Neutrophils isolated from systemic lupus erythematosus patients exhibit a distinct functional phenotype.

Neutrophil dysregulation, particularly of a low-density subset, is associated with systemic lupus erythematosus (SLE); however, the exact role of normal-density neutrophils in SLE remains unknown. This study compares activation and functional phenotypes of neutrophils from SLE patients and healthy controls to determine potential contributions to SLE pathogenesis. Surface activation markers and release of neutrophil extracellular traps (NETs), granule proteins, and cytokines/chemokines were measured in resting and stimulated neutrophils from SLE patients (n=19) and healthy controls (n=10). Select miRNA and mRNA involved in neutrophil development and function were also measured. Resting SLE neutrophils exhibited fewer activation markers compared to control neutrophils, and activation markers were associated with different plasma cytokines/chemokines in SLE patients compared to healthy controls. However, activation markers increased similarly in SLE and control neutrophils following stimulation with a TLR7/8 agonist, neutrophil growth factors, and bacterial mimic. At the resting state, SLE neutrophils produced significantly more CXCL10 (IP-10), with trends toward other increased cytokines/chemokines. Following stimulation, SLE neutrophils produced fewer NETs and proinflammatory cytokines compared to control neutrophils but more MMP-8. In addition, SLE neutrophils expressed less miR130a, miR132, miR27a, and miR223. In conclusion, SLE neutrophils exhibit distinct functional responses compared to control neutrophils. These functional differences may result from differential gene expression via miRNAs. Furthermore, the differences in functional phenotype of SLE neutrophils suggest that they may contribute to SLE differently dependent on the inflammatory milieu.

Extrarenal symptoms associate with worse quality of life in patients enrolled in the AMP RA/SLE Lupus Nephritis Network.

OBJECTIVE: Lupus nephritis (LN) can occur as an isolated component of disease activity or be accompanied by diverse extrarenal manifestations. Whether isolated renal disease is sufficient to decrease health related quality of life (HRQOL) remains unknown. This study compared Patient-Reported Outcomes Measurement Information System 29-Item (PROMIS-29) scores in LN patients with isolated renal disease to those with extrarenal symptoms to evaluate the burden of LN on HRQOL and inform future LN clinical trials incorporating HRQOL outcomes. METHODS: A total of 181 LN patients consecutively enrolled in the multicentre multi-ethnic/racial Accelerating Medicines Partnership completed PROMIS-29 questionnaires at the time of a clinically indicated renal biopsy. Raw PROMIS-29 scores were converted to standardized T scores. RESULTS: Seventy-five (41%) patients had extrarenal disease (mean age 34, 85% female) and 106 (59%) had isolated renal (mean age 36, 82% female). Rash (45%), arthritis (40%) and alopecia (40%) were the most common extrarenal manifestations. Compared with isolated renal, patients with extrarenal disease reported significantly worse pain interference, ability to participate in social roles, physical function, and fatigue. Patients with extrarenal disease had PROMIS-29 scores that significantly differed from the general population by > 0.5 SD of the reference mean in pain interference, physical function, and fatigue. Arthritis was most strongly associated with worse scores in these three domains. CONCLUSION: Most patients had isolated renal disease and extrarenal manifestations associated with worse HRQOL. These data highlight the importance of comprehensive disease management strategies that address both renal and extrarenal manifestations to improve overall patient outcomes.

Longitudinal patterns and predictors of response to standard-of-care therapy in lupus nephritis: data from the Accelerating Medicines Partnership Lupus Network.

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 (ORadj = 3.71 [95%CI = 1.34-10.24]; p = 0.012), > 25% decrease in UPCR from baseline to week 12 (ORadj = 2.61 [95%CI = 1.07-6.41]; p = 0.036), lower chronicity index (ORadj = 1.33 per unit decrease [95%CI = 1.10-1.62]; p = 0.003), and positive anti-dsDNA antibody (ORadj = 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.

Mycophenolate mofetil withdrawal in patients with systemic lupus erythematosus: a multicentre, open-label, randomised controlled trial.

