Join us for the next instalment of the STAGE International Speaker Seminar Series (ISSS) with
Ron Do, PhD
Professor, Genetics and Genomic Sciences
Charles Bronfman Professor, Personalized Medicine
Icahn School of Medicine, Mount Sinai
Free Hybrid (In person/Online) Event | Registration Required
Talk Title:
Advances in Mendelian Randomization: Robust Causal Inference and Identification of Risk Factors for Coronary Artery Disease
Abstract:
Mendelian randomization (MR) is a commonly used approach in human genetics to infer causal risk factors for complex diseases. In this talk, I present research focused on the development and application of MR methods for robust causal inference testing, interpretation, and the identification of causal risk factors for coronary artery disease. First, I demonstrate the detection of widespread horizontal pleiotropy in MR testing between complex traits and diseases. Next, I describe a method that empirically quantifies horizontal pleiotropy in human genetic variation, showing that it is pervasive and primarily driven by extreme polygenicity of complex traits and diseases. Third, I introduce the concept of causal variance to quantify the contribution of a risk factor to disease. Additionally, I present work related to the application of MR in dissecting causal influences for coronary artery disease. This includes the identification of plasma triglycerides as a causal risk factor for coronary artery disease and a phenome-wide MR analysis of plasma triglycerides on 2,600 disease traits. Finally, I highlight a study on using MR as a tool to identify modifiable lifestyle factors that are causal towards coronary artery disease risk.
Speaker Profile:
Dr. Ron Do is the Charles Bronfman Professor in Personalized Medicine and Professor in the Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai. He leads a research program focused on using computational genomic and data science approaches to understand the genetic, biological and clinical basis of human diseases. He pursues this research by developing and applying methods in statistical computing, machine learning, genetic epidemiology, statistical genetics and population genetics to large-scale human genotyping, sequencing, functional and clinical datasets. He has led projects that has used exome sequencing for discovery of novel genetic causes of plasma lipids and myocardial infarction, developed and applied methods to identify causal relationships between risk factors and disease using Mendelian randomization, and analyzed large-scale electronic health record-linked biobank datasets to develop machine learning-based clinical risk scores for human diseases, amongst other activities. Ron has authored over 130 scientific publications, including lead or senior author publications in Nature, New England Journal of Medicine, Journal of American Medical Association, Lancet and Nature Genetics. For his research efforts, he was awarded The Dr. Harold and Golden Lamport Clinical Research Award from the Icahn School of Medicine at Mount Sinai, awarded to junior faculty who show exceptional potential for making significant contributions over an extended period of time. Prior to joining Mount Sinai, Ron was a Canadian Institute of Health Research Banting Postdoctoral Fellow in Human Genetics and Instructor in Medicine in the Center for Human Genetic Research (now Center for Genomic Medicine) at Massachusetts General Hospital and Harvard Medical School. He received his Ph.D. in Human Genetics from McGill University, his M.Sc. in Experimental Medicine and B.Sc. in Cell Biology and Genetics from University of British Columbia.
Sponsors:
CANSSI Ontario STAGE (STAGE) is a training program in genetic epidemiology and statistical genetics housed at the University of Toronto Dalla Lana School of Public Health. It operates with financial and in-kind support from CANSSI Ontario, an extra-departmental unit in the Faculty of Arts & Science at U of T.
STAGE would like to thank our generous seminar sponsors!
For a complete list of sponsors, please see here.
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