Abstract
Chronic kidney disease (CKD) is a major risk factor for cardiovascular events (CVE). We assessed whether circulating levels and genetic variability of endocrine fibroblast growth factors (FGF19, FGF21, and FGF23) could predict CV risk in these patients. In 1,182 participants (815 CKD patients and 367 controls), plasma FGF concentrations and 46 gene variants were analyzed, with participants followed-up for a mean of 37.6 ± 25.7 months for CVE. Clustering based on combined scores for all three FGF concentrations correlated strongly with CKD severity (p < 0.001) and predicted CVE after adjusting for other risk factors [hazard ratio (HR) = 2.03 (1.02-4.05), p = 0.044]. Four SNPs, notably FGF19 rs1307968 [odds ratio OR = 5.14 (1.53,17.27), p = 0.008], were also independently associated with CVE. Incorporating both combined FGF concentration scores and the relevant genetic variants into traditional risk models significantly improved prediction accuracy (AUC increased from 0.713 to 0.779; p < 0.0001). These findings suggest that combining FGF biomarkers with genetic information may enhance CV risk stratification in CKD patients.