BACKGROUND: Mycophenolate mofetil is an immunosuppressant commonly used to treat systemic lupus erythematosus (SLE) and lupus nephritis. It is a known teratogen associated with significant toxicities, including an increased risk of infections and malignancies. Mycophenolate mofetil withdrawal is desirable once disease quiescence is reached, but the timing of when to do so and whether it provides a benefit has not been well-studied. We aimed to determine the effects of mycophenolate mofetil withdrawal on the risk of clinically significant disease reactivation in patients with quiescent SLE on long-term mycophenolate mofetil therapy. METHODS: This multicenter, open-label, randomised trial was conducted in 19 centres in the USA. Eligible patients were aged between 18 and 70 years old, met the American College of Rheumatology (ACR) 1997 SLE criteria, and had a clinical SLEDAI score of less than 4 at screening. Mycophenolate mofetil therapy was required to be stable or decreasing for 2 years or more if initiated for renal indications, or for 1 year or more for non-renal indications. Participants were randomly allocated in a 1:1 ratio to a withdrawal group, who tapered off mycophenolate mofetil over 12 weeks, or a maintenance group who maintained their baseline dose (1-3g per day) for 60 weeks. Adaptive random allocation ensured groups were balanced for study site, renal versus non-renal disease, and baseline mycophenolate mofetil dose (≥2 g per day vs <2 g per day). Clinically significant disease reactivation by week 60 following random allocation, requiring increased doses or new immunosuppressive therapy was the primary endpoint, in the modified intention-to-treat population (all randomly allocated participants who began study-provided mycophenolate mofetil). Non-inferiority was evaluated using an estimation-based approach. The trial was registered at ClinicalTrials.gov (NCT01946880) and is completed. FINDINGS: Between Nov 6, 2013, and April 27, 2018, 123 participants were screened, of whom 102 were randomly allocated to the maintenance group (n=50) or the withdrawal group (n=52). Of the 100 participants included in the modified intention-to-treat analysis (49 maintenance, 51 withdrawal), 84 (84%) were women, 16 (16%) were men, 40 (40%) were White, 41 (41%) were Black, and 76 (76%) had a history of lupus nephritis. The average age was 42 (SD 12·7). By week 60, nine (18%) of 51 participants in the withdrawal group had clinically significant disease reactivation, compared to five (10%) of 49 participants in the maintenance group. The risk of clinically significant disease reactivation was 11% (95% CI 5-24) in the maintenance group and 18% (10-32) in the withdrawal group. The estimated increase in the risk of clinically significant disease reactivation with mycophenolate mofetil withdrawal was 7% (one-sided upper 85% confidence limit 15%). Similar rates of adverse events were observed in the maintenance group (45 [90%] of 50 participants) and the withdrawal group (46 [88%] of 52 participants). Infections were more frequent in the mycophenolate mofetil maintenance group (32 [64%]) compared with the withdrawal group (24 [46%]). INTERPRETATIONS: Mycophenolate mofetil withdrawal is not significantly inferior to mycophenolate mofetil maintenance. Estimates for the rates of disease reactivation and increases in risk with withdrawal can assist clinicians in making informed decisions on withdrawing mycophenolate mofetil in patients with stable SLE. FUNDING: The National Institute of Allergy and Infectious Diseases and the National Institute of Arthritis and Musculoskeletal and Skin Diseases.

Imaging mass cytometry reveals tissue-specific cellular immune phenotypes in the mouse knee following ACL injury.

