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Research Seminar
Div. of Biostatistics & Epidemiology
Dept. of Public Health
Weill Cornell Medical College, New York, NY
Title:
Identifying SNPs for the Secondary Phenotypes in GWA studies: Application to Smoking Behavior
Speaker:
Sanjay Shete, PhD
Affiliation:
Professor
Dept of Biostatistics, Dept. of Epidemiology.
The University of Texas MD Anderson Cancer Center, Houston
When:
Friday, May 18, 2012
12:00 - 1:00 PM
Where:
Department of Public Health's Conference Center A
402 East 67th Street, Level C1
Abstract:
Genetic association studies for binary diseases are designed as case-control studies: the cases are those affected with the primary disease and the controls are free of the disease. At the time of case-control
collection, information about secondary phenotypes is also collected (e.g. smoking intensity on lung cancer case-control study). Association studies of secondary phenotype and genetic variants have received a great deal of interest recently. To study the secondary
phenotypes, investigators are using standard regression approaches, such as logistic regression, where individuals with secondary phenotypes are coded as cases and those without secondary phenotypes are coded as controls. However, using the secondary phenotype
as an outcome variable in a case-control study might lead to a biased estimate of odds ratios (ORs) for genetic variants. This is because the secondary phenotype is associated with the primary disease of interest; therefore, individuals with (case subject)
and without (control subject) the secondary phenotype are not sampled following the principle of a case-control study design. We demonstrate that such analyses will lead to a biased estimate of OR, and the magnitude of the bias depends on the prevalence values
of both the primary disease and the secondary phenotype. We propose new approaches to provide a more accurate OR estimate of genetic variants associated with the secondary phenotype for both un-matched and frequency-matched (with respect to the secondary phenotype
of interest) case-control association studies. The proposed methods account for the prevalence values of the primary disease and secondary phenotype. The performance of our approach was demonstrated via simulation studies as well as a real data analysis. Applying
our new method to smoking intensity as a secondary phenotype reduced the bias in odds ratio estimation for a single-nucleotide polymorphism in CHRNA5-A3 locus.
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Contact: Gaza @ (646) 962-8024 or [log in to unmask]">[log in to unmask]
Samprit Banerjee, PhD
Assistant Professor,
Div. of Biostatistics & Epidemiology,
Dept. of Public Health
Weill Medical College, Cornell University
402 E 67th Street, LA233
New York, NY-10065
Phone: (646) 962-8014 (1-8014, Internal)
Fax: (646) 962-0281
http://www.weill.cornell.edu/public.health