 |
Associate Professor of Human Genetics |
|
| 5912 Buhl 1241 E. Catherine St. SPC 5618 Ann Arbor , MI 48109 -5618 |
||
Research in the Douglas lab is focused on three inter-related areas: statistical genetics, genetic epidemiology, and cancer genetics. The major emphasis of the lab is to identify and characterize the genetic contributions to complex traits and diseases in human populations, with a special interest in the hereditary predisposition to breast cancer and related risk factors. Current projects in the Douglas lab include
(1) Mapping genes for mammographic breast density: The overall goal of this study is to identify and localize the genetic loci and ultimately characterize the genes that explain inter-individual variation in breast density, one of the strongest but perhaps least understood breast cancer risk factors. The two-part hypothesis underlying our study is that (a) there may be increased power to localize and identify breast cancer-related susceptibility genes by examining the genetics of a more proximal but closely related phenotypic endpoint and that (b) there exist genes with strong enough effects on breast density to be detected by linkage analysis. The foundation of our approach is the variance-component method of quantitative trait linkage analysis, whereby information regarding the location of quantitative trait loci is derived from correlations between the quantitative trait in related individuals and genetic markers distributed throughout the genome. Because this approach works best when data can be collected on large, extended families, we are conducting this study in the Old Order Amish of Lancaster County, Pennsylvania, one of oldest and most densely populated Amish settlements in the world.
(2) Examining and characterizing susceptibility genes for prostate cancer: The overall goal of this study is to characterize the genetic basis for the inherited predisposition to prostate cancer. Our hypothesis is that prostate cancer susceptibility loci can be identified and characterized using a family-based association approach. Our approach, which ascertains men with early-onset and/or hereditary prostate cancer and their unaffected brothers, examines the contribution of common variation in known candidate genes and pathways to prostate cancer susceptibility. Because the incidence of prostate cancer varies widely by race and country of origin, it is possible that unrecognized, genetic differences between affected and unaffected men could contribute to spurious results in an association study. The advantage of our family-based association approach, however, is that the unaffected men are ascertained from the same genetic source population as the affected men, thereby eliminating the possibility of confounding due to population substructure.
(3) Identifying genetic variation underlying blood pressure response to changes in dietary salt intake: The overall goal of this study is to identify genes that interact with the environment to influence cardiovascular disease risk. To do so, we are performing 4 short-term interventions known to influence variation in risk factors (e.g., blood pressure) for cardiovascular disease (CVD). Our hypothesis is that the effect of some genes may be restricted to a particular environment (e.g., pre- or post-intervention) while other genes may influence trait variation in response to the intervention. Our primary phenotype of interest is blood pressure response to changes in sodium intake (or salt sensitivity, a significant predictor of all-cause and CVD-related mortality). Our strategy, which takes advantage of recent, technological advances in high-throughput genotyping of single nucleotide polymorphisms (SNPs) across the genome, utilizes linkage and linkage disequilibrium mapping methods to identify regions of the genome linked to or associated with variation in blood pressure response.
(4) Testing and developing methods and strategies to facilitate our gene mapping studies: Our use of statistical-genetic population-based methods to identify and characterize the genetic basis of complex diseases and traits in human populations continues to motivate a number of more methodological projects in the lab. For example, through computer simulation of high-density SNP maps, we are currently evaluating methods, strategies, and software to (a) detect genotyping errors and mutations and (b) conduct linkage analysis in the context of extended pedigrees.
1999-2000 University of Michigan Rackham Predoctoral Fellowship
1995-1998 NIH Predoctoral Traineeship in Genome Science
1993-1994 Tandy Corporation Outstanding Teaching Award
1989-1990 University of Akron College of Education Outstanding Student
1986-1990 University of Akron Honors Scholarship
1986-1990 Carl D. Perkins Teaching Scholarship
2001 University of Michigan, Ph.D. in Biostatistics
1998 University of Michigan, M.S. in Biostatistics
1990 University of Akron, B.A. in Mathematics & Secondary Education
Douglas JA, Gruber SB, Meister KA, Bonner J, Watson P, Krush AJ, Lynch HT. History and molecular genetics of Lynch syndrome in family G A century later. JAMA 2005;294:2195-2202
Douglas JA, Zuhlke KA, Beebe-Dimmer J, Levin AM, Gruber SB, Wood DP, Cooney KA. Identifying Susceptibility Genes for Prostate Cancer A Family-Based Association Study of Polymorphisms in CYP17, CYP19, CYP11A1, and LH. Cancer Epidemiol Biomarkers Prev 2005;14:2035-2039
Rozek LS, Lipkin SM, Fearon ER, Hanash S, Giordano TJ, Greenson JK, Kuick R, Misek DE, Taylor JMG, Douglas JA, Rennert G, Gruber SB. CDX2 polymorphisms, RNA expression, and risk of colorectal cancer. Cancer Research 2005;65:5488-5492
Probst FJ, Hedera P, Sclafani AM, Pomponi MG, Neri G, Tyson J, Douglas JA, Petty EM, Martin DM. Skewed X-inactivation in carriers establishes linkage in an X-linked deafness mental retardation syndrome. J Med Genet 2004;131A:209-212
Silander K, Scott LJ, Valle TT, Mohlke KL, Stringham HM, Wiles KR, Duren WL, Doheny KF, Pugh EW, Chines P, Narisu N, White PP, Fingerlin TE, Jackson AU, Li C, Ghosh S, Magnuson VL, Colby K, Erdos MR, Hill JE, Hollstein P, Humphreys KM, Kasad RA, Lambert J, Lazaridis K, Lin G, Morales-Mena A, Patzkowski K, Pfahl C, Porter R, Rha D, Segal L, Suh YD, Tovar J, Unni A, Welch C, Douglas JA, Epstein MP, Hauser ER, Hagopian W, Buchanan TA, Watanabe RM, Bergman RN, Tuomilehto J, Collins FS, Boehnke M. A large set of Finnish affected sibling pair families with type 2 diabetes suggests susceptibility loci on chromosomes 6, 11, and 14. Diabetes 2004;53:821-829
Beebe-Dimmer JL, Wood DP, Gruber SB, Douglas JA, Bonner JD, Mohai C, Zuhlke KA, Shepard C, Cooney KA. Use of complementary and alternative medicine in men with a family history of prostate cancer a pilot study. Urology 2004;63:282-287
International HapMap Consortium. The international HapMap project. Nature 2003;426:789-796
Douglas JA, Skol AD, Boehnke M. Probability of detecting genotyping errors and mutations as inheritance inconsistencies in nuclear-family data. Am J Hum Genet 2002;70:487-49
Douglas JA, Boehnke M, Gillanders E, Trent JM, Gruber SB. Experimentally-derived haplotypes substantially increase efficiency of linkage disequilibrium studies. Nat Genet 2001;28:361-364
Douglas JA, Erdos MR, Watanabe RM, Braun A, Johnston CL, Oeth P, Mohlke KL, Valle T, Ehnholm C, Buchanan TA, Bergman RN, Collins FS, Boehnke M, Tuomilehto J. The peroxisome proliferator-activated receptor-g2 Pro12Ala variant: association with type 2 diabetes and trait differences. Diabetes 2001;50:886-890
Home