A causal association between obesity and constipation: a two-sample bidirectional Mendelian randomization study and meta-analysis.

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.

BackgroundMyopia is the most prevalent refractive error and a growing global health concern that significantly affects visual function. Researchers have recently emphasized considerably on the influence of lifestyle on myopia incidence and development. This study investigates the relationship between leisure sedentary behaviors (LSB)/physical activity (PA)/sleep traits and myopia.MethodsLSB, PA, and sleep trait-associated genetic variants were used as instrument variables in a Mendelian randomization (MR) study to examine their causal effects on myopia. Summary genome-wide association studies (GWASs) statistical data for LSB and PA were obtained from UK Biobank, and the data of sleep traits was obtained from UK Biobank, UK Biobank and 23andMe, and FinnGen. We used summary statistics data for myopia from MRC IEU. The MR analyses was performed using the inverse variance-weighted (IVW), MR-Egger, weighted median, and MR Pleiotropy RESidual Sum and Outlier methods.ResultsComputer use was genetically predicted to increase the myopia risk [IVW odds ratio (OR) = 1.057; 95% confidence interval (CI), 1.038–1.078; P = 7.04 × 10− 9]. The self-reported moderate-to-vigorous physical activity (MVPA) (IVW OR = 0.962; 95% CI, 0.932–0.993; P = 1.57 × 10− 2) and television watching (IVW OR = 0.973; 95% CI, 0.961–0.985, P = 1.93 × 10− 5) were significantly associated with a lower myopia risk. However, genetically predicted sleep traits or accelerometer-measured physical activity had no significant associations with myopia.ConclusionOur results indicated that computer use is a risk factor for myopia, whereas television watching and MVPA may protect against myopia. These findings shed new light on possible strategies for reducing the prevalence of myopia.

The precise association between green tea intake and gastrointestinal disorders remains controversial. This study aimed to investigate the potential causal association between green tea intake and gastrointestinal disorders through a two-sample Mendelian randomization (MR) study. Utilizing publicly accessible data from genome-wide association studies (GWAS), we identified SNPs strongly linked with the study variables from multiple large databases to serve as instrumental variables (IVs). MR analyses were executed utilizing the inverse variance weighting (IVW) method, with the resultant effect estimates serving as the primary outcome measure. In addition, a multivariate MR design was performed to adjust for smoking and alcohol consumption. To ensure the robustness of our findings, a series of sensitivity analyses were conducted to assess reliability. Univariable MR analysis revealed suggestive associations between green tea intake and gastroesophageal reflux (OR = 0.9950, 95% CI 0.9900-1.0000, p IVW = 0.047), diverticulosis (OR = 0.9998, 95% CI 0.9996-1.0000, p IVW = 0.030), Crohn's disease (OR = 1.0001, 95% CI 1.0000-1.0002, p IVW = 0.019), and cholangitis was observed (OR = 1.0440, 95% CI 1.0100-1.0790, p IVW = 0.011). Multivariate MR analysis indicated after controlling for potential confounders, greater green tea consumption was suggestively associated with the decreased risk of oesophagitis (OR = 0.9667, 95% CI: 0.9405-0.9936, p IVW = 0.016) and gastric cancer (OR = 0.9810, 95% CI: 0.9628-0.9996, p IVW = 0.046). Nevertheless, multivariate MR analysis also showed that greater green tea consumption was suggestively associated with the increased risk of Crohn's disease (OR = 1.0001, 95% CI: 1.0000-1.0002, p IVW = 0.007). Sensitivity analyses confirmed that these results were reliable. Our study provides suggestive evidence that genetically predicted green tea intake is causally associated with the risk of oesophagitis, gastric cancer and Crohn's disease, but a larger GWAS database is needed for validation.

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.

Observational studies have found that obesity is associated with the development of non-suppurative otitis media (NSOM), but the causality and pathogenesis are unclear. This study aimed to investigate the association between obesity, lipid metabolism, and NSOM at the genetic level. We performed a bidirectional two-sample Mendelian randomization (MR) study to examine the causal relationship between obesity, lipid metabolism-related factors, and NSOM by using the datasets obtained from the IEU Open genome-wide association studies (GWAS) Project. Furthermore, a multivariate MR (MVMR) analysis on lipid indicators was conducted to validate the results. We then used obesity or body mass index (BMI) as the exposure and NSOM as the outcome to search for possible mediators in lipids and adipokines. Using NSOM as the outcome, we found nine positive exposure results related to obesity and lipid metabolism. Among them, obesity, BMI, body fat percentage, waist circumference, hip circumference, and resistin were risk factors, while apolipoprotein A1 (apoA1), high-density lipoprotein cholesterol (HDL-C), and nerve growth factor (NGF) were protective factors. Then, we used the obesity and lipid metabolism-related factors as outcomes and NSOM as the exposure to perform the MR analysis, which failed to obtain positive results. In the MVMR analysis, we found that HDL cholesterol and apoA1 remained causally associated with NSOM after correction for other potential confounders. Simultaneously, when obesity or BMI was used as the exposure and NSOM as the outcome, HDL cholesterol or apoA1 served as mediators through a two-step MR analysis. The MR analysis for mediation, obesity, and BMI reduced the production of HDL or apoA1, which served as protective factors affecting the development of NSOM. At the genetic level, obesity and adiposity may promote the development of NSOM, while NSOM has no effect on obesity and adiposity. Obesity can also encourage the progress of NSOM by reducing HDL cholesterol/apoA1. Resistin may be a potential risk factor for NSOM, whereas NGF may be a potential protective factor.

