Leveraging Biobanks and PheWAS to Uncover the Health Consequences of Recent Human Evolution

Abstract

The genomics era has seen a staggering increase in the number of whole genome sequences. This has bolstered studies of human populations, and revealed regions of the genome bearing signatures of selection and other demographic events. However, tying these regions to phenotypic effects in humans is difficult. I addressed this challenge by leveraging densely phenotyped biobank populations from the eMERGE network, a collection of 10 clinical biobanks across the US that connect electronic health records (EHRs) to genotyping data. The eMERGE data enabled me to interrogate the function of human genetic variation on a broad array of phenotypes using the phenome-wide association study (PheWAS) framework. Each chapter describes a project in which I tested hypotheses about the impact of evolutionarily important variants on human health. In the first, I examine the clinical impact of interbreeding between humans and Neanderthals; in the next, I evaluate variants whose allele frequencies have increased drastically since human divergence from chimpanzee; and finally I consider variants affected by GC-biased gene conversion, a recombination-associated mutational process that favors the fixation of G and C alleles. In conclusion, I used large clinical biobanks to uncover novel genotype-phenotype associations that reveal the effects of recent demographic events and evolutionary processes that have shaped the human genome.