Literature DB >> 27111120

Type 2 Diabetes Prevention: Implications of Hemoglobin A1c Genetics.

Aaron Leong1, James B Meigs1.   

Abstract

Hemoglobin A1c (HbA1c) is a biomarker used for population-level screening of type 2 diabetes (T2D) and risk stratification. Large-scale, genome-wide association studies have identified multiple genomic loci influencing HbA1c. We discuss the challenges of classifying these genomic loci as influencing HbA1c through glycemic or nonglycemic pathways, based on their probable biology and pleiotropic associations with erythrocyte traits. We show that putative nonglycemic genetic variants have a measurable, albeit small, impact on the classification of T2D status by HbA1c in white and Asian populations. Accounting for their effect on HbA1c may be relevant when screening populations with higher frequencies of nonglycemic HbA1c-altering alleles. As carriers of such HbA1c-altering alleles have HbA1c levels that may not accurately reflect overall glycemia, we describe how accounting for genotype may improve the performance of HbA1c in T2D prediction models and risk stratification, allowing for lifestyle intervention strategies to be directed towards those who are truly at elevated risk for developing T2D. In a Mendelian randomization framework, genetic variants can be used as instrumental variables to estimate causal relationships between HbA1c and T2D-related complications. This approach may help to support or refute HbA1c as an appropriate biomarker for long-term health outcomes in the general population.

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Year:  2016        PMID: 27111120      PMCID: PMC5275759          DOI: 10.1900/RDS.2015.12.351

Source DB:  PubMed          Journal:  Rev Diabet Stud        ISSN: 1613-6071


  85 in total

1.  A risk score for predicting the incidence of type 2 diabetes in a middle-aged Korean cohort: the Korean genome and epidemiology study.

Authors:  Nam-Kyoo Lim; Sung-Hee Park; Sun-Ja Choi; Kwang-Soo Lee; Hyun-Young Park
Journal:  Circ J       Date:  2012-05-28       Impact factor: 2.993

2.  Is the measurement of glycated hemoglobin A1c alone an efficient screening test for undiagnosed diabetes? Japan National Diabetes Survey.

Authors:  Tomoko Nakagami; Makoto Tominaga; Rimei Nishimura; Nobuo Yoshiike; Makoto Daimon; Toshihide Oizumi; Naoko Tajima
Journal:  Diabetes Res Clin Pract       Date:  2006-10-17       Impact factor: 5.602

3.  Increased hemoglobin A1c threshold for prediabetes remarkably improving the agreement between A1c and oral glucose tolerance test criteria in obese population.

Authors:  Jie Li; Hao Ma; Lixin Na; Shuo Jiang; Lin Lv; Gang Li; Wei Zhang; Guanqiong Na; Ying Li; Changhao Sun
Journal:  J Clin Endocrinol Metab       Date:  2015-03-09       Impact factor: 5.958

Review 4.  Gene expression and biological significance of hexokinase in erythroid cells.

Authors:  Koko Murakami; Hitoshi Kanno; Jakica Tancabelic; Hisaichi Fujii
Journal:  Acta Haematol       Date:  2002       Impact factor: 2.195

5.  HbA(1c) in the prediction of type 2 diabetes compared with fasting and 2-h post-challenge plasma glucose: The Asturias study (1998-2005).

Authors:  S Valdés; P Botas; E Delgado; F Alvarez; F Díaz-Cadórniga
Journal:  Diabetes Metab       Date:  2010-10-08       Impact factor: 6.041

Review 6.  The network of glucokinase-expressing cells in glucose homeostasis and the potential of glucokinase activators for diabetes therapy.

Authors:  Franz M Matschinsky; Mark A Magnuson; Dorothy Zelent; Tom L Jetton; Nicolai Doliba; Yi Han; Rebecca Taub; Joseph Grimsby
Journal:  Diabetes       Date:  2006-01       Impact factor: 9.461

7.  Effect of iron deficiency anemia on the levels of hemoglobin A1c in nondiabetic patients.

Authors:  Erkan Coban; Mustafa Ozdogan; Aysen Timuragaoglu
Journal:  Acta Haematol       Date:  2004       Impact factor: 2.195

