Grant Number:	1R01CA094069-01 Interpret this number
Primary Investigator:	Whittemore, Alice
Organization:	Stanford University
Project Title:	Statistical Methods for Genetic Epidemiology
Fiscal Year:	2002

DESCRIPTION (provided by applicant): Linkage analysis and classical association analysis of case-control data have identified many disease susceptibility genes, and these discoveries will lead to important public health benefits. However, recent evidence suggests that there are substantial barriers to using these methods for further gene discovery. There also is considerable uncertainty at present about optimal designs for characterizing the effects of disease susceptibility genes. The goals of this research are to develop new and improved ways to identify and characterize such genes in complex situations, and to classify individuals with respect to their disease risk. To accomplish these goals, the investigators will build on more than ten years of previous work. Specifically, in 1988 the National Cancer Institute (NCI) awarded an Outstanding Investigator Grant (OIG) to the Principal Investigator for the development and application of new and improved statistical methods for use in epidemiological research. In 1995 this grant was renewed until NCI terminated the OIG Program in 2001. The present application requests funding to continue this statistical research. Its objectives are to develop better ways to design and analyze studies of genetic predisposition and lifestyle characteristics as contributors to familial aggregation of site-specific cancers, particularly cancers of the ovary, breast and prostate. The specific aims are twofold. One is to develop and evaluate improved methods in four problem areas: a) estimating penetrance of mutations of identified genes and modification of such penetrance by nongenetic factors; b) assessing genetic association in family data; c) identifying genes in the presence of genetic heterogeneity; and d) estimating individual indices of genetic admixture. A second specific aim is to validate these methods by application to data from epidemiological studies. These include existing data from the Cooperative Family Registry for Breast Cancer Studies (CFRBCS), new data from the Familial Registry for Ovarian Cancer (FROC), and existing data from three studies of prostate cancer. A major thrust of the work will be the development of user-friendly software to allow epidemiologists to apply the methods to their data.




Data-adaptive multi-locus association testing in subjects with arbitrary genealogical relationships.
Authors: Gong G. , Wang W. , Hsieh C.L. , Van Den Berg D.J. , Haiman C. , Oakley-Girvan I. , Whittemore A.S. .
Source: Statistical Applications In Genetics And Molecular Biology, 2019-04-08 00:00:00.0; 18(3), .
EPub date: 2019-04-08 00:00:00.0.
PMID: 30956231
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A Prediction Tool to Facilitate Risk-Stratified Screening for Squamous Cell Skin Cancer.
Authors: Wang W. , Jorgenson E. , Ioannidis N.M. , Asgari M.M. , Whittemore A.S. .
Source: The Journal Of Investigative Dermatology, 2018 12; 138(12), p. 2589-2594.
EPub date: 2018-07-02 00:00:00.0.
PMID: 30472995
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Germline variation and breast cancer incidence: A gene-based association study and whole-genome prediction of early onset breast cancer.
Authors: Scannell Bryan M. , Argos M. , Andrulis I.L. , Hopper J.L. , Chang-Claude J. , Malone K.E. , John E.M. , Gammon M.D. , Daly M.B. , Terry M.B. , et al. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2018-06-13 00:00:00.0; , .
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FIRE: functional inference of genetic variants that regulate gene expression.
Authors: Ioannidis N.M. , Davis J.R. , DeGorter M.K. , Larson N.B. , McDonnell S.K. , French A.J. , Battle A.J. , Hastie T.J. , Thibodeau S.N. , Montgomery S.B. , et al. .
Source: Bioinformatics (oxford, England), 2017-12-15 00:00:00.0; 33(24), p. 3895-3901.
PMID: 28961785
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Limited influence of germline genetic variation on all-cause mortality in women with early onset breast cancer: evidence from gene-based tests, single-marker regression, and whole-genome prediction.
Authors: Scannell Bryan M. , Argos M. , Andrulis I.L. , Hopper J.L. , Chang-Claude J. , Malone K. , John E.M. , Gammon M.D. , Daly M. , Terry M.B. , et al. .
