Genetically Predicted Gut Microbiota and Bladder Cancer Risk: A Mendelian Randomisation Analysis.

The influences of blood lipids and lipid-regulatory medications on the risk of bladder cancer have long been suspected, and previous findings remain controversial. We aimed to assess the causality between blood lipids or lipid-regulatory medications and bladder cancer susceptibility by means of a comprehensive Mendelian Randomization (MR) study. Genetic proxies from genome-wide association studies (GWAS) of four blood lipid traits and lipid-lowering variants in genes encoding the targets of lipid-regulatory medications were employed. The largest ever GWAS data of blood lipids and bladder cancer involving up to 440,546 and 205,771 individuals of European ancestry were extracted from UK Biobank and FinnGen Project Round 6, respectively. A two-sample bidirectional MR study was performed using the inverse variance weighted as the main method. The heterogeneity, horizontal pleiotropy, MR Steiger, and leave-one-out analyses were also conducted as sensitivity tests. There was indicative evidence that genetically predicted low-density lipoprotein cholesterol (LDL-C) affected bladder cancer susceptibility based on 146 single nucleotide polymorphisms (SNPs) with an odds ratio (OR) of 0.776 (95% confidence interval [CI] = 0.625-0.965, p = 0.022). However, this result became non-significant after two SNPs that possibly drove the effect were removed as demonstrated by leave-one-out analysis. The reversed MR analysis suggested that bladder cancer could not affect serum lipid levels. No causal relationship was found between the lipid-lowering effect of lipid-regulatory medications (fibrates, probucol, statins, ezetimibe, proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitors, and evinacumab) and the risk of bladder cancer. No heterogeneity or pleiotropy was found (all p > 0.05). This MR study revealed for the first time, using the most recent and comprehensive GWAS data to date, that genetically predicted total cholesterol (TC) and the lipid-lowering effect of lipid-regulatory medications had no causal association with bladder cancer susceptibility. We also verified claims from early studies that low-density lipoprotein cholesterol (HDL-C), LDL-C, and triglyceride (TG) are not related to bladder cancer susceptibility either. The current study indicated that lipid metabolism may not be as important in the tumorigenesis of bladder cancer as previously believed.

Background:To understand a causal role of modifiable lifestyle factors in angiotensin-converting enzyme 2 (ACE2) expression (a putative severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] receptor) across 44 human tissues/organs, and in coronavirus disease 2019 (COVID-19) susceptibility and severity, we conducted a phenome-wide two-sample Mendelian randomization (MR) study.Methods:More than 500 genetic variants were used as instrumental variables to predict smoking and alcohol consumption. Inverse-variance weighted approach was adopted as the primary method to estimate a causal association, while MR-Egger regression, weighted median, and MR pleiotropy residual sum and outlier (MR-PRESSO) were performed to identify potential horizontal pleiotropy.Results:We found that genetically predicted smoking intensity significantly increased ACE2 expression in thyroid (β=1.468, p=1.8×10−8), and increased ACE2 expression in adipose, brain, colon, and liver with nominal significance. Additionally, genetically predicted smoking initiation significantly increased the risk of COVID-19 onset (odds ratio=1.14, p=8.7×10−5). No statistically significant result was observed for alcohol consumption.Conclusions:Our work demonstrates an important role of smoking, measured by both status and intensity, in the susceptibility to COVID-19.Funding:XJ is supported by research grants from the Swedish Research Council (VR-2018–02247) and Swedish Research Council for Health, Working Life and Welfare (FORTE-2020–00884).

Smoking, measured by both initiation and intensity, are significantly associated with an elevated expression level of ACE2 in multiple human tissues/organs, subsequently increasing the susceptibility and severity of COVID-19.

