Bidirectional Mendelian Randomization Analysis Research Articles

Genetically Predicted Immune Cell-Mediated Effect of Lipid Metabolism on Allergic Diseases: A Two-Step, Mediation Mendelian Randomization Study

Introduction: An increasing number of studies have demonstrated that dynamic changes in lipid species can affect allergic diseases; however, the causal relationship and mediating role of immune cells remain unclear. Methods: We conducted a bidirectional two-sample mendelian randomization (MR) analysis using genome-wide association study (GWAS) data on 179 lipid species (n = 7,174) and three types of allergic diseases including allergic rhinitis (AR) (n = 370,158), allergic asthma (n = 219,753), and allergic conjunctivitis (n = 377,277). The principal model used was the inverse variance-weighted approach, and a series of sensitivity analyses were conducted to ensure the robustness of the results. We used a two-step MR approach to assess whether the causal effect was mediated by immune cells (n = 3,757). Results: Sterol ester and sphingomyelin played pathogenic roles in allergic asthma, AR, and allergic conjunctivitis; however, the effective subtypes differed. Among them, CD45RA− CD4+ mature T cells and CCR2 on CD14+ CD16+ monocytes affected the promoting impact of sterol ester’s metabolism on allergic asthma and AR with different mediating proportions, while the role of sphingomyelin may not involve the immune cells. Moreover, we observed that HLA-DR on CD33− HLA DR+ myeloid cells, CD11b on CD66b++ myeloid cells, and IgD+ CD38− B cells played the most mediating effect of phosphatidylethanolamine (O−18:2_20:4) in allergic asthma, phosphatidylinositol (16:0_18:1) in AR, and phosphatidylethanolamine (18:0_18:2) in allergic conjunctivitis. Conclusion: This MR study provides evidence for specific lipid species associated with the risk of allergic diseases, especially sterol esters, and identifies the immune cells that mediate this causal relationship.

Association between immune cells and urticaria: a bidirectional Mendelian randomization study

Urticaria is characterized by transient itchy symptoms on the skin, usually accompanied by swelling, which is caused by mast cell activation leading to increased vascular permeability and dilation of the dermis. Urticaria involves recurrent activation of mast cells, T cells, eosinophils, and other immune cells around lesioned venules, with complex regulatory systems affecting mast cell functions, potentially contributing to urticaria pathogenesis. The direct causal relationship between immune cells and urticaria is currently unclear. To address this, our study utilized a bidirectional Mendelian randomization analysis, employing instrumental variables (IVs) associated with immune cells and urticaria, to investigate this causal relationship. First, by utilizing Genome-wide Association Study (GWAS) data, we identified 31 immunophenotypes associated with urticaria risk, with 18 increasing and 13 decreasing the risk. Through rigorous criteria, we identified 4 immunophenotypes that have a strong causal relationship with urticaria. Notably, HLA DR+ CD4+AC, CD45 on CD8br, and HLA DR on plasmacytoid dendritic cells were associated with an increased risk, while CD8dim NKT %lymphocyte was identified as a protective factor. Sensitivity analyses, including the MR-Egger intercept test, scatter plots, funnel plots, and leave-one-out analysis, supported the robustness of the findings. Reverse MR analysis suggested an inverse causal effect of urticaria on CD8dim NKT %lymphocyte, reinforcing the potential bidirectional nature of the relationship between urticaria and immune cell phenotypes. Our research substantiates the bidirectional causal relationship between immune cells and urticaria, thus benefiting for urticaria-targeted therapy development.

Gastroesophageal reflux disease increases predisposition to severe COVID‐19: Insights from integrated Mendelian randomization and genetic analysis