Objective: To develop an imaging mass cytometry method for identifying complex cell phenotypes, inter-cellular interactions, and population changes in the synovium and infrapatellar fat pad (IFP) of the mouse knee following a non-invasive compression injury. Design: Fifteen male C57BL/6 mice were fed a high-fat diet for 8 weeks prior to random assignment to sham, 0.88 â€‹mm, or 1.7 â€‹mm knee compression displacement at 24 weeks of age. 2-weeks after loading, limbs were prepared for histologic and imaging mass cytometry analysis, focusing on myeloid immune cell populations in the synovium and IFP. Results: 1.7 â€‹mm compression caused anterior cruciate ligament (ACL) rupture, development of post-traumatic osteoarthritis, and a 2- to 3-fold increase in cellularity of synovium and IFP tissues compared to sham or 0.88 â€‹mm compression. Imaging mass cytometry identified 11 myeloid cell subpopulations in synovium and 7 in IFP, of which approximately half were elevated 2 weeks after ACL injury in association with the vasculature. Notably, two monocyte/macrophage subpopulations and an MHC IIhi population were elevated 2-weeks post-injury in the synovium but not IFP. Vascular and immune cell interactions were particularly diverse in the synovium, incorporating 8 unique combinations of 5 myeloid cell populations, including a monocyte/macrophage population, an MHC IIhi population, and 3 different undefined F4/80+ myeloid populations. Conclusions: Developing an imaging mass cytometry method for the mouse enabled us to identify a diverse array of synovial and IFP vascular-associated myeloid cell subpopulations. These subpopulations were differentially elevated in synovial and IFP tissues 2-weeks post injury, providing new details on tissue-specific immune regulation.

A novel process for H&E, immunofluorescence, and imaging mass cytometry on a single slide with a concise analytics pipeline.

Imaging mass cytometry (IMC) is a powerful spatial technology that utilizes cytometry time of flight to acquire multiplexed image datasets with up to 40 markers, via metal-tagged antibodies. Recent advances in IMC have led to the inclusion of RNAScope probes and multiple new analysis pipelines have led to faster analyses and better results. However, IMC still suffers from lower resolution (1 µm2 pixels) and relatively small regions of interest (ROIs) (<2 mm2 ) compared to other, light-based microscope technologies. Capturing higher-resolution images on serial sections causes great difficulty when attempting to align cells and structures across serial sections, especially when observing smaller cell types and structures. Therefore, we demonstrate the combination of H&E and multiplex immunofluorescence imaging, for much higher resolution of the structural and cellular compartments found throughout the entire tissue section, with the high-dimensionality of IMC for specific ROIs on a single slide. Additionally, we demonstrate a simple and effective open-source cell segmentation and IMC analysis pipeline with previously published and freely available software.

Ancestry-based differences in the immune phenotype are associated with lupus activity.

Systemic lupus erythematosus (SLE) affects 1 in 537 Black women, which is >2-fold more than White women. Black patients develop the disease at a younger age, have more severe symptoms, and have a greater chance of early mortality. We used a multiomics approach to uncover ancestry-associated immune alterations in patients with SLE and healthy controls that may contribute biologically to disease disparities. Cell composition, signaling, epigenetics, and proteomics were evaluated by mass cytometry; droplet-based single-cell transcriptomics and proteomics; and bead-based multiplex soluble mediator levels in plasma. We observed altered whole blood frequencies and enhanced activity in CD8+ T cells, B cells, monocytes, and DCs in Black patients with more active disease. Epigenetic modifications in CD8+ T cells (H3K27ac) could distinguish disease activity level in Black patients and differentiate Black from White patient samples. TLR3/4/7/8/9-related gene expression was elevated in immune cells from Black patients with SLE, and TLR7/8/9 and IFN-α phospho-signaling and cytokine responses were heightened even in immune cells from healthy Black control patients compared with White individuals. TLR stimulation of healthy immune cells recapitulated the ancestry-associated SLE immunophenotypes. This multiomic resource defines ancestry-associated immune phenotypes that differ between Black and White patients with SLE, which may influence the course and severity of SLE and other diseases.

Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis.

Rheumatoid arthritis (RA) is a systemic autoimmune disease with currently no universally highly effective prevention strategies. Identifying pathogenic immune phenotypes in 'At-Risk' populations prior to clinical disease onset is crucial to establishing effective prevention strategies. Here, we applied mass cytometry to deeply characterize the immunophenotypes in blood from At-Risk individuals identified through the presence of serum antibodies to citrullinated protein antigens (ACPA) and/or first-degree relative (FDR) status (n=52), as compared to established RA (n=67), and healthy controls (n=48). We identified significant cell expansions in At-Risk individuals compared with controls, including CCR2+CD4+ T cells, T peripheral helper (Tph) cells, type 1 T helper cells, and CXCR5+CD8+ T cells. We also found that CD15+ classical monocytes were specifically expanded in ACPA-negative FDRs, and an activated PAX5 low naïve B cell population was expanded in ACPA-positive FDRs. Further, we developed an "RA immunophenotype score" classification method based on the degree of enrichment of cell states relevant to established RA patients. This score significantly distinguished At-Risk individuals from controls. In all, we systematically identified activated lymphocyte phenotypes in At-Risk individuals, along with immunophenotypic differences among both ACPA+ and ACPA-FDR At-Risk subpopulations. Our classification model provides a promising approach for understanding RA pathogenesis with the goal to further improve prevention strategies and identify novel therapeutic targets.

