Large-scale meta-analysis across East Asian and European populations updated genetic architecture and variant-driven biology of rheumatoid arthritis, identifying 11 novel susceptibility loci

Causal association of rheumatoid arthritis with frailty and the mediation role of inflammatory cytokines: A Mendelian randomization study

BACKGROUND

Previous observational studies have suggested the association between rheumatoid arthritis (RA) and frailty. However, it remains obscure whether this association is causal. This study aims to investigate the causal association of RA with frailty and the mediation effect of inflammatory cytokines using Mendelian randomization (MR) design.

METHODS

Summary-level data for RA (N = 58,284), frailty index (FI) (N = 175,226), Fried frailty score (FFS) (N = 386,565), and 41 inflammatory cytokines (N = 8,293) were obtained from recent genome-wide association studies. Univariable and multivariable MR analyses were conducted to investigate and verify the causal association of RA with frailty. The potential mediation effects of inflammatory cytokines were estimated using two-step MR.

RESULTS

Univariable inverse variance weighted MR analysis suggested that genetically determined RA was associated with increased FI (beta=0.021; 95 % CI: 0.012, 0.03; p = 2.2 × 10-6) and FFS (beta=0.011; 95 %CI: 0.007, 0.015; p = 8.811 × 10-8). The consistent results were observed in multivariable MR analysis after adjustment for asthma, smoking, BMI, physical activity, telomere length, and depression. Mediation analysis showed evidence of an indirect effect of RA on FI through monokine induced by interferon-gamma (MIG) with a mediated proportion of 9.8 % (95 %CI: 4.76 %, 19.05 %), on FFS via MIG and stromal cell-derived factor-1 alpha with a mediated proportion of 9.6 % (95 %CI: 0 %, 18.18 %) and 8.44 % (95 %CI: 0 %, 18.18 %), respectively.

CONCLUSION

This study provided credible evidence that genetically predicted RA was associated with a higher risk of frailty. Additionally, inflammatory cytokines were involved in the mechanism of RA-induced frailty.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (β coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

Gut microbiota as a sensor of autoimmune response and treatment for rheumatoid arthritis

Rheumatoid arthritis (RA) is considered a multifactorial condition where interaction between the genetic and environmental factors lead to immune dysregulation causing autoreactivity. While among the various genetic factors, HLA-DR4 and DQ8, have been reported to be the strongest risk factors, the role of various environmental factors has been unclear. Though events initiating autoreactivity remain unknown, a mucosal origin of RA has gained attention based on the recent observations with the gut dysbiosis in patients. However, causality of gut dysbiosis has been difficult to prove in humans. Mouse models, especially mice expressing RA-susceptible and -resistant HLA class II genes have helped unravel the complex interactions between genetic factors and gut microbiome. This review describes the interactions between HLA genes and gut dysbiosis in sex-biased preclinical autoreactivity and discusses the potential use of endogenous commensals as indicators of treatment efficacy as well as therapeutic tool to suppress pro-inflammatory response in rheumatoid arthritis.

Novel insights into the complex interplay of immune dysregulation and inflammatory biomarkers in preeclampsia and fetal growth restriction: A two-step Mendelian randomization analysis

Background

The relationship between genetic immune dysregulation and the occurrence of preeclampsia (PE) or PE with fetal growth restriction (PE with FGR) has yielded inconsistent findings, and the underlying mediators of this association remain elusive. We aimed to explore the causal impact of genetic immune dysregulation on the risk of PE or PE with FGR and to elucidate the role of specific transcriptomes in mediating this relationship.

Methods

A two-step Mendelian randomization (MR) analysis was performed to explore the link between immune dysregulation and PE or PE with FGR, as well as to identify potential inflammatory biomarkers that act as mediators. GWAS summary data for outcomes were obtained from the FinnGen dataset. The analyses encompassed five systemic immune-associated diseases, four chronic genital inflammatory diseases, and thirty-one inflammatory biomarkers. Summary-data-based MR (SMR) and HEIDI analysis were conducted to test whether the effect size of single nucleotide polymorphisms (SNPs) on outcomes was mediated by the expression of immune-associated genes.

Results

The primary univariable analysis revealed a significant positive correlation between systemic lupus erythematosus (SLE), type 1 diabetes (T1D), type 2 diabetes (T2D), and rheumatoid arthritis (RA) with the risk of PE or PE with FGR. Surprisingly, a counterintuitive finding showed a significant negative association between endometriosis of pelvic peritoneum (EMoP) and the risk of PE with FGR. None of the inflammatory factors had a causal relationship with PE or PE with FGR. However, there was a significant association between lymphocyte count and the risk of PE with FGR. Within the lymphocyte subset, both the proportion of Natural Killer (NK) cells and absolute counts of naïve CD4+ T cells demonstrated significant effects on the risk of PE with FGR. Two-step MR analysis underscored the genetically predicted lymphocyte count as a significant mediator between T1D and PE with FGR. Additionally, SMR analysis indicated the potential involvement of SH2B3 in the occurrence of PE with FGR.

Conclusions

Our findings provided substantial evidence of the underlying causal relationship between immune dysregulation and PE or PE with FGR and some of these diseases proved to accelerate immune cells disorders and then contribute to the risk of incident PE or PE with FGR.

Association of Four VEGFA Gene Variants with Rheumatoid Arthritis Risk: A Meta-analysis and Trial Sequential Analysis

The association between rheumatoid arthritis (RA) risk and specific variants of the Vascular Endothelial Growth Factor A (VEGFA) gene remains contentious. This study sought to elucidate the correlations between RA risk and several VEGFA gene variants, including VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), VEGFA-2578 (rs699947), VEGFA-1154 (rs1570360), through a comprehensive meta-analysis. We systematically reviewed literature from the Cochrane Library database, Embase, PubMed, Web of Science, China National Knowledge Infrastructure, and the Wanfang Data Information Service platform to gather relevant case-control studies. Using odds ratio (OR) and 95% confidence interval (95% CI), we analyzed the data to assess potential correlations. Sensitivity analysis and the Egger's test were employed to ensure the results stability and to evaluate potential publication bias. Additionally, trial sequential analysis (TSA) was conducted to validate the findings. Our meta-analysis incorporated ten studies involving 2817 patients and 2855 controls. Results indicated that the AA genotype of VEGFA-1154 (rs1570360) is associated with a reduced risk of RA in the overall population (AG + GG vs AA: P = 0.032 OR = 1.932 95% CI 1.059-3.523). However, no significant association is found for VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), and VEGFA-2578 (rs699947) variants with RA risk. Subgroup analysis revealed a significant association between the VEGF rs3025039(C936) variant and RA risk in the PCR-RFLP group under the TC vs. CC model. TSA confirmed the sufficiency of the sample size for robust conclusions. These findings suggest that the G allele of VEGFA-1154 (rs1570360) may increase RA risk, whereas the A allele appears to confer a protective effect. This study enhances our understanding of the genetic predispositions to RA and underscores the potential role of VEGFA gene variants in its pathogenesis.

Rheumatoid arthritis increases the risk of heart failure: results from the cross-sectional study in the US population and mendelian randomization analysis in the European population

Objective

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease. Among its various complications, heart failure (HF) has been recognized as the second leading cause of cardiovascular death in RA patients. The objective of this study was to investigate the relationship between RA and HF using epidemiological and genetic approaches.

Methods

The study included 37,736 participants from the 1999-2020 National Health and Nutrition Examination Survey. Associations between RA and HF in the US population were assessed with weighted multivariate logistic regression analysis. A two-sample Mendelian randomization (MR) analysis was employed to establish the causal relationship between the two variables. The primary analysis method utilized was inverse variance weighting (IVW). Additionally, horizontal pleiotropy and heterogeneity were assessed to account for potential confounding factors. In cases where multiple independent datasets were accessible during MR analysis, we combined the findings through a meta-analytical approach.

Results

In observational studies, the prevalence of HF in combination with RA reached 7.11% (95%CI 5.83 to 8.39). RA was positively associated with an increased prevalence of HF in the US population [odds ratio (OR):1.93, 95% confidence interval (CI):1.47-2.54, P < 0.0001]. In a MR analysis utilizing a meta-analytical approach to amalgamate the results of the IVW method, we identified a significant causal link between genetically predicted RA and a heightened risk of HF (OR = 1.083, 95% CI: 1.028-1.141; P = 0.003). However, this association was not deemed significant for seronegative RA (SRA) (OR = 1.028, 95% CI: 0.992-1.065; P = 0.126). These findings were consistent across sensitivity analyses and did not indicate any horizontal pleiotropy.

Conclusion

RA correlates with an elevated prevalence of HF within the US population. Furthermore, genetic evidence derived from European populations underscores a causal link between RA and the risk of HF. However this association was not significant in SRA.

MYLK*FLNB and DOCK1*LAMA2 gene-gene interactions associated with rheumatoid arthritis in the focal adhesion pathway

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease caused by a combination of genetic and environmental factors. Rare variants with low predicted effects in genes participating in the same biological function might be involved in developing complex diseases such as RA. From whole-exome sequencing (WES) data, we identified genes containing rare non-neutral variants with complete penetrance and no phenocopy in at least one of nine French multiplex families. Further enrichment analysis highlighted focal adhesion as the most significant pathway. We then tested if interactions between the genes participating in this function would increase or decrease the risk of developing RA disease. The model-based multifactor dimensionality reduction (MB-MDR) approach was used to detect epistasis in a discovery sample (19 RA cases and 11 healthy individuals from 9 families and 98 unrelated CEU controls from the International Genome Sample Resource). We identified 9 significant interactions involving 11 genes (MYLK, FLNB, DOCK1, LAMA2, RELN, PIP5K1C, TNC, PRKCA, VEGFB, ITGB5, and FLT1). One interaction (MYLK*FLNB) increasing RA risk and one interaction decreasing RA risk (DOCK1*LAMA2) were confirmed in a replication sample (200 unrelated RA cases and 91 GBR unrelated controls). Functional and genomic data in RA samples or relevant cell types argue the key role of these genes in RA.

From genomic insights to clinical hope: Targeting NEU1 in IgA nephropathy

BACKGROUND

IgA Nephropathy (IgAN), the primary form of glomerulonephritis, presents significant clinical challenges due to its obscure pathogenesis and lack of targeted treatments. We conducted a proteome-wide Mendelian randomization (MR) study to identify therapeutic targets for IgAN.

