Reciprocal Causal Links in RA Pathogenesis: A Bidirectional MR Study Targeting Th17 Lineage, and CD123-Expressing Dendritic Subsets

BackgroundImmune factors are crucial in the pathogenesis of rheumatoid arthritis (RA), and immune cells play a key role in the development of RA. However, there is still disagreement regarding the specific roles of each type of immune cell in the pathological process of RA.MethodsThis study used bidirectional two-sample Mendelian randomization (MR) analysis to determine the causal relationship between immune cell characteristics and RA. Utilizing publicly available genetic data, we initially treated immune cell characteristics as exposures to investigate their causal effects on the risk of RA. Subsequently, we performed reverse two-sample MR using the positively selected cells from the initial analysis as outcomes, aiming to identify the core immune cells involved. Finally, a comprehensive sensitivity analysis was conducted to validate the robustness, heterogeneity, and horizontal pleiotropy of the results.ResultsUsing data from 731 immune cells as exposures and cell SNPs as instruments, we independently conducted two-sample MR analysis for each patient with RA. The main analytical method used was the IVW method, with a significance level set at P < 0.05 for inclusion. In total, we identified 42 immune cell phenotypes that were causally associated with the onset of RA. For the reverse MR analysis, we used RA as the exposure factor and focused on 42 immune cell phenotypes as outcomes. Our analysis revealed causal relationships between the onset of RA and 7 immune cell phenotypes. Among these, 6 showed positive causal relationships, while 1 exhibited a negative causal relationship.ConclusionsOur study emphasized the causal relationship between immune cells and RA through bidirectional two-sample MR analysis, identifying the immune cells causally associated with RA.

Rheumatoid arthritis (RA) and osteoarthritis (OA) are prevalent chronic joint disorders with immunological pathogenesis. However, the causal relationships between circulating immune cells and them remain largely unknown. Therefore, we conducted a bidirectional two-sample Mendelian randomization (MR) study to determine their causal relationship. Genome-wide association study summary statistics were extracted from publicly available databases regarding immune cell phenotypes, RA, and OA. MR analysis was conducted using five MR methods, with inverse-variance-weighted (IVW) as the primary analysis method. False discovery rate correction (FDR) was used to reduce the likelihood of type 1 errors. We also conducted MR-Egger intercept tests to evaluate horizontal pleiotropy. After FDR adjustment of the P values for the IVW method, the CD27 expression on memory B cells was negatively related to the risk of RA (P < 0.001), and the human leukocyte antigen (HLA)--DR expression on CD14+ monocytes was negatively related to the risk of OA (P < 0.001). We also found that RA was negatively associated with the expression of HLA-DR on myeloid dendritic cells (P < 0.001), but significant horizontal pleiotropy was observed. Our study demonstrates a causal relationship between specific immune cell traits and RA as well as OA, providing further insight into the role of immune cells in the pathogenesis of these disorders.

Causal relationship between cancer and immune cell traits: A two-sample mendelian randomization study

The causal relationship between immune cell signatures and multiple myeloma (MM) pathobiology remains incompletely understood. This study aimed to explore the bidirectional causal associations between 731 circulating immune cell traits and MM risk using a two-sample, bidirectional Mendelian randomization (MR) approach. Two-sample MR analyses were conducted utilizing genome-wide association study (GWAS) summary statistics for 731 immune cell phenotypes and MM GWAS datasets. Sensitivity analyses were performed to assess the robustness and reliability of the findings. Furthermore, meta-analyses were conducted on specific immune cell traits identified through the primary MR analyses to reinforce causal inferences. We identified 11 immune cell traits across 3 immune profiles - absolute cell count (AC), relative cell (RC) frequency, and median fluorescence intensity (MFI) - that exhibited significant causal associations with MM. Three immune traits were associated with an increased risk of MM: CD39+ CD8br %CD8br (P < .001), CD20 on CD20- CD38- cells (P = .002), and CD38 on transitional cells (P < .001). Conversely, 8 immune traits were found to confer a protective effect against MM, including CD11c+ monocyte AC (P = .002), Im myeloid-derived suppressor cell (MDSC) %CD33dim HLA-DR- CD66b- (P = .002), CD8dim %T cell (P < .001), CD8dim %leukocyte (P < .001), CD24 on CD24+ CD27+ cells (P = .003), CD4 on naive CD4+ cells (P < .001), CD11b on Mo MDSCs (P = .002), and HLA-DR on CD33dim HLA-DR+ CD11b- cells (P < .001). The reverse MR analysis demonstrated a significant causal association between the expression of CD19 on CD24+ CD27+ B cells and CD16 on CD14+ CD16+ monocytes in MM. These findings were validated through sensitivity tests and meta-analyses, which confirmed the robustness of the results and the absence of significant heterogeneity. Our bidirectional MR analyses provide compelling evidence for causal relationships between specific immune cell phenotypes and MM risk. These insights deepen the understanding of immune system dysregulation in MM pathogenesis and highlight potential immune-related targets for future therapeutic interventions.

