Risk prediction of kidney function in long-term kidney transplant recipients.

Abstract

Background: Limited tools exist for predicting kidney function in long-term kidney transplant recipients (KTRs). Elabela (ELA), apelin (APLN), and the APJ receptor constitute an axis that regulates vascular and cardiac physiology in opposition to the renin-angiotensin-aldosterone system.

Methods: Longitudinal, observational cohort of 102 KTRs who maintained graft function for at least 24 months, with no acute rejection history or active infection upon presentation. Serum APLN, ELA, fibroblast growth factor 23 (FGF-23) and α Klotho were tested using enzyme-linked immunoassay and compared with a control group of 32 healthy controls (HCs).

Results: When comparing with HCs, higher serum FGF-23, ELA and APLN, but lower ɑ Klotho concentrations were observed in long-term KTRs. Most KTRs had stable trajectories of renal function. Mean estimated glomerular filtration (eGFR) over 2-year follow-up was associated with significantly lower odds of graft loss (OR 0.04, 95% CI 0.01-0.15; p < 0.001). Baseline renal function was significantly correlated with mineral-bone markers (log[FGF-23]: r = -0.24, p = 0.02; log[α-Klotho]: r = 0.34, p < 0.001) but showed no significant association with aplnergic peptides (APLN: r = -0.07, p = 0.51; ELA: r = 0.17, p = 0.10). Univariable random forest regression indicated that baseline eGFR alone explained 87% of the variance in future 2-year eGFR, suggesting its overarching importance in late-term predictions. Incorporating both simple clinical characteristics and candidate serum biomarkers into a model predicting last available eGFR allowed for moderate predictive performance. In univariable Cox Proportion Hazard models, lower log(α-Klotho) (HR 0.26, 95% CI 0.12-0.58; p = 0.001) and higher log(FGF-23) (HR 2.14, 95% CI 1.49-3.09; p < 0.001) were significant predictors of death-censored allograft loss.

Conclusion: Both aplnergic and mineral-bone peptides appear as relevant candidate markers for future studies investigating their predictive performance regarding renal allograft outcomes.