Stratification according to autoantibody status in systemic sclerosis reveals distinct molecular signatures.

OBJECTIVES: Systemic sclerosis (SSc) is a heterogeneous disease, complicating its management. Its complexity and the insufficiency of clinical manifestations alone to delineate homogeneous patient groups further challenge this task. However, autoantibodies could serve as relevant markers for the pathophysiological mechanisms driving the disease. Identifying specific immunological mechanisms based on patients' serological statuses might facilitate a deeper understanding of the diversity of the disease. METHODS: A cohort of 206 patients with SSc enrolled in the PRECISESADS cross-sectional study was examined. Patients were stratified based on their anti-centromere (ACA) and anti-SCL70 (SCL70) antibody statuses. Comprehensive omics analyses including transcriptomic, flow cytometric, cytokine and metabolomic data were analysed to characterise the differences between these patient groups. RESULTS: Patients with SCL70 antibodies showed severe clinical features such as diffuse cutaneous sclerosis and pulmonary fibrosis and were biologically distinguished by unique transcriptomic profiles. They exhibit a pro-inflammatory and fibrotic signature associated with impaired tissue remodelling and increased carnitine metabolism. Conversely, ACA-positive patients exhibited an immunomodulation and tissue homeostasis signature and increased phospholipid metabolism. CONCLUSIONS: Patients with SSc display varying biological profiles based on their serological status. The findings highlight the potential utility of serological status as a discriminating factor in disease severity and suggest its relevance in tailoring treatment strategies and future research directions.

An interactive web application for exploring systemic lupus erythematosus blood transcriptomic diversity.

In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research settings. Large-scale datasets of transcriptome profiling have been collected and made available to the research community in public repositories, but remain poorly accessible and usable by mainstream researchers. Enabling tools and technologies facilitating investigators' interaction with large-scale datasets such as user-friendly web applications could promote data reuse and foster knowledge discovery. Microarray blood transcriptomic data from the LUPUCE cohort (publicly available on Gene Expression Omnibus, GSE49454), which comprised 157 samples from 62 adult SLE patients, were analyzed with the third-generation (BloodGen3) module repertoire framework, which comprises modules and module aggregates. These well-characterized samples corresponded to different levels of disease activity, different types of flares (including biopsy-proven lupus nephritis), different auto-antibody profiles and different levels of interferon signatures. A web application was deployed to present the aggregate-level, module-level and gene-level analysis results from LUPUCE dataset. Users can explore the similarities and heterogeneity of SLE samples, navigate through different levels of analysis, test hypotheses and generate custom fingerprint grids and heatmaps, which may be used in reports or manuscripts. This resource is available via this link: https://immunology-research.shinyapps.io/LUPUCE/. This web application can be employed as a stand-alone resource to explore changes in blood transcript profiles in SLE, and their relation to clinical and immunological parameters, to generate new research hypotheses.

Dual MPO/PR3 ANCA positivity and vasculitis: insights from a 7-cases study and an AI-powered literature review.

OBJECTIVES: Anti-neutrophil cytoplasm antibodies (ANCA)-associated vasculitides (AAV) are rare conditions characterized by inflammatory cell infiltration in small blood vessels, leading to tissue necrosis. While most patients with AAV present antibodies against either myeloperoxidase (MPO) or proteinase 3 (PR3), rare cases of dual positivity for both antibodies (DP-ANCA) have been reported, and their impact on the clinical picture remains unclear. The goal of this study was to investigate the clinical implications, phenotypic profiles and outcomes of patients with DP-ANCA. METHODS: A retrospective screening for DP-ANCA cases was conducted at Brest University Hospital's immunology laboratory (France), analysing ANCA results from March 2013 to March 2022. Clinical, biological, imaging, and histological data were collected for each DP-ANCA case. Additionally, a comprehensive literature review on DP-ANCA was performed, combining an artificial intelligence (AI)-based search using BIBOT software with a manual PUBMED database search. RESULTS: The report of our cases over the last 9 years and those from the literature yielded 103 described cases of patients with DP-ANCA. We identified four distinct phenotypic profiles: (i) idiopathic AAV (∼30%); (ii) drug-induced AAV (∼25%); (iii) autoimmune disease associated with a low risk of developing vasculitis (∼20%); and (iv) immune-disrupting comorbidities (infections, cancers, etc) not associated with AAV (∼25%). CONCLUSION: This analysis of over a hundred DP-ANCA cases suggests substantial diversity in clinical and immunopathological presentations. Approximatively 50% of DP-ANCA patients develop AAV, either as drug-induced or idiopathic forms, while the remaining 50%, characterized by pre-existing dysimmune conditions, demonstrates a remarkably low vasculitis risk. These findings underscore the complex nature of DP-ANCA, its variable impact on patient health, and the necessity for personalized diagnostic and management approaches in these cases.

