Simple Mode Research Articles

Causality of genetically determined blood metabolites on inflammatory bowel disease: a two-sample Mendelian randomization study

Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disease of the gastrointestinal tract, including two subtypes: Crohn’s disease (CD) and ulcerative colitis (UC). Metabolic disorders are important factors in the development of IBD. However, the evidence for the causal relationship between blood metabolites and IBD remains limited. A two-sample MR analysis was applied to evaluate relationships between 486 blood metabolites and IBD. The inverse variance weighted method was chosen as the primary MR analysis method. False discovery rate correction was used to control for false positives in multiple testing. Following complementary and sensitivity analyses were conducted using methods such as weight median, MR-egger, weighted mode, simple mode, Cochran Q test, and MR-PRESSO. Moreover, we performed replication, meta-analysis, Steiger test, and linkage disequilibrium score regression to enhance the robustness of the results. Additionally, we performed metabolic pathway analysis to identify potential metabolic pathways. As a result, we identified four significant causal associations between four blood metabolites and two IBD subtypes. Specifically, one metabolite was identified as being associated with the development of CD (mannose: odds ratio (OR) = 0.19, 95% confidence interval (CI) 0.08–0.43, P = 8.54 × 10–5). Three metabolites were identified as being associated with the development of UC (arachidonate (20:4n6): OR = 0.18, 95% CI 0.11–0.30, P = 2.09 × 10–11; 1, 5-anhydroglucitol: OR = 2.21, 95% CI 1.47–3.34, P = 1.50 × 10–4; 2-stearoylglycerophosphocholine: OR = 2.66, 95% CI 1.53–4.63, P = 5.30 × 10–4). The findings of our study suggested that the identified metabolites and metabolic pathways can be considered as useful circulating metabolic biomarkers for the screening and prevention of IBD in clinical practice, as well as candidate molecules for future mechanism exploration and drug target selection.

Causal association between air pollution and allergic rhinitis, asthma: a Mendelian randomization study.

Observational studies suggest that air pollutants, including particulate matter and nitrogen compounds, could elevate asthma and allergic rhinitis health risks. Nevertheless, the exact nature of the causal relationship between air pollution and asthma and allergic rhinitis remains unknown. This study utilizes the Mendelian randomization (MR) technique to explore the potential causal links between air pollution components (PM2.5, PM2.5-10, PM10, NO₂, and nitrogen dioxide) and the incidence of allergic rhinitis and asthma. A MR study utilized summary statistics from GWAS that are publicly accessible. The inverse variance weighting (IVW) approach served as the foundational analysis technique. To ensure robustness, supplementary methodologies such as the weighted median, MR-Egger regression, simple mode, and weighted model were also applied. Heterogeneity was evaluated using Cochran's Q test, and the presence of pleiotropy was determined through MR-Egger regression. The MR-PRESSO test was employed for outlier detection, and the analysis's sensitivity was scrutinized via a leave-one-out strategy. The IVW technique showed a strong correlation between PM10 and asthma (OR = 0.625, 95% CI = 0.396-0.988, p = 0.044). No significant associations were found between asthma and other air pollutants such as PM2.5, PM2.5-10, NO₂, or nitrogen dioxide. Similarly, allergic rhinitis showed no causal relationships with any studied air pollution metrics. Pleiotropy was absent in the findings. Sensitivity analyses, employing the leave-one-out method, confirmed the stability of these results, unaffected by individual single nucleotide polymorphisms (SNPs). This Mendelian randomization study establishes a causal link between PM10 exposure and asthma, suggesting that interventions to reduce air pollution may decelerate the adverse progression of asthma.

