Associate Professor of Computer Science
Associate Member, Broad Institute
Head, MIT Computational Biology Group (CSAIL)
MIT Department of Electrical Engineering and Computer Science
Perhaps the greatest surprise of human genetic studies is that 90% of disease regions do not affect proteins directly, but instead the circuits that control our genes. This has increased the urgency of mapping the regulatory genome, as a key component for understanding human disease. To address this challenge, we generated maps of genomic control elements across 127 primary human tissues and cell types, and tissue-specific regulatory networks linking these elements to their target genes and their regulators, and we used these maps and circuits to understand how human genetic variation contributes to disease and cancer. The results provide the first unbiased view of disease genetics, sometimes re-shaping our understanding of common disorders. For example, we find that genetic variants contributing to Alzheimer?s disease act primarily through immune processes, rather than neuronal processes, reshaping our therapeutic approaches. We also find that the strongest genetic association with obesity acts via a master switch controlling energy storage vs. energy dissipation in human fat cells, rather than through the control of appetite in the brain. We showed that we can manipulate these circuits by genome editing or gene targeting in human cells and in mice, opening up tissue-autonomous therapeutic avenues against obesity. Lastly, we use our maps and circuits to discover new disease genes in cardiovascular disorders, type 1 diabetes, and prostate cancer, illustrating the power and broad applicability of regulatory annotations and circuits for understanding human disease.