Cristina Ruiz-Romero, Grupo de Investigación de Reumatología (GIR), Plataforma de Proteomica-PROTEORED-ISCIII, INIBIC - Complejo Hospitalario Universitario de A Coruña and Francisco J Blanco, Grupo de Investigación de Reumatología y Salud (GIR-S), Departamento de Fisioterapia, Medicina y Ciencias Biomedicas. Universidad de A Coruña
One of the priorities of translational proteomics is to facilitate the development of precision medicine strategies. These involve a deeper knowledge on the molecular profiles of diseases and patients, improving prediction and prevention and promoting a more personalized and participative medicine. In this field, the HPP initiative on Rheumatic and Autoimmune diseases (RAD-HPP) has focused on the application of proteomics for the development of predictive models for precision medicine. These models would enable the identification of disease phenotypes and the stratification of patients according to their future response to treatment.
In patients with osteoarthritis (OA), the Rheumatology Research Group in A Coruña (http://girblanco.com) has recently developed a kit, named DITOBA, for its diagnosis on the basis of the measurement of four proteins in serum. These proteins were identified in previous proteomic analyses performed by the group on samples from the Prospective Cohort of OA A Coruña (PROCOAC, Spain). A first LC-MS/MS analysis identified eleven peptides associated with OA and subsequently a targeted luminex-based assay was developed to quantify the corresponding proteins in 400 samples from PROCOAC. The inclusion of these proteins into a clinical model composed of demographic and clinical data has resulted in an algorithm for the diagnosis of OA without the need of XRay. Furthermore, a clinical validation of this model has been carried out in 1200 samples from the Osteoarthritis Initiative Cohort (OAI, USA) to qualify its use to monitor disease severity in OA positive cases, and predict the incidence of the disease before 8 years in the negative ones. This kit will facilitate the personalized management of patients suffering OA.
Regarding rheumatoid arthritis (RA), a collaboration between RAD-HPP members has identified a specific autoantibody (anti-CENPF) whose presence in serum is associated with a positive response of the patient to Infliximab (a TNF inhibitor). In this case, the screening was performed on a cohort from Santiago de Compostela (Spain) using planar antigen arrays from the Human Protein Atlas, which contain 42100 PrEST representing 19000 unique proteins. Further targeted validations were carried out on additional samples from A Coruña (Spain) and Sweden (SWEFOT cohort), in this case using in-house made suspension beads arrays. Finally, a statistical analysis was performed to assess the clinical relevance of the findings. The addition of anti-CENPF antibodies to demographic and clinical variables (age, sex and a disease activity score) resulted in the best model to predict responders to Infliximab, showing an area under the curve (AUC) of 0.756 (Lourido et al., Seminars Arthritis Rheum 2020). This study indicates the usefulness of anti-CENPF measurement to guide therapeutic interventions in RA.
Finally, RAD-HPP members have also focused interest on the analysis of the RA citrullinome and its link to clinical phenotypes (Fert-Bober et al., Immunol Rev 2020), and others have participated through the Accelerating Medicines Partnership in RA/SLE Consortium in a ground-breaking work providing a molecular basis by which stromal cells can be therapeutically targeted in RA (Wei et al., Nature 2020). Altogether, these studies show the latest activity of RAD-HPP in the development of initiatives for the application of proteomics strategies to improve the management of patients suffering RAD.