Autoantibodies identify primary Sjögren's syndrome in patients lacking serum IgG specific for Ro/SS-A and La/SS-B.

OBJECTIVE: Identify autoantibodies in anti-Ro/SS-A negative primary Sjögren's syndrome (SS). METHODS: This is a proof-of-concept, case-control study of SS, healthy (HC) and other disease (OD) controls. A discovery dataset of plasma samples (n=30 SS, n=15 HC) was tested on human proteome arrays containing 19 500 proteins. A validation dataset of plasma and stimulated parotid saliva from additional SS cases (n=46 anti-Ro+, n=50 anti-Ro-), HC (n=42) and OD (n=54) was tested on custom arrays containing 74 proteins. For each protein, the mean+3 SD of the HC value defined the positivity threshold. Differences from HC were determined by Fisher's exact test and random forest machine learning using 2/3 of the validation dataset for training and 1/3 for testing. Applicability of the results was explored in an independent rheumatology practice cohort (n=38 Ro+, n=36 Ro-, n=10 HC). Relationships among antigens were explored using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) interactome analysis. RESULTS: Ro+ SS parotid saliva contained autoantibodies binding to Ro60, Ro52, La/SS-B and muscarinic receptor 5. SS plasma contained 12 novel autoantibody specificities, 11 of which were detected in both the discovery and validation datasets. Binding to ≥1 of the novel antigens identified 54% of Ro- SS and 37% of Ro+ SS cases, with 100% specificity in both groups. Machine learning identified 30 novel specificities showing receiver operating characteristic area under the curve of 0.79 (95% CI 0.64 to 0.93) for identifying Ro- SS. Sera from Ro- cases of an independent cohort bound 17 of the non-canonical antigens. Antigenic targets in both Ro+ and Ro- SS were part of leukaemia cell, ubiquitin conjugation and antiviral defence pathways. CONCLUSION: We identified antigenic targets of the autoantibody response in SS that may be useful for identifying up to half of Ro seronegative SS cases.

Immune profiling in Puerto Rican injection drug users with and without HIV-1 infection.

Antiretroviral therapy has been effective in suppressing HIV viral load and enabling people living with HIV to experience longer, more conventional lives. However, as people living with HIV are living longer, they are developing aging-related diseases prematurely and are more susceptible to comorbidities that have been linked to chronic inflammation. Coincident with HIV infection and aging, drug abuse has also been independently associated with gut dysbiosis, microbial translocation, and inflammation. Here, we hypothesized that injection drug use would exacerbate HIV-induced immune activation and inflammation, thereby intensifying immune dysfunction. We recruited 50 individuals not using injection drugs (36/50 HIV+) and 47 people who inject drugs (PWID, 12/47 HIV+). All but 3 of the HIV+ subjects were on antiretroviral therapy. Plasma immune profiles were characterized by immunoproteomics, and cellular immunophenotypes were assessed using mass cytometry. The immune profiles of HIV+/PWID-, HIV-/PWID+, and HIV+/PWID+ were each significantly different from controls; however, few differences between these groups were detected, and only 3 inflammatory mediators and 2 immune cell populations demonstrated a combinatorial effect of injection drug use and HIV infection. In conclusion, a comprehensive analysis of inflammatory mediators and cell immunophenotypes revealed remarkably similar patterns of immune dysfunction in HIV-infected individuals and in people who inject drugs with and without HIV-1 infection.

Genetic load in incomplete lupus erythematosus.

