Causal relationship between green tea intake and gastrointestinal disorders: a two-sample Mendelian randomization study.

Observational studies suggest a potential link between obesity and constipation, but existing results are conflicting. Therefore, we conducted a Mendelian randomization (MR) study and meta-analysis to assess the causal relationship between obesity and the risk of constipation. In this study, independent genetic variants closely related to constipation were acquired from a genome-wide association study (GWAS) to analyze the relationship between genetically predisposed obesity and the risk of constipation. Waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), and body mass index (BMI) were collected from the GWAS. Then, the causal relationship between constipation and obesity was explored using a two-sample MR study in both directions. The robustness of the results was evaluated using sensitivity analysis. Furthermore, a systemic review and meta-analysis were performed to calculate relative risks (RRs) with corresponding 95% confidence intervals (95% CIs). Subgroup analyses stratified by age and obesity degree were completed. To evaluate whether the current studies were affected by unmeasured confounders, E-values of each study were determined. In MR analysis, the incidence of constipation increased with the increase in BMI [inverse variance-weighted (IVW) odds ratio (OR) = 1.138 (1.029, 1.260), p = 0.012]. In addition, constipation was impacted by WC [IVW OR = 1.220 (1.061, 1.402), p = 0.005]. However, there was no evidence that WHR [IVW OR = 1.833 (0.826, 4.065), p = 0.136] or HC [IVW OR = 0.949, (0.836, 1.077), p = 0.415] has a causal effect on constipation. In reverse MR analysis, there was no evidence supporting the causality between constipation and obesity [BMI IVW OR = 1.010 (0.998, 1.022), p = 0.089; WHR IVW OR = 1.000 (0.946, 1.057), p = 0.994; WC IVW OR = 1.008 (0.995, 1.022), p = 0.217; HC IVW OR = 0.996 (0.982, 1.011), p = 0.626]. In the meta-analysis, 14 eligible articles were included, involving 43,488 subjects. According to the results of the meta-analysis, the risk of obesity and overweight significantly increased the risk of constipation [RR = 1.145 (0.952, 1.376)]. This was consistent with the MR analysis results. Moreover, overweight and obesity were significantly related to a higher constipation risk among children [overweight RR = 1.112 (0.943, 1.312); obesity RR = 1.407 (1.282, 1.544)]. Additionally, overweight in adults could decrease the risk of constipation [RR = 0.940 (0.827, 1.068)]. Nevertheless, no significant association was observed between obesity in adults and the risk of constipation [RR = 1.000 (0.768, 1.303)]. Sensitivity analysis revealed the robustness of our findings. In this combined MR study and meta-analysis, obesity is associated with an increased risk of constipation. The MR analysis demonstrates the causal relationship between genetically predisposed obesity and the risk of constipation. More research is required to investigate the potential correlation between obesity and the risk of constipation and associated mechanisms.

The correlation between obesity and primary open-angle glaucoma (POAG) has not yet been fully established. The aim of this study was to investigate the causal relationship between obesity and POAG by a two-sample Mendelian randomization (MR) study. In this study, body mass index (BMI), an index to evaluate general obesity, and waist and hip circumference, indices to evaluate abdominal obesity, were selected as exposures in MR analysis. Single-nucleotide polymorphisms (SNPs) were chosen as instrumental variables (IVs). Summary data from genome-wide association studies (GWASs) based on a European ancestry by Locke et al., with regard to BMI, and Shungin et al., with regard to waist and hip circumference, were used. Genetic predictors of POAG were obtained from public GWAS summary data. To assess the causal effect of obesity on POAG, the inverse variance-weighted (IVW) method was used as the primary method, and other methods, such as MR–Egger, weighted median, simple mode, and weighted mode, were also used as complementary analyses. Finally, we performed Cochran’s Q statistic to assess heterogeneity, and sensitivity analysis was performed to evaluate the reliability and stability of the MR results. MR analysis showed that BMI has a positive effect on the risk of POAG, with 1 standard deviation (SD) increase in BMI; the risk of POAG increases by approximately 90.9% [OR = 1.909; 95% CI= (1.225, 2.975); p = 0.0042)] (analyzed by IVW); there were no heterogeneity and pleiotropy in the result; and waist circumference also had a positive effect on the risk of POAG [OR = 2.319; 95% CI= (1.071, 5.018); p = 0.033)] analyzed by weighted median. As hip circumference increases, with 1 SD increase in hip circumference, the risk of POAG increases by approximately 119% [OR = 2.199; 95% CI= (1.306, 3.703); p = 0.00305)] estimated by IVW, there were not heterogeneity and pleiotropy as for the result. Our study for the first time confirms that obesity might increase the risk of POAG using two-sample MR analysis. These results might provide guidance on the prevention and treatment of POAG.

