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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.

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.

Granzymes are a family of serine proteases that are mainly expressed by CD8 + T cells, natural killer cells and innate-like lymphocytes 1 . Although their primary function is thought to be the induction of cell death in virally infected cells and tumours, accumulating evidence indicates that some granzymes can elicit inflammation by acting on extracellular substrates 1 . We previously found that most tissue CD8 + T cells in rheumatoid arthritis synovium, and in inflamed organs for some other diseases, express granzyme K (GZMK) 2 , a tryptase-like protease with poorly defined function. Here, we show that GZMK can activate the complement cascade by cleaving the C2 and C4 proteins. The nascent C4b and C2b fragments form a C3 convertase that cleaves C3, enabling the assembly of a C5 convertase that cleaves C5. The resulting convertases generate all the effector molecules of the complement cascade: the anaphylatoxins C3a and C5a, the opsonins C4b and C3b, and the membrane attack complex. In rheumatoid arthritis synovium, GZMK is enriched in regions with abundant complement activation, and fibroblasts are the main producers of complement proteins that serve as substrates for GZMK-mediated complement activation. Furthermore, Gzmk -deficient mice are significantly protected from inflammatory disease, exhibiting reduced arthritis and dermatitis, with concomitant decreases in complement activation. Our findings describe the discovery of a previously unidentified mechanism of complement activation that is driven entirely by lymphocyte-derived GZMK. Given the widespread abundance of GZMK -expressing T cells in tissues in chronic inflammatory diseases, GZMK-mediated complement activation is likely to be an important contributor to tissue inflammation in multiple disease contexts. A study finds that a protease called granzyme K can activate the entire complement cascade, explaining how it can drive destructive inflammation in inflammatory diseases such as rheumatoid arthritis.

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.

Rheumatoid arthritis (RA) is a prototypical autoimmune disease that causes destructive tissue inflammation in joints and elsewhere. Clinical challenges in RA include the empirical selection of drugs to treat patients, inadequate responders with incomplete disease remission, and lack of a cure. We profiled the full spectrum of cells in inflamed synovium from patients with RA with the goal of deconstructing the cell states and pathways characterizing pathogenic heterogeneity in RA. Our multicenter consortium effort used multi-modal CITE-seq, RNA-seq, and histology of synovial tissue from 79 donors to build a >314,000 single-cell RA synovial cell atlas with 77 cell states from T, B/plasma, natural killer, myeloid, stromal, and endothelial cells. We stratified tissue samples into six distinct cell type abundance phenotypes (CTAPs) individually enriched for specific cell states. These CTAPs demonstrate the striking diversity of RA synovial inflammation, ranging from marked enrichment of T and B cells (CTAP-TB) to a congregation of specific myeloid, fibroblast, and endothelial cells largely lacking lymphocytes (CTAP-EFM). Disease-relevant cytokines, histology, and serology metrics are associated with certain CTAPs. This comprehensive RA synovial atlas and molecular, tissue-based CTAP stratification reveal new insights into RA pathology and heterogeneity, which could lead to novel targeted-treatment approaches in RA. Competing Interest Statement A.H.J. reports research support from Amgen, outside the submitted work. K.W. is a consultant for Mestag Therapeutics and Gilead Sciences and reports grant support from Gilead Sciences. S.M.G. reports research support from Novartis and is a consultant for UCB, outside the submitted work. V.M.H. is a co-founder of Q32 Bio and has previously received sponsored research from Janssen and been a consultant for Celgene and BMS, outside the submitted work. A.F. reports personal fees from Abbvie, Roche, and Janssen and grant support from Roche, UCB, Nascient, Mestag, GlaxoSmithKline, and Janssen, outside the submitted work. D.A.R. reports personal fees from Pfizer, Janssen, Merck, Scipher Medicine, GlaxoSmithKline, and Bristol-Myers Squibb and grant support from Janssen and Bristol-Myers Squibb, outside the submitted work. In addition, D.A.R. is a co-inventor on a patent submitted on T peripheral helper cells. M.B.B. is a founder for Mestag Therapeutics and a consultant for GlaxoSmithKline, 4FO Ventures, and Scailyte AG. S.R. is a founder for Mestag Therapeutics, a scientific advisor for Janssen and Pfizer, and a consultant for Gilead and Rheos Medicines.

