Causal analysis of the impact of serum 25-hydroxyvitamin D levels on laryngeal cancer: A two-sample mendelian randomization study.

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

It has been shown that people with type 2 diabetes have a higher risk of synovitis and tenosynovitis, but previous studies were mainly observational, which may be biased and does not allow for a cause-and-effect relationship. Therefore, we conducted a two-sample Mendelian randomization (MR) study to investigate the causal relationship. We obtained data on "type 2 diabetes" and "synovitis, tenosynovitis" from published large-scale genome-wide association studies (GWAS). The data were obtained from the FinnGen consortium and UK Biobank, both from European population samples. We used three methods to perform a two-sample MR analysis and also performed sensitivity analysis. The results of all three MR methods we used for the analysis illustrated that T2DM increases the risk factor for the development of synovitis and tenosynovitis. Specifically, for the IVW method as the primary analysis outcome, OR = 1.0015 (95% CI, 1.0005 to 1.0026), P = 0.0047; for the MR Egger method as the supplementary analysis outcome, OR = 1.0032 (95% CI, 1.0007 to 1.0056), P = 0.0161; for the weighted median method, OR = 1.0022 (95% CI, 1.0008 to 1.0037), p = 0.0018. In addition, the results of our sensitivity analysis suggest the absence of heterogeneity and pleiotropy in our MR analysis. In conclusion, the results of our MR analysis suggest that T2DM is an independent risk factor for increased synovitis and tenosynovitis.

Breast cancer is a common cancer type that leads to cancer-related deaths among women. HER2-positive breast cancer, in particular, is associated with poor prognosis due to its high aggressiveness, increased risk of recurrence, and metastasis potential. Previous observational studies have explored potential associations between inflammatory cytokines and the risk of two breast cancer subtypes (HER2-positive and HER2-negative), but the results have been inconsistent. To further elucidate the causal relationship between inflammatory cytokines and the two breast cancer subtypes, we conducted a two-sample Mendelian randomization (MR) study. We employed a two-sample bidirectional MR analysis using publicly available genome-wide association study (GWAS) statistics. After obtaining instrumental variables, we conducted MR analyses using five different methods to ensure the reliability of our results. Additionally, we performed tests for heterogeneity and horizontal pleiotropy. Subsequently, we conducted a reverse MR study by reversing exposure and outcome variables. Evidence from our IVW analysis revealed that genetically predicted levels of IL-5 [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.04-1.35, P = 0.012], IL-7 (OR: 1.11, 95% CI: 1.01-1.22, P = 0.037), and IL-16 (OR: 1.13, 95% CI: 1.02-1.25, P = 0.025) were associated with an increased risk of HER2-positive breast cancer. Conversely, IL-10 (OR: 1.14, 95% CI: 1.03-1.26, P = 0.012) was associated with an increased risk of HER2-negative breast cancer. These results showed no evidence of heterogeneity or horizontal pleiotropy (P > 0.05). Results from the reverse MR analysis indicated no potential causal association between breast cancer and inflammatory cytokines (P > 0.05). Our findings demonstrate that IL-5, IL-7, and IL-16 are risk factors for HER2-positive breast cancer, with varying degrees of increased probability of HER2-positive breast cancer associated with elevated levels of these inflammatory cytokines. Conversely, IL-10 is a risk factor for HER2-negative breast cancer. Reverse studies have confirmed that breast cancer is not a risk factor for elevated levels of inflammatory cytokines. This series of results clarifies the causal relationship between different types of inflammatory cytokines and different subtypes of breast cancer. Based on this research, potential directions for the mechanism research of different inflammatory cytokines and different subtypes of breast cancer have been provided, and potential genetic basis for identifying and treating different subtypes of breast cancer have been suggested.

Investigating the causal association between heme oxygenase-1 and asthma: A bidirectional two-sample Mendelian randomization analysis in a European population

Genetic proxy of lipid-lowering drugs and calcific aortic valve stenosis: A Mendelian randomization study

