Single-cell and genome-wide Mendelian randomization identifies causative genes for gout.

BACKGROUND: Gout is a prevalent manifestation of metabolic osteoarthritis induced by elevated blood uric acid levels. The purpose of this study was to investigate the mechanisms of gene expression regulation in gout disease and elucidate its pathogenesis. METHODS: The study integrated gout genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and methylation quantitative trait loci (mQTL) data for analysis, and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and gout. RESULTS: We identified 17 association signals for gout at unique genetic loci, including four genes related by protein-protein interaction network (PPI) analysis: TRIM46, THBS3, MTX1, and KRTCAP2. Additionally, we discerned 22 methylation sites in relation to gout. The study also found that genes such as TRIM46, MAP3K11, KRTCAP2, and TM7SF2 could potentially elevate the risk of gout. Through a Mendelian randomization (MR) analysis, we identified three proteins causally associated with gout: ADH1B, BMP1, and HIST1H3A. CONCLUSION: According to our findings, gout is linked with the expression and function of particular genes and proteins. These genes and proteins have the potential to function as novel diagnostic and therapeutic targets for gout. These discoveries shed new light on the pathological mechanisms of gout and clear the way for future research on this condition.

Association between plasma proteome and pulmonary heart disease: A two-stage Mendelian randomization analysis.

Pulmonary heart disease (PHD) involves altered structure and function of the right ventricle caused by an abnormal respiratory system that causes pulmonary hypertension. However, the association between changes in plasma proteomics and PHD remains unclear. Hence, we aimed to identify causal associations between genetically predicted plasma protein levels and PHD. Mendelian randomization was performed to test the target proteins associated with PHD. Summary statistics for the human plasma proteome and pulmonary heart disease were acquired from the UK Biobank (6038 cases and 426 977 controls) and the FinnGen study (6753 cases and 302 401 controls). Publicly available pQTLs datasets for human plasma proteins were obtained from a largescale genome-wide association study in the INTERVAL study. The results were validated using a case-control cohort. We first enrolled 3622 plasma proteins with conditionally independent genetic variants; three proteins (histo-blood group ABO system transferase, activating signal cointegration 1 complex subunit 1, and calcium/calmodulin-dependent protein kinase I [CAMK1]) were significantly associated with the risk of pulmonary heart disease in the UK Biobank cohort. Only CAMK1 was successfully replicated (odds ratio: 1.1056, 95% confidence interval: 1.019-1.095, p = 0.0029) in the FinnGen population. In addition, the level of CAMK1 in 40 patients with PHD was significantly higher (p = 0.023) than that in the control group. This work proposes that CAMK1 is associated with PHD, underscoring the importance of the calcium signaling pathway in the pathophysiology to improve therapies for PHD.

Dietary factors and Alzheimer's disease risk: a Mendelian randomization study.

BACKGROUND: Prior observational research has investigated the association between dietary patterns and Alzheimer's disease (AD) risk. Nevertheless, due to constraints in past observational studies, establishing a causal link between dietary habits and AD remains challenging. METHODS: Methodology involved the utilization of extensive cohorts sourced from publicly accessible genome-wide association study (GWAS) datasets of European descent for conducting Mendelian randomization (MR) analyses. The principal analytical technique utilized was the inverse-variance weighted (IVW) method. RESULTS: The MR analysis conducted in this study found no statistically significant causal association between 20 dietary habits and the risk of AD (All p > 0.05). These results were consistent across various MR methods employed, including MR-Egger, weighted median, simple mode, and weighted mode approaches. Moreover, there was no evidence of horizontal pleiotropy detected (All p > 0.05). CONCLUSION: In this MR analysis, our finding did not provide evidence to support the causal genetic relationships between dietary habits and AD risk.

Causal relationship between serum metabolites and juvenile idiopathic arthritis: a mendelian randomization study.

