# Interplay Between Fibroblast Growth Factor-19, Beta-Klotho, and Receptors Impacts Cardiovascular Risk in Chronic Kidney Disease

## TL;DR

This study shows that FGF19 and beta-Klotho levels, along with genetic variants, can help predict cardiovascular risk in patients with chronic kidney disease.

## Contribution

The study introduces a novel cardiovascular risk model for CKD patients integrating FGF19/β-Klotho biomarker profiles and genetic variants.

## Key findings

- A cluster with low/intermediate FGF19 and high β-Klotho was linked to higher cardiovascular risk in CKD patients.
- Genetic variants in FGFR1 and KLB were independently associated with cardiovascular outcomes.
- A combined model using biomarkers, SNPs, and traditional factors achieved strong predictive accuracy (C-index = 0.80).

## Abstract

Background: Chronic kidney disease (CKD) markedly increases the risk of cardiovascular events (CVE), yet conventional biomarkers often fail to capture this excess risk. We evaluated whether circulating levels and genetic variability within the FGF19/β-Klotho/FGFR axis contribute to CV risk stratification in CKD. Methods: In 579 CKD patients, plasma FGF19 and β-Klotho concentrations were quantified, and 64 genetic variants across FGF19, KLB, FGFR1, and FGFR4 genes were analyzed. Results: Cluster analysis identified three distinct biomarker profiles, with one cluster—characterized by low/intermediate FGF19 and markedly elevated β-Klotho—showing significantly reduced CV event-free survival. After adjustment for clinical covariates, this cluster was independently associated with higher CV risk [HR = 2.97 (1.12–7.92), p = 0.029]. Two genetic variants also showed independent associations: FGFR1 rs2288696 (protective) [HR = 0.51 (0.27–0.95), p = 0.029] and KLB rs2687971 (risk-increasing) [HR = 2.03 (0.97–4.27), p = 0.046]. A combined CV risk model incorporating biomarker clusters, relevant SNPs, and traditional risk factors achieved good discriminative ability (C-index = 0.80), with the FGF19/β-Klotho cluster showing predictive importance comparable to diabetes and previous CV history. Conclusions: These results indicate that integrating FGF19-Klotho biomarkers with genetic information may improve CV risk prediction in CKD.