BackgroundPrevious observational study findings have indicated a vital association between gut microbiota features and retinal diseases based on the “gut–retina” axis. However, whether their relationships underlie causal effects remains to be established.MethodsInstrumental variables of 211 gut microbiota taxa were obtained from a genome‐wide association study (GWAS), and 28 gut‐associated metabolites and pathways were included as exposures. A two‐sample Mendelian randomization (MR) study was carried out to estimate gut microbiota effects on diabetic retinopathy (DR), early age‐related macular degeneration (eAMD), retinal detachments and breaks (RDs/RBs), retinal vascular occlusion (RVO), disorders of the choroid and retina (D‐C/R), and visual impairment. MR methods, including inverse variance weighted (IVW), MR‒Egger, weighted median, simple mode, and weighted mode methods, were used to investigate the causal relationship between gut microbiota features and various outcomes. Heterogeneity, pleiotropy, and stability tests of MR results were performed, and Bonferroni’s correction was used to test the strength of the causal relationships between exposures and outcomes, as well as reverse and multivariable MR analyses.ResultsThrough MR analysis of 211 microbes and six clinical phenotypes, a total of 35 gut microbiome and 3 associated metabolites were found to be associated with various outcomes. Cochrane’s Q test revealed that there was no significant heterogeneity between various single‐nucleotide polymorphisms. In addition, no significant level of pleiotropy was found according to the MR‒Egger and MR‐PRESSO global tests. After the Bonferroni‐corrected test, Genus id.2041 (OR = 0.874, 95% CI: 0.816–0.936, p = 1.10e − 04, IVW) showed robust causality with D‐C/R, which had a nominal association with multiple other retinal diseases as well. Seven exposure–outcome effects markedly remained valid when BMI or alcohol intake frequency was separately included in multivariable MR analyses. According to the results of reverse MR analysis, no significant causal effect of outcomes was found on gut microbiota. No significant heterogeneity of instrumental variables or horizontal pleiotropy was found.ConclusionWe confirmed a potential causal relationship between some gut microbiota features and retinal diseases, thus providing new insights into the gut microbiota–mediated mechanism of retinopathy and indicating vital biomarkers for potential diagnostic, therapeutic, and prevention strategies.

ObjectiveThe causal association between osteoarthritis (OA) and bladder cancer remains unclear. This Mendelian randomization (MR) study was carried out to assess the potential causal effects of any OA, knee OA and hip OA, and bladder cancer.MethodGenome‐wide association study (GWAS) summary data for OA and bladder cancer were obtained in GWAS CATALOG, UK Biobank, and FinnGen Consortium. Inverse‐variance weighted (IVW) approach was primarily conducted to evaluate the causal relationships between OA and bladder cancer, and MR‐Egger intercept and Cochran's Q test were mainly used to estimate heterogeneity and pleiotropy. MR‐PRESSO was used to test the presence of horizontal outliers. Leave‐one‐out analysis was utilized to ensure the reliability of the results.ResultsA higher genetic predisposition to any OA has a causal association with bladder cancer risk, while neither knee OA nor hip OA is causally linked to bladder cancer. MR‐Egger intercept analysis exhibited that any OA and knee OA had no pleiotropic effect on the risk of bladder cancer, and Cochran's Q test showed that any OA, knee OA and hip OA had no heterogeneity on bladder cancer risk. Neither MR PRESSO analysis nor leave‐one‐out analysis revealed any outlier SNPs.ConclusionsThis MR study exhibited a positive cause‐and‐effect relationship between any type of OA and bladder cancer risk, but not between site‐specific OA, knee OA and hip OA, and bladder cancer. Attention should be paid to the screening and prevention of bladder cancer in OA patients at any site.

Increasing evidence indicates a significant correlation between gut microbiota (GM) and susceptibility to chronic kidney disease (CKD). However, causal relationship presence remains uncertain. Mendelian randomization (MR) was applied to evaluate potential causal relation from GM to CKD. Genomic association analysis aggregates publicly online databases, utilizing Genome-Wide Association Study (GWAS) database focused on GM and CKD. For examination of potential causal connection from GM to CKD, a 2-way, 2-sample Mendelian randomization (MR) method was applied. Sensitivity analyses were utilized to scrutinize for heterogeneity, horizontal pleiotropy, MR outcomes resilience. Result from inverse variance weighting (IVW) method revealed that 10 microbiotas such as Porphyromonadaceae (OR = 1.351, 95% CI: 1.114-1.638, P = .002), Dorea (OR = 1.236, 95% CI: 1.040-1.468, P = .016), Ruminococcus torques group (OR = 1.290, 95% CI: 1.035-1.608, P = .024) are potential CKD risk factors. Five microbiotas, including the Prevotellaceae (OR = 0.814, 95% CI: 0.719-0.922, P = .001) are potential CKD protective factors. Sensitivity analyses reveal no horizontal pleiotropy or heterogeneity. Additionally, reverse MR results unveiled potential relation between CKD and disorders in 3 microbiotas, including Senegalimassilia. According to the investigation, MR method was employed to delve into reciprocal causal connection from GM to CKD. Our findings identified 15 types of GM causally linked to CKD, as well as CKD demonstrating causal associations with 3 types of GM. Further exploration of these associated GM types is hopeful to raise novel insights, for CKD preventing and early monitoring.

