Investigation of the causal association between Parkinson's disease and autoimmune disorders: a bidirectional Mendelian randomization study.

Background: To date, an increasing number of epidemiological evidence has pointed to potential relationships between Parkinson's disease (PD) and various autoimmune diseases (AIDs), however, no definitive conclusions has been drawn about whether PD is causally related to AIDs risk. Methods: By employing summary statistics from the latest and most extensive genome-wide association studies (GWAS), we performed a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal associations between PD and a variety of 17 AIDs, encompassing multiple sclerosis, neuromyelitis optica spectrum disorder, myasthenia gravis, asthma, inflammatory bowel disease, Crohn's disease, ulcerative colitis, irritable bowel syndrome, celiac disease, primary biliary cirrhosis, primary sclerosing cholangitis, type 1 diabetes, ankylosing spondylitis, rheumatoid arthritis, systemic lupus erythematosus, psoriasis and vitiligo. Inverse-variance weighted (IVW) was adopted as the main statistical approach to obtain the causal estimates of PD on different AIDs, supplemented by a series of complementary analyses (weighted median, MR Egger regression, and MR-PRESSO) for further strengthening the robustness of results. Results: Our MR findings suggested that genetically predicted higher liability to PD was causally associated with a decreased risk of irritable bowel syndrome (OR = 0.98; 95% CI: 0.96-0.99; P = 0.032). On the contrary, IVW analysis showed a potential positive correlation between genetically determined PD and the incidence of type 1 diabetes (OR = 1.10; 95%CI: 1.02-1.19; P = 0.010). Subsequent MR tests ended up in similar results, confirming our findings were reliable. Additionally, in the reverse MR analyses, we did not identify any evidence to support the causal relationship of genetic predisposition to AIDs with PD susceptibility. Conclusion: In general, a bifunctional role that PD exerted on the risk of developing AIDs was detected in our studies, both protecting against irritable bowel syndrome occurrence and raising the incidence of type 1 diabetes. Future studies, including population-based observational studies and molecular experiments in vitro and in vivo, are warranted to validate the results of our MR analyses and refine the underlying pathological mechanisms involved in PD-AIDs associations.

Dissecting causal relationships between primary biliary cholangitis and extrahepatic autoimmune diseases based on Mendelian randomization.

As an autoimmune disease, up to 73% of patients with primary biliary cholangitis (PBC) have a combination of extrahepatic autoimmune diseases (EHAIDs); however, the causal relationship between PBC and EHAIDs is unclear. The genome-wide association analyses provided 14 GWAS data for PBC and EHAIDs, and bidirectional, two-sample MR analyses were performed to examine the relationship between PBC and EHAIDs. The analysis using MR provides a strong and meaningful estimation of the bidirectional correlation between PBC and 7 EHAIDs: rheumatoid arthritis, systemic lupus erythematosus, Sjögren's syndrome, systemic sclerosis, autoimmune hypothyroidism, inflammatory bowel disease and ulcerative colitis of its types. In addition, PBC increases the risk of autoimmune thyroid diseases such as autoimmune hyperthyroidism and Graves' disease, as well as multiple sclerosis and psoriasis. Additionally, PBC is identified as a risk factor for Crohn's disease and Celiac disease. Based on genetic evidence, there may be connections between PBC and specific EHAIDs: not all coexisting EHAIDs induce PBC, and vice versa. This underscores the significance of prioritizing PBC in clinical practice. Additionally, if any liver function abnormalities are observed during treatment or with EHAIDs, it is crucial to consider the possibility of comorbid PBC.

Mechanisms and functions of lncRNAs linked to autoimmune disease risk alleles.

Recent advances in human genomics technologies have helped uncover genetic risk alleles for many complex autoimmune diseases. Intriguingly, over 90% of genome-wide association study (GWAS) risk alleles reside within the non-coding regions of the genome. An emerging new frontier of functional and mechanistic studies have shed light on the functional relevance of risk alleles that lie within long noncoding RNAs (lncRNAs). Here, we review the mechanisms and functional implications of five evolutionarily conserved lncRNAs that display risk allele association with highly prevalent autoimmune diseases.