METHODS

Utilizing a plasma proteome dataset comprising 4907 blood plasma proteins as the exposure variable, and renal biopsy-confirmed IgAN cases as the outcome, this study employed MR to pinpoint proteins potentially pathogenic to IgAN. The robustness of our findings was affirmed through external dataset validation, reverse causation testing, and Bayesian colocalization analysis. Additionally, we conducted phenotypic scanning and analyzed downstream metabolites to investigate candidate proteins's biological function.

RESULTS

In our study, a significant association was identified between an increase in neuraminidase 1 (NEU1) expression and the risk of IgAN. Specifically, a one standard deviation increase in NEU1 expression was associated with an odds ratio of 11.80 for the development of IgAN (95% confidence interval: 4.03-34.54). This association was substantiated across various statistical models and external validations. Colocalization analysis indicated a shared causal variant between NEU1 expression and IgAN. Furthermore, an increased influenza risk associated with NEU1 was observed, supporting the therapeutic potential of NEU1 inhibitors for IgAN. However, our study found no significant role for neuraminic acid-related metabolites in IgAN's development, suggesting an independent pathway for NEU1's influence.

CONCLUSION

This study identifies NEU1 as a promising therapeutic target for IgAN, backed by robust genetic evidence. Future research should explore NEU1's therapeutic potential in diverse populations and clinical scenarios, further establishing its role in IgAN.

Chronic Overlapping Pain Conditions and Nociplastic Pain

Chronic Overlapping Pain Conditions (COPCs) are a subset of chronic pain conditions commonly comorbid with one another and more prevalent in women and assigned female at birth (AFAB) individuals. Pain experience in these conditions may better fit with a new mechanistic pain descriptor, nociplastic pain, and nociplastic type pain may represent a shared underlying factor among COPCs. We applied GenomicSEM common-factor genome wide association study (GWAS) and multivariate transcriptome-wide association (TWAS) analyses to existing GWAS output for six COPCs in order to find genetic variation associated with nociplastic type pain, followed by genetic correlation (linkage-disequilibrium score regression), gene-set and tissue enrichment analyses. We found 24 independent single nucleotide polymorphisms (SNPs), and 127 unique genes significantly associated with nociplastic type pain, and showed nociplastic type pain to be a polygenic trait with significant SNP-heritability. We found significant genetic overlap between multisite chronic pain and nociplastic type pain, and to a smaller extent with rheumatoid arthritis and a neuropathic pain phenotype. Tissue enrichment analyses highlighted cardiac and thyroid tissue, and gene set enrichment analyses emphasized potential shared mechanisms in cognitive, personality, and metabolic traits and nociplastic type pain along with distinct pathology in migraine and headache. We use a well-powered network approach to investigate nociplastic type pain using existing COPC GWAS output, and show nociplastic type pain to be a complex, heritable trait, in addition to contributing to understanding of potential mechanisms in development of nociplastic pain.

Enhanced fracture risk prediction: a novel multi-trait genetic approach integrating polygenic scores of fracture-related traits

The novel metaPGS, integrating multiple fracture-related genetic traits, surpasses traditional polygenic scores in predicting fracture risk. Demonstrating a robust association with incident fractures, this metaPGS offers significant potential for enhancing clinical fracture risk assessment and tailoring prevention strategies.

INTRODUCTION

Current polygenic scores (PGS) have limited predictive power for fracture risk. To improve genetic prediction, we developed and evaluated a novel metaPGS combining genetic information from multiple fracture-related traits.

METHODS

We derived individual PGS from genome-wide association studies of 16 fracture-related traits and employed an elastic-net logistic regression model to examine the association between the 16 PGSs and fractures. An optimal metaPGS was constructed by combining 11 significant individual PGSs selected by the elastic regularized regression model. We evaluated the predictive power of the metaPGS alone and in combination with clinical risk factors recommended by guidelines. The discrimination ability of metaPGS was assessed using the concordance index. Reclassification was assessed using net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS

The metaPGS had a significant association with incident fractures (HR 1.21, 95% CI 1.18-1.25 per standard deviation of metaPGS), which was stronger than previously developed bone mineral density (BMD)-related individual PGSs. Models with PGS_FNBMD, PGS_TBBMD, and metaPGS had slightly higher but statistically non-significant c-index than the base model (0.640, 0.644, 0.644 vs. 0.638). However, the reclassification analysis showed that compared to the base model, the model with metaPGS improves the reclassification of fracture.

CONCLUSIONS

The metaPGS is a promising approach for stratifying fracture risk in the European population, improving fracture risk prediction by combining genetic information from multiple fracture-related traits.

A comprehensive review on the role of mesenchymal stromal/stem cells in the management of rheumatoid arthritis

INTRODUCTION

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease with systemic manifestations. Although the success of immune modulatory drug therapy is considerable, about 40% of patients do not respond to treatment. Mesenchymal stromal/stem cells (MSCs) have been demonstrated to have therapeutic potential for inflammatory diseases.

AREAS COVERED

This review provides an update on RA disease and on pre-clinical and clinical studies using MSCs from bone marrow, umbilical cord, adipose tissue, and dental pulp, to regulate the immune response. Moreover, the clinical use, safety, limitations, and future perspective of MSCs in RA are discussed. Using the PubMed database and ClincalTrials.gov, peer-reviewed full-text papers, abstracts and clinical trials were identified from 1985 through to April 2023.

EXPERT OPINION

MSCs demonstrated a satisfactory safety profile and potential for clinical efficacy. However, it is mandatory to deepen the investigations on how MSCs affect the proinflammatory deregulated RA patients' cells. MSCs are potentially good candidates for severe RA patients not responding to conventional therapies but a long-term follow-up after stem cells treatment and standardized protocols are needed. Future research should focus on well-designed multicenter randomized clinical trials with adequate sample sizes and properly selected patients satisfying RA criteria for a valid efficacy evaluation.

Graves' disease and the risk of five autoimmune diseases: A Mendelian randomization and colocalization study

BACKGROUND

Epidemiological studies have consistently demonstrated a high prevalence of concurrent autoimmune diseases in individuals with Graves' disease (GD).

OBJECTIVE

The objective of this study is to establish a causal association between GD and autoimmune diseases.

METHODS

We employed a two-sample Mendelian randomization (MR) to infer a causal association between GD and five autoimmune diseases, namely rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Crohn's disease (CD), ulcerative colitis (UC), and amyotrophic lateral sclerosis (ALS), in the East Asian and European population. Genetic correlations were explored through linkage disequilibrium score regression analysis (LDSC). Finally, colocalization analyses were performed to investigate possible genetic foundations.

RESULTS

Bidirectional MR analysis indicated that genetically predicted GD increased the risk of RA (Odds Ratio (OR): 1.34, 95 % Confidence Interval (CI): 1.21 to 1.47, P < 0.001) and SLE (OR: 1.21, 95%CI: 1.08 to 1.35, P < 0.001) in the East Asian population. In contrast, we found that genetically predicted RA (OR: 1.14, 95%CI: 1.05 to 1.24, P = 0.002) and SLE (OR: 1.10, 95%CI: 1.03 to 1.17, P = 0.003) were associated with a higher risk of GD. The results have been partially validated in European cohorts. Colocalization analysis suggested the potential existence of shared causal variants between GD and other autoimmune diseases. In particular, gene ARID5B may play an important role in the incidence of autoimmune diseases.

CONCLUSION

This study has confirmed that GD was associated with RA and SLE and found a possible key gene ARID5B. It may be necessary to strengthen detection to prevent the occurrence of comorbidities in clinical practice.

Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing

BACKGROUND

Chronic pain is a common, poorly understood condition. Genetic studies including genome-wide association studies have identified many relevant variants, which have yet to be translated into full understanding of chronic pain. Transcriptome-wide association studies using transcriptomic imputation methods such as S-PrediXcan can help bridge this genotype-phenotype gap.

METHODS

We carried out transcriptomic imputation using S-PrediXcan to identify genetically regulated gene expression associated with multisite chronic pain in 13 brain tissues and whole blood. Then, we imputed genetically regulated gene expression for over 31,000 Mount Sinai BioMe participants and performed a phenome-wide association study to investigate clinical relationships in chronic pain-associated gene expression changes.

RESULTS

We identified 95 experiment-wide significant gene-tissue associations (p < 7.97 × 10-7), including 36 unique genes and an additional 134 gene-tissue associations reaching within-tissue significance, including 53 additional unique genes. Of the 89 unique genes in total, 59 were novel for multisite chronic pain and 18 are established drug targets. Chronic pain genetically regulated gene expression for 10 unique genes was significantly associated with cardiac dysrhythmia, metabolic syndrome, disc disorders/dorsopathies, joint/ligament sprain, anemias, and neurologic disorder phecodes. Phenome-wide association study analyses adjusting for mean pain score showed that associations were not driven by mean pain score.

CONCLUSIONS

We carried out the largest transcriptomic imputation study of any chronic pain trait to date. Results highlight potential causal genes in chronic pain development and tissue and direction of effect. Several gene results were also drug targets. Phenome-wide association study results showed significant associations for phecodes including cardiac dysrhythmia and metabolic syndrome, thereby indicating potential shared mechanisms.

Autoimmune diseases and their genetic link to bronchiectasis: insights from a genetic correlation and Mendelian randomization study

Background

Previous studies have demonstrated that autoimmune diseases are closely associated with bronchiectasis (BE). However, the causal effects between autoimmune diseases and BE remain elusive.

Methods

All summary-level data were obtained from large-scale Genome-Wide Association Studies (GWAS). The univariate Mendelian randomization (UVMR) was utilized to investigate the genetic causal correlation (rg) of 12 autoimmune diseases and bronchiectasis, The Multivariable Mendelian Randomization (MVMR) method was used to explore the effects of the confounding factors. Further investigation was conducted to identify potential intermediate factors using mediation analysis. Finally, the linkage disequilibrium score regression (LDSC) method was used to identify genetic correlations among complex traits. A series of sensitivity analyses was performed to validate the robustness of the results.