There are growing concerns about the climate impacts of absorbing organic carbon (also known as brown carbon, BrC) in the environment, yet its chemical composition and association with the light absorption capabilities remain poorly understood. This study characterized water-soluble and water-insoluble organic carbon (WSOC and WIOC) from residential solid fuel combustion at the molecular level and evaluated their quantitative relationship with mass absorption efficiency (MAE). The MAE values at λ = 365 nm from biomass burning were significantly higher than those from coal combustion (p < 0.05). Thousands of peaks were identified in the m/z range of 150–800, with the most intense ion peaks occurring between m/z 200–500 for WSOC and m/z 600–800 for WIOC, respectively. The CHO group predominated in the WSOC extract from biomass burning emissions, while sulfur-containing compounds (SOCs) including CHOS and CHONS were more intense in the WIOC extract, particularly from coal emissions. Emissions of the CHON group were positively correlated with the fuel nitrogen content (r = 0.936; p < 0.05), explaining their higher abundance in coal emissions compared to biomass. The SOC emissions were more predominant during flaming phases, as indicated by a positive correlation with modified combustion efficiency (MCE) (r = 0.750; p < 0.05). The unique formulas of coal combustion aerosols were in the lower H/C and O/C regions, with higher unsaturated compounds in the van Krevelen (VK) diagram. In the WIOC extract, coal combustion emissions contained significantly higher fractions of condensed aromatics (32 %–59 %) compared to only 4.3 %–9.7 % in biomass burning emissions. In contrast, the CHOS group in biomass burning emissions was characterized by larger condensed aromatic compound fractions than those in coal combustion. Moreover, the CHOS aromatic compound fractions were positively correlated with MAE values in both WSOC (r = 0.714; p < 0.05) and WIOC extracts (r = 0.929; p < 0.001), suggesting that these compounds significantly contributed to MAE variabilities across different fuels.

Background Few studies have investigated the depth of intraoperative analgesia with non-opioid anesthesia. This study evaluated whether opioid-free anesthesia can provide an effective analgesia-antinociception balance monitored by the / pain threshold index in laparoscopic radical colectomy. Methods We enrolled 102 patients undergoing laparoscopic radical colectomy with general anesthesia. Participants were randomly allocated into two groups to receive opioid-free anesthesia (group OFA) with dexmedetomidine (loading dose with 0.6 μg·kg −1 for 10 min and then 0.5 μg·kg −1 ·h −1 continuous infusion) and sevoflurane plus bilateral paravertebral blockade (0.2 μg·kg −1 dexmedetomidine and 0.5% ropivacaine 15 ml per side) or opioid-based anesthesia (group OA) with remifentanil, sevoflurane, and bilateral paravertebral blockade (0.5% ropivacaine 15 ml per side). The primary outcome variable was pain intensity during the operation, as assessed by the pain threshold index with the multifunction combination monitor HXD- I. Results were analyzed using repeated measures analysis of variance and Student’s t -test. The secondary outcomes were wavelet index, lactic levels, and blood glucose concentration during the operation. The visual analog scale (VAS), rescue analgesic consumption, and side-effects of opioids after surgery were further assessed. Results One hundred and one patients were included in the analysis. Analysis revealed that the intraoperative pain threshold index readings were not significantly different between the groups from incision to the end of the operation ( P  = 0.06). Furthermore, similar changes in the brain wavelet index readings were observed in the OFA and OA groups. There was no statistical difference in VAS scores between the groups ( P  > 0.05); however, non-opioid anesthesia did reduce the rescue analgesic consumption after operation ( P  < 0.05). In the OFA group, the blood glucose levels increased by 20% compared to baseline and were significantly higher than those in the OA group ( P  < 0.001). The incidences of postoperative nausea and vomiting, urine retention, intestinal paralysis and pruritus were not significantly different from those in the OA group ( P  > 0.05). Conclusions This study suggests that compared to the opioid anesthesia regimen, our opioid-free anesthesia regimen achieved an equally effective intraoperative pain threshold index in laparoscopic radical colectomy. The incidence of opioid-related adverse reactions was not different between regimens, and intraoperative blood glucose levels were higher with opioid-free anesthesia. Trial registration ChiCTR1900021223, 02/02/2019, Title: \" Opioid-free anesthesia in laparoscopic surgery: a randomized controlled trial \". Website: hppts:// www.chictr.ogr.cn