Emerging strategies for treating autoimmune disease with genetically modified dendritic cells.

Gene editing of living cells has become a crucial tool in medical research, enabling scientists to address fundamental biological questions and develop novel strategies for disease treatment. This technology has particularly revolutionized adoptive transfer cell therapy products, leading to significant advancements in tumor treatment and offering promising outcomes in managing transplant rejection, autoimmune disorders, and inflammatory diseases. While recent clinical trials have demonstrated the safety of tolerogenic dendritic cell (TolDC) immunotherapy, concerns remain regarding its effectiveness. This review aims to discuss the application of gene editing techniques to enhance the tolerance function of dendritic cells (DCs), with a particular focus on preclinical strategies that are currently being investigated to optimize the tolerogenic phenotype and function of DCs. We explore potential approaches for in vitro generation of TolDCs and provide an overview of emerging strategies for modifying DCs. Additionally, we highlight the primary challenges hindering the clinical adoption of TolDC therapeutics and propose future research directions in this field.

Causal association between autoimmune liver disease and Sjögren's syndrome: A Mendelian randomization study.

BACKGROUND: Observational studies have found an association between autoimmune liver disease (AILD) and Sjögren's syndrome (SS). However, the causal relationship between the two remains unknown. Clinical guidelines indicate that the coexistence of AILD with other autoimmune diseases may impact prognosis and quality of life; hence, early recognition and management of extrahepatic autoimmune diseases is particularly crucial. Against this backdrop, this study aimed to utilize Mendelian randomization (MR) methods to investigate the potential causal relationship between AILD and SS. METHODS: We extracted summary statistics on AILD and SS from publicly available genome-wide association studies (GWAS) databases to identify appropriate instrumental variables (IVs). The inverse-variance weighted (IVW) method was utilized as the primary approach, with the weighted median (WM) method and MR-Egger method employed as supplementary methods to evaluate the potential causal relationship between the two conditions. Sensitivity analyses, including Cochran's Q test, MR-polynomial residuals and outliers (MR-PRESSO), MR-Egger intercept test, and the leave-one-out test, were performed to assess the stability of the results. RESULTS: The MR study results indicate a significant causal relationship between PBC and PSC with the risk of SS in the European population (IVW: odds ratio [OR] = 1.155, 95% confidence interval [CI]: 1.092-1.222, p < .001; IVW: OR = 1.162, 95% CI: 1.051-1.284, p = .003). A series of sensitivity analyses have confirmed the reliability of the results. CONCLUSIONS: Our study indicates that the presence of both PBC and PSC increases the susceptibility to SS. However, no reliable causal relationship was found between SS and the risk of PBC or PSC. These findings contribute to elucidating the potential pathogenic mechanisms of the disease and are of significant importance for the management of patients with PBC and PSC.

One gene to rule them all - clinical perspectives of a potent suppressor of cytokine signaling - SOCS1.

The discovery of Suppressor of Cytokine Signaling 1 (SOCS1) in 1997 marked a significant milestone in understanding the regulation of Janus kinase/Signal transducer and activator of transcription (JAK/STAT) signaling pathways. Subsequent research deciphered its cellular functions, and recent insights into SOCS1 deficiencies in humans underscored its critical role in immune regulation. In humans, SOCS-haploinsufficiency (SOCS1-HI) presents a diverse clinical spectrum, encompassing autoimmune diseases, infection susceptibility, and cancer. Variability in disease manifestation, even within families sharing the same genetic variant, raises questions about clinical penetrance and the need for individualized treatments. Current therapeutic strategies include JAK inhibition, with promising results in controlling inflammation in SOCS1-HI patients. Hematopoietic stem cell transplantation and gene therapy emerge as promising avenues for curative treatments. The evolving landscape of SOCS1 research, emphasizes the need for a nuanced understanding of genetic variants and their functional consequences.

Genetic association and causal relationship between multiple modifiable risk factors and autoimmune liver disease: a two-sample mendelian randomization study.

