Literature DB >> 27439680

Genetic-risk assessment of GWAS-derived susceptibility loci for type 2 diabetes in a 10 year follow-up of a population-based cohort study.

Min Jin Go1, Young Lee1, Suyeon Park1,2, Soo Heon Kwak3, Bong-Jo Kim1, Juyoung Lee1.   

Abstract

To date, genome-wide meta-analyses have identified genetic susceptibility to type 2 diabetes mellitus (T2D) predominantly in populations of European ancestry. However, comprehensive genetic-risk assessment based on previous GWAS loci has not been fully tested in non-European populations. To evaluate whether a genetic-risk score (GRS) could improve T2D-risk prediction in the Korean population, a GRS (GRS-55) was constructed by summing 55 risk alleles based on the 1000 Genomes imputation in the Korean Association Resource study (T2D cases=1042 and controls=2943 at baseline). We also constructed another GRS (GRS-19) based on nominal significance and consistent direction of effect. In mean difference tests, the mean value of the GRS-19 was significantly higher in T2D cases than in controls at baseline examination. In a model adjusted for area, age, sex and body mass index, weighted GRS-19 was found to be associated with enhanced effect sizes of T2D risk under consistent C-statistics. In addition, we confirmed cumulative risk effects on incidence rates of T2D, fasting plasma glucose and glycated hemoglobin (HbA1c) levels in a longitudinal 10 year of follow-up study. These findings highlight that a genotype score comprised of 19 common variants contributed to T2D-risk prediction in the Korean population. Further multi-locus epistatic interactions may provide the possibility to improve risk prediction in C-statistics for discrimination or reclassification.

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Year:  2016        PMID: 27439680     DOI: 10.1038/jhg.2016.93

Source DB:  PubMed          Journal:  J Hum Genet        ISSN: 1434-5161            Impact factor:   3.172


  32 in total

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Authors:  Marco Dauriz; Bianca C Porneala; Xiuqing Guo; Lawrence F Bielak; Patricia A Peyser; Nefertiti H Durant; Mercedes R Carnethon; Riccardo C Bonadonna; Enzo Bonora; Donald W Bowden; Jose C Florez; Myriam Fornage; Marie-France Hivert; David R Jacobs; Edmond K Kabagambe; Cora E Lewis; Joanne M Murabito; Laura J Rasmussen-Torvik; Stephen S Rich; Jason L Vassy; Jie Yao; Jeffrey J Carr; Sharon L R Kardia; David Siscovick; Christopher J O'Donnell; Jerome I Rotter; Josée Dupuis; James B Meigs
Journal:  Circ Cardiovasc Genet       Date:  2015-03-24

2.  Genetic risk assessment of type 2 diabetes-associated polymorphisms in African Americans.

Authors:  Jessica N Cooke; Maggie C Y Ng; Nicholette D Palmer; S Sandy An; Jessica M Hester; Barry I Freedman; Carl D Langefeld; Donald W Bowden
Journal:  Diabetes Care       Date:  2012-02       Impact factor: 19.112

3.  Identification of allelic heterogeneity at type-2 diabetes loci and impact on prediction.

Authors:  Yann C Klimentidis; Jin Zhou; Nathan E Wineinger
Journal:  PLoS One       Date:  2014-11-13       Impact factor: 3.240

4.  Gene-carbohydrate and gene-fiber interactions and type 2 diabetes in diverse populations from the National Health and Nutrition Examination Surveys (NHANES) as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study.

Authors:  Raquel Villegas; Robert J Goodloe; Bob E McClellan; Jonathan Boston; Dana C Crawford
Journal:  BMC Genet       Date:  2014-06-14       Impact factor: 2.797

5.  Genome-wide association study in a Chinese population identifies a susceptibility locus for type 2 diabetes at 7q32 near PAX4.

