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Fan et al.demonstrated, in real-world settings, achieving early lupus low disease activity state (LLDAS) in systemic lupus erythematosus (SLE) patients treated with telitacicept or belimumab is feasible, with predictors including higher baseline lymphocyte counts, higher serum albumin levels, and telitacicept use, while hematological involvement is associated with a lower likelihood of early LLDAS achievement; these findings highlight the importance of these factors in identifying patients who are likely to benefit from treatment. L’Estrange-Stranieri et al.reviewed the phosphorylation and protein-binding targets of Lyn, a Src family protein tyrosine kinase, plays a critical role in SLE by influencing B lymphocyte and myeloid cell signaling; research over the past 30 years has revealed that Lyn’s function is affected by both gain-of-function mutations and altered signaling pathways, leading to severe autoinflammation, with studies showing mixed results that may reflect disease heterogeneity and suggest Lyn’s potential role in patient stratification; this review covers Lyn’s phosphorylation and protein-binding targets, its structural domains involved in function, and recent updates on Lyn’s role in SLE. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ovarian cancer is the most common cause of death from gynecological cancer. Understanding the biology of this disease, particularly how tumor-associated lymphocytes and fibroblasts contribute to the progression and metastasis of the tumor, has been impeded by the lack of a suitable tumor xenograft model. We report a simple and reproducible system in which the tumor and tumor stroma are successfully engrafted into NOD-scid IL2Rγ(null) (NSG) mice. This is achieved by injecting tumor cell aggregates derived from fresh ovarian tumor biopsy tissues (including tumor cells, and tumor-associated lymphocytes and fibroblasts) i.p. into NSG mice. Tumor progression in these mice closely parallels many of the events that are observed in ovarian cancer patients. Tumors establish in the omentum, ovaries, liver, spleen, uterus, and pancreas. Tumor growth is initially very slow and progressive within the peritoneal cavity with an ultimate development of tumor ascites, spontaneous metastasis to the lung, increasing serum and ascites levels of CA125, and the retention of tumor-associated human fibroblasts and lymphocytes that remain functional and responsive to cytokines for prolonged periods. With this model one will be able to determine how fibroblasts and lymphocytes within the tumor microenvironment may contribute to tumor growth and metastasis, and will make it possible to evaluate the efficacy of therapies that are designed to target these cells in the tumor stroma.

While durable antibody responses from long-lived plasma cell (LLPC) populations are important for protection against pathogens, LLPC may be harmful if they produce antibodies against self-proteins or self-nuclear antigens as occurs in autoimmune diseases such as systemic lupus erythematosus (SLE). Thus, the elimination of autoreactive LLPC may improve the treatment of antibody-driven autoimmune diseases. However, LLPC remain a challenging therapeutic target. Here, we compare the matched bone marrow (BM) and peripheral blood (PBL) plasma cell (PC) compartments of SLE and healthy donors (HD). We show a similar distribution of CD138- and CD138+ PC, including putative LLPC (CD19- CD138+ CD38+), between SLE and HD BM. For both SLE and HD, CD138+ PC are at a higher frequency in BM than PBL. Expression of Ki-67 associates with the PBL compartment where it is found on all PC subsets regardless of CD19 or CD138 expression. Transcriptomic analysis identifies an interferon (IFN) gene signature in transitional B cells in the SLE BM, but surprisingly also in the BM PC derived from SLE. BM PC and B cells phosphorylate STAT1 in response to type I IFN stimulation in vitro , but with decreased fold change compared to those from the PBL. While BM PC bind type I IFN receptor-blocking antibody anifrolumab, it is to a lesser degree than circulating B cells. Anti-nuclear autoantibodies (ANA) are found in the BM supernatant and PBL serum of SLE patients. Both SLE and HD BM-derived PC have increased survival compared to their PBL counterparts when treated with verdinexor. In summary, these findings show evidence of IFN activation in BM PC from SLE.

Background Leveraging the Accelerating Medicines Partnership (AMP) Lupus Nephritis (LN) dataset, we evaluated longitudinal patterns, rates, and predictors of response to standard-of-care therapy in patients with lupus nephritis. Methods Patients from US academic medical centers with class III, IV, and/or V LN and a baseline urine protein/creatinine (UPCR) ratio ≥ 1.0 ( n  = 180) were eligible for this analysis. Complete response (CR) required the following: (1) UPCR < 0.5; (2) normal serum creatinine (≤ 1.3 mg/dL) or, if abnormal, ≤ 125% of baseline; and (3) prednisone ≤ 10 mg/day. Partial response (PR) required the following: (1) > 50% reduction in UPCR; (2) normal serum creatinine or, if abnormal, ≤ 125% of baseline; and (3) prednisone dose ≤ 15 mg/day. Results Response rates to the standard of care at week 52 were CR = 22.2%; PR = 21.7%; non-responder (NR) = 41.7%, and not determined (ND) = 14.4%. Only 8/180 (4.4%) patients had a week 12 CR sustained through week 52. Eighteen (10%) patients attained a week 12 PR or CR and sustained their responses through week 52 and 47 (26.1%) patients achieved sustained PR or CR at weeks 26 and 52. Week 52 CR or PR attainment was associated with baseline UPCR > 3 (OR adj  = 3.71 [95%CI = 1.34–10.24]; p  = 0.012), > 25% decrease in UPCR from baseline to week 12 (OR adj  = 2.61 [95%CI = 1.07–6.41]; p  = 0.036), lower chronicity index (OR adj = 1.33 per unit decrease [95%CI = 1.10–1.62]; p  = 0.003), and positive anti-dsDNA antibody (OR adj  = 2.61 [95%CI = 0.93–7.33]; p  = 0.069). Conclusions CR and PR rates at week 52 were consistent with the standard-of-care response rates observed in prospective registrational LN trials. Low sustained response rates underscore the need for more efficacious therapies and highlight how critically important it is to understand the molecular pathways associated with response and non-response.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction 1 . There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity 1 , 2 . Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments. Single-cell transcriptomic and proteomic data from synovial tissue from individuals with rheumatoid arthritis classify patients into groups based on abundance of cell states that can provide insights into pathology and predict individual treatment responses.