Source: Breast Cancer Research And Treatment, 2017-05-13 00:00:00.0; , .
EPub date: 2017-05-13 00:00:00.0.
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Predicting Prostate Cancer Recurrence After Radical Prostatectomy.
Authors: Jeffers A. , Sochat V. , Kattan M.W. , Yu C. , Melcon E. , Yamoah K. , Rebbeck T.R. , Whittemore A.S. .
Source: The Prostate, 2017 02; 77(3), p. 291-298.
EPub date: 2016-10-24 00:00:00.0.
PMID: 27775165
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Evaluating disease prediction models using a cohort whose covariate distribution differs from that of the target population.
Authors: Powers S. , McGuire V. , Bernstein L. , Canchola A.J. , Whittemore A.S. .
Source: Statistical Methods In Medical Research, 2017-01-01 00:00:00.0; , p. 962280217723945.
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PMID: 28812439
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Risk Prediction For Epithelial Ovarian Cancer In 11 United States-based Case-control Studies: Incorporation Of Epidemiologic Risk Factors And 17 Confirmed Genetic Loci
Authors: Clyde M.A. , Palmieri Weber R. , Iversen E.S. , Poole E.M. , Doherty J.A. , Goodman M.T. , Ness R.B. , Risch H.A. , Rossing M.A. , Terry K.L. , et al. .
Source: American Journal Of Epidemiology, 2016-10-15 00:00:00.0; 184(8), p. 579-589.
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REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants.
Authors: Ioannidis N.M. , Rothstein J.H. , Pejaver V. , Middha S. , McDonnell S.K. , Baheti S. , Musolf A. , Li Q. , Holzinger E. , Karyadi D. , et al. .
Source: American Journal Of Human Genetics, 2016-10-06 00:00:00.0; 99(4), p. 877-885.
EPub date: 2016-10-06 00:00:00.0.
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Parity and Oral Contraceptive Use in Relation to Ovarian Cancer Risk in Older Women.
Authors: McGuire V. , Hartge P. , Liao L.M. , Sinha R. , Bernstein L. , Canchola A.J. , Anderson G.L. , Stefanick M.L. , Whittemore A.S. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2016 Jul; 25(7), p. 1059-63.
PMID: 27197274
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Identification of Susceptibility Loci for Cutaneous Squamous Cell Carcinoma.
Authors: Asgari M.M. , Wang W. , Ioannidis N.M. , Itnyre J. , Hoffmann T. , Jorgenson E. , Whittemore A.S. .
Source: The Journal Of Investigative Dermatology, 2016 May; 136(5), p. 930-7.
PMID: 26829030
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Practical problems with clinical guidelines for breast cancer prevention based on remaining lifetime risk.
Authors: Quante A.S. , Whittemore A.S. , Shriver T. , Hopper J.L. , Strauch K. , Terry M.B. .
Source: Journal Of The National Cancer Institute, 2015 Jul; 107(7), .
PMID: 25956172
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Assessing Absolute Changes In Breast Cancer Risk Due To Modifiable Risk Factors
Authors: Quante A.S. , Herz J. , Whittemore A.S. , Fischer C. , Strauch K. , Terry M.B. .
Source: Breast Cancer Research And Treatment, 2015 Jul; 152(1), p. 193-7.
PMID: 26012643
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The role of genome sequencing in personalized breast cancer prevention.
Authors: Sieh W. , Rothstein J.H. , McGuire V. , Whittemore A.S. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2014 Nov; 23(11), p. 2322-7.
PMID: 25342391
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Assessing the goodness of fit of personal risk models.
Authors: Gong G. , Quante A.S. , Terry M.B. , Whittemore A.S. .
Source: Statistics In Medicine, 2014-08-15 00:00:00.0; 33(18), p. 3179-90.
EPub date: 2014-08-15 00:00:00.0.
PMID: 24753038
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Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment.