Previous observational studies have shown that green tea consumption is associated with a reduced incidence of digestive system cancers (DSCs). However, the observed association could be due to confounding factors. Therefore, we used a two-sample Mendelian randomization (MR) approach to assess the causal effect of green tea intake on the risk of five common DSCs. Independent genetic variants strongly associated with green tea consumption in European and East Asian populations were selected as instrumental variables in genome-wide association studies involving up to 64,949 European individuals and 152,653 East Asian individuals, respectively. The associations between genetic variants and DSCs were extracted from the FinnGen study and the Japan Biobank. The primary analysis was performed using random-effects inverse variance weighting (IVW). Other MR analyses, including weighted mode-based estimate, weighted-median, MR-Egger regression, Mendelian Randomization-Pleiotropy Residual Sum and Outlier (MR-PRESSO) analysis, were used for sensitivity analyses. In addition, a multivariate MR design was performed to adjust for smoking and alcohol consumption. The IVW results showed no causal relationship between tea intake and DSCs risk in European population (esophagus cancer: odds ratio (OR) = 1.044, 95% confidence interval (CI) 0.992-1.099, p = 0.096; stomach cancer: OR = 0.988, 95% CI 0.963-1.014, p = 0.368; colorectal cancer: OR = 1.003, 95% CI 0.992-1.015, p = 0.588; liver cancer: OR = 0.996, 95% CI 0.960-1.032, p = 0.808; pancreatic cancer: OR = 0.990, 95% CI 0.965-1.015, p = 0.432). The MR-Egger regression, MR-PRESSO analysis and other methods also confirmed the reliability of the conclusion. Similarly, no significant association was found between green tea consumption and the incidence of DSCs among East Asians. This relationship is not significant even after adjusting for smoking and alcohol consumption (P > 0.05). Our study provides evidence that genetically predicted green tea intake is not causally associated with the development of DSCs in the European and East Asian population.

In order to elucidate the correlation and its pathways between liver diseases and vascular dementia (VaD). We performed two-sample Mendelian randomization (MR) study. We performed a two-sample MR study using summary-level genome-wide association study (GWAS) data for 4 liver diseases (nonalcoholic fatty liver disease [NAFLD], nonalcoholic steatohepatitis [NASH], alcoholic liver disease [ALD], and fibrosis/cirrhosis [FACOL]) and VaD. Inverse variance weighted (IVW) served as the primary analysis, complemented by a suite of sensitivity analyses (Cochran Q test, MR-Egger regression and MR pleiotropy residual sum and outlier [MR-PRESSO]). Furthermore, multivariable MR (MVMR) was conducted to adjust for key metabolic traits, including fasting glucose and triglycerides. The IVW analysis indicated that no significant causal associations were found between any of the 4 liver diseases and the risk of VaD. Sensitivity analyses indicated that the results for NAFLD and FACOL may be affected by heterogeneity, and NAFLD may also be affected by horizontal pleiotropy. Crucially, after adjusting for genetic liability to elevated triglycerides or fasting glucose in MVMR analyses, the initially null association for NAFLD became significant, revealing a protective effect against VaD. Associations for other liver diseases remained null after adjustment. This MR study found no direct causal link between liver diseases and VaD. However, adjusting for glucose or triglycerides revealed a potential protective effect of NAFLD, suggesting metabolic factors may confound the association. Further research is warranted to disentangle the complex relationship between these health conditions.