Background: Accumulation of inflammatory leukocytes in articular tissues is the hallmark feature of rheumatoid arthritis (RA). Increasing evidence from observational studies has suggested that several cytokines may be involved in the development of RA. However, traditional observational studies are susceptible to bias from confounding and reverse causation; therefore, the potential causal relationships of individual cytokines with the risk of RA remain elusive. Objective: In this study, we evaluated whether genetically determined circulating levels of cytokines were associated with the risk of RA by performing Mendelian randomization (MR). Methods: We identified single nucleotide polymorphisms (SNPs) associated with circulating levels of cytokines and growth factors from a genome-wide association study (GWAS) including 8,293 participants of Finnish ancestry as instrumental variables (IVs). The association estimates of these IVs with the risk of RA were obtained from a GWAS meta-analysis including 14,361 RA cases and 43,923 controls of European ancestry. We conducted a series of MR analyses to assess the relationship between genetically determined circulating cytokines and the risk of RA, including the random-effects inverse variance-weighted, weighted-median, MR-Egger regression, and MR pleiotropy residual sum and outlier tests. For potential cytokine-RA associations supported by MR evidence, sensitivity analyses were further performed using restricted IV sets of SNPs with colocalization evidence and that excluding pleiotropic SNPs. Results: In the primary MR analysis, there was a suggestive inverse association between genetically determined circulating level of macrophage inflammatory protein-1β (MIP-1b) and the risk of RA [odds ratio (OR): 0.95, 95% confidence interval (CI) = 0.92-0.99, p = 0.016]. The effect estimates were similar in alternative MR analyses. Among SNPs used as IVs for MIP-1b, we found 92 SNPs without documented pleiotropy and three SNPs with evidence of colocalization. The association of MIP-1b with RA from sensitivity analyses using these two sets of restricted IVs remained stable. Conclusion: Our study suggests that genetically determined elevated circulating level of MIP-1b may be associated with a lower risk of RA. Further studies are warranted to determine how MIP-1b and related pathways may contribute to the development of RA.

Rheumatoid arthritis (RA) is one of the most common autoimmune joint disorders that leads to cartilage degradation. However, its specific correlation with immune cells has not been thoroughly clarified. Based on the two-sample Mendelian randomization (MR) analysis, the association between RA and 731 immune phenotypes which include morphological parameters (MP), relative cell (RC), median fluorescence intensities (MFI), and absolute cells (AC) was comprehensively determined. After false discovery rate correction, RA and immunophenotypes were statistically associated with each other. It was observed that four immune phenotypes, including 1 MPs, 8 RCs, 15 MFIs, and 10 ACs were causally associated with the risk of RA. Meanwhile, several identified immune traits could serve as independent factors for RA and be robust against pleiotropy. While considering the role of RA in immune traits, the involvement of RA in multiple immunophenotypes including CD62L- myeloid DC AC, CD3 on secreting Treg, CD3 on activated and secreting Treg, and CD3 on CD4 Treg was revealed. This study is the first comprehensive evaluation of the interaction between immune response and RA risk, thus providing therapeutic strategies for RA from an immunological perspective.