BACKGROUND: Juvenile Idiopathic Arthritis (JIA) is a condition that occurs when individuals under the age of 16 develop arthritis that lasts for more than six weeks, and the cause is unknown. The development of JIA may be linked to serum metabolites. Nevertheless, the association between JIA pathogenesis and serum metabolites is unclear, and there are discrepancies in the findings across studies. METHODS: In this research, the association between JIA in humans and 486 serum metabolites was assessed using genetic variation data and genome-wide association study. The identification of causal relationships was accomplished through the application of univariate Mendelian randomization (MR) analysis. Various statistical methods, including inverse variance weighted and MR-Egger, were applied to achieve this objective. To ensure that the findings from the MR analysis were trustworthy, a number of assessments were carried out. To ensure the accuracy of the obtained results, a range of techniques were utilised including the Cochran Q test, examination of the MR-Egger intercept, implementation of the leave-one-out strategy, and regression analysis of linkage disequilibrium scores. In order to identify the specific metabolic pathways associated with JIA, our primary objective was to perform pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes. RESULTS: Two-sample summary data MR analyses and sensitivity analyses showed that five metabolites were significantly causally associated with JIA, including two risk factors-kynurenine (odds ratio [OR]: 16.39, 95% confidence interval [CI]: 2.07-129.63, p = 5.11 × 10- 6) and linolenate (OR: 16.48, 95% CI: 1.32-206.22, p = 0.030)-and three protective factors-3-dehydrocarnitine (OR: 0.32, 95% CI: 0.14-0.72, p = 0.007), levulinate (4-oxovalerate) (OR: 0.40, 95% CI: 0.20-0.80, p = 0.010), and X-14,208 (phenylalanylserine) (OR: 0.68, 95% CI: 0.51-0.92, p = 0.010). Furthermore, seven metabolic pathways, including α-linolenic acid metabolism and pantothenate and CoA biosynthesis, are potentially associated with the onset and progression of JIA. CONCLUSION: Five serum metabolites, including kynurenine and 3-dehydrocarnitine, may be causally associated with JIA. These results provide a theoretical framework for developing effective JIA prevention and screening strategies.

Association of dietary nutrient intake with type 2 diabetes: A Mendelian randomization study.

Observational research suggests that the evidence linking dietary nutrient intake (encompassing minerals, vitamins, amino acids, and unsaturated fatty acids) to type 2 diabetes (T2D) is both inconsistent and limited. This study aims to explore the potential causal relationship between dietary nutrients and T2D. Causal estimation utilized Mendelian randomization techniques. Single nucleotide polymorphisms linked to dietary nutrients were identified from existing genome-wide association studies and used as instrumental variables. Genome-wide association studies data pertinent to T2D were sourced from the DIMANTE consortium and the FinnGen database. Techniques including inverse variance weighting (IVW), weighted mode, weighted median, and Mendelian randomization-Egger were employed for causal inference, complemented by sensitivity analysis. Genetically predicted higher phenylalanine (IVW: odds ratio = 1.10 95% confidence interval 1.04-1.17, P = 1.5 × 10-3, q_pval = 3.4 × 10-2) and dihomo-gamma-linolenic acid (IVW: odds ratio = 1.001 95% confidence interval 1.0006-1.003, P = 3.7 × 10-3, q_pval = 4.1 × 10-2) levels were directly associated with T2D risk. Conversely, no causal relationships between other nutrients and T2D were established. We hypothesize that phenylalanine and dihomo-gamma-linolenic acid contribute to the pathogenesis of T2D. Clinically, the use of foods with high phenylalanine content may pose potential risks for patients with a heightened risk of T2D. Our study provides evidence supporting a causal link between dietary nutrient intake and the development of T2D.

Associations between varicose veins and heart failure: A genetic correlation and mendelian randomization study.

Varicose veins and heart failure (HF) are increasingly prevalent. Although numbers of observational studies have indicated that varicose veins might contribute to the risk of HF, the causal relationship between them remains unclear due to the uncontrolled confounding factors and reverse causation bias. Therefore, this study aimed to explore the potential causal relationship between varicose veins and HF. Based on publicly released genome-wide association studies (GWAS), gene correlation was assessed using linkage disequilibrium score (LDSC) regression, and we conducted a two-sample Mendelian randomization (TSMR) analysis to infer the causal relationship. We performed the Inverse variance weighted (IVW) method as the primary analysis, and used Weighted median, MR-Egger, weighted mode, simple mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods to detect and correct for horizontal pleiotropy. LDSC revealed there was a positive genetic correlation between varicose veins and HF (rg = 0.1726184, Se = 0.04511803, P = .0001). The results of the IVW method indicated that genetically predicted varicose veins were associated with an increased risk of HF (odds ratio (OR) = 1.03; 95% confidence interval (CI): 1.01-1.06; P = .009). Our findings illustrated the significant causal effect of varicose veins on HF, suggesting that people with varicose veins might have a higher risk of HF. The results provided a novel and important perspective into the development mechanism of HF.

