Pathways and moleculaR analysEs to Derive multi-omIC signatures predictive to response to Treatment in JIA – PREDICT-JIA

Juvenile Idiopathic Arthritis (JIA) is an heterogeneous group of inflammatory arthritis, that cripples pediatric patients, with very little information available on the potential genetic contribution, in pathophysiology and variable responses rates to available therapies. Thus, overall, JIA has very significant unmet medical needs. Among several JIA subsets, we aim to study patients with early-onset antinuclear antibody positive JIA (EO ANA+ JIA, 50% of a cohort of 1,200 JIA patients in Necker hospital) and patients with systemic JIA (sJIA, 20% of the JIA patients in Necker). Our project PREDICT-JIA, (Pathways and moleculaR analysEs to Derive multi-omIC signatures predictive to response to Treatment in JIA), aims at better understanding the molecular basis of this multifactorial disease, by performing a multi-OMIC analysis on Peripheral Blood Mononuclear Cells (PBMCs) collected before and 3 to 6 months following targeted biologic treatments by the soluble Tumor necrosis factor alpha (TNF) receptor, etanercept or the interleukin-1 (IL-1) receptor antagonist, anakinra, in EO ANA+ JIA and sJIA patients respectively. These are the most commonly used treatments at the early phase of the disease. These last years, a treat-to-target approach was recommended in JIA patients, aiming at achieving inactive disease within the first months of treatment. Based on transcriptomic, epigenomic, proteomic experiments performed at the single-cell level, combined with genomics, cellular immunophenotyping, autoantibodies and cytokines/chemokines analyses, we intend to identify and validate “pathological” cell clusters and new biomarkers, characteristic of our patients, but also predictive of responders, i.e., patients who achieve inactive disease on treatment, and non-or partial responders. By combining, in a synergistic way, our expertise in performing multi-OMICs analyses, on PBMCs, at the single-cell level (Partner 1) and in studying autoimmune/autoinflammatory responses (Partner 2), we intend to deliver new biomarkers and molecular signatures that could guide clinician in their therapeutic decisions, therefore benefit patients, but also setup new areas of research. Partners 1 and 2 are both group leaders at Imagine Institute and have been collaborating on rare genetic autoimmune/autoinflammatory diseases using single-cell multi-OMICs experiments since 2017.