Single-cell transcriptomic analysis of hematopoietic progenitor cells from patients with systemic lupus erythematosus reveals interferon-inducible reprogramming in early progenitors.

Introduction: Immune cells that contribute to the pathogenesis of systemic lupus erythematosus (SLE) derive from adult hematopoietic stem and progenitor cells (HSPCs) within the bone marrow (BM). For this reason, we reasoned that fundamental abnormalities in SLE can be traced to a BM-derived HSPC inflammatory signature. Methods: BM samples from four SLE patients, six healthy controls, and two umbilical cord blood (CB) samples were used. CD34+ cells were isolated from BM and CB samples, and single-cell RNA-sequencing was performed. Results: A total of 426 cells and 24,473 genes were used in the analysis. Clustering analysis resulted in seven distinct clusters of cell types. Mutually exclusive markers, which were characteristic of each cell type, were identified. We identified three HSPC subpopulations, one of which consisted of proliferating cells (MKI67 expressing cells), one T-like, one B-like, and two myeloid-like progenitor subpopulations. Differential expression analysis revealed i) cell cycle-associated signatures, in healthy BM of HSPC clusters 3 and 4 when compared with CB, and ii) interferon (IFN) signatures in SLE BM of HSPC clusters 3 and 4 and myeloid-like progenitor cluster 5 when compared with healthy controls. The IFN signature in SLE appeared to be deregulated following TF regulatory network analysis and differential alternative splicing analysis between SLE and healthy controls in HSPC subpopulations. Discussion: This study revealed both quantitative-as evidenced by decreased numbers of non-proliferating early progenitors-and qualitative differences-characterized by an IFN signature in SLE, which is known to drive loss of function and depletion of HSPCs. Chronic IFN exposure affects early hematopoietic progenitors in SLE, which may account for the immune aberrancies and the cytopenias in SLE.

Disentangling the riddle of systemic lupus erythematosus with antiphospholipid syndrome: blood transcriptome analysis reveals a less-pronounced IFN-signature and distinct molecular profiles in venous versus arterial events.

INTRODUCTION: Systemic lupus erythematosus with antiphospholipid syndrome (SLE-APS) represents a challenging SLE endotype whose molecular basis remains unknown. METHODS: We analysed whole-blood RNA-sequencing data from 299 patients with SLE (108 SLE-antiphospholipid antibodies (aPL)-positive, including 67 SLE-APS; 191 SLE-aPL-negative) and 72 matched healthy controls (HC). Pathway enrichment analysis, unsupervised weighted gene coexpression network analysis and machine learning were applied to distinguish disease endotypes. RESULTS: Patients with SLE-APS demonstrated upregulated type I and II interferon (IFN) pathways compared with HC. Using a 100-gene random forests model, we achieved a cross-validated accuracy of 75.6% in distinguishing these two states. Additionally, the comparison between SLE-APS and SLE-aPL-negative revealed 227 differentially expressed genes, indicating downregulation of IFN-α and IFN-γ signatures, coupled with dysregulation of the complement cascade, B-cell activation and neutrophil degranulation. Unsupervised analysis of SLE transcriptome identified 21 gene modules, with SLE-APS strongly linked to upregulation of the 'neutrophilic/myeloid' module. Within SLE-APS, venous thromboses positively correlated with 'neutrophilic/myeloid' and 'B cell' modules, while arterial thromboses were associated with dysregulation of 'DNA damage response (DDR)' and 'metabolism' modules. Anticardiolipin and anti-ß2GPI positivity-irrespective of APS status-were associated with the 'neutrophilic/myeloid' and 'protein-binding' module, respectively. CONCLUSIONS: There is a hierarchical upregulation and-likely-dependence on IFN in SLE with the highest IFN signature observed in SLE-aPL-negative patients. Venous thrombotic events are associated with neutrophils and B cells while arterial events with DDR and impaired metabolism. This may account for their differential requirements for anticoagulation and provide rationale for the potential use of mTOR inhibitors such as sirolimus and the direct fIIa inhibitor dabigatran in SLE-APS.

A network-based approach reveals long non-coding RNAs associated with disease activity in lupus nephritis: key pathways for flare and potential biomarkers to be used as liquid biopsies.

Objective: A blood-based biomarker is needed to assess lupus nephritis (LN) disease activity, minimizing the need for invasive kidney biopsies. Long non-coding RNAs (lncRNAs) are known to regulate gene expression, appear to be stable in human plasma, and can serve as non-invasive biomarkers. Methods: Transcriptomic data of whole blood samples from 74 LN patients and 20 healthy subjects (HC) were analyzed to identify differentially expressed (DE) lncRNAs associated with quiescent disease and flares. Weighted gene co-expression network analysis (WGCNA) was performed to uncover lncRNAs with a central role (hub lncRNAs) in regulating key biological processes that drive LN disease activity. The association of hub lncRNAs with disease activity was validated using RT-qPCR on an independent cohort of 15 LN patients and 9 HC. cis- and trans-targets of validated lncRNAs were explored in silico to examine potential mechanisms of their action. Results: There were 444 DE lncRNAs associated with quiescent disease and 6 DE lncRNAs associated with flares (FDR <0.05). WGCNA highlighted IFN signaling and B-cell activity/adaptive immunity as the most significant processes contributing to nephritis activity. Four disease-activity-associated lncRNAs, namely, NRIR, KLHDC7B-DT, MIR600HG, and FAM30A, were detected as hub genes and validated in an independent cohort. NRIR and KLHDC7B-DT emerged as potential key regulators of IFN-mediated processes. Network analysis suggests that FAM30A and MIR600HG are likely to play a central role in the regulation of B-cells in LN through cis-regulation effects and a competing endogenous RNA mechanism affecting immunoglobulin gene expression and the IFN-λ pathway. Conclusions: The expression of lncRNAs NRIR, KLHDC7B-DT, FAM30A, and MIR600HG were associated with disease activity and could be further explored as blood-based biomarkers and potential liquid biopsy on LN.