Predicting Diabetes: Our Relentless Quest for Genomic Nuggets

DIABETES EPIDEMIC—The latest estimates from the Center for Disease Control and Prevention indicate that in 2010 approximately 26 million American adults had diabetes and 79 million had prediabetes (1). African Americans and other ethnic groups continue to suffer higher rates of diabetes than whites. Worldwide, diabetes affects 285 million adults (2). Type 2 diabetes accounts for ;95% of all cases. The exact reasons for the diabetes epidemic, and its predilection for certain ethnic groups, are unknown. However, interactions between genetic predisposition and environmental triggers (or accelerants) are generally presumed to underlie the etiology of diabetes (3–5) (Fig. 1). The best known environmental risk factors are dietary habits, physical inactivity, and obesity; interventions that ameliorate these risk factors prevent the development of type 2 diabetes (6,7). By contrast, knowledge of the genetic basis of diabetes is incomplete, despite Herculean efforts (8–12). Genome-wide association studies have accelerated the discovery of single-nucleotide polymorphisms (SNPs) at numerous loci. Comparison of the frequencies of these SNPs in case-control studies has enabled the calculation of the odds of their association with specific disease phenotypes. To date, genome-wide studies have added more than 4,000 SNPs involving some 200 diseases, including .30 diabetes-related SNPs (diabetoSNPs). The analysis of diabetoSNPs has intrinsic appeal as a tool for diabetes prediction, and could also yield potential clues to ethnic disparities in the susceptibility to type 2 diabetes. Because the diabetoSNPs individually confer modest effects, investigators have adopted an approach based on cumulative genetic risk score (GRS) at several loci to improve sensitivity (13–16). Using available information on the relative odds of diabetes per risk allele (11,12), investigators can further calculate a weighted GRS.