Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. Genome-wide association study for type 2 diabetes: clinical applications Valeriya Lyssenko and Leif Groop Introduction Until recently, dissecting the genetics of complex poly- genic diseases in which environmental factors interact with genetic variants in the predisposition to the disease has not been a trivial task and success has been limited. In contrast, dissection of monogenic diseases has been a success story and mutations giving rise to six forms of monogenic forms of maturity onset diabetes of the young have been identified [1–3]. At the other end of the spectrum, the polygenic type 2 diabetes is caused by ‘mild’ variations in several genes, which interact with environmental triggers to cause late onset of the disease. There is ample evidence that type 2 diabetes has a strong genetic component. The concordance of type 2 diabetes in monozygotic twins is approximately 70% compared with 20–30% in dizygotic twins [4,5]. The lifetime risk of developing the disease is about 40% in offspring of one parent with type 2 diabetes – greater if the mother is affected – [6], the risk approaching 70% if both parents have diabetes. In prospective studies we have demon- strated that first-degree family history is associated with two-fold increased risk of future type 2 diabetes [7,8  ]. The challenge has been to find genetic markers which explain the excess risk associated with family history of diabetes. During the last years, the common variant– common disease hypothesis has emerged which assumes that common single-nucleotide polymorphisms (SNPs) (frequency >5%) increase susceptibility to polygenic diseases like type 2 diabetes and obesity. However, there are examples of rare variants influencing metabolic traits in the population [9,10], suggesting that both rare and common variants may contribute to the development of common diseases. Genome-wide association study approach for mapping genetic variability A problem in the field of genetics of complex diseases is the difficulty to replicate an initial association. The main reason for this is underpowered studies due to small sample size. The International HapMap Project (http:// www.hapmap.org) and a public–private SNP consortium Department of Clinical Sciences/Diabetes & Endocrinology and Lund University Diabetes Centre, Lund University, University Hospital Malmo ¨ , Malmo ¨, Sweden Correspondence to Dr Valeriya Lyssenko, MD, PhD, Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, CRC, University Hospital Malmo ¨ , 20502 Malmo ¨ , Sweden Tel: +46 40 391214; fax: +46 40 391222; e-mail: Valeri.Lyssenko@med.lu.se Current Opinion in Lipidology 2009, 20:87–91 Purpose of review Dissecting the genetics of complex polygenic diseases in which environmental factors interact with genetic variants in the predisposition to the disease has not been a trivial task and success has been limited. The purpose of this review is to provide insights into recent advances in genetics of type 2 diabetes. Recent findings In the past year, together the consortia of several genome-wide association studies for type 2 diabetes have identified 19 common variants increasing susceptibility to disease. Most novel loci seem to influence the capacity of beta-cells to increase insulin secretion in response to increase in insulin resistance or body weight. Combined genetic information ultimately might aid in personalized prediction of disease risk; however, genetic tests cannot be offered yet to predict disease. The main reason is that the increased risk associated with each risk variant is small. We have only begun to explore the role of rare variants with stronger effects or copy number variations in the pathogenesis of type 2 diabetes. Summary Rapid progress in the genetics of type 2 diabetes has significantly improved our understanding of disease pathogenesis and provided promising opportunities for drug discoveries over the coming years. Keywords beta-cell function, genome-wide association study, prediction, type 2 diabetes Curr Opin Lipidol 20:87–91 ß 2009 Wolters Kluwer Health | Lippincott Williams & Wilkins 0957-9672 0957-9672 ß 2009 Wolters Kluwer Health | Lippincott Williams & Wilkins DOI:10.1097/MOL.0b013e32832923af