Genetic markers of type 2 diabetes: Progress in genome-wide association studies and clinical application for risk prediction

Xueyin Wang, Garrett Strizich, Yonghua Hu, Tao Wang, Robert C. Kaplan, Qibin Qi

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

Type 2 diabetes (T2D) has become a leading public health challenge worldwide. To date, a total of 83 susceptibility loci for T2D have been identified by genome-wide association studies (GWAS). Application of meta-analysis and modern genotype imputation approaches to GWAS data from diverse ethnic populations has been key in the effort to discover T2D loci. Genetic information is expected to play a vital role in the prediction of T2D, and many efforts have been made to develop T2D risk models that include both conventional and genetic risk factors. Yet, because most T2D genetic variants identified have small effect size individually (10%-20% increased risk of T2D per risk allele), their clinical utility remains unclear. Most studies report that a genetic risk score combining multiple T2D genetic variants does not substantially improve T2D risk prediction beyond conventional risk factors. In this article, we summarize the recent progress of T2D GWAS and further review the incremental predictive performance of genetic markers for T2D.

Original languageEnglish (US)
Pages (from-to)24-35
Number of pages12
JournalJournal of Diabetes
Volume8
Issue number1
DOIs
StatePublished - Jan 1 2016

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Keywords

  • Area under the receiver operating characteristic curve
  • Genetics
  • Genome-wide association studies
  • Type 2 diabetes

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism

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