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
Most human variants identified by genome-wide association studies are believed to affect traits by altering gene expression. This belief is supported by considerable circumstantial evidence, but statistical methods are unable to link most trait-associated variants to gene expression-a problem we refer to as "missing regulation." Many explanations have been proposed, including the possibility that natural selection on gene expression limits power. Here, we take a novel approach to the question of...
Journal article
CONCLUSIONS: Biallelic LAMP3 variants are associated with an interstitial lung disease phenotype with variable expressivity. Evaluation for LAMP3 variants should be considered in individuals with unexplained interstitial lung disease.