Evolution and Prediction of Genetic Disease Risks in Ancient and Modern Humans

Joseph Lachance, Ph.D.
School of Biological Sciences
Georgia Institute of Technology

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ABSTRACT
Human genomes have been shaped by natural selection, population bottlenecks, and archaic admixture. These evolutionary processes contribute to hereditary differences in disease risk across populations. Here, I explore how disease risk has changed over time and address some of the challenges of applying precision medicine approaches to diverse global populations. My lab’s research fits into four broad themes: anthropological genetics, analysis of ancient DNA, population genetics of prostate cancer in Africa, and improving the transferability of polygenic risk scores. By combining genetic data with mathematical models and computer simulations, we have been able to infer the complex demographic history of diverse human populations (including evidence of sex-biased admixture and interbreeding with unknown “ghost” populations). My lab has also applied precision medicine approaches to ancient human genomes and used time series data to infer the strength of natural selection acting on disease-associated alleles. Differences in risk allele frequencies across populations can contribute to health disparities, including elevated rates of aggressive cancer in men of African descent. Research in my lab has focused on the evolutionary causes of this health disparity and the development of a novel genotyping array that is optimized for detecting genetic associations with prostate cancer in sub-Saharan Africa. Finally, genetic predictions do not always generalize well across populations. To address this challenge, we leveraged evolutionary information to improve the transferability of polygenic risk scores.