Causal relationship of interleukin-6 and its receptor on sarcopenia traits using mendelian randomization.

BACKGROUND: Previous research has extensively examined the role of interleukin 6 (IL-6) in sarcopenia. However, the presence of a causal relationship between IL-6, its receptor (IL-6R), and sarcopenia remains unclear. METHOD: In this study, we utilized summary-level data from genome-wide association studies (GWAS) focused on appendicular lean mass (ALM), hand grip strength, and walking pace. Single nucleotide polymorphisms (SNPs) were employed as genetic instruments for IL-6 and IL-6R to estimate the causal effect of sarcopenia traits. We adopted the Mendelian randomization (MR) approach to investigate these associations using the inverse variance weighted (IVW) method as the primary analytical approach. Additionally, we performed sensitivity analyses to validate the reliability of the MR results. RESULT: This study revealed a significant negative association between main IL-6R and eQTL IL-6R on the left grip strength were - 0.013 (SE = 0.004, p < 0.001) and -0.029 (SE = 0.007, p < 0.001), respectively. While for the right grip strength, the estimates were - 0.011 (SE = 0.001, p < 0.001) and - 0.021 (SE = 0.008, p = 0.005). However, no evidence of an association for IL-6R with ALM and walking pace. In addition, IL-6 did not affect sarcopenia traits. CONCLUSION: Our study findings suggest a negative association between IL-6R and hand grip strength. Additionally, targeting IL-6R may hold potential value as a therapeutic approach for the treatment of hand grip-related issues.

Identifying potential drug targets for idiopathic pulmonary fibrosis: a mendelian randomization study based on the druggable genes.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic fibrotic interstitial lung disease characterized by progressive dyspnea and decreased lung function, yet its exact etiology remains unclear. It is of great significance to discover new drug targets for IPF. METHODS: We obtained the cis-expression quantitative trait locus (cis-eQTL) of druggable genes from eQTLGen Consortium as exposure and the genome wide association study (GWAS) of IPF from the International IPF Genetics Consortium as outcomes to simulate the effects of drugs on IPF by employing mendelian randomization analysis. Then colocalization analysis was performed to calculate the probability of both cis-eQTL of druggable genes and IPF sharing a causal variant. For further validation, we conducted protein quantitative trait locus (pQTL) analysis to reaffirm our findings. RESULTS: The expression of 45 druggable genes was significantly associated with IPF susceptibility at FDR < 0.05. The expression of 23 and 15 druggable genes was significantly associated with decreased forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLco) in IPF patients, respectively. IPF susceptibility and two significant genes (IL-7 and ABCB2) were likely to share a causal variant. The results of the pQTL analysis demonstrated that high levels of IL-7 in plasma are associated with a reduced risk of IPF (OR = 0.67, 95%CI: 0.47-0.97). CONCLUSION: IL-7 stands out as the most promising potential drug target to mitigate the risk of IPF. Our study not only sheds light on potential drug targets but also provides a direction for future drug development in IPF.

Causal relationship between rheumatoid arthritis and bronchiectasis: a bidirectional mendelian randomization study.