Immune system and inflammation had a great influence on the progression of muscle atrophy. However, the causal relationship with specific immune cell traits remained uncertain. The aim of this study was to elucidate the genetic influences on these associations, providing insights into the underlying mechanisms of muscle atrophy. A bidirectional two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationship between immune cell phenotypes and muscle atrophy. Data on immune cell phenotypes were obtained from a research cohort containing data on 731 immune cell phenotypes and data on muscle atrophy were sourced from a Finnish database. MR analysis was performed using the MR-Egger method, weighted median, inverse variance weighting, heterogeneity testing, sensitivity analysis, and multiplicity analysis, with results subjected to false discovery rate(FDR) correction. Additionally, the UK Biobank cohort was utilized as an external validation. A total of 31 immune phenotypes with causal relationships with muscle atrophy were identified, including various phenotypes of conventional dendritic cells, myeloid cells, T cells/B cells/natural killer cells, regulatory cells, and T cell maturation stages. Among them, 12 immune phenotypes were identified as exhibiting a positive causal relationship with muscle atrophy, while 19 immune phenotypes were demonstrated to have a negative causal association, highlighting the complex interactions between immune cells and muscle health. The results of the reverse MR analysis indicated that a negative correlation between muscle atrophy and CD28 on secreting Treg (OR = 0.9038, 95%CI:0.8308 ~ 0.9832, P = 0.0186). A significant positive correlation was revealed by external datasets between the CD25 on IgD + CD38- immune phenotype and the risk of muscle atrophy, which was consistent with the trend observed in the training group (OR = 1.1041, 95% CI: 1.1005–1.1076, P = 0.0263). No evidence of pleiotropy was observed, and the reliability of these findings was demonstrated by the leave-one-out analysis. The findings highlight significant correlations between certain immune cell features and muscle atrophy, providing potential targets for further investigation of immunological mechanisms and therapeutic interventions for this condition.

BackgroundImmune cell phenotypes have been implicated in the development and progression of esophageal cancer (EC), but their causal relationships remain unclear. This study aimed to explore the potential causal associations between immune cell traits and EC risk using Mendelian randomization (MR) analysis.MethodsA bidirectional two-sample MR analysis was conducted using genome-wide association study data from European populations. Genetic variants significantly associated with 731 immune cell phenotypes (P < 5 × 10−8) were selected as instrumental variables. The primary analysis employed the inverse variance weighted method, with sensitivity analyses including MR-Egger, weighted median, simple mode, and weighted mode methods. Heterogeneity and pleiotropy were assessed using Cochran’s Q test and MR-Egger intercept test.ResultsSeven immune cell phenotypes were positively associated with an increased risk of EC, including SSC-A + on CD8 + T cells (P = 0.006), CD16 + monocytes (P = 0.013), and myeloid dendritic cells (P = 0.014). Conversely, CD3 + on HLA-DR + T cells (P = 0.017) and CD4 + T cell absolute count (P = 0.014) showed protective effects against EC. Sensitivity analyses confirmed these associations with minimal heterogeneity or pleiotropy. Reverse MR analysis found no evidence suggesting that EC causally influences immune cell phenotypes.ConclusionThis study provides genetic evidence supporting causal relationships between specific immune cell phenotypes and EC risk. Immune traits such as T cells, monocytes, and dendritic cells may serve as potential biomarkers or therapeutic targets for EC management. Further studies are needed to validate these findings and explore their clinical implications.