BackgroundAlthough anxiety disorders are one of the most prevalent mental disorders, their underlying biological mechanisms have not yet been fully elucidated. In recent years, genetically determined metabolites (GDMs) have been used to reveal the biological mechanisms of mental disorders. However, this strategy has not been applied to anxiety disorders. Herein, we explored the causality of GDMs on anxiety disorders through Mendelian randomization study, with the overarching goal of unraveling the biological mechanisms.MethodsA two-sample Mendelian randomization (MR) analysis was implemented to assess the causality of GDMs on anxiety disorders. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas four different GWAS datasets of anxiety disorders were the outcomes. Notably, all datasets were acquired from publicly available databases. A genetic instrumental variable (IV) was used to explore the causality between the metabolite and anxiety disorders for each metabolite. The MR Steiger filtering method was implemented to examine the causality between metabolites and anxiety disorders. The standard inverse variance weighted (IVW) method was first used for the causality analysis, followed by three additional MR methods (the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods) for sensitivity analyses in MR analysis. MR-Egger intercept, and Cochran’s Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. Bonferroni correction was used to determine the causative association features (P < 1.03 × 10–4). Furthermore, metabolic pathways analysis was performed using the web-based MetaboAnalyst 5.0 software. All statistical analysis were performed in R software. The STROBE-MR checklist for the reporting of MR studies was used in this study.ResultsIn MR analysis, 85 significant causative relationship GDMs were identified. Among them, 11 metabolites were overlapped in the four different datasets of anxiety disorders. Bonferroni correction showing1-linoleoylglycerophosphoethanolamine (ORfixed-effect IVW = 1.04; 95% CI 1.021–1.06; Pfixed-effect IVW = 4.3 × 10–5) was the most reliable causal metabolite. Our results were robust even without a single SNP because of a “leave-one-out” analysis. The MR-Egger intercept test indicated that genetic pleiotropy had no effect on the results (intercept = − 0.0013, SE = 0.0006, P = 0.06). No heterogeneity was detected by Cochran’s Q test (MR-Egger. Q = 7.68, P = 0.742; IVW. Q = 12.12, P = 0.436). A directionality test conducted by MR Steiger confirmed our estimation of potential causal direction (P < 0.001). In addition, two significant pathways, the “primary bile acid biosynthesis” pathway (P = 0.008) and the “valine, leucine, and isoleucine biosynthesis” pathway (P = 0.03), were identified through metabolic pathway analysis.ConclusionThis study provides new insights into the causal effects of GDMs on anxiety disorders by integrating genomics and metabolomics. The metabolites that drive anxiety disorders may be suited to serve as biomarkers and also will help to unravel the biological mechanisms of anxiety disorders.

Previous studies have reported that the inappropriate use of allopurinol may increase the risk of cerebrovascular accidents, but some studies have also confirmed that allopurinol is a protective factor against stroke. To clarify whether there is a relevant causal relationship between allopurinol and cerebral infarction, we conducted a two-sample Mendelian randomization (MR) study. Data on single nucleotide polymorphisms (SNPs) associated with allopurinol and genome-wide association studies of cerebral infarction were obtained from the genome-wide association study (GWAS) web site. Five basic MR analyses were performed using MR-Egger regression, weighted median (WM1), inverse variance weighting (IVW), weighted mode (WM2), and simple mode. Sensitivity analysis was subsequently performed to detect horizontal pleiotropy, heterogeneity, and potential outliers. The final analysis results were mainly based on the IVW estimates. A total of 10 SNPs were used as instrumental variables (IVs). MR analysis [(IVW: odds ratio (OR) = 1.053, 95% confidence interval (CI): 1.019-1.088, P = 0.002), (WM1: OR = 1.053, 95% CI: 1.009-1.098, P = 0.017), (WM2: OR = 1.050, 95% CI: 1.008-1.095, P = 0.044), (MR Egger: Q = 4.285, P = 0.830)] showed a positive causal association between allopurinol and the risk of cerebral infarction. Sensitivity analysis such as horizontal pleiotropy and heterogeneity increased the reliability of this result. The results of this study provide direct evidence that there is a causal relationship between allopurinol and cerebral infarction and that allopurinol may increase the risk of cerebral infarction.

