Will the interplay between genetic markers for risk factors for a disease and the disease itself bring genetics closer to clinical practice? Great expectations

Abstract

Since the beginning of the era of genome-wide association studies (GWAS), >1200 human GWAS have now examined >200 diseases and traits, and found almost 4000 single nucleotide polymorphism (SNP) associations.1 This number is quite impressive, but up to now it is largely unknown how we can incorporate these findings into the clinical setting. One of the challenges for successful GWAS in the future will be to apply the findings in a way that accelerates drug and diagnostics development. This includes better integration of genetic studies into the drug development process and a focus on the role of genetic variation in maintaining health as a blueprint for designing new drugs and diagnostics.2 To do so, we have to make a shift from intermediate phenotypes, such as systolic blood pressure, LDL-cholesterol levels, or C-reactive protein levels, to clinical outcomes such as coronary heart disease (CHD), myocardial infarction (MI), or diabetes. GWAS thus far have typically been designed to assess associations of millions of SNPs with only a single risk factor or disease.3 However, since many cardiovascular risk factors and biomarkers are correlated and in combination contribute to disease and traits, it is hypothesized that genetic associations for risk factors and traits must be overlapping.4 Thus, the question that has to be asked is whether SNPs associated with risk factors for clinical outcomes such as CHD or MI are also associated with the incidence of CHD and MI themselves, and vice …