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Background: Growing evidence indicates a potential association between the gut microbiome and psoriasis. Nevertheless, the precise nature of these associations and whether they constitute causal relationships remain unclear., Methods: A rigorous bidirectional two-sample Mendelian randomization study was undertaken to establish a putative causal link between gut microbiota and psoriasis. We drew upon publicly available datasets containing summary statistics from GWAS to accomplish this. Utilizing various analytical techniques, including inverse variance weighting, MR-Egger, weighted median, weighted model, and MR-PRESSO, we sought to validate the putative causal association between gut microbiota and psoriasis. A reverse Mendelian randomization analysis was conducted to further investigate the relationship., Results: After conducting a forward Mendelian randomization analysis, a causal relationship was established between 19 gut microbiota and psoriasis. Furthermore, the reverse MR study revealed causality between psoriasis and 13 gut microbiota. Notably, no substantial heterogeneity of instrumental variables or horizontal pleiotropy was observed., Conclusion: This research suggests a potential genetic association and causal nexus between gut microorganisms and psoriasis, indicating potential implications for the clinical management and therapy of psoriasis. Additional observational studies with a larger population sample size and animal model experiments are imperative to fully elucidate this association's underlying mechanisms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Qian, Shi, Zhang, Bi and Tan.)

Background and Purpose: The causal association between inflammatory cytokines and the development of intracranial aneurysm (IA), unruptured IA (uIA) and subarachnoid hemorrhage (SAH) lacks clarity., Methods: The summary-level datasets for inflammatory cytokines were extracted from a genome-wide association study of the Finnish Cardiovascular Risk in Young Adults Study and the FINRISK survey. The summary statistics datasets related to IA, uIA and SAH were obtained from the genome-wide association study meta-analysis of the International Stroke Genetics Consortium and FinnGen Consortium. The primary method employed for analysis was inverse variance weighting (false discovery rate), supplemented by sensitivity analyses to address pleiotropy and enhance robustness., Results: In the International Stroke Genetics Consortium, 10, six and eight inflammatory cytokines exhibited a causal association with IA, uIA and SAH, respectively (false discovery rate, p < 0.05). In FinnGen datasets, macrophage Inflammatory Protein-1 Alpha (MIP&#95;1A), MIP&#95;1A and interferon γ-induced protein 10 (IP&#95;10) were verified for IA, uIA and SAH, respectively. In the reverse Mendelian randomization analysis, the common cytokines altered by uIA and SAH were vascular endothelial growth factor (VEGF), MIP&#95;1A, IL&#95;9, IL&#95;10 and IL&#95;17, respectively. The meta-analysis results show that MIP&#95;1A and IP&#95;10 could be associated with the decreased risk of IA, and MIP&#95;1A and IP&#95;10 were associated with the decreased risk of uIA and SAH, respectively. Notably, the levels of VEGF, MIP&#95;1A, IL&#95;9, IL&#95;10 and TNF&#95;A were increased with uIA. Comprehensive heterogeneity and pleiotropy analyses confirmed the robustness of these results., Conclusion: Our study unveils a bidirectional association between inflammatory cytokines and IA, uIA and SAH. Further investigations are essential to validate their relationship and elucidate the underlying mechanisms., (© 2024 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Background and Objective: Epidemiological studies have shown that sleep disorders are risk factors for Alzheimer's disease (AD), but the causal relationship between sleep disorders and AD risk is unknown. We aim to assess the potential genetic causal association between sleep characteristics and AD, which may contribute to early identification and prediction of risk factors for AD., Methods: Seven sleep-related traits and the outcome phenotype AD were selected from published genome-wide association studies (GWASs). These sleep-related characteristics and instrumental variables (IVs) for AD were extracted. Two-sample and multivariate Mendelian randomization (MR) analyses were performed to assess the causal relationships between sleep characteristics and AD. The inverse variance weighted (IVW), weighted median (WME), weighted mode (WM), MR-Egger regression (MR-Egger) and simple mode (SM) models were used to evaluate causality. The existence of pleiotropy was detected and corrected by MR-Egger regression, MR pleiotropy residuals and outliers., Results: A two-sample MR study revealed a positive causal association between sleep duration and the onset of AD (OR = 1.002, 95 % CI: 1.000-1.004), and the risk of AD increased with increasing sleep duration. The MR-Egger regression method and MR-PRESSO were used to identify and correct pleiotropy, indicating that there was no horizontal pleiotropy. Heterogeneity was evaluated by Cochran's Q, which indicated no heterogeneity. In a multivariate MR study with seven sleep characteristics corrected for each other, we found that sleep duration remained causally associated with AD (OR = 1.004, 95 % CI: 1.000-1.007). Moreover, we found that after mutual correction, daytime napping had a causal relationship with the onset of AD, and daytime napping may reduce the risk of AD (OR = 0.995, 95 % CI: 0.991-1.000)., Conclusion: This study is helpful for the early identification and prediction of risk factors for AD, long sleep durations are a risk factor for AD, and daytime napping can reduce the risk of AD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Background: Observational studies have suggested that obstructive sleep apnea (OSA) may have a potential carcinogenic role. However, the results of these studies were inconsistent and the underlying genetic mechanisms have yet to be fully understood., Methods: We conducted a Mendelian randomization (MR) analysis using large-scale genome-wide association studies summary statistics to explore the possible causal effect of OSA on the risk of 16 specific-site cancers in the European population., Results: The MR analysis revealed a significantly negative correlation between OSA and the susceptibility to prostate cancer (OR: 0.87, 95%CI 0.79-0.95, p = 0.002) and a causal increase in the vulnerability to pancreatic malignancies (OR: 2.02, 95%CI 1.1-3.7, p = 0.02). However, no causal effects of OSA on other specific-site cancers were found. Sensitivity analyses demonstrated no significant heterogeneity or horizontal pleiotropy, thus validating the robustness of the original results., Conclusion: Our MR provided important insights into the causal associations between OSA and cancer risk, highlighting both protective and potentially harmful effects of OSA on different cancer types., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Objective: Temporomandibular disorders (TMD) affect the temporomandibular joint and associated structures. Despite its prevalence and impact on quality of life, the underlying mechanisms of TMD remain unclear. Magnetic resonance imaging studies suggest brain abnormalities in patients with TMD. However, these lines of evidence are essentially observational and cannot infer a causal relationship. This study employs Mendelian randomisation (MR) to probe causal relationships between TMD and brain changes., Methods: Genome-wide association study (GWAS) summary statistics for TMD were collected, along with brain imaging-derived phenotypes (IDPs). Instrumental variables were selected from the GWAS summary statistics and used in bidirectional 2-sample MR analyses. The inverse-variance weighted analysis was chosen as the primary method. In addition, false discovery rate (FDR) correction of P value was used., Results: Eleven IDPs related to brain imaging alterations showed significant causal associations with TMD (P-FDR < .05), validated through sensitivity analysis. In forward MR, the mean thickness of left caudal middle frontal gyrus (OR, 0.76; 95% CI, 0.67-0.87; P-FDR = 1.15  ×  10 -2 ) and the volume of right superior frontal gyrus (OR, 1.24; 95% CI, 1.10-1.39; P-FDR = 2.26  ×  10 -2 ) exerted significant causal effects on TMD. In the reverse MR analysis, TMD exerted a significant causal effect on 9 IDPs, including the mean thickness of the left medial orbitofrontal cortex (β = -0.10; 95% CI, -0.13 to -0.08; P-FDR = 2.06 × 10 -11 ), the volume of the left magnocellular nucleus (β = -0.15; 95% CI, -0.22 to -0.09; P-FDR = 3.26 × 10 -4 ), the mean intensity of the right inferior-lateral ventricle (β = -0.09; 95% CI, -0.14 to -0.04; P-FDR = 2.23 × 10 -2 ), the volume of grey matter in the anterior division of the left superior temporal gyrus (β = 0.09; 95% CI,  0.04-0.14; P-FDR = 1.69 × 10 -2 ), and so forth., Conclusions: This study provides genetic evidence supporting the bidirectional causal associations between TMD and brain IDPs, shedding light on potential neurobiological mechanisms underlying TMD development and its relationship with brain structure., Competing Interests: Conflict of interest None disclosed., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Abstract Background To investigate the causal association between serum 25-hydroxyvitamin D (25OHD), calcium (Ca), and parathyroid hormone (PTH) levels and the risk of coronary artery disease (CAD) in patients with diabetes using a Mendelian randomization approach. Methods Genetic signatures associated with serum 25OHD, Ca, and PTH levels were extracted from recently published genome-wide association study (GWAS), including 79,366, 39,400, 29,155 individuals, respectively. Genetic association estimates for CAD in patients with diabetes were obtained from a GWAS of 15,666 individuals with diabetes (3,968 CAD cases, 11,696 controls). The inverse-variance-weighted method was employed for the primary analysis, and other robust methods were applied for sensitivity analyses. Results Six, seven and five single nucleotide polymorphisms were identified as instrumental variables for serum 25OHD, Ca and PTH levels, respectively. There was no significant association between genetically predicted serum 25OHD levels and the risk of CAD in patients with diabetes (odds ratio (OR) = 1.04, 95% confidence interval (CI): 0.58 - 1.87, P = 0.888). Similarly, genetically predicted serum Ca (OR = 1.83, 95% CI: 0.62 – 5.35, P = 0.273) and PTH levels (OR = 1.27, 95% CI: 0.67 – 2.44, P = 0.464) were not significantly associated with the risk of CAD in patients with diabetes. These findings were robust in sensitivity analyses. Conclusions/interpretation Serum 25OHD, Ca and PTH levels may not be causally associated with the risk of CAD in patients with diabetes.