Results

The LDSC analysis revealed significant genetic correlations between BE and Crohn's disease (CD) (rg = 0.220, P = 0.037), rheumatoid arthritis (RA) (rg = 0.210, P = 0.021), and ulcerative colitis (UC) (rg = 0.247, P = 0.023). However, no genetic correlation was found with other autoimmune diseases (P > 0.05). The results of the primary IVW analysis suggested that for every SD increase in RA, there was a 10.3% increase in the incidence of BE (odds ratio [OR] = 1.103, 95% confidence interval [CI] 1.055-1.154, P = 1.75×10-5, FDR = 5.25×10-5). Furthermore, for every standard deviation (SD) increase in celiac disease (CeD), the incidence of BE reduced by 5.1% (OR = 0.949, 95% CI 0.902-0.999, P = 0.044, FDR = 0.044). We also observed suggestive evidence corresponding to a 3% increase in BE incidence with T1DM (OR = 1.033, 95% CI 1.001-1.066, P = 0.042, FDR = 0.063). Furthermore, MVMR analysis showed that RA was an independent risk factor for BE, whereas mediator MR analysis did not identify any mediating factors. The sensitivity analyses corroborated the robustness of these findings.

Conclusion

LDSC analysis revealed significant genetic correlations between several autoimmune diseases and BE, and further MVMR analysis showed that RA is an independent risk factor for BE.

Systemic proteome adaptions to 7-day complete caloric restriction in humans

Surviving long periods without food has shaped human evolution. In ancient and modern societies, prolonged fasting was/is practiced by billions of people globally for religious purposes, used to treat diseases such as epilepsy, and recently gained popularity as weight loss intervention, but we still have a very limited understanding of the systemic adaptions in humans to extreme caloric restriction of different durations. Here we show that a 7-day water-only fast leads to an average weight loss of 5.7 kg (±0.8 kg) among 12 volunteers (5 women, 7 men). We demonstrate nine distinct proteomic response profiles, with systemic changes evident only after 3 days of complete calorie restriction based on in-depth characterization of the temporal trajectories of ~3,000 plasma proteins measured before, daily during, and after fasting. The multi-organ response to complete caloric restriction shows distinct effects of fasting duration and weight loss and is remarkably conserved across volunteers with >1,000 significantly responding proteins. The fasting signature is strongly enriched for extracellular matrix proteins from various body sites, demonstrating profound non-metabolic adaptions, including extreme changes in the brain-specific extracellular matrix protein tenascin-R. Using proteogenomic approaches, we estimate the health consequences for 212 proteins that change during fasting across ~500 outcomes and identified putative beneficial (SWAP70 and rheumatoid arthritis or HYOU1 and heart disease), as well as adverse effects. Our results advance our understanding of prolonged fasting in humans beyond a merely energy-centric adaptions towards a systemic response that can inform targeted therapeutic modulation.

Evidence for Genetic Causal Relationships Between Multiple Immune-Mediated Inflammatory Diseases and Age-Related Macular Degeneration: A Univariable and Multivariable Mendelian Randomization Study

INTRODUCTION

With the global aging population on the rise, age-related macular degeneration (AMD) poses a growing healthcare burden. Prior research hints at immune-mediated inflammatory diseases (IMIDs) potentially elevating AMD risk via diverse mechanisms. However, causality remains disputed as a result of confounding factors. Hence, our Mendelian randomization (MR) study aims to untangle this link, mitigating confounding effects to explore the IMID-AMD causal relationship. This study aims to investigate the causal relationship between IMIDs and AMD, providing new strategies for the prevention and treatment of AMD in clinical practice.

METHODS

This study was registered with PROSPERO, CRD42023469815. We obtained data on IMIDs and AMD from Genome-Wide Association Studies (GWAS) summary statistics and the FinnGen consortium. Rigorous selection steps were applied to screen for eligible instrumental single nucleotide polymorphisms (SNPs). We conducted univariate Mendelian randomization, inverse variance-weighted (IVW), weighted median, Mendelian randomization-Egger (MR-Egger), and multivariate Mendelian randomization (MVMR) analyses. Various sensitivity analysis methods were employed to assess pleiotropy and heterogeneity. The aim was to explore the causal relationships between IMIDs and AMD.

RESULTS

The MR analysis revealed that Crohn's disease (CD) (IVW: odd ratios (OR) 1.05, 95% CI (confidence interval) 1.01-1.10, p = 0.007), rheumatoid arthritis (RA) (IVW: OR 1.09, 95% CI 1.04-1.15, p = 0.0001), and type 1 diabetes (T1D) (IVW: OR 1.05, 95% CI 1.02-1.09, p = 0.001) were correlated with an elevated risk of AMD, while multiple sclerosis (MS) (IVW: OR 2.78E-18, 95% CI 2.23E-31 to 3.48E-05, p = 0.008) appeared to be protective against AMD. These findings were supported by an array of MR analysis methodologies and the MVMR approach.

CONCLUSION

Our study results, based on MR, provide genetic evidence indicating a causal relationship between specific IMIDs and AMD. CD, RA, and T1D are factors increasing the risk of AMD, while MS may have a protective effect.

Association of HLA-DRB1 locus with treatment response to abatacept or TNF inhibitors in patients with seropositive rheumatoid arthritis

The strongest genetic risk factor for rheumatoid arthritis (RA) has been known as HLA-DRB1 based on amino acid positions 11, 71, and 74. This study analyzed the association between specific HLA-DRB1 locus and treatment response to abatacept or TNF inhibitors (TNFi) in patients with seropositive RA. A total of 374 Korean RA patients were treated with abatacept (n = 110) or TNFi (n = 264). Associations between HLA-DRB1 and treatment response after 6 months were analyzed using multivariable logistic regression. Seropositive RA patients with HLA-DRB1 shared epitope (SE) had a favorable response to abatacept (OR = 3.67, P = 0.067) and an inversely associated response to TNFi (OR 0.57, P = 0.058) based on EULAR response criteria, but the difference was not statistically significant in comparison to those without SE. In analyses using amino acid positions of HLA-DRB1, a significant association was found between valine at amino acid position 11 of SE and good response to abatacept (OR = 6.46, P = 5.4 × 10-3). The VRA haplotype also showed a good response to abatacept (OR = 4.56, P = 0.013), but not to TNFi. Our results suggest that treatment response to abatacept or TNFi may differ depending on HLA-DRB1 locus in seropositive RA, providing valuable insights for selecting optimal therapy.

Genetically proxied therapeutic inhibition of lipid-lowering drug targets and risk of rheumatoid arthritis disease: a Mendelian randomization study

OBJECTIVE

To evaluate the potential impact of consistent use of similar treatments over a long period; it is essential to investigate the potential correlation between genetic variations that influence the expression or function of pharmacological targets for reducing lipid levels and the risk of developing rheumatoid arthritis.

METHODS

We used variants in the following genes to conduct Mendelian randomization analyses: HMGCR (encoding the target for statins), PCSK9 (encoding the target for PCSK9 inhibitors, such as evolocumab and alirocumab), and NPC1L1 (encoding the target for ezetimibe). Data from lipid genetics consortia (173,082 sample size) were used to weight variations according to their correlations with low-density lipoprotein cholesterol (LDL-C). In two large datasets (total n = 19,562 cases, 501,655 controls). We conducted a meta-analysis of Mendelian randomization estimates, weighted by LDL-C levels, on the regional differences in the risk of rheumatoid arthritis using data from two large databases.

RESULTS

We approached SMR and IVW-MR analyses to examine the relationship between target gene expression (including HMGCR, PCSK9, and NPC1L1) and LDL-C levels mediated by these genes with RA. The IVW-MR analysis revealed no significant association between genetically predicted LDL-C concentration and the risk of RA (OR = 0.88, 95% CI = 0.59-1.29; OR = 0.91, 95% CI = 0.67-1.23; OR = 0.81, 95% CI = 0.49-1.36; all p > 0.05). Similarly, our findings from the SMR approach provided no evidence to suggest that gene expression of HMGCR, PCSK9, and NPC1L1 was associated with the risk of RA (OR = 0.91, 95% CI = 0.79-1.05, p = 0.207; OR = 0.96, 95% CI = 0.85-1.09, p = 0.493).

CONCLUSIONS

Our results do not provide evidence to support the hypothesis that reducing LDL-C levels with statins, alirocumab, or ezetimibe effectively prevents the risk of developing RA. However, our study provides valuable insights into the assessment of lipid-lowering agents in RA, which can enhance our understanding of the condition and assist in clinical practice by aiding in the determination and monitoring of RA status to clinical response.

Potential association of genetically predicted lipid and lipid-modifying drugs with rheumatoid arthritis: A Mendelian randomization study

BACKGROUND

Past studies have demonstrated that patients diagnosed with rheumatoid arthritis (RA) often exhibit abnormal levels of lipids. Furthermore, certain lipid-modifying medications have shown effectiveness in alleviating clinical symptoms associated with RA. However, the current understanding of the causal relationship between lipids, lipid-modifying medications, and the risk of developing RA remains inconclusive. This study employed Mendelian randomization (MR) to investigate the causal connection between lipids, lipid-modifying drugs, and the occurrence of RA.

METHODS

We obtained genetic variation for lipid traits and drug targets related to lipid modification from three sources: the Global Lipids Genetics Consortium (GLGC), UK Biobank, and Nightingale Health 2020. The genetic data for RA were acquired from two comprehensive meta-analyses and the R8 of FINNGEN, respectively. These variants were employed in drug-target MR analyses to establish a causal relationship between genetically predicted lipid-modifying drug targets and the risk of RA. For suggestive lipid-modified drug targets, we conducted Summary-data-based Mendelian Randomization (SMR) analyses and using expression quantitative trait loci (eQTL) data in relevant tissues. In addition, we performed co-localization analyses to assess genetic confounders.

RESULTS

Our analysis revealed no significant causal relationship between lipid and RA. We observed that the genetically predicted 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) -mediated low density lipoprotein cholesterol (LDL-C) (OR 0.704; 95% CI 0.56, 0.89; P = 3.43×10-3), Apolipoprotein C-III (APOC3) -mediated triglyceride (TG) (OR 0.844; 95% CI 0.77, 0.92; P = 1.50×10-4) and low density lipoprotein receptor (LDLR) -mediated LDL-C (OR 0.835; 95% CI 0.73, 0.95; P = 8.81×10-3) were significantly associated with a lowered risk of RA. while Apolipoprotein B-100 (APOB) -mediated LDL-C (OR 1.212; 95%CI 1.05,1.40; P = 9.66×10-3) was significantly associated with an increased risk of RA.