AbstractObjectiveThis study aims to investigate the potential causal relationship, shared genomic loci, as well as potential molecular pathways and tissue‐specific expression patterns between gastroesophageal reflux disease (GERD) and the risk of hospitalized/severe 2019 coronavirus disease (COVID‐19).MethodsWe employed linkage disequilibrium score regression and bidirectional Mendelian randomization (MR) analysis to explore potential genetic associations between GERD (N = 602,604) and hospitalized COVID‐19 (N = 2095,324) as well as severe COVID‐19 (N = 1086,211). Additionally, shared genomic loci were extracted from common pivotal regions, further confirmed through corresponding colocalization analyses. GERD‐driven molecular pathway network was constructed using extensive literature data mining to understand the molecular‐level impacts of GERD on COVID‐19.ResultsOur results revealed a significant positive genetic correlation between GERD and both hospitalized (rg = 0.418) and severe COVID‐19 (rg = 0.314). Furthermore, the MR analysis demonstrated a unidirectional causal effect of genetic predisposition to GERD on COVID‐19 outcomes, including hospitalized COVID‐19 (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.27–1.44, p = 9.17e − 12) and severe COVID‐19 (OR: 1.27, 95% CI: 1.18–1.37, p = 1.20e − 05). Additionally, GERD and both COVID‐19 conditions shared one genomic locus with lead‐SNPs rs1011407 and rs1123573, corresponding to the transcription factor BCL11A. Colocalization analysis further demonstrated a significant positive correlation between genome‐wide association study and expression quantitative trait locus (eQTL) abnormalities, including rs1011407 (eQTL_p = 2.35e − 07) and rs1123573 (eQTL_p = 2.74e − 05). Molecular pathway analysis indicated that GERD might promote the progression of COVID‐19 by inducting immune‐activated and inflammation‐related pathways.ConclusionThese findings confirm that genetically determined GERD may increase the susceptibility to hospitalized/severe COVID‐19. The shared genetic loci and the potential molecular pathways offer valuable insights into causal connections between GERD and COVID‐19.

Shared genetic architecture of psychiatric disorders and hemorrhoidal disease: a large-scale genome-wide cross-trait analysis

BackgroundThe genetic association between psychiatric disorders and hemorrhoidal disease (HEM) is still not well known. The work aims to investigate their comorbidity at a genetic level.MethodsUtilizing recent large-scale genome-wide association studies (GWAS), we investigated the genetic overlap at the single nucleotide polymorphism (SNP), gene, and molecular level between depression and HEM, bipolar disorder (BD) and HEM, neuroticism and HEM, as well as schizophrenia (SCZ) and HEM. The cross-trait genes were validated through the utilization of transcriptome and proteome methodologies. The causal link was assessed using bidirectional two-sample Mendelian randomization analysis (MR) analysis. MRlap corrects for the potential bias in estimation caused by sample overlap.ResultsWe discovered significant positive genetic associations between these four types of psychiatric disorders and HEM. Cross-phenotypic association analyses identified shared SNPs along with 17 specific loci between psychiatric disorders and HEM. MAGMA identified a total of 2304 pleiotropic genes, several of which showed significant expression in the results of transcriptome and proteome analyses. We observed that these genes are mostly associated with the regulation of transcription factors and particular DNA binding activities. Lastly, MR analysis provided evidence supporting a correlation between these conditions.ConclusionThis study revealed a genetic correlation between four psychiatric disorders and HEM, identified pleiotropic loci, found multiple candidate genes, and confirmed causal relationships. This has enhanced our comprehension of the common genetic mechanisms of psychiatric disorders and HEM.

Assessing the causal role of the structural connectome in temporomandibular disorders: A Mendelian randomization study

ABSTRACT Objective We examined the relationships between the structural connectome and temporomandibular disorders (TMDs). Methods Bidirectional Mendelian randomization analyses were conducted using Genome-wide association studies data on the structural connectome and TMDs. Results Positive associations with TMD risk were found for white matter structural connectivity from the left hemisphere limbic network to putamen, left hemisphere salience_ventral attention network to caudate, right hemisphere visual network to thalamus, and right hemisphere salience_ventral attention network to right hemisphere control network, while negative associations were observed for connectivity from the left hemisphere control and somatomotor networks to pallidum, left hemisphere somatomotor network to right hemisphere dorsal attention network, and right hemisphere somatomotor network to hippocampus (p< 0.05). In TMD patients, connectivity from the Left-hemisphere visual network to putamen was reduced, whereas connectivity from the Left-hemisphere limbic network to left-hemisphere control network was increased (p< 0.05). Conclusion Our findings provide insights into the TMD pathogenesis.

Serum vitamin C levels and risk of osteoporosis: results from a cross-sectional study and Mendelian randomization analysis