BackgroundThe causal direction and magnitude of the associations between telomere length (TL) and cardiovascular diseases (CVDs) remain uncertain due to susceptibility of reverse causation and confounding. This study aimed to investigate the associations between TL and CVDs using Mendelian randomization (MR).Materials and methodsIn this two-sample MR study, we identified 154 independent TL-associated genetic variants from a genome-wide association study (GWAS) consisting of 472,174 individuals (aged 40–69) in the UK Biobank. Summary level data of CVDs were obtained from different GWASs datasets. Methods of inverse variance weighted (IVW), Mendelian Randomization-Egger (MR-Egger), Mendelian Randomization robust adjusted profile score (MR-RAPS), maximum likelihood estimation, weighted mode, penalized weighted mode methods, and Mendelian randomization pleiotropy residual sum and outlier test (MR-PRESSO) were conducted to investigate the associations between TL and CVDs.ResultsOur findings indicated that longer TL was significantly associated with decreased risk of coronary atherosclerosis [odds ratio (OR), 0.85; 95% confidence interval (CI), 0.75–0.95; P = 4.36E-03], myocardial infarction (OR, 0.72; 95% CI, 0.63–0.83; P = 2.31E-06), ischemic heart disease (OR, 0.87; 95% CI, 0.78–0.97; P = 1.01E-02), stroke (OR, 0.87; 95% CI, 0.79–0.95; P = 1.60E-03), but an increased risk of hypertension (OR, 1.12; 95% CI, 1.02–1.23; P = 2.00E-02). However, there was no significant association between TL and heart failure (OR, 0.94; 95% CI, 0.87–1.01; P = 1.10E-01), atrial fibrillation (OR, 1.01; 95% CI, 0.93–1.11; P = 7.50E-01), or cardiac death (OR, 0.95; 95% CI, 0.82–1.10; P = 4.80E-01). Both raw and outlier corrected estimates from MR-PRESSO were consistent with those of IVW results. The sensitivity analyses showed no evidence of pleiotropy (MR-Egger intercept, P > 0.05), while Cochran’s Q test and MR-Egger suggested different degrees of heterogeneity.ConclusionOur MR study suggested that longer telomeres were associated with decreased risk of several CVDs, including coronary atherosclerosis, myocardial infarction, ischemic heart disease, and stroke, as well as an increased risk of hypertension. Future studies are still warranted to validate the results and investigate the mechanisms underlying these associations.

BackgroundThe relationship between tea consumption and the risk of breast cancer is inconsistent in previous observational studies and is still in dispute. We intended to detect the causal association between tea consumption and breast cancer risk using two-sample Mendelian randomization (MR) analysis.Materials and methodsThe summary statistics of tea consumption was obtained from the UK Biobank Consortium with 349,376 individuals and breast cancer information was obtained from the Breast Cancer Association Consortium (BCAC) (122,977 cases and 105,974 non-cases). Sensitivity analyses of evaluating the influence of outliers and pleiotropy effects were performed by a variety of MR methods under different model assumptions.ResultsAfter potentially excluding pleiotropic single nucleotide polymorphisms (SNPs) using the MR Pleiotropy RESidual Sum and Outlier method, the odds ratio (OR) for per extra daily cup of tea intake for overall, estrogen receptor (ER)-positive, and ER-negative breast cancer risk was 1.029 [95% confidence interval (CI) = 0.983–1.077, P = 0.2086], 1.050 (95% CI = 0.994–1.109, P = 0.078), and 1.081 (95% CI = 0.990–1.103, P = 0.6513), respectively. The results were consistent with a sensitivity analysis that excluded SNPs associated with other phenotypes, manifesting that the findings were convincing and robust. Moreover, in the multivariable MR analysis, the null associations for breast cancer risk remained after adjusting for smoking and alcohol consumption separately or together.ConclusionOur MR results based on genetic data did not support a causal relationship between tea consumption and breast cancer risk.

PurposeThe effect of hyperglycemia on periodontitis is mainly based on observational studies, and inconsistent results were found whether periodontal treatment favors glycemic control. The two-way relationship between periodontitis and hyperglycemia needs to be further elucidated. This study aims to evaluate the causal association of periodontitis with glycemic traits using bi-directional Mendelian randomization (MR) approach.MethodsSummary statistics were sourced from large-scale genome-wide association study conducted for fasting glucose (N = 133,010), HbA1c (N = 123,665), type 2 diabetes (T2D, N = 659,316), and periodontitis (N = 506,594) among European ancestry. The causal relationship was estimated using the inverse-variance weighted (IVW) model and further validated through extensive complementary and sensitivity analyses.ResultsOverall, IVW showed that a genetically higher level of fasting glucose was significantly associated with periodontitis (OR = 1.119; 95% CI = 1.045–1.197; PFDR= 0.007) after removing the outlying instruments. Such association was robust and consistent through other MR models. Limited evidence was found suggesting the association of HbA1C with periodontitis after excluding the outliers (IVW OR = 1.123; 95% CI = 1.026–1.229; PFDR= 0.048). These linkages remained statistically significant in multivariate MR analyses, after adjusting for body mass index. The reverse direction MR analyses did not exhibit the causal association of genetic liability to periodontitis with any of the glycemic trait tested.ConclusionsOur MR study reaffirms previous findings and extends evidence to substantiate the causal effect of hyperglycemia on periodontitis. Future studies with robust genetic instruments are needed to confirm the causal association of periodontitis with glycemic traits.

BackgroundSeveral observational studies have identified that handgrip strength was inversely associated with cardiovascular diseases (CVDs). Nevertheless, causality remains controversial. We conducted Mendelian randomization (MR) analysis to examine whether handgrip strength and risk of CVDs are causally associated.MethodsWe identified 160 independent single nucleotide polymorphisms (SNPs) for right-hand grip strength and 136 independent SNPs for left-hand grip strength at the genome-wide significant threshold (P < 5 × 10−8) from UK Biobank participants and evaluated these in relation to risk of CVDs. MR estimates was calculated using the inverse-variance weighted (IVW) method and multiple sensitivity analysis was further conducted.ResultsGenetical liability to handgrip strength was significantly associated with coronary artery disease (CAD) and myocardial infarction (MI), but not stroke, hypertension, or heart failure. Additionally, there was significant association between right-hand grip strength and atrial fibrillation (OR, 0.967; 95% CI, 0.950–0.984; p = 0.000222), however, suggestive significance was found between left-hand grip strength and atrial fibrillation (OR, 0.977; 95% CI, 0.957–0.998; p = 0.033). Results were similar in several sensitivity analysis.ConclusionOur study provides support at the genetic level that handgrip strength is negatively associated with the risk of CAD, MI, and atrial fibrillation. Specific handgrip strength interventions on CVDs warrant exploration as potential CVDs prevention measures.

