Rheumatoid arthritis (RA) is a complex, systemic autoimmune disease that primarily affects the lining of the synovial joints and involves an intricate interplay among genotype and environmental triggers. Early RA starts with the infiltration of the synovial compartment by leukocytes. Then, the synovial fluid is inundated with pro-inflammatory mediators inducing an inflammatory cascade characterised by fibroblast-like synoviocytes (FLS) interactions with cells of the innate and adaptive immune system. Cytokines are key mediators, whereas drugs inhibiting these cytokines lead to RA therapies. Unfortunately, 40% of patients fail to respond to therapy.

Recently, many studies have shown that RA FLS activation and the subsequent joint damage they perpetuate are associated with an altered metabolism that may be therapeutically targetable.Thus, RA FLS-directed therapies could become a complementary approach to immune-directed therapies.

I will present our efforts to construct a virtual RA FLS and develop a computational method to simulate large-scale coupled logical and metabolic models using Boolean and constraint-based modelling. The digital RA FLS can be used to predict intervention points for minimising the sustained inflammation, bone erosion, and cartilage destruction and identify druggable metabolic switches that could help us reprogram these cells to acquire an anti-inflammatory phenotype.

About the speaker

Dr. Anna Niarakis is an Associate Professor, HDR at UEVE, Paris-Saclay, affiliated with GenHotel, European Research Laboratory for Rheumatoid Arthritis, Genopole. She holds a 3-year delegation for research at INRIA, in the group Lifeware. She has a broad scientific background in Biochemistry, Biology, and Pharmaceutical Technology and post-doctoral studies in Computational Systems Biology & Bioinformatics with expertise in complex human diseases. She is a co-leader of the Disease Maps consortium, an active member of CoLoMoTo (Consortium for Logical Modelling Tools), and a former coordinator of SysMod (Systems Modelling).