Incident chronic kidney disease risk and the predictive value of the uric acid-to-HDL ratio in lean and non-lean MASLD: a prospective cohort and multi-omics study.

BACKGROUND

Although metabolic dysfunction-associated steatotic liver disease (MASLD) is an independent risk factor for chronic kidney disease (CKD), validated clinical markers for individualized renal risk stratification remain limited, especially in lean patients. Therefore, we aimed to evaluate an accessible index to predict this risk and explore the underlying pathophysiological mechanisms.

METHODS

We investigated incident CKD risk among UK Biobank participants across a biomarker-based FLI cohort (N = 353,325) and an imaging-based MRI-PDFF cohort (N = 33,155). The participants with MASLD were stratified into lean and non-lean groups. We then evaluated uric acid to HDL ratio (UHR) as a continuous proxy to assess metabolic-related renal risk, and integrated Mendelian randomization (MR), plasma proteomics, and single-cell RNA sequencing to identify circulating mediators.

RESULTS

While non-lean MASLD consistently increased CKD risk, the risk in lean MASLD differed by metabolic status. FLI-defined lean MASLD, characterized by severe metabolic abnormalities, predicted a higher incident CKD risk, whereas MRI-defined lean MASLD with milder metabolic traits showed no such association. Furthermore, UHR showed a dose-response relationship with CKD and provided better predictive value than the TyG index. MR analyses revealed that MASLD increases CKD risk indirectly through metabolic burden. Integrative multi-omics analyses suggested AHSG and CPB2 as potential circulating markers of this metabolic-renal axis.

CONCLUSIONS

In MASLD, the severity of systemic metabolic burden is a key determinant of incident CKD risk across both lean and non-lean individuals. To quantify this burden, UHR serves as a robust continuous proxy that provides better renal risk stratification than the TyG index for both lean and non-lean patients. Furthermore, AHSG and CPB2 represent potential circulating biomarkers for this metabolic-renal link.