Background and Aims: Epidemiological studies have suggested positive associations between asthma and the risk of cardiovascular diseases (CVDs). However, causality remains inconclusive. We aim to explore the causal associations between asthma and CVDs risk using the Mendelian Randomization (MR) approach. Methods: We obtained summary-level data for eight CVDs [including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), stroke, ischemic stroke, large artery stroke, small vessel stroke, and cardioembolic stroke] from several large genome-wide association studies (GWASs) and the FinnGen consortium. Nine lead single-nucleotide polymorphisms associated with asthma (p < 5 x 10-8) were identified from the GWAS conducted by the Trans-National Asthma Genetic Consortium. MR analyses were performed using the inverse variance weighted method, supplemented by the weighted median and MR-Egger methods. Results: Inverse variance weighted method showed suggestive effects of genetically determined asthma on AF (odds ratio (OR), 1.08; 95% confidence interval (CI), 1.02, 1.14; p = 0.009) and HF (OR, 1.05; 95% CI, 1.01, 1.09; p = 0.029). We found no causal associations between asthma and other CVDs. No horizontal pleiotropy was observed. Conclusion: This MR study provides genetic evidence suggesting a causal association between asthma and the risk of AF and HF, although not at the level of significance after multiple testing correction. Programs aimed at treating asthma among asthmatics might help prevent the adverse health effects inflicted by CVDs. [ABSTRACT FROM AUTHOR]

Background: A growing number of cohort studies revealed an inverse association between cheese intake and cardiovascular diseases, yet the causal relationship is unclear. Objective: To assess the causal relationship between cheese intake, and cardiovascular diseases and cardiovascular biomarkers. Methods: A two-sample Mendelian randomization (MR) analysis based on publicly available genome-wide association studies was employed to infer the causal relationship. The effect estimates were calculated using the random-effects inverse-variance-weighted method. Results: Cheese intake per standard deviation increase causally reduced the risks of type 2 diabetes (odds ratio (OR) = 0.46; 95% confidence interval (CI), 0.34–0.63; p = 1.02 × 10−6), heart failure (OR = 0.62; 95% CI, 0.49–0.79; p = 0.0001), coronary heart disease (OR = 0.65; 95% CI, 0.53–0.79; p = 2.01 × 10−5), hypertension (OR = 0.67; 95% CI, 0.53–0.84; p = 0.001), and ischemic stroke (OR = 0.76; 95% CI, 0.63–0.91; p = 0.003). Suggestive evidence of an inverse association between cheese intake and peripheral artery disease was also observed. No associations were observed for atrial fibrillation, cardiac death, pulmonary embolism, or transient ischemic attack. The better prognosis associated with cheese intake may be explained by lower body mass index (BMI; effect estimate = −0.58; 95% CI, from −0.88 to −0.27; p = 0.0002), waist circumference (effect estimate = −0.49; 95% CI, from −0.76 to −0.23; p = 0.0003), triglycerides (effect estimate = −0.33; 95% CI, from −0.50 to −0.17; p = 4.91 × 10−5), and fasting glucose (effect estimate = −0.20; 95% CI, from −0.33 to −0.07; p = 0.0003). There was suggestive evidence of a positive association between cheese intake and high-density lipoprotein. No influences were observed for blood pressure or inflammation biomarkers. Conclusions: This two-sample MR analysis found causally inverse associations between cheese intake and type 2 diabetes, heart failure, coronary heart disease, hypertension, and ischemic stroke. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: The causal association between educational attainment (EA) and stroke remains unclear. Hence, a novel multivariable Mendelian randomization (MVMR) approach was applied to solve this issue.Methods: The single nucleotide polymorphisms (SNPs) from a recent genome-wide association study (GWAS) on years of schooling served as instruments. Univariable mendelian randomization (MR) and MVMR analyses were performed to detect the relationship between genetically predicted EA and the stroke risk. In the MVMR, cigarette consumption, alcohol consumption, body mass index (BMI), intelligence, and hypertension were adjusted. The summary statistics for stroke from the MEGASTROKE consortium included 446,696 participants (40,585 cases of stroke and 34,217 cases of ischemic stroke), most of whom were of European descent.Results: In the univariable MR, genetically predicated EA could decrease the risks of total stroke (OR = 0.66, 95% CI 0.61-0.72, P = 2.70 × 10-23), ischemic stroke (OR = 0.67, 95% CI 0.61-0.73, P = 2.58 × 10-18), large artery atherosclerosis (OR = 0.51, 95% CI 0.40-0.64, P = 1.80 × 10-8), small vessel stroke (OR = 0.60, 95% CI 0.49-0.73, P = 5.59 × 10-7), and cardioembolic stroke (OR = 0.81, 95% CI 0.68-0.96, P = 1.46 × 10-2) using the inverse-variance weighted (IVW) estimator. Higher EA might be negatively correlated with the odds of total stroke (OR = 0.62, 95% CI 0.50-0.77, P = 1.44 × 10-5), ischemic stroke (OR = 0.63, 95% CI 0.50-0.80, P = 1.41 × 10-4), and cardioembolic stroke (OR = 0.59, 95% CI 0.39-0.90, P = 0.01), but was not significant in large artery atherosclerosis (OR = 0.65, 95% CI 0.37-1.15, P = 0.14) and small vessel stroke (OR = 0.68, 95% CI 0.41-1.13, P = 0.14) after controlling other exposures.Conclusions: We found that genetically predicated higher EA decreased the risks of total stroke, ischemic stroke, and cardioembolic stroke, independent of smoking, alcohol consumption, BMI, intelligence, and hypertension. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation is the most common arrhythmia disease. Animal and observational studies have found a link between iron status and atrial fibrillation. However, the causal relationship between iron status and AF remains unclear. The purpose of this investigation was to use Mendelian randomization (MR) analysis, which has been widely applied to estimate the causal effect, to reveal whether systemic iron status was causally related to atrial fibrillation. Methods: Single nucleotide polymorphisms (SNPs) strongly associated (P < 5 × 10−8) with four biomarkers of systemic iron status were obtained from a genome-wide association study involving 48,972 subjects conducted by the Genetics of Iron Status consortium. Summary-level data for the genetic associations with atrial fibrillation were acquired from the AFGen (Atrial Fibrillation Genetics) consortium study (including 65,446 atrial fibrillation cases and 522,744 controls). We used a two-sample MR analysis to obtain a causal estimate and further verified credibility through sensitivity analysis. Results: Genetically instrumented serum iron [OR 1.09; 95% confidence interval (CI) 1.02–1.16; p = 0.01], ferritin [OR 1.16; 95% CI 1.02–1.33; p = 0.02], and transferrin saturation [OR 1.05; 95% CI 1.01–1.11; p = 0.01] had positive effects on atrial fibrillation. Genetically instrumented transferrin levels [OR 0.90; 95% CI 0.86–0.97; p = 0.006] were inversely correlated with atrial fibrillation. Conclusion: In conclusion, our results strongly elucidated a causal link between genetically determined higher iron status and increased risk of atrial fibrillation. This provided new ideas for the clinical prevention and treatment of atrial fibrillation. [ABSTRACT FROM AUTHOR]

Simple Summary: During the COVID-19 pandemic, cancer patients are regarded as a highly vulnerable population. Given the unavoidable bias and unmeasured confounders in observational studies, the causal effects of cancers on COVID-19 outcomes are largely unknown. In the study, we tried to evaluate the causal effects of cancers on COVID-19 outcomes using the Mendelian randomization (MR) approach. No strong evidence was observed to support a causal role of cancer in COVID-19 development. Previous observational correlations between cancers and COVID-19 outcomes were likely confounded. Large and well-conducted epidemiological studies are required to determine whether cancers causally contribute to increased risk of COVID-19. Observational studies have shown increased COVID-19 risk among cancer patients, but the causality has not been proven yet. Mendelian randomization analysis can use the genetic variants, independently of confounders, to obtain causal estimates which are considerably less confounded. We aimed to investigate the causal associations of cancers with COVID-19 outcomes using the MR analysis. The inverse-variance weighted (IVW) method was employed as the primary analysis. Sensitivity analyses and multivariable MR analyses were conducted. Notably, IVW analysis of univariable MR revealed that overall cancer and twelve site-specific cancers had no causal association with COVID-19 severity, hospitalization or susceptibility. The corresponding p-values for the casual associations were all statistically insignificant: overall cancer (p = 0.34; p = 0.42; p = 0.69), lung cancer (p = 0.60; p = 0.37; p = 0.96), breast cancer (p = 0.43; p = 0.74; p = 0.43), endometrial cancer (p = 0.79; p = 0.24; p = 0.83), prostate cancer (p = 0.54; p = 0.17; p = 0.58), thyroid cancer (p = 0.70; p = 0.80; p = 0.28), ovarian cancer (p = 0.62; p = 0.96; p = 0.93), melanoma (p = 0.79; p = 0.45; p = 0.82), small bowel cancer (p = 0.09; p = 0.08; p = 0.19), colorectal cancer (p = 0.85; p = 0.79; p = 0.30), oropharyngeal cancer (p = 0.31; not applicable, NA; p = 0.80), lymphoma (p = 0.51; NA; p = 0.37) and cervical cancer (p = 0.25; p = 0.32; p = 0.68). Sensitivity analyses and multivariable MR analyses yielded similar results. In conclusion, cancers might have no causal effect on increasing COVID-19 risk. Further large-scale population studies are needed to validate our findings. [ABSTRACT FROM AUTHOR]