BackgroundIn some observational studies, attention-deficit/hyperactivity disorder has been linked to allergic diseases, but the findings are debatable. This study aimed to determine whether attention-deficit/hyperactivity disorder (ADHD) is causally related to allergic asthma, allergic rhinitis, pollen allergy, allergic urticaria, and allergic conjunctivitis using the two-sample Mendelian Randomization (MR) approach.MethodsWe did a two-sample Mendelian randomization (MR) study, which chose single nucleotide polymorphisms (SNPs) that are highly associated with attention-deficit/hyperactivity disorder (ADHD) levels from the Psychiatric Genomics Consortium (PGC) on 20,183 cases and 35,191 controls as our instruments. Outcomes datasets included genome-wide association study (GWAS) meta-analysis (n = 1,415,804). The summary statistics of outcome data were obtained from the FinnGen datasets including allergic asthma (10,877 cases and 180,942 controls), allergic rhinitis (8,430 cases and 298,829 controls), pollen allergy (4555cases and 301,734 controls), allergic urticaria (1792 cases and 299,491 controls) and allergic conjunctivitis (15,567 cases and 293,587 controls). Inverse variance weighted, MR-Egger, weighted median, were used to estimate the causal association between ADHD and allergic diseases. Cochran’s Q test was used to quantify the heterogeneity of instrumental variables. MR-Egger intercept test, leave-one-out analysis, and the funnel plot were all used in sensitivity analyses.ResultsThe Mendelian randomization (MR) analysis indicated that ADHD in inverse variance weighted [odds ratio (OR) = 1.0612; 95% confidence interval (CI):1.0192–1.1049; p = 0.0039] lightly increased the risk of allergic asthma. In MR sensitivity analyses of the weighted median, a similar association was found. But no evidence for an effect of ADHD on allergic asthma risk was found in additional methods: MR-Egger (OR = 0.9592, 95% CI: 0.8384–1.0974, p = 0.5457), and weighted median (OR: =1.0341, 95% CI: 0.9785–1.0929, p = 0.2330). Also, no strong evidence for an effect of ADHD on other allergic diseases (allergic rhinitis, pollen allergy, allergic urticaria, and allergic conjunctivitis) incidence was found using the inverse variance weighted (IVW) method, weighted median method, and MR-Egger regression.ConclusionAlthough several studies have found a link between ADHD and allergic diseases, our findings do not support that ADHD could increase allergic diseases incidence. Randomized controlled trials or Mendelian randomization studies with larger samples are still needed to draw more precise conclusions.

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.

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.

Effects of genetically determined mineral status on life expectancy: a Mendelian randomization study.

Assessing causal relationship between non-alcoholic fatty liver disease and risk of atrial fibrillation

The connection between appendiceal disease and cancers of the digestive tract has attracted widespread attention, but conclusion remain controversial. It is still unclear whether appendiceal disease has a definite causal effect on cancer. Our research aims to explore the causal relationship between appendiceal diseases and digestive system tumors. A two-sample Mendelian randomization (MR) analysis was conducted using genome-wide association study datasets to explore the causal impact of appendiceal disease on the risk of cancers. Five different MR methods were used to investigate causality. The stability, heterogeneity, and pleiotropy of MR were also assessed. The presence of appendiceal disease could reduce the incidence of rectal cancer (odds ratio = 0.588, 95% confidence interval: 0.392–0.881, P = .010, by inverse variance weighted method). There was no significant causal effect of appendiceal disease on the risk of other cancers. No horizontal pleiotropy was observed in the MR analysis, and leave-one-out analysis confirmed the stability of the results. The potential causal relationship between appendiceal disease and cancer risk was only observed with rectal cancer in populations of European ancestry. Future work will provide more robust evidence for the connection between appendiceal disease and cancers.

Previous studies have reported a complex relationship between inflammatory cytokines and kidney stone disease (KSD). The purpose of this paper is to investigate the potential causal impact of inflammatory cytokines on KSD by Mendelian randomization (MR) analysis. In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between inflammatory cytokines and kidney stone disease. Utilizing GWAS summary data of inflammatory cytokines and KSD, we performed the first two-sample MR analysis. Genetic variants in GWASs related to inflammatory cytokines were employed as instrumental variables (IVs). The data on cytokines were derived from 14,824 participants and analyzed by utilizing the Olink Target-96 Inflammation Panel. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Reverse MR analysis, Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results. 91 cytokines were enrolled in the MR analysis after strict quality control of IV. The IVW analysis revealed 2 cytokines as risk factors for KSD: Cystatin D (OR 1.06, 95% CI 1.01-1.11), Fibroblast growth factor 5 (OR 1.06, 95% CI 1.00-1.12), suggesting they are positively associated with the occurrence of kidney stones. We also found 3 protective associations between cytokines and KSD: Artemin (OR 0.86, 95% CI 0.78-0.96), T-cell surface glycoprotein CD6 isoform (OR 0.92, 95% CI 0.88-0.98), STAM-binding protein (OR 0.83, 95% CI 0.69-0.99). There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our MR Egger's intercept test, Cochrane Q-test, and MR-PRESSO, which were all > 0.05. Our study explored a variety of inflammatory cytokines related to KSD through MR analysis, which validated several previous findings and provided some new potential biomarkers for KSD. However, the findings require further investigation to validate their exact functions in the pathogenesis and evolution of KSD.

