We develop computational tools and statistical approaches to characterize patterns of genetic variation in human populations, and we apply these methods to define the genetic basis of common diseases and complex traits.
We have strong and active links with clinicians, biostatisticians and population geneticists in and around Boston, and elsewhere.
method development - meta-analysis and imputation
Genome-wide association studies have led to the identification of scores of common gene variants as having a role in disease, but the nature and extent of the contribution of rare variation to polygenic disease is still largely unknown. Sequencing methods are rapidly improving and falling in cost, allowing for comprehensive and complete characterization of genetic variation in large numbers of individuals, but new computational methods are needed to analyze these data.
Specifically, one of the questions we are currently pursuing is if and how reference data sets like HapMap (or 1000 Genomes, when finished) can be used to extract maximal information about common and rare variation in individuals (for example, through imputation-based methods). In addition, we are developing meta-analytic approaches to combine data from multiple genomic studies in multiple population samples.
Human immunodeficiency virus (HIV) infection typically leads to persistent viremia and progressive clinical disease (AIDS), and has resulted in more than 20 million deaths worldwide.
We are leading genetic projects in the International HIV Controllers Study, founded by Bruce Walker at the Partners AIDS Research Center at MGH, and currently funded by the Bill and Melinda Gates Foundation. HIV controllers are a remarkable subset of persons infected with HIV who are able to achieve long-term control of viremia and avoid immunodeficiency in the absence of antiretroviral therapy. Our aim is to better understand the host genetic basis of durable virus control in these individuals to identify potential targets for vaccine design.
We are currently performing a genome-wide association study in 1000 HIV controllers and 3000 chronic progressors at the Broad Institute.
We work with David Hafler and Phil De Jager (both neurologists at the BWH) on genetic studies to identify genes that confer risk to multiple sclerosis, as part of the International Multiple Sclerosis Genetics Consortium. We have recently performed a whole-genome scan, demonstrating a role of the IL2RA and IL7RA genes in MS. We are currently working on a meta-analysis of multiple genome scans to increase the power to detect novel variants of more modest effect.
We work with Christopher Newton-Cheh, a cardiovascular epidemiologist and complex trait geneticist at Massachusetts General Hospital, on electrocardiographic QT interval, a known risk factor for sudden cardiac death. We are currently involved in a large-scale meta-analysis across the Framingham Heart Study, The Rotterdam Study, and the Cardiovascular Health Study (as part of the CHARGE Consortium).
We are collaborating with the group of Jonathan Rosand, neurologist in the Center for Human Genetic Research at Massachusetts General Hospital. We are participating in the International Stroke Genetics Consortium to perform a large-scale genome-wide association study in multiple patient collections across the world.