This study aimed to explore the causal association between inflammatory bowel disease (IBD) and the risk of type 2 diabetes (T2D) based on a two-sample Mendelian randomization (MR) study. Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published two genome-wide association studies (GWAS) including SNPs related to IBD, UC, or CD in European participants (n = 71,997) and East Asian participants (n = 16,805). Two GWAS including SNPs associated with T2D included 655,666 Europeans and 433,540 East Asians. A series of screening processes were performed to select qualified instrumental SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the MR-Egger regression, and the weighted median to estimate the causal effects of IBD, ulcerative colitis (UC) or Crohn' disease (CD) on T2D. Cochran's Q test was conducted to evaluate the statistical heterogeneity between SNPs in the IVW method. The leave-one-out analysis was employed to assess whether the results were caused by any single SNP associated with IBD, UC, or CD. Odds ratio (OR) and 95% confidence interval (CI) were calculated. The IVW results demonstrated that IBD could increase the risk of T2D in the European population (OR = 1.0230, 95%CI: 1.0073-1.0390). UC was positively associated with the risk of T2D according to the weighted median (OR = 1.0274, 95%CI: 1.0009-1.0546) and IVW (OR = 1.0244, 95%CI: 1.0071-1.0421) results in the European population. The IVW results indicated that the CD was positively associated with the risk of T2D in the European population (OR = 1.0187, 95%CI: 1.0045-1.0330). In the East Asian population, there are no associations between the IBD, UC, or CD and the risk of T2D (all P > 0.05). MVMR results revealed that the causal effect UC on T2D was still statistically significant after including body mass index (BMI) or low-density lipoprotein (LDL). IBD, UC, or CD had causal effects on the risk of T2D in the European population, which might provide evidence for the prevention of T2D in patients with IBD, UC, or CD.

BackgroundRecent research has established the correlation between gut microbiota and periodontitis via oral-gut axis. Intestinal dysbiosis may play a pivotal bridging role in extra-oral inflammatory comorbidities caused by periodontitis. However, it is unclear whether the link is merely correlative or orchestrated by causative mechanistic interactions. This two-sample Mendelian randomization (MR) study was performed to evaluate the potential bidirectional causal relationships between gut microbiota and periodontitis.Materials and MethodsA two-sample MR analysis was performed using summary statistics from genome-wide association studies (GWAS) for gut microbiota (n = 18,340) and periodontitis (cases = 12,251; controls = 22,845). The inverse-variance weighted (IVW) method was used for the primary analysis, and we employed sensitivity analyses to assess the robustness of the main results. The PhenoScanner database was then searched for pleiotropy SNPs associated with potential confounders. In order to identify the possibly influential SNPs, we further conducted the leave-one-out analysis. Finally, a reverse MR analysis was performed to evaluate the possibility of links between periodontitis and genetically predicted gut microbiota alternation.Results2,699 single nucleotide polymorphisms (SNPs) associated with 196 microbiota genera were selected as instrumental variables (IVs). IVW method suggested that order Enterobacteriales (OR: 1.35, 95% CI 1.10–1.66), family Bacteroidales S24.7group (OR: 1.22, 95% CI 1.05–1.41), genus Lachnospiraceae UCG008 (OR: 1.16, 95% CI 1.03–1.31), genus Prevotella 7 (OR: 1.11, 95% CI 1.01–1.23), and order Pasteurellales (OR: 1.12, 95% CI 1.00–1.26) may be associated with a higher risk of periodontitis, while genus Ruminiclostridium 6 may be linked to a lower risk (OR: 0.82, 95% CI 0.70–0.95). The sensitivity and heterogeneity analyses yielded no indication of horizontal pleiotropy or heterogeneity. Only the association between order Enterobacteriales and the likelihood of periodontitis remained consistent across all alternative MR approaches. In the reverse MR analysis, four microbiota genera were genetically predicted to be down-regulated in periodontitis, whereas two were predicted to be up-regulated.ConclusionsThe present MR analysis demonstrated the potential bidirectional causal relationships between gut microbiota and periodontitis. Our research provided fresh insights for the prevention and management of periodontitis. Future research is required to support the finding of our current study.

