Dr. Hae Kyung Im was born in Pusan, South Korea, and immigrated to Argentina where she grew up; she received her BS and MS equivalent degree in Physics surrounded by the beautiful mountains of the Patagonian Andes. After trying out manufacturing and information security consulting, she came to the University of Chicago where she received her MS in Financial Mathematics and her PhD in Statistics. After a short incursion in Wall Street she came back to academic research where she discovered her love for genomic data science. She was appointed Assistant Professor in the Section of Genetic Medicine in July 2016. She is member of two large international consortia: Genotype Tissue Expression and Accelerating Medicines Partnership Type 2 Diabetes. Dr Im runs a genomic data science lab that develops statistical methods to sift through massive amounts of genomic and other high dimensional data with the ultimate goal of making discoveries that can be translated to improve human health. One focus of the lab is to understand the mechanisms underlying the genetic control of human diseases and related traits.
Over the last decade and half, the field of genomics and complex trait genetics has experienced spectacular progress. We have discovered thousands of genomic loci that are robustly linked to complex diseases including type 2 diabetes, cardiovascular diseases, and most cancer types. However, most of these associated gene loci are located outside of the protein coding regions so that the underlying mechanisms are not well understood. Motivated by the growing consensus that these affect disease risk through the regulation of gene expression levels (how much of the gene is transcribed into mRNAs), Dr Im has proposed a suite of methods that use genetically predicted expression levels as probes to find likely causal genes. Unlike traditional genome wide association studies where the results are undecipherable genetic marker names, her method points to genes so that follow up studies can be more easily designed.
Extensions of Dr. Im’s method called PrediXcan is currently an active area of method development.
Furthermore, Dr Im’s Lab has applied her methods to integrate the massive amounts of genetic and phenotypic data currently available in public and restricted repositories. This led to the creation of a growing catalog of the phenomewide (across all human phenotypes) consequences of gene expression variation. The results are shared openly (http://gene2pheno.org) with visitors from over 400 cities around the world.