BackgroundThe role of vitamin C as an antioxidant in guarding against osteoporosis in adults is still debated. This research employs both a cross-sectional study and a two-sample bidirectional Mendelian randomization (MR) analysis to explore how serum vitamin C levels correlate with the incidence of osteoporosis among adults.MethodsIn this study, we utilized data from the National Health and Nutrition Examination Survey (NHANES) database for the years 2003–2006, and 2017–2018 to conduct both a cross-sectional analysis and MR to investigate the relationship between serum vitamin C levels and the risk of osteoporosis in adults. We adjusted our analyses for essential demographic and lifestyle variables, and applied logistic regression techniques. Genetic determinants of vitamin C levels were analyzed through MR, using methods like inverse-variance weighted (IVW) and MR-Egger to assess causality. Statistical computations were carried out in R, incorporating visual tools such as restricted cubic spline curves (RCS) and forest plots to clarify the dose–response dynamics and variations across different subgroups. This study was approved by the NCHS Ethics Review Board, and informed consent was obtained from all participants.ResultsIn our investigation, we analyzed data from 3,940 participants, among whom 291 were diagnosed with osteoporosis. The logistic regression analysis of serum vitamin C quartiles did not indicate a significant trend. The most adjusted model showed a slight, albeit inconsistent, protective effect in the highest quartile (OR = 0.68, 95% CI: 0.47–0.99, P = 0.22). Mendelian randomization, employing methods such as IVW, reinforced the absence of a significant causal relationship between serum vitamin C levels and osteoporosis risk (IVW OR = 1.000, 95% CI: 0.999–1.001, P = 0.601).Subgroup analyses, visualized through forest plots and restricted cubic spline (RCS) curves, supported the primary findings, showing no significant effects or interactions between vitamin C levels and osteoporosis risk across different demographic and lifestyle subgroups. The RCS analysis particularly highlighted a lack of significant non-linear relationships between serum vitamin C concentration and the odds of osteoporosis (P for nonlinear = 0.840).ConclusionsThe cross-sectional study revealed that higher serum vitamin C levels do not consistently correlate with a reduced risk of osteoporosis. Meanwhile, the Mendelian randomization analysis confirmed that there is no genetic evidence to suggest a causal relationship between vitamin C levels and osteoporosis risk. Recent research highlights the polygenic nature of osteoporosis, with genetic predispositions playing a significant role in disease risk. The relationship between serum vitamin C and osteoporosis requires further research. This suggests the need for further investigation into the connection between vitamin C and bone health.

Association between gut microbiota, plasma metabolites, and ovarian cancer: A Mendelian randomization study

Numerous studies have demonstrated a correlation between alterations in gut microbiota (GM) and levels of body metabolites in ovarian cancer (OC). However, the specific causal relationships underlying these associations remain unclear. This study utilized summary statistics of GM from the MiBioGen consortium, along with an unprecedented dataset comprising 1091 blood metabolites and 309 metabolite ratios from the UK Biobank, in conjunction with OC data from the FinnGen Consortium R9 release. We conducted bidirectional Mendelian randomization (MR) analyses to investigate the causal relationships between GM and OC. Additionally, a two-step MR approach was employed to identify potential mediating metabolites. Our analysis revealed significant associations between 6 specific microbiota taxa and OC. Furthermore, we identified several plasma metabolites that act as mediators of the association between GM and OC. In the two-step MR analysis, we observed a negative correlation between 4-methoxyphenol sulfate and pregnenetriol disulfate levels with OC. The genus Lachnospiraceae UCG008 potentially increases the risk of OC by decreasing 4-methoxyphenol sulfate levels, while the genus Howardella may elevate the risk of OC by reducing pregnenetriol disulfate levels, with mediation proportions of 22.35% and 4.23%, respectively. Additionally, levels of dilinoleoyl-GPE (18:2/18:2) and N-acetylkynurenine (2) were positively correlated with OC. The inhibitory effect of the genus Ruminococcus 1 on OC may be mediated through 1,2-dilinoleoyl-GPE (18:2/18:2) and N-acetylkynurenine (2), with mediation proportions of 10.15% and 11.32%, respectively. Our findings highlight the complex relationship among GM, plasma metabolites, and OC. The identified associations and mediation effects offer valuable insights into potential therapeutic approaches targeting GM for the management of OC.

Exploring causal associations between dietary intake and liver diseases: A bidirectional Mendelian randomization study

Previous evidence suggests that dietary intake can affect liver diseases; However, the causal relationship between dietary intake and liver diseases remains unclear. To investigate this, we conducted a bidirectional Mendelian randomization (MR) analysis to comprehensively assess the potential causal relationship between dietary intake and liver diseases. Two-sample bidirectional MR was performed based on genome-wide association studies summary data from the UK Biobank and FinnGen database. The primary analysis method for evaluating causal relationships was inverse-variance weighted. Supplementary analyses included MR-Egger and weighted median methods. Subsequently, sensitivity analyses were performed using Cochran Q test, MR-Egger intercept test, MR-PRESSO, RadialMR, and leave-one-out analysis to assess heterogeneity and horizontal pleiotropy. MR evidence indicated that genetically predicted poultry intake (adjusted odds ratio [OR] = 0.04, 95% confidence interval [CI] = 0.00–0.43, P = .007) and salad/raw vegetable intake (adjusted OR = 0.18, 95% CI = 0.04–0.83, P = .028) were directly associated with a reduced risk of cirrhosis. Conversely, there is no causal association between dietary intake and nonalcoholic fatty liver disease, alcoholic liver disease, or hepatocellular carcinoma. This study provides evidence supporting the impact of dietary intake on liver disease. Increased intake of poultry and salad/raw vegetables is associated with a reduced risk of cirrhosis. These findings can inform preventive and therapeutic strategies for cirrhosis.