Association of Combined Anti-Ro52/TRIM21 and Anti-Ro60/SSA Antibodies With Increased Sjögren Disease Severity Through Interferon Pathway Activation.

OBJECTIVE: The biologic diagnosis of primary Sjögren disease (SjD) mainly relies on anti-Ro60/SSA antibodies, whereas the significance of anti-Ro52/TRIM21 antibodies currently remains unclear. The aim of this study was to characterize the clinical, serological, biologic, transcriptomic, and interferon profiles of patients with SjD according to their anti-Ro52/TRIM21 antibody status. METHODS: Patients with SjD from the European PRECISESADS (n = 376) and the Brittany Diagnostic Suspicion of primitive Sjögren's Syndrome (DIApSS); (n = 146) cohorts were divided into four groups: double negative (Ro52-/Ro60-), isolated anti-Ro52/TRIM21 positive (Ro52+), isolated anti-Ro60/SSA positive (Ro60+), and double-positive (Ro52+/Ro60+) patients. Clinical information; EULAR Sjögren Syndrome Disease Activity Index, a score representing systemic activity; and biologic markers associated with disease severity were evaluated. Transcriptome data obtained from whole blood by RNA sequencing and type I and II interferon signatures were analyzed for PRECISESADS patients. RESULTS: In the DIApSS cohort, Ro52+/Ro60+ patients showed significantly more parotidomegaly (33.3% vs 0%-11%) along with higher ß2-microglobulin (P = 0.0002), total immunoglobulin (P < 0.0001), and erythrocyte sedimentation rate levels (P = 0.002) as well as rheumatoid factor (RF) positivity (66.2% vs 20.8%-25%) compared to other groups. The PRECISESADS cohort corroborated these observations, with increased arthritis (P = 0.046), inflammation (P = 0.005), hypergammaglobulinemia (P < 0.0001), positive RF (P < 0.0001), leukopenia (P = 0.004), and lymphopenia (P = 0.009) in Ro52+/Ro60+ patients. Cumulative EULAR Sjögren Syndrome Disease Activity Index results further confirmed these disparities (P = 0.002). Transcriptome analysis linked anti-Ro52/TRIM21 antibody positivity to interferon pathway activation as an underlying cause for these clinical correlations. CONCLUSION: These results suggest that the combination of anti-Ro52/TRIM21 and anti-Ro60/SSA antibodies is associated with a clinical, biologic, and transcriptional profile linked to greater disease severity in SjD through the potentiation of the interferon pathway activation by anti-Ro52/TRIM21 antibodies.

Harnessing large language models (LLMs) for candidate gene prioritization and selection.

