[Educational attainment increases the risk of developing allergic rhinitis and (or) eczema: a Mendelian randomization study based on genome-wide association studies in European patients].

Objective: To determine the causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema using Mendelian randomization (MR) analyses. Methods: This study was a secondary data analysis based on the summary data of genome-wide association studies (GWAS), which involved 293 723 participants (educational attainment) from the Social Science Genetics Association Consortium and 462 013 participants [allergic rhinitis and (or) eczema] from the UK Biobank. Genetic variants that were closely related to educational attainment were identified as instrumental variables. Two-sample MR analyses, including inverse-variance weighted (IVW), MR-Egger regression, weighted median method and weighted model-based estimation, were performed to investigate the causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema, in which the odds ratio (OR) values were used as indicators. Results: A total of 70 single-nucleotide polymorphisms (SNPs) were chosen as instrumental variables. The MR-Egger regression results suggested that the genetic pleiotropy was unlikely to bias our results (P=0.107). In the univariable MR analyses, IVW regression showed that the risk of allergic rhinitis and (or) eczema was OR=1.044 (95%CI: 1.020-1.069, P<0.001) and OR=1.170 (95%CI: 1.074-1.256, P<0.001), respectively, for the increase in the duration of education by one year or one standard deviation (SD) (3.71 years). In the reverse MR analysis, IVW regression showed little evidence that allergic rhinitis and (or) eczema affected educational attainment (OR=1.020, 95%CI: 0.927-1.023, P=0.683). The results of the weighted median method and weighted mode-based estimation were consistent with the results of IVW. Conclusion: This study suggests that there is a positive causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema, which means that educational attainment can increase the occurrence of allergic rhinitis and (or) eczema.

Is Type 2 Diabetes Mellitus Associated with Spinal Degenerative Disorders?: Evidence from Observational and 2-Sample Mendelian Randomization Analyses.

BACKGROUND: Type 2 diabetes mellitus (T2DM) and spinal degenerative disorders (SDD) are common diseases that frequently coexist. However, both traditional observational studies and recent Mendelian randomization (MR) studies have demonstrated conflicting evidence on the association between T2DM and SDD. This comparative study explored and compared the association between T2DM and SDD using observational and MR analyses. METHODS: For observational analyses, cross-sectional studies (44,972 participants with T2DM and 403,095 participants without T2DM), case-control studies (38,234 participants with SDD and 409,833 participants without SDD), and prospective studies (35,550 participants with T2DM and 392,046 participants without T2DM with follow-up information until 2022) were performed to test the relationship between T2DM and SDD using individual-level data from the U.K. Biobank from 2006 to 2022. For MR analyses, the associations between single-nucleotide polymorphisms with SDD susceptibility obtained using participant data from the U.K. Biobank, which had 407,938 participants from 2006 to 2022, and the FinnGen Consortium, which had 227,388 participants from 2017 to 2022, and genetic predisposition to T2DM obtained using summary statistics from a pooled genome-wide association study involving 1,407,282 individuals were examined. The onset and severity of T2DM are not available in the databases being used. RESULTS: Participants with T2DM were more likely to have SDD than their counterparts. Logistic regression analysis identified T2DM as an independent risk factor for SDD, which was confirmed by the Cox proportional hazard model results. However, using single-nucleotide polymorphisms as instruments, the MR analyses demonstrated no causal relationship between T2DM and SDD. The lack of such an association was robust in the sensitivity analysis, and no pleiotropy was seen. CONCLUSIONS: Our results suggest that the association between T2DM and SDD may be method-dependent. Researchers and clinicians should be cautious in interpreting the association, especially the causal association, between T2DM and SDD. Our findings provide fresh insights into the association between T2DM and SDD by various analysis methods and guide future research and clinical efforts in the effective prevention and management of T2DM and SDD. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Exploring the relationship between life course adiposity and sepsis: insights from a two-sample Mendelian randomization analysis.