The causal role of body mass index (BMI) in bladder cancer (BC) by Mendelian randomization (MR) has not yet been reported. We evaluated the causal associations between the measures of obesity (BMI, waist circumference, and body fat percentage) and BC. We conducted a 2-sample MR analysis to assess the genetic effect of measures of obesity on BC. The BMI dataset (GWAS ID: ukb-b-2303) comprised 454,884 Europeans, and we identified 9,851,867 single nucleotide polymorphisms (SNPs). The waist circumference data (GWAS ID: ukb-b-9405) included 462,166 Europeans and 9,851,867 SNPs. The body fat percentage dataset (GWAS ID: ukb-a-264) contained data from 331,117 Europeans and 10,894,596 SNPs. For the outcome data, the GWAS ID was finn-b-C3_BLADDER, consisting of 1115 cases and 217,677 controls, with 16,380,466 SNPs. The inverse-variance weighted (IVW) model was used as the primary MR analysis. Cochran Q-statistic was used to identify heterogeneity between the SNPs. The MR-Egger and MR-PRESSO methods were employed to assess directional pleiotropy and outlier SNPs. We detected a decisive causal link between BMI and BC by the IVW analysis (odds ratio [OR] = 1.41, 95% confidence interval [CI]: 1.08-1.85, P = .011). The IVW analyses revealed a significant correlation between BC and waist circumference (OR = 1.55, 95% CI: 1.08-2.12, P = .016). However, the IVW method (OR = 1.49, 95% CI: 0.99-2.00, P = .05) did not report any statistical significance between body fat percentage and BC. We did not observe heterogeneity and directional pleiotropy in the 3 pairs of MR studies. The 2-sample MR analysis revealed a conceivable causal association between obesity (BMI, waist circumference) and BC.

Previous observational studies and meta-analyses have indicated that prostate cancer and testosterone levels could be potential risk factors for bladder cancer. However, these studies are vulnerable to confounding variables and reverse causality. Thus, we conducted a 2-sample Mendelian Randomization (MR) study to elucidate the causal link between the presence of prostate cancer or testosterone levels and bladder cancer. We acquired summary statistics for the presence of prostate cancer or testosterone levels and bladder cancer from genome-wide association studies (GWAS). MR analysis was employed to investigate the potential causal relationship between the presence of prostate cancer or testosterone levels and bladder cancer. The primary method employed was the inverse variance weighted (IVW) method, with results rigorously assessed through sensitivity analysis. IVW Mendelian randomization results demonstrated that prostate cancer was causally associated with an elevated risk of bladder cancer in FinnGen (OR 1.22, 95% CI, 1.13-1.31, P < .001), UK Biobank (OR 17.9, 95% CI, 3.28-97.62, P < .001), and the PRACTICAL database (OR 1.13, 95% CI, 1.05-1.22, P < .001). There was no evidence of heterogeneity in the effects of genetic factors on bladder cancer risk, as indicated by Cochran's Q statistical test (FinnGen Q = 68.86, P = .13; UK Biobank Q = 29.05, P = .61; PRACTICAL Q = 108.88, P = .48). Sensitivity analyses confirmed the stability and robustness of the genetically determined risk effect of prostate cancer on bladder cancer. However, there was no causal link between testosterone levels and bladder cancer (P > .05). This study identified that genetically predicted prostate cancer was causally linked to an increased risk of bladder cancer. Appropriate measures should be taken to prevent the subsequent development of bladder cancer in patients with prostate cancer.

Studies suggest a possible association between Epstein-Barr virus (EBV) infection and bladder cancer (BCa) risk, though this remains unclear. Secreted frizzled-related protein (sFRP) is also linked to BCa, with some DNA viruses potentially regulating its expression. This study used Mendelian randomization (MR) and colocalization analysis to explore the causal relationship between EBV infection, BCa risk, and the mediating role of sFRP. We first performed a two-sample MR study to assess the causal relationship between 5 EBV-related antibodies (AEB-IgG, EA-D, EBNA-1, VCA-p18, ZEBRA) and BCa using the Finnish Consortium’s R11 dataset, validated with R10. Reverse MR analysis followed. For significant results, multivariable MR (MVMR) was applied to adjust for confounding risk factors. A two-step MR explored the potential mediating role of 3 sFRPs (sFRP1, sFRP2, sFRP3) between positive exposures and BCa. Colocalization analysis were conducted for positive exposures, mediators, and BCa, with multiple sensitivity analyses confirming the robustness of the results. The two-sample Mendelian randomization study found that EBNA-1 (OR = 1.15, 95% CI: 1.01–1.30; p = 0.039) and VCA-p18 (OR = 1.36, 95% CI: 1.13–1.64; p = 0.001) may increase BCa risk, with only VCA-p18 (P_fdr = 0.006) showing a significant effect after False Discovery Rate (FDR) correction. The Finnish Consortium R10 replication study yielded similar results, and reverse MR analysis did not suggest reverse causality. After MVMR adjusted for relevant confounders, VCA-p18 (OR = 1.40, 95% CI: 1.13–1.74; p = 0.002) still significantly increased BCa risk. Two-step MR identified sFRP2 as a mediator, with VCA-p18 down-regulating sFRP2 expression to elevate BCa risk. Colocalization analysis suggested a shared causal variant (nearby gene HLA-DQA1) between VCA-p18 and BCa (PPH4 = 65.44%). Multiple sensitivity analyses confirmed the robustness of the results. Our study suggests that EBV infection (VCA-p18 antibody) may increase the risk of BCa by lowering sFRP2 levels. Additionally, EBNA-1 antibodies may also contribute to an elevated risk of BCa. We hope these findings will provide new insights for future research on the association between EBV and BCa.

