Biology subjects

Ribet, C.

Publications and source records attributed to Ribet, C..

4 recordsLinked to original sources

bioRxiv2026

A regulatory T cell signature provides a shared molecular basis for the therapeutic window of opportunity in rheumatic disease

Rheumatic diseases, including rheumatoid arthritis (RA), spondyloarthritis (SpA) and osteoarthritis (OA), show distinct phenotypes yet respond to overlapping therapies, implicating shared immune mechanisms. In the Transimmunom cohort, we profiled peripheral blood from 240 individuals (47 healthy, 44 OA, 91 RA, 58 SpA) across deep immunophenotyping, immunoproteomics and Treg-Teff transcriptomics. Single-layer analyses revealed broader Treg than Teff remodeling, along with a shared pattern of reduced activated Tregs and expanded Helios+ Tregs across all diseases, alongside a decrease in functional Treg subpopulations, including CTLA4+ and CD45RA- Tregs. In RA specifically, LAG3+ Tregs were also expanded. Combining omics layers outperformed single-layer approaches for disease classification. Among individual layers, Treg transcriptomes were most discriminative, and integration uncovered disease-specific programs. Unsupervised clustering identified a cross-disease cluster independent of activity, treatment and age, mapping to early disease (<= years) and dominated by a Treg dysfunction-associated program. These results provide a biological rationale for the therapeutic "window of opportunity" concept and duration-stratified Treg-directed trials.

immunology↗

bioRxiv2024

Immunological Profiling in Knee Osteoarthritis: Treg Dysfunction as Key Driver of Pain

Pain is the hallmark symptom of osteoarthritis (OA) and its biological drivers remain poorly understood. While the role of innate immunity in OA has been extensively studied, the involvement of adaptive immunity, in particular regulatory T cells (Tregs), is not well understood. Using a comprehensive multi-omic approach on the peripheral blood from 46 knee OA patients with similar radiographic stage, including deep immunophenotyping, cytokine profiling, transcriptomic and T-cell receptor analysis on sorted CD4 Tregs and effector T cells (Teff), we identified an immunological signature associated with OA-related pain. Cytokines promoting Treg expansion and activation (with increases of sIL2-RA, sTNFR1, sTNFR2) were correlated with the Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain subscore, suggesting a potential Treg dysfunction. Nineteen T cell subsets were correlated with WOMAC pain. Notably, we found a negative correlation of cell subsets associated with Treg expansion and activation (FoxP3+CTLA4+, CD4+CD57+, Treg CD95+, CD4 Treg CD45RA-). Differential gene expression analysis between patients with low and high WOMAC pain intensity (threshold [≥] 40/100) revealed an upregulation of inflammasome-related genes such as IL1RL1, IL31RA, IFITM3, NLRP3, IFNG in Tregs. Functional enrichment analysis highlighted an overrepresentation of innate immune response, IL-8, and interferon activation pathways suggesting a pro-inflammatory state in Tregs of patients with high pain intensity. Collectively, our systems immunology approach highlights multiple associations between Treg dysfunctionality and OA-related pain, providing new insights into the adaptive immune systems contribution to OA-related pain.

immunology↗

bioRxiv2024

IL-1β Signaling Modulates T Follicular Helper and Regulatory Cells in Human Lymphoid Tissues

BackgroundDysregulation of the T follicular helper (Tfh) and T follicular regulatory (Tfr) homeostasis in the germinal center (GC) can result in antibody-mediated autoimmunity. While interleukin-1{beta} (IL-1{beta}) has been shown to be an important modulator of the GC response in animal models via the expression of IL-1 agonist (IL-1R1) and antagonist (IL-1R2) receptors on follicular T cells, such regulation has not yet been studied in humans. MethodsWe investigated Tfh and Tfr phenotypes in human secondary lymphoid organs -- namely tonsils, spleens, and mesenteric lymph nodes -- using flow cytometry, single-cell transcriptomics, and in vitro cell culture. We also benchmarked our findings with a cohort of patients with autoimmune and inflammatory diseases. ResultsWe found that Tfh and Tfr cells exhibit organ-specific phenotypes related to their activation status and IL-1 receptor expression. An excess of IL-1R1 over IL-1R2 was linked to the emergence of a unique activated Tfr subset that combines features of both Treg and GC-Tfh cells. Single-cell transcriptomics and in vitro studies showed that IL-1{beta} signaling through IL-1R1 promotes follicular T-cell activation. Inhibiting IL-1{beta} resulted in upregulation of IL-1R1 expression, showing a fine-tuned regulation. In autoimmune patients, high IL-1{beta} and circulating Tfr levels correlated with higher autoantibody levels, linking inflammation, IL-1{beta} signaling, and the Tfr/Tfh balance. ConclusionsOur study underscores the pivotal role of IL-1{beta} in follicular T-cell activation, contributing to pathological antibody production in humans. Targeting IL-1{beta} signaling in Tfh and Tfr cells could offer new treatment strategies for antibody-mediated autoimmune diseases.

immunology↗

bioRxiv2018

Clinical data specification and coding for cross-analyses with omics data in autoimmune disease trials

ObjectivesAutoimmune and inflammatory diseases (AIDs) form a continuum of autoimmune and inflammatory diseases, yet AIDs nosology is based on syndromic classification. The TRANSIMMUNOM trial (NCT02466217) was designed to re-evaluate AIDs nosology through clinic-biological and multi-omics investigations of patients with one of 19 selected AIDs. To allow cross-analyses of clinic-biological data together with omics data, we needed to integrate clinical data in a harmonized database.\n\nMaterials and MethodsWe assembled a clinical expert consortium (CEC) to select relevant clinic-biological features to be collected for all patients and a cohort management team comprising biologists, clinicians and computer scientists to design an electronic case report form (eCRF). The eCRF design and implementation has been done on OpenClinica, an open-source CFR-part 11 compliant electronic data capture system.\n\nResultsThe CEC selected 865 clinical and biological parameters. The CMT selected coded the items using CDISC standards into 5835 coded values organized in 28 structured eCRFs. Examples of such coding are check boxes for clinical investigation, numerical values with units, disease scores as a result of an automated calculations, and coding of possible treatment formulas, doses and dosage regimens per disease.\n\nDiscussion21 CRFs were designed using OpenClinica v3.14 capturing the 5835 coded values per patients. Technical adjustment have been implemented to allow data entry and extraction of this amount of data, rarely achieved in classical eCRFs designs.\n\nConclusionsA multidisciplinary endeavour offers complete and harmonized CRFs for AID clinical investigations that are used in TRANSIMMUNOM and will benefit translational research team.

clinical trials↗