Project: Personalized treatment in IgA Nephropathy
Network: ERA PerMed
IgA Nephropathy (IgAN) is the most common primary glomerulonephritis, a major cause of end stage renal disease. Different therapeutic options are available, but only a fraction of patients responds to specific treatments. Guidance predicting response is currently lacking. To serve this urgent need, the project aims at developing a biomarker-based algorithm that allows predicting a drug response in IgAN, personalizing therapeutic intervention and significantly improving patient management. The project is based on extensive previous work on urinary peptide/protein biomarkers. The applicants have demonstrated that classifiers based on urinary peptides enable early detection of chronic kidney disease and early intervention, guided by a specific, personal, molecular profile. Further studies demonstrated the presence of specific biomarkers for IgAN. The ability of urinary peptides to display drug response, and, more important, to predict response, could be demonstrated in recent studies. The technology, capillary electrophoresis coupled mass spectrometry (CE-MS), is a routine analytical technique applied for individual diagnosis, also in large randomized clinical trials. Based on these extensive data, in this project the application of CE-MS to guide personalized intervention in IgAN is proposed. Using biobanked samples from patients with known outcome from multiple clinical centres, urinary peptides and classifiers significantly associated with response to immunosuppressive treatment in IgAN will be identified. An algorithm to predict response based on the urinary peptides and, if applicable, on other relevant variables, will be developed and tested in an independent sample. If the algorithm enabling personalized intervention in IgAN shows significant benefit, a well powered clinical trial will be planned to support implementation in routine care. The large number of leading clinical centres as partners in the consortium will substantially ease clinical implementation.