BACKGROUND: Epidemiological observational studies have elucidated a correlation between rheumatoid arthritis (RA) and bronchiectasis. However, the causal nature of this association remains ambiguous. To clarify this potential causal linkage, we conducted a two-sample Mendelian randomization (MR) analysis to explore the bidirectional causality between RA and bronchiectasis. METHODS: Summary statistics for RA and bronchiectasis were obtained from the IEU OpenGWAS database We employed various methods, including inverse variance weighting (IVW), MR-Egger, weighted median, weighted mode, and simple mode, to explore potential causal links between RA and bronchiectasis. Additionally, a series of sensitivity studies, such as Cochran's Q test, MR Egger intercept test, and leave-one-out analysis, were conducted to assess the MR analysis's accuracy further. RESULTS: In the forward MR analysis, the primary analysis indicated that a genetic predisposition to RA correlated with an increased risk of bronchiectasis in European populations (IVW odds ratio (OR): 1.28, 95% confidence interval (CI): 1.20-1.37, p = 1.18E-13). Comparable results were noted in the East Asian subjects (IVW OR: 1.55, 95% CI: 1.30-1.34, p = 8.33E-07). The OR estimates from the other four methods were consistent with those obtained from the IVW method. Sensitivity analysis detected no evidence of horizontal pleiotropy or heterogeneity. Conversely, in the reverse MR analysis, we found no evidence to support a genetic causality between bronchiectasis and RA in either European or East Asian populations. CONCLUSION: This study indicates that genetic predisposition to RA correlates with a heightened risk of bronchiectasis in both European and East Asian populations. These results imply that routine screening for bronchiectasis in RA patients could be beneficial, and effective management of RA may contribute to a reduced risk of bronchiectasis. Future research should aim to clarify the underlying mechanisms linking these two conditions.

Dried fruit intake can lower the risk of ulcerative colitis: evidence from a Mendelian randomization study.

BACKGROUND AND OBJECTIVES: This study aims to examine the causal relationship between dietary factors and ulcerative colitis (UC). METHODS AND STUDY DESIGN: The analysis utilized data from genome-wide association studies (GWAS). Dried fruit, vegetables, processed meat, fresh fruit, and cereal intake were examined as exposure factors. UC was considered the outcome. Two-sample Mendelian randomization (TSMR) analysis was performed using methods. Heterogeneity and horizontal pleiotropy assessments were conducted to ensure the robustness of our findings. Additionally, we applied False Discovery Rate (FDR) corrections for multiple tests. RESULTS: The analysis revealed a significant inverse causal relationship between dried fruit intake and UC risk (odds ratio [OR]: 0.488, 95% confidence interval [CI]: 0.261 to 0.915, p = 0.025). No significant association was observed between vegetable intake (OR: 1.742, 95% CI: 0.561 to 5.415, p = 0.337), processed meat intake (OR: 1.136, 95% CI: 0.552 to 2.339, p = 0.729), fresh fruit intake (OR: 0.977, 95% CI: 0.465 to 2.054, p = 0.952), cereal intake (OR: 1.195, 95% CI: 0.669 to 2.134, p = 0.547). The low heterogeneity observed across analyses and the confirmation of stability through leave-one-out analysis reinforce the reliability of these results. Moreover, after adjusting for multiple tests, none of the dietary factors reached a p-value below the conventional significance threshold of 0.05. CONCLUSIONS: This study provides evidence of a potential association between dried fruit intake and a reduced risk of UC. Further MR studies incorporating larger GWAS datasets are needed to confirm these findings.

Appendicular lean mass and the risk of stroke and Alzheimer's disease: a mendelian randomization study.