The causal relationship between gut microbiota (GM) and pancreatic cancer (PC) remains unclear. This study aimed to investigate the potential genes underlying this mechanism. GM Genome-wide association study (GWAS) summary data were from the MiBioGen consortium. PC GWAS data were from the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalogue. To detect the causal relationship between GM and PC, we implemented three complementary Mendelian randomization (MR) methods: Inverse Variance Weighting (IVW), MR-Egger and Weighted Median, followed by sensitivity analyses. Furthermore, we integrated GM GWAS data with blood cis-expression quantitative trait loci (eQTLs) and blood cis-DNA methylation QTL (mQTLs) using Summary data-based Mendelian Randomization (SMR) methods. This integration aimed to prioritize potential GM-affecting genes through SMR analysis of two molecular traits. PC cis-eQTLs and cis-mQTLs were summarized from The Cancer Genome Atlas (TCGA) data. Through colocalization analysis of GM cis-QTLs and PC cis-QTLs data, we identified common genes that influence both GM and PC. Our study found a causal association between GM and PC, including four protective and five risk-associated GM [Inverse Variance Weighted (IVW), p < 0.05]. No significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was found. The gene SVBP was identified as a GM-affecting gene using SMR analysis of two molecular traits (FDR<0.05, P_HEIDI>0.05). Additionally, two genes, MCM6 and RPS26, were implicated in the interaction between GM and PC based on colocalization analysis (PPH4>0.5). In summary, this study provides evidence for future research aimed at developing suitable therapeutic interventions and disease prevention.

ObjectiveTo investigate the impact of gut microbiota on osteoporosis and identify the mediating role of blood metabolites in this process.MethodsThis two-sample Mendelian randomization (MR) study utilized summary level data from genome-wide association studies (GWAS). Gut microbiota GWAS data were obtained from the MiBio-Gen consortium meta-analysis (n=13,266), while osteoporosis summary statistics were sourced from the FinnGen consortium R9 release data (7300 cases and 358,014 controls). Metabolite data, including 1400 metabolites or metabolite ratios, were derived from a study involving 8,299 unrelated individuals. The primary MR method employed was the inverse variance weighted (IVW) method. Reverse MR analysis was conducted on bacteria causally associated with osteoporosis in forward MR. The gut microbiota with the smallest p-value was selected as the top influencing factor for subsequent mediation analysis. A two-step MR approach quantified the proportion of the blood metabolite effect on gut microbiota influencing osteoporosis. IVW and Egger methods were used to assess heterogeneity and horizontal pleiotropy.ResultsIVW estimates indicated a suggestive effect of family Christensenellaceae on osteoporosis (odds ratio(OR) = 1.292, 95% confidence interval(CI): 1.110–1.503, P =9.198 × 10−4). Reverse MR analysis revealed no significant causal effect of osteoporosis on family Christensenellaceae (OR = 0.947, 95% CI: 0.836–1.072, P =0.386). The proportion of the effect of family Christensenellaceae on osteoporosis mediated by circulating levels of 3,4-dihydroxybutyrate was 9.727%. No significant heterogeneity or horizontal pleiotropy was detected in the instrumental variables used for MR analysis.ConclusionThis study establishes a causal link between family Christensenellaceae and osteoporosis, with a minor proportion of the effect mediated by elevated circulating levels of 3,4-dihydroxybutyrate. Further randomized controlled trials (RCTs) are warranted to validate this conclusion.

