SHORT CONCLUSION: In conclusion, INDELs and VNTRs could have important functional consequences in the pathophysiology of obesity, and research on them should be continued to facilitate obesity prediction, prevention, and treatment.
METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics.
RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7).
CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans.
IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.
AIMS: This study was aimed to examine the association between BsmI polymorphism and risk of vitamin D deficiency, obesity and insulin resistance in adolescents living in a tropical country.
METHODS: Thirteen-year-old adolescents were recruited via multistage sampling from twenty-three randomly selected schools across the city of Kuala Lumpur, Malaysia (n = 941). Anthropometric measurements were obtained. Obesity was defined as body mass index higher than the 95th percentile of the WHO chart. Levels of fasting serum vitamin D (25-hydroxyvitamin D (25(OH)D)), glucose and insulin were measured. HOMA-IR was calculated as an indicator for insulin resistance. Genotyping was performed using the Sequenom MassARRAY platform (n = 807). The associations between BsmI and vitamin D, anthropometric parameters and HOMA-IR were examined using analysis of covariance and logistic regression.
RESULT: Those with AA genotype of BsmI had significantly lower levels of 25(OH)D (p = 0.001) compared to other genotypes. No significant differences was found across genotypes for obesity parameters. The AA genotype was associated with higher risk of vitamin D deficiency (p = 0.03) and insulin resistance (p = 0.03) compared to GG. The A allele was significantly associated with increased risk of vitamin D deficiency compared to G allele (adjusted odds ratio (OR) = 1.63 (95% Confidence Interval (CI) 1.03-2.59, p = 0.04). In those with concurrent vitamin D deficiency, having an A allele significantly increased their risk of having insulin resistance compared to G allele (adjusted OR = 2.66 (95% CI 1.36-5.19, p = 0.004).
CONCLUSION: VDR BsmI polymorphism was significantly associated with vitamin D deficiency and insulin resistance, but not with obesity in this population.