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.

METHODS: We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data.

RESULTS: Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: linoleic acid odds ratio (OR) = 1.00, 95% confidence interval (CI) = 0.98-1.02; arachidonic acid OR = 1.00, 95% CI = 0.99-1.01; and dihomo-gamma-linolenic acid OR = 0.95, 95% CI = 0.87-1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex.

CONCLUSIONS: Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk.

OBJECTIVES: First, to summarize the main design features of a prospective case-control study -nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort- on plasma concentrations of persistent organic pollutants (POPs) and pancreatic cancer risk. And second, to assess the main methodological challenges posed by associations among characteristics and habits of study participants, fasting status, time from blood draw to cancer diagnosis, disease progression bias, basis of cancer diagnosis, and plasma concentrations of lipids and POPs. Results from etiologic analyses on POPs and pancreatic cancer risk, and other analyses, will be reported in future articles.

METHODS: Study subjects were 1533 participants (513 cases and 1020 controls matched by study centre, sex, age at blood collection, date and time of blood collection, and fasting status) enrolled between 1992 and 2000. Plasma concentrations of 22 POPs were measured by gas chromatography - triple quadrupole mass spectrometry (GC-MS/MS). To estimate the magnitude of the associations we calculated multivariate-adjusted odds ratios by unconditional logistic regression, and adjusted geometric means by General Linear Regression Models.

RESULTS: There were differences among countries in subjects' characteristics (as age, gender, smoking, lipid and POP concentrations), and in study characteristics (as time from blood collection to index date, year of last follow-up, length of follow-up, basis of cancer diagnosis, and fasting status). Adjusting for centre and time of blood collection, no factors were significantly associated with fasting status. Plasma concentrations of lipids were related to age, body mass index, fasting, country, and smoking. We detected and quantified 16 of the 22 POPs in more than 90% of individuals. All 22 POPs were detected in some participants, and the smallest number of POPs detected in one person was 15 (median, 19) with few differences by country. The highest concentrations were found for p,p'-DDE, PCBs 153 and 180 (median concentration: 3371, 1023, and 810 pg/mL, respectively). We assessed the possible occurrence of disease progression bias (DPB) in eight situations defined by lipid and POP measurements, on one hand, and by four factors: interval from blood draw to index date, tumour subsite, tumour stage, and grade of differentiation, on the other. In seven of the eight situations results supported the absence of DPB.

METHODS: To gain a more comprehensive picture on how these markers can modulate BC risk, alone or in conjunction, we performed simultaneous measurements of LTL and mtDNA copy number in up to 570 BC cases and 538 controls from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. As a first step, we measured LTL and mtDNA copy number in 96 individuals for which a blood sample had been collected twice with an interval of 15 years.

RESULTS: According to the intraclass correlation (ICC), we found very good stability over the time period for both measurements, with ICCs of 0.63 for LTL and 0.60 for mtDNA copy number. In the analysis of the entire study sample, we observed that longer LTL was strongly associated with increased risk of BC (OR 2.71, 95% CI 1.58-4.65, p = 3.07 × 10- 4 for highest vs. lowest quartile; OR 3.20, 95% CI 1.57-6.55, p = 1.41 × 10- 3 as a continuous variable). We did not find any association between mtDNA copy number and BC risk; however, when considering only the functional copies, we observed an increased risk of developing estrogen receptor-positive BC (OR 2.47, 95% CI 1.05-5.80, p = 0.04 for highest vs. lowest quartile).