Estimation on gene-environment interaction in the partial case-control study.
- Author:
Jian-ling BAI
1
;
Peng-cheng XUN
;
Yang ZHAO
;
Hao YU
;
Hong-bing SHEN
;
Qing-yi WEI
;
Feng CHEN
Author Information
- Publication Type:Journal Article
- MeSH: Case-Control Studies; Environment; Genotype; Humans; Linear Models; Logistic Models; Models, Statistical; Reproducibility of Results
- From: Chinese Journal of Epidemiology 2006;27(1):72-75
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo introduce the approaches for estimating gene-environment interaction based on partial case-control studies.
METHODSThe effects of logistic model and log-linear model for estimating the main effects and gene-environment interaction effect were estimated by means of maximum likelihood methods in traditional case-control studies, case-only studies and partial case-control studies, respectively. An example was also illustrated.
RESULTSIn traditional case-control study with complete data, the results of logistic model and log-linear model were equivalent. In case-only study without any information about controls, the logistic model can also efficiently estimate gene-environment interaction. In partial case-control study, environmental information was collected from all of the cases and controls, while genetic information was only collected from cases. For this case-control study with incomplete data, a suitable parameterized log-linear model could simultaneously and efficiently estimate the main effect of environment and gene-environment interaction, whereas the logistic model could not.
CONCLUSIONFor a partial case-control study, log-linear model could estimate not only the main effect of environment but also gene-environment interaction. If genotype and exposure were independent, estimators from partial case-control were as precisely as those from complete-data case-control studies.