BACKGROUND: Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for selecting candidate genes, knowledge-driven methods must contend with the challenge of efficiently sifting through extensive volumes of biomedical information. This work aimed to assess the utility of large language models (LLMs) for knowledge-driven gene prioritization and selection. METHODS: In this proof of concept, we focused on 11 blood transcriptional modules associated with an Erythroid cells signature. We evaluated four leading LLMs across multiple tasks. Next, we established a workflow leveraging LLMs. The steps consisted of: (1) Selecting one of the 11 modules; (2) Identifying functional convergences among constituent genes using the LLMs; (3) Scoring candidate genes across six criteria capturing the gene's biological and clinical relevance; (4) Prioritizing candidate genes and summarizing justifications; (5) Fact-checking justifications and identifying supporting references; (6) Selecting a top candidate gene based on validated scoring justifications; and (7) Factoring in transcriptome profiling data to finalize the selection of the top candidate gene. RESULTS: Of the four LLMs evaluated, OpenAI's GPT-4 and Anthropic's Claude demonstrated the best performance and were chosen for the implementation of the candidate gene prioritization and selection workflow. This workflow was run in parallel for each of the 11 erythroid cell modules by participants in a data mining workshop. Module M9.2 served as an illustrative use case. The 30 candidate genes forming this module were assessed, and the top five scoring genes were identified as BCL2L1, ALAS2, SLC4A1, CA1, and FECH. Researchers carefully fact-checked the summarized scoring justifications, after which the LLMs were prompted to select a top candidate based on this information. GPT-4 initially chose BCL2L1, while Claude selected ALAS2. When transcriptional profiling data from three reference datasets were provided for additional context, GPT-4 revised its initial choice to ALAS2, whereas Claude reaffirmed its original selection for this module. CONCLUSIONS: Taken together, our findings highlight the ability of LLMs to prioritize candidate genes with minimal human intervention. This suggests the potential of this technology to boost productivity, especially for tasks that require leveraging extensive biomedical knowledge.

Machine Learning for the Identification of a Common Signature for Anti-SSA/Ro 60 Antibody Expression Across Autoimmune Diseases.

OBJECTIVE: Anti-Ro autoantibodies are among the most frequently detected extractable nuclear antigen autoantibodies, mainly associated with primary Sjögren's syndrome (SS), systemic lupus erythematosus (SLE), and undifferentiated connective tissue disease (UCTD). This study was undertaken to determine if there is a common signature for all patients expressing anti-Ro 60 autoantibodies regardless of their disease phenotype. METHODS: Using high-throughput multiomics data collected from the cross-sectional cohort in the PRECISE Systemic Autoimmune Diseases (PRECISESADS) study Innovative Medicines Initiative (IMI) project (genetic, epigenomic, and transcriptomic data, combined with flow cytometry data, multiplexed cytokines, classic serology, and clinical data), we used machine learning to assess the integrated molecular profiling of 520 anti-Ro 60+ patients compared to 511 anti-Ro 60- patients with primary SS, patients with SLE, and patients with UCTD, and 279 healthy controls. RESULTS: The selected clinical features for RNA-Seq, DNA methylation, and genome-wide association study data allowed for a clear distinction between anti-Ro 60+ and anti-Ro 60- patients. The different features selected using machine learning from the anti-Ro 60+ patients constituted specific signatures when compared to anti-Ro 60- patients and healthy controls. Remarkably, the transcript Z score of 3 genes (ATP10A, MX1, and PARP14), presenting with overexpression associated with hypomethylation and genetic variation and independently identified using the Boruta algorithm, was clearly higher in anti-Ro 60+ patients compared to anti-Ro 60- patients regardless of disease type. Our findings demonstrated that these signatures, enriched in interferon-stimulated genes, were also found in anti-Ro 60+ patients with rheumatoid arthritis and those with systemic sclerosis and remained stable over time and were not affected by treatment. CONCLUSION: Anti-Ro 60+ patients present with a specific inflammatory signature regardless of their disease type, suggesting that a dual therapeutic approach targeting both Ro-associated RNAs and anti-Ro 60 autoantibodies should be considered.

A new molecular classification to drive precision treatment strategies in primary Sjögren's syndrome.

There is currently no approved treatment for primary Sjögren's syndrome, a disease that primarily affects adult women. The difficulty in developing effective therapies is -in part- because of the heterogeneity in the clinical manifestation and pathophysiology of the disease. Finding common molecular signatures among patient subgroups could improve our understanding of disease etiology, and facilitate the development of targeted therapeutics. Here, we report, in a cross-sectional cohort, a molecular classification scheme for Sjögren's syndrome patients based on the multi-omic profiling of whole blood samples from a European cohort of over 300 patients, and a similar number of age and gender-matched healthy volunteers. Using transcriptomic, genomic, epigenetic, cytokine expression and flow cytometry data, combined with clinical parameters, we identify four groups of patients with distinct patterns of immune dysregulation. The biomarkers we identify can be used by machine learning classifiers to sort future patients into subgroups, allowing the re-evaluation of response to treatments in clinical trials.