BackgroundThe pathogenesis of rheumatoid arthritis (RA) is an immune imbalance, in which various inflammatory immune cells and pro-inflammatory factors are involved. Interleukin-17 (IL-17), a potent pro-inflammatory cytokine, has been found to have increased expression in the joints of patients with RA compared to healthy individuals. However, the causal relationship between the expression level of IL-17 or IL-17 receptor (IL-17R) and RA remained unknown. In this study, two-sample Mendelian randomization (MR) was used to investigate the causal relationship between IL-17 and RA.MethodsSummary statistics for RA (14,361 RA cases and 43,923 healthy controls) and IL-17 (3,301 samples) were obtained from an available meta-analysis of published genome-wide association studies (GWAS). Relevant single nucleotide polymorphisms (SNPs) were selected by executing quality control steps from the GWAS summary results. Then we used bi-directional two-sample Mendelian randomization (MR) and multi-variable MR (MVMR) analysis to examine evidence of causality. MR and MVMR analyses progressed mainly using inverse variance weighted (IVW), weighted median (WM), and MR-Egger regression methods, which were applied to the genetic instrumental variables (IVs) of IL-17A/IL-17 RA, IL-17C/IL-17 RC, and IL-17D/IL-17RD and RA. For assessing the robustness of the results, we also carried out a sensitivity analysis to assess heterogeneity and pleiotropy, such as MR-Egger, leave-one-out, and MR pleiotropy residual sum and outlier (MR-PRESSO).ResultsTwo-sample MR Analysis showed the causal relationship between IL-17A/IL-17RA and RA. The presence of genetically high IL-17A/IL-17RA may increase the risk of RA (IL-17A(OR = 1.095; 95% C.I., 0.990-1.210, p.adj = 0.013), IL-17RA(OR = 1.113, 95%CI = 1.006-1.231, p.adj = 0.006)). However, the results indicated that IL-17C/IL-17RC, and IL-17D/IL-17RD demonstrated no causal impact on RA (IL-17C(OR = 1.007, 95%CI = 0.890-1.139, p.adj = 0.152), IL-17RC(OR = 1.006, 95%CI = 0.904-1.119, p.adj = 0.152), IL-17D(OR = 0.979, 95%CI = 0.843-1.137, p.adj = 0.130), IL-17RD(OR = 0.983, 95%CI = 0.876-1.104, p.adj = 0.129)). Furthermore, MVMR analysis shown that IL-17RA(OR = 1.049, 95% CI: 0.997-1.102, p.adj = 0.014) was associated with increased risk of RA. Sensitivity analysis showed no heterogeneity and pleiotropy, suggesting that the above results were robust and reliable.ConclusionThe MR analysis provides evidence that IL-17A/IL-17RA are risk factors for RA. This emphasizes the importance of intervention on IL-17A/IL-17RA in patients with RA. Developing drugs that limit IL-17A may reduce the risk of RA.

The synovial immune microenvironment plays a critical role in the onset and advancement of osteoarthritis (OA), but previous findings on some immune cells were inconsistent. This study seeks to comprehensively investigate the causal association between a multitude of immune cell traits and OA. We performed this bidirectional Mendelian randomization (MR) analysis between a genome-wide association studies (GWAS) summary statistics containing 407,746 European ancestry and the largest GWAS data on 731 immune phenotypes. A replication analysis was conducted on a dataset containing 63,556 participants for validating the positive results. The causal effects were primarily estimated through inverse variance weighted (IVW) method, with four other methods (MR Egger, weighted median, simple mode, weighted mode) to reinforce the strength of causal evidence. Multiple sensitivity analyses (MR Egger, IVW method, leave-one-out analysis) were applied to mitigate the impact of heterogeneity and horizontal pleiotropy. Additionally, we employed a bioinformatics analysis by xCell algorithm to examine the expression of these immune cell phenotypes in OA and normal synovial tissues. After false discovery rate (FDR) correction test, thirteen immune cell traits exhibited significant causal relationships with OA. These immune cell phenotypes came from seven groups, including B cell (n=3), conventional dendritic cell (cDC) (n=3), monocyte (n=3), myeloid cell (n=1), T cell, B cell, natural killer (NK) cell (TBNK) (n=2), regulatory T cell (Treg) (n=1). The strongest effects on OA were found in "CD64 on CD14- CD16+ monocyte" [odds ratio (OR): 1.044; 95% confidence interval (CI): 1.012-1.076; PFDR=0.03] and "CD16+ monocyte %monocyte" (OR: 0.948; 95% CI: 0.916-0.980; PFDR=0.009). Sensitivity analyses did not detect any evidence of heterogeneity and horizontal pleiotropy. We also identify five immune traits influenced by OA. Additionally, replication analysis reconfirmed the causal effect of "CD64 on CD14- CD16+ monocyte" (OR: 1.102; 95% CI: 1.046-1.161; PFDR<0.001) and "HLA DR+ NK %NK" (OR: 0.945; 95% CI: 0.908-0.983; PFDR=0.03) on OA. Our findings reveal the causal relationships between specific immune cells and OA, offering genetic insights into the role of immune cells in OA pathogenesis and guiding the exploration of novel immunological treatments for OA.

