Abstract
A number of open questions in human evolutionary genetics would become tractable if we were able to directly measure evolutionary fitness. As a step towards this goal, we developed a method to test whether individual genetic variants, or sets of genetic variants, currently influence viability. The approach consists in testing whether the frequency of an allele varies across ages, accounting for variation in ancestry. We applied it to the Genetic Epidemiology Research on Aging (GERA) cohort and to the parents of participants in the UK Biobank. In the UK Biobank, variants that delay puberty timing are enriched in longer-lived parents (P~6×10−8 for fathers and P~1×10−4 for mothers), consistent with epidemiological studies. Similarly, in mothers, variants associated with later age at first birth are associated with a longer lifespan (P~6×10−4) and fewer children (P~3×10−9), pointing to an apparent trade-off between effects on fertility and longevity. Signals are also observed in fathers for variants influencing cholesterol level, heart disease risk, body mass index, and asthma, as well as for variants near CHRNA3 (P~ 4×10−8). In the GERA cohort, in contrast, only one signal is detected, for the APOE ε4 allele (P < 10−15). Results in the two cohorts suggest that even variants with late onset effects are kept at low frequency by purifying selection. In turn, the differences between these two cohorts point to gene-by-environment interactions influencing the genetic architecture of viability. Beyond these findings, our analysis serves as a proof of principle for how upcoming biomedical datasets can be used to learn about selection effects in contemporary humans.