Investigating potential drug targets for IgA nephropathy and membranous nephropathy through multi-queue plasma protein analysis: a Mendelian randomization study based on SMR and co-localization analysis

BackgroundMembranous nephropathy (MN) and IgA nephropathy (IgAN) pose challenges in clinical treatment with existing therapies primarily focusing on symptom relief and often yielding unsatisfactory outcomes. The search for novel drug targets remains crucial to address the shortcomings in managing both kidney diseases.MethodsUtilizing GWAS data for MN (ncase = 2150, ncontrol = 5829) and IgAN (ncase = 15587, ncontrol = 462197), instrumental variables for plasma proteins were derived from recent GWAS. Sensitivity analysis involved bidirectional Mendelian randomization analysis, MR Steiger, Bayesian co-localization, and Phenotype scanning. The SMR analysis using eQTL data from the eQTLGen Consortium was conducted to assess the availability of selected protein targets. The PPI network was constructed to reveal potential associations with existing drug treatment targets.ResultsThe study, subjected to the stringent Bonferroni correction, revealed significant associations: four proteins with MN and three proteins with IgAN. In plasma protein cis-pQTL data from two cohorts, an increase in one standard deviation in PLA2R1 (OR = 2.01, 95%CI = 1.83–2.21), AIF1 (OR = 9.04, 95%CI = 4.69–17.41), MLN (OR = 3.79, 95%CI = 2.12–6.78), and NFKB1 (OR = 29.43, 95%CI = 7.73–112.0) was associated with an increased risk of MN. Additionally, in plasma protein cis-pQTL data, a standard deviation increase in FCGR3B (OR = 1.15, 95%CI = 1.09–1.22) and BTN3A1 (OR = 4.05, 95%CI = 2.65–6.19) correlated with elevated IgAN risk, while AIF1 (OR = 0.58, 95%CI = 0.46–0.73) exhibited IgAN protection. Bayesian co-localization indicated that PLA2R1 (coloc.abf-PPH4 = 0.695), NFKB1 (coloc.abf-PPH4 = 0.949), FCGR3B (coloc.abf-PPH4 = 0.909), and BTN3A1 (coloc.abf-PPH4 = 0.685) share the same variants associated with MN and IgAN. The SMR analysis indicated a causal link between NFKB1 and BTN3A1 plasma protein eQTL in both conditions, and BTN3A1 was validated externally.ConclusionGenetically influenced plasma levels of PLA2R1 and NFKB1 impact MN risk, while FCGR3B and BTN3A1 levels are causally linked to IgAN risk, suggesting potential drug targets for further clinical exploration, notably BTN3A1 for IgAN.

Causal association between remnant cholesterol level and risk of cardiovascular diseases: a bidirectional two sample mendelian randomization study

Serum lipids have been associated with an increased risk of various cardiovascular diseases (CVDs) in several observational studies, but the causal inference between the remnant cholesterol (RC) levels and several CVDs risk has not been established. The purpose of this study was to investigate whether there is a causal relationship between RC levels and risk of developing CVDs by a bidirectional two-sample Mendelian randomization (TSMR) analysis. One TSMR analysis was performed using the publicly released large-scale genome-wide association study (GWAS) data. Inverse variance weighted (IVW) method was chosen as the main analysis method, and MR-Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. We conducted a series of sensitivity analyses to assess the robustness of the main results, including the Cochran’s Q test, MR-Egger intercept test, leave-one-out sensitivity analysis, and funnel plot. The main IVW method revealed that genetically predicted serum level of RC is significantly associated with an increased risk of developing ischemic heart disease (OR = 1.409, 95%CI = 1.284–1.546, P value = 4.753E-13), unstable angina pectoris (OR = 1.621, 95%CI = 1.398–1.880, P value = 1.672E-10), myocardial infarction (OR = 1.526, 95%CI = 1.337–1.741, P value = 3.771E-10), cardiac arrest (OR = 1.595, 95%CI = 1.322–1.924, P value = 1.076E-06), heart failure (OR = 1.086, 95%CI = 1.009–1.169, P value = 0.028), hypertension (OR = 1.089, 95%CI = 1.043–1.136, P value = 9.458E-05), major coronary heart disease (CHD) events (OR = 1.515, 95%CI = 1.376–1.669, P value = 3.217E-17), coronary atherosclerosis (OR = 1.388, 95%CI = 1.231–1.564, P value = 7.739E-08), cardiac arrhythmias (OR = 1.067, 95%CI = 1.008–1.130, P value = 0.025), and atrial fibrillation and flutter (OR = 1.122, 95%CI = 1.039–1.211, P value = 0.003). Additionally, the causal associations between the RC levels and these CVDs remained significant after correcting for the false discovery rate (all P value < 0.05). However, this study did not find any significant association of RC with cardiomyopathy and pericarditis (both P value > 0.05). Heterogeneity existed in the IVs of RC and ischemic heart disease, unstable angina pectoris, myocardial infarction, heart failure, hypertension, major CHD events, cardiomyopathy, coronary atherosclerosis, cardiac arrhythmias and atrial fibrillation and flutter using the Cochran’s Q test (all P value < 0.05). Moreover, there was no horizontal pleiotropy in this study (all P value > 0.05). The leave-one-out sensitivity analyses showed that the causal effects between RC level and CVDs (except for heart failure, cardiomyopathy, pericarditis and cardiac arrhythmias) are not driven by a single SNP. The funnel plots showed that there is no obvious potential bias in our study. In the replication analysis, the genetically predicted RC levels were positively associated with a 43.12% higher risk of coronary artery disease. This present study supported the causal link between RC and heightened the risk of CVDs, indicating that RC-lowering treatment might be effective in preventing CVDs.

