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.
CONCLUSION: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.
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.
METHODS: We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide.
FINDINGS: Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur.
INTERPRETATION: Our results provide the evidence base for targeting vaccination campaigns within risk zones, as well as emphasising their high effectiveness. Our study highlights areas where public health authorities should be most vigilant for potential spread or importation events.
FUNDING: Bill & Melinda Gates Foundation.
METHODS: The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values.
RESULTS: The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations.
CONCLUSIONS: Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.
OBJECTIVE: The purpose of this study was to describe the natural history of acute elevated Micra vs traditional transvenous lead thresholds.
METHODS: Micra study VVI patients with threshold data (at 0.24 ms) at implant (n = 711) were compared with Capture study patients with de novo transvenous leads at 0.4 ms (n = 538). In both cohorts, high thresholds were defined as >1.0 V and very high as >1.5 V. Change in pacing threshold (0-6 months) with high (1.0 to ≤1.5 V) or very high (>1.5 V) thresholds were compared using the Wilcoxon signed-rank test.
RESULTS: Of the 711 Micra patients, 83 (11.7%) had an implant threshold of >1.0 V at 0.24 ms. Of the 538 Capture patients, 50 (9.3%) had an implant threshold of >1.0 V at 0.40 ms. There were no significant differences in patient characteristics between those with and without an implant threshold of >1.0 V, with the exception of left ventricular ejection fraction in the Capture cohort (high vs low thresholds, 53% vs 58%; P = .011). Patients with an implant threshold of >1.0 V decreased significantly (P < .001) in both cohorts. Micra patients with high and very high thresholds decreased significantly (P < .01) by 1 month, with 87% and 85% having 6-month thresholds lower than the implant value. However, when the capture threshold at implant was >2 V, only 18.2% had a threshold of ≤1 V at 6 months and 45.5% had a capture threshold of >2 V.
CONCLUSIONS: Pacing thresholds in most Micra patients with elevated thresholds decrease after implant. Micra device repositioning may not be necessary if the pacing threshold is ≤2 V.
METHODS AND RESULTS: The primary outcome (risk of cardiac failure, pacemaker syndrome, or syncope related to the Micra system or procedure) was compared between successfully implanted patients from the Micra IDE trial with a primary pacing indication associated with AF or history of AF (AF group) and those without (non-AF group). Among 720 patients successfully implanted with Micra, 228 (31.7%) were in the non-AF group. Reasons for selecting VVI pacing in non-AF patients included an expectation for infrequent pacing (66.2%) and advanced age (27.2%). More patients in the non-AF group had a condition that precluded the use of a transvenous pacemaker (9.6% vs. 4.7%, P = 0.013). Atrial fibrillation patients programmed to VVI received significantly more ventricular pacing compared to non-AF patients (median 67.8% vs. 12.6%; P
METHODS: Eleven case-control studies within the International Pancreatic Cancer Case-control Consortium took part in the present study, including in total 2838 case and 4748 control women. Pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated using a 2-step logistic regression model and adjusting for relevant covariates.
RESULTS: An inverse OR was observed in women who reported having had hysterectomy (ORyesvs.no, 0.78; 95% CI, 0.67-0.91), remaining significant in postmenopausal women and never-smoking women, adjusted for potential PC confounders. A mutually adjusted model with the joint effect for hormone replacement therapy (HRT) and hysterectomy showed significant inverse associations with PC in women who reported having had hysterectomy with HRT use (OR, 0.64; 95% CI, 0.48-0.84).
CONCLUSIONS: Our large pooled analysis suggests that women who have had a hysterectomy may have reduced risk of PC. However, we cannot rule out that the reduced risk could be due to factors or indications for having had a hysterectomy. Further investigation of risk according to HRT use and reason for hysterectomy may be necessary.