Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis.

Lupus nephritis (LN) is a frequent manifestation of systemic lupus erythematosus, and fewer than half of patients achieve complete renal response with standard immunosuppressants. Identifying non-invasive, blood-based pathologic immune alterations associated with renal injury could aid therapeutic decisions. Here, we used mass cytometry immunophenotyping of peripheral blood mononuclear cells in 145 patients with biopsy-proven LN and 40 healthy controls to evaluate the heterogeneity of immune activation in patients with LN and to identify correlates of renal parameters and treatment response. Unbiased analysis identified 3 immunologically distinct groups of patients with LN that were associated with different patterns of histopathology, renal cell infiltrates, urine proteomic profiles, and treatment response at one year. Patients with enriched circulating granzyme B+ T cells at baseline showed more severe disease and increased numbers of activated CD8 T cells in the kidney, yet they had the highest likelihood of treatment response. A second group characterized primarily by a high type I interferon signature had a lower likelihood of response to therapy, while a third group appeared immunologically inactive by immunophenotyping at enrollment but with chronic renal injuries. Main immune profiles could be distilled down to 5 simple cytometric parameters that recapitulate several of the associations, highlighting the potential for blood immune profiling to translate to clinically useful non-invasive metrics to assess immune-mediated disease in LN.

Single-cell computational machine learning approaches to immune-mediated inflammatory disease: New tools uncover novel fibroblast and macrophage interactions driving pathogenesis.

Recent advances in single-cell sequencing technologies call for greater computational scalability and sensitivity to analytically decompose diseased tissues and expose meaningful biological relevance in individual cells with high resolution. And while fibroblasts, one of the most abundant cell types in tissues, were long thought to display relative homogeneity, recent analytical and technical advances in single-cell sequencing have exposed wide variation and sub-phenotypes of fibroblasts of potential and apparent clinical significance to inflammatory diseases. Alongside anticipated improvements in single cell spatial sequencing resolution, new computational biology techniques have formed the technical backbone when exploring fibroblast heterogeneity. More robust models are required, however. This review will summarize the key advancements in computational techniques that are being deployed to categorize fibroblast heterogeneity and their interaction with the myeloid compartments in specific biological and clinical contexts. First, typical machine-learning-aided methods such as dimensionality reduction, clustering, and trajectory inference, have exposed the role of fibroblast subpopulations in inflammatory disease pathologies. Second, these techniques, coupled with single-cell predicted computational methods have raised novel interactomes between fibroblasts and macrophages of potential clinical significance to many immune-mediated inflammatory diseases such as rheumatoid arthritis, ulcerative colitis, lupus, systemic sclerosis, and others. Third, recently developed scalable integrative methods have the potential to map cross-cell-type spatial interactions at the single-cell level while cross-tissue analysis with these models reveals shared biological mechanisms between disease contexts. Finally, these advanced computational omics approaches have the potential to be leveraged toward therapeutic strategies that target fibroblast-macrophage interactions in a wide variety of inflammatory diseases.

Association of differentially expressed genes and autoantibody type in patients with systemic sclerosis.

OBJECTIVES: The aims of this study were to investigate the relationship between the type of autoantibody and gene expression profile in skin lesions from patients with SSc, and to identify specific dysregulated pathways in SSc patients compared with healthy controls. METHODS: Sixty-one patients with SSc from the Genetics vs Environment in Scleroderma Outcome Study cohort and 36 healthy controls were included in this study. Differentially expressed genes were extracted and functional enrichment and pathway analysis were conducted. RESULTS: Compared with healthy controls, lists containing 2, 71, 10, 144 and 78 differentially expressed genes were created for patients without specific autoantibody, ACA, anti-U1 RNP antibody (RNP), anti-RNA polymerase III antibody (RNAP) and anti-topoisomerase I antibody (ATA), respectively. While part of the enriched pathways overlapped, distinct pathways were identified except in those patients lacking specific autoantibody. The distinct enriched pathways included 'keratinocyte differentiation' for ACA, 'nuclear factor κB signalling' and 'cellular response to TGF-ß stimulus' for RNAP, 'interferon α/ß signalling' for RNP, and 'cellular response to stress' for ATA. Cell type signature score analysis revealed that macrophages/monocytes, endothelial cells and fibroblasts were associated with ACA, RNAP, ATA and the severity of the SSc skin lesions. CONCLUSION: Pathogenic pathways were identified according to the type of autoantibody by leveraging gene expression data of patients and controls from a multicentre cohort. The current study may promote the search for new therapeutic targets for SSc.

