Exploring the unknown: assumptions about allelic architecture and strategies for susceptibility variant discovery

Abstract

Identification of common-variant associations for many common disorders has been highly effective, but the loci detected so far typically explain only a small proportion of the genetic predisposition to disease. Extending explained genetic variance is one of the major near-term goals of human genetic research. Next-generation sequencing technologies offer great promise, but optimal strategies for their deployment remain uncertain, not least because we lack a clear view of the characteristics of the variants being sought. Here, I discuss what can and cannot be inferred about complex trait disease architecture from the information currently available and review the implications for future research strategies.

Figure 1

Causal variant signals and their genomic distribution. Two possible versions of the state of nature are presented (see text). In one ('even'), causal variants differing in terms of allele frequency (color scale) and effect size (height of bar) are distributed randomly across the genome: the location of common-variant (red/orange) associations of modest effect provides no guide to the location of lower-frequency variants (yellow/green), some of which have quite large effects. In the other ('lumpy'), causal variants congregate around certain genomic positions ('genes'): GWA studies that reveal the location of the common-variant associations will also reveal the positions of lower-frequency variants, and the proportion of disease biology explained by the loci discovered through GWA studies will be far greater than the proportion of variance explained would suggest.