The link between salt intake and the risk of gastric cancer remains uncertain, and a causal relationship has not been established. Therefore, clarifying the causal effect of salt intake on the risk of gastric cancer using reliable causal inference methods is necessary. The aim of this study was to assess the causal association between salt intake and cancer by integrating summary-level genome-wide association study (GWAS) data. Two-sample Mendelian randomization (MR) analyses were performed using summary statistics from a GWAS. Inverse-variance weighted (IVW) regression, Mendelian randomization-Egger (MR-Egger) regression, and weighted median analyses were used to evaluate the causal relationship between salt intake and gastric cancer. Moreover, Mendelian Randomization Pleiotropy RESidual Sum of Squares and Outliers and MR-Egger analyses were used to evaluate the level of multipotency, and "leave-one-out" sensitivity analysis was assessed. The IVW method estimate indicated that salt intake was not correlated with gastric cancer incidence. The IVW (β = 0.1008, standard error [SE] = 0.1510, odds ratio [OR] = 1.1061, 95% confidence interval [CI], 0.82-1.48, P = .5042), MR-Egger regression (β = 0.059, SE = 0.5318, OR = 1.0612, 95% CI, 0.37-3.01, P = .9111), and weighted median (β = 0.2639, SE = 0.2298, OR = 1.3020, 95% CI, 0.82-2.04, P = .2508) analyses revealed no causal relationship between salt intake and gastric cancer risk (P > .05). In addition, the funnel plot and MR-Egger analysis (P = .6694 > .05) did not indicate horizontal pleiotropy or heterogeneity. GWAS data from public databases were used in this study, and the causal relationship between salt intake and gastric cancer risk was analyzed via a two-sample MR method. The results revealed no genetic causal relationship between salt intake and gastric cancer.

