S2 File -

BackgroundAn association between primary biliary cholangitis (PBC) and connective tissue diseases (CTDs) [rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjögren’s syndrome (SS), systemic sclerosis (SSc)] has been found in observational studies. However, the direction causality is unclear. The aim of this study was to assess the causality between PBC and CTDs and to promote early screening, pre-emptive therapy, and accurate stratification.MethodsA two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between PBC [Genome-Wide Association Study (GWAS) meta-analysis, 8021 cases/16498 controls], and SLE (GWAS meta-analysis, 8021 cases/16489 controls), RA(FinnGen, 6236 cases/14727 controls), SS(FinnGen, 2495 cases/365533 controls), SSc (FinnGen, 302 cases/213145 controls). Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by four sensitivity analyses to assess the robustness of the results.ResultsThe IVW revealed that genetically predicted PBC increased the risk of SLE [odd’s ratio (OR) = 1.43, 95% confidence interval (CI) 1.30–1.58, P ConclusionsOur study provided new genetic evidence for a causal relationship between PBC and CTDs. PBC increased the risk of SLE, RA, and SS. Our findings highlighted the importance of active screening and intervention for CTDs in patients with PBC.</div

Heterogeneity and pleiotropy tests for the associations between PBC and CTD.

Heterogeneity and pleiotropy tests for the associations between PBC and CTD.</p

S4 File -

BackgroundAn association between primary biliary cholangitis (PBC) and connective tissue diseases (CTDs) [rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjögren’s syndrome (SS), systemic sclerosis (SSc)] has been found in observational studies. However, the direction causality is unclear. The aim of this study was to assess the causality between PBC and CTDs and to promote early screening, pre-emptive therapy, and accurate stratification.MethodsA two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between PBC [Genome-Wide Association Study (GWAS) meta-analysis, 8021 cases/16498 controls], and SLE (GWAS meta-analysis, 8021 cases/16489 controls), RA(FinnGen, 6236 cases/14727 controls), SS(FinnGen, 2495 cases/365533 controls), SSc (FinnGen, 302 cases/213145 controls). Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by four sensitivity analyses to assess the robustness of the results.ResultsThe IVW revealed that genetically predicted PBC increased the risk of SLE [odd’s ratio (OR) = 1.43, 95% confidence interval (CI) 1.30–1.58, P ConclusionsOur study provided new genetic evidence for a causal relationship between PBC and CTDs. PBC increased the risk of SLE, RA, and SS. Our findings highlighted the importance of active screening and intervention for CTDs in patients with PBC.</div

Causal effects of PBC on the risk of CTDs assessed by different Mendelian randomization methods.

PBC for exposure, CTDs for outcome. PBC, primary biliary cholangitis; SLE, systemic lupus erythematosus; RA, rheumatoid arthritis; SS, Sjögren’s syndrome; SSc, systemic sclerosis. SNP, single-nucleotide polymorphism; OR, odds ratio; CI, confidence interval. IVW, inverse-variance weighted; IVW(mre), inverse-variance weighted(multiplicative random effects).</p

Causal effects of CTDs on the risk of PBC assessed by inverse Mendelian randomization method.

CTDs for exposure, PBC for outcome. PBC, primary biliary cholangitis; SLE, systemic lupus erythematosus; RA, rheumatoid arthritis; SS, Sjögren’s syndrome; SSc, systemic sclerosis. SNP, single-nucleotide polymorphism; OR, odds ratio; CI, confidence interval. IVW, inverse-variance weighted; IVW(mre), inverse-variance weighted(multiplicative random effects).</p

Genome-wide association study (GWAS) datasets used in the study.

