Circulating Humanin Improves the Prognostic Accuracy of Cardiovascular Risk Models in Chronic Hemodialysis Patients

Abstract

Cardiovascular morbidity and mortality (CVMM) remain highly prevalent among end-stage kidney disease (ESKD) patients undergoing chronic hemodialysis (HD). Nevertheless, risk prediction in this setting is limited by the complexity of factors involved and the individual patients' characteristics. In this study, we evaluated whether circulating levels of Humanin, a micropeptide reflecting mitochondrial dysfunction, could refine CVMM prediction when included in established risk models for CVMM in ESKD-HD. Eighty-three chronic HD patients (mean age 67 ± 12 years; 74.7% male) were enrolled in a 24-month prospective multicenter study. CVMM (fatal or non-fatal CV events requiring hospitalization) occurred in 33 patients (39.7%). The performances of an internal prognostic model based on cohort-related risk predictors and four externally generated and validated risk scores (AROii-2, jDOPPS, You et al., and Zhang et al.) were compared before and after the inclusion of Humanin. Humanin displayed a curvilinear association with CVMM, with both low (<462 pg/mL) and high (>778 pg/mL) levels linked to an increased risk. CVMM was best predicted by the internal model (AUC 0.671; R2 0.13), followed by the Zhang (0.669; 0.12), AROii-2 (0.632; 0.05), You (0.628; 0.07), and jDOPPS (0.610; 0.03) scores. All models were well calibrated. Humanin inclusion remarkably improved discrimination (ΔAUC spanning from 0.083 to 0.109), calibration, explained variance (R2 gain from 9 to 15%), and reclassification (Net Reclassification Improvement: 8-27.9%; Integrated Discrimination Index: 4.4-7.3%) of all models considered. Integration of Humanin significantly enhances the predictive accuracy of CVMM risk models in HD patients, supporting its potential role as an additive biomarker in this high-risk population.