BACKGROUND: The intricate etiology of autoimmune liver disease (AILD) involves genetic, environmental, and other factors that yet to be completely elucidated. This study comprehensively assessed the causal association between genetically predicted modifiable risk factors and AILD by employing Mendelian randomization. METHODS: Genetic variants associated with 29 exposure factors were obtained from genome-wide association studies (GWAS). Genetic association data with autoimmune hepatitis (AIH), primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) were also obtained from publicly available GWAS. Univariate and multivariate Mendelian randomization analyses were performed to identify potential risk factors for AILD. RESULTS: Genetically predicted rheumatoid arthritis (RA) (OR = 1.620, 95%CI 1.423-1.843, P = 2.506 × 10- 13) was significantly associated with an increased risk of AIH. Genetically predicted smoking initiation (OR = 1.637, 95%CI 1.055-2.540, P = 0.028), lower coffee intake (OR = 0.359, 95%CI 0.131-0.985, P = 0.047), cholelithiasis (OR = 1.134, 95%CI 1.023-1.257, P = 0.017) and higher C-reactive protein (CRP) (OR = 1.397, 95%CI 1.094-1.784, P = 0.007) were suggestively associated with an increased risk of AIH. Genetically predicted inflammatory bowel disease (IBD) (OR = 1.212, 95%CI 1.127-1.303, P = 2.015 × 10- 7) and RA (OR = 1.417, 95%CI 1.193-1.683, P = 7.193 × 10- 5) were significantly associated with increased risk of PBC. Genetically predicted smoking initiation (OR = 1.167, 95%CI 1.005-1.355, P = 0.043), systemic lupus erythematosus (SLE) (OR = 1.086, 95%CI 1.017-1.160, P = 0.014) and higher CRP (OR = 1.199, 95%CI 1.019-1.410, P = 0.028) were suggestively associated with an increased risk of PBC. Higher vitamin D3 (OR = 0.741, 95%CI 0.560-0.980, P = 0.036) and calcium (OR = 0.834, 95%CI 0.699-0.995, P = 0.044) levels were suggestive protective factors for PBC. Genetically predicted smoking initiation (OR = 0.630, 95%CI 0.462-0.860, P = 0.004) was suggestively associated with a decreased risk of PSC. Genetically predicted IBD (OR = 1.252, 95%CI 1.164-1.346, P = 1.394 × 10- 9), RA (OR = 1.543, 95%CI 1.279-1.861, P = 5.728 × 10- 6) and lower glycosylated hemoglobin (HbA1c) (OR = 0.268, 95%CI 0.141-0.510, P = 6.172 × 10- 5) were positively associated with an increased risk of PSC. CONCLUSIONS: Evidence on the causal relationship between 29 genetically predicted modifiable risk factors and the risk of AIH, PBC, and PSC is provided by this study. These findings provide fresh perspectives on the management and prevention strategies for AILD.

The causal relationship between sarcoidosis and autoimmune diseases: a bidirectional Mendelian randomization study in FinnGen.

Background: Sarcoidosis has been considered to be associated with many autoimmune diseases (ADs), but the cause-and-effect relationship between these two diseases has not been fully explored. Therefore, the objective of this study is to explore the possible genetic association between sarcoidosis and ADs. Methods: We conducted a bidirectional Mendelian randomization (MR) study using genetic variants associated with ADs and sarcoidosis (4,041 cases and 371,255 controls) from the FinnGen study. The ADs dataset comprised 96,150 cases and 281,127 controls, encompassing 44 distinct types of autoimmune-related diseases. Subsequently, we identified seven diseases within the ADs dataset with a case size exceeding 3,500 and performed subgroup analyses on these specific diseases. Results: The MR evidence supported the causal association of genetic predictors of ADs with an increased risk of sarcoidosis (OR = 1.79, 95% CI = 1.59 to 2.02, P IVW-FE = 1.01 × 10-21), and no reverse causation (OR = 1.05, 95% CI 0.99 to 1.12, P IVW-MRE = 9.88 × 10-2). Furthermore, subgroup analyses indicated that genetic predictors of type 1 diabetes mellitus (T1DM), celiac disease, and inflammatory bowel disease (IBD) were causally linked to an elevated risk of sarcoidosis (All P < 6.25 × 10-3). Conversely, genetic predictors of sarcoidosis showed causal associations with a higher risk of type 1 diabetes mellitus (P < 6.25 × 10-3). Conclusion: The present study established a positive causal relationship between genetic predictors of ADs (e.g. T1DM, celiac disease, and IBD) and the risk of sarcoidosis, with no evidence of reverse causation.

