BACKGROUND: Chronic kidney disease (CKD) contributes to global morbidity and mortality. Early, targeted intervention can help mitigate its impact. CK273 is a urinary peptide classifier previously validated in a prospective clinical trial for the early detection of nephropathy. We hypothesized that drug-induced molecular changes in the urinary peptidome could be predicted in silico and guide selecting interventions for individual patients. METHODS: The efficacy of the urinary peptidomic classifier CKD273 in predicting major adverse kidney events (≥ 40% decline in estimated glomerular filtration rate or kidney failure -median follow-up: 1.50 (95%CI 0.35, 5.0) years), was confirmed in a retrospective cohort of 935 participants. In silico prediction of treatment effects from four drug-based interventions (Mineralocorticoid receptor antagonist, Sodium-glucose co-transporter 2 inhibitor, Glucagon-like peptide-1 receptor agonist, and Angiotensin receptor blocker), dietary intervention (olive oil), and exercise was performed based on: a) individual baseline urinary peptide profiles, and b) previously defined fold changes in peptide abundance after treatment in clinical trials. Following recalibration to align with outcomes of these trials, CKD273 scores were calculated for each patient after in silico treatment. For combination treatments, the effects of multiple interventions were combined. RESULTS: Simulated interventions demonstrated a significant reduction in median CKD273 scores, from 0.57 (IQR: 0.19-0.81) before to 0.039 (IQR: -0.192-0.363) after the most beneficial intervention (paired Wilcoxon test, P < 0.0001). The combination of all available treatments was not the most frequently predicted optimal intervention. Patients with higher baseline CKD273 scores required more complex intervention combinations to achieve the greatest score reduction. CONCLUSIONS: This study supports the feasibility of in silico predicting effects of therapeutic interventions on CKD progression. By identifying the most beneficial treatment combinations for individual patients, this approach paves the way for precision medicine trials in CKD. A prospective study is currently being planned to validate the in silico-guided intervention approach and determine its exact benefits on patient-relevant outcomes.

Atherothrombosis and Vascular Biology Program Baker Heart and Diabetes Institute Melbourne VIC Australia

Centre for Genomic and Experimental Medicine Institute of Genetics and Cancer University of Edinburgh Edinburgh UK

Centre of Systems Biology Biomedical Research Foundation of the Academy of Athens Athens Greece

Department of Cardiometabolic Health University of Melbourne VIC Australia

Department of Clinical Medicine University of Copenhagen Copenhagen Denmark

Department of Internal Medicine 3rd Faculty of Medicine Charles University and University Hospital Královské Vinohrady Prague Czech Republic

Department of Internal Medicine 4 Medical University Innsbruck Innsbruck Austria

Department of Internal Medicine and Paediatrics Nephrology Section Ghent University Hospital Ghent Belgium

Department of Medicine and Immunology Monash University Melbourne VIC Australia

Department of Nephrology Angiology and Rheumatology Klinikum Bayreuth GmbH Bayreuth Germany

Department of Nephrology Medizincampus Oberfranken Friedrich Alexander University Erlangen Nürnberg Erlangen Germany

Department of Physiology Anatomy Microbiology La Trobe University Melbourne VIC Australia

Division of Nephrology and KfH Renal Unit Hospital St Georg Leipzig Germany

Hull and East Yorkshire NHS Hospitals Trust Castle Hill Hospital Cottingham UK

Institute for Molecular Cardiovascular Research University Hospital RWTH Aachen Aachen Germany

Institute of Cardiovascular and Metabolic Disease Institut National de La Santé Et de La Recherche Médicale U1297 Toulouse France

Instituto de Investigación Sanitaria de La Fundación Jiménez Díaz UAM Madrid Spain

Kuratorium for Dialysis and Transplantation Bayreuth Bayreuth Germany

Martin Luther University Halle Wittenberg Germany

Mosaiques Diagnostics GmbH Rotenburger Straße 20 30659 Hannover Germany

Non Profit Research Institute Alliance for the Promotion of Preventive Medicine Mechlin Belgium

School of Cardiovascular and Metabolic Health University of Glasgow Glasgow UK

Steno Diabetes Center Copenhagen Herlev Denmark

Université de Toulouse Toulouse France

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