih Chung Tham
  • Anke Tönjes
  • Nicholas J Wareham
  • Gonneke Willemsen
  • Tom Wilsgaard
  • Aroon D Hingorani
  • EPIC-CVD Consortium
  • EPIC-InterAct Consortium
  • Lifelines Cohort Study
  • Josephine Egan
  • Luigi Ferrucci
  • G Kees Hovingh
  • Antti Jula
  • Mika Kivimaki
  • Meena Kumari
  • Inger Njølstad
  • Colin N A Palmer
  • Manuel Serrano Ríos
  • Michael Stumvoll
  • Hugh Watkins
  • Tin Aung
  • Matthias Blüher
  • Michael Boehnke
  • Dorret I Boomsma
  • Stefan R Bornstein
  • John C Chambers
  • Daniel I Chasman
  • Yii-Der Ida Chen
  • Yduan-Tsong Chen
  • Ching-Yu Cheng
  • Francesco Cucca
  • Eco J C de Geus
  • Panos Deloukas
  • Michele K Evans
  • Myriam Fornage
  • Yechiel Friedlander
  • Philippe Froguel
  • Leif Groop
  • Myron D Gross
  • Tamara B Harris
  • Caroline Hayward
  • Chew-Kiat Heng
  • Erik Ingelsson
  • Norihiro Kato
  • Bong-Jo Kim
  • Woon-Puay Koh
  • Jaspal S Kooner
  • Antje Körner
  • Diana Kuh
  • Johanna Kuusisto
  • Markku Laakso
  • Xu Lin
  • Yongmei Liu
  • Ruth J F Loos
  • Patrik K E Magnusson
  • Winfried März
  • Mark I McCarthy
  • Albertine J Oldehinkel
  • Ken K Ong
  • Nancy L Pedersen
  • Mark A Pereira
  • Annette Peters
  • Paul M Ridker
  • Charumathi Sabanayagam
  • Michele Sale
  • Danish Saleheen
  • Juha Saltevo
  • Peter EH Schwarz
  • Wayne H H Sheu
  • Harold Snieder
  • Timothy D Spector
  • Yasuharu Tabara
  • Jaakko Tuomilehto
  • Rob M van Dam
  • James G Wilson
  • James F Wilson
  • Bruce H R Wolffenbuttel
  • Tien Yin Wong
  • Jer-Yuarn Wu
  • Jian-Min Yuan
  • Alan B Zonderman
  • Nicole Soranzo
  • Xiuqing Guo
  • David J Roberts
  • Jose C Florez
  • Robert Sladek
  • Josée Dupuis
  • Andrew P Morris
  • E-Shyong Tai
  • Elizabeth Selvin
  • Jerome I Rotter
  • Claudia Langenberg
  • Inês Barroso
  • James B Meigs

Abstract

Background: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes. Methods & findings: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04–1.06, per HbA1c-raising allele, p = 3 × 10−29); whereas GS-E was not (OR = 1.00, 95% CI 0.99–1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66–0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38–0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55–0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants. Conclusions: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses. Ines Barroso and colleagues identify a genetic variant that leads to reduced levels of HbA1c in African American adults; 2% of this population are at risk of missed diagnosis for diabetes.Why was this study done?: What did the researchers do and find?: What do these findings mean?:

Suggested Citation

  • Eleanor Wheeler & Aaron Leong & Ching-Ti Liu & Marie-France Hivert & Rona J Strawbridge & Clara Podmore & Man Li & Jie Yao & Xueling Sim & Jaeyoung Hong & Audrey Y Chu & Weihua Zhang & Xu Wang & Peng , 2017. "Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis," PLOS Medicine, Public Library of Science, vol. 14(9), pages 1-30, September.
  • Handle: RePEc:plo:pmed00:1002383
    DOI: 10.1371/journal.pmed.1002383
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    1. Young Jin Kim & Sanghoon Moon & Mi Yeong Hwang & Sohee Han & Hye-Mi Jang & Jinhwa Kong & Dong Mun Shin & Kyungheon Yoon & Sung Min Kim & Jong-Eun Lee & Anubha Mahajan & Hyun-Young Park & Mark I. McCar, 2022. "The contribution of common and rare genetic variants to variation in metabolic traits in 288,137 East Asians," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Jennifer P. Nguyen & Timothy D. Arthur & Kyohei Fujita & Bianca M. Salgado & Margaret K. R. Donovan & Hiroko Matsui & Ji Hyun Kim & Agnieszka D’Antonio-Chronowska & Matteo D’Antonio & Kelly A. Frazer, 2023. "eQTL mapping in fetal-like pancreatic progenitor cells reveals early developmental insights into diabetes risk," Nature Communications, Nature, vol. 14(1), pages 1-22, December.

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