OBJECTIVE: Patients with incomplete lupus erythematosus (ILE) have lupus features but insufficient criteria for SLE classification. Some patients with ILE transition to SLE, but most avoid major organ involvement. This study tested whether the milder disease course in ILE is influenced by reduced SLE risk allele genetic load. METHODS: We calculated the genetic load based on 99 SLE-associated risk alleles in European American patients with SLE (≥4 American College of Rheumatology (ACR) 1997 criteria, n=170), patients with ILE (3 ACR 1997 criteria, n=169), a subset of patients with ILE not meeting Systemic Lupus International Collaborating Clinics (SLICC) classification (ILESLICC, n=119) and healthy controls (n=133). Unweighted genetic loads were calculated as the total sum of risk alleles for each individual, while weighted genetic loads were defined as the sum of risk alleles multiplied by the natural logarithm of the previously published OR of each risk allele for SLE susceptibility. RESULTS: The median unweighted and weighted SLE risk allele genetic load was significantly greater in patients with ILE (unweighted: 81, p value=0.01; weighted: 16.3, p value=0.001) and patients with SLE (80, p value=0.02; 16.29, p value=0.0006) compared with healthy controls (78, 15.76). Patients with ILESLICC trended towards an increased genetic load, although not statistically significant (unweighted: 80, p value=0.14; weighted: 16.05, p value=0.07). However, the median genetic load did not significantly differ between ILE and SLE, and genetic load did not differentiate patients with ILE and SLE (area under the curve=0.51, p=0.78) by receiver operator characteristic analysis. CONCLUSIONS: Patients with ILE and SLE have comparable genetic loads of SLE risk loci, suggesting similar genetic predispositions between these conditions. Phenotypical differences between SLE and ILE may instead be influenced by ILE-specific variants and gene-environment interactions.

Unique Serum Immune Phenotypes and Stratification of Oklahoma Native American Rheumatic Disease Patients.

OBJECTIVE: Native American (NA) populations have higher rates of rheumatic disease and present with overlapping disease symptoms and nontraditional serologic features, thus presenting an urgent need for better biomarkers in NA diagnostics. This study used a machine learning approach to identify immune signatures that more effectively stratify NA patients with rheumatic disease. METHODS: Adult NA patients with autoantibody-positive (AAB+) rheumatoid arthritis (RA; n = 28), autoantibody negative (AAB-) RA (n = 18), systemic autoimmune rheumatic disease (n = 28), arthralgia/osteoarthritis (n = 28), or polyarthritis/undifferentiated connective tissue disease (n = 28), and control patients (n = 28) provided serum samples for cytokine, chemokine, and AAB assessment. Random forest clustering and soluble mediator groups were used to identify patients and control patients with similar biologic signatures. The American College of Rheumatology criteria specific for systemic disease and RA identified differences in disease manifestations across clusters. RESULTS: Serum soluble mediators were not homogenous between different NA rheumatic disease diagnostic groups, reflecting the heterogeneity of autoimmune diseases. Clustering by serum biomarkers created 5 analogous immune phenotypes. Soluble mediators and pathways associated with chronic inflammation and involvement of the innate, B cell, T follicular helper cell, and interferon-associated pathways, along with regulatory signatures, distinguished the 5 immune signatures among patients. Select clinical features were associated with individual immune profiles. Patients with low inflammatory and higher regulatory signatures were more likely to have few clinical manifestations, whereas those with T cell pathway involvement had more arthritis. CONCLUSION: Serum protein signatures distinguished NA patients with rheumatic disease into distinct immune subsets. Following these immune profiles over time may assist with earlier diagnoses and help guide more personalized treatment approaches.

Disease diagnostics using machine learning of immune receptors.