ObjectivePrevious studies have shown that human immunodeficiency virus (HIV) infection is associated with hypertension; however, the results of these studies are affected by a variety of confounding factors. There is no definite evidence to prove a causal relationship between these two factors. This study aimed to investigate the causal relationship between HIV infection and hypertension.MethodsA two-sample Mendelian randomization (MR) study was conducted using genome-wide association study (GWAS) statistics published online. The data were collected mainly from the OpenGWAS and FinnGen databases. The HIV database contained 357 HIV patients and 218,435 control patients; the hypertension database contained 54,358 patients and 408,652 control patients; and the blood pressure database contained 436,424 samples. Random effect inverse variance weighting (IVW) was used as the main analysis method, weighted median and Mr-Egger analysis methods were used to ensure the accuracy of the results, and Cochran’s Q test and Mr-Egger regression methods were used to detect heterogeneity and correct multiple horizontal effects. Finally, the leave-one-out method was used to analyse the reliability of the test results. In order to further verify the research results, different databases were used and the same statistical method was used for a replication analysis. In order to prevent false positive results caused by multiple tests, Bonferroni correction is used to correct the statistical results.ResultsAfter screening, a total of 9 SNPs (single-nucleotide polymorphisms) were selected as the instrumental variable (IV) used in this study. The IVW MR analysis results showed a causal relationship between HIV infection and the risk of hypertension (IVW: OR = 1.001, P = 0.03). When systolic blood pressure was the outcome, the IVW method results were positive (OR = 1.004, P = 0.01280), and when diastolic blood pressure was the outcome, the weighted median method results were positive (OR = 1.004, P = 0.04570). According to the sensitivity analysis, the results of this study were unlikely to be affected by heterogeneity and horizontal pleiotropy. The leave-one-out analysis showed that the results of this study did not change significantly with the elimination of a single SNP. In replication analysis, when diastolic blood pressure was taken as the outcome, the weighted median method was positive (OR = 1.042, P = 0.037). Sensitivity analysis shows that there is heterogeneity, but there is no horizontal pleiotropy. The leave-one-out analysis showed that the results of this study did not change significantly with the elimination of a single SNP.ConclusionAs the first exploratory study using MR method to study the causal relationship between HIV infection and hypertension and blood pressure, this study found that HIV infection may increase systolic and diastolic blood pressure and increase the risk of hypertension. PLWH, as a high-risk group of cardiovascular and cerebrovascular diseases, should prevent the occurrence of hypertension in order to further improve their quality of life. However, this study also has some limitations. The results of the relationship between HIV infection and hypertension and blood pressure may be affected by the lack of statistical efficacy. In order to further confirm this conclusion, more large-scale RCT or genetic studies should be carried out.

The development of ankylosing spondylitis (AS) is closely related to autoimmune system dysfunction. Type 1 diabetes mellitus (T1DM) is an autoimmune disease that is a risk factor for many diseases. This study aimed to investigate the causal relationship between T1DM mellitus and AS genetically. A genome-wide association study (GWAS) of causal relationships between exposure (T1DM) and outcome (AS) was performed using summary data from the GWAS database. We conducted a two-sample Mendelian randomization (MR) study of these two diseases. Inverse variance weighting (IVW) was used as the primary analysis method, with MR Egger, weighted median, and weighted mode used as supplementary methods. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept, MR-Pleiotropy RESidual Sum and outlier methods, leave-one-out analysis, and funnel plots. A total of 11 single nucleotide polymorphisms (SNPs)were identified for instrumental variables(IVs) for MR analysis.IVW found that T1DM was causally associated with AS ((IVW: OR = 1.0006 (95% CI 1.0001, 1.0011), p = 0.0057; MR-Egger: OR = 1.0003 (95% CI 0.9995, 1.0012), p = 0.4147; weighted median: OR = 1.0006 (95% CI 1.0003, 1.0008), p = 0.0001; weighted mode: OR = 1.0007 (95% CI 1.0005, 1.0009), p = 0.0001). No horizontal pleiotropy was found for the MR-Egger intercept, and leave -one-out analysis found that the results remained stable after the removal of individual SNPs. The results of the two-sample MR analysis supported a causal relationship between T1DM and AS risk.