Roles of blood metabolites in mediating the relationship between vitiligo and autoimmune diseases: Evidence from a Mendelian randomization study.

OBJECTIVE: This study employed Mendelian Randomization (MR) to investigate the causal relationship between genetic susceptibility to vitiligo and the risk of various autoimmune diseases, along with the mediating role of blood metabolites. METHODS: We performed two-sample MR analyses using aggregated genome-wide association studies (GWAS) data on 486 blood metabolites, vitiligo, and nine autoimmune diseases to investigate blood metabolites' causal effects on the susceptibility of vitiligo and the associations of vitiligo with nine autoimmune comorbidities. We also applied multivariable MR to unravel metabolites by which vitiligo influences the pathogenesis of autoimmune diseases. RESULTS: Our findings indicate that vitiligo amplified the risk of several autoimmune diseases, including rheumatoid arthritis (OR 1.17; 95 % CI 1.08-1.27), psoriasis (OR 1.10; 95 % CI 1.04-1.17), type 1 diabetes (OR 1.41; 95 % CI 1.23-1.63), pernicious anemia (OR 1.23; 95 % CI 1.12-1.36), autoimmune hypothyroidism (OR 1.19; 95 % CI 1.11-1.26), alopecia areata (OR 1.22; 95 % CI 1.10-1.35), and autoimmune Addison's disease (OR 1.22; 95 % CI 1.12-1.33). Additionally, our analysis identified correlations with vitiligo for 14 known (nine risk, five protective) and seven uncharacterized serum metabolites. After adjusting for genetically predicted levels of histidine and pyruvate, the associations between vitiligo and these diseases were attenuated. CONCLUSIONS: We substantiated vitiligo's influence on susceptibility to seven autoimmune diseases and conducted a thorough investigation of serum metabolites correlated with vitiligo. Histidine and pyruvate are potential mediators of vitiligo associated with autoimmune diseases.By combining metabolomics with genomics, we provide new perspectives on the etiology of vitiligo and its immune comorbidities.

Genetic mapping across autoimmune diseases reveals shared associations and mechanisms.

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

Integrating single cell expression quantitative trait loci summary statistics to understand complex trait risk genes.

Transcriptome-wide association study (TWAS) is a popular approach to dissect the functional consequence of disease associated non-coding variants. Most existing TWAS use bulk tissues and may not have the resolution to reveal cell-type specific target genes. Single-cell expression quantitative trait loci (sc-eQTL) datasets are emerging. The largest bulk- and sc-eQTL datasets are most conveniently available as summary statistics, but have not been broadly utilized in TWAS. Here, we present a new method EXPRESSO (EXpression PREdiction with Summary Statistics Only), to analyze sc-eQTL summary statistics, which also integrates 3D genomic data and epigenomic annotation to prioritize causal variants. EXPRESSO substantially improves existing methods. We apply EXPRESSO to analyze multi-ancestry GWAS datasets for 14 autoimmune diseases. EXPRESSO uniquely identifies 958 novel gene x trait associations, which is 26% more than the second-best method. Among them, 492 are unique to cell type level analysis and missed by TWAS using whole blood. We also develop a cell type aware drug repurposing pipeline, which leverages EXPRESSO results to identify drug compounds that can reverse disease gene expressions in relevant cell types. Our results point to multiple drugs with therapeutic potentials, including metformin for type 1 diabetes, and vitamin K for ulcerative colitis.

