Objective:

To explore the relationship between circadian rhythm disruption and Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and identify potential protein biomarkers for predicting MASLD risk, which could enhance early detection and treatment strategies.

Key Findings:

• Lower RA was significantly associated with a higher prevalence of MASLD (crude OR = 2.61; 95% CI [2.42, 2.81]; adjusted OR = 1.15; 95% CI [1.02, 1.31]).
• Eighteen candidate proteins were identified as potential biomarkers for RA-related MASLD.
• The 18-protein model demonstrated high predictive capability with AUC values exceeding 0.94 across various machine learning techniques.

Interpretation:

The study confirms that lower RA is independently linked to MASLD and highlights 18 overlapping plasma proteins as promising biomarkers for predicting RA-related MASLD, suggesting avenues for future research and clinical applications.

Limitations:

• The study relies on observational data, which may limit causal inferences.
• Potential confounding factors not accounted for in the analysis could affect results.
• Findings may not be generalizable beyond the UK Biobank population.

Conclusion:

The findings suggest that monitoring circadian rhythm through RA and the identified protein biomarkers could provide new avenues for predicting and potentially treating MASLD.