CONCLUSIONS

Our study did not find any supporting evidence to suggest that lipids are a risk factor for RA. However, we observed significant associations between HMGCR, APOC3, LDLR, and APOB with the risk of RA.

A landscape of gene expression regulation for synovium in arthritis

The synovium is an important component of any synovial joint and is the major target tissue of inflammatory arthritis. However, the multi-omics landscape of synovium required for functional inference is absent from large-scale resources. Here we integrate genomics with transcriptomics and chromatin accessibility features of human synovium in up to 245 arthritic patients, to characterize the landscape of genetic regulation on gene expression and the regulatory mechanisms mediating arthritic diseases predisposition. We identify 4765 independent primary and 616 secondary cis-expression quantitative trait loci (cis-eQTLs) in the synovium and find that the eQTLs with multiple independent signals have stronger effects and heritability than single independent eQTLs. Integration of genome-wide association studies (GWASs) and eQTLs identifies 84 arthritis related genes, revealing 38 novel genes which have not been reported by previous studies using eQTL data from the GTEx project or immune cells. We further develop a method called eQTac to identify variants that could affect gene expression by affecting chromatin accessibility and identify 1517 regions with potential regulatory function of chromatin accessibility. Altogether, our study provides a comprehensive synovium multi-omics resource for arthritic diseases and gains new insights into the regulation of gene expression.

The causal effect of two occupational factors on osteoarthritis and rheumatoid arthritis: a Mendelian randomization study

Background

Osteoarthritis (OA) and rheumatoid arthritis (RA) are two common types of arthritis. We conducted a two-sample Mendelian randomization (MR) study to estimate the causal effects of two common occupational factors-job involves heavy manual or physical work and job involves mainly walking or standing-on OA and RA in individuals of European ancestry.

Methods

Instruments were chosen from genome-wide association studies (GWASs) that identified independent single nucleotide polymorphisms (SNPs) robustly linked to job involves heavy manual or physical work (N = 263,615) as well as job involves mainly walking or standing (N = 263,556). Summary statistics for OA and RA were taken from the Integrative Epidemiology Unit (IEU) GWAS database; both discovery and replication GWAS datasets were considered. The primary analysis utilized the inverse variance weighted (IVW) MR method supplemented by various sensitivity MR analyses.

Results

In the IVW model, we found that genetically predicted job involves heavy manual or physical work was significantly associated with OA in both the discovery [odds ratio (OR) = 1.034, 95% confidence interval (CI): 1.016-1.053, P = 2.257 × 10-4] and replication (OR = 1.857, 95% CI: 1.223-2.822, P = 0.004) analyses. The causal associations were supported in diverse sensitivity analyses. MR analyses suggested no causal effect of genetically predicted job involves heavy manual or physical work on RA. Similarly, our data provided no evidence that genetically predicted job involves mainly walking or standing was related to OA and RA.

Conclusions

Our MR study suggests that job involves heavy manual or physical work is a risk factor for OA. It is of utmost importance to create preventive strategies aimed at reducing its impact on OA at such work sites.

Single-cell insights into immune dysregulation in rheumatoid arthritis flare versus drug-free remission

Immune-mediated inflammatory diseases (IMIDs) are typically characterised by relapsing and remitting flares of inflammation. However, the unpredictability of disease flares impedes their study. Addressing this critical knowledge gap, we use the experimental medicine approach of immunomodulatory drug withdrawal in rheumatoid arthritis (RA) remission to synchronise flare processes allowing detailed characterisation. Exploratory mass cytometry analyses reveal three circulating cellular subsets heralding the onset of arthritis flare - CD45RO+PD1hi CD4+ and CD8+ T cells, and CD27+CD86+CD21- B cells - further characterised by single-cell sequencing. Distinct lymphocyte subsets including cytotoxic and exhausted CD4+ memory T cells, memory CD8+CXCR5+ T cells, and IGHA1+ plasma cells are primed for activation in flare patients. Regulatory memory CD4+ T cells (Treg cells) increase at flare onset, but with dysfunctional regulatory marker expression compared to drug-free remission. Significant clonal expansion is observed in T cells, but not B cells, after drug cessation; this is widespread throughout memory CD8+ T cell subsets but limited to the granzyme-expressing cytotoxic subset within CD4+ memory T cells. Based on our observations, we suggest a model of immune dysregulation for understanding RA flare, with potential for further translational research towards novel avenues for its treatment and prevention.

Mendelian randomization reveals systemic lupus erythematosus and rheumatoid arthritis and risk of adverse pregnancy outcomes

BACKGROUND

The effect of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) on adverse pregnancy outcomes is a controversial topic. This study aimed to use Mendelian randomization (MR) analysis to assess the causal relationship between SLE, RA and adverse pregnancy outcomes.

METHODS

Genetic variants for SLE and RA, as well as adverse pregnancy outcomes, were derived from pooled statistics from large public genome-wide association studies. Several methods, such as inverse variance weighting (IVW), MR-Egger, weighted median and MR-Pleiotropic Residuals Sum and Outliers, were employed to estimate two-sample causality.

RESULTS

Genetic prediction of SLE was associated with higher odds of preterm labour [odds ratio (OR) 1.03, 95 % confidence interval (CI) 1.01-1.05; p = 0.008]. RA was associated with higher odds of preterm labour (OR 1.03, 95 % CI 1.01-1.06; p = 0.009), pre-eclampsia or eclampsia (OR 1.04, 95 % CI 1.01-1.07; p = 0.005), and poor fetal growth (OR 1.08, 95 % CI 1.04-1.12; p = 2.91 × 10-5). The results of bidirectional MR analysis did not indicate that SLE was associated with spontaneous abortion, pre-eclampsia or eclampsia, preterm rupture of membranes, or poor fetal growth (p-value for IVW 0.13-0.97).

CONCLUSIONS

This study found a genetic association between SLE and the risk of preterm labour, and highlights the importance of perinatal care and monitoring for patients with SLE. Furthermore, RA was found to be associated with a wide range of adverse outcomes, including preterm labour, pre-eclampsia or eclampsia, and poor fetal growth; as such, there is a need for more intensive therapeutic interventions and prenatal monitoring.

GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region

Here we report the largest Asian genome-wide association study (GWAS) for systemic sclerosis performed to date, based on data from Japanese subjects and comprising of 1428 cases and 112,599 controls. The lead SNP is in the FCGR/FCRL region, which shows a penetrating association in the Asian population, while a complete linkage disequilibrium SNP, rs10917688, is found in a cis-regulatory element for IRF8. IRF8 is also a significant locus in European GWAS for systemic sclerosis, but rs10917688 only shows an association in the presence of the risk allele of IRF8 in the Japanese population. Further analysis shows that rs10917688 is marked with H3K4me1 in primary B cells. A meta-analysis with a European GWAS detects 30 additional significant loci. Polygenic risk scores constructed with the effect sizes of the meta-analysis suggest the potential portability of genetic associations beyond populations. Prioritizing the top 5% of SNPs of IRF8 binding sites in B cells improves the fitting of the polygenic risk scores, underscoring the roles of B cells and IRF8 in the development of systemic sclerosis. The results also suggest that systemic sclerosis shares a common genetic architecture across populations.

Interleukin-18 Gene Polymorphisms and Rheumatoid Arthritis Susceptibility: An Umbrella Review of Meta-Analyses

This study systematically analyzes the association between interleukin-18 (IL-18) gene polymorphisms and rheumatoid arthritis (RA) susceptibility. The electronic databases Ovid MEDLINE, Ovid Excerpta Medica Database, and Cochrane Library were searched to identify meta-analyses that included case-control studies reporting IL-18 gene polymorphisms and RA susceptibility. Data were reanalyzed using Review Manager Software 5.1, and Mantel-Haenszel random effects were applied for the five genetic models: allelic, recessive, dominant, homozygote, and heterozygote. The effect size of odds ratios (ORs) and their corresponding 95% confidence interval (CI) were calculated. A total of seven meta-analyses with poor quality were included. The IL-18 polymorphisms -607 A/C, -137 C/G, -920 T/C, and -105 C/A have been reported. With weak evidence, IL-18 -607 A/C polymorphisms were associated with a reduced risk of RA susceptibility using the allele model (OR = 0.76, 95% CI: 0.61 - 0.93, p=0.01), dominant model (OR = 0.67, 95% CI: 0.50 - 0.90, p=0.008), homozygote model (OR = 0.57, 95% CI: 0.35 - 0.91, p=0.02), and heterozygote model (OR = 0.71, 95% CI: 0.54 - 0.93, p=0.01) in the overall population. IL-18 gene polymorphisms and RA susceptibility are affected by ethnicity: With weak evidence, IL-18 -137 C/G polymorphisms were related to reduce RA susceptibility in the Asian population (allele model: OR = 0.59, 95% CI: 0.40 - 0.88, p=0.01; dominant model: OR = 0.57, 95% CI: 0.37 - 0.89, p=0.01; heterozygote model: OR = 0.60, 95% CI: 0.38 - 0.94, p=0.03). IL-18 -607 A/C gene polymorphisms are a protective factor for RA susceptibility in the overall population, and IL-18 -137 C/G gene polymorphisms are a protective factor for RA susceptibility in the Asian population. Further studies are needed to confirm these results owing to the limitations of the included studies.

Ameliorative effect of Alangium chinense (Lour.) Harms on rheumatoid arthritis by reducing autophagy with targeting regulate JAK3-STAT3 and COX-2 pathways

ETHNOPHARMACOLOGICAL RELEVANCE

Alangium chinense has been used as traditional folk medicine for centuries to treat rheumatoid arthritis (RA) by Guizhou Miao nationality with remarkable clinical effect. But the mechanism of its anti-RA is not fully clarified.

AIM OF THE STUDY

To explore the effect and underlying mechanism of A. chinense against RA.

MATERIAL AND METHODS

RA rats were induced by CII/IFA, and oral administrated with or without ethyl acetate extracts of Alangium chinense (ACEE) and tripterygium glycosides (GTW). Then arthritis scores, inflammatory factors in serum and histological evaluation were evaluated to assess the degree of joints disease. Proteomics were conducted via LC-MS/MS to clarify the mechanism of ACEE preliminarily, and further examined by immunohistochemistry, immunofluorescence, western botting, and molecular docking.