Causal relationship between C-reactive protein and ischemic stroke caused by atherosclerosis: A Mendelian randomization study

ObjectivesThis study investigates the association between C-reactive protein (CRP) and ischemic stroke caused by large artery atherosclerosis (LAA). MethodsFive Mendelian Randomization (MR) methodologies were used for two-sample analyses: Inverse Variance Weighting (IVW), MR-Egger regression, Weighted Median (WM), Simple Mode, and Weighted Mode. CRP exposure data were obtained from aggregated summary statistics from a meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry (n = 343,524; UK Biobank). Stroke data were used as the outcome, with specific dataset details for relevant subtypes (cases = 40,585, controls = 406,111). ResultsIn the CRP GWAS dataset, selected single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) showed genome-wide significance and a causal relationship with CRP, particularly in relation to LAA stroke. IVW indicated a robust causal connection between CRP and LAA stroke (Beta = 0.151, SE = 0.055, P = 0.006). The WM approach supported this relationship (Beta = 0.176, SE = 0.082, P = 0.033). However, MR-Egger regression suggested a potential absence of a causal link (Beta = 0.098, SE = 0.077, P = 0.206), with minimal influence from horizontal pleiotropy (Intercept = 0.0029; P = 0.317). The Simple mode found no significant association (Beta = 0.046, SE = 0.217, P = 0.834), while the Weighted mode revealed a significant causal association (Beta = 0.138, SE = 0.059, P = 0.020) between CRP and LAA stroke. ConclusionsMR analysis provides evidence for a potential causal relationship between CRP and an increased risk of LAA stroke.

Does metformin really reduce prostate cancer risk: an up-to-date comprehensive genome-wide analysis

BackgroundThe relationship between metformin use and prostate cancer (PCa) risk has yet to be clear despite more than a decade of debate on this topic. Hence, we aimed to investigate the causal role of metformin in reducing PCa risk through an up-to-date comprehensive genome-wide analysis.MethodsWe employed validated instrument variables of metformin use derived from a prior high-quality study, including five potential targets (AMPK, GCG, GDF15, MCI and MG3). Mendelian randomization (MR) analysis was performed to harmonize genetically predicted metformin use and PCa phenotypes. PCa phenotypes were from two large genome-wide association studies (GWAS), the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) and the FinnGen cohort. Seven methods were applied to generate MR results: the inverse variance weighted (IVW), IVW with multiplicative random effects, MR-Egger, MR-Egger (bootstrap), weighted median, simple mode and weighted mode. Strict sensitivity analysis was conducted to satisfy core assumptions of MR design.ResultsWe enrolled 32 significant single nucleotide polymorphisms (SNPs) that involved with metformin use. Nearly all targets yielded insignificant primary results (IVW with multiplicative random effects), except that AMPK target posed a positive effect on PCa risk from FinnGen cohort [odds ratio (OR): 6.09, 95% confidence interval (CI): 1.10-33.53, P value: 0.038]. The general effect of metformin use, comprising all 5 targets, also yielded negative results (random-effect meta-analysis with OR: 1.09, 95% CI: 0.76–1.58, P value: 0.637 for PRACTICAL; OR: 2.55, 95% CI: 0.58–11.16, P value: 0.215 for FinnGen). None of the sensitivity analyses provided support for a causal association between metformin use and PCa risk.ConclusionThis up-to-date study did not support the protective role of metformin in reducing PCa risk, considering each target, overall effect, and sensitivity analysis. It is imperative to reflect on the presumed “almighty medicine” and ongoing phase III trials are anticipated to assess the anti-neoplasm effect of metformin.

The causal relationship of depression, anxiety, and neuroticism with endometriosis: A bidirectional 2-sample Mendelian randomization study.

Endometriosis, identified by the abnormal growth of endometrial cells beyond the inner lining of the uterus, often manifests through symptoms like painful menstruation and challenges in conceiving. Observational studies suggest that endometriosis is often comorbid with mental disorders, including anxiety and depression. The nature of these connections, whether they are causal, is still debated and calls for further empirical evidence. We utilized a bidirectional 2-sample Mendelian randomization (MR) approach, harnessing genome-wide association study data to explore the connections among depression, anxiety, neuroticism, and endometriosis. To scrutinize the causative connections between mental health issues and endometriosis, Inverse Variance Weighting (IVW) was employed as the primary analytical tool, complemented by Weighted Median Estimation, Simple mode, Weighted mode, and MR-Egger regression for additional analysis. To examine the potential for reverse causation, reverse MR was applied. To strengthen the reliability of our findings, we carried out sensitivity analyses that included heterogeneity tests, tests for pleiotropy, and leave-one-out analyses. The IVW analysis revealed a significant correlation between the genetic inclination towards depression and a heightened risk of developing endometriosis [Odds Ratio (OR) = 1.151, 95% Confidence Interval (CI) = 1.025-1.293, P = .017]. Similarly, a genetic predisposition to neuroticism was significantly associated with an increased risk of endometriosis (OR = 1.128, 95% CI = 1.038-1.226, P = .004). However, no causative link was found between genetic susceptibility to anxiety and the occurrence of endometriosis. Reverse MR analysis did not support a bidirectional genetic susceptibility between endometriosis and psychiatric disorders. The MR analysis presents genetic data supporting the notion that depression and neuroticism are risk factors for endometriosis. Conversely, it found no evidence of a causal connection between anxiety and the development of endometriosis. Enhancing mental health treatment should be considered a preventive measure against endometriosis.

