Application of Crossover Analysis-logistic Regression in the Assessment of Gene- environmental Interactions for Colorectal Cancer

Abstract

Background: Analysis of gene-gene and gene-environment interactions for complex multifactorial human disease faces challenges regarding statistical methodology. One major difficulty is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes or environmental exposures. Based on our previous case-control study in Chongqing of China, we have found increased risk of colorectal cancer exists in individuals carrying a novel homozygous TT at locus rs1329149 and known homozygous AA at locus rs671. Methods: In this study, we proposed statistical methodcrossover analysis in combination with logistic regression model, to further analyze our data and focus on assessing gene-environmental interactions for colorectal cancer. Results: The results of the crossover analysis showed that there are possible multiplicative interactions between loci rs671 and rs1329149 with alcohol consumption. Multifactorial logistic regression analysis also validated that loci rs671 and rs1329149 both exhibited a multiplicative interaction with alcohol consumption. Moreover, we also found additive interactions between any pair of two factors (among the four risk factors: gene loci rs671, rs1329149, age and alcohol consumption) through the crossover analysis, which was not evident on logistic regression. Conclusions: In conclusion, the method based on crossover analysis-logistic regression is successful in assessing additive and multiplicative gene-environment interactions, and in revealing synergistic effects of gene loci rs671 and rs1329149 with alcohol consumption in the pathogenesis and development of colorectal cancer.

Dietary factors and polymorphisms in vitamin D metabolism genes: the risk and prognosis of colorectal cancer in northeast China

“…Univariate and multivariate logistic regression analyses were used to calculate crude and adjusted ORs and 95% CIs. The combined and interactive effects between genetic polymorphisms and dietary factors were estimated by crossover analysis and multivariate logistic regression 51 .…”

Are dietary factors involved in the association of CDH4 methylation and breast cancer risk?

“…The same statistical methods were also used to determine the effects of dietary factors and lifestyle on CDH4 methylation in tumor tissue DNA. A cross-over study and multivariate logistic regression were used to assess the combined and interactive effects between CDH4 methylation, dietary factors, and lifestyle in breast cancer cases (24) . The correlation between CDH4 methylation in tumor tissue DNA, PBL DNA in breast tumor tissue, and clinicopathological characteristics were evaluated by a Chi-square test.…”

Association between the HSPA1B ±1267A/G Polymorphism and Cancer Risk: a Meta-analysis of 14 Case-Control Studies

“…For example, several GWAS studies have reported polymorphisms at 6p21.3 were associated with lung cancer risk, but they did not exist in Asians according to the HapMap project (Hung et al, 2008;Wang et al, 2008;Broderick et al, 2009). The other reason may be that different ethnicities which live in different regions have various dietary habits and lifestyles and expose to multiple environmental factors, and thus yield diverse gene-environment interactions (Latvala et al, 2011;Wu et al, 2012).…”