Background and Aims: Observational studies have examined serum urate levels in relation to coronary heart disease (CHD) and myocardial infarction (MI). Whether these associations are causal remains controversial, due to confounding factors and reverse causality. We aim to investigate the causality of these associations using Mendelian randomization method.Methods and Results: Instrumental variables were obtained from the largest genome-wide association studies of serum urate (457,690 individuals) to date. Summary statistics were from CARDIoGRAMplusC4D consortium (60,801 CHD cases; 43,676 MI cases), FinnGen (21,012 CHD cases; 12,801 MI cases), UK Biobank (10,157 CHD cases; 7018 MI cases), and Biobank Japan (29,319 CHD cases). Inverse-variance weighted method was applied as the main results. Other statistical methods and reverse MR analysis were conducted in the supplementary analyses. Elevated genetically determined serum urate levels were associated with increased risks of CHD and MI. The association pattern remained for the datasets in FinnGen, the combined results of three independent data sources (CHD: odds ratio (OR), 1.10; 95%CI, 1.06-1.15; p = 4.2 × 10-6; MI: OR, 1.12; 95%CI, 1.07-1.18; p = 2.7 × 10-6), and East Asian population. Interestingly, sex-specific subgroup analyses revealed that these associations kept in men only, but not among women in individuals of European ancestry. No consistent evidence was found for the causal effect of CHD or MI on serum urate levels.Conclusion: We provide consistent evidence for the causal effect of genetically predicted serum urate levels on CHD and MI, but not the reverse effect. Urate-lowering therapy may be of cardiovascular benefit in the prevention of CHD and MI, especially for men. [ABSTRACT FROM AUTHOR]

• Our study was first and most comprehensive study to assess the causal relationship between circulating immune cells and diverse sites of OA. • Our results highlight the intricate interplay between immune cells and OA, suggesting potential targets for therapeutic interventions to manage disease progression and alleviate symptoms. Osteoarthritis (OA) is a common degenerative joint disease, with its etiology remaining poorly understood. Our study aims to explore the causal associations between immune cells and OA, with the goal of generating a new perspective for targeted intervention strategies. A bidirectional two-sample Mendelian randomization (MR) analysis was performed to estimate the causality between multiple circulating immune cells and different sites of OA. The immune cell traits analyzed included the counts of circulating white blood cells (WBC), lymphocytes, monocytes, neutrophils, eosinophils, and basophils, as well as certain subsets of T and B lymphocytes. The OA types included were OA at any site, knee OA, hip OA, spine OA, thumb OA, and hand OA. Inverse-variance weighted (IVW), MR-Egger, weight median and weight mode were used to evaluate causal effects, with IVW being the main analysis method. Sensitivity analyses were conducted to assess heterogeneity and pleiotropy. Our findings indicated that resting regulatory T cell (Treg) absolute counts (AC) were causally associated with an increased risk for spine OA [odds ratio (OR), 1.051; 95 % confidence interval (CI), 1.018–1.086; P =0.0005, P FDR =0.0350], and spine OA showed a positive causal relationship with the neutrophils count (OR, 1.104; 95 %CI, 1.032–1.181; P =0.0039, P FDR =0.0233). Besides, OA at any site was correlated with a rise in circulating eosinophils count (OR, 1.05; 95 %CI, 1.021–1.079; P =0.0007, P FDR =0.0041), while knee OA was associated with decreased total WBC (OR, 0.945; 95 %CI, 0.912–0.979; P =0.0016, P FDR =0.0048) and monocytes counts (OR, 0.958; 95 %CI, 0.934–0.982; P =0.0007, P FDR = 0.0041). No evidence of heterogeneity or horizontal pleiotropy was detected. Our study has demonstrated the causal associations between multiple immune cells and diverse joint OA. These results highlight the intricate interplay between immune cells and OA, suggesting potential targets for therapeutic interventions to manage disease progression and alleviate symptoms. [ABSTRACT FROM AUTHOR]

• SLAMF1 plays a crucial role in the development of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). • SLAMF1 is linked to both rheumatoid arthritis (RA) and interstitial lung disease (ILD). Elevated expression of SLAMF1 has been observed in patients with RA and pulmonary fibrosis, correlating with a poor prognosis. • We developed a rat model of RA-ILD and found that SLAMF1 expression was significantly higher in lung tissues compared to normal rats. • The biological role of SLAMF1 in RA-ILD may involve multiple immune cell infiltrations and extracellular matrix (ECM) synthesis in lung tissues. • SLAMF1 could serve as a new biomarker for assessing RA-ILD risk and represents a promising target for therapeutic interventions in pulmonary complications associated with RA. Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is a common complication of rheumatoid arthritis (RA) that result in significant morbidity and mortality. Understanding the molecular mechanisms underlying RA-ILD is crucial for effective prevention. This study aims to identify the specific molecule that mediate the causal association between RA and ILD, as well as to explore its potential mechanisms in the pathogenesis of RA-ILD. Using two-sample Mendelian randomization (MR) analyses, we investigated the causal relationship among 16,987 blood genes, RA and ILD. Subsequently, a two-step MR technique was employed to identify significant genes that mediate the association between RA and ILD, and to quantify their proportion of mediation effect. To validate the genes as mediators, the replication MR analysis was conducted and the in vivo experiment was performed using an established animal model of RA-ILD. Furthermore, integrated bioinformatic analyses were conducted to elucidate the specific biological functions of the determined mediator in pathogenesis of RA-ILD. Nine genes, namely MAPK8IP2, TAF11, SLAMF1, DAB2IP, GLUL, SLC4A10, PRSS35, NFX1, and PLK3, were identified as mediators. Among them, SLAMF1 was validated as the most significant mediator, accounting for 4.693% of the mediating effect on the causal relationship between RA and ILD. Upregulated mRNA expression of SLAMF1 was observed in the animal model of RA-ILD compared to controls. Bioinformatic analyses revealed that SLAMF1 was overexpressed in patients with lung fibrosis and correlated with a poor prognosis. Specifically, SLAMF1 was found to be predominantly overexpressed in T cells in lung tissues of patients with lung fibrosis. Additionally, the functional role of SLAMF1 was associated with multiple immune cell infiltrations and the biological process of extracellular matrix synthesis in pulmonary tissues from patients with lung fibrosis. SLAMF1 may play a crucial role as a molecular mediator in the causal association between RA and ILD, and participate in multiple mechanisms underlying the pathogenesis of RA-ILD. This research provides insights into how the development of RA influences the risk of ILD and offers potential interventional targets against RA-ILD. [ABSTRACT FROM AUTHOR]

Background and AimsVitamin D deficiency is a common disorder and has been linked with atrial fibrillation (AF) in several observational studies, although the causal relationships remain unclear. We conducted a Mendelian randomization (MR) analysis to determine the causal association between serum 25-hydroxyvitamin D [25(OH)D] concentrations and AF.Methods and ResultsThe analyses were performed using summary statistics obtained for single-nucleotide polymorphisms (SNPs) identified from large genome-wide association meta-analyses conducted on serum 25(OH)D (N = 79,366) and AF (N = 1,030,836). Six SNPs related to serum 25(OH)D were used as instrumental variables. The association between 25(OH)D and AF was estimated using both the fixed-effect and random-effects inverse variance weighted (IVW) method. The MR analyses found no evidence to support a causal association between circulating 25(OH)D level and risk of AF using random-effects IVW (odds ratio per unit increase in log 25(OH)D = 1.003, 95% CI, 0.841–1.196; P = 0.976) or fixed-effect IVW method (OR = 1.003, 95% CI, 0.876–1.148; P = 0.968). Sensitivity analyses yielded similar results. No heterogeneity and directional pleiotropy were detected.ConclusionUsing summary statistics, this MR study suggests that genetically predicted circulating vitamin D concentrations, especially for a non-deficient range, were not causally associated with AF in the general population. Future studies using non-linear design and focusing on the vitamin D deficiency population are needed to further evaluate the causal effect of vitamin D concentrations on AF.

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.

Background and AimsObservational epidemiological studies have suggested that atopic dermatitis (AD) was associated with an increased risk of cardiovascular diseases (CVDs). However, causality remains to be established. In the present study, Mendelian randomization (MR) analyses were used to evaluate whether AD and CVDs are causally associated.MethodsThis study was based on summary statistics of genome-wide association studies (GWASs) for a set of cardiovascular outcomes including heart failure (HF), coronary artery disease (CAD), myocardial infarction (MI), atrial fibrillation (AF), stroke, and stroke subtypes. A total of 19 independent single nucleotide polymorphisms associated with AD were identified at a genome-wide significance threshold (P < 5 × 10−8) based on a large GWAS meta-analysis. MR estimates were pooled using the inverse variance weighted method. Complementary analyses further evaluated the robustness of the results.ResultsGenetically determined AD was causally associated with HF [odds ratio (OR), 1.07; 95% confidence interval (CI), 1.03–1.10; P = 1.11 × 10−4]. However, there was no causal association between AD and the risk of AF, CAD, MI, stroke, and stroke subtypes. Complementary analyses returned similar results. No horizontal pleiotropy was found.ConclusionThis MR study provided evidence to support that AD exerted an effect contributing to HF. No significant associations were found for other cardiovascular outcomes. The study suggested that prevention and early diagnosis of AD may help prevent HF. Improved awareness of these associations is warranted for better management of CVDs in the future.