Authors: Kurian A.W. , Hare E.E. , Mills M.A. , Kingham K.E. , McPherson L. , Whittemore A.S. , McGuire V. , Ladabaum U. , Kobayashi Y. , Lincoln S.E. , et al. .
Source: Journal Of Clinical Oncology : Official Journal Of The American Society Of Clinical Oncology, 2014-07-01 00:00:00.0; 32(19), p. 2001-9.
EPub date: 2014-04-14 00:00:00.0.
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A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age.
Authors: Ahsan H. , Halpern J. , Kibriya M.G. , Pierce B.L. , Tong L. , Gamazon E. , McGuire V. , Felberg A. , Shi J. , Jasmine F. , et al. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2014 Apr; 23(4), p. 658-69.
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Two-stage Sampling Designs For External Validation Of Personal Risk Models
Authors: Whittemore A.S. , Halpern J. .
Source: Statistical Methods In Medical Research, 2013-04-16 00:00:00.0; , .
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Breast cancer risk assessment across the risk continuum: genetic and nongenetic risk factors contributing to differential model performance.
Authors: Quante A.S. , Whittemore A.S. , Shriver T. , Strauch K. , Terry M.B. .
Source: Breast Cancer Research : Bcr, 2012-11-05 00:00:00.0; 14(6), p. R144.
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Breast cancer risk for noncarriers of family-specific BRCA1 and BRCA2 mutations: findings from the Breast Cancer Family Registry.
Authors: Kurian A.W. , Gong G.D. , John E.M. , Johnston D.A. , Felberg A. , West D.W. , Miron A. , Andrulis I.L. , Hopper J.L. , Knight J.A. , et al. .
Source: Journal Of Clinical Oncology : Official Journal Of The American Society Of Clinical Oncology, 2011-12-01 00:00:00.0; 29(34), p. 4505-9.
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Optimal methods for meta-analysis of genome-wide association studies.
Authors: Zhou B. , Shi J. , Whittemore A.S. .
Source: Genetic Epidemiology, 2011 Nov; 35(7), p. 581-91.
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Evaluating health risk models.
Authors: Whittemore A.S. .
Source: Statistics In Medicine, 2010-10-15 00:00:00.0; 29(23), p. 2438-52.
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Increased cancer risks for relatives of very early-onset breast cancer cases with and without BRCA1 and BRCA2 mutations.
Authors: Dite G.S. , Whittemore A.S. , Knight J.A. , John E.M. , Milne R.L. , Andrulis I.L. , Southey M.C. , McCredie M.R. , Giles G.G. , Miron A. , et al. .
Source: British Journal Of Cancer, 2010-09-28 00:00:00.0; 103(7), p. 1103-8.
EPub date: 2010-09-28 00:00:00.0.
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Estimating gene penetrance from family data.
Authors: Gong G. , Hannon N. , Whittemore A.S. .
Source: Genetic Epidemiology, 2010 May; 34(4), p. 373-81.
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Second malignant neoplasms in survivors of pediatric Hodgkin's lymphoma treated with low-dose radiation and chemotherapy.
Authors: O'Brien M.M. , Donaldson S.S. , Balise R.R. , Whittemore A.S. , Link M.P. .
Source: Journal Of Clinical Oncology : Official Journal Of The American Society Of Clinical Oncology, 2010-03-01 00:00:00.0; 28(7), p. 1232-9.
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Performance of prediction models for BRCA mutation carriage in three racial/ethnic groups: findings from the Northern California Breast Cancer Family Registry.
Authors: Kurian A.W. , Gong G.D. , John E.M. , Miron A. , Felberg A. , Phipps A.I. , West D.W. , Whittemore A.S. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2009 Apr; 18(4), p. 1084-91.
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Significance levels for studies with correlated test statistics.
Authors: Shi J. , Levinson D.F. , Whittemore A.S. .
Source: Biostatistics (oxford, England), 2008 Jul; 9(3), p. 458-66.