Objectives: The relationship between adiposity and sepsis has received increasing attention. This study aims to explore the causal relationship between life course adiposity and the sepsis incidence. Methods: Mendelian randomization (MR) method was employed in this study. Instrumental variants were obtained from genome-wide association studies for life course adiposity, including birth weight, childhood body mass index (BMI), childhood obesity, adult BMI, waist circumference, visceral adiposity, and body fat percentage. A meta-analysis of genome-wide association studies for sepsis including 10,154 cases and 454,764 controls was used in this study. MR analyses were performed using inverse variance weighted, MR Egger regression, weighted median, weighted mode, and simple mode. Instrumental variables were identified as significant single nucleotide polymorphisms at the genome-wide significance level (P < 5×10-8). The sensitivity analysis was conducted to assess the reliability of the MR estimates. Results: Analysis using the MR analysis of inverse variance weighted method revealed that genetic predisposition to increased childhood BMI (OR = 1.29, P = 0.003), childhood obesity (OR = 1.07, P = 0.034), adult BMI (OR = 1.38, P < 0.001), adult waist circumference (OR = 1.01, P = 0.028), and adult visceral adiposity (OR = 1.53, P < 0.001) predicted a higher risk of sepsis. Sensitivity analysis did not identify any bias in the MR results. Conclusion: The results demonstrated that adiposity in childhood and adults had causal effects on sepsis incidence. However, more well-designed studies are still needed to validate their association.

Mendelian randomization study and mediation analysis about the relation of inflammatory bowel disease and diabetic retinopathy: the further exploration of gut-retina axis.

Background: The concept of the gut-retinal axis proposed by previous scholars primarily focused on the relationship between intestinal microbiota and retinal diseases, and few further expanded the relationship between intestinal diseases and retinal diseases. To further substantiate the concept of the gut-retinal axis, we analyzed inflammatory bowel disease (IBD) and diabetic retinopathy (DR) using Mendelian randomization (MR), and use mediation analysis to further explore the potential substances that influence this causal relationship. Methods: The genome-wide association study's (GWAS) summary statistics for genetic variations were utilized in a Mendelian randomization (MR) investigation. GWAS data on IBD (including ulcerative colitis (UC), Crohn's disease (CD), and IBD) for non-Finnish Europeans (NFE) were sourced from published articles. In contrast, data on DR (including DR and diabetic maculopathy (DMP)) were obtained from FinnGen R9. The causal relationship has been investigated using inverse variance weighted (IVW), MR-Egger, and weighted median and sensitivity analysis was applied to verify the stability of the results. In addition, we applied mediation analysis to investigate whether circulating inflammatory proteins and plasma lipids played a mediating role, and calculated its effect ratio. Results: The causal relationship between IBD and DR was discovered by employing the inverse variance weighted (IVW) method and weighted median method. In forward MR, UC was significantly associated with lower risk of DR (IVW: OR=0.874; 95%CI= 0.835-0.916; P value= 1.28E-08) (Weighted median: OR=0.893; 95%CI= 0.837-0.954; P value= 7.40E-04). In reverse MR, it was shown that DR (IVW: OR=0.870; 95%CI= 0.828-0.914; P value= 2.79E-08)(Weighted median: OR=0.857; 95%CI= 0.801-0.916; P value= 6.40E-06) and DMP (IVW: OR=0.900; 95%CI= 0.865-0.937; P value= 3.34E-07)(Weighted median: OR=0.882; 95%CI= 0.841-0.924; P value= 1.82E-07) could reduce the risk of CD. What's more, DR is associated with a lower risk of IBD according to genetic prediction (IVW: OR=0.922; 95%CI= 0.873-0.972; P value= 0.002) (Weighted median: OR=0.924; 95%CI= 0.861-0.992; P value= 0.029). Fibroblast growth factor 21 (FGF21), phosphatidylcholine (PC), and triacylglycerol (TG) serve as mediators in these relationships. Conclusions: Our research offers novel insights and sources for investigating the gut-retina axis in the genetic relationship between IBD and DR. We discover four mediators and more about the association between the intestine and retinal disorders and provide more evidence for the gut-retinal axis theory.

