1 February 2010
Although GWAs have identified many SNPs associated with common disease, they have as yet had little success in identifying the causative genetic variants. Those that have been identified have only a weak effect on disease risk, and therefore only explain a small proportion of the heritable, genetic component of susceptibility to that disease. This has led to the common disease-common variant hypothesis, which predicts that common disease-causing genetic variants exist in all human populations, but each individual variant will necessarily only have a small effect on disease susceptibility (i.e. a low associated relative risk).
An alternative hypothesis is the common disease, many rare variants hypothesis, which postulates that disease is caused by multiple strong-effect variants, each of which is only found in a few individuals. Dickson et al. in a paper in PLoS Biology postulate that these rare variants can be indirectly associated with common variants; they call these synthetic associations and demonstrate how further investigation could help explain findings from GWA studies [Dickson et al. (2010) PLoS Biol. 8(1):e1000294]. In simulation experiments, 30% of synthetic associations were caused by the presence of rare causative variants and furthermore, the strength of the association with common variants also increased if the number of rare causative variants increased.
The researchers also demonstrated that causative variants could be located at some distance from the marker SNP and still contribute to the association, demonstrating this using real data from individuals with sickle cell anaemia and hearing loss and controls. The implication of this finding is that sequencing close to a marker SNP may not necessarily identify causative gene(s), leading the authors to suggest that whole-genome sequencing may be a better approach to finding such variants, whilst acknowledging that it is still unclear what proportion of GWAS signals may be due to common versus rare variants.
Comment: Rare genetic variants are important contributors to disease, and can in some cases be identified by whole genome sequencing such as exome sequencing (see previous news) and targeted sequencing of the X-chromosome (see previous news). Their role in common disease such as obesity has also been demonstrated by recent identification of CNVs associated with obesity (see previous news).
However, identifying these rare, causative variants for any disease is not an easy task, due to the enormous amount of sequence variation present in individual genomes. The identification of rare variants that are causal in common diseases can be still more problematic; many may only be present in subsets or clusters of people with a given disease e.g. individual families.