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Prevalence of pathogenic BRCA1 mutation carriers in 5 US racial/ethnic groups.
Authors: John E.M. , Miron A. , Gong G. , Phipps A.I. , Felberg A. , Li F.P. , West D.W. , Whittemore A.S. .
Source: Jama, 2007-12-26 00:00:00.0; 298(24), p. 2869-76.
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Comparison of admixture and association mapping in admixed families.
Authors: Clarke G. , Whittemore A.S. .
Source: Genetic Epidemiology, 2007 Nov; 31(7), p. 763-75.
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Assessing environmental modifiers of disease risk associated with rare mutations.
Authors: Whittemore A.S. .
Source: Human Heredity, 2007; 63(2), p. 134-43.
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Sex steroid hormones in young manhood and the risk of subsequent prostate cancer: a longitudinal study in African-Americans and Caucasians (United States).
Authors: Tsai C.J. , Cohn B.A. , Cirillo P.M. , Feldman D. , Stanczyk F.Z. , Whittemore A.S. .
Source: Cancer Causes & Control : Ccc, 2006 Dec; 17(10), p. 1237-44.
PMID: 17111254
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Getting more from digital SNP data.
Authors: El Karoui N. , Zhou W. , Whittemore A.S. .
Source: Statistics In Medicine, 2006-09-30 00:00:00.0; 25(18), p. 3124-33.
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Nonparametric linkage analysis using person-specific covariates.
Authors: Whittemore A.S. , Halpern J. .
Source: Genetic Epidemiology, 2006 Jul; 30(5), p. 369-79.
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Breast and ovarian cancer in relatives of cancer patients, with and without BRCA mutations.
Authors: Lee J.S. , John E.M. , McGuire V. , Felberg A. , Ostrow K.L. , DiCioccio R.A. , Li F.P. , Miron A. , West D.W. , Whittemore A.S. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2006 Feb; 15(2), p. 359-63.
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Prostate specific antigen levels in young adulthood predict prostate cancer risk: results from a cohort of Black and White Americans.
Authors: Whittemore A.S. , Cirillo P.M. , Feldman D. , Cohn B.A. .
Source: The Journal Of Urology, 2005 Sep; 174(3), p. 872-6; discussion 876.
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Covariate adjustment in family-based association studies.
Authors: Whittemore A.S. , Halpern J. , Ahsan H. .
Source: Genetic Epidemiology, 2005 Apr; 28(3), p. 244-55.
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Histologic types of epithelial ovarian cancer: have they different risk factors?
Authors: Kurian A.W. , Balise R.R. , McGuire V. , Whittemore A.S. .
Source: Gynecologic Oncology, 2005 Feb; 96(2), p. 520-30.
PMID: 15661246
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Prevalence of BRCA1 mutation carriers among U.S. non-Hispanic Whites.
Authors: Whittemore A.S. , Gong G. , John E.M. , McGuire V. , Li F.P. , Ostrow K.L. , Dicioccio R. , Felberg A. , West D.W. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2004 Dec; 13(12), p. 2078-83.
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Classifying disease chromosomes arising from multiple founders, with application to fine-scale haplotype mapping.
Authors: Yu K. , Martin R.B. , Whittemore A.S. .
Source: Genetic Epidemiology, 2004 Nov; 27(3), p. 173-81.
PMID: 15389930
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Logistic regression of family data from retrospective study designs.
Authors: Whittemore A.S. , Halpern J. .
Source: Genetic Epidemiology, 2003 Nov; 25(3), p. 177-89.
PMID: 14557986
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Genetic association tests for family data with missing parental genotypes: a comparison.
Authors: Whittemore A.S. , Halpern J. .
Source: Genetic Epidemiology, 2003 Jul; 25(1), p. 80-91.
PMID: 12813729
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Optimal designs for estimating penetrance of rare mutations of a disease-susceptibility gene.
Authors: Gong G. , Whittemore A.S. .
Source: Genetic Epidemiology, 2003 Apr; 24(3), p. 173-80.
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