BACKGROUND: Appendicular lean mass (ALM) is a good predictive biomarker for sarcopenia. And previous studies have reported the association between ALM and stroke or Alzheimer's disease (AD), however, the causal relationship is still unclear, The purpose of this study was to evaluate whether genetically predicted ALM is causally associated with the risk of stroke and AD by performing Mendelian randomization (MR) analyses. METHODS: A two-sample MR study was designed. Genetic variants associated with the ALM were obtained from a large genome-wide association study (GWAS) and utilized as instrumental variables (IVs). Summary-level data for stroke and AD were generated from the corresponding GWASs. We used random-effect inverse-variance weighted (IVW) as the main method for estimating causal effects, complemented by several sensitivity analyses, including the weighted median, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Multivariable analysis was further conducted to adjust for confounding factors, including body mass index (BMI), type 2 diabetes mellitus (T2DM), low density lipoprotein-C (LDL-C), and atrial fibrillation (AF). RESULTS: The present MR study indicated significant inverse associations of genetically predicted ALM with any ischemic stroke ([AIS], odds ratio [OR], 0.93; 95% confidence interval [CI], 0.89-0.97; P = 0.002) and AD (OR, 090; 95% CI 0.85-0.96; P = 0.001). Regarding the subtypes of AIS, genetically predicted ALM was related to the risk of large artery stroke ([LAS], OR, 0.86; 95% CI 0.77-0.95; P = 0.005) and small vessel stroke ([SVS], OR, 0.80; 95% CI 0.73-0.89; P < 0.001). Regarding multivariable MR analysis, ALM retained the stable effect on AIS when adjusting for BMI, LDL-C, and AF, while a suggestive association was observed after adjusting for T2DM. And the estimated effect of ALM on LAS was significant after adjustment for BMI and AF, while a suggestive association was found after adjusting for T2DM and LDL-C. Besides, the estimated effects of ALM were still significant on SVS and AD after adjustment for BMI, T2DM, LDL-C, and AF. CONCLUSIONS: The two-sample MR analysis indicated that genetically predicted ALM was negatively related to AIS and AD. And the subgroup analysis of AIS revealed a negative causal effect of genetically predicted ALM on LAS or SVS. Future studies are required to further investigate the underlying mechanisms.

Integrated analysis of single cell-RNA sequencing and Mendelian randomization identifies lactate dehydrogenase B as a target of melatonin in ischemic stroke.

AIMS: Despite the success of single-cell RNA sequencing in identifying cellular heterogeneity in ischemic stroke, clarifying the mechanisms underlying these associations of differently expressed genes remains challenging. Several studies that integrate gene expression and gene expression quantitative trait loci (eQTLs) with genome wide-association study (GWAS) data to determine their causal role have been proposed. METHODS: Here, we combined Mendelian randomization (MR) framework and single cell (sc) RNA sequencing to study how differently expressed genes (DEGs) mediating the effect of gene expression on ischemic stroke. The hub gene was further validated in the in vitro model. RESULTS: We identified 2339 DEGs in 10 cell clusters. Among these DEGs, 58 genes were associated with the risk of ischemic stroke. After external validation with eQTL dataset, lactate dehydrogenase B (LDHB) is identified to be positively associated with ischemic stroke. The expression of LDHB has also been validated in sc RNA-seq with dominant expression in microglia and astrocytes, and melatonin is able to reduce the LDHB expression and activity in vitro ischemic models. CONCLUSION: Our study identifies LDHB as a novel biomarker for ischemic stroke via combining the sc RNA-seq and MR analysis.

MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation.

BACKGROUND: Mendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies and is often used as a sensitivity analysis for pleiotropy. However, because there are no plurality valid regression estimators, modal estimators for multivariable-MR have been under-explored. METHODS: We use the residual framework for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and an estimator which instead has the residuals fed into the contamination mixture method (CM), multivariable-CM. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer's disease as an applied example. RESULTS: In our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer's disease, while education, and household income do not have a causal effect. CONCLUSIONS: Here we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, "multivariable-CM" which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This estimator uses a plurality of variants valid assumption, and appears to provide precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy.

Valid instrumental variable selection method using negative control outcomes and constructing efficient estimator.

In observational studies, instrumental variable (IV) methods are commonly applied when there are unmeasured covariates. In Mendelian randomization, constructing an allele score using many single nucleotide polymorphisms is often implemented; however, estimating biased causal effects by including some invalid IVs poses some risks. Invalid IVs are those IV candidates that are associated with unobserved variables. To solve this problem, we developed a novel strategy using negative control outcomes (NCOs) as auxiliary variables. Using NCOs, we are able to select only valid IVs and exclude invalid IVs without knowing which of the instruments are invalid. We also developed a new two-step estimation procedure and proved the semiparametric efficiency of our estimator. The performance of our proposed method was superior to some previous methods through simulations. Subsequently, we applied the proposed method to the UK Biobank dataset. Our results demonstrate that the use of an auxiliary variable, such as an NCO, enables the selection of valid IVs with assumptions different from those used in previous methods.

Causal relationship between sarcopenia with osteoarthritis and the mediating role of obesity: a univariate, multivariate, two-step Mendelian randomization study.