RESULTS

ACEE decreased joints swelling, cell abscission and necrosis of joint tissues arthropathy of RA rats, and attenuated expression of TNF-α, IL-1β, IL-6, PGE2, TGF-β. Meanwhile, differentially expressed proteins in the ACEE treated groups were observed, which were involved in RA, spliceosome, cell adhesion molecules, phagosome and lysosome signaling pathways. Moreover, ACEE significantly ameliorated arthropathy, suppressed JAK-STAT pathway (JAK3, p-JAK3, STAT3, iNOS, RANKL), COX-2 pathway (COX-2, TNF-α, IL-6I, L-1β, 5-LOX), and autophagic signaling pathway (LC3-Ⅰ, LC3-Ⅱ, p62, mTOR). But it showed little effect on the expression of COX-1, JAK1, JAK2, TyK2.

CONCLUSION

It is the first evidence that A. chinense significantly ameliorates RA, and the underlying immune mechanism involves reducing autophagy with targeting regulate JAK3-STAT3 and COX-2 pathways.

Association of Interleukin 23 Receptor Polymorphisms with Predisposition to Rheumatoid Arthritis: An Updated Meta and Trial Sequential Analysis

The etiology of Rheumatoid Arthritis (RA) development remained unclear, and several factors, such as environmental, genetic, and immune system dysfunction, have been attributed to the susceptibility. Interleukin 23 (IL23) induces expansion of the Th17 cells through the IL-23 receptor (IL-23R) and believes in playing a major role in RA pathogenesis. Various genetic mutants in the IL23R gene (rs10489629, rs1343151, rs2201841, rs7517847, rs1004819, rs10889677, rs11209026, rs7530511) have been associated with the susceptibility RA, but results are contradictories. We performed a meta-analysis to establish the association of IL23R polymorphisms with susceptibility RA. For the meta-analysis, a detailed search of databases like Google Scholar, PubMed, Scopus, Web of Science, and Science Direct was conducted, and data were extracted from the included reports. The meta-analysis was performed by the Comprehensive Meta-Analysis v3 software. A significant association of IL-23R rs11209026 (AA vs. GG: Odds ratio = 2.250, p-value = 0.01; AA vs. GG+GA: Odds ratio = 2.271, p-value = 0.01), rs1343151 (A vs. G: Odds ratio = 1.091, p-value = 0.001; AA vs. GG: Odds ratio = 1.209, p-value = 0.001; GA vs. GG: Odds ratio = 1.116, p-value = 0.004; AA+GA vs. GG: Odds ratio = 1.135, p-value = 0.000; AA vs. GG+GA: Odds ratio = 1.144, p-value = 0.012) and rs10889677 (CA vs. CC: Odds ratio = 1.375, p-value = 0.041) polymorphisms were observed with increased susceptibility for the development of RA. In contrast, IL-23R rs10489629 (G vs. A: odds ratio = 0.901, p-value = 0.047, GG vs. AA: Odds ratio = 0.763, p-value = 0.022, GG vs. AA+AG: Odds ratio = 0.852, p-value = 0.00) and IL23R rs2201841 (CC vs. TT+TC: Odds ratio = 0.826, p-value = 0.026) variants were linked with protection against the development of RA. In addition, the trial sequential analysis revealed the inclusion of a sufficient number of studies in the present meta-analysis, and no further additional studies are required. IL-23R variants are associated with genetic susceptibility or resistance against the development of RA.

Cell-Specific Gene Networks and Drivers in Rheumatoid Arthritis Synovial Tissues

Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease characterized by inflammation and hyperplasia of the synovial tissues. RA pathogenesis involves multiple cell types, genes, transcription factors (TFs) and networks. Yet, little is known about the TFs, and key drivers and networks regulating cell function and disease at the synovial tissue level, which is the site of disease. In the present study, we used available RNA-seq databases generated from synovial tissues and developed a novel approach to elucidate cell type-specific regulatory networks on synovial tissue genes in RA. We leverage established computational methodologies to infer sample-specific gene regulatory networks and applied statistical methods to compare network properties across phenotypic groups (RA versus osteoarthritis). We developed computational approaches to rank TFs based on their contribution to the observed phenotypic differences between RA and controls across different cell types. We identified 18,16,19,11 key regulators of fibroblast-like synoviocyte (FLS), T cells, B cells, and monocyte signatures and networks, respectively, in RA synovial tissues. Interestingly, FLS and B cells were driven by multiple independent co-regulatory TF clusters that included MITF, HLX, BACH1 (FLS) and KLF13, FOSB, FOSL1 (synovial B cells). However, monocytes were collectively governed by a single cluster of TF drivers, responsible for the main phenotypic differences between RA and controls, which included RFX5, IRF9, CREB5. Among several cell subset and pathway changes, we also detected reduced presence of NKT cell and eosinophils in RA synovial tissues. Overall, our novel approach identified new and previously unsuspected KDG, TF and networks and should help better understanding individual cell regulation and co-regulatory networks in RA pathogenesis, as well as potentially generate new targets for treatment.

Gene Network Analyses Identify Co-regulated Transcription Factors and BACH1 as a Key Driver in Rheumatoid Arthritis Fibroblast-like Synoviocytes

RNA-sequencing and differential gene expression studies have significantly advanced our understanding of pathogenic pathways underlying Rheumatoid Arthritis (RA). Yet, little is known about cell-specific regulatory networks and their contributions to disease. In this study, we focused on fibroblast-like synoviocytes (FLS), a cell type central to disease pathogenesis and joint damage in RA. We used a strategy that computed sample-specific gene regulatory networks (GRNs) to compare network properties between RA and osteoarthritis FLS. We identified 28 transcription factors (TFs) as key regulators central to the signatures of RA FLS. Six of these TFs are new and have not been previously implicated in RA, and included BACH1, HLX, and TGIF1. Several of these TFs were found to be co-regulated, and BACH1 emerged as the most significant TF and regulator. The main BACH1 targets included those implicated in fatty acid metabolism and ferroptosis. The discovery of BACH1 was validated in experiments with RA FLS. Knockdown of BACH1 in RA FLS significantly affected the gene expression signatures, reduced cell adhesion and mobility, interfered with the formation of thick actin fibers, and prevented the polarized formation of lamellipodia, all required for the RA destructive behavior of FLS. This is the first time that BACH1 is shown to have a central role in the regulation of FLS phenotypes, and gene expression signatures, as well as in ferroptosis and fatty acid metabolism. These new discoveries have the potential to become new targets for treatments aimed at selectively targeting the RA FLS.

Causality between rheumatoid arthritis and the risk of cognitive impairment: a Mendelian randomization study

BACKGROUND

There is mounting proof that rheumatoid arthritis (RA) and cognitive decline are related. These studies, however, have not all been uniform, and others have not discovered such a correlation. It is essential to investigate the link between RA and cognitive decline.

METHOD

We conducted a Mendelian randomization analysis utilizing three different publicly accessible RA GWAS summary datasets and a variety of meticulously verified instrumental variables. We mostly used inverse variance weighting (IVW), as well as MR-Egger, weighted median, MR-PRESSO, and several sensitivity analyses, to figure out the link between RA and cognitive impairment (CI).

RESULTS

Our MR study identified the causality between RA and declining cognitive performance (β = - 0.010, 95% CI of - 0.017 to - 0.003, P = 4.33E-03) and cognitive function (β = - 0.029, 95% CI of - 0.053 to - 0.005, P = 1.93E-02). The consistent direction of the connection is revealed by sensitivity analysis utilizing the weighted median and the MR-Egger method. Furthermore, we reproduced our findings across two additional RA datasets and found identical outcomes, strengthening the validity of our findings.

CONCLUSION

This study offers proof of causality between RA and an increased risk of CI. Our findings highlight the importance of examining RA patients for cognitive ability, which may open up fresh ideas for the prevention of CI.

Immune-mediated inflammatory diseases and the risk of valvular heart disease: a Mendelian randomization study

BACKGROUND

Observational studies have suggested that immune-mediated inflammatory diseases (IMIDs) are associated with a higher risk of valvular heart disease (VHD). But the potential causal association is not clear. Therefore, we used Mendelian randomization (MR) analysis to assess the causal association of IMIDs with VHD risk.

METHODS

A two-sample MR analysis was performed to confirm the causal association of several common IMIDs (systemic lupus erythematosus, SLE; rheumatoid arthritis, RA; multiple sclerosis, MS; ankylosing spondylitis, AS; psoriasis, PSO; inflammatory bowel disease, IBD) with the risk of VHD. The exposure data is derived from published genome-wide association studies (GWASs) and outcome data come from the FinnGen database (47,003 cases and 182,971 controls). Inverse-variance weighted (IVW), MR-Egger, and weighted median methods were performed to assess the causal association. The study design applied univariable MR and multivariable MR.

RESULTS

The MR analysis indicated that several genetically predicted IMIDs increased the risk of VHD, including SLE (odds ratio (OR) = 1.014; 95% confidence interval (CI) =  < 1.001,1.028 > ; p = 0.036), RA (OR = 1.017; 95% CI =  < 1.002,1.031 > ; p = 0.025), and IBD (OR = 1.018; 95% CI =  < 1.002,1.033 > ; p = 0.023). Multivariable MR indicated that the adverse effect of these IMIDs on VHD was dampened to varying degrees after adjusting for smoking, obesity, coronary artery disease, and hypertension.

CONCLUSION

Our findings support the first genetic evidence of the causality of genetically predicted IMIDs with the risk of developing into VHD. Our results deliver a viewpoint that further active intervention needs to be explored to mitigate VHD risk in patients with SLE, RA, and IBD. Key Points • Genetically predicted systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and inflammatory bowel disease (IBD) are causally associated with valvular heart disease (VHD). • To reduce the risk of VHD in patients with SLE, RA, and IBD, active interventions should be further explored.