Genome-wide association study (GWAS) datasets used in the study.</p

S3 File -

BackgroundAn association between primary biliary cholangitis (PBC) and connective tissue diseases (CTDs) [rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjögren’s syndrome (SS), systemic sclerosis (SSc)] has been found in observational studies. However, the direction causality is unclear. The aim of this study was to assess the causality between PBC and CTDs and to promote early screening, pre-emptive therapy, and accurate stratification.MethodsA two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between PBC [Genome-Wide Association Study (GWAS) meta-analysis, 8021 cases/16498 controls], and SLE (GWAS meta-analysis, 8021 cases/16489 controls), RA(FinnGen, 6236 cases/14727 controls), SS(FinnGen, 2495 cases/365533 controls), SSc (FinnGen, 302 cases/213145 controls). Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by four sensitivity analyses to assess the robustness of the results.ResultsThe IVW revealed that genetically predicted PBC increased the risk of SLE [odd’s ratio (OR) = 1.43, 95% confidence interval (CI) 1.30–1.58, P ConclusionsOur study provided new genetic evidence for a causal relationship between PBC and CTDs. PBC increased the risk of SLE, RA, and SS. Our findings highlighted the importance of active screening and intervention for CTDs in patients with PBC.</div

S1 File -

BackgroundAn association between primary biliary cholangitis (PBC) and connective tissue diseases (CTDs) [rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjögren’s syndrome (SS), systemic sclerosis (SSc)] has been found in observational studies. However, the direction causality is unclear. The aim of this study was to assess the causality between PBC and CTDs and to promote early screening, pre-emptive therapy, and accurate stratification.MethodsA two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between PBC [Genome-Wide Association Study (GWAS) meta-analysis, 8021 cases/16498 controls], and SLE (GWAS meta-analysis, 8021 cases/16489 controls), RA(FinnGen, 6236 cases/14727 controls), SS(FinnGen, 2495 cases/365533 controls), SSc (FinnGen, 302 cases/213145 controls). Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by four sensitivity analyses to assess the robustness of the results.ResultsThe IVW revealed that genetically predicted PBC increased the risk of SLE [odd’s ratio (OR) = 1.43, 95% confidence interval (CI) 1.30–1.58, P ConclusionsOur study provided new genetic evidence for a causal relationship between PBC and CTDs. PBC increased the risk of SLE, RA, and SS. Our findings highlighted the importance of active screening and intervention for CTDs in patients with PBC.</div

Diagram of the two-sample Mendelian randomization (MR) study for the association between PBC and CTDs.

PBC, primary biliary cholangitis; SLE, systemic lupus erythematosus; RA, rheumatoid arthritis; SS, Sjögren’s syndrome; SSc, systemic sclerosis.</p

Table_5_Identification of NETs-related biomarkers and molecular clusters in systemic lupus erythematosus.xls

Neutrophil extracellular traps (NETs) is an important process involved in the pathogenesis of systemic lupus erythematosus (SLE), but the potential mechanisms of NETs contributing to SLE at the genetic level have not been clearly investigated. This investigation aimed to explore the molecular characteristics of NETs-related genes (NRGs) in SLE based on bioinformatics analysis, and identify associated reliable biomarkers and molecular clusters. Dataset GSE45291 was acquired from the Gene Expression Omnibus repository and used as a training set for subsequent analysis. A total of 1006 differentially expressed genes (DEGs) were obtained, most of which were associated with multiple viral infections. The interaction of DEGs with NRGs revealed 8 differentially expressed NRGs (DE-NRGs). The correlation and protein-protein interaction analyses of these DE-NRGs were performed. Among them, HMGB1, ITGB2, and CREB5 were selected as hub genes by random forest, support vector machine, and least absolute shrinkage and selection operator algorithms. The significant diagnostic value for SLE was confirmed in the training set and three validation sets (GSE81622, GSE61635, and GSE122459). Additionally, three NETs-related sub-clusters were identified based on the hub genes’ expression profiles analyzed by unsupervised consensus cluster assessment. Functional enrichment was performed among the three NETs subgroups, and the data revealed that cluster 1 highly expressed DEGs were prevalent in innate immune response pathways while that of cluster 3 were enriched in adaptive immune response pathways. Moreover, immune infiltration analysis also revealed that innate immune cells were markedly infiltrated in cluster 1 while the adaptive immune cells were upregulated in cluster 3. As per our knowledge, this investigation is the first to explore the molecular characteristics of NRGs in SLE, identify three potential biomarkers (HMGB1, ITGB2, and CREB5), and three distinct clusters based on these hub biomarkers.</p