BADERC-David Altshuler

David Altshuler, M.D., Ph.D.

Human genetic variation and the genetic basis of type 2 diabetes in humans

For the past decade, my group has aimed to make possible the discovery of novel processes causal in common human diseases through studies of inherited genomic variation. Our approach has been to characterize and catalogue patterns of human genetic variation, to develop methods for genome-wide studies of sequence variants (single nucleotide and copy number variants both common and rare), and to apply these methods to dissect the genetic contribution of type 2 diabetes and other diseases.

Specifically, we contributed to understanding patterns of genetic variation in the human genome, characterizing SNPs and copy number variants, linkage disequilibrium properties, and the underlying influence of recombination rate and population history. We led in the creation of the public genome-wide SNP map, and the SNP Consortium, HapMap and 1000 Genomes Projects. We contributed to development of microarray methods for genome-wide measurement of genetic variation, and to statistical methods for design and analysis of genetic association studies.

We performed association studies that led to the discovery of over three dozen novel genomic loci harboring causal variants influencing type 2 diabetes, serum lipids, myocardial infarction, prostate cancer, systemic lupus erythematosis and rheumatoid arthritis.

In 2007 Science Magazine named studies of genomic variation as Breakthrough of the Year, and highlighted our work. (In 2005, Science including the International HapMap Project in the citation naming studies of human evolution as breakthrough of that year.)

We are now focusing on discovering the genes and mutations responsible at each locus, extending the mapping approach to query all genetic variation (not only common variants), and using this information to gain new insights into disease mechanisms, with the ultimate goal of developing new targets for therapeutic intervention and disease prevention

References:

Diabetes Genetics Initiative of Broad, Lund and Novartis “Genome-Wide Association Analysis Identifies Loci for Type 2 Diabetes and Triglyceride Levels” Science 2007 ;316:1331-6. *DA was PI of the project and corresponding author
Zeggini E, Scott LJ, Saxena R, Voight BF for the DIAGRAM Consortium (2008) “Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes” Nature Genetics 40(5):638-45.
Myocardial Infarction Genetics Consortium (2009). “Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants”. Nature Genetics 41(3):334-41.
Lyssenko V, Nagorny CL, Erdos MR, Wierup N, Jonsson A, Spégel P, Bugliani M, Saxena R, Fex M, Pulizzi N, Isomaa B, Tuomi T, Nilsson P, Kuusisto J, Tuomilehto J, Boehnke M, Altshuler D, Sundler F, Eriksson JG, Jackson AU, Laakso M, Marchetti P, Watanabe RM, Mulder H, Groop L (2009). “Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion”. Nature Genetics 41(1):82-8.






			David Altshuler, M.D., Ph.D. Human genetic variation and the genetic basis of type 2 diabetes in humans For the past decade, my group has aimed to make possible the discovery of novel processes causal in common human diseases through studies of inherited genomic variation. Our approach has been to characterize and catalogue patterns of human genetic variation, to develop methods for genome-wide studies of sequence variants (single nucleotide and copy number variants both common and rare), and to apply these methods to dissect the genetic contribution of type 2 diabetes and other diseases. Specifically, we contributed to understanding patterns of genetic variation in the human genome, characterizing SNPs and copy number variants, linkage disequilibrium properties, and the underlying influence of recombination rate and population history. We led in the creation of the public genome-wide SNP map, and the SNP Consortium, HapMap and 1000 Genomes Projects. We contributed to development of microarray methods for genome-wide measurement of genetic variation, and to statistical methods for design and analysis of genetic association studies. We performed association studies that led to the discovery of over three dozen novel genomic loci harboring causal variants influencing type 2 diabetes, serum lipids, myocardial infarction, prostate cancer, systemic lupus erythematosis and rheumatoid arthritis. In 2007 Science Magazine named studies of genomic variation as Breakthrough of the Year, and highlighted our work. (In 2005, Science including the International HapMap Project in the citation naming studies of human evolution as breakthrough of that year.) We are now focusing on discovering the genes and mutations responsible at each locus, extending the mapping approach to query all genetic variation (not only common variants), and using this information to gain new insights into disease mechanisms, with the ultimate goal of developing new targets for therapeutic intervention and disease prevention References: Diabetes Genetics Initiative of Broad, Lund and Novartis “Genome-Wide Association Analysis Identifies Loci for Type 2 Diabetes and Triglyceride Levels” Science 2007 ;316:1331-6. DA was PI of the project and corresponding author Zeggini E, Scott LJ, Saxena R, Voight BF for the DIAGRAM Consortium (2008) “Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes” Nature Genetics 40(5):638-45. Myocardial Infarction Genetics Consortium (2009). “Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants”. Nature Genetics 41(3):334-41. Lyssenko V, Nagorny CL, Erdos MR, Wierup N, Jonsson A, Spégel P, Bugliani M, Saxena R, Fex M, Pulizzi N, Isomaa B, Tuomi T, Nilsson P, Kuusisto J, Tuomilehto J, Boehnke M, Altshuler D*, Sundler F, Eriksson JG, Jackson AU, Laakso M, Marchetti P, Watanabe RM, Mulder H, Groop L (2009). “Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion”. Nature Genetics 41(1):82-8.