Causal relationship between inflammatory markers and left ventricle geometry and function: A 2-sample Mendelian randomization study.

Studies have shown that some inflammatory markers can predict the risk of cardiovascular disease (CVD) and affect the structure and function of the heart. However, a causal relationship between inflammatory markers and the cardiac structure and function has not yet been established. Thus, we conducted a 2-sample Mendelian randomization (MR) study to explore the potential causal relationship between inflammatory markers and prognostically-related left ventricular (LV) parameters. Instrumental variables (IVs) for C-reactive protein (CRP), interleukin-6 (IL-6), and myeloperoxidase (MPO) levels were selected from the databases of large genome-wide association studies (GWAS). Summary statistics for LV parameters, including LV mass, ejection fraction, end-diastolic and systolic volumes, and the ratio of LV mass to end-diastolic volume, were obtained from cardiovascular magnetic resonance studies of the UK Biobank (n = 16923). The inverse-variance weighted (IVW) method was the primary analytical method used, and was complemented with the MR-Egger, weighted median, simple mode, weighted mode, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods. Sensitivity analysis was performed to evaluate the robustness of the results. CRP was significantly associated with the LV mass in the IVW method (β = -0.13 g [95% confidence interval [CI], 0.78 g-1.00 g], P = .046). A higher standard deviation of genetically-predicted CRP levels was associated with a 0.13 ± 0.06 g lower LV mass. No causal relationships of IL-6 and MPO with LV parameters were found. No evidence of heterogeneity and pleiotropy was detected. Sensitivity analyses confirmed the robustness of the results. Two-sample MR analysis revealed a causal association between increased CRP level and decreased LV mass, whereas IL-6 and MPO levels did not influence the LV parameters. However, further research is required to validate our findings.

Association between serum total cholesterol and the development of gastric cancer: A two-way two-sample Mendelian randomization study.

Previous epidemiologic studies have suggested a potential negative correlation between total cholesterol (TC) and Gastric cancer (GC); however, several observational studies have shown conflicting results and have failed to provide definitive evidence for a causal relationship between TC and GC. Therefore, we conducted a 2-sample bidirectional Mendelian randomization (MR) study to explore the genetic correlation and potential causal relationship between the 2 variables. We screened for single nucleotide polymorphisms (SNPs) associated with TC and GC utilizing a large-scale genome-wide association study (GWAS) public database. The causal relationship was analyzed using 5 MR analysis methods: inverse variance weighting (IVW), weighted median, MR-Egger regression, weighted mode, and simple mode. Additionally, reverse MR analysis was performed to evaluate the possibility of reverse causality. Sensitivity analyses were conducted, including heterogeneity tests, horizontal multiple validity tests, and leave-one-out tests. After meticulous screening, 79 SNPs were identified as instrumental variables (IVs). The IVW method revealed a causal relationship between TC and GC (OR = 0.844; 95% CI: 0.741-0.961; P = .01). Sensitivity analyses did not detect significant horizontal pleiotropy. Though heterogeneity was observed in the forward MR analysis (IVW, Qp = 0.0006), the results remained reliable as we utilized the IVW random-effects model as the primary analytical method. Furthermore, inverse MR analysis found no evidence of reverse causality between TC and GC, effectively ruling out the influence of GC on the reverse causality of TC. Our MR study provided evidence of a causal association between TC and GC, suggesting that TC acts as a protective factor against GC due to its negative association with the disease.

