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Assessing Gene-Gene Interaction Involved In Nasopharyngeal Carcinoma

Guangzhou, China


This pilot study uses a case-control study design in a high-risk area of Southern China. Using blood samples from a large number of newly diagnosed nasopharyngeal carcinoma (NPC) cases and friend controls, we will genotype 10 selected genes (CYPA1, CYPA2, CYP2E1, CYP2D6, GSTT1, GSTM1, NAT1, NAT2, NQO1, and CYP1B1) based on biological plausibility, and record information on smoking status, consumption of salted fish, and preserved fruits and vegetables. To date, we collected blood samples from 500 NPC cases and 500 controls who match cases by gender and age. We finished genotyping CYP1A1, CYP1A2, CYP2E1 and CYP1B1 on 1000 subjects.

We performed univariate analysis to assess association between NPC and genetic and environmental risk factors. Further, we also used logistic regression analysis to assess gene-gene interactions involved in NPC.

While no positive signals were obtained for CYP1A1, CYP1A2, CYP1B1, we detected a significant association between a haplotype in CYP2E1 and increased NPC risk (p-value=0.008) and the haplotype frequency was estimated to be 0.162 in this study population. Single point analysis suggested that SNPs hCV2431884 and hCV2431878 contribute to the signal, which may suggest that these two SNPs are in linkage disequilibrium with a potentially causal SNP for NPC. Further research is needed to verify this finding. More genotyping is ongoing and gene-gene interaction will be assessed for their role in NPC development.

To summarize, this pilot study has helped us develop an effective questionnaire, determined the appropriate sample size for the large scale study, and estimated the variability of polymorphisms of interest in the population of GuangDong. Further, we will apply for future funding to explore an adaptive regression methodology to assess gene-gene interaction by constructing predictors as Boolean combinations of binary covariates, using simulated annealing, in collaboration with the Department of Biostatistics at JHSPH.


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