Plasma proteins and inflammatory dermatoses: proteome-wide Mendelian randomization and colocalization analyses.

Current genome-wide association studies (GWAS) of plasma proteomes provide additional possibilities for finding new drug targets for inflammatory dermatoses. We performed proteome-wide Mendelian randomization (MR) and colocalization analyses to identify novel potential drug targets for inflammatory dermatoses. We performed MR and colocalization analysis using genetic variation as instrumental variables to determine the causal relationship between circulating plasma proteins and inflammatory dermatoses. 5 plasma proteins were found to be causally associated with dermatitis eczematosa, SLE, urticaria and psoriasis using cis-pQTLs as instrumental variables, but not found in AD and LP. 19 candidate genes with high colocalization evidence were identified. These potential drug targets still require more research and rigorous validation in future trials.

Assessing causal associations of blood counts and biochemical indicators with pulmonary arterial hypertension: a Mendelian randomization study and results from national health and nutrition examination survey 2003-2018.

Background: Blood counts and biochemical markers are among the most common tests performed in hospitals and most readily accepted by patients, and are widely regarded as reliable biomarkers in the literature. The aim of this study was to assess the causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension (PAH). Methods: A two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between blood counts and biochemical indicators with PAH. The genome-wide association study (GWAS) for blood counts and biochemical indicators were obtained from the UK Biobank (UKBB), while the GWAS for PAH were sourced from the FinnGen Biobank. Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by three sensitivity analyses to assess the robustness of the results. And we conducted an observational study using data from National Health and Nutrition Examination Survey (NHANES) 2003-2018 to verify the relationship. Results: The MR analysis primarily using the IVW method revealed genetic variants of platelet count (OR=2.51, 95% CI 1.56-4.22, P<0.001), platelet crit(OR=1.87, 95% CI1.17-7.65, P=0.022), direct bilirubin (DBIL)(OR=1.71, 95%CI 1.18-2.47,P=0.004), insulin-like growth factor (IGF-1)(OR=0.51, 95% CI 0.27-0.96, P=0.038), Lipoprotein A (Lp(a))(OR=0.66, 95% CI 0.45-0.98, P=0.037) and total bilirubin (TBIL)(OR=0.51, 95% CI 0.27-0.96, P=0.038) were significantly associated with PAH. In NHANES, multivariate logistic regression analyses revealed a significant positive correlation between platelet count and volume and the risk of PAH, and a significant negative correlation between total bilirubin and PAH. Conclusion: Our study reveals a causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension. These findings offer novel insights into the etiology and pathological mechanisms of PAH, and emphasizes the important value of these markers as potential targets for the prevention and treatment of PAH.

Causal role of immune cells in thyroid cancer: a bidirectional Mendelian randomization study.

Background: The immune system plays an important role in the development and treatment of thyroid cancer(THCA).However, the correlation between immune cells and THCA has not been systematically studied. Methods: This study used a two-sample Mendelian randomization (MR) study to determine the causal relationship between immune cell characteristics and THCA. Based on a large sample of publicly available genetic data, we explored the causal relationship between 731 immune cell characteristics and THCA risk. The 731 immunophenotypes were divided into 7 groups, including B cell panel(n=190),cDC panel(n=64),Maturation stages of T cell panel(n=79),Monocyte panel(n=43),Myeloid cell panel(n=64),TBNK panel(n=124),and Treg panel(n=167). The sensitivity of the results was analyzed, and heterogeneity and horizontal pleiotropy were excluded. Results: After FDR correction, the effect of immunophenotype on THCA was not statistically significant. It is worth mentioning, however, that there are some unadjusted low P-values phenotypes. The odds ratio (OR) of CD62L on monocyte on THCA risk was estimated to be 0.953 (95% CI=0.930~0.976, P=1.005×10-4),and which was estimated to be 0.975(95% CI=0.961-0.989, P=7.984×10-4) for Resting Treg%CD4 on THCA risk. Furthermore, THCA was associated with a reduced risk of 5 immunophenotype:CD25 on CD39+ CD4 on Treg (OR=0.871, 95% CI=0.812~0.935, P=1.274×10-4), activated Treg AC (OR=0.884, 95% CI=0.820~0.953, P=0.001), activated & resting Treg % CD4 Treg (OR=0.872, 95%CI=0.811~0.937,P=2.109×10-4),CD28- CD25++ CD8br AC(OR=0.867,95% CI=0.809~0.930,P=6.09×10-5),CD28-CD127-CD25++CD8brAC(OR=0.875,95%CI=0.814~0.942,P=3.619×10-4).THCA was associated with an increased risk of Secreting Treg % CD4 Treg (OR=1.143, 95% CI=1.064~1.229, P=2.779×10-4) and CD19 on IgD+ CD24+ (OR=1.118, 95% CI=1.041~1.120, P=0.002). Conclusions: These findings suggest the causal associations between immune cells and THCA by genetic means. Our results may have the potential to provide guidance for future clinical research.