BACKGROUND: Recent genetic evidence supports a causal role for sarcopenia in osteoarthritis, which may be mediated by the occurrence of obesity or changes in circulating inflammatory protein levels. Here, we leveraged publicly available genome-wide association study data to investigate the intrinsic causal relationship between sarcopenia, obesity, circulating inflammatory protein levels, and osteoarthritis. METHODS: In this study, we used Mendelian randomization analyses to explore the causal relationship between sarcopenia phenotypes (Appendicular lean mass [ALM], Low hand-grip strength [LHG], and usual walking pace [UWP]) and osteoarthritis (Knee osteoarthritis [KOA], and Hip osteoarthritis [HOA]). Univariable Mendelian randomization (UVMR) analyses were performed using the inverse variance weighted (IVW) method, MR-Egger, weighted median method, simple mode, and weighted mode, with the IVW method being the primary analytical technique. Subsequently, the independent causal effects of sarcopenia phenotype on osteoarthritis were investigated using multivariate Mendelian randomization (MVMR) analysis. To further explore the mechanisms involved, obesity and circulating inflammatory proteins were introduced as the mediator variables, and a two-step Mendelian randomization analysis was used to explore the mediating effects of obesity and circulating inflammatory proteins between ALM and KOA as well as the mediating proportions. RESULTS: UVMR analysis showed a causal relationship between ALM, LHG, UWP and KOA [(OR = 1.151, 95% CI: 1.087-1.218, P = 1.19 × 10-6, PFDR = 7.14 × 10-6) (OR = 1.215, 95% CI: 1.004-1.470; P = 0.046, PFDR = 0.055) (OR = 0.503, 95% CI: 0.292-0.867; P = 0.013, PFDR = 0.027)], and a causal relationship between ALM, UWP and HOA [(OR = 1.181, 95% CI: 1.103-1.265, P = 2.05 × 10-6, PFDR = 6.15 × 10-6) (OR = 0.438, 95% CI: 0.226-0.849, P = 0.014, PFDR = 0.022)]. In the MVMR analyses adjusting for confounders (body mass index, insomnia, sedentary behavior, and bone density), causal relationships were observed between ALM, LHG, UWP and KOA [(ALM: OR = 1.323, 95%CI: 1.224- 1.431, P = 2.07 × 10-12), (LHG: OR = 1.161, 95%CI: 1.044- 1.292, P = 0.006), (UWP: OR = 0.511, 95%CI: 0.290- 0.899, P = 0.020)], and between ALM and HOA (ALM: OR = 1.245, 95%CI: 1.149- 1.348, P = 7.65 × 10-8). In a two-step MR analysis, obesity was identified to play a potential mediating role in ALM and KOA (proportion mediated: 5.9%). CONCLUSIONS: The results of this study suggest that decreased appendicular lean mass, grip strength, and walking speed increase the risk of KOA and decreased appendicular lean mass increases the risk of HOA in patients with sarcopenia in a European population. Obesity plays a mediator role in the occurrence of KOA due to appendicular lean body mass reduction.

Associations between immune cells signatures and osteoarthritis: An integrated analysis of bidirectional Mendelian randomization and Bayesian colocalization.