Although there is an association between abdominal aortic aneurysm (AAA) and circulating immune cell phenotypes, the exact causal relationship remains unclear. This study aimed to explore the causal relationships between immune cell phenotypes and AAA risk using a bidirectional two-sample Mendelian randomization approach. Data from genome-wide association studies pertaining to 731 immune cell traits and AAA were systematically analyzed. Using strict selection criteria, we identified 339 immune traits that are associated with at least 3 single nucleotide polymorphisms. A comprehensive MR analysis was conducted using several methods including Inverse Variance Weighted, Weighted Median Estimator, MR-Egger regression, Weighted Mode, and Simple Median methods. CD24 on switched memory cells (OR = 0.922, 95% CI 0.914–0.929, P = 2.62e−79) at the median fluorescence intensities level, and SSC-A on HLA-DR + natural killer cells (OR = 0.873, 95% CI 0.861–0.885, P = 8.96e−81) at the morphological parameter level, exhibited the strongest causal associations with AAA. In the reverse analysis, no significant causal effects of AAA on immune traits were found. The study elucidates the causal involvement of multiple circulating immune cell phenotypes in AAA development, signifying their potential as diagnostic markers or therapeutic targets. These identified immune traits may be crucial in modulating AAA-related inflammatory pathways.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation in synovial joints and influenced by genetic and environmental factors. The immune system, comprising various cells that either exacerbate or reduce inflammation, plays a central role in RA pathogenesis. Despite extensive research, the causal relationships between immune cell phenotypes and RA remain unclear. We employed a two-sample Mendelian randomization (MR) approach to investigate the causal associations between 731 immune cell phenotypes and RA. Genetic variants, carefully selected based on rigorous criteria, served as instrumental variables to ensure analytical validity. Data on RA were derived from the FinnGen database, whereas immune cell phenotype data were obtained from the genome-wide association studies catalog. We employed 5 MR methods, including inverse variance weighted and MR Egger, to ensure robust causal inference. We assessed for pleiotropy and heterogeneity and adjusted findings using the False Discovery Rate. After False Discovery Rate adjustment (threshold < 0.05), inverse variance weighted analysis revealed potential causal relationships between 4 immune cell types and RA: CD62L− dendritic cells %dendritic cells (P = 3.88E‐05; 95% confidence interval [CI] = 1.056), CD19 on IgD+ CD38− naive cells (P = 1.75E‐04; 95% CI = 0.969), CD45RA on TD CD8br (P = 5.59E‐04; 95% CI = 0.919), and HLA DR on CD33− HLA DR+ (P = 8.13E‐05; 95% CI = 1.422). In reverse Mendelian studies, specific immune cell phenotypes were found to be associated with RA risk and progression: the percentage of memory B cells among lymphocytes (P = 2.74E‐04; 95% CI = 0.861), IgD+ CD24+ cells among lymphocytes (P = 6.93E‐04; 95% CI = 0.867), CD4+ CD8dim cells among lymphocytes (P = 2.92E‐04; 95% CI = 0.802), CD4+ CD8dim cells among leukocytes (P = 4.37E‐04; 95% CI = 0.814), and CD24 expression on IgD+CD24+ cells (P = 1.05E‐04; 95% CI = 0.857). These results identify immune cell phenotypes closely linked to RA susceptibility and progression. The findings suggest that specific immune cell phenotypes are not only influenced by RA but may also contribute to its development and progression. These results offer new insights into the immunological underpinnings of RA and highlight potential targets for therapeutic intervention. Future research should focus on validating these causal relationships in diverse populations and exploring the molecular mechanisms involved.