Exploring causal correlations between inflammatory cytokines and intervertebral disc degeneration: A Mendelian randomization.

Inflammatory cytokines have been reported to be related to intervertebral disc degeneration (IVDD) in several previous studies. However, it remains unclear about the causal relationship between inflammatory cytokines and IVDD. This study employs Mendelian randomization (MR) to analyze the causal link between inflammatory cytokines and the risk of IVDD. We used genetic variants associated with inflammatory cytokines from a meta-analysis of genome-wide association study (GWAS) in 8293 Finns as instrumental variables and IVDD data were sourced from the FinnGen consortium. The main analytical approach utilized Inverse-Variance Weighting (IVW) with random effects to assess the causal relationship. Additionally, complementary methods such as MR-Egger, weighted median, simple mode, weighted mode, and MR pleiotropy residual sum and outlier were employed to enhance the robustness of the final results. We found interferon-gamma (IFN-γ, p = 2.14 × 10-6, OR = 0.870, 95% CI = 0.821-0.921), interleukin-1 beta (IL-1b, p = 0.012, OR = 0.951, 95% CI = 0.914-0.989), interleukin-4 (IL-4, p = 0.034, OR = 0.946, 95% CI = 0.899-0.996), interleukin-18 (IL-18, p = 0.028, OR = 0.964, 95% CI = 0.934-0.996), granulocyte colony-stimulating factor (GCSF, p = 0.010, OR = 0.919, 95% CI = 0.861-0.980), and Stromal cell-derived factor 1a (SDF1a, p = 0.014, OR = 1.072, 95% CI = 1.014-1.134) were causally associated with risk of IVDD. Our MR analyses found a potential causal relationship between six inflammation cytokines (IFN-γ, IL-1b, IL-4, IL-18, SDF1a, and GCSF) and altered IVDD risk.

Genetically predicted 1091 blood metabolites and 309 metabolite ratios in relation to risk of type 2 diabetes: a Mendelian randomization study.

Metabolic dysregulation represents a defining characteristic of Type 2 diabetes (T2DM). Nevertheless, there remains an absence of substantial evidence establishing a direct causal link between circulating blood metabolites and the promotion or prevention of T2DM. In addressing this gap, we employed Mendelian randomization (MR) analysis to investigate the potential causal association between 1,091 blood metabolites, 309 metabolite ratios, and the occurrence of T2DM. Data encompassing single-nucleotide polymorphisms (SNPs) for 1,091 blood metabolites and 309 metabolite ratios were extracted from a Canadian Genome-wide association study (GWAS) involving 8,299 participants. To evaluate the causal link between these metabolites and Type 2 diabetes (T2DM), multiple methods including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode were employed. p-values underwent correction utilizing False Discovery Rates (FDR). Sensitivity analyses incorporated Cochran's Q test, MR-Egger intercept test, MR-PRESSO, Steiger test, leave-one-out analysis, and single SNP analysis. The causal effects were visualized via Circos plot, forest plot, and scatter plot. Furthermore, for noteworthy, an independent T2DM GWAS dataset (GCST006867) was utilized for replication analysis. Metabolic pathway analysis of closely correlated metabolites was conducted using MetaboAnalyst 5.0. The IVW analysis method utilized in this study revealed 88 blood metabolites and 37 metabolite ratios demonstrating a significant causal relationship with T2DM (p < 0.05). Notably, strong causal associations with T2DM were observed for specific metabolites: 1-linoleoyl-GPE (18:2) (IVW: OR:0.930, 95% CI: 0.899-0.962, p = 2.16 × 10-5), 1,2-dilinoleoyl-GPE (18:2/18:2) (IVW: OR:0.942, 95% CI: 0.917-0.968, p = 1.64 × 10-5), Mannose (IVW: OR:1.133, 95% CI: 1.072-1.197, p = 1.02 × 10-5), X-21829 (IVW: OR:1.036, 95% CI: 1.036-1.122, p = 9.44 × 10-5), and Phosphate to mannose ratio (IVW: OR:0.870, 95% CI: 0.818-0.926, p = 1.29 × 10-5, FDR = 0.008). Additionally, metabolic pathway analysis highlighted six significant pathways associated with T2DM development: Valine, leucine and isoleucine biosynthesis, Phenylalanine metabolism, Glycerophospholipid metabolism, Alpha-Linolenic acid metabolism, Sphingolipid metabolism, and Alanine, aspartate, and glutamate metabolism. This study identifies both protective and risk-associated metabolites that play a causal role in the development of T2DM. By integrating genomics and metabolomics, it presents novel insights into the pathogenesis of T2DM. These findings hold potential implications for early screening, preventive measures, and treatment strategies for T2DM.

