Evolutionary evidence of the effect of rare variants on disease etiology

Abstract

The common disease/common variant hypothesis has been popular for describing the genetic architecture of common human diseases for several years. According to the originally stated hypothesis, one or a few common genetic variants with a large effect size control the risk of common diseases. A growing body of evidence, however, suggests that rare single-nucleotide polymorphisms (SNPs), i.e. those with a minor allele frequency of less than 5%, are also an important component of the genetic architecture of common human diseases. In this study, we analyzed the relevance of rare SNPs to the risk of common diseases from an evolutionary perspective and found that rare SNPs are more likely than common SNPs to be functional and tend to have a stronger effect size than do common SNPs. This observation, and the fact that most of the SNPs in the human genome are rare, suggests that rare SNPs are a crucial element of the genetic architecture of common human diseases. We propose that the next generation of genomic studies should focus on analyzing rare SNPs. Further, targeting patients with a family history of the disease, an extreme phenotype, or early disease onset may facilitate the detection of risk-associated rare SNPs.

Fig. 1

Distribution of single-nucleotide polymorphisms (SNPs) from the Encyclopedia of DNA Elements (ENCODE) (orange bars) and of all SNPs reported in the International HapMap Database (blue bars) by minor allele frequency (MAF).

Fig. 2

Proportion of nonsynonymous single-nucleotide polymorphisms (nsSNPs) predicted to be protein damaging, by minor allele frequency (MAF). Each point represents the proportion of functional nsSNPs in a given MAF category. Error bars indicate standard error. (A) The proportion predicted by using the PolyPhen method. The black line is the unadjusted logarithmic regression curve, and the orange line is the curve adjusted for PolyPhen's sensitivity and specificity. (B) The proportion predicted by using the sorting intolerant from tolerant (SIFT) method.

Fig. 3

The proportions of functional single-nucleotide polymorphisms (SNPs) among radical (blue line) and conservative (green line) amino acid substitutions are shown. Predictive curves (gray) and equations are shown separately for radical and conservative substitutions. Error bars indicate standard error.

Fig. 4

The relationship between the change in accessible surface propensity (dprop) and minor allele frequency (MAF). Each dot represents a SNP.

Fig. 5

The association between odds ratio (OR) and minor allele frequency (MAF). The orange line represents the regression curve. The variation in MAF explains up to 26% of the variation in the OR. On the figure, the maximum OR is limited to 4: several single-nucleotide polymorphisms with ORs higher than 4 are not shown, although they were included in the computation of correlation coefficients.