Clinical studies have shown that cardiovascular diseases in patients with type 1 diabetes (T1D) are often atypical or asymptomatic. The link between T1D and arrhythmia remains unclear. To infer causality between T1D and arrhythmia at the genetic level, we conducted a Mendelian randomization study through the genetic tools of T1D. In this study, we used genetic variables and summary statistics from genome-wide association studies of T1D and arrhythmia. Single nucleotide polymorphisms were selected based on the assumptions of instrumental variables. The inverse variance-weighted method was used as the primary analysis to summarize the causal effects between exposure and outcome. The weighted median and weighted mode methods were used as secondary methods. We tested for horizontal pleiotropy using the MR-Egger method and detected heterogeneity using the Q-test. A leave-one-out sensitivity analysis was performed. Scatter plots, forest plots, and funnel plots were used to visualize the results of the MR analysis. In this study, we selected 28 T1D-related SNPs as instrumental variables. The IVW [odds ratio (OR) = 0.98, 95 % confidence interval (CI) = 0.97−1.00, P = 0.008], weighted median (OR = 0.98, 95 % CI = 0.96 − 0.99, P = 0.009), and weighted mode (OR = 0.98, 95 % CI = 0.96−0.99, P = 0.018) analysis methods suggested a causal effect of T1D on arrhythmia. The MR-Egger method indicated no horizontal pleiotropy (P = 0.649), and the Q-test showed no heterogeneity (IVW, P = 0.653). Our MR analysis revealed a causal association between T1D and the development of arrhythmia, indicating that patients with T1D had a higher risk of arrhythmia. [ABSTRACT FROM AUTHOR]

Background: Observational studies have found an association between increased whole body water mass (BWM) and atrial fibrillation (AF). However, the causality has yet to be confirmed. To provide feasible protective measures on disease development, we performed Mendelian randomization (MR) design to estimate the potential causal relationship between increased BWM and AF. Methods: We implemented a two-sample MR study to assess whether increased BWM causally influences AF incidence. For exposure, 61 well-powered genetic instruments extracted from UK Biobank (N = 331,315) were used as the proxies of BWM. Summary genetic data of AF were obtained from FinnGen (Ncase = 22,068; Ncontrol = 116,926). Inverse-variance weighted (IVW), MR-Egger and weighted median methods were selected to infer causality, complemented with a series of sensitivity analyses. MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) and Radial MR were employed to identify outliers. Furthermore, risk factor analyses were performed to investigate the potential mechanisms between increased BWM and AF. Results: Genetic predisposition to increased BWM was demonstrated to be significantly associated with AF in the IVW model (OR = 2.23; 95% CI = 1.47–3.09; p = 1.60 × 10−7), and the result was consistent in other MR approaches. There was no heterogeneity or pleiotropy detected in sensitivity analysis. MR-PRESSO identified no outliers with potential pleiotropy after excluding outliers by Radial MR. Furthermore, our risk factor analyses supported a positive causal effect of genetic predicted increased BWM on edematous diseases. Conclusions: MR estimates showed that a higher BWM could increase the risk of AF. Pathological edema is an important intermediate link mediating this causal relationship.

Background: Observational 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. Methods: A 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. Results: A 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. Conclusion: Our 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. [ABSTRACT FROM AUTHOR]

Context: Observational studies have suggested that higher resting heart rate (RHR) may be associated with increased cardiometabolic risk. However, causal associations are not fully understood. Objective: We aimed to examine the direction, strength, and causality of the associations of RHR with cardiometabolic traits. Methods: We assessed the strength of associations between measured RHR and cardiometabolic traits in 506 211 and 372 452 participants from China Kadoorie Biobank (CKB) and UK Biobank (UKB). Mendelian randomization (MR) analyses were used to make causal inferences in 99 228 and 371 508 participants from CKB and UKB, respectively. Results: We identified significant directionally concordant observational associations between RHR and higher total cholesterol, triglycerides (TG), low-density lipoprotein, C-reactive protein (CRP), glucose, body mass index, waist-hip ratio (WHR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) after the Bonferroni correction. MR analyses showed that 10 beat/min higher genetically predicted RHR was trans-ethnically associated with a higher DBP (beta 2.059 [95% CI 1.544, 2.574] mmHg in CKB; 2.037 [1.845, 2.229] mmHg in UKB), higher CRP (0.180 [0.057, 0.303] log mg/L in CKB; 0.154 [0.134, 0.174] log mg/L in UKB), higher TG (0.052 [−0.009, 0.113] log mmol/L in CKB; 0.020 [0.010, 0.030] log mmol/L in UKB) and higher WHR (0.218 [−0.033, 0.469] % in CKB; 0.225 [0.111, 0.339] % in UKB). In the opposite direction, higher genetically predicted SBP, TG, glucose, and WHR, and lower high-density lipoprotein, were associated with elevated RHR. Conclusion: Our large-scale analyses provide causal evidence for associations between RHR and cardiometabolic traits, highlighting the importance of monitoring heat rate as a means of alleviating the adverse effects of metabolic disorders. [ABSTRACT FROM AUTHOR]

Background: The association reported between tea intake and type 2 diabetes (T2D) is inconsistent in previous studies and remains controversial. We aimed to explore the causal relationship between tea intake, T2D, and glycemic traits including hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), fasting serum insulin (FSI), and homeostasis model of insulin resistance (HOMA-IR) levels. Methods: A 2-sample Mendelian randomization (MR) was performed using summary statistics from large-scale genome-wide association studies of tea intake from the UK Biobank, T2D from the DIAGRAM consortium, and glycemic traits from the Magic consortium. The findings were verified through sensitivity analyses using various MR methods with different model assumptions and by comprehensively evaluating the influence of pleiotropy effects and outliers. Results: With the use of a two-sample MR with inverse variance-weighted method, the odds ratio per unit SD change of tea intake (SD: 2.85 cups/day) for T2D, HbA1c, FPG, FSI, and HOMA-IR levels was 0.949 (95% CI 0.844–1.067, p = 0.383), 0.994 (95% CI 0.975–1.013, p = 0.554), 0.996 (95% CI 0.978–1.015, p = 0.703), 0.968 (95% CI 0.948–0.986, p = 0.001), and 0.953 (95% CI 0.900–1.009, p = 0.102), respectively. The results were consistent with those of the other six methods that we used with different model assumptions, suggesting that the findings were robust and convincing. We also performed various sensitivity analyses for outlier removal, pleiotropy detection, and leave-one-out analysis. Conclusion: Our MR results did not support the causal effect of tea intake on T2D and crucial glycemic traits. These findings suggest that previous observational studies may have been confounded. [ABSTRACT FROM AUTHOR]

Background: Observational studies suggested that multiple sclerosis (MS) is associated with cardiovascular diseases (CVDs). However, the causal association has not been fully elucidated. Thus, we aim to assess the causality of the associations of MS with risk of CVDs. Methods: A two-sample Mendelian randomization (MR) study was performed to explore the causality. Genetic instruments were identified for MS from a genome-wide association study (GWAS) involving 115,803 individuals. Summary-level data for CVDs were obtained from different GWAS meta-analysis studies. MR analysis was conducted mainly using the inverse-variance weighted (IVW) method. Sensitivity analyses were further performed to ensure the robustness of the results. Results: This MR study found suggestive evidence that genetic liability to MS was associated with an increased risk of coronary artery disease (CAD) [odds ratio (OR), 1.02; 95% confidence interval (CI), 1.00–1.04; p = 0.03], myocardial infarction (MI) (OR, 1.03; 95% CI, 1.00–1.06; p = 0.01), heart failure (HF) (OR, 1.02; 95% CI, 1.00–1.04; p = 0.02), all-cause stroke (AS) (OR, 1.02; 95% CI, 1.00–1.05; p = 0.02), and any ischemic stroke (AIS) (OR, 1.02; 95% CI, 1.00–1.05; p = 0.04). The null-association was observed between MS and the other CVDs. Further analyses found little evidence of pleiotropy. Conclusions: We provided suggestive genetic evidence for the causal associations of MS with increased risk of CAD, MI, HF, AS, and AIS, which highlighted the significance of active monitoring and prevention of cardiovascular risk to combat cardiovascular comorbidities in MS patients. [ABSTRACT FROM AUTHOR]