Causal inference of the effect of blood proteome on the risk of head and neck cancer: two-sample Mendelian randomization

Early diagnosis of head and neck cancer can improve therapeutic outcomes but remains a challenge. The blood proteome can comprise a key source of biomarkers that enable the early diagnosis and precision medicine in head and neck cancer, but blood protein biomarkers of head and neck cancer are not well delineated. Here we applied two-sample Mendelian randomization to a GWAS dataset of 1478 blood proteins and large dataset of head and neck cancer cases and controls to identify blood proteome traits associated with head and neck cancer. Multiple two-sample Mendelian randomization (MR) methods were used to assess causal effects of the exposures, including: Inverse-variance weighted (IVW), Mendelian randomization-Egger method, Weight Median method, simple mode, weight mode. Sensitivity analysis was performed by using heterogeneity test, pleiotropy test and one-by-one exclusion test. Multivariable MR analyses were performed to assess the effects of obesity, diabetes mellitus, and smoking. A significant causal association between A Disintegrin and metalloproteinase domain-containing protein 23 (ADAM23) and head and neck cancer was noted. The sensitivity analysis indicated no significant bias. Multivariate analysis showed that the effect for ADAM23 remained significant after adjusting for the indirect effects of obesity, diabetes mellitus and smoking. In sum, this study showed a significant causal role of genetically dysregulated ADAM23 protein with head and neck cancer risk. The specific mechanisms underlying the role of ADAM23 in mediating head and neck cancer risk, and its role as a potential therapeutic target and biomarker, need further investigation.

Borderline personality disorder and risk of atrial fibrillation: insights from a bidirectional Mendelian randomization study.

Atrial fibrillation (AF) is one of the most common form of arrhythmia. Previous studies have shown a link between AF and mental illness. However, the causal relationship between mental illness and AF remains unclear. The purpose of this study was to investigate the bidirectional causal relationship between borderline personality disorder (BPD) and AF. We used the bidirectional Two-sample Mendelian randomization (TSMR) method to evaluate the causal relationship between BPD and AF. Instrumental variables associated with BPD were derived from a genome-wide association study involving 214,816 Europeans (2,637 cases and 212,179 controls). We then obtained atrial fibrillation data from the GWAS meta-analysis (60,620 cases and 970,216 controls). The TSMR analyses were performed in five methods, namely fixed-effect inverse-variance weighted (IVW) method、random-effect IVW method, MR Egger regression method, Weighted median method and Simple mode method. Several sensitivity analyses are used to test the robustness of positive results. The fixed-effect inverse-variance weighted model [Odds ratio (OR), 1.033, 95% confidence interval (CI), 1.011-1.056, P = 0.0031], random-effect inverse-variance weighted model (OR, 1.033; 95%CI, 1.005-1.062; P = 0.0191) and Weighted median (OR, 1.034; 95%CI, 1.002-1.068; P = 0.0394) all showed that genetically predicted BPD was associated with an increased risk of AF. Sensitivity analysis using other MR Methods, including the MR-Egger intercept, MR-Presso method, and leave-one-out analyses, showed that the results were robust. In reverse MR analysis, there was no causal relationship of AF on BPD. Our study provides a causal relationship between BPD and AF. This means that patients with BPD should be monitored for the occurrence of AF. Early screening and proper management of BPD may show anti-arrhythmic benefits.