A causal relationship between particulate matter 2.5 and obesity and its related indicators: a Mendelian randomization study of European ancestry.

Background: In recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous. Methods: Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings. Results: The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21. Conclusion: Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.

Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis.

Background and objective: Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. Our objective was to explore the correlation between heavy metal exposures and the incidence of DKD. Methods: We analyzed data from the NHANES (2005-2020), using machine learning, and cross-sectional survey. Our study also involved a bidirectional two-sample Mendelian randomization (MR) analysis. Results: Machine learning reveals correlation coefficients of -0.5059 and - 0.6510 for urinary Ba and urinary Tl with DKD, respectively. Multifactorial logistic regression implicates urinary Ba, urinary Pb, blood Cd, and blood Pb as potential associates of DKD. When adjusted for all covariates, the odds ratios and 95% confidence intervals are 0.87 (0.78, 0.98) (p = 0.023), 0.70 (0.53, 0.92) (p = 0.012), 0.53 (0.34, 0.82) (p = 0.005), and 0.76 (0.64, 0.90) (p = 0.002) in order. Furthermore, multiplicative interactions between urinary Ba and urinary Sb, urinary Cd and urinary Co, urinary Cd and urinary Pb, and blood Cd and blood Hg might be present. Among the diabetic population, the OR of urinary Tl with DKD is a mere 0.10, with a 95%CI of (0.01, 0.74), urinary Co 0.73 (0.54, 0.98) in Model 3, and urinary Pb 0.72 (0.55, 0.95) in Model 2. Restricted Cubic Splines (RCS) indicate a linear linkage between blood Cd in the general population and urinary Co, urinary Pb, and urinary Tl with DKD among diabetics. An observable trend effect is present between urinary Pb and urinary Tl with DKD. MR analysis reveals odds ratios and 95% confidence intervals of 1.16 (1.03, 1.32) (p = 0.018) and 1.17 (1.00, 1.36) (p = 0.044) for blood Cd and blood Mn, respectively. Conclusion: In the general population, urinary Ba demonstrates a nonlinear inverse association with DKD, whereas in the diabetic population, urinary Tl displays a linear inverse relationship with DKD.

Role of plasma fatty acid in age-related macular degeneration: insights from a mendelian randomization analysis.