Background: Despite accumulating epidemiological studies support that diabetes increases the risk of Alzheimer's disease (AD), the causal associations between diabetes and AD remain inconclusive. The present study aimed to explore: i) whether diabetes is causally related to the increased risk of AD; ii) and if so, which diabetes-related physiological parameter is associated with AD; iii) why diabetes drugs can be used as candidates for the treatment of AD. Two-sample Mendelian randomization (2SMR) was employed to perform the analysis. Results: Firstly, the 2SMR analysis provided a suggestive association between genetically predicted type 1 diabetes (T1D) and a slightly increased AD risk (OR = 1.04, 95% CI = [1.01, 1.06]), and type 2 diabetes (T2D) showed a much stronger association with AD risk (OR = 1.34, 95% CI = [1.05, 1.70]). Secondly, further 2SMR analysis revealed that diabetes-related physiological parameters like fasting blood glucose and total cholesterol levels might have a detrimental role in the development of AD. Thirdly, we obtained 74 antidiabetic drugs and identified SNPs to proxy the targets of antidiabetic drugs. 2SMR analysis indicated the expression of three target genes, ETFDH, GANC, and MGAM, were associated with the increased risk of AD, while CPE could be a protective factor for AD. Besides, further PPI network found that GANC interacted with MGAM, and further interacted with CD33, a strong genetic locus related to AD. Conclusions: In conclusion, the present study provides evidence of a causal association between diabetes and increased risk of AD, and also useful genetic clues for drug development. [ABSTRACT FROM AUTHOR]

Evidence from observational studies for the effect of tea consumption on obesity is inconclusive. This study aimed to verify the causal association between tea consumption and obesity through a two-sample Mendelian randomization (MR) analysis in general population-based datasets. The genetic instruments, single nucleotide polymorphisms (SNPs) associated with tea consumption habits, were obtained from genome-wide association studies (GWAS): UK Biobank, Nurses' Health Study, Health Professionals Follow-up Study, and Women's Genome Health Study. The effect of the genetic instruments on obesity was analyzed using the UK Biobank dataset (among ∼500,000 participants). The causal relationship between tea consumption and obesity was analyzed by five methods of MR analyses: inverse variance weighted (IVW) method, MR-Egger regression method, weighted median estimator (WME), weighted mode, and simple mode. Ninety-one SNPs were identified as genetic instruments in our study. A mild causation was found by IVW (odds ratio [OR] = 0.998, 95% confidence interval [CI] = 0.996 to 1.000, p = 0.049]), which is commonly used in two-sample MR analysis, indicating that tea consumption has a statistically significant but medically weak effect on obesity control. However, the other four approaches did not show significance. Since there was no heterogeneity and pleiotropy in this study, the IVW approach has the priority of recommendation. Further studies are needed to clarify the effects of tea consumption on obesity-related health problems in detail. [ABSTRACT FROM AUTHOR]

Background: Low intelligence has been shown to be associated with a high risk of cardiovascular disease in observational studies. It remains unclear whether the association is causal. This study aimed to explore the causal association of intelligence with coronary artery disease (CAD) and myocardial infarction (MI). Methods: A two-sample Mendelian randomization study was designed to infer the causality. A total of 121 single nucleotide polymorphisms were selected as a genetic instrumental variable for intelligence. Summary data on CAD (n = 184,305) and MI (n = 171,875) were obtained from the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis (CARDIoGRAM) plus The Coronary Artery Disease (C4D) Genetics (CARDIoGRAMplusC4D) consortium and the FinnGen study. Inverse variance weighting method was used to calculate the effect estimates. Sensitivity analyses including other statistical models and leave-one-out analysis were conducted to verify the robustness of results. MR-Egger test was performed to assess the pleiotropy. Results: Genetically predicted higher intelligence was significantly associated with lower risk of CAD (OR,.76; 95%CI,.69–.85; p = 1.5 × 10–7) and MI (OR,.78; 95%CI,.70–.87; p = 7.9 × 10–6). The results remained consistent in the majority of the sensitivity analyses and were repeated in the FinnGen datasets. MR-Egger test suggested no evidence of directional pleiotropy for the association with coronary artery disease (intercept = −.01, p =.19) and myocardial infarction (intercept = −.01, p =.06). Conclusion: This Mendelian randomization analysis provided genetic evidence for the causal association between low intelligence and increased risks of CAD and MI. [ABSTRACT FROM AUTHOR]

Context: Observational studies have been associated obesity with chronic kidney disease (CKD) and arterial stiffness, but the causality remains unclear. Objective: We aimed to investigate the causality of obesity with CKD and arterial stiffness using mendelian randomization (MR) analysis. Methods: We genotyped 14 body mass index (BMI)-associated variants validated in East Asians in 11 384 Chinese adults. A genetic risk score based on the 14 variants and the 14 individual single-nucleotide variations (SNVs, formerly single-nucleotide polymorphisms [SNPs]) were respectively used as instrumental variables (IVs). CKD was defined as estimated glomerular filtration rate less than 60 mL/min/1.73 m². Arterial stiffness was defined as brachial-ankle pulse wave velocity greater than 1550 cm/s. Results: Using the genetic risk score as the IV, we demonstrated causal relations of each 1-SD increment in BMI with CKD (odds ratio [OR]: 2.36; 95% CI, 1.11-5.00) and arterial stiffness (OR: 1.71; 95% CI, 1.22-2.39). Using the 14 SNVs individually as IVs, each 1-SD increment in BMI was casually associated with CKD (OR: 2.58; 95% CI, 1.39-4.79) and arterial stiffness (OR: 1.87; 95% CI, 1.24-2.81) in the inverse-variance weighted analysis, and MR-Egger regression revealed no evidence of horizontal pleiotropy (both P for intercept ≥ .34). The causality between obesity and CKD was validated in 2-sample MR analysis among Europeans (681 275 of Genetic Investigation of ANthropometric Traits and 133 413 of CKD Genetics). Conclusion: This study provided novel insights into the causality of obesity with CKD and arterial stiffness, highlighting the importance of weight management for primary prevention and control of subclinical vascular diseases. [ABSTRACT FROM AUTHOR]

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.

BackgroundHeart failure (HF), primarily caused by conditions such as coronary heart disease or cardiomyopathy, is a global health problem with poor prognosis and heavy burden on healthcare systems. As biomarkers of myocardial injury and fibrosis, suppression of tumorigenicity 2 (ST2) and galectin-3 were recommended for prognosis stratification in HF guidelines. However, the causality between these two mediators and HF remains obscure. This study aimed to explore the causal relationship of genetically determined ST2 and galectin-3 with the risk of HF.MethodsWe used the two-sample Mendelian randomization (MR) method, incorporating available genome-wide association summary statistics, to investigate the causal association of ST2 and galectin-3 with HF risk. We applied inverse-variance weighted analysis as the main method of analysis.ResultsIn our final MR analysis, 4 single-nucleotide polymorphisms (SNPs) of ST2 and galectin-3, respectively, were identified as valid instrumental variables. Fixed-effect inverse variance weighted (IVW) analysis indicated that genetically predicted ST2 and galectin-3 were not causally associated with HF risk 3. [odds ratio (OR) = 0.9999, 95% confidence interval [CI] = 0.9994–1.0004, p = 0.73; OR = 1.0002, 95% CI = 0.9994–1.0010, p = 0.60, respectively]. These findings were robust in sensitivity analyses, including MR-Egger regression and leave-one-out analysis.ConclusionThis MR study provided no evidence for the causal effects of ST2 and galectin-3 on HF risk.

BackgroundObservational studies suggested that multiple sclerosis (MS) is associated with cardiovascular diseases (CVDs). However, the causal association has not been fully elucidated. Thus, we aim to assess the causality of the associations of MS with risk of CVDs.MethodsA two-sample Mendelian randomization (MR) study was performed to explore the causality. Genetic instruments were identified for MS from a genome-wide association study (GWAS) involving 115,803 individuals. Summary-level data for CVDs were obtained from different GWAS meta-analysis studies. MR analysis was conducted mainly using the inverse-variance weighted (IVW) method. Sensitivity analyses were further performed to ensure the robustness of the results.ResultsThis MR study found suggestive evidence that genetic liability to MS was associated with an increased risk of coronary artery disease (CAD) [odds ratio (OR), 1.02; 95% confidence interval (CI), 1.00–1.04; p = 0.03], myocardial infarction (MI) (OR, 1.03; 95% CI, 1.00–1.06; p = 0.01), heart failure (HF) (OR, 1.02; 95% CI, 1.00–1.04; p = 0.02), all-cause stroke (AS) (OR, 1.02; 95% CI, 1.00–1.05; p = 0.02), and any ischemic stroke (AIS) (OR, 1.02; 95% CI, 1.00–1.05; p = 0.04). The null-association was observed between MS and the other CVDs. Further analyses found little evidence of pleiotropy.ConclusionsWe provided suggestive genetic evidence for the causal associations of MS with increased risk of CAD, MI, HF, AS, and AIS, which highlighted the significance of active monitoring and prevention of cardiovascular risk to combat cardiovascular comorbidities in MS patients.