Mendelian randomization study supports the causal effects of air pollution on longevity via multiple age-related diseases

Growing evidence suggests that exposure to fine particulate matter (PM2.5) may reduce life expectancy; however, the causal pathways of PM2.5 exposure affecting life expectancy remain unknown. Here, we assess the causal effects of genetically predicted PM2.5 concentration on common chronic diseases and longevity using a Mendelian randomization (MR) statistical framework based on large-scale genome-wide association studies (GWAS) (>400,000 participants). After adjusting for other types of air pollution and smoking, we find significant causal relationships between PM2.5 concentration and angina pectoris, hypercholesterolaemia and hypothyroidism, but no causal relationship with longevity. Mediation analysis shows that although the association between PM2.5 concentration and longevity is not significant, PM2.5 exposure indirectly affects longevity via diastolic blood pressure (DBP), hypertension, angina pectoris, hypercholesterolaemia and Alzheimer's disease, with a mediated proportion of 31.5, 70.9, 2.5, 100, and 24.7%, respectively. Our findings indicate that public health policies to control air pollution may help improve life expectancy.

Understanding interleukin 11 as a disease gene and therapeutic target

Interleukin 11 (IL11) is an elusive member of the IL6 family of cytokines. While initially thought to be a haematopoietic and cytoprotective factor, more recent data show instead that IL11 is redundant for haematopoiesis and toxic. In this review, the reasons that led to the original misunderstandings of IL11 biology, which are now understandable, are explained with particular attention on the use of recombinant human IL11 in mice and humans. Following tissue injury, as part of an evolutionary ancient homeostatic response, IL11 is secreted from damaged mammalian cells to signal via JAK/STAT3, ERK/P90RSK, LKB1/mTOR and GSK3β/SNAI1 in autocrine and paracrine. This activates a program of mesenchymal transition of epithelial, stromal, and endothelial cells to cause inflammation, fibrosis, and stalled endogenous tissue repair, leading to organ failure. The role of IL11 signalling in cell- and organ-specific pathobiology is described, the large unknowns about IL11 biology are discussed and the promise of targeting IL11 signalling as a therapeutic approach is reviewed.

Association of autoimmune diseases with the occurrence and 28-day mortality of sepsis: an observational and Mendelian randomization study

BACKGROUND

Observational studies have indicated a potential association between autoimmune diseases and the occurrence of sepsis, with an increased risk of mortality among affected patients. However, whether a causal relationship exists between the two remains unknown.

METHODS

In the Mendelian randomization (MR) study, we accessed exposure Genome-wide association study (GWAS) data from both the MRC Integrative Epidemiology Unit (MRC-IEU) and the FinnGen consortium. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. We employed univariable, multivariable, and reverse MR analyses to explore potential associations between autoimmune disorders and sepsis and its 28-day mortality. Additionally, a two-step mediation MR analysis was performed to investigate indirect factors possibly influencing the relationship between autoimmune disorders and sepsis. Afterward, we conducted an observational analysis to further explore the relationship between autoimmune disease and occurrence as well as 28-day mortality of sepsis using a real-world database (the MIMIC-IV database). A cohort of 2537 patients diagnosed with autoimmune disease were extracted from the database for analysis. Multivariable logistic regression models were used to confirm the association between autoimmune diseases and the occurrence of sepsis, as well as the 28-day mortality associated with sepsis.

RESULTS

In univariable MR analysis, there appeared to be causal relationships between genetically predicted type 1 diabetes (OR = 1.036, 95% CI = 1.023-1.048, p = 9.130E-09), rheumatoid arthritis (OR = 1.077, 95% CI = 1.058-1.097, p = 1.00E-15) and sepsis, while a potential causal link was observed between celiac disease and sepsis (OR = 1.013, 95% CI = 1.002-1.024, p = 0.026). In a subsequent multivariable MR analysis, only rheumatoid arthritis was found to be independently associated with the risk of sepsis (OR = 1.138, 95% CI = 1.044-1.240, p = 3.36E-03). Furthermore, there was no causal link between autoimmune disorders and 28-day mortality from sepsis. In reverse MR analysis, sepsis was suggested to potentially trigger the onset of psoriasis (OR = 1.084, 95% CI = 1.040-1.131, p = 1.488E-04). In the real-world observational study, adjusting for multiple confounders, rheumatoid arthritis (OR = 1.34, 95% CI = 1.11-1.64, p = 0.003) and multiple sclerosis (OR = 1.31, 95% CI = 1.03-1.68, p = 0.02) were associated with a higher risk of sepsis. In addition, we did not find that autoimmune diseases were associated with 28-day mortality from sepsis.

CONCLUSION

Both in observational and MR analysis, only rheumatoid arthritis is highly correlated with occurrence of sepsis. However, autoimmune disease was not associated with an increased 28-day mortality in patient with sepsis. Sepsis may increase the risk of developing psoriasis.

Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability

In autoimmune diseases such as rheumatoid arthritis, the immune system attacks the body's own cells. Developing a precise understanding of the cell states where noncoding autoimmune risk variants impart causal mechanisms is critical to developing curative therapies. Here, to identify noncoding regions with accessible chromatin that associate with cell-state-defining gene expression patterns, we leveraged multimodal single-nucleus RNA and assay for transposase-accessible chromatin (ATAC) sequencing data across 28,674 cells from the inflamed synovial tissue of 12 donors. Specifically, we used a multivariate Poisson model to predict peak accessibility from single-nucleus RNA sequencing principal components. For 14 autoimmune diseases, we discovered that cell-state-dependent ('dynamic') chromatin accessibility peaks in immune cell types were enriched for heritability, compared with cell-state-invariant ('cs-invariant') peaks. These dynamic peaks marked regulatory elements associated with T peripheral helper, regulatory T, dendritic and STAT1+CXCL10+ myeloid cell states. We argue that dynamic regulatory elements can help identify precise cell states enriched for disease-critical genetic variation.

Synovial Tissue Heterogeneity in Japanese Patients With Rheumatoid Arthritis Elucidated Using a Cell-Type Deconvolution Approach

OBJECTIVE

Recent advances in single-cell RNA sequencing technology have improved our understanding of the immunological landscape of rheumatoid arthritis (RA). We aimed to stratify the synovium from East Asian patients with RA by immune cell compositions and gain insight into the inflammatory drivers of each synovial phenotype.

METHODS

Synovial tissues were obtained from East Asian patients in Japan with RA (n = 41) undergoing articular surgery. The cellular composition was quantified by a deconvolution approach using a public single-cell-based reference. Inflammatory pathway activity was calculated by gene set variation analysis, and chromatin accessibility was evaluated using assay of transposase accessible chromatin-sequencing.

RESULTS

We stratified RA synovium into three distinct subtypes based on the hierarchical clustering of cellular composition data. One subtype was characterized by abundant HLA-DRAhigh synovial fibroblasts, autoimmune-associated B cells, GZMK+ GZMB+ CD8+ T cells, interleukin (IL)1-β+ monocytes, and plasmablasts. In addition, tumor necrosis factor (TNF)-α, interferons (IFNs), and IL-6 signaling were highly activated in this subtype, and the expression of various chemokines was significantly enhanced. Moreover, we found an open chromatin region overlapping with RA risk locus rs9405192 near the IRF4 gene, suggesting the genetic background influences the development of this inflammatory synovial state. The other two subtypes were characterized by increased IFNs and IL-6 signaling, and expression of molecules associated with degeneration, respectively.

CONCLUSION

This study adds insights into the synovial heterogeneity in East Asian patients and shows a promising link with predominant inflammatory signals. Evaluating the site of inflammation has the potential to lead to appropriate drug selection that matches the individual pathology.

Appraising the causal relationship between thyroid function and rheumatoid arthritis: a two-sample bidirectional Mendelian randomization study

Background

Hypothyroidism and hyperthyroidism are observationally associated with rheumatoid arthritis (RA), but causality is unclear. To evaluate the causal relationship between thyroid function and RA, we conducted a two-Sample bidirectional Mendelian Randomization (MR) study.

Methods

Single nucleotide polymorphisms associated with six phenotypes were selected from the FinnGen biobank database, The ThyroidOmics Consortium database, and the IEU Open GWAS database. For the forward MR analysis, we selected hypothyroidism (N=213,390), Graves' disease (GD) (N=199,034), other types of hyperthyroidism (N=190,799), free thyroxine (FT4, N=49,269), and thyroid-stimulating hormone (TSH, N=54,288) as the five related thyroid function phenotypes for exposure, with RA (N=58,284) as the outcome. Reverse MR analysis selected RA as the exposure and five phenotypes of thyroid function as the outcome. The Inverse variance weighting (IVW) method was used as the primary analysis method, supplemented by weighted median (WM) and MR-Egger methods. Cochran's Q test, MR-PRESSO, MR-Egger regression methods, and leave-one-out analysis were employed to assess sensitivity and pleiotropy.

Results

Forward MR evidence indicates that genetic susceptibility to hypothyroidism is associated with an increased risk of RA (ORIvw=1.758, P=7.61×10-5). Reverse MR evidence suggests that genetic susceptibility to RA is associated with an increased risk of hypothyroidism (ORIvw=1.274, P=3.88×10-20), GD (ORIvw=1.269, P=8.15×10-05), and other types of hyperthyroidism (ORIvw=1.141, P=1.80×10-03). There is no evidence to support a forward or reverse causal relationship between genetic susceptibility to RA and FT4, TSH.

Conclusion

Our results provide genetic evidence supporting bidirectional causal relationships between thyroid function and RA. These findings inform preventive strategies and interventions targeting RA and thyroid dysfunction.

Genetic evidence for causal effects of leukocyte counts on risk for rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterized by the accumulation of leukocytes and inflammatory mediators within the synovial tissue. Leukocyte counts are proposed to play a role in the pathogenesis of RA. However, the causality remains unclear. To investigate the causal relationship between various leukocytes and RA by implementing two-sample univariable Mendelian Randomization (MR) and multivariable MR. MR analysis was performed using respective genome-wide association study (GWAS) summary statistics for the exposure traits (eosinophil counts, neutrophil counts, lymphocyte counts, monocyte counts, basophil counts, and white blood cell counts) and outcome trait (RA). Summary statistics for leukocytes were extracted from the Blood Cell Consortium meta-analysis and INTERVAL studies. Public GWAS information for RA included 14,361 cases and 43,923 controls. Inverse variance weighted, weighted median, MR-Egger regression, MR pleiotropy residual sum and outlier, and multivariable MR analyses were performed in MR analysis. Univariable MR found elevated eosinophil counts (OR 1.580, 95% CI 1.389-2.681, p = 1.30 × 10-7) significantly increased the risk of RA. Multivariable MR further confirmed that eosinophil counts were a risk factor for RA. Increased eosinophils were associated with higher risk of RA. Further elucidations of the causality and mechanisms underlying are likely to identify feasible interventions to promote RA prevention.