BackgroundObservational studies have suggested that hearing impairment (HI) was associated with the risk of falls, but it remains unclear if this association is of causal nature.MethodsA two-sample Mendelian randomization (MR) study was conducted to investigate the causal association between HI and falls in individuals of European descent. Summary data on the association of single nucleotide polymorphisms (SNPs) with HI were obtained from the hitherto largest genome-wide association study (GWAS) (n = 323,978), and statistics on the association of SNPs with falls were extracted from another recently published GWAS (n = 461,725). MR Steiger filtering method was applied to determine the causal direction between HI and falls. Inverse-variance weighted (IVW) method was employed as the main approach to analyze the causal association between HI and falls, whereas weighted median, simple mode, weighted mode, and MR-Egger methods were used as complementary analyses. The MR-Egger intercept test, the MR-PRESSO test, and Cochran's Q statistic were performed to detect the potential directional pleiotropy and heterogeneity, respectively. The odds ratio (OR) with 95% confidence intervals (CIs) was used to evaluate this association.ResultsA total of 18 SNPs were identified as valid instrumental variables in our two-sample MR analysis. The positive causality between HI and risk of falls was indicated by IVW [OR 1.108 (95% CI 1.028, 1.194), p = 0.007]. The sensitivity analyses yielded comparable results. The “leave-one-out” analysis proved that lack of a single SNP did not affect the robustness of our results. The MR-Egger intercept test exhibited that genetic pleiotropy did not bias the results [intercept = −2.4E−04, SE = 0.001, p = 0.832]. Cochran's Q test revealed no heterogeneity.ConclusionOur MR study revealed a causal association between genetically predicted HI and falls. These results provide further evidence supporting the need to effectively manage HI to minimize fall risks and improve quality of life.

Background: In observational studies, the self-reported walking pace has been associated with the risk of cardiovascular diseases (CVD). However, whether those associations indicate causal links remains unclear. We performed two-sample Mendelian randomization (MR) analyses to evaluate the causal effect of walking pace on several CVD outcomes, including atrial fibrillation (AF), heart failure (HF), any stroke, ischemic stroke (IS), and IS subtypes. Methods: Genetic variants associated with self-reported walking pace were selected as instrumental variables (IVs) from the latest genome-wide association studies (GWAS). Summary-level data for outcomes were obtained from the corresponding GWAS and the FinnGen consortium. The random-effects inverse variance weighted (IVW) method was used as the main MR analysis, supplemented by replication analyses using data from the FinnGen. To explore the effect of pleiotropy due to adiposity-related traits, we further conducted MR analyses by excluding the adiposity-related IVs and regression-based multivariable MR adjusting for body mass index (BMI). Results: The MR results indicated significant inverse associations of self-reported walking pace with risks of AF [odds ratio (OR), 0.577; 95% confidence interval (CI), 0.442, 0.755; p = 5.87 × 10−5], HF (OR, 0.307; 95% CI, 0.229, 0.413; p = 5.31 × 10−15), any stroke (OR, 0.540; 95% CI, 0.388, 0.752; p = 2.63 × 10−4) and IS (OR, 0.604; 95% CI, 0.427, 0.853; p = 0.004) and suggestive inverse association of self-reported walking pace with cardioembolic stroke (CES) (OR, 0.492; 95% CI, 0.259, 0.934; p = 0.030). Similar results were replicated in the FinnGen consortium and persisted in the meta-analysis. However, there was no causality between walking pace and large artery stroke (OR, 0.676; 95% CI, 0.319, 1.434; p = 0.308) or small vessel stroke (OR, 0.603; 95% CI, 0.270, 1.349; p = 0.218). When excluding adiposity-related IVs and adjusting for BMI, the associations for HF and any stroke did not change substantially, whereas the associations for AF, IS, and CES were weakened. Conclusion: Our findings suggested that genetically predicted increasing walking pace exerted beneficial effects on AF, HF, any stroke, IS, and CES. Adiposity might partially mediate the effect of walking pace on AF, IS, and CES.