Background: The association reported between tea intake and type 2 diabetes (T2D) is inconsistent in previous studies and remains controversial. We aimed to explore the causal relationship between tea intake, T2D, and glycemic traits including hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), fasting serum insulin (FSI), and homeostasis model of insulin resistance (HOMA-IR) levels.Methods: A 2-sample Mendelian randomization (MR) was performed using summary statistics from large-scale genome-wide association studies of tea intake from the UK Biobank, T2D from the DIAGRAM consortium, and glycemic traits from the Magic consortium. The findings were verified through sensitivity analyses using various MR methods with different model assumptions and by comprehensively evaluating the influence of pleiotropy effects and outliers.Results: With the use of a two-sample MR with inverse variance-weighted method, the odds ratio per unit SD change of tea intake (SD: 2.85 cups/day) for T2D, HbA1c, FPG, FSI, and HOMA-IR levels was 0.949 (95% CI 0.844–1.067, p = 0.383), 0.994 (95% CI 0.975–1.013, p = 0.554), 0.996 (95% CI 0.978–1.015, p = 0.703), 0.968 (95% CI 0.948–0.986, p = 0.001), and 0.953 (95% CI 0.900–1.009, p = 0.102), respectively. The results were consistent with those of the other six methods that we used with different model assumptions, suggesting that the findings were robust and convincing. We also performed various sensitivity analyses for outlier removal, pleiotropy detection, and leave-one-out analysis.Conclusion: Our MR results did not support the causal effect of tea intake on T2D and crucial glycemic traits. These findings suggest that previous observational studies may have been confounded.

Background: Low intelligence has been shown to be associated with a high risk of cardiovascular disease in observational studies. It remains unclear whether the association is causal. This study aimed to explore the causal association of intelligence with coronary artery disease (CAD) and myocardial infarction (MI).Methods: A two-sample Mendelian randomization study was designed to infer the causality. A total of 121 single nucleotide polymorphisms were selected as a genetic instrumental variable for intelligence. Summary data on CAD (n = 184,305) and MI (n = 171,875) were obtained from the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis (CARDIoGRAM) plus The Coronary Artery Disease (C4D) Genetics (CARDIoGRAMplusC4D) consortium and the FinnGen study. Inverse variance weighting method was used to calculate the effect estimates. Sensitivity analyses including other statistical models and leave-one-out analysis were conducted to verify the robustness of results. MR-Egger test was performed to assess the pleiotropy.Results: Genetically predicted higher intelligence was significantly associated with lower risk of CAD (OR, .76; 95%CI, .69–.85; p = 1.5 × 10–7) and MI (OR, .78; 95%CI, .70–.87; p = 7.9 × 10–6). The results remained consistent in the majority of the sensitivity analyses and were repeated in the FinnGen datasets. MR-Egger test suggested no evidence of directional pleiotropy for the association with coronary artery disease (intercept = −.01, p = .19) and myocardial infarction (intercept = −.01, p = .06).Conclusion: This Mendelian randomization analysis provided genetic evidence for the causal association between low intelligence and increased risks of CAD and MI.

Evidence from observational studies for the effect of tea consumption on obesity is inconclusive. This study aimed to verify the causal association between tea consumption and obesity through a two-sample Mendelian randomization (MR) analysis in general population-based datasets. The genetic instruments, single nucleotide polymorphisms (SNPs) associated with tea consumption habits, were obtained from genome-wide association studies (GWAS): UK Biobank, Nurses’ Health Study, Health Professionals Follow-up Study, and Women’s Genome Health Study. The effect of the genetic instruments on obesity was analyzed using the UK Biobank dataset (among ∼500,000 participants). The causal relationship between tea consumption and obesity was analyzed by five methods of MR analyses: inverse variance weighted (IVW) method, MR-Egger regression method, weighted median estimator (WME), weighted mode, and simple mode. Ninety-one SNPs were identified as genetic instruments in our study. A mild causation was found by IVW (odds ratio [OR] = 0.998, 95% confidence interval [CI] = 0.996 to 1.000, p = 0.049]), which is commonly used in two-sample MR analysis, indicating that tea consumption has a statistically significant but medically weak effect on obesity control. However, the other four approaches did not show significance. Since there was no heterogeneity and pleiotropy in this study, the IVW approach has the priority of recommendation. Further studies are needed to clarify the effects of tea consumption on obesity-related health problems in detail.

Background and Objectives: The precise impact of tea consumption on the risk of depression remains unclear. This study aimed to explore the relationship between the consumption patterns of tea and the likelihood of depression onset, utilizing a two-sample Mendelian randomization (MR) methodology., Methods and Study Design: We utilized available genome-wide association study (GWAS) datasets on tea intake and depressive disorders. To investigate the causal relationship between tea consumption and depression, we employed a set of two-sample Mendelian Randomization (MR) methods. These included the inverse-variance weighted (IVW) analysis, weighted median approach, and MR-Egger regression. Additionally, we utilized MR-PRESSO and the MR-Egger intercept test for the detection of pleiotropic effects. To ensure the robustness and consistency of our findings, a sensitivity analysis was carried out, applying the 'leave-one-out' strategy. The Bayesian weighted Mendelian randomization (BWMR) was employed to conduct additional testing on the obtained results., Results: The study's outcomes revealed a causal association between increased tea intake and an increased risk of depression (Inverse-Variance Weighted Analysis: Odds Ratio [OR] = 1.029, 95% Confidence Interval [CI]: 1.003-1.055, p = 0.027). This was observed despite variations in instrumental variables and the nonexistence of horizontal pleiotropy. Furthermore, the robustness of our Mendelian Randomization investigation was affirmed through the implementation of the 'leave-one-out' method in our sensitivity analysis. The findings from BWMR were in line with those obtained from IVW (BWMR: OR=1.030, 95% CI: 1.003-1.057, p = 0.029)., Conclusions: The results from this study indicate a substantial and positive causal link between the regularity of tea drinking and the risk of depression onset., Competing Interests: All authors declare no relationships with companies that might have an interest in the submitted work in the previous three years; and no non-financial interests that may be relevant to the submitted work

Background: Previous studies have suggested a potential association between irritability and the risk of various diseases. However, establishing a causal relationship has remained a significant challenge. To address this issue, we employed Mendelian randomization (MR), a sophisticated approach that leverages genotype data to emulate the conditions of randomized controlled trials. This method enables us to investigate the potential causal link between irritability and the susceptibility to esophageal diseases., Methods: We conducted an extensive multivariable MR analysis using summary-level data from genome-wide association studies (GWAS) encompassing various esophageal diseases, including gastroesophageal reflux disease (GERD), esophageal cancer (EC), and Barrett's esophagus. Both univariable and multivariable MR analyses were performed to elucidate and confirm the causal association between genetically predicted irritability and the incidence of esophageal diseases., Results: Based on our primary causal effects model utilizing MR analyses with the inverse-variance weighted (IVW) method, genetically predicted irritability was identified as a risk factor for GERD (OR = 2.413; 95 % CI: 1.678-3.470; P = 2.03E-06) and Barrett's esophagus (OR = 2.306; 95 % CI: 1.042-5.101; P = 0.039). However, irritability was not found to be associated with the risk of EC, even after adjusting for BMI, smoking initiation, and alcohol consumption., Conclusion: The multivariable MR analysis performed in this study demonstrated a causal relationship between irritability and esophageal diseases. It is imperative to acknowledge the need for further large-scale prospective studies to validate these findings., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Observational studies have suggested a correlation between hyperuricemia and pulmonary arterial hypertension (PAH), yet the causal relationship remains uncertain. We aimed to establish this link using Mendelian Randomization (MR) methods., Objectives: Based on publicly accessible data, our study employs MR to determine the causal relationship between uric acid (UA) and PAH., Method: MR analysis was conducted among individuals of European descent. Genetic instruments linked to UA (p-value < 5 × 10 -8 ) were extracted from the Chronic Kidney Disease Genetic Consortium and genome-wide association study databases. PAH risk genetic associations were sourced separately. We employed four MR methods (MR-Egger, weighted median, inverse variance weighted, and weighted mode) with selected instrumental variables to assess the causal association between UA and PAH. MR-PRESSO was used to evaluate pleiotropy and outlier Single Nucleotide Polymorphisms (SNPs), while Cochran's Q test and funnel plot assessed SNP heterogeneity. Leave-one-out analysis examined SNP impacts on causal assessment., Result: Two-sample MR analysis revealed a positive, causal relationship between UA levels and PAH., Conclusion: Our MR analysis provides robust evidence of a causal link between serum UA and PAH, suggesting UA's potential as a biomarker and therapeutic target for PAH., Competing Interests: Declaration of competing interest The authors declare that there are no financial interests or personal relationships that could have appeared to influence the work reported in this paper. All authors have contributed to this research and concur with the content of the manuscript., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Osteoarthritis (OA) is a common degenerative disease that affects millions of individuals worldwide., Objective: There is no conclusive epidemiological evidence regarding the relationship between OA, depression, and whole-body fat mass. In this study, we conducted a two-step Mendelian randomization analysis to determine the causal relationships between them., Design: The published summary-level data are from genome-wide association studies (GWAS). Our study included 357,957 samples and 10,828,862 SNPs. Finally, the outcome GWAS data for OA came from a GWAS on the genetic architecture of OA using UK Biobank data. This study included 50,508 samples and 15,845,511 SNPs. We used five different modes of analysis, including inverse variance weighted meta-analysis (IVW), MR-Egger regression, weighted median, simple mode, and weighted mode, to explore causal relationships., Results: We found a positive correlation between depression and body fat mass, with depression leading to body fat mass an increase in (IVW result: p = 3.39E-07, OR (95 % CI) =2.16 (1.61, 2.90)). We also found a positive correlation between body fat mass and OA, with body fat mass increasing the risk of OA (IVW result: p = 1.65E-33, OR (95 % CI) = 1.98 (1.77, 2.21). Body fat mass played an important role as a mediator in the causal relationship between depression and OA, with approximately 14 % of the risk of OA caused by depression being mediated by body fat mass., Conclusions: Our study offers reliable evidence that depression has a detrimental impact on the risk of OA. Future research can support these associations from improving depressed effect, including social, biological, and behavioral factors, to reduce the risk of chronic diseases such as osteoarthritis. And we identified high-risk variation of alleles which associated with OA and depression can be used to predict disease and provide a basis for clinical intervention and treatment of OA., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024. Published by Elsevier B.V.)