Rheumatoid arthritis increases the risk of malignant neoplasm of bone and articular cartilage: a two-sample bidirectional mendelian randomization study

OBJECTIVE

Prior research has revealed a heightened prevalence of neoplasms in individuals diagnosed with rheumatoid arthritis (RA). The primary objective of this study is to delve into the causal association between RA and two distinct types of neoplasms: benign neoplasm of bone and articular cartilage (BNBAC) and malignant neoplasm of bone and articular cartilage (MNBAC).

METHODS

We employed summary data from genome-wide association analyses (GWAS) to investigate the causal relationship between RA and two neoplasms, BNBAC and MNBAC, using a two-sample bidirectional Mendelian randomization (MR) study design. The IEU OpenGWAS database provided the GWAS summary data for RA, while the Finnish consortium supplied the GWAS summary data for BNBAC and MNBAC. Our analysis involved the utilization of eight distinct MR methods, namely random-effects inverse variance weighted (IVW), MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and fixed effects IVW. Subsequently, we conducted assessments to evaluate heterogeneity, horizontal pleiotropy, outliers, the impact of a single-nucleotide polymorphism (SNP), and adherence to the assumption of normal distribution in the MR analysis.

RESULTS

The results from the MR analysis revealed that there was no significant genetic association between RA and BNBAC (P = 0.427, odds ratio [OR] 95% confidence interval [CI] = 0.971 [0.904-1.044]). However, a positive genetic association was observed between RA and MNBAC (P = 0.001, OR 95% CI = 1.413 [1.144-1.745]). Conducting a reverse MR analysis, we found no evidence to support a genetic causality between BNBAC (P = 0.088, OR 95% CI = 1.041 [0.994-1.091]) or MNBAC (P = 0.168, OR 95% CI = 1.013 [0.995-1.031]) and RA. Our MR analysis demonstrated the absence of heterogeneity, horizontal pleiotropy, and outliers and confirmed that the effect was not driven by a single SNP. Additionally, the data exhibited a normal distribution.

CONCLUSION

The findings of this study demonstrate that RA constitutes a significant risk factor for MNBAC. In the context of clinical application, it is advisable to conduct MNBAC screening in RA patients and remain vigilant regarding its potential manifestation. Importantly, the outcomes of this investigation introduce a fresh vantage point into the understanding of the tumorigenesis associated with RA.

The effect of immunomodulatory drugs on aortic stenosis: a Mendelian randomisation analysis

There are currently no approved pharmacological treatment options for aortic stenosis (AS), and there are limited identified drug targets for this chronic condition. It remains unclear whether inflammation plays a role in AS pathogenesis and whether immunomodulation could become a therapeutic target. We evaluated the potentially causal association between inflammation and AS by investigating the genetically proxied effects of tocilizumab (IL6 receptor, IL6R, inhibitor), canakinumab (IL1β inhibitor) and colchicine (β-tubulin inhibitor) through a Mendelian randomisation (MR) approach. Genetic proxies for these drugs were identified as single nucleotide polymorphisms (SNPs) in the gene, enhancer or promoter regions of IL6R, IL1β or β-tubulin gene isoforms, respectively, that were significantly associated with serum C-reactive protein (CRP) in a large European genome-wide association study (GWAS; 575,531 participants). These were paired with summary statistics from a large GWAS of AS in European patients (653,867 participants) to then perform primary inverse-variance weighted random effect and sensitivity MR analyses for each exposure. This analysis showed that genetically proxied tocilizumab was associated with reduced risk of AS (OR 0.56, 95% CI 0.45-0.70 per unit decrease in genetically predicted log-transformed CRP). Genetically proxied canakinumab was not associated with risk of AS (OR 0.80, 95% CI 0.51-1.26), and only one suitable SNP was identified to proxy the effect of colchicine (OR 34.37, 95% CI 1.99-592.89). The finding that genetically proxied tocilizumab was associated with reduced risk of AS is concordant with an inflammatory hypothesis of AS pathogenesis. Inhibition of IL6R may be a promising therapeutic target for AS management.

Causal association of rheumatoid arthritis with obstructive lung disease: Evidence from Mendelian randomization study

BACKGROUND

Observational studies have found an association between rheumatoid arthritis (RA) and risk of obstructive lung disease (ORDs). However, whether RA plays a role in ORDs development remains unclear.

OBJECTIVES

This study aimed to explore the causal association of RA with ORDs.

METHODS

Both univariable and multivariable Mendelian randomization (MR) analyses were employed. Summary statistics for RA were obtained from the genome-wide association study (GWAS) meta-analysis, and the GWAS data source of ORDs, including the chronic obstructive pulmonary disease (COPD) and asthma, was accessed from the FinnGen Biobank. Causal Analysis Using Summary Effect Estimates (CAUSE) method was used to improve statistical power. multivariable and two-step mediation MR was applied to calculate the independent and mediated effects.

RESULTS

The causal estimates by univariable and CAUSE results indicated genetic predisposition to RA had an effect on the increased risk of asthma/COPD (A/C) (ORCAUSE = 1.03; 95% CI: 1.02-1.04), COPD/asthma related infections (ACI) (ORCAUSE = 1.02; 95% CI: 1.01-1.03) and COPD/asthma related pneumonia or pneumonia derived septicemia (ACP) (ORCAUSE = 1.02; 95% CI: 1.01-1.03). Genetic predisposition to RA was significantly associated with early onset COPD (ORCAUSE = 1.02; 95% CI: 1.01-1.03) and asthma (ORCAUSE = 1.02; 95% CI: 1.01-1.03) risk and suggestively associated with non-allergic asthma (nAA) risk. After adjustment for confounders, independent causal effects remained for the associations of RA with risk of A/C, ACI, and ACP, as well as COPD, early-onset COPD, and asthma [total, nAA and allergic asthma (AA)] risk. Mediation analyses revealed no potential mediator.

CONCLUSION

This study indicates a causal effect of increased genetic predisposition to RA on an increased risk of ORDs, including COPD and asthma, especially early-onset COPD and nAA, and on asthma/COPD related infections, pneumonia or pneumonia derived septicemia.

Association between genetically predicted rheumatoid arthritis and alopecia areata: a two-sample Mendelian randomization study

Background

Although numerous observational studies have indicated a potential association between autoimmune diseases, such as rheumatoid arthritis (RA) and alopecia areata (AA), the research reports lack a clear causal relationship. In this study, our objective is to utilize the Mendelian randomization (MR) design to examine the potential causal association between RA and AA.

Methods

To investigate the causal relationship between RA and AA, we utilized large-scale gene aggregation data from genome-wide association studies (GWAS), including RA (n=58,284) and AA (n=361,822) based on previous observational studies. In our analysis, we mainly employed the inverse variance-weighted (IVW) method of the random effects model, supplemented by the weighted median (WM) method and the MR Egger method.

Results

The findings from the IVW methods revealed a significant association between genetically predicted RA and an increased likelihood of AA, as evidenced by an odds ratio of 1.21 (95%CI = 1.11-1.32; P < 0.001. Both the WM method and MR-Egger regression consistently showed significant directional outcomes (Both P < 0.05), indicating a robust association between RA and AA. Additionally, both the funnel plot and the MR-Egger intercepts provided evidence of the absence of directional pleiotropy, suggesting that the observed association is not influenced by other common genetic factors.

Conclusions

The results of the study suggest a possible link between genetically predicted RA and AA. This finding highlights the importance for individuals diagnosed with RA to remain vigilant and aware of the potential development of AA. Regular monitoring and early detection can be crucial in managing and addressing this potential complication.

Inflammatory arthritis and eye diseases: a Mendelian randomization study

Objectives

The aim of this study was to determine causal associations between inflammatory arthritis and eye diseases (disorders of sclera, cornea, iris, and ciliary body [DSCIC] and disorders of choroid and retina [DCR]).

Methods

Genome-wide association studies' summary data of rheumatoid arthritis (RA) from a large-scale meta-analysis were used to identify genetically predicted RA. UK Biobank source data predicted ankylosing spondylitis (AS), psoriatic arthritis (PsA), and juvenile idiopathic arthritis (JIA). Furthermore, data from the FinnGen Biobank were used to identify genetically predicted eye diseases. Two-sample Mendelian randomization analysis was used to assess the causal relationship between inflammatory arthritis and eye diseases in the European population. Inverse-variance weighting (IVW) was used as the primary method, while MR-Egger, weighted median, and MR-PRESSO outlier test were used to detect heterogeneity and pleiotropy.

Results

Genetically determined RA was indeed observed to have a causal effect on DSCIC (odds ratio [OR] = 1.084, p = 2.353 × 10-10) and DCR (OR = 1.151, p = 1.584 × 10-19). AS was causally associated with DSCIC (OR = 1.068, p < 2.024 × 10-8). In addition, PsA was also found to have a causal association with an increased risk of 17.9% for the development of DSCIC (OR = 1.179, p = 0.003). On the flip side, DSCIC increased the risk of JIA (OR = 2.276, p = 0.003).

Conclusion

Our study provided genetic evidence for the causal associations of RA, AS, and PsA with an increased risk of DSCIC, and a causal association between RA and DCR was also identified. In addition, DSCIC greatly increased the risk of JIA.

Response to anti-IL17 therapy in inflammatory disease is not strongly impacted by genetic background

Response to the anti-IL17 monoclonal antibody secukinumab is heterogeneous, and not all participants respond to treatment. Understanding whether this heterogeneity is driven by genetic variation is a key aim of pharmacogenetics and could influence precision medicine approaches in inflammatory diseases. Using changes in disease activity scores across 5,218 genotyped individuals from 19 clinical trials across four indications (psoriatic arthritis, psoriasis, ankylosing spondylitis, and rheumatoid arthritis), we tested whether genetics predicted response to secukinumab. We did not find any evidence of association between treatment response and common variants, imputed HLA alleles, polygenic risk scores of disease susceptibility, or cross-disease components of shared genetic risk. This suggests that anti-IL17 therapy is equally effective regardless of an individual's genetic background, a finding that has important implications for future genetic studies of biological therapy response in inflammatory diseases.