BACKGROUND: An imbalance in lipid metabolism has been linked to the development of AMD, but the causal relationship between AMD and plasma fatty acids (FAs) remains controversial. Using a two-sample Mendelian randomization (MR) approach, we sought to evaluate the impact of specific FA plasma levels on the risk of different AMD subtypes. METHODS: We analysed genome-wide association data of circulating FAs from 115,006 European-descended individuals in the UK Biobank. These data were used in a two-sample MR framework to assess the potential role of circulating FAs in developing wet and dry AMD. Sensitivity analyses were conducted to ensure the robustness of our findings. Additional multivariable and locus-specific MR analyses were conducted to evaluate direct effects of FA on AMD subtypes, minimizing biases from lipoprotein-related traits and triglycerides. RESULTS: Mendelian randomization revealed associations of omega-3 was associated with decreased wet (OR 0.78, 95%CI 0.66-0.92) and dry AMD (0.85, 0.74-0.97) risk, showed a protective effect on AMD. Notably, the omega-6 to omega-3 ratio showed potential causal effects on both wet (1.27, 1.03-1.56) and dry AMD (1.18, 1.02-1.37). Multivariable MR suggested that the causal relationship of omega-3, omega-6 to omega-3 ratio on wet AMD persists after conditioning on HDL, LDL and triglycerides, albeit with slightly diminished evidence strength. Locus-specific MR linked to omega-3(FADS1, 0.89, 0.82-0.98; FADS2, 0.88, 0.81-0.96) and omega-6 to omega-3 ratio (FADS1, 1.10, 1.02-1.20; FADS2, 1.11, 1.03-1.20) suggests causal effects of these factors on wet AMD. CONCLUSIONS: The associations between plasma FA concentrations and AMD, suggest potential causal role of omega-3, and the omega-6 to omega-3 ratio in wet AMD. These results underscore the impact of an imbalanced circulating omega-3 and omega-6 FA ratio on AMD pathophysiology from MR perspective.

Integrated analysis of single-cell RNA-seq, bulk RNA-seq, Mendelian randomization, and eQTL reveals T cell-related nomogram model and subtype classification in rheumatoid arthritis.

Objective: Rheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy. Methods: scRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features. Results: By analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients. Conclusion: Our findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

Causal association between immune cells and lung cancer risk: a two-sample bidirectional Mendelian randomization analysis.

Background: Previous studies have highlighted the crucial role of immune cells in lung cancer development; however, the direct link between immunophenotypes and lung cancer remains underexplored. Methods: We applied two-sample Mendelian randomization (MR) analysis, using genetic variants as instruments to determine the causal influence of exposures on outcomes. This method, unlike traditional randomized controlled trials (RCTs), leverages genetic variants inherited randomly at conception, thus reducing confounding and preventing reverse causation. Our analysis involved three genome-wide association studies to assess the causal impact of 731 immune cell signatures on lung cancer using genetic instrumental variables (IVs). We initially used the standard inverse variance weighted (IVW) method and further validated our findings with three supplementary MR techniques (MR-Egger, weighted median, and MR-PRESSO) to ensure robustness. We also conducted MR-Egger intercept and Cochran's Q tests to assess heterogeneity and pleiotropy. Additionally, reverse MR analysis was performed to explore potential causality between lung cancer subtypes and identified immunophenotypes, using R software for all statistical calculations. Results: Our MR analysis identified 106 immune signatures significantly associated with lung cancer. Notably, we found five suggestive associations across all sensitivity tests (P<0.05): CD25 on IgD- CD24- cells in small cell lung carcinoma (ORIVW =0.885; 95% CI: 0.798-0.983; P IVW =0.022); CD27 on IgD+ CD24+ cells in lung squamous cell carcinoma (ORIVW =1.054; 95% CI: 1.010-1.100; P IVW =0.015); CCR2 on monocyte cells in lung squamous cell carcinoma (ORIVW =0.941; 95% CI: 0.898-0.987; P IVW =0.012); CD123 on CD62L+ plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) as well as on plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) in lung squamous cell carcinoma. Conclusion: This study establishes a significant genomic link between immune cells and lung cancer, providing a robust basis for future clinical research aimed at lung cancer management.

Repurposing lipid-lowering drugs on asthma and lung function: evidence from a genetic association analysis.