Background: Adiposity is closely related to osteoarthritis, but the causal effects of different types of adiposity on osteoarthritis are indistinct. This study conducted a Mendelian Randomization (MR) analysis for the causal effects of general adiposity and abdominal adiposity on knee osteoarthritis (KOA) and hip osteoarthritis (HOA). Methods: The general adiposity was assessed by body mass index (BMI), while the abdominal adiposity was evaluated with waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR). The data used in this two-sample MR analysis originated from genome-wide association studies (GWAS). Significant (p < 5 × 10−8) and independent (r2 < 0.01) single-nucleotide polymorphisms were selected as instrumental variables for the MR analysis. Subsequently, this study used the inverse variance weighted, weighted median, and other methods for the causal inference, and the results were presented as odds ratios (OR). Moreover, sensitivity analyses were conducted to assess the stability and reliability of the results. Results: The MR results revealed positive causal effects of BMI on KOA (OR: 1.694; 95% CI: from 1.492 to 1.923; p = 3.96 × 10−16) and HOA (OR: 1.412; 95% CI: from 1.196 to 1.666; p = 4.58 × 10−5). Additionally, WC and HC both positively and causally related to KOA (WC: OR: 1.827; 95% CI: from 1.564 to 2.134; p = 2.68 × 10−14; HC: OR: 1.610; 95% CI: from 1.357 to 1.912; p = 5.03 × 10−8) and HOA (WC: OR: 1.491; 95% CI: from 1.254 to 1.772; p = 5.85 × 10−6; HC: OR: 1.439; 95% CI: from 1.205 to 1.719; p = 5.82 × 10−5). However, no causal relationship existed between WHR and obesity. These results were robust according to the sensitivity analyses. Conclusions: This study indicated that both general and abdominal obesity had positive causal effects on knee osteoarthritis and hip osteoarthritis.

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.

Previous observational studies have suggested a potential link between depression and cervical spondylosis (CS). While it is known that depression and CS can coexist, the specific relationship between them is not fully understood. We hypothesize that there may be connections between the two conditions, but the independent causal relationship of depression as a risk factor for CS, remains uncertain. This particular study has important implications for the future clinical treatment of depression and cervical spondylosis because Mendelian randomization has not been widely used in this field. We obtained valuable results through big data analysis and have guiding significance for future research. We conducted a two-sample Mendelian randomization (MR) study using data from genome-wide association studies to investigate the causal relationship between depression and CS in individuals of European ancestry. Additionally, we examined the impact of CS on susceptibility to depression using large population-level genetic data (number of depression SNPs: 9,761,853; number of CS SNPs: 9,851,867). The primary approach for data analysis was the inverse-variance weighted (IVW) method to estimate potential causal effects. Furthermore, we performed sensitivity analyses utilizing methods such as Manhattan plot (CMplot), linkage disequilibrium (LD), F-filtering, removal of phenoscanner, MR-Egger, weighted median, MR-PRESSO simple mode weighted mode MR pleiotropy test MR heterogeneity assessment leave-one-out analysis to ensure result robustness. Our findings indicated that an elevated likelihood of CS was linked to depression [IVW odds ratio (OR): 1.322, 95% confidence interval (CI): 1.205-1.441, P=0.01243]. There was reciprocal evidence of causation, with the genetic predisposition to depression significantly heightening susceptibility to CS [IVW odds ratio (OR): 1.426, 95% confidence interval (CI): 1.236-1.651, P=0.01775]. This investigation provides genetic support for a bidirectional causal association between depression and CS. Specifically, individuals with depression are at greater risk of developing CS. Addressing depression may serve as an effective approach in mitigating or preventing the burden of CS and vice versa.