Background: Obesity is a well-established risk factor for atrial fibrillation (AF). Previous epidemiological research on obesity and AF often focused on adult populations and now broadened to earlier in life. Therefore, this study aimed to determine the relationships between obesity at different periods of life and the risk of AF.Methods: A two-sample Mendelian randomization (MR) study design using summarised data from 6 genome-wide association studies (GWASs) was employed in this study. Single nucleotide polymorphisms (SNPs) associated with adult obesity, childhood obesity, childhood body mass index (BMI), waist-to-hip ratio adjusted for BMI (WHRadjBMI), birth weight and AF were independently retrieved from large-scale GWASs. For SNP identification, the genome-wide significance threshold was set at p <5.00×10-8. To obtain causal estimates, MR analysis was conducted using the inverse variance-weighted (IVW) method. The weighted median, MR-Egger methods and MR-robust adjusted profile score (MR-RAPS) were used to evaluate the robustness of MR analysis.Results: A total of 204 SNPs were identified as the genetic instrumental variables (5 SNPs for childhood obesity, 13 SNPs for childhood BMI, 137 SNPs for birth weight, 35 SNPs for adult WHRadjBMI, and 14 SNPs for adult obesity). The results of MR analysis demonstrated that the genetically predicted adult obesity, childhood BMI, and birth weight were associated with AF risk. Notably, a 1 unit standard deviation (1-SD) increase in adult obesity was related to a 13% increased risk of AF [p=6.51×10-7, OR, 1.13 (95% CI, 1.08-1.19)], a 1-SD increase in childhood BMI was related to a 18% increased risk of AF [p=1.77×10-4, OR, 1.18 (95% CI, 1.08-1.29)], and a 1-SD increase in birth weight was related to a 26% increased risk of AF [p=1.27×10-7, OR, 1.26 (95% CI, 1.16-1.37)]. There was no evidence of pleiotropy or heterogeneity between the MR estimates obtained from multiple SNPs.Conclusion: Our study reveals the association of genetic susceptibility to obesity with a higher risk of AF. Moreover, an earlier age at obesity was associated with an increased risk of AF. Therefore, public awareness of the dangers of obesity and active early weight control may prevent the development of AF.

Facial aging is a complex process influenced by environmental factors, genetics, and lifestyle. The contribution of the skin microbiota to this process remains poorly understood. This two-sample Mendelian randomization (MR) study was performed using genome-wide genotype data from the UK Biobank and previously published studies on skin microbiota. The primary approach for MR analyses included inverse-variance weighting (IVW), MR-Egger regression, simple mode, weighted median, and weighted mode methods. Sensitivity analyses were performed to assess heterogeneity and pleiotropy, and reverse-direction MR analyses were performed to evaluate potential reverse causation. The MR analysis identified ten skin microbiotas with potential causal relationships with facial aging. Protective skin microbiotas included Genus Finegoldia, ASV011 [Staphylococcus (unc.)], ASV008 [Staphylococcus (unc.)], phylum Firmicutes, Family Rhodobacteraceae, and ASV021 [Micrococcus (unc.)], which were negatively associated with facial aging. Conversely, Order Pseudomonadales, Family Moraxellaceae, ASV039 [Acinetobacter (unc.)], and phylum Bacteroidetes were positively associated with facial aging, indicating a risk factor for accelerated aging. Sensitivity analyses confirmed the robustness of these findings, and reverse-direction MR analyses did not suggest any reverse causation. This study identified specific skin microbial that may influence facial aging and offered new insights into the rejuvenation strategies. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Alzheimer's disease (AD) is an increasing public health concern with the aging of the global population. Understanding the genetic correlation and potential causal relationships between blood metabolites and AD may provide important insights into the metabolic dysregulation underlying this neurodegenerative disorder. The aim of this study was to investigate the causal relationship between blood metabolites and AD using Mendelian randomization (MR) analysis. Association data were obtained from three large-scale genome-wide association studies of 486 blood metabolites (N = 7,824), AD (71,880 cases and 383,378 controls), early-onset AD (N = 303,760), and late-onset AD (N = 307,112). Causal associations between blood metabolites and AD were assessed using inverse variance weighting (IVW), MR-Egger, and weighted median methods. Bidirectional two-sample MR analysis was used to identify causal blood metabolites. MR-PRESSO, MR-Egger, and Cochran-Q were used to quantify instrumental variable heterogeneity and horizontal pleiotropy. Using MR and sensitivity analysis, we identified 40 blood metabolites with potential causal associations with AD. After applying false discovery rate (FDR) correction, two metabolites, gamma-glutamylphenylalanine (OR = 1.15, 95% CI: 1.06-1.24, p = 3.88×10-4, q = 0.09) and X-11317 (OR = 1.16, 95% CI: 1.08-1.26, p = 1.14×10-4, q = 0.05), retained significant associations with AD. Reverse MR analysis indicated no significant causal effect of AD on blood metabolites. No significant instrumental variable heterogeneity or horizontal pleiotropy was found. This two-sample MR study provides compelling evidence for a potential causal relationship between blood metabolic dysregulation and susceptibility to AD. Further investigation of the biological relevance of the identified metabolites to AD and additional supporting evidence is warranted.