A bidirectional Mendelian randomization analysis of the causal relationship between inflammatory bowel disease and breast cancer based on estrogen receptor status

The incidence of patients diagnosed with either breast cancer (BC) or inflammatory bowel disease (IBD) is increasing each year. IBD has been shown to be strongly associated with the development of a variety of solid tumors, but the relationship with breast cancer is not yet definitive. We explored the causative relationship between IBD and BC using a Mendelian randomization (MR) strategy. MR-Egger regression, weighted median (WM), simple median (SM), maximum likelihood (ML), and inverse variance weighting (IVW) methods were among the analytical techniques used in this work. The examination of heterogeneity was conducted by the use of Cochran's Q test and Rucker's Q test. The sensitivity analysis in this study used the IVW and MR-Egger methodologies. The results of our investigation suggested that IBD had a beneficial impact on estrogen receptor-negative (ER-) breast cancer (odds ratio (OR) = 0.92, P = 0.02). The study did not find a significant association between IBD and the risk of developing overall breast cancer (OR = 0.99, P = 0.60), as well as estrogen receptor-positive (ER+) breast cancer (OR = 1.02, P = 0.60) specifically. In addition, our study findings indicated that there was a detrimental association between ER+ breast cancer and IBD as determined using reverse MR analysis (OR = 1.07, P = 0.04). Furthermore, this analysis failed to observe any significant association between overall breast cancer (OR = 1.07, P = 0.07) or ER- breast cancer (OR = 0.99, P = 0.89) and IBD. Our bidirectional MR study yielded a correlation between IBD and some specific hormone receptor status of BC.

Investigating the impact of metabolic syndrome and its components on pancreas fat: a Bidirectional Mendelian randomization study

Objective: Metabolic syndrome (MetS) and fatty pancreas are two prevalent health conditions that are strongly associated with an elevated risk of developing type 2 diabetes, cardiovascular disease, and pancreatic cancer. Understanding the causal relationship between these conditions is important for developing effective prevention and treatment strategies. In this study, we performed a bidirectional Mendelian randomization analysis to investigate the potential causal relationship between MetS and fatty pancreas. Methods: This study undertook bidirectional Mendelian randomization. Genetic instruments for obesity, glycemic, lipid, and blood pressure were identified as instrumental variables for MetS traits in order to evaluate their causal role in pancreatic fat etiology. Summary level data for pancreas fat (PF) were obtained from a genome-wide association study conducted in the UK Biobank. Results: There was no causal relationship between MetS as a binary trait and PF. In addition, a causal association of increasing Waist-to-Hip Ratio (WHR) with pancreatic fat risk was found [odds ratio (OR)=1.173, 95% confidence interval (CI): 1.067-1.288, p=9*10-4]. Notably, there is no evidence of a causal relationship between PF and glycemic, lipid, and blood pressure. Sensitivity analyses did not indicate that pleiotropy was an important source of bias. Conclusion: MetS had no causal relationship with pancreatic fat. Of the components of the metabolic syndrome, only abdominal obesity and pancreatic fat were observed to be causally related.