Authors:  R C W Ma; C Hu; C H Tam; R Zhang; P Kwan; T F Leung; G N Thomas; M J Go; K Hara; X Sim; J S K Ho; C Wang; H Li; L Lu; Y Wang; J W Li; Y Wang; V K L Lam; J Wang; W Yu; Y J Kim; D P Ng; H Fujita; K Panoutsopoulou; A G Day-Williams; H M Lee; A C W Ng; Y-J Fang; A P S Kong; F Jiang; X Ma; X Hou; S Tang; J Lu; T Yamauchi; S K W Tsui; J Woo; P C Leung; X Zhang; N L S Tang; H Y Sy; J Liu; T Y Wong; J Y Lee; S Maeda; G Xu; S S Cherny; T F Chan; M C Y Ng; K Xiang; A P Morris; S Keildson; R Hu; L Ji; X Lin; Y S Cho; T Kadowaki; E S Tai; E Zeggini; M I McCarthy; K L Hon; L Baum; B Tomlinson; W Y So; Y Bao; J C N Chan; W Jia
Journal:  Diabetologia       Date:  2013-03-27       Impact factor: 10.122

6.  Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.

Authors:  Ying Wu; Lindsay L Waite; Anne U Jackson; Wayne H-H Sheu; Steven Buyske; Devin Absher; Donna K Arnett; Eric Boerwinkle; Lori L Bonnycastle; Cara L Carty; Iona Cheng; Barbara Cochran; Damien C Croteau-Chonka; Logan Dumitrescu; Charles B Eaton; Nora Franceschini; Xiuqing Guo; Brian E Henderson; Lucia A Hindorff; Eric Kim; Leena Kinnunen; Pirjo Komulainen; Wen-Jane Lee; Loic Le Marchand; Yi Lin; Jaana Lindström; Oddgeir Lingaas-Holmen; Sabrina L Mitchell; Narisu Narisu; Jennifer G Robinson; Fred Schumacher; Alena Stančáková; Jouko Sundvall; Yun-Ju Sung; Amy J Swift; Wen-Chang Wang; Lynne Wilkens; Tom Wilsgaard; Alicia M Young; Linda S Adair; Christie M Ballantyne; Petra Bůžková; Aravinda Chakravarti; Francis S Collins; David Duggan; Alan B Feranil; Low-Tone Ho; Yi-Jen Hung; Steven C Hunt; Kristian Hveem; Jyh-Ming J Juang; Antero Y Kesäniemi; Johanna Kuusisto; Markku Laakso; Timo A Lakka; I-Te Lee; Mark F Leppert; Tara C Matise; Leena Moilanen; Inger Njølstad; Ulrike Peters; Thomas Quertermous; Rainer Rauramaa; Jerome I Rotter; Jouko Saramies; Jaakko Tuomilehto; Matti Uusitupa; Tzung-Dau Wang; Michael Boehnke; Christopher A Haiman; Yii-Der I Chen; Charles Kooperberg; Themistocles L Assimes; Dana C Crawford; Chao A Hsiung; Kari E North; Karen L Mohlke
Journal:  PLoS Genet       Date:  2013-03-21       Impact factor: 5.917

7.  The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases.

Authors:  Mirko Manchia; Jeffrey Cullis; Gustavo Turecki; Guy A Rouleau; Rudolf Uher; Martin Alda
Journal:  PLoS One       Date:  2013-10-11       Impact factor: 3.240

8.  Joint effects of known type 2 diabetes susceptibility loci in genome-wide association study of Singapore Chinese: the Singapore Chinese health study.

Authors:  Zhanghua Chen; Mark A Pereira; Mark Seielstad; Woon-Puay Koh; E Shyong Tai; Yik-Ying Teo; Jianjun Liu; Chris Hsu; Renwei Wang; Andrew O Odegaard; Bharat Thyagarajan; Revati Koratkar; Jian-Min Yuan; Myron D Gross; Daniel O Stram
Journal:  PLoS One       Date:  2014-02-10       Impact factor: 3.240

9.  Use of net reclassification improvement (NRI) method confirms the utility of combined genetic risk score to predict type 2 diabetes.