An elevated polyclonal free light chain level reflects a strong interferon signature in patients with systemic autoimmune diseases.

High amount of polyclonal free light chains (FLC) are reported in systemic autoimmune diseases (SAD) and we took advantage of the PRECISESADS study to better characterize them. Serum FLC levels were explored in 1979 patients with SAD (RA, SLE, SjS, Scl, APS, UCTD, MCTD) and 614 healthy controls. Information regarding clinical parameters, disease activity, medications, autoantibodies (Ab) and the interferon α and/or γ scores were recorded. Among SAD patients, 28.4% had raised total FLC (from 12% in RA to 30% in SLE and APS) with a normal kappa/lambda ratio. Total FLC levels were significantly higher in SAD with inflammation, active disease in SLE and SjS, and an impaired pulmonary functional capacity in SSc, while independent from kidney impairment, infection, cancer and treatment. Total FLC concentrations were positively correlated among the 10/17 (58.8%) autoantibodies (Ab) tested with anti-RNA binding protein Ab (SSB, SSA-52/60 kDa, Sm, U1-RNP), anti-dsDNA/nucleosome Ab, rheumatoid factor and negatively correlated with complement fractions C3/C4. Finally, examination of interferon (IFN) expression as a potential driver of FLC overexpression was tested showing an elevated level of total FLC among patients with a high IFNα and IFNγ Kirou's score, a strong IFN modular score, and the detection in the sera of B-cell IFN dependent factors, such as TNF-R1/TNFRSF1A and CXCL10/IP10. In conclusion, an elevated level of FLC, in association with a strong IFN signature, defines a subgroup of SAD patients, including those without renal affectation, characterized by increased disease activity, autoreactivity, and complement reduction.

Is hypophosphataemia an independent predictor of mortality in critically ill patients with bloodstream infection? A multicenter retrospective cohort study.

BACKGROUND: Hypophosphataemia affects up to one-third of patients in the intensive care unit (ICU) and is particularly common during sepsis. Experimental data suggest that hypophosphataemia leads to an acquired dysfunction of leukocytes, thus promoting infections and increasing the risk of death during sepsis. OBJECTIVES: The aim of our study was to investigate the association between hypophosphataemia and mortality in critically ill patients with a bloodstream infection (BSI). METHODS: We performed a retrospective study in three ICUs during an 18-month period. All adults with a BSI diagnosed in the ICU were eligible. Patients with and without hypophosphataemia, defined as phosphataemia below 0.8 mmol/L, were compared. A multivariate survival analysis using a Cox proportional hazard regression model was conducted to study the association between hypophosphataemia and 90-d mortality. RESULTS/FINDINGS: Among the 3783 patients admitted to the three participating ICUs within the 18-month study period, 203 met the inclusion criteria and 193 were analysed. Fifty-four patients had hypophosphataemia. After adjusting for confounders, hypophosphataemia was significantly associated with a twofold increased risk of 90-d mortality (hazard ratio = 2.10 [1.177-3.80], p = 0.013). This association is particularly strong in patients without shock. CONCLUSIONS: Hypophosphataemia was independently associated with a twofold increase in 90-d mortality in ICU patients with a BSI. These results suggest that investigators and physicians should include phosphataemia as a predictor of the severity of BSIs. Further research is warranted to better understand this association and to determine the potential benefits of systematic monitoring of phosphataemia and phosphorus supplementation. CLINICAL TRIAL REGISTRATION: NCT03529058.

Tocilizumab controls bone turnover in early polymyalgia rheumatica.

