An Atlas of Dietary Intakes and Medication Uses on Risk of Bladder Cancer: A Wide-Angle Mendelian Randomization Analysis.

BACKGROUND: Observational studies suggests that diets and medications affect bladder cancer (BC) development, which are subject to confounding and difficult to make causal inference. Here we aimed to investigate whether those observational associations are causal and determining the potential directions and pathways. METHODS: We used 2-sample Mendelian randomization (MR) analysis to assess associations of dietary intakes, medication uses and molecules with BC risk. Genetic summary data were derived from participants of predominantly European ancestry with rigorous instruments selection, where univariable MR, mediation MR and multivariable MR were performed. RESULTS: The results of univariable MR showed 4 dietary intakes and 4 medication uses having a protective effect on BC, while 4 circulating metabolites, 440 circulating proteins and 2 gut microbes were observed to be causally associated with BC risk. Through mediation MR, we found 572 analytes showing consistent mediating effects between dietary intakes or medication uses and BC risk. Furthermore, 9 out of 16 diet-medication pairs showed significant interactions and alterations on BC when consumed jointly. CONCLUSION: In summary, the findings obtained from the current study have important implications for informing prevention strategies that point to potential lifestyle interventions or medication prescriptions to reduce the risk of developing BC.HighlightsThe current study extends observational literature in showing the importance of diets and medications on bladder cancer prevention.The associations of diets and medications on bladder cancer prevention might be through circulating metabolites, circulating proteins and gut microbiotaOur results provide a new understanding of interactions in certain diet-medication pairs which should be taken into account by both physicians and patients during the development of a treatment strategy.

The effects of the interaction of genetic predisposition with lifestyle factors on bladder cancer risk.

OBJECTIVES: To investigate the association of polygenic risk score (PRS) and bladder cancer (BC) risk and whether this PRS can be offset by a healthy lifestyle. METHODS: Individuals with BC (n = 563) and non-BC controls (n = 483 957) were identified in the UK Biobank, and adjusted Cox regression models were used. A PRS was constructed based on 34 genetic variants associated with BC development, while a healthy lifestyle score (HLS) was constructed based on three lifestyle factors (i.e., smoking, physical activity, and diet). RESULTS: Overall, a negative interaction was observed between the PRS and the HLS (P = 0.02). A 7% higher and 28% lower BC risk per 1-standard deviation (SD) increment in PRS and HLS were observed, respectively. A simultaneous increment of 1 SD in both HLS and PRS was associated with a 6% lower BC risk. In addition, individuals with a high genetic risk and an unfavourable lifestyle showed an increased BC risk compared to individuals with low genetic risk and a favourable lifestyle (hazard ratio 1.55, 95% confidence interval 1.16-1.91; P for trend <0.001). Furthermore, population-attributable fraction (PAF) analysis showed that 12%-15% of the BC cases might have been prevented if individuals had adhered to a healthy lifestyle. CONCLUSION: This large-scale cohort study shows that a genetic predisposition combined with unhealthy behaviours have a joint negative effect on the risk of developing BC. Behavioural lifestyle changes should be encouraged for people through comprehensive, multifactorial approaches, although high-risk individuals may be selected based on genetic risk.

Association of demographic and clinical factors with risk of acute pancreatitis: An exposure-wide Mendelian randomization study.

BACKGROUND: The incidence of acute pancreatitis (AP) is increasing over years, which brings enormous economy and health burden. However, the aetiologies of AP and underlying mechanisms are still unclear. Here, we performed a two-sample Mendelian randomization (MR) analysis to investigate the associations between all reported possible risk factors and AP using publicly available genome-wide association study summary statistics. METHODS: A series of quality control steps were taken in our analysis to select eligible instrumental single nucleotide polymorphisms which were strongly associated with exposures. To make the conclusions more robust and reliable, we utilized several analytical methods (inverse-variance weighting, MR-PRESSO method, weighted median, MR-Egger regression) that are based on different assumptions of two-sample MR analysis. The MR-Egger intercept test, radial regression and leave-one-out sensitivity analysis were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of these genetic variants on each exposure. A two-step MR method was applied to explore mediators in significant associations. RESULTS: Genetic predisposition to cholelithiasis (effect estimate: 17.30, 95% CI: 12.25-22.36, p = 1.95 E-11), body mass index (0.32, 95% CI: 0.13-0.51, p < 0.001), body fat percentage (0.57, 95% CI: 0.31-0.83, p = 1.31 E-05), trunk fat percentage (0.36, 95% CI: 0.14-0.59, p < 0.005), ever smoked (1.61, 95% CI: 0.45-2.77, p = 0.007), and limbs fat percentage (0.55, 95% CI: 0.41-0.69, p < 0.001) were associated with an increased risk of AP. In addition, whole-body fat-free mass (-0.32, 95% CI: -0.55 to -0.10, p = 0.004) was associated with a decrease risk of AP. CONCLUSION: Genetic predisposition to cholelithiasis, obesity and smoking could be causally associated with an increased risk of AP, and whole body fat-free mass could be associated with a decreased risk of AP.