Identification of novel genes associated with dysregulation of B cells in patients with primary Sjögren's syndrome.

BACKGROUND: The aim of this study was to identify the molecular mechanism of dysregulation of B cell subpopulations of primary Sjögren's syndrome (pSS) at the transcriptome level. METHODS: We enrolled patients with pSS (n = 6) and healthy controls (HCs) (n = 6) in the discovery cohort using microarray and pSS (n = 14) and HCs (n = 12) in the validation cohort using quantitative PCR (qPCR). Peripheral B cells acquired from these subjects were separated by cell sorting into four subsets: CD38-IgD+ (Bm1), CD38+IgD+ (naive B cells), CD38highIgD+ (pre-germinal centre B cells) and CD38±IgD- (memory B cells). We performed differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA). RESULTS: Expression of the long non-coding RNA LINC00487 was significantly upregulated in all B cell subsets, as was that of HLA and interferon (IFN) signature genes. Moreover, the normalized intensity value of LINC00487 significantly correlated with the disease activity score of all pSS B cell subsets. Studies of human B cell lines revealed that the expression of LINC00487 was strongly induced by IFNα. WGCNA revealed six gene clusters associated with the B cell subpopulation of pSS. Further, SOX4 was identified as an inter-module hub gene. CONCLUSION: Our transcriptome analysis revealed key genes involved in the dysregulation of B cell subpopulations associated with pSS. TRIAL REGISTRATION: Not required.

Subtypes in eosinophilic granulomatosis with polyangiitis classified according to rheumatoid factor.

To investigate the relevance of RF in patients with EGPA, we reviewed consecutive patients who were newly diagnosed with EGPA from August 1998 to February 2019 in Keio University Hospital with RF titer at diagnosis available. We divided the patients according to the median level of RF titer of 75 IU/mL and compared clinical features between the two groups. Among 16 patients identified, 8 patients were in the RF high group and the other 8 patients were in the RF low group. All patients in the high RF group were negative for MPO-ANCA, whereas all in the low RF group was positive for MPO-ANCA with a mean titer of 103 IU/mL. The eosinophil count at diagnosis was significantly higher in the RF high group than the RF low group (20001/µL vs 5144/µL, p < 0.01). Gastrointestinal lesion was significantly more frequent in the RF high group, and parenchymal organ lesions, such as heart and renal organ involvement, were frequent in the RF low group. With principal component analysis, RF high and low groups were clearly divided by the combination of eosinophil count, MPO-ANCA titer, gastrointestinal lesions, musculoskeletal symptoms, and disease activity score. Those results suggest EGPA can be divided into two groups in association with RF.Key Points• Our study showed that patients with EGPA can be separated into two groups according to RF titer.• The two subtypes reflect different underlying pathogenesis in EGPA, and the optimal treatment for them may be different.

Inflammatory tenosynovitis and enthesitis induced by immune checkpoint inhibitor treatment.

Reports about immune-related adverse events (IrAEs) induced by immune checkpoint inhibitors (ICIs) have been increasing. Although the importance of understanding joint involvement and myalgia as an IrAE has grown, little is known about its characteristics. The aim of this study was to investigate the incidence and clinical characteristics of articular IrAEs. We reviewed 133 patients who were treated with ICIs in our institution and referred to our rheumatologic. Among them, 2 (1.5%) developed arthritis during the use of anti-PD-1 inhibitor, and there was one patient with joint pain after anti-PD-L1 inhibitor who was referred to our department from another institution. No patients had antecedent inflammatory arthritis or any relevant medical history. All 3 patients were negative for anti-nuclear antibody, rheumatoid factor, and anti-cyclic citrullinated peptide antibody. The ultrasonography showed tenosynovitis and enthesitis in both small and large joints with no or insignificant synovitis. Joint pain improved gradually within 6 months with only NSAIDs in 2 patients, and disappeared quickly in the other patient 2 weeks after 20 mg/day of predonisolone. Our report suggested diverse phenotypes of joint involvement and highlighted the importance of accumulating such patients.