J Shen1, R Wang, X Xu. 1. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100083, China.
Abstract
OBJECTIVE: Taking GST M1 as an example to introduce analytic method of interaction models between the polymorphism(s) of metabolic gene(s) and environmental exposure in stomach cancer susceptibility. METHODS: Using community-based case-control design, combined with molecular biological techniques (PCR) and multiple variables logistic regression models, we analyzed 112 intestinal types of stomach cancer cases with endoscopy and pathology diagnosis in the Yangzhong City Hospital during January 1997 and December 1998. A total of 675 controls were selected from persons who had no history of digestive system cancers. RESULTS: After adjustment of confounding variables with both GST M1 null genotype and history of ever tobacco smoking, the results showed a significant types of 4 gene-environment interaction. Interaction index (gamma) value was 3.38 and OR(eg) value was 8.40, suggesting that a super multiplicative interaction occurred. The results also showed that GST M1 null genotype had a high exposure-gene effect interaction with tobacco smoking (pack year), while gamma values were 0.995, 2.085 and 2.157 respectively. A low exposure-gene effect interaction was found in GST M1 null genotype with the amount of (kg x year) alcohol consumption while gamma values were 1.01 and 0.97 respectively. CONCLUSION: Logistic regression model can be used to evaluate gene-environment interaction and dose-response of exposure-gene effect.
OBJECTIVE: Taking GST M1 as an example to introduce analytic method of interaction models between the polymorphism(s) of metabolic gene(s) and environmental exposure in stomach cancer susceptibility. METHODS: Using community-based case-control design, combined with molecular biological techniques (PCR) and multiple variables logistic regression models, we analyzed 112 intestinal types of stomach cancer cases with endoscopy and pathology diagnosis in the Yangzhong City Hospital during January 1997 and December 1998. A total of 675 controls were selected from persons who had no history of digestive system cancers. RESULTS: After adjustment of confounding variables with both GST M1 null genotype and history of ever tobacco smoking, the results showed a significant types of 4 gene-environment interaction. Interaction index (gamma) value was 3.38 and OR(eg) value was 8.40, suggesting that a super multiplicative interaction occurred. The results also showed that GST M1 null genotype had a high exposure-gene effect interaction with tobacco smoking (pack year), while gamma values were 0.995, 2.085 and 2.157 respectively. A low exposure-gene effect interaction was found in GST M1 null genotype with the amount of (kg x year) alcohol consumption while gamma values were 1.01 and 0.97 respectively. CONCLUSION: Logistic regression model can be used to evaluate gene-environment interaction and dose-response of exposure-gene effect.