Authors:  Claudia H T Tam; Janice S K Ho; Ying Wang; Vincent K L Lam; Heung Man Lee; Guozhi Jiang; Eric S H Lau; Alice P S Kong; Xiaodan Fan; Jean L F Woo; Stephen K W Tsui; Maggie C Y Ng; Wing Yee So; Juliana C N Chan; Ronald C W Ma
Journal:  PLoS One       Date:  2013-12-20       Impact factor: 3.240

10.  Polygenic type 2 diabetes prediction at the limit of common variant detection.

Authors:  Jason L Vassy; Marie-France Hivert; Bianca Porneala; Marco Dauriz; Jose C Florez; Josée Dupuis; David S Siscovick; Myriam Fornage; Laura J Rasmussen-Torvik; Claude Bouchard; James B Meigs
Journal:  Diabetes       Date:  2014-02-11       Impact factor: 9.337

View more
  9 in total

1.  Genetic variants associated with patent ductus arteriosus in extremely preterm infants.

Authors:  John M Dagle; Kelli K Ryckman; Cassandra N Spracklen; Allison M Momany; C Michael Cotten; Joshua Levy; Grier P Page; Edward F Bell; Waldemar A Carlo; Seetha Shankaran; Ronald N Goldberg; Richard A Ehrenkranz; Jon E Tyson; Barbara J Stoll; Jeffrey C Murray
Journal:  J Perinatol       Date:  2018-12-05       Impact factor: 2.521

2.  Genetic risk scores in the prediction of plasma glucose, impaired insulin secretion, insulin resistance and incident type 2 diabetes in the METSIM study.

Authors:  Alena Stančáková; Teemu Kuulasmaa; Johanna Kuusisto; Karen L Mohlke; Francis S Collins; Michael Boehnke; Markku Laakso
Journal:  Diabetologia       Date:  2017-06-01       Impact factor: 10.122

3.  Relationship between glucose homeostasis and obesity in early life-a study of Italian children and adolescents.

Authors:  Zhanna Balkhiyarova; Rosa Luciano; Marika Kaakinen; Anna Ulrich; Aleksey Shmeliov; Marzia Bianchi; Laura Chioma; Bruno Dallapiccola; Inga Prokopenko; Melania Manco
Journal:  Hum Mol Genet       Date:  2022-03-03       Impact factor: 6.150

Review 4.  Knowledge discovery in genetics of diabetes in Iran, a roadmap for future researches.

Authors:  Saeed Ebrahimi Fana; Fataneh Esmaeili; Shahnaz Esmaeili; Fatemeh Bandaryan; Ensieh Nasli Esfahani; Mahsa Mohammad Amoli; Farideh Razi
Journal:  J Diabetes Metab Disord       Date:  2021-07-05

5.  Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer's disease.

Authors:  Samuel Morabito; Emily Miyoshi; Neethu Michael; Vivek Swarup
Journal:  Hum Mol Genet       Date:  2020-10-10       Impact factor: 6.150

6.  Screening of noise-induced hearing loss (NIHL)-associated SNPs and the assessment of its genetic susceptibility.

Authors:  Xuhui Zhang; Yaqin Ni; Yi Liu; Lei Zhang; Meibian Zhang; Xinyan Fang; Zhangping Yang; Qiang Wang; Hao Li; Yuyong Xia; Yimin Zhu
Journal:  Environ Health       Date:  2019-04-04       Impact factor: 5.984

7.  Prospective association of a genetic risk score with major adverse cardiovascular events in patients with coronary artery disease.

Authors:  Chen Zhao; Pin Zhu; Qile Shen; Li Jin
Journal:  Medicine (Baltimore)       Date:  2017-12       Impact factor: 1.817

8.  Genetic risk score of common genetic variants for impaired fasting glucose and newly diagnosed type 2 diabetes influences oxidative stress.

Authors:  Minjoo Kim; Minkyung Kim; Limin Huang; Sun Ha Jee; Jong Ho Lee
Journal:  Sci Rep       Date:  2018-05-18       Impact factor: 4.379

Review 9.  Biomarkers for type 2 diabetes.

Authors:  Markku Laakso
Journal:  Mol Metab       Date:  2019-09       Impact factor: 7.422

  9 in total

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