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Transcriptomic analysis of immune cells in a multi-ethnic cohort of systemic lupus erythematosus patients identifies ethnicity- and disease-specific expression signatures.

ABSTRACT: Systemic lupus erythematosus (SLE) is an autoimmune disease in which outcomes vary among different racial groups. We leverage cell-sorted RNA-seq data (CD14+ monocytes, B cells, CD4+ T cells, and NK cells) from 120 SLE patients (63 Asian and 57 White individuals) and apply a four-tier approach including unsupervised clustering, differential expression analyses, gene co-expression analyses, and machine learning to identify SLE subgroups within this multiethnic cohort. K-means clustering on each cell-type resulted in three clusters for CD4 and CD14, and two for B and NK cells. To understand the identified clusters, correlation analysis revealed significant positive associations between the clusters and clinical parameters including disease activity as well as ethnicity. We then explored differentially expressed genes between Asian and White groups for each cell-type. The shared differentially expressed genes across cells were involved in SLE or other autoimmune-related pathways. Co-expression analysis identified similarly regulated genes across samples and grouped these genes into modules. Finally, random forest classification of disease activity in the White and Asian cohorts showed the best classification in CD4+ T cells in White individuals. The results from these analyses will help stratify patients based on their gene expression signatures to enable SLE precision medicine.

SUBMITTER: Andreoletti G

PROVIDER: S-EPMC8060402 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Systemic lupus erythematosus (SLE) is a chronic autoimmune disease of unknown etiology, linked to alterations in both the innate and the adaptive immune system. Due to the heterogeneity of the clinical presentation, the diagnosis of SLE remains complicated and is often made years after the first symptoms manifest, delaying treatment, and worsening the prognosis. Several studies have shown that signaling lymphocytic activation molecule family (SLAMF) receptors are aberrantly expressed and dysfunctional in SLE immune cells, contributing to the altered cellular function observed in these patients. The aim of this study was to determine whether altered co-/expression of SLAMF receptors on peripheral blood mononuclear cells (PBMC) identifies SLE characteristic cell populations. To this end, single cell mass cytometry and bioinformatic analysis were exploited to compare SLE patients to healthy and autoimmune diseases controls. First, the expression of each SLAMF receptor on all PBMC populations was investigated. We observed that SLAMF1+ B cells (referred to as SLEB1) were increased in SLE compared to controls. Furthermore, the frequency of SLAMF4+ monocytes and SLAMF4+ NK were inversely correlated with disease activity, whereas the frequency SLAMF1+ CD4+ TDEM cells were directly correlated with disease activity. Consensus clustering analysis identified two cell clusters that presented significantly increased frequency in SLE compared to controls: switch memory B cells expressing SLAMF1, SLAMF3, SLAMF5, SLAMF6 (referred to as SLESMB) and circulating T follicular helper cells expressing the same SLAMF receptors (referred to as SLEcTFH). Finally, the robustness of the identified cell populations as biomarkers for SLE was evaluated through ROC curve analysis. The combined measurement of SLEcTFH and SLEB1 or SLESMB cells identified SLE patients in 90% of cases. In conclusion, this study identified an immune signature for SLE based on the expression of SLAMF receptors on PBMC, further highlighting the involvement of SLAMF receptors in the pathogenesis of SLE.

Project description:BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disorder which could lead to inflammation and fibrosis in various organs. Pulmonary fibrosis is a severe complication in patients with SLE. Nonetheless, SLE-derived pulmonary fibrosis has unknown pathogenesis. Of pulmonary fibrosis, Idiopathic pulmonary fibrosis (IPF) is a typicality and deadly form. Aiming to investigate the gene signatures and possible immune mechanisms in SLE-derived pulmonary fibrosis, we explored common characters between SLE and IPF from Gene Expression Omnibus (GEO) database.ResultsWe employed the weighted gene co-expression network analysis (WGCNA) to identify the shared genes. Two modules were significantly identified in both SLE and IPF, respectively. The overlapped 40 genes were selected out for further analysis. The GO enrichment analysis of shared genes between SLE and IPF was performed with ClueGO and indicated that p38MAPK cascade, a key inflammation response pathway, may be a common feature in both SLE and IPF. The validation datasets also illustrated this point. The enrichment analysis of common miRNAs was obtained from the Human microRNA Disease Database (HMDD) and the enrichment analysis with the DIANA tools also indicated that MAPK pathways' role in the pathogenesis of SLE and IPF. The target genes of these common miRNAs were identified by the TargetScan7.2 and a common miRNAs-mRNAs network was constructed with the overlapped genes in target and shared genes to show the regulated target of SLE-derived pulmonary fibrosis. The result of CIBERSORT showed decreased regulatory T cells (Tregs), naïve CD4+ T cells and rest mast cells but increased activated NK cells and activated mast cells in both SLE and IPF. The target genes of cyclophosphamide were also obtained from the Drug Repurposing Hub and had an interaction with the common gene PTGS2 predicted with protein-protein interaction (PPI) and molecular docking, indicating its potential treatment effect.ConclusionsThis study originally uncovered the MAPK pathway, and the infiltration of some immune-cell subsets might be pivotal factors for pulmonary fibrosis complication in SLE, which could be used as potentially therapeutic targets. The cyclophosphamide may treat SLE-derived pulmonary fibrosis through interaction with PTGS2, which could be activated by p38MAPK.

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Transcriptomic analysis of immune cells in a multi-ethnic cohort of systemic lupus erythematosus patients identifies ethnicity- and disease-specific expression signatures.

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