METHODS: We did a genome-wide association study of NKTCL in multiple populations from east Asia. We recruited a discovery cohort of 700 cases with NKTCL and 7752 controls without NKTCL of Han Chinese ancestry from 19 centres in southern, central, and northern regions of China, and four independent replication samples including 717 cases and 12 650 controls. Three of these independent samples (451 cases and 5301 controls) were from eight centres in the same regions of southern, central, and northern China, and the fourth (266 cases and 7349 controls) was from 11 centres in Hong Kong, Taiwan, Singapore, and South Korea. All cases had primary NKTCL that was confirmed histopathologically, and matching with controls was based on geographical region and self-reported ancestry. Logistic regression analysis was done independently by geographical regions, followed by fixed-effect meta-analyses, to identify susceptibility loci. Bioinformatic approaches, including expression quantitative trait loci, binding motif and transcriptome analyses, and biological experiments were done to fine-map and explore the functional relevance of genome-wide association loci to the development of NKTCL.

FINDINGS: Genetic data were gathered between Jan 1, 2008, and Jan 23, 2019. Meta-analysis of all samples (a total of 1417 cases and 20 402 controls) identified two novel loci significantly associated with NKTCL: IL18RAP on 2q12.1 (rs13015714; p=2·83 × 10-16; odds ratio 1·39 [95% CI 1·28-1·50]) and HLA-DRB1 on 6p21.3 (rs9271588; 9·35 × 10-26 1·53 [1·41-1·65]). Fine-mapping and experimental analyses showed that rs1420106 at the promoter of IL18RAP was highly correlated with rs13015714, and the rs1420106-A risk variant had an upregulatory effect on IL18RAP expression. Cell growth assays in two NKTCL cell lines (YT and SNK-6 cells) showed that knockdown of IL18RAP inhibited cell proliferation by cell cycle arrest in NKTCL cells. Haplotype association analysis showed that haplotype 47F-67I was associated with reduced risk of NKTCL, whereas 47Y-67L was associated with increased risk of NKTCL. These two positions are component parts of the peptide-binding pocket 7 (P7) of the HLA-DR heterodimer, suggesting that these alterations might account for the association at HLA-DRB1, independent of the previously reported HLA-DPB1 variants.

INTERPRETATION: Our findings provide new insights into the development of NKTCL by showing the importance of inflammation and immune regulation through the IL18-IL18RAP axis and antigen presentation involving HLA-DRB1, which might help to identify potential therapeutic targets. Taken in combination with additional genetic and other risk factors, our results could potentially be used to stratify people at high risk of NKTCL for targeted prevention.

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 conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.

RESULTS: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.