BACKGROUND: Previous investigations have explored the associations between immune cell signatures and osteoarthritis (OA); however, causality remains unclear. This study employs an integrated analysis, combining bidirectional Mendelian randomization (MR) and Bayesian colocalization (Coloc), to investigate causal relationships between 731 immune cells signatures and OA, identifying shared causal variants. METHODS: Utilizing publicly available summary data, this study primarily employs inverse variance weighting (IVW). Supplementary methods include MR-Egger regression, weighted median, weight mode, and simple mode. Various sensitivity tests, including Cochran's Q test, MR pleiotropy Residual Sum and Outlier, and leave-one-out tests, were conducted to assess the robustness of the analysis results. Coloc was employed to identify shared causal genetic variants among potential associations. RESULTS: IVW analysis revealed 196 immune cell signatures potentially linked to OA across diverse subtypes. Reverse MR analyses indicated the causal impact of OA on the levels of 140 immune cell signatures, with subtype-specific variations. Notably, several specific associations, including CD64 on CD14-CD16 + monocyte for Hip OA (OR = 1.0593, 95 % CI: 1.0260-1.0938, P = 0.0004), HLA-DR on CD14 + CD16- monocyte (OR = 0.9664, 95 % CI: 0.9497-0.9834, P = 0.0001), HLA-DR on CD14 + monocyte (OR = 0.9680, 95 % CI: 0.9509-0.9853, P = 0.0003) in the Knee or Hip OA, PDL-1 on CD14-CD16 + monocyte by All OA (OR = 1.7091, 95 %CI:1.2494-2.3378, P = 0.0008), and herpesvirus entry mediator on effector memory CD4 + T cell by Spine OA (OR = 0.5200, 95 %CI:0.3577-0.7561, P = 0.0006) remained significant post-Bonferroni correction. Sensitivity tests validated the credibility of the IVW analysis. Additionally, Coloc revealed several potential associations among shared genetic variants, including rs115328872, rs1800973, and rs317667. CONCLUSIONS: Our findings provide evidence for the potential involvement of immune cell signatures in OA development, revealing avenues for early prevention and innovative therapeutic strategies.

Association between allergic diseases and both psoriasis and psoriatic arthritis: a bidirectional 2-sample Mendelian randomization study.

Background An increasing body of observational studies has indicated a potential link between allergic diseases, namely atopic dermatitis (AD), allergic rhinitis (AR), allergic asthma (AA), and psoriasis (PSO) as well as psoriatic arthritis (PSA). However, the presence and causal direction of this association remain uncertain. Methods We conducted two-sample Mendelian randomization (TSMR) analyses utilizing summary statistics derived from genome-wide association studies (GWAS) consortia. The summary statistics were obtained from a substantial participant cohort, consisting of 116,000 individuals (21,000 AD cases and 95,000 controls), 462,933 individuals (26,107 AR cases and 436,826 controls), and 140,308 individuals (4859 AA cases and 135,449 controls). The summary statistics for PSO (9267 cases and 360,471 controls) and PSA (3186 cases and 240,862 controls) were sourced from the FinnGen database. The primary analytical approach employed inverse variance weighting (IVW) as the main method within TSMR. We validated our findings through a series of sensitivity analyses. Furthermore, we performed reverse TSMR analyses to evaluate the potential presence of reverse causality. Results Our investigation revealed a potential protective effect of AD against both PSO (OR = 0.922, 95% CI = 0.863-0.984, p = 0.015)and PSA(OR = 0.915, 95% CI = 0.843-0.993, p = 0.033). Moreover, employing inverse MR analysis, we obtained compelling evidence supporting the protective role of PSO in preventing AD (OR = 0.891, 95% CI = 0.829-0.958, p = 0.002), as well as AR (OR = 0.998, 95% CI = 0.996-0.999, p = 0.008), these associations remained statistically significant even after Bonferroni correction was applied to account for multiple comparisons. Furthermore, our findings did not reveal any substantial causal relationship between AA and either PSO or PSA. Conclusion Our study provides compelling evidence that PSO significantly confers protection against both AD and AR, while AD is likely to act as a protective factor for both PSO and PSA. Despite previous studies suggesting an association between allergic diseases and the incidence of PSO and PSA, our findings do not support this claim. To obtain more accurate and reliable conclusions regarding the causal mechanisms involved, larger sample sizes in randomized controlled trials or MR studies are warranted.

Juvenile idiopathic arthritis and primary ovarian failure: a two-sample Mendelian randomization analysis in a mixed-gender cohort.

Background: The causal relationship between juvenile idiopathic arthritis (JIA) and primary ovarian failure (POF) remains uncertain. To elucidate this relationship, we employed a two-sample Mendelian randomization analysis. Methods: The single nucleotide polymorphisms (SNPs) associated with JIA were obtained from a previously published genome-wide association study (GWAS), while the pooled data for POF originated from the FinnGen consortium. The study populations consisted exclusively of individuals of European descent. In our Mendelian randomization analysis, we performed inverse-variance weighted analysis, weighted-median analysis, weighted-mode analysis and Mendelian randomization-Egger regression analysis, supplemented by sensitivity analyses to validate the accuracy and robustness of the findings. Results: The IVW (OR = 1.23, 95% CI 1.06-1.43; P = 0.007) and weighted median (OR = 1.25, 95% CI 1.06-1.47; P = 0.009), along with sensitivity analysis validation, provide compelling evidence of a significant causal association between JIA and POF. Conclusion: The study revealed a significant causal association between genetically predicted JIA and POF, indicating that JIA significantly elevates the risk of developing POF. Therefore, it is recommended to implement screening for premature ovarian failure in women diagnosed with JIA.

