Professor of Biomedical Informatics, Harvard Medical School
Professor of Medicine, Brigham and Women’s Hospital
Dr. Sunyaev
is a computational genomicist and geneticist. Research in his lab encompasses
many aspects of population genetic variation including the origin of mutations,
the effect of allelic variants on molecular function, population and
evolutionary genetics, and genetics of human complex and Mendelian traits. He
developed several computational and statistical methods widely adopted by the
community.
Dr. Sunyaev
obtained a PhD in molecular biophysics from the Moscow Institute of Physics and
Technology and completed his postdoctoral training in bioinformatics at the
European Molecular Biology Laboratory (EMBL). He is an Associate Member at
Broad Institute of MIT and Harvard. He co-leads the NHGRI-funded Genome
Sequencing Program Analysis Center and is actively involved in the Undiagnosed
Diseases Network and in the Brigham Genomic Medicine program. He also
co-organizes the Boston Evolutionary Genomics Group.
Professor of Biomedical Informatics, Harvard Medical School
Professor of Medicine, Brigham and Women’s Hospital
Dr. Sunyaev
is a computational genomicist and geneticist. Research in his lab encompasses
many aspects of population genetic variation including the origin of mutations,
the effect of allelic variants on molecular function, population and
evolutionary genetics, and genetics of human complex and Mendelian traits. He
developed several computational and statistical methods widely adopted by the
community.
Dr. Sunyaev
obtained a PhD in molecular biophysics from the Moscow Institute of Physics and
Technology and completed his postdoctoral training in bioinformatics at the
European Molecular Biology Laboratory (EMBL). He is an Associate Member at
Broad Institute of MIT and Harvard. He co-leads the NHGRI-funded Genome
Sequencing Program Analysis Center and is actively involved in the Undiagnosed
Diseases Network and in the Brigham Genomic Medicine program. He also
co-organizes the Boston Evolutionary Genomics Group.
Journal article
Background: Low-density lipoprotein cholesterol (LDL-C) is a well-established risk factor for cardiovascular disease, and it plays a causal role in the development of atherosclerosis. Genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with LDL-C. Most of these risk loci fall in non-coding regions of the genome, and it is unclear how these non-coding variants affect circulating lipid levels. One hypothesis is that genetically mediated...
Journal article
Gene networks encapsulate biological knowledge, often linked to polygenic diseases. While model system experiments generate many plausible gene networks, validating their role in human phenotypes requires evidence from human genetics. Rare variants provide the most straightforward path for such validation. While single-gene analyses often lack power due to rare variant sparsity, expanding the unit of association to networks offers a powerful alternative, provided it integrates network...