Associations between systemic inflammatory biomarkers and metabolic dysfunction associated steatotic liver disease: a cross-sectional study of NHANES 2017-2020.

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a primary cause of chronic liver disease, with potential progression to cirrhosis and hepatocellular carcinoma (HCC). Although systemic inflammatory biomarkers are associated with liver diseases, their specific role in MASLD remains unclear. This study examines the association between systemic inflammatory biomarkers and MASLD.

METHODS

This cross-sectional study enrolled 6613 adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) spanning from 2017 to March 2020. Among these participants,, 34.67% were aged 40-59 years, 50.85% were female, and 63.26% were Non-Hispanic White. We investigated 10 inflammatory biomarkers: ALI, SIRI, SII, SIPS, IBI, NLR, PLR, CAR, LMR, and PNI. Logistic regression models were performed to assess the linear association between systemic inflammatory biomarkers and MASLD. Restricted cubic spline (RCS) regression was employed to explore potential nonlinear relationships between biomarkers and MASLD risk. Additionally, subgroup analyses were conducted to examine the influence of various demographic and clinical characteristics on the observed associations.

RESULTS

After adjusting for key confounders, NLR and PLR exhibited negative association with MASLD risk, while ALI, CAR, and PNI exhibited the opposite association (P < 0.05). Most biomarkers, including ALI, SIRI, IBI, CAR, LMR, and PNI, exhibited significant non-linear correlations with MASLD (P < 0.05). Subgroup analyses revealed substantial age-related differences in the association between ALI and MASLD risk, as well as varying relationships between PNI and MASLD risk across various cardiovascular outcomes (P < 0.05).

CONCLUSION

Systemic inflammatory biomarkers are significantly associated with MASLD risk. Large-scale prospective studies are warranted to confirm these findings and elucidate the underlying mechanisms.