Causal Associations of DNA Methylation and Cardiovascular Disease: A Two-Sample Mendelian Randomization Study.

Background: There is growing evidence that concentrations of DNA methylation are associated with cardiovascular disease; however, it is unclear whether this association reflects a causal relationship. Methods: We utilized a two-sample Mendelian randomization (MR) approach to investigate whether DNA methylation can affect the risk of developing cardiovascular disease in human life. We primarily performed the inverse variance weighted (IVW) method to analyze the causal effect of DNA methylation on multiple cardiovascular diseases. Additionally, to ensure the robustness of our findings, we conducted several sensitivity analyses using alternative methodologies. These analysis methods included maximum likelihood, MR-Egger regression, weighted median method, and weighted model methods. Results: Inverse variance weighted estimates suggested that an SD increase in DNA methylation Hannum age acceleration exposure increased the risk of cardiac arrhythmias (OR = 1.03, 95% CI 1.00-1.05, p = 0.0290) and atrial fibrillation (OR = 1.03, 95% CI 1.00-1.05, p = 0.0022). We also found that an SD increase in DNA methylation PhenoAge acceleration exposure increased the risk of heart failure (OR = 1.01, 95% CI 1.00-1.03, p = 0.0362). Exposure to DNA methylation-estimated granulocyte proportions was found to increase the risk of hypertension (OR = 1.00, 95% CI 1.00-1.0001, p = 0.0291). Exposure to DNA methylation-estimated plasminogen activator inhibitor-1 levels was found to increase the risk of heart failure (OR = 1.00, 95% CI 1.00-1.00, p = 0.0215). Conclusion: This study reveals a causal relationship between DNA methylation and CVD. Exposed to high levels of DNA methylation Hannum age acceleration inhabitants with an increased risk of cardiac arrhythmias and atrial fibrillation. DNA methylation PhenoAge acceleration levels exposure levels were positively associated with the increased risk of developing heart failure. This has important implications for the prevention of cardiovascular diseases.

Association between air pollution and skin cutaneous melanoma: A Mendelian randomization study.

There has been a consistent and notable increase in the global prevalence of skin cutaneous melanoma (SKCM). Although genetic factors are closely associated with the occurrence and development of melanoma, the potential influence of environmental factors cannot be overlooked. The existing literature lacks a definitive consensus on the correlation between air pollution and the incidence rate of SKCM. This study seeks to investigate the causal relationship between air pollution, specifically focusing on particulate matter (PM) 2.5, PM2.5-10, PM10, and nitrogen oxides, and the risk of SKCM. A 2-sample Mendelian randomization (MR) method was applied, utilizing extensive publicly accessible genome-wide association studies summary datasets within European populations. The primary analytical method employed was the inverse variance weighted method. Supplementary methods, including the weighted median model, MR-Egger, simple model, and weighted model, were chosen to ensure robust analysis. Heterogeneity assessment was conducted using Cochran's Q test. To identify potential pleiotropy, both MR-Egger regression and the MR-PRESSO global test were employed. Additionally, a sensitivity analysis was performed using the leave-one-out method. The analysis revealed no statistically significant association between air pollution and SKCM risk, with specific findings as follows: PM2.5 (P = .485), PM2.5-10 (P = .535), PM10 (P = .136), and nitrogen oxides (P = .745). While some results exhibited heterogeneity, all findings demonstrated an absence of pleiotropy. This study did not find substantive evidence supporting a causal relationship between air pollution and the risk of SKCM within European populations. The comprehensive MR analysis, encompassing various pollutants, suggests that environmental factors such as air pollution may not be significant contributors to the development of SKCM.