Causal relationship between PCSK9 inhibitor and autoimmune diseases: a drug target Mendelian randomization study

BACKGROUND

In addition to decreasing the level of cholesterol, proprotein convertase subtilis kexin 9 (PCSK9) inhibitor has pleiotropic effects, including immune regulation. However, the impact of PCSK9 on autoimmune diseases is controversial. Therefore, we used drug target Mendelian randomization (MR) analysis to investigate the effect of PCSK9 inhibitor on different autoimmune diseases.

METHODS

We collected single nucleotide polymorphisms (SNPs) of PCSK9 from published genome-wide association studies statistics and conducted drug target MR analysis to detect the causal relationship between PCSK9 inhibitor and the risk of autoimmune diseases. 3-Hydroxy-3-methylglutaryl-assisted enzyme A reductase (HMGCR) inhibitor, the drug target of statin, was used to compare the effect with that of PCSK9 inhibitor. With the risk of coronary heart disease as a positive control, primary outcomes included the risk of systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), myasthenia gravis (MG), multiple sclerosis (MS), asthma, Crohn's disease (CD), ulcerative colitis (UC), and type 1 diabetes (T1D).

RESULTS

PCSK9 inhibitor significantly reduced the risk of SLE (OR [95%CI] = 0.47 [0.30 to 0.76], p = 1.74 × 10-3) but increased the risk of asthma (OR [95%CI] = 1.15 [1.03 to 1.29], p = 1.68 × 10-2) and CD (OR [95%CI] = 1.38 [1.05 to 1.83], p = 2.28 × 10-2). In contrast, HMGCR inhibitor increased the risk of RA (OR [95%CI] = 1.58 [1.19 to 2.11], p = 1.67 × 10-3), asthma (OR [95%CI] = 1.21 [1.04 to 1.40], p = 1.17 × 10-2), and CD (OR [95%CI] = 1.60 [1.08 to 2.39], p = 2.04 × 10-2).

CONCLUSIONS

PCSK9 inhibitor significantly reduced the risk of SLE but increased the risk of asthma and CD. In contrast, HMGCR inhibitor may be a risk factor for RA, asthma, and CD.

Modulation of the immunity and inflammation by autophagy

Autophagy, a highly conserved cellular self-degradation pathway, has emerged with novel roles in the realms of immunity and inflammation. Genome-wide association studies have unveiled a correlation between genetic variations in autophagy-related genes and heightened susceptibility to autoimmune and inflammatory diseases. Subsequently, substantial progress has been made in unraveling the intricate involvement of autophagy in immunity and inflammation through functional studies. The autophagy pathway plays a crucial role in both innate and adaptive immunity, encompassing various key functions such as pathogen clearance, antigen processing and presentation, cytokine production, and lymphocyte differentiation and survival. Recent research has identified novel approaches in which the autophagy pathway and its associated proteins modulate the immune response, including noncanonical autophagy. This review provides an overview of the latest advancements in understanding the regulation of immunity and inflammation through autophagy. It summarizes the genetic associations between variants in autophagy-related genes and a range of autoimmune and inflammatory diseases, while also examining studies utilizing transgenic animal models to uncover the in vivo functions of autophagy. Furthermore, the review delves into the mechanisms by which autophagy dysregulation contributes to the development of three common autoimmune and inflammatory diseases and highlights the potential for autophagy-targeted therapies.

Increased Risk of Rheumatoid Arthritis in Patients With Asthma: A Genetic Association Study Using Two-Sample Mendelian Randomization Analysis

OBJECTIVE

Observational studies have explored the association between asthma and some types of arthritis, including rheumatoid arthritis and osteoarthritis, but the results are largely contradictory. We aimed to investigate the causal effects of asthma on arthritis, including osteoarthritis, rheumatoid arthritis, gout, and ankylosing spondylitis.

METHODS

Two-sample Mendelian randomization (MR) analysis was used to investigate the causal effects of asthma on each arthritis. The genetic instruments for asthma were obtained from a large genome-wide association study of asthma. The inverse-variance weighted (IVW) method was used as the main analysis of MR. Bonferroni-adjusted P value threshold was used to account for multiple comparisons.

RESULTS

MR-IVW analysis suggested that adult-onset asthma (AOA) was associated with increased risk of rheumatoid arthritis. The odds ratio for rheumatoid arthritis associated with AOA and childhood-onset asthma (COA) were 1.018 (95% confidence interval [95% CI], 1.011-1.025; P < 0.001) and 1.006 (95% CI 1.001-1.012; P = 0.046), respectively. For osteoarthritis, gout, or ankylosing spondylitis, all the MR analyses showed no significant causal effects of AOA or COA on them. We also performed a reverse MR analysis to explore the causal effects of rheumatoid on all asthma, allergic asthma, or nonallergic asthma and found no significant causal effects on them.

CONCLUSION

Genetically predicted AOA predisposes patients to an increased risk of rheumatoid arthritis but has no causal effects on osteoarthritis, gout, and ankylosing spondylitis. The result of COA on rheumatoid arthritis is suggestive of potential causal relationship but needs to be confirmed in further studies.

Mendelian Randomization Analyses of Chronic Immune-Mediated Diseases, Circulating Inflammatory Biomarkers, and Cytokines in Relation to Liver Cancer

Liver cancer is closely linked to chronic inflammation. While observational studies have reported positive associations between extrahepatic immune-mediated diseases and systemic inflammatory biomarkers and liver cancer, the genetic association between these inflammatory traits and liver cancer remains elusive and merits further investigation. We conducted a two-sample Mendelian randomization (MR) analysis, using inflammatory traits as exposures and liver cancer as the outcome. The genetic summary data of both exposures and outcome were retrieved from previous genome-wide association studies (GWAS). Four MR methods, including inverse-variance-weighted (IVW), MR-Egger regression, weighted-median, and weighted-mode methods, were employed to examine the genetic association between inflammatory traits and liver cancer. Nine extrahepatic immune-mediated diseases, seven circulating inflammatory biomarkers, and 187 inflammatory cytokines were analyzed in this study. The IVW method suggested that none of the nine immune-mediated diseases were associated with the risk of liver cancer, with odds ratios of 1.08 (95% CI 0.87-1.35) for asthma, 0.98 (95% CI 0.91-1.06) for rheumatoid arthritis, 1.01 (95% CI 0.96-1.07) for type 1 diabetes, 1.01 (95% CI 0.98-1.03) for psoriasis, 0.98 (95% CI 0.89-1.08) for Crohn's disease, 1.02 (95% CI 0.91-1.13) for ulcerative colitis, 0.91 (95% CI 0.74-1.11) for celiac disease, 0.93 (95% CI 0.84-1.05) for multiple sclerosis, and 1.05 (95% CI 0.97-1.13) for systemic lupus erythematosus. Similarly, no significant association was found between circulating inflammatory biomarkers and cytokines and liver cancer after correcting for multiple testing. The findings were consistent across all four MR methods used in this study. Our findings do not support a genetic association between extrahepatic inflammatory traits and liver cancer. However, larger-scale GWAS summary data and more genetic instruments are needed to confirm these findings.

Metabolic signature of healthy lifestyle and risk of rheumatoid arthritis: observational and Mendelian randomization study

BACKGROUND

While substantial evidence reveals that healthy lifestyle behaviors are associated with a lower risk of rheumatoid arthritis (RA), the underlying metabolic mechanisms remain unclear.

OBJECTIVES

This study aimed to identify the metabolic signature reflecting a healthy lifestyle and investigate its observational and genetic linkage with RA risk.

METHODS

This study included 87,258 UK Biobank participants (557 cases of incident RA) aged 37 to 73 years with complete lifestyle, genotyping and nuclear magnetic resonance (NMR) metabolomics data. A healthy lifestyle was assessed based on five factors: healthy diet, regular exercise, not smoking, moderate alcohol consumption, and normal body mass index. The metabolic signature was developed by summing selected metabolites' concentrations weighted by the coefficients using elastic net regression. We used multivariate Cox model to assess the associations between metabolic signatures and RA risk, and examined the mediating role of the metabolic signature in the impact of a healthy lifestyle on RA. We performed genome-wide association analysis (GWAS) to obtain genetic variants associated with the metabolic signature, then conducted Mendelian randomization (MR) analyses to detect causality.

RESULTS

The metabolic signature comprised of 81 metabolites, robustly correlated with healthy lifestyle ( r = 0.45, P = 4.2 × 10^-15). The metabolic signature was inversely associated with RA risk (HR per SD increment: 0.76, 95% CI: 0.70-0.83), and largely explained protective effects of healthy lifestyle on RA with 64% (95%CI: 50.4-83.3) mediation proportion. One and two-sample MR analyses also consistently showed the associations of genetically inferred per SD increment in metabolic signature with a reduction in RA risk (HR: 0.84, 95% CI: 0.75-0.94, P = 0.002 and OR: 0.84, 95% CI: 0.73-0.97, P = 0.02 respectively).

CONCLUSION

Our findings implicate the metabolic signature reflecting healthy lifestyle as a potential causal mediator in the development of RA, highlighting the importance of early lifestyle intervention and metabolic tracking for precise prevention of RA.

Computational Fluid Dynamics (CFD) Model for Analysing the Role of Shear Stress in Angiogenesis in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterised by an attack on healthy cells in the joints. Blood flow and wall shear stress are crucial in angiogenesis, contributing to RA's pathogenesis. Vascular endothelial growth factor (VEGF) regulates angiogenesis, and shear stress is a surrogate for VEGF in this study. Our objective was to determine how shear stress correlates with the location of new blood vessels and RA progression. To this end, two models were developed using computational fluid dynamics (CFD). The first model added new blood vessels based on shear stress thresholds, while the second model examined the entire blood vessel network. All the geometries were based on a micrograph of RA blood vessels. New blood vessel branches formed in low shear regions (0.840-1.260 Pa). This wall-shear-stress overlap region at the junctions was evident in all the models. The results were verified quantitatively and qualitatively. Our findings point to a relationship between the development of new blood vessels in RA, the magnitude of wall shear stress and the expression of VEGF.