Unlocking the genetic tapestry of autoimmune diseases: Unveiling common genes across multiple conditions.

OBJECTIVES: This study aimed to unravel the complexities of autoimmune diseases by conducting a comprehensive analysis of gene expression data across 10 conditions, including systemic lupus erythematosus (SLE), psoriasis, Sjögren's syndrome, sclerosis, immune-associated diseases, osteoarthritis, cystic fibrosis, inflammatory bowel disease (IBD), type 1 diabetes, and Guillain-Barré syndrome. METHODS: Gene expression profiles were rigorously examined to identify both upregulated and downregulated genes specific to each autoimmune disease. The study employed visual representation techniques such as heatmaps, volcano plots, and contour-MA plots to provide an intuitive understanding of the complex gene expression patterns in these conditions. RESULTS: Distinct gene expression profiles for each autoimmune condition were uncovered, with psoriasis and osteoarthritis standing out due to a multitude of both upregulated and downregulated genes, indicating intricate molecular interplays in these disorders. Notably, common upregulated and downregulated genes were identified across various autoimmune conditions, with genes like SELENBP1, MMP9, BNC1, and COL1A1 emerging as pivotal players. CONCLUSION: This research contributes valuable insights into the molecular signatures of autoimmune diseases, highlighting the unique gene expression patterns characterizing each condition. The identification of common genes shared among different autoimmune conditions, and their potential role in mitigating the risk of rare diseases in patients with more prevalent conditions, underscores the growing significance of genetics in healthcare and the promising future of personalized medicine.

The casual relationship between autoimmune diseases and multiple myeloma: a Mendelian randomization study.

Observational studies showed possible associations between systemic lupus erythematosus and multiple myeloma. However, whether there is a casual relationship between different types of autoimmune diseases (type 1 diabetes mellitus, rheumatoid arthritis, systemic lupus erythematosus, psoriasis, multiple sclerosis, primary sclerosing cholangitis, primary biliary cirrhosis, and juvenile idiopathic arthritis) and multiple myeloma (MM) is not well known. We performed a two-sample Mendelian randomization (MR) study to estimate the casual relationship. Summary-level data of autoimmune diseases were gained from published genome-wide association studies while data of MM was obtained from UKBiobank. The Inverse-Variance Weighted (IVW) method was used as the primary analysis method to interpret the study results, with MR-Egger and weighted median as complementary methods of analysis. There is causal relationship between primary sclerosing cholangitis [OR = 1.00015, 95% CI 1.000048-1.000254, P = 0.004] and MM. Nevertheless, no similar causal relationship was found between the remaining seven autoimmune diseases and MM. Considering the important role of age at recruitment and body mass index (BMI) in MM, we excluded these relevant instrument variables, and similar results were obtained. The accuracy and robustness of these findings were confirmed by sensitivity tests. Overall, MR analysis suggests that genetic liability to primary sclerosing cholangitis could be causally related to the increasing risk of MM. This finding may serve as a guide for clinical attention to patients with autoimmune diseases and their early screening for MM.

Targeting pathogenic CD8+ tissue-resident T cells with chimeric antigen receptor therapy in murine autoimmune cholangitis.

Primary biliary cholangitis (PBC) is a cholestatic autoimmune liver disease characterized by autoreactive T cell response against intrahepatic small bile ducts. Here, we use Il12b-/-Il2ra-/- mice (DKO mice) as a model of autoimmune cholangitis and demonstrate that Cd8a knockout or treatment with an anti-CD8α antibody prevents/reduces biliary immunopathology. Using single-cell RNA sequencing analysis, we identified CD8+ tissue-resident memory T (Trm) cells in the livers of DKO mice, which highly express activation- and cytotoxicity-associated markers and induce apoptosis of bile duct epithelial cells. Liver CD8+ Trm cells also upregulate the expression of several immune checkpoint molecules, including PD-1. We describe the development of a chimeric antigen receptor to target PD-1-expressing CD8+ Trm cells. Treatment of DKO mice with PD-1-targeting CAR-T cells selectively depleted liver CD8+ Trm cells and alleviated autoimmune cholangitis. Our work highlights the pathogenic role of CD8+ Trm cells and the potential therapeutic usage of PD-1-targeting CAR-T cells.

Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes.

Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10-7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.

Shared genetic architecture between autoimmune disorders and B-cell acute lymphoblastic leukemia: insights from large-scale genome-wide cross-trait analysis.

BACKGROUND: To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved. METHODS: Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations. RESULTS: Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P < 5 × 10-8), 16 of which had strong evidence of colocalization. We demonstrated that several loci have been previously reported (e.g., 17q21) and discovered some novel loci (e.g., 10p12, 5p13). Further gene-level identified 194 unique pleiotropic genes, for example IKZF1, GATA3, IKZF3, GSDMB, and ORMDL3. Pathway analysis determined the key role of cellular response to cytokine stimulus, B cell activation, and JAK-STAT signaling pathways. SNP-level and gene-level tissue enrichment suggested that crucial role pleiotropic mechanisms involved in the spleen, whole blood, and EBV-transformed lymphocytes. Also, hyprcoloc and stratified LD score regression analyses revealed that B cells at different developmental stages may be involved in mechanisms shared between two different diseases. Finally, two-sample MR analysis determined causal effects of asthma and rheumatoid arthritis on B-ALL. CONCLUSIONS: Our research proved shared genetic architecture between autoimmune disorders and B-ALL and shed light on the potential mechanism that might involve in.

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.

Association of autoimmune and allergic diseases with senile cataract: a bidirectional two-sample Mendelian randomization study.

Background: Many observational studies have been reported that patients with autoimmune or allergic diseases seem to have a higher risk of developing senile cataract, but the views are not consistent. In order to minimize the influence of reverse causality and potential confounding factors, we performed Mendelian Randomization (MR) analysis to investigate the genetic causal associations between autoimmune, allergic diseases and senile cataract. Methods: Single nucleotide polymorphisms associated with ten common autoimmune and allergic diseases were obtained from the IEU Open genome-wide association studies (GWAS) database. Summary-level GWAS statistics for clinically diagnosed senile cataract were obtained from the FinnGen research project GWAS, which consisted of 59,522 individuals with senile cataracts and 312,864 control individuals. MR analysis was conducted using mainly inverse variance weighted (IVW) method and further sensitivity analysis was performed to test robustness. Results: As for ten diseases, IVW results confirmed that type 1 diabetes (OR = 1.06; 95% CI = 1.05-1.08; p = 2.24×10-12), rheumatoid arthritis (OR = 1.05; 95% CI = 1.02-1.08; p = 1.83×10-4), hypothyroidism (OR = 2.4; 95% CI = 1.42-4.06; p = 1.12×10-3), systemic lupus erythematosus (OR = 1.02; 95% CI = 1.01-1.03; p = 2.27×10-3), asthma (OR = 1.02; 95% CI = 1.01-1.03; p = 1.2×10-3) and allergic rhinitis (OR = 1.07; 95% CI = 1.02-1.11; p = 2.15×10-3) were correlated with the risk of senile cataract. Celiac disease (OR = 1.04; 95% CI = 1.01-1.08; P = 0.0437) and atopic dermatitis (OR = 1.05; 95% CI = 1.01-1.10; P = 0.0426) exhibited a suggestive connection with senile cataract after Bonferroni correction. These associations are consistent across weighted median and MR Egger methods, with similar causal estimates in direction and magnitude. Sensitivity analysis further proved that these associations were reliable. Conclusions: The results of the MR analysis showed that there were causal relationships between type 1 diabetes, rheumatoid arthritis, hypothyroidism, systemic lupus erythematosus, asthma, allergic rhinitis and senile cataract. To clarify the possible role of autoimmune and allergy in the pathophysiology of senile cataract, further studies are needed.

Theoretical Studies of DNA Microarray Present Potential Molecular and Cellular Interconnectivity of Signaling Pathways in Immune System Dysregulation.

