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Genetic-risk assessment of GWAS-derived susceptibility loci for type 2 diabetes in a 10 year follow-up of a population-based cohort study
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نویسنده
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Go Min Jin ,Lee Young ,Park Suyeon ,Kwak Soo Heon ,Kim Bong-Jo ,Lee Juyoung
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منبع
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journal of human genetics - 2016 - دوره : 61 - شماره : 12 - صفحه:1009 -1012
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چکیده
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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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آدرس
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Korea National Institute of Health, Division of Structural and Functional Genomics, South Korea, Korea National Institute of Health, Division of Structural and Functional Genomics, South Korea, Korea National Institute of Health, Division of Structural and Functional Genomics, South Korea. Soonchunhyang University, Department of Biostatistics, South Korea, Seoul National University Hospital, Department of Internal Medicine, South Korea, Korea National Institute of Health, Division of Structural and Functional Genomics, South Korea, Korea National Institute of Health, Division of Structural and Functional Genomics, South Korea
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Authors
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