BackgroundRecent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression.ObjectiveTo explore the faecal and salivary microbiota as potential diagnostic biomarkers.MethodsWe applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case–control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case–control study (n=76), in the validation phase.ResultsFaecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19–9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation.ConclusionTaken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Human arsenic methylation efficiency has been consistently associated with arsenic-induced disease risk. Interindividual variation in arsenic methylation profiles is commonly observed in exposed populations, and great effort has been put into the study of potential determinants of this variability. Among the factors that have been evaluated, body mass index (BMI) has not been consistently associated with arsenic methylation efficiency, however an underrepresentation of the upper BMI distribution was commonly observed in these studies. This study investigated potential factors contributing to variations in the metabolism of arsenic, with specific interest in the effect of BMI where more than half of the population was overweight or obese. We studied 624 adult women exposed to arsenic in drinking water from three independent populations. Multivariate regression models showed that higher BMI, arsenic (+3 oxidation state) methyltransferase (AS3MT) genetic variant 7388, and higher total urinary arsenic, were significantly associated with low percentage of urinary arsenic excreted as monomethylarsonic acid (%uMMA) or high ratio between urinary dimethylarsinic acid and uMMA (uDMA/uMMA); while AS3MT genetic variant M287T was associated with high %uMMA and low uDMA/uMMA. The association between BMI and arsenic methylation efficiency was also evident in each of the three populations when studied separately. This strong association observed between high BMI and low %uMMA and high uDMA/uMMA underscores the importance of BMI as a potential arsenic-associated disease risk factor, and should be carefully considered in future studies associating human arsenic metabolism and toxicity.

ObjectivesTo characterise the association between type 2 diabetes mellitus (T2DM) subtypes (new-onset T2DM (NODM) or long-standing T2DM (LSDM)) and pancreatic cancer (PC) risk, to explore the direction of causation through Mendelian randomisation (MR) analysis and to assess the mediation role of body mass index (BMI).DesignInformation about T2DM and related factors was collected from 2018 PC cases and 1540 controls from the PanGenEU (European Study into Digestive Illnesses and Genetics) study. A subset of PC cases and controls had glycated haemoglobin, C-peptide and genotype data. Multivariate logistic regression models were applied to derive ORs and 95% CIs. T2DM and PC-related single nucleotide polymorphism (SNP) were used as instrumental variables (IVs) in bidirectional MR analysis to test for two-way causal associations between PC, NODM and LSDM. Indirect and direct effects of the BMI-T2DM-PC association were further explored using mediation analysis.ResultsT2DM was associated with an increased PC risk when compared with non-T2DM (OR=2.50; 95% CI: 2.05 to 3.05), the risk being greater for NODM (OR=6.39; 95% CI: 4.18 to 9.78) and insulin users (OR=3.69; 95% CI: 2.80 to 4.86). The causal association between T2DM (57-SNP IV) and PC was not statistically significant (ORLSDM=1.08, 95% CI: 0.86 to 1.29, ORNODM=1.06, 95% CI: 0.95 to 1.17). In contrast, there was a causal association between PC (40-SNP IV) and NODM (OR=2.85; 95% CI: 2.04 to 3.98), although genetic pleiotropy was present (MR-Egger: p value=0.03). Potential mediating effects of BMI (125-SNPs as IV), particularly in terms of weight loss, were evidenced on the NODM-PC association (indirect effect for BMI in previous years=0.55).ConclusionFindings of this study do not support a causal effect of LSDM on PC, but suggest that PC causes NODM. The interplay between obesity, PC and T2DM is complex.