A bidirectional two-sample Mendelian randomization study to evaluate the relationship between psoriasis and interstitial lung diseases

BackgroundPrior observational studies have suggested a potential direct link between psoriasis (PSO) and interstitial lung disease (ILD). Consequently, we applied Mendelian randomization (MR) to further evaluate the bidirectional causal relationships between PSO and its different phenotypes [psoriatic arthritis (PSA)/psoriasis vulgaris (PSV)] and ILD.MethodsData regarding PSO/PSA/PSV and ILD were sourced from publicly accessible genome-wide association studies (GWAS) databases, focusing on European populations. We used five algorithms— MR Egger, weighted median, inverse-variance weighted (IVW), simple mode, and weighted mode— to evaluate the causal relationships between PSO/PSA/PSV and ILD, with a primary emphasis on the IVW method.ResultsThe analysis indicated a potential association between PSA and an elevated risk of ILD [IVW odds ratio (OR): 1.035 (95% CI 1.008, 1.064; P = 0.012)], with no evidence of a direct relationship between total PSO and PSV with ILD. Conversely, no substantial evidence emerged from the reverse MR analysis to suggest that ILD significantly affects total PSO or the specific PSA/PSV phenotypes.ConclusionOur findings provide genetic evidence supporting the notion that PSA may be a contributory risk factor for ILD. Further investigations are warranted to explore the underlying mechanisms of this potential causal relationship between PSA and ILD.

The Causal Relationship Between Skin Microbiota and Facial Aging: A Mendelian Randomization Study.

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 .

Associations of Circulating Biomarkers with Disease Risks: A Two-Sample Mendelian Randomization Study.

Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Here, we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR-Egger. We use the MR-base resource (v0.5.6) from Hemani et al. 2018 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan). We report novel causal relationships found by four or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in four or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction. This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.

The role of gut microbiota in prostate cancer progression: A Mendelian randomization study of immune mediation.

The potential relationship between the gut microbiota and prostate cancer, possibly influenced by immune cells, remains unclear. This study employed the mediation Mendelian randomization (MR) technique to investigate the causal link between the gut microbiota, immune cells, and prostate cancer. Data on immune cell activity were sourced from Valeria Orrù's research, whereas the genome-wide association study outcome dataset was obtained from the Integrative Epidemiology Unit database. The bidirectional MR analysis utilized 5 different methods: inverse variance weighted (IVW), weighted median, MR-Egger regression, weighted mode, and simple mode. In addition, the mediating effect of immune cells on the gut microbiota and prostate cancer was explored using mediation analysis. Eighty-three single nucleotide polymorphisms associated with prostate cancer were screened as instrumental variables. In a positive MR analysis with gut microbiota as the exposure factor, IVW showed an association between 8 gut microbiota and prostate cancer. Additionally, 9 types of immune cells have been found to be associated with prostate cancer using methods such as IVW. MR analysis of the gut microbiota on immune cells (beta1) revealed a negative correlation between Bifidobacterium and CD39+ T regulatory cells (Tregs; odds ratio [OR] = 0.785, 95% confidence interval [CI] = 0.627-0.983, P = .03). Furthermore, MR analysis of immune cells in prostate cancer disease (beta2) showed that CD39+Tregs are a risk factor for prostate cancer (OR = 1.215, 95% CI = 1.027-1.354, P = .04). Moreover, MR analysis of gut microbiota in prostate cancer (total effect) indicated that Bifidobacterium is a protective factor for prostate cancer (OR = 0.905, 95% CI = 0.822-0.977, P = .04). The sensitivity analysis verified the robustness of the above results. Mediation analysis demonstrated that CD39+Tregs partially mediate the causal relationship between Bifidobacterium and prostate cancer. This study demonstrates that Bifidobacterium inhibits prostate cancer progression through CD39+Tregs as mediators, providing new ideas and approaches for the treatment and prevention of prostate cancer.