OBJECTIVE: To explore the correlation between asthma risk and genetic variants affecting the expression or function of lipid-lowering drug targets. METHODS: We conducted Mendelian randomization (MR) analyses using variants in several genes associated with lipid-lowering medication targets: HMGCR (statin target), PCSK9 (alirocumab target), NPC1L1 (ezetimibe target), APOB (mipomersen target), ANGPTL3 (evinacumab target), PPARA (fenofibrate target), and APOC3 (volanesorsen target), as well as LDLR and LPL. Our objective was to investigate the relationship between lipid-lowering drugs and asthma through MR. Finally, we assessed the efficacy and stability of the MR analysis using the MR Egger and inverse variance weighted (IVW) methods. RESULTS: The elevated triglyceride (TG) levels associated with the APOC3, and LPL targets were found to increase asthma risk. Conversely, higher LDL-C levels driven by LDLR were found to decrease asthma risk. Additionally, LDL-C levels (driven by APOB, NPC1L1 and HMGCR targets) and TG levels (driven by the LPL target) were associated with improved lung function (FEV1/FVC). LDL-C levels driven by PCSK9 were associated with decreased lung function (FEV1/FVC). CONCLUSION: In conclusion, our findings suggest a likely causal relationship between asthma and lipid-lowering drugs. Moreover, there is compelling evidence indicating that lipid-lowering therapies could play a crucial role in the future management of asthma.

Rheumatoid arthritis reduces the risk of colorectal cancer through immune inflammation mediation.

There is a close relationship between immune-mediated inflammation and cancer, and there is still controversy over whether rheumatoid arthritis (RA) increases the risk of malignancy. We first used Mendelian randomization (MR) analysis to explore the potential causal relationship between RA and pan-cancer. And verify the effect of immune-mediated inflammation on cancer through intermediate MR analysis. Then we extracted the standardized incidence rate of malignancy in RA patients relative to the general population through large-scale meta-analysis. Finally, we performed pan-cancer analysis on the RA related genes obtained from MR analysis. And perform immune related analysis on key genes to reveal the association between RA and malignancy. The MR analysis demonstrated a negative correlation between RA and pan-cancer (p = 0.008). Autoimmune traits were the main mediating variable for the causal relationship between RA and pan-cancer. Based on the results of the meta-analysis, we validated that RA reduces the risk of developing colorectal cancer (SIR = 0.69, 95% CI 0.53-0.85). Pan-cancer analysis also showed that high expression of RA related genes was negatively correlated with colon adenocarcinoma. IL6R was the gene with the highest correlation among them, and its correlation with immune cells was higher in colorectal cancer than in other malignancy. Our MR study provides evidence that RA was associated with reduced risk of colorectal cancer. This effect is caused by immune-mediated inflammation, with IL6R being a key regulatory gene.

Investigating the causal association between gut microbiota and type 2 diabetes: a meta-analysis and Mendelian randomization.

Background: Studies have shown that gut dysbiosis contributes to the pathophysiology of type 2 diabetes mellitus (T2DM). Identifying specific gut microbiota dysbiosis may provide insight into the pathogenesis of T2DM. Purpose: This study investigated the causal relationship between gut microbiota and T2DM using meta-analysis and Mendelian randomization (MR). Methods: In the first part, we searched for literature on gut microbiota and T2DM, and conducted a meta-analysis. We observed differences in glycosylated hemoglobin and fasting blood glucose levels in both groups. Second, we obtained GWAS data from genome-wide association study database 19 (GWAS). We used two-sample MR analysis to verify the forward and reverse causal associations between gut microbiota and T2DM. Additionally, we selected the European GWAS data from the European Bioinformatics Institute (EBI) as a validation set for external validation of the MR analysis. In the third part, we aimed to clarify which gut microbiota contribute to the degree of causal association between group disorders and T2DM through multivariate MR analysis and Bayesian model averaging (MR-BMA). Results: 1. According to the meta-analysis results, the glycated hemoglobin concentration in the gut probiotic intervention group was significantly lower than in the control group. Following treatment, fasting blood glucose levels in the intervention group were significantly lower than those in the control group. 2. The results of two samples MR analysis revealed that there were causal relationships between six gut microbiota and T2DM. Genus Haemophilus and order Pasteurellaceae were negatively correlated with T2DM. Genus Actinomycetes, class Melanobacteria and genus Lactobacillus were positively correlated. Reverse MR analysis demonstrated that T2DM and gut microbiota did not have any reverse causal relationship. The external validation data set showed a causal relationship between gut microbiota and T2DM. 3. Multivariate MR analysis and MR-BMA results showed that the independent genus Haemophilus collection had the largest PP. Conclusion: Our research results suggest that gut microbiota is closely related to T2DM pathogenesis. The results of further MR research and an analysis of the prediction model indicate that a variety of gut microbiota disorders, including genus Haemophilus, are causally related to the development of T2DM. The findings of this study may provide some insight into the diagnosis and treatment of T2DM. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO.

