Towards a complete resolution of the genetic architecture of disease

Abstract

After years of linear gains in the genetic dissection of human disease we are now in a period of exponential discovery. This is particularly apparent for complex disease. Genome-wide association studies (GWAS) have provided myriad associations between common variability and disease, and have shown that common genetic variability is unlikely to explain the entire genetic predisposition to disease. Here we detail how one can expand on this success and systematically identify genetic risks that lead or predispose to disease using next-generation sequencing. Geneticists have had for many years a protocol to identify Mendelian disease. A similar set of tools is now available for the identification of rare moderate-risk loci and common low-risk variants. Whereas major challenges undoubtedly remain, particularly regarding data handling and the functional classification of variants, we suggest that these will be largely practical and not conceptual.

Figure 1

Schematic of the genetic architecture landscape in disease and the applicability of current methods to finding risk and causative alleles. Modified from the concept presented by Manolio and colleagues.