8.  Common variants near TERC are associated with mean telomere length.

Authors:  Veryan Codd; Massimo Mangino; Pim van der Harst; Peter S Braund; Michael Kaiser; Alan J Beveridge; Suzanne Rafelt; Jasbir Moore; Chris Nelson; Nicole Soranzo; Guangju Zhai; Ana M Valdes; Hannah Blackburn; Irene Mateo Leach; Rudolf A de Boer; Masayuki Kimura; Abraham Aviv; Alison H Goodall; Willem Ouwehand; Dirk J van Veldhuisen; Wiek H van Gilst; Gerjan Navis; Paul R Burton; Martin D Tobin; Alistair S Hall; John R Thompson; Tim Spector; Nilesh J Samani
Journal:  Nat Genet       Date:  2010-02-07       Impact factor: 38.330

9.  Common variants at 10 genomic loci influence hemoglobin A₁(C) levels via glycemic and nonglycemic pathways.

Authors:  Nicole Soranzo; Serena Sanna; Eleanor Wheeler; Christian Gieger; Dörte Radke; Josée Dupuis; Nabila Bouatia-Naji; Claudia Langenberg; Inga Prokopenko; Elliot Stolerman; Manjinder S Sandhu; Matthew M Heeney; Joseph M Devaney; Muredach P Reilly; Sally L Ricketts; Alexandre F R Stewart; Benjamin F Voight; Christina Willenborg; Benjamin Wright; David Altshuler; Dan Arking; Beverley Balkau; Daniel Barnes; Eric Boerwinkle; Bernhard Böhm; Amélie Bonnefond; Lori L Bonnycastle; Dorret I Boomsma; Stefan R Bornstein; Yvonne Böttcher; Suzannah Bumpstead; Mary Susan Burnett-Miller; Harry Campbell; Antonio Cao; John Chambers; Robert Clark; Francis S Collins; Josef Coresh; Eco J C de Geus; Mariano Dei; Panos Deloukas; Angela Döring; Josephine M Egan; Roberto Elosua; Luigi Ferrucci; Nita Forouhi; Caroline S Fox; Christopher Franklin; Maria Grazia Franzosi; Sophie Gallina; Anuj Goel; Jürgen Graessler; Harald Grallert; Andreas Greinacher; David Hadley; Alistair Hall; Anders Hamsten; Caroline Hayward; Simon Heath; Christian Herder; Georg Homuth; Jouke-Jan Hottenga; Rachel Hunter-Merrill; Thomas Illig; Anne U Jackson; Antti Jula; Marcus Kleber; Christopher W Knouff; Augustine Kong; Jaspal Kooner; Anna Köttgen; Peter Kovacs; Knut Krohn; Brigitte Kühnel; Johanna Kuusisto; Markku Laakso; Mark Lathrop; Cécile Lecoeur; Man Li; Mingyao Li; Ruth J F Loos; Jian'an Luan; Valeriya Lyssenko; Reedik Mägi; Patrik K E Magnusson; Anders Mälarstig; Massimo Mangino; María Teresa Martínez-Larrad; Winfried März; Wendy L McArdle; Ruth McPherson; Christa Meisinger; Thomas Meitinger; Olle Melander; Karen L Mohlke; Vincent E Mooser; Mario A Morken; Narisu Narisu; David M Nathan; Matthias Nauck; Chris O'Donnell; Konrad Oexle; Nazario Olla; James S Pankow; Felicity Payne; John F Peden; Nancy L Pedersen; Leena Peltonen; Markus Perola; Ozren Polasek; Eleonora Porcu; Daniel J Rader; Wolfgang Rathmann; Samuli Ripatti; Ghislain Rocheleau; Michael Roden; Igor Rudan; Veikko Salomaa; Richa Saxena; David Schlessinger; Heribert Schunkert; Peter Schwarz; Udo Seedorf; Elizabeth Selvin; Manuel Serrano-Ríos; Peter Shrader; Angela Silveira; David Siscovick; Kjioung Song; Timothy D Spector; Kari Stefansson; Valgerdur Steinthorsdottir; David P Strachan; Rona Strawbridge; Michael Stumvoll; Ida Surakka; Amy J Swift; Toshiko Tanaka; Alexander Teumer; Gudmar Thorleifsson; Unnur Thorsteinsdottir; Anke Tönjes; Gianluca Usala; Veronique Vitart; Henry Völzke; Henri Wallaschofski; Dawn M Waterworth; Hugh Watkins; H-Erich Wichmann; Sarah H Wild; Gonneke Willemsen; Gordon H Williams; James F Wilson; Juliane Winkelmann; Alan F Wright; Carina Zabena; Jing Hua Zhao; Stephen E Epstein; Jeanette Erdmann; Hakon H Hakonarson; Sekar Kathiresan; Kay-Tee Khaw; Robert Roberts; Nilesh J Samani; Mark D Fleming; Robert Sladek; Gonçalo Abecasis; Michael Boehnke; Philippe Froguel; Leif Groop; Mark I McCarthy; W H Linda Kao; Jose C Florez; Manuela Uda; Nicholas J Wareham; Inês Barroso; James B Meigs
Journal:  Diabetes       Date:  2010-09-21       Impact factor: 9.461

