Grant Details
Grant Number: |
5R01CA094069-03 Interpret this number |
Primary Investigator: |
Whittemore, Alice |
Organization: |
Stanford University |
Project Title: |
Statistical Methods for Genetic Epidemiology |
Fiscal Year: |
2004 |
Abstract
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.
Publications
None