IgA Nephropathy (IgAN) is a major cause of end stage renal disease necessitating maintenance dialysis treatment but guidance predicting therapy response is currently lacking. Therefore the project aims at developing a biomarker-based algorithm that predicts drug response in IgAN, personalizing intervention and significantly improving patient management. The ability of urinary peptides to display drug response could be demonstrated in recent studies by capillary electrophoresis coupled mass spectrometry (CE-MS). Using samples from patients with known outcome from multiple clinical centres, urinary peptides significantly associated with response to specific treatment 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 designed to support implementation in routine care.