Autoimmunity is defined as the inability to regulate immunological activities in the body, especially in response to external triggers, leading to the attack of the tissues and organs of the host. Outcomes include the onset of autoimmune diseases whose effects are primarily due to dysregulated immune responses. In past years, there have been cases that show an increased susceptibility to other autoimmune disorders in patients who are already experiencing the same type of disease. Research in this field has started analyzing the potential molecular and cellular causes of this interconnectedness, bearing in mind the possibility of advancing drugs and therapies for the treatment of autoimmunity. With that, this study aimed to determine the correlation of four autoimmune diseases, which are type 1 diabetes (T1D), psoriasis (PSR), systemic sclerosis (SSc), and systemic lupus erythematosus (SLE), by identifying highly preserved co-expressed genes among datasets using WGCNA. Functional annotation was then employed to characterize these sets of genes based on their systemic relationship as a whole to elucidate the biological processes, cellular components, and molecular functions of the pathways they are involved in. Lastly, drug repurposing analysis was performed to screen candidate drugs for repositioning that could regulate the abnormal expression of genes among the diseases. A total of thirteen modules were obtained from the analysis, the majority of which were associated with transcriptional, post-transcriptional, and post-translational modification processes. Also, the evaluation based on KEGG suggested the possible role of TH17 differentiation in the simultaneous onset of the four diseases. Furthermore, clomiphene was the top drug candidate for regulating overexpressed hub genes; meanwhile, prilocaine was the top drug for regulating under-expressed hub genes. This study was geared towards utilizing transcriptomics approaches for the assessment of microarray data, which is different from the use of traditional genomic analyses. Such a research design for investigating correlations among autoimmune diseases may be the first of its kind.

Large-scale genome-wide association studies reveal the genetic causal etiology between air pollutants and autoimmune diseases.

BACKGROUND: Epidemiological evidence links a close correlation between long-term exposure to air pollutants and autoimmune diseases, while the causality remained unknown. METHODS: Two-sample Mendelian randomization (TSMR) was used to investigate the role of PM10, PM2.5, NO2, and NOX (N = 423,796-456,380) in 15 autoimmune diseases (N = 14,890-314,995) using data from large European GWASs including UKB, FINNGEN, IMSGC, and IPSCSG. Multivariable Mendelian randomization (MVMR) was conducted to investigate the direct effect of each air pollutant and the mediating role of common factors, including body mass index (BMI), alcohol consumption, smoking status, and household income. Transcriptome-wide association studies (TWAS), two-step MR, and colocalization analyses were performed to explore underlying mechanisms between air pollution and autoimmune diseases. RESULTS: In TSMR, after correction of multiple testing, hypothyroidism was causally associated with higher exposure to NO2 [odds ratio (OR): 1.37, p = 9.08 × 10-4] and NOX [OR: 1.34, p = 2.86 × 10-3], ulcerative colitis (UC) was causally associated with higher exposure to NOX [OR: 2.24, p = 1.23 × 10-2] and PM2.5 [OR: 2.60, p = 5.96 × 10-3], rheumatoid arthritis was causally associated with higher exposure to NOX [OR: 1.72, p = 1.50 × 10-2], systemic lupus erythematosus was causally associated with higher exposure to NOX [OR: 4.92, p = 6.89 × 10-3], celiac disease was causally associated with lower exposure to NOX [OR: 0.14, p = 6.74 × 10-4] and PM2.5 [OR: 0.17, p = 3.18 × 10-3]. The risky effects of PM2.5 on UC remained significant in MVMR analyses after adjusting for other air pollutants. MVMR revealed several common mediators between air pollutants and autoimmune diseases. Transcriptional analysis identified specific gene transcripts and pathways interconnecting air pollutants and autoimmune diseases. Two-step MR revealed that POR, HSPA1B, and BRD2 might mediate from air pollutants to autoimmune diseases. POR pQTL (rs59882870, PPH4=1.00) strongly colocalized with autoimmune diseases. CONCLUSION: This research underscores the necessity of rigorous air pollutant surveillance within public health studies to curb the prevalence of autoimmune diseases.