Title: Genetic Risk Factors for Type 2 Diabetes: Insights from the Emerging Genomic Evidence
Volume: 10
Issue: 2
Author(s): Evangelia E. Ntzani and Fotini K. Kavvoura
Affiliation:
Keywords:
Complex traits, genome-wide association studies, risk score, systematic review, type 2 diabetes, heritability, hyperglycaemia, obesity, stroke, cardiovascular disease
Abstract: Type-2 diabetes is a complex disease modified by a number of environmental and genetic factors that contribute at varying degrees to the final phenotype and possibly interact with each other. Deciphering the genetic background of the disease serves multiple goals ranging from expanding our knowledge on the disease pathogenesis and identifying future targets for drug development to successfully personalizing clinical disease prediction and prognosis. In the present review, we aimed to systematically appraise the current evidence from genome-wide association studies (GWAS) on type- 2 diabetes, identify the gene targets that have been assessed to-date, and discuss issues that stem from the rapid growth of this literature. Our search identified more than 60 recently identified loci implicated with type-2 diabetes and related traits assessed in populations of European and Asian ancestry. A considerable number of the proposed genes seem to be related to beta-cell development and function, but there are several genes identified as “diabetes-genes” whose underlying pathway linked to diabetes remains poorly understood. Despite the increasing numbers of identified genetic markers, a large proportion of the observed type-2 diabetes heritability remains unexplained; larger GWAS on enhanced genotyping platforms, refined ascertainment of the characteristics of the populations under study and additional information from wholegenome sequencing will contribute to a more comprehensive view of the genetic architecture of the disease. This information is also anticipated to improve the predictive ability of multiple-loci genetic risk scores that will eventually be able to identify disease susceptibility over and above the traditional non-genetic risk factors.