Clinical diagnoses rely on a wide variety of laboratory tests and imaging studies, interpreted alongside physical examination findings and the patient's history and symptoms. Currently, the tools of diagnosis make limited use of the immune system's internal record of specific disease exposures encoded by the antigen-specific receptors of memory B cells and T cells, and there has been little integration of the combined information from B cell and T cell receptor sequences. Here, we analyze extensive receptor sequence datasets with three different machine learning representations of immune receptor repertoires to develop an interpretive framework, MAchine Learning for Immunological Diagnosis (Mal-ID) , that screens for multiple illnesses simultaneously. This approach is effective in identifying a variety of disease states, including acute and chronic infections and autoimmune disorders. It is able to do so even when there are other differences present in the immune repertoires, such as between pediatric or adult patient groups. Importantly, many features of the model of immune receptor sequences are human-interpretable. They independently recapitulate known biology of the responses to infection by SARS-CoV-2 and HIV, provide evidence of receptor antigen specificity, and reveal common features of autoreactive immune receptor repertoires, indicating that machine learning on immune repertoires can yield new immunological knowledge. This framework could be useful in identifying immune responses to new infectious diseases as they emerge.

A Flare Risk Index Informed by Select Immune Mediators in Systemic Lupus Erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is marked by immune dysregulation linked to varied clinical disease activity. Using a unique longitudinal cohort of SLE patients, this study sought to identify optimal immune mediators informing an empirically refined flare risk index (FRI) reflecting altered immunity prior to clinical disease flare. METHODS: Thirty-seven SLE-associated plasma mediators were evaluated by microfluidic immunoassay in 46 samples obtained in SLE patients with an imminent clinical disease flare (preflare) and 53 samples obtained in SLE patients without a flare over a corresponding period (pre-nonflare). SLE patients were selected from a unique longitudinal cohort of 106 patients with classified SLE (meeting the American College of Rheumatology 1997 revised criteria for SLE or the Systemic Lupus International Collaborating Clinics 2012 revised criteria for SLE). Autoantibody specificities, hybrid SLE Disease Activity Index (hSLEDAI) scores, clinical features, and medication usage were also compared at preflare (mean ± SD 111 ± 47 days prior to flare) versus pre-nonflare (99 ± 21 days prior to nonflare) time points. Variable importance was determined by random forest analysis with logistic regression subsequently applied to determine the optimal number and type of analytes informing a refined FRI. RESULTS: Preflare versus pre-nonflare differences were not associated with demographics, autoantibody specificities, hSLEDAI scores, clinical features, nor medication usage. Forward selection and backward elimination of mediators ranked by variable importance resulted in 17 plasma mediator candidates differentiating preflare from pre-nonflare visits. A final combination of 11 mediators best informed a newly refined FRI, which achieved a maximum sensitivity of 97% and maximum specificity of 98% after applying decision curve analysis to define low, medium, and high FRI scores. CONCLUSION: We verified altered immune mediators associated with imminent disease flare, and a subset of these mediators improved the FRI to identify SLE patients at risk of imminent flare. This molecularly informed, proactive management approach could be critical in prospective clinical trials and the clinical management of lupus.

Dysregulated long non-coding RNA in Sjögren's disease impacts both interferon and adaptive immune responses.

OBJECTIVE: Sjögren's disease (SjD) is an autoimmune disease characterised by inflammatory destruction of exocrine glands. Patients with autoantibodies to Ro/SSA (SjDRo+) exhibit more severe disease. Long non-coding RNAs (lncRNAs) are a functionally diverse class of non-protein-coding RNAs whose role in autoimmune disease pathology has not been well characterised. METHODS: Whole blood RNA-sequencing (RNA-seq) was performed on SjD cases (n=23 Ro/SSA negative (SjDRo-); n=27 Ro/SSA positive (SjDRo+) and healthy controls (HCs; n=27). Bioinformatics and pathway analyses of differentially expressed (DE) transcripts (log2 fold change ≥2 or ≤0.5; padj<0.05) were used to predict lncRNA function. LINC01871 was characterised by RNA-seq analyses of HSB-2 cells with CRISPR-targeted LINC01871 deletion (LINC01871-/ -) and in vitro stimulation assays. RESULTS: Whole blood RNA-seq revealed autoantibody-specific transcription profiles and disproportionate downregulation of DE transcripts in SjD cases relative to HCs. Sixteen DE lncRNAs exhibited correlated expression with the interferon (IFN)-regulated gene, RSAD2, in SjDRo+ (r≥0.65 or ≤-0.6); four antisense lncRNAs exhibited IFN-regulated expression in immune cell lines. LINC01871 was upregulated in all SjD cases. RNA-seq and pathway analyses of LINC01871-/ - cells implicated roles in cytotoxic function, differentiation and IFNγ induction. LINC01871 was induced by IFNγ in a myeloid cell line and regulated by calcineurin/NFAT pathway and T cell receptor (TCR) signalling in primary human T cells. CONCLUSION: LINC01871 influences expression of many immune cell genes and growth factors, is IFNγ inducible, and regulated by calcineurin signalling and TCR ligand engagement. Altered LINC01871 expression may influence the dysregulated T cell inflammatory pathways implicated in SjD.