Background and Aims: Coffee consumption has been suggested to increase the risk of migraine. However, causality remains inconclusive. In the present study, we performed a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between coffee consumption and migraine. Methods: We obtained nine single-nucleotide polymorphisms (SNPs) associated with coffee consumption at genome-wide significance (p < 5 × 10−8) from a large genome-wide association study (GWAS) based on the UK Biobank study (included 375,833 individuals). Summary-level data for any migraine (AM) and its subtypes (migraine with aura (MA) and migraine without aura (MO)) were obtained from the largest available GWAS of migraine conducted by the International Headache Genetics Consortium (IHGC) (included 59,674 cases and 316,078 controls). MR estimates were pooled using fixed-effect inverse-variance weighted (IVW) as the main method. Sensitivity analyses were further performed using weighted median, MR-Egger, and MR-PRESSO to assess the robustness of our findings. Results: Genetically-predicted 50% increase of coffee consumption was not causally associated with the risk of AM (odds ratio (OR), 0.97; 95% confidence interval (CI), 0.83–1.14; p = 0.71), MA (OR, 0.81; 95%CI, 0.58, 1.12; p = 0.19), or MO (OR, 0.97; 95%CI, 0.72, 1.30; p = 0.83) in the fixed-effect IVW methods. Sensitivity analyses returned similar results. No directional pleiotropy was found. Conclusion: This MR study does not support a causal relationship between genetically predicted coffee consumption and the risk of migraine. Coffee consumption is likely not a trigger nor a prevention strategy for migraine headaches. [ABSTRACT FROM AUTHOR]

Background: Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear. Genome-wide association studies (GWASs) offer an unprecedented opportunity to untangle the relationship between metabolites and NDDs. Methods: By leveraging two-sample Mendelian randomization (MR) approaches and relying on GWASs summary statistics, we here explore the causal association between 486 metabolites and five NDDs including Alzheimer's Disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Parkinson's disease (PD), and multiple sclerosis (MS). We validated our MR results with extensive sensitive analyses including MR-PRESSO and MR-Egger regression. We also performed linkage disequilibrium score regression (LDSC) and colocalization analyses to distinguish causal metabolite-NDD associations from genetic correlation and LD confounding of shared causal genetic variants. Finally, a metabolic pathway analysis was further conducted to identify potential metabolite pathways. Results: We detected 164 metabolites which were suggestively associated with the risk of NDDs. Particularly, 2-methoxyacetaminophen sulfate substantially affected ALS (OR = 0.971, 95%CIs: 0.961 ∼ 0.982, FDR = 1.04E-4) and FTD (OR = 0.924, 95%CIs: 0.885 ∼ 0.964, FDR = 0.048), and X-11529 (OR = 1.604, 95%CIs: 1.250 ∼ 2.059, FDR = 0.048) and X-13429 (OR = 2.284, 95%CIs: 1.457 ∼ 3.581, FDR = 0.048) significantly impacted FTD. These associations were further confirmed by the weighted median and maximum likelihood methods, with MR-PRESSO and the MR-Egger regression removing the possibility of pleiotropy. We also observed that ALS or FTD can alter the metabolite levels, including ALS and FTD on 2-methoxyacetaminophen sulfate. The LDSC and colocalization analyses showed that none of the identified associations could be driven by genetic correlation or confounding by LD with common causal loci. Multiple metabolic pathways were found to be involved in NDDs, such as "urea cycle" (P = 0.036), "arginine biosynthesis" (P = 0.004) on AD and "phenylalanine, tyrosine and tryptophan biosynthesis" (P = 0.046) on ALS. Conclusion: our study reveals robust bidirectional causal associations between servaral metabolites and neurodegenerative diseases, and provides a novel insight into metabolic mechanism for pathogenesis and therapeutic strategies of these diseases. [ABSTRACT FROM AUTHOR]

Background : Whether a gluten-free diet (GFD) is a cause of irritable bowel syndrome (IBS) remains controversial. We aim at exploring the causal relationship between gluten intake and IBS within Mendelian randomization (MR) design. Methods: We conducted a two-sample MR and selected single-nucleotide polymorphisms (SNPs) associated with GFD as instrumental variables (IVs). SNPs and genetic associations with GFD and IBS were obtained from the latest genome-wide association studies (GWAS) in Europeans (GFD: cases: 1,376; controls: 63,573; IBS: cases:1,121; controls: 360,073). We performed inverse variance weighting (IVW) as the primary method with several sensitivity analyses like MR-Egger and MR-PRESSO for quality control. The above analyses were re-run using another large dataset of IBS, as well as changing the p -value threshold when screening IVs, to verify the stability of the results. Results: The final estimate indicated significant causal association [per one copy of effect allele predicted log odds ratio (OR) change in GFD intake: OR = 0.97, 95% confidence interval (CI) 0.96 to 0.99, p < 0.01] without heterogeneity statistically (Q = 2.48, p = 0.78) nor horizontal pleiotropy biasing the causality (p = 0.92). Consistent results were found in validation analyses. Results of MR Steiger directionality test indicated the accuracy of our estimate of the causal direction (Steiger p < 0.001). Conclusion: GFD might be a protective factor of IBS. Therefore, we suggest taking a diet of lower gluten intake into account in IBS prevention and clinical practice. [ABSTRACT FROM AUTHOR]

Background: The interactions and associations between insomnia, depressive symptoms, and subjective well-being are complex, thus it is hard to explore the effect and direction of causalities. This bidirectional Mendelian randomization (MR) study was to assess the causal associations of insomnia with depressive symptoms and subjective well-being.Methods: Summary statistics for insomnia, depressive symptoms, and subjective well-being were obtained from three large-scale genome-wide association studies (GWAS) of European ancestry. MR analyses were mainly conducted with the inverse-variance-weighted (IVW) method. The weighted-median method, MR-Egger method, and MR-Pleiotropy RESidual Sum and Outlier (PRESSO) test were adopted to test whether the estimates were robust. The adjusted MR analysis was performed to avoid the effect of potential pleiotropy.Results: There was evidence to support a causal association between genetically predicted insomnia and depressive symptoms (beta (β) = 0.086, 95% confidence interval (CI) = 0.068 to 0.104, P = 8.6E-21). Meanwhile, genetically predicted depressive symptoms was associated with a higher risk of insomnia (β = 0.543, 95% CI = 0.331 to 0.754, P = 4.8E-07). Genetically predicted insomnia was negatively associated with subjective well-being (β = -0.043, 95% CI = -0.063 to -0.024, P = 1.2E-05). There was evidence of reverse causality between insomnia and subjective well-being (β = -0.821, 95% CI = -1.012 to -0.630, P = 4.0E-17).Conclusions: MR analysis indicates bidirectional causal associations of insomnia with depressive symptoms and subjective well-being. People should give serious attention to and attempt to resolve the problems of insomnia, depressive symptoms, and subjective well-being, whichever comes first. [ABSTRACT FROM AUTHOR]