Associations of metabolic dysfunction-associated steatotic liver disease and cardiometabolic burden with urinary tubular biomarker abnormalities: a cross-sectional health examination study

Background Metabolic dysfunction-associated steatotic liver disease (MASLD) frequently coexists with cardiometabolic abnormalities and has been associated with kidney disease. However, its relationship with urinary markers of tubular dysfunction and the extent to which this association overlaps with accompanying cardiometabolic burden remain unclear. We examined the associations of MASLD and cumulative cardiometabolic burden with urinary tubular biomarker abnormalities in a health-examination population. Methods This cross-sectional study included 7,011 adults undergoing routine health examinations between January 2020 and December 2023. MASLD was defined by ultrasonographically detected hepatic steatosis in the presence of at least one cardiometabolic risk criterion. Urinary N-acetyl- β -D-glucosaminidase (uNAG), α 1-microglobulin (uA1M), β 2-microglobulin (u β 2M), and retinol-binding protein (uRBP) were evaluated. The primary outcome was a composite urinary tubular biomarker abnormality, defined as at least one abnormal urinary biomarker. A cardiometabolic burden score ranging from 0 to 5 was constructed from adiposity, elevated blood pressure, dysglycemia, hypertriglyceridemia, and low high-density lipoprotein cholesterol. Multivariable logistic regression with sequential covariate adjustment was used to examine the association of MASLD with the composite outcome. Cardiometabolic burden was analyzed separately without adjustment for its constituent components. Results Among 7,011 participants, 3,552 (50.7%) were classified as having MASLD. MASLD was associated with greater odds of the composite urinary biomarker abnormality after adjustment for age and sex (odds ratio [OR], 1.24; 95% confidence interval [CI], 1.11–1.39; P < 0.001). This association was attenuated after additional adjustment for measured cardiometabolic and renal characteristics (OR, 1.02; 95% CI, 0.89–1.17; P = 0.785). In separate analyses, each one-point increase in cardiometabolic burden was associated with higher odds of the composite urinary biomarker abnormality after adjustment for age and sex (OR, 1.21; 95% CI, 1.16–1.26; P < 0.001), with similar results after additional adjustment for estimated glomerular filtration rate (OR, 1.22; 95% CI, 1.16–1.27; P < 0.001). Greater cardiometabolic burden was also associated with higher concentrations of uNAG, uA1M, u β 2M, and uRBP in age- and sex-adjusted analyses. Conclusions In this cross-sectional health-examination cohort, the association between MASLD and urinary tubular biomarker abnormalities was substantially attenuated after conditioning on measured cardiometabolic characteristics, whereas greater cumulative cardiometabolic burden remained consistently associated with urinary biomarker abnormalities. These findings demonstrate substantial statistical overlap between MASLD and cardiometabolic risk but do not establish mediation or causality. Prospective studies using standardized urine collection and concentration-normalized biomarker measurements are needed to determine the temporal and prognostic significance of these associations.