Loss-of-function variants in SAT1 cause X-linked childhood-onset systemic lupus erythematosus.

OBJECTIVES: Families that contain multiple siblings affected with childhood onset of systemic lupus erythematosus (SLE) likely have strong genetic predispositions. We performed whole exome sequencing (WES) to identify familial rare risk variants and to assess their effects in lupus. METHODS: Sanger sequencing validated the two ultra-rare, predicted pathogenic risk variants discovered by WES and identified additional variants in 562 additional patients with SLE. Effects of a splice site variant and a frameshift variant were assessed using a Minigene assay and CRISPR/Cas9-mediated knock-in (KI) mice, respectively. RESULTS: The two familial ultra-rare, predicted loss-of-function (LOF) SAT1 variants exhibited X-linked recessive Mendelian inheritance in two unrelated African-American families. Each LOF variant was transmitted from the heterozygous unaffected mother to her two sons with childhood-onset SLE. The p.Asp40Tyr variant affected a splice donor site causing deleterious transcripts. The young hemizygous male and homozygous female Sat1 p.Glu92Leufs*6 KI mice spontaneously developed splenomegaly, enlarged glomeruli with leucocyte infiltration, proteinuria and elevated expression of type I interferon-inducible genes. SAT1 is highly expressed in neutrophils and encodes spermidine/spermine-N1-acetyltransferase 1 (SSAT1), a rate-limiting enzyme in polyamine catabolism. Young male KI mice exhibited neutrophil defects and decreased proportions of Foxp3 +CD4+ T-cell subsets. Circulating neutrophil counts and proportions of Foxp3 +CD4+ T cells correlated with decreased plasma levels of spermine in treatment-naive, incipient SLE patients. CONCLUSIONS: We identified two novel SAT1 LOF variants, showed the ability of the frameshift variant to confer murine lupus, highlighted the pathogenic role of dysregulated polyamine catabolism and identified SAT1 LOF variants as new monogenic causes for SLE.

The promise of precision medicine in rheumatology.

Systemic autoimmune rheumatic diseases (SARDs) exhibit extensive heterogeneity in clinical presentation, disease course, and treatment response. Therefore, precision medicine - whereby treatment is tailored according to the underlying pathogenic mechanisms of an individual patient at a specific time - represents the 'holy grail' in SARD clinical care. Current strategies include treat-to-target therapies and autoantibody testing for patient stratification; however, these are far from optimal. Recent innovations in high-throughput 'omic' technologies are now enabling comprehensive profiling at multiple levels, helping to identify subgroups of patients who may taper off potentially toxic medications or better respond to current molecular targeted therapies. Such advances may help to optimize outcomes and identify new pathways for treatment, but there are many challenges along the path towards clinical translation. In this Review, we discuss recent efforts to dissect cellular and molecular heterogeneity across multiple SARDs and future directions for implementing stratification approaches for SARD treatment in the clinic.

Genome-wide association study identifies Sjögren's risk loci with functional implications in immune and glandular cells.

Sjögren's disease is a complex autoimmune disease with twelve established susceptibility loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant (GWS) regions in Sjögren's cases of European ancestry: CD247, NAB1, PTTG1-MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2, SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08. Interrogation of bioinformatics databases refine the associations, define local regulatory networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to >40. Many GWS SNPs are eQTLs for genes within topologically associated domains in immune cells and/or eQTLs in the main target tissue, salivary glands.