Causal Links Between Renal Function and Cardiac Structure, Function, and Disease Risk

Background: Chronic kidney disease (CKD) increases the risk of adverse cardiovascular outcomes. However, the causal relationships between renal function and cardiovascular diseases (CVD) remain incompletely understood. This study aimed to determine the causal relationships between genetic susceptibility to impaired renal function and the risk of CVD endpoints, as well as cardiac structure and function detectable by cardiac magnetic resonance imaging (CMR). Methods: Bidirectional Mendelian randomization (MR) analyses were conducted using summary-level data from genome-wide association studies. The exposures were blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (UACR), and CKD. The outcomes included atrial fibrillation, coronary artery disease (CAD), myocardial infarction, heart failure, stroke, and various CMR parameters. Sensitivity analyses, multivariable MR adjusting for cardiometabolic traits, and replication in the FinnGen cohort were performed. Results: Elevated BUN levels (OR 1.505; 95% CI 1.077 to 2.103; P = 0.017) were causally associated with increased CAD risk, but this relationship was attenuated after adjusting for cardiometabolic traits. Increased UACR was causally linked to higher risks of CAD (OR 1.260; 95% CI 1.042 to 1.523; P = 0.017), myocardial infarction (OR 1.424; 95% CI 1.137 to 1.783; P = 0.002), and stroke (OR 1.182; 95% CI 1.012 to 1.379; P = 0.035), with the association for stroke remaining significant after multivariable adjustment. Reduced eGFR was causally related to decreases in ascending aorta diameter, proximal pulmonary artery diameter, right atrial size, left ventricular stroke volume, and right ventricular volumes, even after accounting for potential confounders. CKD was causally associated with a reduced pulmonary artery-to-aorta ratio and proximal pulmonary artery diameter. Conclusions: This comprehensive MR study establishes causal roles of genetic susceptibility to impaired renal function influencing cardiovascular outcomes and cardiac structure.

Shared genetic associations and etiology between obstructive sleep apnea and CVDs: A genome-wide cross-trait analysis and bidirectional Mendelian randomization analysis.

To investigate the genetic correlations and potential causal relationships between obstructive sleep apnea (OSA) and various cardiovascular diseases (CVDs), aiming to enhance understanding of shared genetic mechanisms and improve recognition and treatment of OSA in patients with CVDs. Utilizing genome-wide association study (GWAS) data, we analyzed shared genetics between OSA and CVDs using linkage disequilibrium score regression (LDSC), multi-trait analysis of GWAS (MTAG), and genotype-tissue expression analysis (GTEx TSEA). We further investigated causal relationships using Bayesian colocalization tests, bidirectional Mendelian randomization (MR), and latent causal variable (LCV) analysis. We found strong associations between OSA and multiple CVDs: coronary artery disease (CAD), heart failure (HF), myocardial infarction (MI), stroke, and atrial fibrillation (AF). Novel SNPs related to CVDs were identified during single-trait MTAG analysis. By applying cross-trait MTAG, we identified 15 shared loci between OSA and CAD, 25 shared loci between OSA and MI, and 7 shared loci between OSA and HF. Shared genes are primarily expressed in the blood, heart, kidney, liver, muscle, and pancreas. MR analysis indicated a significant causal effect of OSA on HF and AF as a causal factor for OSA. LCV analysis suggested that AF was causally associated with OSA, while HF showed partial causality. Our study suggests strong genetic correlations between OSA and several CVDs. Further research is needed on the associations between OSA and CVDs, as well as the mechanisms of the identified loci.

Brisk walking pace offsets venous thromboembolism risk equivalent to established monogenic mutations.

Mendelian mutations in F2 and F5 genes are known risk factors for venous thromboembolism (VTE). This study aimed to explore the association between walking pace and VTE, compare its risk with Mendelian mutations, and identify if blood biomarkers mediate this effect. We followed 445,261 UK Biobank participants free of VTE at baseline. Walking pace was self-reported, and carrier status for F2 and F5 gene mutations was determined by rs1799963 and rs6025 genotypes. We used a Cox proportional hazard model to estimate walking pace's effect on VTE risk, bidirectional Mendelian randomization (MR) analysis to assess causality, and mediation analysis to explore blood biomarkers. Over a median follow-up of 12.8 years, 11,155 incident VTE cases were identified. The 10-year incidence rates for brisk and slow walking paces were 1.32% and 3.90%, respectively. For F5 carriers, the rates were 1.70% (brisk pace) and 3.62% (slow pace). Brisk walking pace reduced VTE risk in F5 carriers (2.65%) compared to non-carriers with a slow pace (3.66%). MR analysis confirmed a causal relationship from walking pace to VTE risk. Mediation analysis revealed that serum albumin and cystatin C mediated 8.7% to 11.7% of the effect of brisk walking pace on VTE risk. A slow walking pace is causally associated with increased VTE risk. A brisk walking pace mitigates VTE risk, particularly in individuals with F5 gene mutations, and this effect is partially mediated by serum albumin and cystatin C.