Causal relationship between bladder cancer and gut microbiota contributes to the gut-bladder axis: a two-sample Mendelian randomization study

Simple SummaryBladder cancer, an age-related disorder, primarily affects individuals aged 65 and older. Accelerated biological aging, which is linked to increased cancer susceptibility, raises questions about its association with bladder cancer risk. We evaluated four widely recognized epigenetic clocks—HannumAge, HorvathAge, GrimAge, and PhenoAge—for their relationship with bladder cancer risk in a large case–control study. By leveraging genome-wide-association study (GWAS) data and constructing weighted genetic risk scores (GRS), we found that higher HannumAge and HorvathAge GRS were significantly associated with increased bladder cancer risk (OR = 1.69, 95% CI: 1.44–1.98, p = 1.56 × 10−10 and OR = 1.09, 95% CI: 1.00–1.19, p = 0.04, respectively). Mendelian randomization (MR) analysis using inverse-variance weighting (IVW) confirmed these associations, which was also supported by sensitivity analyses. However, GrimAge and PhenoAge showed no significant association with bladder cancer risks. Our findings highlighted the link between accelerated biological aging and elevated bladder cancer risk.Bladder cancer is an age-related disease, with over three-quarters of cases occurring in individuals aged 65 years and older. Accelerated biological aging has been linked to elevated cancer risks. Epigenetic clocks serve as excellent predictors of biological age, yet it remains unclear whether they are associated with bladder cancer risk. In this large case–control study, we assessed the associations between four well-established epigenetic clocks—HannumAge, HorvathAge, GrimAge, and PhenoAge—and bladder cancer risk. Utilizing single nucleotide polymorphisms (SNPs), which were identified in a genome-wide association study (GWAS), linked to these clocks as instruments, we constructed a weighted genetic risk score (GRS) for each clock. We discovered that higher HannumAge and HorvathAge GRS were significantly associated with increased bladder cancer risk (OR = 1.69 per SD increase, 95% CI, 1.44–1.98, p = 1.56 × 10−10 and OR = 1.09 per SD increase, 95% CI, 1.00–1.19, p = 0.04, respectively). Employing a summary statistics-based Mendelian randomization (MR) method, inverse-variance weighting (IVW), we found consistent risk estimates for bladder cancer with both HannumAge and HorvathAge. Sensitivity analyses using weighted median analysis and MR-Egger regression further supported the validity of the IVW method. However, GrimAge and PhenoAge were not associated with bladder cancer risk. In conclusion, our data provide the first evidence that accelerated biological aging is associated with elevated bladder cancer risk.

Increasing evidence indicates that gut microbiota dysbiosis is related to synovitis and tenosynovitis. Nonetheless, whether these associations are causal is currently unknown. A two-sample Mendelian randomization (MR) study was performed to reveal the causality of gut microbiota with synovitis and tenosynovitis. The summary statistical data from a large-scale genome-wide association study (GWAS) were applied as the basis for a two-sample MR analysis. The causal effect was estimated using inverse variance weighted (IVW), weighted median, simple mode, MR-Egger, and weighted mode methods, of which IVW was the important method. Meanwhile, the pleiotropy and heterogeneity were detected and measured using MR-Egger regression, Cochran's Q statistics, funnel plots, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods. The IVW technique demonstrated that genetically predicted five genera, namely Gordonibacter [odds ratio (OR) = 0.999, 95% confidence interval (CI): (0.9977, 0.9998), p = 0.019], Paraprevotella [OR = 0.999, 95% CI: (0.9971, 0.9999), p = 0.036], Lachnoclostridium [OR = 0.998, 95% CI: (0.9954, 0.9999), p = 0.041], RuminococcaceaeUCG003 [OR = 0.997, 95% CI: (0.9955, 0.9994), p = 0.011], and FamilyXIIIAD3011group [OR = 0.997, 95% CI: (0.9954, 0.9992), p = 0.006] were negatively correlated with the risk of synovitis and tenosynovitis, while two other genera, namely Ruminococcustorquesgroup [OR = 1.003, 95% CI: (1.0004, 1.0049), p = 0.019] and Parabacteroides [OR = 1.003, 95% CI: (1.0002, 1.0052), p = 0.035] were positively associated with synovitis and tenosynovitis risk. In addition, the data of sensitivity analyses demonstrated that there were no outliers, horizontal pleiotropy, or heterogeneity in the causal relationship of the above-mentioned gut microbiota on synovitis and tenosynovitis (p > 0.05). The results of the study suggested that the gut microbiota was causally involved in synovitis and tenosynovitis and identified specific bacterial taxa that affect synovitis and tenosynovitis, which provide new insights into the pathogenesis underlying the development of synovitis and tenosynovitis mediated by gut microbiota.

Genetic liability to acne is associated with increased risk of inflammatory bowel disease: A Mendelian randomization study