  Identifying drivers of complex traits from the noisy signals of genetic
variation obtained from high throughput genome sequencing technologies is a
central challenge faced by human geneticists today. We hypothesize that the
variants involved in complex diseases are likely to exhibit non-neutral
evolutionary signatures. Uncovering the evolutionary history of all variants is
therefore of intrinsic interest for complex disease research. However, doing so
necessitates the simultaneous elucidation of the targets of natural selection
and population-specific demographic history. Here we characterize the action of
natural selection operating across complex disease categories, and use
population genetic simulations to evaluate the expected patterns of genetic
variation in large samples. We focus on populations that have experienced
historical bottlenecks followed by explosive growth (consistent with most human
populations), and describe the differences between evolutionarily deleterious
mutations and those that are neutral. Genes associated with several complex
disease categories exhibit stronger signatures of purifying selection than
non-disease genes. In addition, loci identified through genome-wide association
studies of complex traits also exhibit signatures consistent with being in
regions recurrently targeted by purifying selection. Through simulations, we
show that population bottlenecks and rapid growth enables deleterious rare
variants to persist at low frequencies just as long as neutral variants, but
low frequency and common variants tend to be much younger than neutral
variants. This has resulted in a large proportion of modern-day rare alleles
that have a deleterious effect on function, and that potentially contribute to
disease susceptibility.