Causal relationship between bone mineral density and intervertebral disc degeneration: a univariate and multivariable mendelian randomization study

BackgroundAlthough previous studies have suggested a possible association between bone mineral density (BMD) and intervertebral disc degeneration (IDD), the causal relationship between them remains unclear. Evidence from accumulating studies indicates that they might mutually influence one another. However, observational studies may be affected by potential confounders. Meanwhile, Mendelian randomization (MR) study can overcome these confounders to assess causality.ObjectivesThis Mendelian randomization (MR) study aimed to explore the causal effect of bone mineral density (BMD) on intervertebral disc degeneration (IDD).MethodsSummary data from genome-wide association studies of bone mineral density (BMD) and IDD (the FinnGen biobank) have been acquired. The inverse variance weighted (IVW) method was utilized as the primary MR analysis approach. Weighted median, MR-Egger regression, weighted mode, and simple mode were used as supplements. The Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression were performed to assess horizontal pleiotropy. Cochran’s Q test evaluated heterogeneity. Leave-one-out sensitivity analysis was further conducted to determine the reliability of the causal relationship. Multivariate MR (MVMR) analyses used multivariable inverse variance-weighted methods to individually and jointly adjust for four potential confounders, body mass index (BMI), Type2 diabetes, hyperthyroidism and smoking. A reverse MR analysis was conducted to assess potential reverse causation.ResultsIn the univariate MR analysis, femoral neck bone mineral density (FNBMD), heel bone mineral density (eBMD), lumbar spine bone mineral density (LSBMD), and total body bone mineral density (TB BMD) had a direct causal effect on intervertebral disc degeneration (IDD) [FNBMD-related analysis: OR(95%CI) = 1.17 (1.04 to 1.31), p = 0.008, eBMD-related analysis: OR(95%CI) = 1.06 (1.01 to 1.12), p = 0.028, LSBMD-related analysis: OR(95%CI) = 1.20 (1.10 to 1.31), p = 3.38E-7,TB BMD-related analysis: OR(95%CI) = 1.20 (1.12 to 1.29), p = 1.0E-8]. In the MVMR analysis, it was revealed that, even after controlling for confounding factors, heel bone mineral density (eBMD), lumbar spine bone mineral density (LSBMD), and total body bone mineral density (TB BMD) still maintained an independent and significant causal association with IDD(Adjusting for heel bone mineral density: beta = 0.073, OR95% CI = 1.08(1.02 to 1.14), P = 0.013; Adjusting for lumbar spine bone mineral density: beta = 0.11, OR(95%CI) = 1.12(1.02 to 1.23), P = 0.03; Adjusting for total body bone mineral density: beta = 0.139, OR95% CI = 1.15(1.06 to 1.24), P = 5.53E − 5). In the reverse analysis, no evidence was found to suggest that IDD has an impact on BMD.ConclusionsThe findings from our univariate and multivariable Mendelian randomization analysis establish a substantial positive causal association between BMD and IDD, indicating that higher bone mineral density may be a significant risk factor for intervertebral disc degeneration. Notably, no causal effect of IDD on these four measures of bone mineral density was observed. Further research is required to elucidate the underlying mechanisms governing this causal relationship.

Body shape from birth to adulthood is associated with skeletal development: A Mendelian randomization study

BackgroundObservational studies have shown that childhood obesity is associated with adult bone health but yield inconsistent results. We aimed to explore the potential causal association between body shape and skeletal development. MethodsWe used two-sample Mendelian randomization (MR) to estimate causal relationships between body shape from birth to adulthood and skeletal phenotypes, with exposures including placental weight, birth weight, childhood obesity, BMI, lean mass, fat mass, waist circumference, and hip circumference. Independent genetic instruments associated with the exposures at the genome-wide significance level (P < 5 × 10−8) were selected from corresponding large-scale genome-wide association studies. The inverse-variance weighted analysis was chosen as the primary method, and complementary MR analyses included the weighted median, MR-Egger, weighted mode, and simple mode. ResultsThe MR analysis shows strong evidence that childhood (β = −1.29 × 10−3, P = 8.61 × 10−5) and adulthood BMI (β = −1.28 × 10−3, P = 1.45 × 10−10) were associated with humerus length. Tibiofemoral angle was negatively associated with childhood BMI (β = −3.60 × 10−1, P = 3.00 × 10−5) and adolescent BMI (β = −3.62 × 10−1, P = 2.68 × 10−3). In addition, genetically predicted levels of appendicular lean mass (β = 1.16 × 10−3, P = 1.49 × 10−13), whole body fat mass (β = 1.66 × 10−3, P = 1.35 × 10−9), waist circumference (β = 1.72 × 10−3, P = 6.93 × 10−8) and hip circumference (β =1.28 × 10−3, P = 4.34 × 10−6) were all associated with tibia length. However, we found no causal association between placental weight, birth weight and bone length/width. ConclusionsThis large-scale MR analysis explores changes in growth patterns in the length/width of major bone sites, highlighting the important role of childhood body shape in bone development and providing insights into factors that may drive bone maturation.

