Interdisciplinary

Fatty liver disease ages differently than healthy livers at molecular level

How the science connects

Gene expressionAgingFatty liver disease

AI Insight

This study analyzed liver gene expression data from 1,354 samples to investigate how metabolic dysfunction-associated steatotic liver disease (MASLD) affects molecular aging patterns. Researchers found that MASLD creates disease-specific aging trajectories distinct from normal liver aging, with only 22 genes overlapping between the two groups and some showing opposite trends. The disease-related aging changes involved disrupted protein regulation, cellular stress responses, and p53-mediated cell death pathways, rather than simply accelerating normal aging processes.


These findings suggest that MASLD requires disease-specific therapeutic strategies rather than general anti-aging interventions, and that age-stratified risk assessment tools for MASLD should account for distinct molecular trajectories at different life stages, particularly around ages 35 and 75 where trajectory changes were observed.


Understand the Science

by Tanchun Wang, Qin Huang, Yan Wang, Cong Li, Juan Ni, Fang Xie

Background

Age-related molecular trajectories of metabolic dysfunction-associated steatotic liver disease (MASLD) remain insufficiently characterized, limiting age-stratified risk assessment and intervention.

Objective

To test whether MASLD-related molecular changes with age merely reflect accelerated physiological aging or represent a disease-specific divergence.

Methods

We utilized public transcriptomic data from normal liver and MASLD samples to identify differential transcriptomic signals. We employed Spearman correlation analysis and generalized additive models (GAM) for nonlinear age-related trajectory modeling, and functional enrichment analysis for signaling pathway characterization.

Results

We integrated 1,354 public liver transcriptome samples from GEO and GTEx databases to construct a cross-age cohort. Differential expression and age-correlation analyses showed minimal overlap (only 22 genes) between age-associated genes in MASLD and controls, with some genes displaying opposite age-related trends. GAM identified four major expression patterns in MASLD—stable, early-life change, late-life acceleration, and mid-life fluctuation—with trajectory inflection time points around ages ~35 and ~75. Functional enrichment indicated that control age-associated genes mainly involved classical cell cycle processes, whereas MASLD changes were enriched for protein deubiquitination, proteostasis imbalance, and p53-related stress and apoptotic signaling. Many MASLD age-associated genes were also associated with fibrosis stage or NAS, largely in concordant directions.

Conclusion

MASLD exhibits disease-specific age-related transcriptional remodeling characterized by dysregulation of proteostasis and deubiquitination pathways, activation of cellular stress-response programs, and enrichment of p53-associated apoptotic signaling, rather than a simple acceleration of physiological aging.

Source: Integrated liver transcriptomic data reveal differences in aging-associated regulation between metabolic dysfunction-associated steatotic liver disease and normal liver aging