10.  Multiple nonglycemic genomic loci are newly associated with blood level of glycated hemoglobin in East Asians.

Authors:  Peng Chen; Fumihiko Takeuchi; Jong-Young Lee; Huaixing Li; Jer-Yuarn Wu; Jun Liang; Jirong Long; Yasuharu Tabara; Mark O Goodarzi; Mark A Pereira; Young Jin Kim; Min Jin Go; Daniel O Stram; Eranga Vithana; Chiea-Chuen Khor; Jianjun Liu; Jiemin Liao; Xingwang Ye; Yiqin Wang; Ling Lu; Terri L Young; Jeannette Lee; Ah Chuan Thai; Ching-Yu Cheng; Rob M van Dam; Yechiel Friedlander; Chew-Kiat Heng; Woon-Puay Koh; Chien-Hsiun Chen; Li-Ching Chang; Wen-Harn Pan; Qibin Qi; Masato Isono; Wei Zheng; Qiuyin Cai; Yutang Gao; Ken Yamamoto; Keizo Ohnaka; Ryoichi Takayanagi; Yoshikuni Kita; Hirotsugu Ueshima; Chao A Hsiung; Jinrui Cui; Wayne H-H Sheu; Jerome I Rotter; Yii-Der I Chen; Chris Hsu; Yukinori Okada; Michiaki Kubo; Atsushi Takahashi; Toshihiro Tanaka; Frank J A van Rooij; Santhi K Ganesh; Jinyan Huang; Tao Huang; Jianmin Yuan; Joo-Yeon Hwang; Myron D Gross; Themistocles L Assimes; Tetsuro Miki; Xiao-Ou Shu; Lu Qi; Yuan-Tson Chen; Xu Lin; Tin Aung; Tien-Yin Wong; Yik-Ying Teo; Bong-Jo Kim; Norihiro Kato; E-Shyong Tai
Journal:  Diabetes       Date:  2014-03-19       Impact factor: 9.461

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  3 in total

1.  Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.

Authors:  Chloé Sarnowski; Aaron Leong; Laura M Raffield; Peitao Wu; Paul S de Vries; Daniel DiCorpo; Xiuqing Guo; Huichun Xu; Yongmei Liu; Xiuwen Zheng; Yao Hu; Jennifer A Brody; Mark O Goodarzi; Bertha A Hidalgo; Heather M Highland; Deepti Jain; Ching-Ti Liu; Rakhi P Naik; Jeffrey R O'Connell; James A Perry; Bianca C Porneala; Elizabeth Selvin; Jennifer Wessel; Bruce M Psaty; Joanne E Curran; Juan M Peralta; John Blangero; Charles Kooperberg; Rasika Mathias; Andrew D Johnson; Alexander P Reiner; Braxton D Mitchell; L Adrienne Cupples; Ramachandran S Vasan; Adolfo Correa; Alanna C Morrison; Eric Boerwinkle; Jerome I Rotter; Stephen S Rich; Alisa K Manning; Josée Dupuis; James B Meigs
Journal:  Am J Hum Genet       Date:  2019-09-26       Impact factor: 11.025

2.  Genome-wide meta-analysis in Japanese populations identifies novel variants at the TMC6-TMC8 and SIX3-SIX2 loci associated with HbA1c.

Authors:  Tsuyoshi Hachiya; Shohei Komaki; Yutaka Hasegawa; Hideki Ohmomo; Kozo Tanno; Atsushi Hozawa; Gen Tamiya; Masayuki Yamamoto; Kuniaki Ogasawara; Motoyuki Nakamura; Jiro Hitomi; Yasushi Ishigaki; Makoto Sasaki; Atsushi Shimizu
Journal:  Sci Rep       Date:  2017-11-23       Impact factor: 4.379

3.  Socioeconomic position links circulatory microbiota differences with biological age.

Authors:  Hannah Craven; Dagmara McGuinness; Sarah Buchanan; Norman Galbraith; David H McGuinness; Brian Jones; Emilie Combet; Denise Mafra; Peter Bergman; Anne Ellaway; Peter Stenvinkel; Umer Z Ijaz; Paul G Shiels
Journal:  Sci Rep       Date:  2021-06-16       Impact factor: 4.996

  3 in total

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