BackgroundBeef is common in daily diet, but its association with the risk of rheumatoid arthritis (RA) remains uncertain. The objective of this study is to explore the relationship between beef intake and the risk of RA.Materials and methodsWe investigated the association between beef intake and risk of RA by multivariate logistic regression, based on the National Health and Nutrition Examination Survey (NHANES) 1999–2016 involving 9,618 participants. The dose–response relationship between beef intake and RA was explored as well. Furthermore, we performed Mendelian randomization (MR) analysis to examine the causal effect of beef intake on RA. Genetic instruments for beef intake were selected from a genome-wide association study (GWAS) including 335,576 individuals from the UK Biobank study, and summary statistics relating to RA were obtained from a GWAS meta-analysis of 14,361 RA patients and 43,923 controls. The inverse-variance weighted (IVW) approach was used to estimate the causal association, and MR-Egger regression and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test were applied to evaluate the pleiotropy and outliers.ResultsCompared with the lowest quintile (0 to ≤33.50 g/d), beef intake was found to be significantly associated with the risk of RA [odds ratio (OR): 1.94; 95% confidence interval (CI): 1.20–3.12] in the third quintile (50.26 to ≤76.50 g/d). Moreover, a reversed “U” dose–response relationship between beef and RA (Pnon–linearity = 0.023) was found. In the MR analysis, beef intake was associated with an increased risk of RA (OR: 3.05; 95% CI: 1.11–8.35; P = 0.030) by the IVW method. The results from MR-Egger regression and MR-PRESSO test showed that there were no pleiotropic variations and outliers.ConclusionThis study indicated that there is suggestive evidence to support the causal effect of beef intake on the risk of RA, while further studies are warranted to elucidate the exact association.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by complex immune interactions. Elucidating the causal relationships between blood cell perturbations, immune cell subsets, and RA can provide valuable insights into its pathogenesis. This study employed bidirectional two-sample Mendelian Randomization (MR) to explore the causal effects of blood cell perturbations on RA risk, with a focus on immune cell mediation. Genetic data from large-scale Genome-Wide Association Studies (GWAS) were utilized to select instrumental variables (IVs) for exposure, mediator, and outcome. Inverse Variance Weighted (IVW) analysis was applied, supplemented by sensitivity tests. Mediation analysis was conducted to assess the indirect effects mediated by immune cells. Significant causal associations were identified between perturbations in reticulocytes, monocytes, and lymphocytes and specific immune cell subsets, including CD3 + CD39 + regulatory T cells (Tregs) and CD45RA + terminally differentiated CD8 + T cells (CD45RA + TD CD8 + cells). Erythropoiesis perturbation was associated with a reduced RA risk, while perturbations in monocytes and lymphocytes were found to facilitate RA progression through immune-mediated mechanisms. This study underscores the pivotal role of immune cell subsets in mediating the effects of blood cell perturbations on RA development. These findings suggest that targeting immune cell-mediated pathways, particularly those involving Tregs and CD8 + T cells, can provide new therapeutic strategies for RA management. Key Points • Causal Relationships: Mendelian randomization (MR) analysis identified significant causal relationships between specific blood cell disturbances (e.g., reticulocytes, monocytes, and lymphocytes) and rheumatoid arthritis (RA). • Role of Immune Cells: CD3 + CD39 + regulatory T cells (Tregs) and CD45RA + Terminally Differentiated CD8 + T cells (CD45RA + TD CD8 + cells) mediate the association between blood cell disturbances and RA. • Protective Role of Reticulocytes: Reticulocyte disturbances under potassium chloride (KCl) conditions are negatively associated with RA, potentially protecting joints from inflammatory damage by reducing oxidative stress. • Protective Role of Non-Classical Monocytes: Baseline disturbances in monocyte median side scatter are negatively associated with RA, suggesting non-classical monocytes may reduce RA-related inflammation. • Positive Association of Lymphocyte Disturbances with RA: Lymphocyte side scatter standard deviation under colchicine disturbances shows a significant positive association with RA, indicating abnormal T cell activation may exacerbate RA progression.AQ.

Editor's evaluation: Phenome-wide Mendelian randomisation analysis identifies causal factors for age-related macular degeneration