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Mouse Model of Metabolic Dysfunction-Associated Steatotic Liver Disease with Fibrosis
Published on: July 18, 2025
Fatty Liver Index as an Upstream Marker of Glycaemic and Cardiometabolic Dysregulation Preceding MASLD: Evidence From
Hongmei Zhang1, Yifan Hu2, Jiajie Cai1
1West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Objective:
Metabolic dysfunction-associated fatty liver disease (MASLD) is reversible in the preclinical metabolic stage. However, the temporal interactions between hepatic steatosis and cardiometabolic abnormalities remain poorly understood.
Research Design And Methods:
This longitudinal study included 4186 participants from the China Multi-Ethnic Cohort (CMEC) and 2620 participants from the UK Biobank (UKB) with data available at both baseline and follow-up. Hepatic steatosis was assessed using the Fatty Liver Index (FLI). Cardiometabolic risk factors, including blood pressure, blood glucose and lipid profiles, were measured at both time points. Cross-lagged panel network analysis was applied to construct temporal networks linking hepatic steatosis and cardiometabolic factors. Centrality metrics, including out-expected influence (Out-EI), in-expected influence (In-EI), and bridge-expected influence (Bridge-EI), were used to identify key nodes within the networks.
Results:
Across both cohorts, pathways from baseline FLI to subsequent blood pressure and blood glucose predominated over reverse pathways (β FLI → SBP = 0.079 versus β SBP → FLI = 0.016; β FLI → FBG = 0.056 versus β FBG → FLI = 0.022 in CMEC, and β FLI → SBP = 0.046 versus β SBP → FLI = 0.000; β FLI → FBG = 0.018 versus β FBG → FLI = -0.005 in UKB), suggesting that hepatic steatosis was more strongly associated with subsequent elevations in these cardiometabolic factors during the preclinical metabolic stage of MASLD. Centrality analyses indicated that FLI occupied a relatively upstream and central position within the temporal network, with consistently high Out-EI and Bridge-EI in both CMEC and UKB (FLI Out-EI = 0.344 and Bridge-EI = 0.344 in CMEC; Out-EI = 0.209 and Bridge-EI = 0.209 in UKB). In contrast, Fasting Blood Glucose (FBG) primarily functioned as a downstream affected node, exhibiting higher In-EI (FBG In-EI = 0.189 in CMEC; 0.159 in UKB).
Conclusions:
FLI emerged as an upstream and central marker of metabolic dysregulation in the preclinical metabolic stage of MASLD, whereas FBG appeared to represent a downstream manifestation. Our findings clarify the temporal dynamics of metabolic dysregulation in this stage and highlight FLI as a potential priority marker for early screening.
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