OBJECTIVES: This study explores changes in the bone homeostasis by testing the N-terminal collagen type I extension propeptide (PINP) marker for osteo-formation and the carboxy-terminal region of collagen type I (CTX-I) marker for osteo-resorption in patients taking tocilizumab for polymyalgia rheumatica (PMR). METHODS: Twenty patients were included in the prospective open-label TENOR study (Clinicaltrials.gov NCT01713842) and received three monthly tocilizumab infusions, followed by corticosteroids starting at week (W) 12. PINP and CTX-I were tested at inclusion (W0), after tocilizumab but before steroid initiation (W12), at the end of the protocol (W24) and were compared to healthy controls. Information regarding disease activity, bone mineral density using scanographic bone attenuation correlation (SBAC), inflammatory parameters and interleukin (IL)-6 levels were collected during the follow-up of the patients. RESULTS: PMR patients were characterised by a reduction in bone mineral density and a higher level of CTX-I relative to healthy controls matched in age and sex at baseline. PINP levels increased at W12 (P< 0.001, versus W0) following tocilizumab introduction and CTX-I levels decreased at W24 and after steroid initiation (P=0.001, versus W0). Such modifications explain the altered correlation observed between PINP and CTX-I at W0 (r=0.255 at W0 versus r=0.641 in healthy controls) and its correction after treatment (r=0.760 at W12 and r=0.767 at W24). Finally, greater changes in PINP were observed in patients whose circulating IL-6 levels decreased after tocilizumab therapy. CONCLUSIONS: Control of bone turnover, in part through the inhibition of the IL-6 axis, is observed during tocilizumab and subsequent steroid treatment of PMR.

Antiphospholipid autoantibody detection is important in all patients with systemic autoimmune diseases.

Antiphospholipid (aPL) autoantibodies are uncommon in systemic autoimmune diseases (SADs). However, the European PRECISESADS study provides the opportunity to better characterize this rare association. The study was composed of 1818 patients with SADs including 453 with systemic lupus erythematosus (SLE), 359 with rheumatoid arthritis (RA), 385 with systemic sclerosis (SSc), 367 with Sjögren's syndrome (SjS), 94 with mixed connective tissue disease (MCTD), and 160 with undifferentiated connective tissue disease (UCTD). Assays used for aPL determination include the lupus anticoagulant (LAC) analysis using the dilute Russell's viper venom time (dRVVT) assay plus anti-cardiolipin (aCL) and anti-aß2GPI autoantibodies of IgG and IgM isotype. Information regarding clinical and biological characteristics of SAD patients was available. Among SAD patients, the prevalence of aPL differs significantly between two groups: SLE (57.6%) and non-SLE SADs (13.7%, p < 10-4). Next, association between aPL plus thrombosis and miscarriage were observed in both SLE and non-SLE patients. Thrombosis was best predicted in SLE patients by dRVVT (OR = 6.1; IC95:3.5-10.3) and miscarriage by aCL±ß2GPI IgG (OR = 2.5; IC95:1.2-5.2); while in non-SLE SADs the best predictors were aCL±ß2GPI IgG for thrombosis (OR = 6.6; IC95:2.4-18.4) and aCL±ß2GPI IgM for miscarriage (OR = 2.9; IC95:1.2-6.8). In the case of multiple positivity of aPL, the risk for thrombosis and miscarriage was increased. Central nervous system involvement characterized the SLE patients, in contrast to pulmonary and skin fibrosis, valve lesions, hypertension, elevated creatinemia, C4 fraction reduction, platelet reduction and inflammation that characterized the non-SLE SAD patients. Anti-PL determination remains important in SADs patients and should not be restricted to only SLE patients.

Toll-Like Receptors, Infections, and Rheumatoid Arthritis.

