|Grant Number:||5R01CA122844-05 Interpret this number|
|Primary Investigator:||Douglas, Julie|
|Organization:||University Of Michigan|
|Project Title:||Mapping Genes for Mammographic Breast Density|
DESCRIPTION (provided by applicant): Increased mammographic breast density is one of the strongest independent predictors of breast cancer risk, yet perhaps the least understood. Family and twin studies provide compelling evidence for a substantial genetic influence on breast density. However, the specific genetic loci that contribute to the wide inter- individual variation in breast density are largely unknown. The overall objective of this proposal is to identify and localize the genetic loci and ultimately to characterize the genes that explain inter-individual variation in breast density using state-of-the-art mammography, new and objective density estimation tools and programs, and sophisticated molecular and statistical genetic methods in the Old Order Amish population of Lancaster County, Pennsylvania. The hypothesis underlying this proposal is that there exist genes with strong enough effects on breast density to be detected by linkage analysis. With relatively similar cultural and environmental experiences, a well-defined, genetically closed population structure, and extensive genealogical records, the Old Order Amish provide an ideal context in which to study the genetic contributions to breast density. The overall design of this proposal is the positional cloning of genes for breast density using related women (particularly sisters) from extended Amish families. The specific aims are to (1) recruit and characterize 1,200 Amish women with regard to breast density and factors known or suspected to modify breast density, (2) determine if the genetic and/or environmental contributions to breast density (and related traits) differ between pre- and post-menopausal women, (3) determine if the phenotypic correlation between breast density and related traits is mediated by the same genetic and/or environmental factors, (4) identify and localize loci for breast density through genome-wide quantitative trait linkage analyses utilizing a high-density map of -6,000 single nucleotide polymorphisms (SNPs), and (5) determine if chromosomal regions linked to variation in breast density are also linked to variation in factors known or suspected to modify breast density. The proposed research will likely result in the identification of one or more loci for breast density over the project period. Lessons learned from this research may provide important insights into the genetic etiology of breast density and its relationship with other breast cancer risk factors and ultimately inform future strategies for breast cancer prevention and control.
Pedmine--a Simulated Annealing Algorithm To Identify Maximally Unrelated Individuals In Population Isolates
Authors: Douglas J.A. , Sandefur C.I. .
Source: Bioinformatics (oxford, England), 2008-04-15 00:00:00.0; 24(8), p. 1106-8.
Mammographic Breast Density--evidence For Genetic Correlations With Established Breast Cancer Risk Factors
Authors: Douglas J.A. , Roy-Gagnon M.H. , Zhou C. , Mitchell B.D. , Shuldiner A.R. , Chan H.P. , Helvie M.A. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2008 Dec; 17(12), p. 3509-16.
Extent And Distribution Of Linkage Disequilibrium In The Old Order Amish
Authors: Van Hout C.V. , Levin A.M. , Rampersaud E. , Shen H. , O'Connell J.R. , Mitchell B.D. , Shuldiner A.R. , Douglas J.A. .
Source: Genetic Epidemiology, 2010 Feb; 34(2), p. 146-50.
Dynamic Multiple Thresholding Breast Boundary Detection Algorithm For Mammograms
Authors: Wu Y.T. , Zhou C. , Chan H.P. , Paramagul C. , Hadjiiski L.M. , Daly C.P. , Douglas J.A. , Zhang Y. , Sahiner B. , Shi J. , et al. .
Source: Medical Physics, 2010 Jan; 37(1), p. 391-401.
Computerized Image Analysis: Texture-field Orientation Method For Pectoral Muscle Identification On Mlo-view Mammograms
Authors: Zhou C. , Wei J. , Chan H.P. , Paramagul C. , Hadjiiski L.M. , Sahiner B. , Douglas J.A. .
Source: Medical Physics, 2010 May; 37(5), p. 2289-99.
A Method To Prioritize Quantitative Traits And Individuals For Sequencing In Family-based Studies
Authors: Shah K.P. , Douglas J.A. .
Source: Plos One, 2013; 8(4), p. e62545.
Genome-wide Association Study Identifies Multiple Loci Associated With Both Mammographic Density And Breast Cancer Risk
Authors: Lindström S. , Thompson D.J. , Paterson A.D. , Li J. , Gierach G.L. , Scott C. , Stone J. , Douglas J.A. , dos-Santos-Silva I. , Fernandez-Navarro P. , et al. .
Source: Nature Communications, 2014; 5, p. 5303.
Rare Variant Apoc3 R19x Is Associated With Cardio-protective Profiles In A Diverse Population-based Survey As Part Of The Epidemiologic Architecture For Genes Linked To Environment Study
Authors: Crawford D.C. , Dumitrescu L. , Goodloe R. , Brown-Gentry K. , Boston J. , McClellan B. , Sutcliffe C. , Wiseman R. , Baker P. , Pericak-Vance M.A. , et al. .
Source: Circulation. Cardiovascular Genetics, 2014 Dec; 7(6), p. 848-53.
Novel Associations Between Common Breast Cancer Susceptibility Variants And Risk-predicting Mammographic Density Measures
Authors: Stone J. , Thompson D.J. , Dos Santos Silva I. , Scott C. , Tamimi R.M. , Lindstrom S. , Kraft P. , Hazra A. , Li J. , Eriksson L. , et al. .
Source: Cancer Research, 2015-06-15 00:00:00.0; 75(12), p. 2457-67.