Identifying causal relationships between 35 blood and urine biomarkers and urologic cancers: MR-meta combined with Bayesian colocalization Mendelian randomization analysis

BackgroundBlood and urine biomarkers have been associated with urologic tumors, but their causal relationship with urologic tumors is unclear.MethodsWe performed a bidirectional Mendelian randomization (MR) analysis of the association between 35 blood and urine biomarkers and urological tumors in our discovery cohort. A Bayesian weighting approach was used to validate the positive results identified in the discovery cohort, and steiger filtering analysis was used to distinguish causality from reverse causality. Bayesian colocalization analysis was used to analyze which single nucleotide polymorphisms (SNPs) specifically co-located between the positive blood and urine biomarkers and the disease phenotypes were driven, and MR-positive results from the discovery cohort and the validation cohort were combined using the MR-meta method.ResultsSeveral blood and urine biomarkers were found to be significantly and causally associated with urologic cancers. Notably, calcium (OR: 1.34, 95%CI 1.10–1.63, P = 0.0040) and sex hormone-binding globulin (SHBG) (OR: 0.81, 95%CI 0.70–0.95, P = 0.0092) were associated with bladder cancer; gamma glutamyl transferase (GGT) (OR: 0.91, 95%CI 0.83–0.99, P = 0.0209), lipoprotein A (Lp(a)) (OR: 1.12, 95%CI 1.01–1.24, P = 0.0399), and insulinlike growth factor 1 (IGF 1) (OR: 1.10, 95%CI 1.01–1.20, P = 0.0220) were linked to prostate cancer (PCa); non albumin protein (OR: 0.78, 95%CI 0.65–0.93, P = 0.0065) and total protein (OR: 0.80, 95%CI 0.64–0.99, P = 0.0380) were linked to renal cancer; and apolipoprotein A (Apo-A) (OR: 0.56, 95%CI 0.32–0.98, P = 0.0426) and urate (OR:1.89, 95%CI 1.03–3.47, P = 0.0399) were associated with renal pelvis cancer. These associations were validated in an independent cohort, with GGT, IGF 1, and Lp(a) being consistently linked to PCa.ConclusionThis study identified significant biomarkers associated with urological cancers in blood and urine. These include GGT, IGF 1, and Lp(a), which are strong biomarkers for PCa. In addition, the findings of this study provide evidence for a handful of risk and protective factors for the development of urologic cancers.

Causal Effects of Gastroesophageal Reflux on Chronic Rhinosinusitis: A Bidirectional Two-Sample Mendelian Randomization Study.

Observational studies have shown a bidirectional association between gastroesophageal reflux (GER) and chronic rhinosinusitis (CRS) or chronic rhinitis (CR), but it is not clear whether this association is causal. This study was to investigate the causality between GER and CRS or CR using bidirectional two-sample Mendelian randomization (MR) analysis. Using pooled data from large genome-wide association studies (GWAS), genetic loci independently associated with GER, CRS and CR in populations of European and American ancestry were selected as instrumental variables (IVs). The inverse variance weighted (IVW) method was used to analyse the random effects model of MR, and the odds ratio (OR) was used as the evaluation index to explore the bidirectional causality between GER and CRS or CR. Single nucleotide polymorphism (SNP) outliers were detected using MR-pleiotropy Residual Sum and Outliers (MR-PRESSO). The MR-Egger intercept test examined the horizontal pleiotropy of SNPs. The "leave-one-out" sensitivity analysis examined whether MR results were affected by a single SNP. The main results of IVW showed that GER increased the risk of CRS (OR = 1.3795, 95% CI = 1.188-1.603, p < 0.0500) and CR (OR = 1.3941, 95% CI = 1.1671-1.6652, p < 0.0500). The obtained SNPs as IVs for GER, CRS and CR had no significant horizontal pleiotropy, heterogeneity or bias. Regarding the reverse directions, no notable associations could be found. This MR analysis revealed that genetically predicted GER had a causal effect on an increased risk of CRS or CR, but not vice versa. These results have great implications for the management of CRS (especially for refractory CRS) or CR in clinical practice.

Relationship between myocardial infarction and atrial fibrillation: A bidirectional Mendelian randomization study.