Systemic lupus erythematosus (SLE) is prototypical autoimmune disease driven by pathological T cell–B cell interactions 1 , 2 . Expansion of T follicular helper (T FH ) and T peripheral helper (T PH ) cells, two T cell populations that provide help to B cells, is a prominent feature of SLE 3 , 4 . Human T FH and T PH cells characteristically produce high levels of the B cell chemoattractant CXCL13 (refs.  5 , 6 ), yet regulation of T cell CXCL13 production and the relationship between CXCL13 + T cells and other T cell states remains unclear. Here, we identify an imbalance in CD4 + T cell phenotypes in patients with SLE, with expansion of PD-1 + /ICOS + CXCL13 + T cells and reduction of CD96 hi IL-22 + T cells. Using CRISPR screens, we identify the aryl hydrocarbon receptor (AHR) as a potent negative regulator of CXCL13 production by human CD4 + T cells. Transcriptomic, epigenetic and functional studies demonstrate that AHR coordinates with AP-1 family member JUN to prevent CXCL13 + T PH /T FH cell differentiation and promote an IL-22 + phenotype. Type I interferon, a pathogenic driver of SLE 7 , opposes AHR and JUN to promote T cell production of CXCL13. These results place CXCL13 + T PH /T FH cells on a polarization axis opposite from T helper 22 (T H 22) cells and reveal AHR, JUN and interferon as key regulators of these divergent T cell states. Insufficient AHR activation has been suggested in SLE, and augmenting AHR activation therapeutically may prevent CXCL13 + T PH /T FH differentiation and the subsequent recruitment of B cells and formation of lymphoid aggregates in inflamed tissues.

Rheumatoid arthritis (RA) is an autoimmune disease involving antigen-specific T and B cells. Here, we perform single-cell RNA and repertoire sequencing on paired synovial tissue and blood samples from 12 seropositive RA patients. We identify clonally expanded CD4 + T cells, including CCL5+ cells and T peripheral helper (Tph) cells, which show a prominent transcriptomic signature of recent activation and effector function. CD8 + T cells show higher oligoclonality than CD4 + T cells, with the largest synovial clones enriched in GZMK+ cells. CD8 + T cells with possibly virus-reactive TCRs are distributed across transcriptomic clusters. In the B cell compartment, NR4A1+ activated B cells, and plasma cells are enriched in the synovium and demonstrate substantial clonal expansion. We identify synovial plasma cells that share BCRs with synovial ABC, memory, and activated B cells. Receptor-ligand analysis predicted IFNG and TNFRSF members as mediators of synovial Tph-B cell interactions. Together, these results reveal clonal relationships between functionally distinct lymphocyte populations that infiltrate the synovium of patients with RA. Activated B cells and T cells accumulate within joints of patients with rheumatoid arthritis. Here, the authors use single-cell transcriptome and repertoire profiling to identify clonally expanded synovial B cells and T cells and define their phenotypes and predicted cell-cell interactions.

Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer–gene maps from disease-relevant tissues. Building enhancer–gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer–gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer–gene maps, essential for defining noncoding variant function. SCENT is a nonparametric method that models association between chromatin accessibility and gene expression in single-cell multimodal datasets, enabling construction of cell-type-specific enhancer–gene maps to aid mapping of candidate causal variants and genes for common diseases.

Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identify 24 chromatin classes and predict their associated transcription factors, including a CD8  +  GZMK + class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating with an RA tissue transcriptional atlas, we propose that these chromatin classes represent ‘superstates’ corresponding to multiple transcriptional cell states. Finally, we demonstrate the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance, as well as the nomination of classes mediating the effects of putatively causal RA genetic variants. The epigenetic changes underlying the heterogeneity of RA disease presentation have been the subject of intense scrutiny. In this study, the authors use multiple single-cell sequencing datasets to define ‘chromatin superstates’ in patients with RA, which associate with distinct transcription factors and disease phenotypes.

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis- eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses. scHLApers is an analysis pipeline that quantifies single-cell expression of HLA genes using a personalized genomic reference. Mapping of HLA expression quantitative trait loci at single-cell resolution identifies dynamic effects across cell states.