Abstract
Introduction: Parathyroid hormone (PTH) remains the primary biomarker used to classify and monitor chronic kidney disease–mineral and bone disorder (CKD-MBD); nonetheless, its reliability for risk stratification and treatment guidance is limited. Multidimensional biomarker clustering that integrates indicators of bone turnover, vascular calcification, inflammatory and oxidative stress may better capture the heterogeneity of clinical phenotypes, improve risk stratification, and inform on new therapeutic approaches in dialysis care. Methods: We conducted a computational analysis of a multicentric cohort study including 471 patients undergoing hemodialysis. The Partitioning Around Medoids algorithm was used to cluster the cohort by a pathophysiology-based biomarker panel (noxPTH, intact parathyroid hormone [iPTH], osteoprotegerin [OPG], soluble receptor activator of nuclear factor-κB ligand [sRANKL], antioxidative capacity [ImAnOx], oxidative capacity [PerOx], β-Crosslaps [β-CL], and high-sensitivity C-reactive protein [hsCRP]) at baseline. The cluster phenotypes were characterized by anthropometrics, imaging, and clinical data. Cluster-specific outcomes and event patterns were assessed after 1 year. Results: A total of 4 distinct clusters were identified. Cluster 1 reflected a high bone turnover state with high antioxidative capacity and high bone-specific alkaline phosphatase. Cluster 2 showed low bone turnover with high antioxidative capacity and high sclerostin levels. Cluster 3 exhibited an inflammatory–oxidative phenotype and the highest 1-year mortality; cluster membership improved prediction of events beyond clinical covariates. This phenotype was marked by high aortic calcium burden, vascular disease, markers of vitamin D degradation, low vaccine response, and hepatic steatosis. Cluster 4 showed a balanced biomarker profile and the highest rate of reclassification after 1 year. Conclusion: Multidimensional biomarker clustering captures heterogeneity in bone and vascular disease phenotypes of CKD-MBD, exhibiting differential mortality risk and event patterns and highlighting inflammation as an important pathway for further studies.