Many studies have shown that myocardial infarction (MI) is significantly associated with atrial fibrillation (AF), but the causal relationship between MI and AF has not been established. Therefore, we performed this Mendelian randomization (MR) study to investigate the relationship between MI and AF. We used a publicly available summary statistical dataset for MI based on genome-wide analysis studies (GWAS; ebi-a-GCST011364; 14,825 cases and 2680 controls) and a summary statistical dataset for AF based on an European GWAS (finn-b-I9_AF_REIMB; 10,516 cases and 116,926 controls). The 2-sample bidirectional MR analysis was performed using the inverse-variance weighted (IVW), MR-Egger, and weighted median methods. The causal effect of MI on AF was analyzed using 30 MI-specific single nucleotide polymorphisms (SNPs) that were characterized as instrumental variables (IVs) based on the GWAS data. The causal effect of MI on AF was confirmed by the IVW (odds ratio [OR] 1.42; 95% confidence interval [CI] 1.27-1.58; P < .001), MR-Egger (OR: 1.49; 95% CI: 1.15-1.93; P = .005), and weighted median (OR: 1.42; 95% CI: 1.24-1.63; P < .001) analyses. Furthermore, in the reverse MR analyses, the causal effect of AF on MI was analyzed using 20 AF-specific SNPs that were screened as IVs. The causal effect of AF on MI was significant based on the results from the IVW method (OR: 1.05; 95% CI: 1.00-1.09; P = .033). In conclusion, the bidirectional MR analyses demonstrated a clear bidirectional causal association between MI and AF.

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

BackgroundThe association between heme oxygenase-1 (HO-1) and asthma has been a subject of debate in both observational and experimental studies. We aimed to evaluate the potential causal relationship between HO-1 and asthma. Materials and methodsA bidirectional two-sample Mendelian randomization (TSMR) study was conducted to examine the causal relationship between HO-1 and asthma. In the forward Mendelian randomization (MR) analyses, HO-1 was considered as the exposure, while asthma as the outcome. Conversely, in the reverse MR analyses, asthma was regarded as the exposure, and HO-1 as the outcome. Data for HO-1 and asthma were obtained from publicly accessible genome-wide association studies (GWAS). These causal relationships were identified through 5 MR methods, namely MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, and weighted mode. Additionally, sensitivity tests were conducted to assess the robustness of MR study. Finally, additional asthma datasets and childhood asthma were selected to validate the findings. ResultsIn the forward MR analyses, according to the IVW method, genetically predicted HO-1 displays a negative correlation with the risk of asthma (OR 0.947, 95% CI 0.905–0.990). It was not found any SNP overly sensitive or disproportionately responsible for the outcome. No evidence of heterogeneity and pleiotropy between SNPs was observed. Genetically predicted asthma was not associated with HO-1 in reverse MR analyses using the IVW method. The same results were validated in additional asthma datasets and in childhood asthma. ConclusionThe results of MR analysis revealed heme oxygenase-1 as a protective factor for asthma.

Effect of tea consumption on the development of hypertension, diabetes, and obesity: a bidirectional two-sample Mendelian randomization analysis

BackgroundThe effect of tea consumption on conditions such as hypertension, diabetes, and obesity has attracted significant global interest. However, the results of various studies on this topic have been mixed and somewhat contentious. Therefore, we conducted a Mendelian randomization (MR) analysis to investigate the causal relationships between tea consumption and the aforementioned health conditions.MethodsA bidirectional two-sample MR analysis was used to systematically explores the associations between tea consumption and hypertension, diabetes, and obesity. MR-Egger regression, weighted median, inverse variance weighted, and weighted mode methods were used to evaluate the potential causal associations. Leave-one-out sensitivity test was used to check the robustness of the IVW estimates.ResultsMR analysis indicated that genetically predicted tea consumption is associated with a protective effect against hypertension, with an odds ratio (OR) of 0.78 and a 95% confidence interval (CI) ranging from 0.64 to 0.95. Additionally, tea consumption appeared to have a potential protective effect on type 2 diabetes and obesity related to excessive calorie intake, influenced by specific single nucleotide polymorphisms (SNPs), namely “rs57462170” and “rs17685.” No causal link was observed between the consumption of green or herbal tea and hypertension, diabetes, or obesity. However, there was a marginal negative association between type 2 diabetes and tea consumption and (OR = 0.99; 95% CI: 0.97–1.00) and a significant negative correlation between obesity due to excessive calorie intake and green tea consumption (OR = 0.35; 95% CI: 0.16–0.78).ConclusionThis study demonstrates a protective causal relationship between the consumption of tea (including black and green teas) and reduced risk of hypertension. Furthermore, our results suggest that tea intake may also have a protective effect on type 2 diabetes and obesity. The results recommend further research to verify or refine these findings.