BackgroundObservational studies have revealed that dried fruit intake may be associated with cancer incidence; however, confounding factors make the results prone to be disturbed. Therefore, we conducted a two-sample Mendelian randomization (MR) study to explore the causal relationship between dried fruit intake and 11 site-specific cancers.Materials and methodsForty-three single nucleoside polymers (SNPs) with robust genome-wide association study (GWAS) evidence, strongly correlated with dried fruit intake, were used as instrumental variables (IVs) in this study. The summary-level genetic datasets of site-specific cancers were obtained from the Oncoarray oral cavity and oropharyngeal cancer consortium, International Lung Cancer Consortium, Breast Cancer Association Consortium (BCAC), Ovarian Cancer Association Consortium, PanScan1, and GWAS of other scholars. We analyzed the causality between dried fruit intake and 11 site-specific cancers using the inverse-variance-weighted (IVW) and weighted median (WM) methods. For the results of the MR analysis, Cochran’s Q test was used to check for heterogeneity, and multiplicative random effects were used to evaluate the heterogeneity further. Gene pleiotropy was tested using MR-Egger regression and MR-PRESSO methods. In addition, the main results of this study were validated by using the summary statistical data from the FinnGen and UK Biobank databases, and adjusted body mass index (BMI), years of education, fresh fruit intake, and vitamin C using multivariable MR analysis to ensure the stability of the research results.ResultsThe evidence from IVW analyses showed that each increase of dried fruit intake by one standard deviation was statistically significantly associated with 82.68% decrease of oral cavity/pharyngeal cancer incidence risk (P = 0.0131), 67.01% decrease of lung cancer incidence risk (P = 0.0011), 77% decrease of squamous cell lung cancer incidence risk (P = 0.0026), 53.07% decrease of breast cancer incidence risk (P = 4.62 × 10–5), 39.72% decrease of ovarian cancer incidence risk (P = 0.0183), 97.26% decrease of pancreatic cancer incidence risk (P = 0.0280), 0.53% decrease of cervical cancer incidence risk (P = 0.0482); however, there was no significant effect on lung adenocarcinoma (P = 0.4343), endometrial cancer (P = 0.8742), thyroid cancer (P = 0.6352), prostate cancer (P = 0.5354), bladder cancer (P = 0.8996), and brain cancer (P = 0.8164). In the validation part of the study results, the causal relationship between dried fruit intake and lung cancer (P = 0.0043), squamous cell lung cancer (P = 0.0136), and breast cancer (P = 0.0192) was determined. After adjusting for the potential impact of confounders, the causal relationship between dried fruit intake and lung cancer (P = 0.0034), squamous cell lung cancer (P = 0.046), and breast cancer (P = 0.0001) remained. The sensitivity analysis showed that our results were stable and reliable.ConclusionThe intake of dried fruits may have a protective effect against some site-specific cancers. Therefore, health education and a reasonable adjustment of dietary proportions may help in the primary prevention of cancer.

BackgroundThe relationship between 25-hydroxyvitamin D (25(OH)D) levels and the risk of laryngeal cancer (LC) is unclear. This study aimed to explore the causal association between 25(OH)D levels and LC risk using the two-sample Mendelian randomization (MR) analysis.MethodsSingle-nucleotide polymorphisms for 25(OH)D levels and LC were extracted from published genome-wide association studies (GWAS) or the Medical Research Council Integrative Epidemiology Unit (MRC-IEU) Open GWAS project. Univariable MR and multivariable MR analyses were performed. Five MR methods including MR-Egger, weighted-median, inverse-variance weighted (IVW), simple mode, and weighted mode were applied.ResultsUnivariable MR analysis identified the fact that genetically predicted higher levels of 25(OH)D were associated with lower odds of LC [IVW: (odds ratio (OR) = 0.9993, 95% confidence interval (CI), 0.9987–0.9999; P = 0.019)]. Multivariable MR analyses suggested that genetically predicted higher levels of 25(OH)D were correlated with lower risk of LC after adjusting for pack-years of cigarette smoking (CS) [IVW: (OR = 0.9993, 95% CI, 0.9987–0.9998; P = 0.006)] or both pack-years of CS and weekly alcoholic drinks [IVW: (OR = 0.9993, 95% CI, 0.9988–0.9998; P = 0.011)], but this was not significant after adjusting only for weekly alcoholic drinks [IVW: (OR = 0.9995, 95% CI, 0.9989–1.0001; P = 0.077)].ConclusionsThis MR analyses supported a slight protective effect of higher levels of 25(OH)D on the risk of LC.