MAY 12, 2016 03:00 PM PDT

Using big data to interpret genomes for diagnostics, therapeutics, and precision medicine

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  • Assistant Professor, Director of Clinical Genome Informatics, Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mou
      r. Chen is Director of Clinical Genome Informatics ( at Icahn Institute of Genetics and Multiscale Biology. His research focuses on developing databases, genome repositories, and clinical applications to interpret personal genomes for clinical diagnosis, precision medicine, predictive disease risk, and novel therapeutics.

      Prior to Mount Sinai, he led the collaborative efforts at Stanford University to drive personalized medicine and clinical diagnosis on Mendelian and complex diseases using genome and exome sequencing. Dr. Chen also helped launch a startup company Personalis, which won the VA's contract for the Million Veteran Genome project.

      Dr. Chen has a broad interest in translational bioinformatics and genome interpretation, and has published over 80 papers in Lancet, Cell, Nature Biotechnology, Nature Methods, Science Translational Medicine, PNAS, AJHG, JCI, PLoS Genetics, PLoS Computational Biology, Genome Research, Genome Biology, Genome Medicine, and AJT. He holds numerous patents for software and databases on personalized medicine, diagnosis, and structure modeling.


    Millions of individuals have been sequenced or genotyped and linked with medical records, providing an exciting opportunity for therapeutic target discovery. My lab has been using a resilience approach to learn from success instead of failure, and analyzed hundreds of thousands of genomes with electronic medical records to drive target discovery for childhood Mendelian diseases, Alzheimer’s disease, and cardiovascular traits.

    I will describe how we analyzed 589,305 genomes and identified 13 genetic super heroes who carry fully penetrant childhood Mendelian diseases but are healthy in our recent resilience project, and how we decoded individuals who carry APOE e4/e4 risk variants but are resilient for Alzheimer’s disease. I will further describe how we analyzed individuals who have a loss of gene but carry favorable cardiovascular traits, identified potential therapeutic targets to lower fasting glucose levels, and validated the effects in mice.

    Learning objectives:

    • How to interpret genetic variants using 150,000 genomes from diseased and healthy cohorts, and variants with validated molecular functional impact from 30 million literature.
    • How to use resilient approach to interpret thousands of genomes with medical records for therapeutic target discovery.

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