Causal relationships between height, screen time, physical activity, sleep and myopia: univariable and multivariable Mendelian randomization.

Background: This study aims to investigate the independent causal relation between height, screen time, physical activity, sleep and myopia. Methods: Instrumental variables (IVs) for exposures and outcome were obtained from the largest publicly available genome-wide association studies (GWAS) databases. First, we performed a bidirectional univariate MR analysis using primarily the inverse variance weighted method (IVW) with height, screen time, physical activity and sleep as the exposure and myopia as the outcome to investigate the causal relationship between exposures and myopia. Sensitivity analysis was used to demonstrate its robustness. Then the multivariable MR (MVMR) and MR-based mediation approach was further used to estimate the mediating effect of potential confounders (education and time outdoors) on causality. Results: The results of univariate MR analysis showed that taller height (OR = 1.009, 95% CI = 1.005-1.012, p = 3.71 × 10-7), longer time on computer (OR = 1.048, 95% CI = 1.029-1.047, p = 3.87 × 10-7) and less moderate physical activity (OR = 0.976, 95% CI = 0.96-0.991 p = 2.37 × 10-3) had a total effect on the increased risk of developing myopia. Meanwhile our results did not have sufficient evidence to support the causal relationship between chronotype (p = 0.637), sleep duration (p = 0.952) and myopia. After adjusting for education, only taller height remains an independent risk factor for myopia. After adjusting for education, the causal relationship between height, screen and myopia still had statistical significance. A reverse causal relationship was not found in our study. Most of the sensitivity analyses showed consistent results with those of the IVW method. Conclusion: Our MR study revealed that genetically predicted taller height, longer time on computer, less moderate physical activity increased the risk of myopia. After full adjustment for confounders, only height remained independently associated with myopia. As a complement to observational studies, the results of our analysis provide strong evidence for the improvement of myopia risk factors and provide a theoretical basis for future measures to prevent and control myopia in adolescents.

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.

Exploring the causal association between uric acid and lung cancer in east Asian and European populations: a mendelian randomization study.

BACKGROUND: Lung cancer still ranks first in the mortality rate of cancer. Uric acid is a product of purine metabolism in humans. Its presence in the serum is controversial; some say that its high levels have a protective effect against tumors, others say the opposite, that is, high levels increase the risk of cancer. Therefore, the aim of this study was to investigate the potential causal association between serum uric acid levels and lung cancer. METHODS: Mendelian randomization was used to achieve our aim. Sensitivity analyses was performed to validate the reliability of the results, followed by reverse Mendelian analyses to determine a potential reverse causal association. RESULTS: A significant causal association was found between serum uric acid levels and lung cancer in East Asian and European populations. Further sublayer analysis revealed a significant causal association between uric acid and small cell lung cancer, while no potential association was observed between uric acid and non-small cell lung cancer, squamous lung cancer, and lung adenocarcinoma. The sensitivity analyses confirmed the reliability of the results. Reverse Mendelian analysis showed no reverse causal association between uric acid and lung cancer. CONCLUSIONS: The results of this study suggested that serum uric acid levels were negatively associated with lung cancer, with uric acid being a potential protective factor for lung cancer. In addition, uric acid level monitoring was simple and inexpensive. Therefore, it might be used as a biomarker for lung cancer, promoting its wide use clinical practice.