The relationship between cataracts and Alzheimer's disease (AD) has been reported in recent observational studies. However, it is still unclear whether a causal effect of cataracts on AD or reverse causation exists. To explore the association between cataracts and AD genetically, we performed a bidirectional two-sample Mendelian randomization study. We obtained genetic instrumental variables related to cataracts and AD from recently published genome-wide association studies (GWASs). SNP-outcome associations for AD were obtained from a GWAS with 111,326 cases and 677,663 controls. SNP-outcome associations for cataracts were drawn from two sources: a GWAS with 67,844 cases and 517,399 controls and the FinnGen consortium (42,843 cases and 262,698 controls). Inverse variance weighted (IVW) was used as the primary method for Mendelian randomization (MR) analyses. No genetic evidence suggested that cataracts were associated with the risk of AD (IVW odds ratio =1.04, 95% confidence interval: 0.98-1.10, p=0.199). In contrast, an effect of genetically determined AD on a decreased risk of cataract was observed with suggestive evidence (IVW odds ratio =0.96, 95% confidence interval: 0.93-0.99, p=0.004). However, this result might be distorted by survival bias. Genetically determined cataracts were not related to AD, as demonstrated by our study. In contrast, there was suggestive evidence that AD might prevent cataract development, but there might be potential survival bias. To define the exact association between the two diseases, more prospective research and studies on the pathogenesis are needed.

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.

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.

BackgroundHepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths globally, and infection with the hepatitis B virus (HBV) is one of the major risk factors for the development of HCC. However, the definitive causal relationship between HBV infection and liver cancer has not been clearly established. In this study, we employed Mendelian randomization (MR) to estimate the causal effect of HBV infection on hepatocellular carcinoma by using genetic variations as instrumental variables.MethodsWe obtained summary statistics from genome-wide association studies (GWAS) related to hepatocellular carcinoma and hepatitis B. We conducted Mendelian randomization analysis, using genetic variants associated with HBV infection as instrumental variables to estimate the risk of liver cancer. In our MR analysis, we employed the inverse variance weighted (IVW) method and performed sensitivity analyses and robustness assessments using MR Egger regression and the weighted median method.ResultsOur MR analysis revealed a significant causal association, indicating that HBV infection leads to liver cancer (IVW odds ratio = 2.233, 95% confidence interval = 1.844–2.703, P < 0.001). Sensitivity analyses using MR Egger regression and the weighted median method confirmed the causal effect, with no evidence of horizontal pleiotropy. Similar results were observed across different MR methods, supporting a strong causal association between HBV and liver cancer risk. Specifically, we observed a causal effect of CD25 on the IgD-CD38- B cell subset (β = 1.15, 95% CI 1.07–1.24, P = 3.0 × 10^− 4). Additionally, five immune phenotypes were significantly associated with HCC risk: HLA DR + + monocytes.ConclusionThis MR study demonstrates a causal relationship between HBV infection and liver cancer risk, highlighting HBV as a potential causal factor in the development of hepatocellular carcinoma.

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.

Several studies have explored the relationship between intracranial aneurysms and psychiatric disorders; nevertheless, the causal connection remains ambiguous. This study aimed to evaluate the causal link between intracranial aneurysms and specific psychiatric disorders. A two-sample Mendelian randomization (MR) analysis was conducted utilizing aggregated genome-wide association study (GWAS) data from the International Stroke Genetics Association for Intracranial Aneurysms (IAs), unruptured Intracranial Aneurysm (uIA), and aneurysmal Subarachnoid Hemorrhage (aSAH). Psychiatric disorder data, encompassing Schizophrenia (SCZ), Bipolar Disorder (BD), and Panic Disorder (PD), were sourced from the Psychiatric Genomics Consortium (PGC), while Cognitive Impairment (CI) data, comprising Cognitive Function (CF) and Cognitive Performance (CP), were obtained from IEU OpenGWAS publications. Causal effects were evaluated using inverse variance weighted (IVW), MR-Egger, and weighted median methods, with the robustness of findings assessed via sensitivity analyses employing diverse methodological approaches. Our MR analysis indicated no discernible causal link between intracranial aneurysm (IA) and an elevated susceptibility to psychiatric disorders. However, among individuals with genetically predisposed unruptured intracranial aneurysms (uIA), there was a modest reduction in the risk of SCZ (IVW odds ratio [OR] = 0.95, 95% confidence interval [CI] 0.92-0.98, p = 0.0002). Similarly, IAs also exhibited a moderate reduction in SCZ risk (OR = 0.92, 95% CI 0.86-0.99, p = 0.02). Nevertheless, limited evidence was found to support a causal association between intracranial aneurysms and the risk of the other three psychiatric disorders. Our findings furnish compelling evidence suggesting a causal influence of intracranial aneurysms on psychiatric disorders, specifically, both IAs and uIA exhibit a negative causal association with SCZ.

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.