Relationship between Sjogren's syndrome and gastroesophageal reflux: A bidirectional Mendelian randomization study

The clinical incidence of sjogren's syndrome combined with gastroesophageal reflux disease is high. Existing observational studies have shown inconsistent results in the association between gastroesophageal reflux disease (GERD) and Sjogren's syndrome (SS).We observed that the symptoms of SS patients also improved after receiving GERD-related treatment. Therefore, we aimed to investigate the relationship between GERD and SS through a bidirectional two-sample Mendelian randomization (MR) study. Independent SNPs associated with GERD and SS were selected from a genome-wide association study (GWAS) as instrumental variables to conduct a bidirectional two-sample Mendelian analysis of GERD and SS. Genetic data were obtained from two databases for the following two outcomes: Gastroesophageal reflux (IEU Open GWAS) [sample size = 602,604 (patients = 129,080; nonpatients = 473,524)] and SS (FinnGen) [sample size = 392,423 (patients = 2,495; nonpatients = 389,928)]. Statistical methods for the MR analysis included the inverse-variance weighting method, weighted median, simple mode and weighted mode, as well as heterogeneity and sensitivity analyses using the Cochran Q statistic, MR‒Egger regression, outlier detection methods (MR-PRESSO). In addition, Steiger Test was conducted to test the direction of causality. MR analysis showed a positive correlation between GERD and SS risk [odds ratio (OR) = 1.3279 (95% confidence interval 1.0312–1.7099, P = 0.0280)]. However, in contrast, no significant causal effect of SS on GERD was observed [OR = 1.0024 (95% CI 0.9651–1.0412; P = 0.8995)]. This bidirectional two-sample Mendelian randomization study confirmed a causal relationship between SS and GERD, and suggested that GERD is a risk factor for SS, while SS does not affect GERD.

Causal Involvement of Immune Cells in Chronic Obstructive Pulmonary Disease: A Mendelian Randomization Study.

The immune cells play a substantial role in the development and progression of chronic obstructive pulmonary disease (COPD). We aim to investigate the causal involvement of immune cells in COPD via a Mendelian randomization (MR) analysis. Published genome-wide association studies (GWAS) statistics on immune cells were analyzed, with genetic variants identified as instrumental variables (IVs). Inverse-variance weighting (IVW), weighted median, and MR-Egger regression methods were employed, along with simple mode and weighted mode adopted in the two-sample MR analysis. Sensitivity analysis was conducted to examine the heterogeneity, horizontal pleiotropy, and stability of the causal relationship. IVW results suggested that CCR2 on CD62L+ plasmacytoid dendritic cells (DC), CCR2 on plasmacytoid DC, CD11b on CD66b++ myeloid cells, CD19 on CD20- CD38- CD24+ memory B cell subset, CD25 on transitional B cells, and CD25++CD8br %CD8br T cells were risk factors for the development of COPD. Besides, CD127 on effector memory-like cytotoxic T lymphocytes lacking expression of co-stimulatory molecule 28 (CD28-EM CTLs) and HLA DR+ NK ACs expressing human leukocyte antigen DR molecules while being natural killer cells (%NK ACs) were protective factors for COPD. This study unveiled a causal relationship between immune cell phenotype and COPD. These findings offer new insights for the prevention and treatment of COPD using COPD-associated immune cells.

Associations of Circulating Biomarkers with Disease Risks: a Two-Sample Mendelian Randomization Study.

Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Here we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR Egger. We use the MR-base resource (v0.5.6)1 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016)2-4 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan). We report novel causal relationships found by 4 or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in 4 or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction. This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.