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Genetic Epidemiology

The etiology of most aging-related diseases is multifactorial, with genetic factors having a substantial effect on a range of diseases, including coronary heart disease, diabetes, obesity, stroke, hypertension, osteoporosis, and cancer. In recognition of the importance of genetics to the etiology of common aging-related diseases, many epidemiology studies have expanded to incorporate consideration of genetic risk factors. Some population studies are now conducted on family-based samples to allow explicit estimation of familial influences on disease risk. These may include genetic association and linkage studies to identify specific genes influencing disease risk, assessment of gene-by-gene and gene-by-environment interaction effects, and assessment of genetic influences that influence multiple disease endpoints (e.g., genetic effects that jointly influence cardiovascular disease and diabetes, cardiovascular disease and osteoporosis, dyslipidemia and longevity, etc.).

Research training in genetic epidemiology focuses on learning the analytic and statistical methods used in genetic epidemiology, including familial aggregation and heritability analysis, linkage analysis, genetic association studies (including genome-wide association studies), and quantitative genetic analyses such as assessment of genetic correlations to assess evidence of pleiotropy.

Representative Publications

A common variant in fibroblast growth factor binding protein 1 (FGFBP1) is associated with bone mineral density and influences gene expression in vitro. Hoppman N, McLenithan JC, McBride DJ, Shen H, Bruder J, Bauer RL, Shaffer JR, Liu J, Streeten EA, Shuldiner AR, Kammerer CM, Mitchell BD. Bone. 2010 May 5. [Epub ahead of print]

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Dupuis J et al. Nat Genet. 2010 Feb;42(2):105-16. Epub 2010 Jan 17. Erratum in: Nat Genet.2010 May;42(5):464. PMID: 20081858

Genome-wide association scan identifies variants near Matrix Metalloproteinase (MMP) genes on chromosome 11q21-22 strongly associated with serum MMP-1 levels. Cheng YC, Kao WH, Mitchell BD, O'Connell JR, Shen H, McArdle PF, Gibson Q, Ryan KA, Shuldiner AR, Pollin TI. Circ Cardiovasc Genet. 2009 Aug;2(4):329-37. Epub 2009 May 14. PMID: 20031604

COL4A1 is associated with arterial stiffness by genome-wide association scan. Tarasov KV, Sanna S, Scuteri A, Strait JB, Orrù M, Parsa A, Lin PI, Maschio A, Lai S, Piras MG, Masala M, Tanaka T, Post W, O'Connell JR, Schlessinger D, Cao A, Nagaraja R, Mitchell BD, Abecasis GR, Shuldiner AR, Uda M, Lakatta EG, Najjar SS. Circ Cardiovasc Genet. 2009 Apr;2(2):151-8. Epub 2009 Feb 18. PMID: 20031579

Sequence variation in IGF1R is associated with differences in insulin levels in nondiabetic Old Order Amish. Naj AC, Kao WH, O'Connell JR, Mitchell BD, Silver KD. Diabetes Metab Res Rev. 2009 Nov;25(8):773-9. PMID: 19877134

Variation in the gene TAS2R38 is associated with the eating behavior disinhibition in Old Order Amish women. Dotson CD, Shaw HL, Mitchell BD, Munger SD, Steinle NI. Appetite. 2010 Feb;54(1):93-9. Epub 2009 Sep 25. PMID: 19782709

Serum 25-hydroxyvitamin d levels are not associated with subclinical vascular disease or C-reactive protein in the old order amish. Michos ED, Streeten EA, Ryan KA, Rampersaud E, Peyser PA, Bielak LF, Shuldiner AR, Mitchell BD, Post W. Calcif Tissue Int. 2009 Mar;84(3):195-202. Epub 2009 Jan 16. PMID: 19148561

Association of a common nonsynonymous variant in GLUT9 with serum uric acid levels in old order amish. McArdle PF, Parsa A, Chang YP, Weir MR, O'Connell JR, Mitchell BD, Shuldiner AR. Arthritis Rheum. 2008 Sep;58(9):2874-81. PMID: 18759275