High Throughput Isolation and Data Independent Acquisition Mass Spectrometry (DIA-MS) of Urinary Extracellular Vesicles to Improve Prostate Cancer Diagnosis.

Proteomic profiling of extracellular vesicles (EVs) represents a promising approach for early detection and therapeutic monitoring of diseases such as cancer. The focus of this study was to apply robust EV isolation and subsequent data-independent acquisition mass spectrometry (DIA-MS) for urinary EV proteomics of prostate cancer and prostate inflammation patients. Urinary EVs were isolated by functionalized magnetic beads through chemical affinity on an automatic station, and EV proteins were analyzed by integrating three library-base analyses (Direct-DIA, GPF-DIA, and Fractionated DDA-base DIA) to improve the coverage and quantitation. We assessed the levels of urinary EV-associated proteins based on 40 samples consisting of 20 cases and 20 controls, where 18 EV proteins were identified to be differentiated in prostate cancer outcome, of which three (i.e., SERPINA3, LRG1, and SCGB3A1) were shown to be consistently upregulated. We also observed 6 out of the 18 (33%) EV proteins that had been developed as drug targets, while some of them showed protein-protein interactions. Moreover, the potential mechanistic pathways of 18 significantly different EV proteins were enriched in metabolic, immune, and inflammatory activities. These results showed consistency in an independent cohort with 20 participants. Using a random forest algorithm for classification assessment, including the identified EV proteins, we found that SERPINA3, LRG1, or SCGB3A1 add predictable value in addition to age, prostate size, body mass index (BMI), and prostate-specific antigen (PSA). In summary, the current study demonstrates a translational workflow to identify EV proteins as molecular markers to improve the clinical diagnosis of prostate cancer.

Integrative Multi-Omics Analysis for the Determination of Non-Muscle Invasive vs. Muscle Invasive Bladder Cancer: A Pilot Study.

OBJECTIVES: The molecular landscape of non-muscle-invasive (NMIBC) and muscle-invasive (MIBC) bladder cancer based on molecular characteristics is essential but poorly understood. In this pilot study we aimed to identify a multi-omics signature that can distinguish MIBC from NMIBC. Such a signature can assist in finding potential mechanistic biomarkers and druggable targets. METHODS: Patients diagnosed with NMIBC (n = 15) and MIBC (n = 11) were recruited at a tertiary-care hospital in Nanjing from 1 April 2021, and 31 July 2021. Blood, urine and stool samples per participant were collected, in which the serum metabolome, urine metabolome, gut microbiome, and serum extracellular vesicles (EV) proteome were quantified. The differences of the global profiles and individual omics measure between NMIBC vs. MIBC were assessed by permutational multivariate analysis and the Mann-Whitney test, respectively. Logistic regression analysis was used to assess the association of each identified analyte with NMIBC vs. MIBC, and the Spearman correlation was used to investigate the correlations between identified analytes, where both were adjusted for age, sex and smoking status. RESULTS: Among 3168 multi-omics measures that passed the quality control, 159 were identified to be differentiated in NMIBC vs. MIBC. Of these, 46 analytes were associated with bladder cancer progression. In addition, the global profiles showed significantly different urine metabolome (p = 0.029), gut microbiome (p = 0.036), and serum EV (extracellular vesicles) proteome (p = 0.039) but not serum metabolome (p = 0.059). We also observed 17 (35%) analytes that had been developed as drug targets. Multiple interactions were obtained between the identified analytes, whereas for the majority (61%), the number of interactions was at 11-20. Moreover, unconjugated bilirubin (p = 0.009) and white blood cell count (p = 0.006) were also shown to be different in NMIBC and MIBC, and associated with 11 identified omics analytes. CONCLUSIONS: The pilot study has shown promising to monitor the progression of bladder cancer by integrating multi-omics data and deserves further investigations.