Universität zu Lübeck
UNIVERSITÄTSKLINIKUM Schleswig-Holstein - Campus Lübeck
Institut für Medizinische Biometrie und Statistik
Direktor: Prof. Dr. rer. nat. Andreas Ziegler
UNIVERSITÄTSKLINIKUM Schleswig-Holstein - Campus Lübeck
Institut für Medizinische Biometrie und Statistik
Direktor: Prof. Dr. rer. nat. Andreas Ziegler
Adaption of an Empirical Bayes approach to investigate gene-environment interactions in large consortia
12. Mai 2010 - 15:27 — Schatton
Dr. Rebecca Hein
Deutsches Krebsforschungszentrum, Heidelberg
Ort des Vortrages:
AM S1
Uhrzeit:
10.00 Uhr s.t.
Datum:
4. Juni 2010 The case-only approach is more powerful to detect gene-environment interactions (GxE) than the case-control approach if the assumption of gene-environment (G-E) independence is valid. Specifically, this assumption may be violated in presence of population stratification. The empirical-Bayes (EB) procedure tests for interaction and exploits the G-E independence assumption but does not rely on this assumption (Mukherjee and Chatterjee, Biometrics, 2008, 64(3):685-94). Therefore, the EB method can have increased power compared to the case-control approach while the type I error is smaller than that of the case-only approach if the independence assumption is violated (Mukherjee et al., 2008).
The Breast Cancer Association Consortium (BCAC) is an international multidisciplinary consortium. Investigators combine data on genetic and environmental/life-style factors of their individual studies, aiming to increase the power for identifying genes that may be related to the risk of breast cancer. Besides the analyses of genetic main effects, GxE analyses involving known environmental risk factors are employed to detect new susceptibility genes. BCAC involves population-based (pb) studies (providing control samples that are considered to be representative for the population from which the cases were drawn) as well as non-population-based (npb) studies with non- representative controls.
For the analysis of genetic main effects it is supposed that reliable estimates can be obtained when combining the results of pb as well as npb studies in a meta-analysis, since it is assumed that minor allele frequencies in the control samples of the npb studies and those in the population from which the cases of the npb studies were drawn are similar. However, for the computation of GxE effect estimates this assumption may not be valid, since unrepresentative control samples may distort the estimates of environmental main and GxE effects.
To cope with this problem one may (1) conduct case-control analyses using pb studies only, which, however, results in a decrease in sample size or (2) perform case-only analyses, which may yield false positive results due to possible G-E dependence. Alternatively, one may use an adapted EB approach that makes use of all available samples while aiming to maintain the pre-specified significance level.
Simulations to estimate type I error and power of the different approaches are ongoing. Results will be presented.