Michael Boehnke, Ph.D.

Richard G. Cornell Distinguished University Professor of Biostatistics

Director, Center for Statistical Genetics

Director, Genome Science Training Program

M4108 SPH II
1420 Washington Heights
Ann Arbor, Michigan 48109-2029

Office: (734) 936-1001; Fax: (734) 615-8322

E-mail: boehnke@umich.edu

Website(s): Center for Statistical Genetics; Genome Science Training Program; FUSION Study of Type 2 Diabetes

Curriculum Vitae (PDF, 97,881 KB)

Professional Summary

Dr. Boehnke's research focuses on problems of study design and statistical analysis of human genetic data with a particular emphasis on development and application of statistical methods for human gene mapping. His current statistical methods research focuses on genome-wide association studies of diseases and disease-related traits.  He is principal investigator of the Finland-United States Investigation of NIDDM Genetics (FUSION) Study, which seeks to identify genetic variants that predispose to type 2 diabetes.  He is involved in genome-wide association consortia which seek to identify genetic variants that infleunce anthropometric traits, glucose and insulin levels, lipids levels, and blood pressure.  He also leads a genome-wide association study of bipolar disorder and is involved in studies of glaucoma.

Courses Taught

BIOSTAT503: Introduction to Biostatistics    Syllabus (PDF)

Education

Ph.D., Biomathematics, UCLA, 1983
B.A., Mathematics, University of Oregon, 1977

Research Interest & Projects

Design and Analysis of Human Gene Mapping Studies
Identifying Genes for Type 2 Diabetes: FUSION
Pritzker Neuropsychiatric Disorders Research Consortium
Targeted Genetics Analysis of T2D and Quantitative Traits
Integrated Parametric and Non-Parametric Mapping for Genome-Wide Association Data.
Molecular Genetics of Primary Open-Angle Glaucoma
Molecular Epidemiology of Colorectal Cancer

Selected Publications

Li M. , Boehnke M. and Abecassis GR. (2005). Joint modeling of linkage and association: identifying SNPs responsible for a linkage signal. American Journal of Human Genetics , 76, 934-949.

Skol A. D., Scott L. J., Abecasis G.R., Boehnke M. (2006). Joint analysis is more efficient for whole genome association studies. Nature Genetics, 38, 209-213.

Willer C. J., Scott L. J., Bonnycastle L. L., Jackson A. U., Chines P., Pruim R., Bark C. W., Tsai Y. Y., Pugh E. W., Doheny K. F., Kinnunen L., Mohlke K. L., Valle T. T., Bergman R. N., Tuomilehto J., Collins F. S., Boehnke M. (2006). Tag SNP selection for Finnish individuals based on the CEPH Utah HapMap database. Genetic Epidemiology, 30, 180-190.

Li, M., Boehnke, M., and Abecasis, G.R. (2006). Efficient study designs for test of genetic association using sibship data and unrelated cases and controls. American Journal of Human Genetics

Scott L.J., Bonnycastle L.L., Willer C.J., Sprau A.G., Jackson A.U., Narisu N., Duren W.L., Chines P.S., Stringham H.M., Erdos M.R., Valle T.T., Tuomilehto J., Bergman R.N., Mohlke K.L., Collins F.C., and Boehnke M. (2006). Association of Transcription Factor 7-Like 2 (TCF7L2) variants with type 2 diabetes in a Finnish sample Diabetes , 55, 2649-2653.

Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, Erdos MR, Stringham HM, Chines PS, Jackson AU, Prokunina-Olsson L, Ding CJ, Swift AJ, Narisu N, Hu T, Pruim R, Xiao R, Li X-Y, Conneely KN, Riebow NL, Sprau AG, Tong M, White PP, Hetrick KN, Barnhart MW, Bark CW, Goldstein JL, Watkins L, Xiang F, Saramies J, Buchanan TA, Watanabe RM, Valle TT, Kinnunen L, Abecasis GR, Pugh EW, Doheny KF, Bergman RN, Tuomilehto J, Collins FS, and Boehnke M (2007). A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants Science, 316, 1341-1345.

Skol A.D., Scott L.J., Abecasis G.R., Boehnke M. (2007). Optimal Designs for Two-Stage Genome-Wide Association Studies Genetic Epidemiology, 31, 776-788.

Conneely KN and Boehnke M (2007). So many correlated tests, so little time! Rapid adjustment of p-values for multiple correlated tests American Journal of Human Genetics, 1158-1168.

Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, Heath SC, Timpson NJ, Najjar SS, Stringham HM, Strait J, Duren WL, Maschio A, Busonero F, Mulas A, Albai G, Swift AJ, Morken MA, Narisu N, Bennett D, Parish S, Shen H, Galan P, Meneton P, Hercberg S, Zelenika D, Chen W-M, Li Y, Sundvall J, Watanabe RM, Nagaraja R, Ebrahim S, Lawlor DA, Ben-Shlomo Y, Davey-Smith G, Shuldiner AR, Collins R, Bergman RN, Uda M, Tuomilehto J, Cao A, Collins FS, Lakatta E, Lathrop GM, Boehnke M, Schlessinger D, Mohlke KL, and Abecasis GR (2008). Genome-wide association scans identify novel loci that influence lipid levels and risk of coronary artery disease Nature Genetics, 40, 161-169.

Zeggini E., Scott L.J., Saxena R., Voight B.F., Marchini J.L., Hu T., de Bakker P.I., Abecasis G.R., Laakso M., Stefansson K., Pedersen O., Wareham N.J., Barroso I., Hattersley A.T., Collins F.S., Groop L., McCarthy M.I., Boehnke M..,Altshuler D. (2008). Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature Genetics , 40, 638-645.

Professional Affiliations

American Society for Human Genetics
International Genetic Epidemiology Society