Toll-like receptors (TLR) that belong to the group of protein recognition receptor (PPR) provide an innate immune response following the sensing of conserved pathogen-associated microbial patterns (PAMPs) and changes in danger-associated molecular patterns (DAMPs) that are generated as a consequence of cellular injury. Analysis of the TLR pathway has moreover offered new insights into the pathogenesis of rheumatoid arthritis (RA). Indeed, a dysfunctional TLR-mediated response characterizes RA patients and participates in establishment of a chronic inflammatory state. Such an inappropriate TLR response has been attributed (i) to the report of important alterations in the microbiota and abnormal responses to infectious agents as part of RA; (ii) to the abnormal presence of TLR-ligands in the serum and synovial fluid of RA patients; (iii) to the overexpression of TLR molecules; (iv) to the production of a large panel of pro-inflammatory cytokines downstream of the TLR pathway; and (v) to genetic variants and epigenetic factors in susceptible RA patients promoting a hyper TLR response. As a consequence, the development of promising therapeutic strategies targeting TLRs for the treatment and prevention of RA is emerging.

Complement System: a Neglected Pathway in Immunotherapy.

Approved for the treatment of autoimmune diseases, hematological malignancies, and solid cancers, several monoclonal antibodies (mAb) make use of complement in their mechanism of action. Such an assessment is based on comprehensive investigations that used mouse models, in vitro studies, and analyses from patients at initiation (basal level to highlight deficiencies) and after treatment initiation (mAb impact on complement), which have further provided key insights into the importance of the complement activation and/or complement deficiencies in mAb activity. Accordingly, new approaches can now be developed with the final objective of increasing the clinical efficacy of mAb. These improvements include (i) the concurrent administration of fresh frozen plasma during mAb therapy; (ii) mAb modifications such as immunoglobulin G subclass switching, Fc mutation, or IgG hexamerization to improve the fixation and activation of C1q; (iii) optimization of the target recognition to induce a higher complement-dependent cytotoxicity (CDC) and/or complement-dependant cellular cytotoxicity (CDCC); and (iv) the control of soluble and cellular complement inhibitors.

News and meta-analysis regarding anti-Beta 2 glycoprotein I antibodies and their determination.

Recent advances allow us to propose antibodies targeting beta-2-glycoprotein I (ß2-GPI) as the most specific antibodies associated with anti-phospholipid syndrome (APS). Therefore, there is now a crucial need for powerful biological assays to adequately monitor them. It is well established that these antibodies recognize mainly cryptic epitopes, which requires a great deal of consideration in the choice of laboratory tests to identify these antibodies. To this end, an update on the pathophysiological role of ß2-GPI and a meta-analysis were conducted providing an overview of the current progress towards anti-ß2-GPI detection.

[Biological diagnosis of pheochromocytoma: is there an interest in urinary metanephrines measurement over 3 consecutive days?] / Diagnostic biologique du phéochromocytome : le dosage des dérivés méthoxylés urinaires sur 3 jours consécutifs présente-t-il un intérêt ?

Pheochromocytoma and paraganglioma are neuroendocrine tumors characterized by a catecholamine production potential. The biochemical diagnosis for this type of tumor is carried out through the metanephrine titration on 24-hours urines. Some authors have suggested that the sensitivity of the test could be improved by sampling and analyzing urines 3 days in a row (cycle) versus a unique measurement but this method has never been fully evaluated. The goal of this study was to establish a comparison of diagnosis performances between urinary metanephrines measurement for 3 consecutive days, and metanephrines measurement on a unique 24-hour sample. Patients of Brest Regional University Hospital whose 3-consecutive day 24-hour urine samples had been analyzed from January 2011 to May 2017 were included in this study. The primary endpoint was the comparison of diagnostic performances of urinary metanephrine titration over a single day versus 3 consecutive days. Eighty-two patients for a total of 103 cycles among which 7 revealed a pheochromocytoma were analyzed. ROC curve analysis shows that the metanephrine cycle titration method is more efficient than the metanephrine single titration method (metanephrine: AUC=0.881 against 0.826 respectively; normetanephrine: AUC=0.946 against 0.901 respectively). Urinary titration over 3 days allows the diagnosis of 100% (7/7) of pheochromocytomas against 85.7% (6/7) for the the single urinary titration. In conclusion, metanephrine titration over 3 consecutive days of 24-hours urine samples shows a better sensitivity and better diagnosis performances for detecting pheochromocytoma and paraganglioma than the single titration method.