Dataset Information

Hepatic transcriptome profiling reveals early signatures associated with disease transition from non-alcoholic steatosis to steatohepatitis.

ABSTRACT:

Background and aim

Non-alcoholic fatty liver disease (NAFLD) is becoming a leading cause of chronic liver disease worldwide. The molecular events that influence disease progression from non-alcoholic fatty liver (NAFL) to aggressive non-alcoholic steatohepatitis (NASH) remain incompletely understood, leading to lack of mechanism-based targeted treatment options for NASH. This study aims to identify early signatures associated with disease progression from NAFL to NASH in mice and humans.

Materials and methods

Male C57BL/6J mice were fed a high-fat, -cholesterol, and - fructose (HFCF) diet for up to 9 months. The extent of steatosis, inflammation, and fibrosis was evaluated in liver tissues. Total RNA sequencing (RNA-seq) was conducted to determine liver transcriptomic changes.

Results

After being fed the HFCF diet, mice sequentially developed steatosis, early steatohepatitis, steatohepatitis with fibrosis, and eventually spontaneous liver tumor. Hepatic RNA-seq revealed that the key signatures during steatosis progression to early steatohepatitis were pathways related to extracellular matrix organization and immune responses such as T cell migration, arginine biosynthesis, C-type lectin receptor signaling, and cytokine-cytokine receptor interaction. Genes regulated by transcription factors forkhead box M1 (FOXM1) and negative elongation factor complex member E (NELFE) were significantly altered during disease progression. This phenomenon was also observed in patients with NASH.

Conclusions

In summary, we identified early signatures associated with disease progression from NAFL to early NASH in a mouse model that recapitulated key metabolic, histologic, and transcriptomic changes seen in humans. The findings from our study may shed light on the development of novel preventative, diagnostic, and therapeutic strategies for NASH.

SUBMITTER: Magee N

PROVIDER: S-EPMC9977163 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Hepatic transcriptome profiling reveals early signatures associated with disease transition from non-alcoholic steatosis to steatohepatitis.

Magee Nancy N Ahamed Forkan F Eppler Natalie N Jones Elizabeth E Ghosh Priyanka P He Lily L Zhang Yuxia Y

Liver research (Beijing, China) 20221122 4

<h4>Background and aim</h4>Non-alcoholic fatty liver disease (NAFLD) is becoming a leading cause of chronic liver disease worldwide. The molecular events that influence disease progression from non-alcoholic fatty liver (NAFL) to aggressive non-alcoholic steatohepatitis (NASH) remain incompletely understood, leading to lack of mechanism-based targeted treatment options for NASH. This study aims to identify early signatures associated with disease progression from NAFL to NASH in mice and humans. ...[more]

PMID: 36864891

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Project description:BackgroundThis study aims to identify early metabolomic biomarkers of gestational diabetes mellitus (GDM) and evaluate their association with hepatic steatosis.MethodsWe compared maternal serum metabolomic profiles between women who developed GDM (n = 118) and matched controls (n = 118) during the first (10-14 gestational weeks) and second (24-28 gestational weeks) trimesters using ultra-performance liquid chromatography coupled with mass spectrometry. Mediation analysis was performed to evaluate the mediating role of metabolic dysfunction-associated steatotic liver disease (MASLD) in the relationship between metabolites and subsequent development of GDM. A refined prediction model was developed to predict GDM using established clinical factors and selected metabolites.ResultsSignificant alterations in circulating metabolites, including amino acids, bile acids, and phospholipids, were observed in the GDM group compared to controls during early pregnancy. Mediation analysis revealed that several metabolites, including glycocholic acid (proportion mediated (PM) = 31.9%), butanoyl carnitine (PM = 25.7%), and uric acid (PM = 22.4%), had significant indirect effects on GDM incidence mediated by hepatic steatosis. The refined prediction model composed of clinical factors and selected metabolites in the first trimester demonstrated higher performance in predicting GDM development than the established prediction model composed solely of clinical factors (AUC, 0.85 vs. 0.63, p < 0.001).ConclusionsWomen who developed GDM exhibited altered metabolomic profiles from early pregnancy, which showed a significant correlation with GDM, with MASLD as a mediator. Selected metabolomic biomarkers may serve as predictive markers and potential targets for early risk assessment and intervention in GDM.Research insightsWHAT IS CURRENTLY KNOWN ABOUT THIS TOPIC?: Gestational diabetes mellitus (GDM) is a common pregnancy complication with significant health risks. Early identification of women at high risk for GDM is crucial for timely intervention and improved outcomes. WHAT IS THE KEY RESEARCH QUESTION?: What alterations in circulating metabolites during early pregnancy are associated with subsequent GDM development? Does metabolic dysfunction-associated steatotic liver disease (MASLD) mediate the association between specific metabolites and GDM risk? WHAT IS NEW?: Significant alterations in bile acids, amino acids, phosphatidylethanolamines, and phosphatidylinositols were observed in early pregnancy sera of women who later developed GDM. MASLD significantly mediated the effects of several metabolites on GDM risk, with mediation proportions ranging from 9.7 to 31.9%. A refined prediction model composed of clinical factors and metabolites significantly improved the performance in predicting GDM development. HOW MIGHT THIS STUDY INFLUENCE CLINICAL PRACTICE?: These results provide new insights into early metabolic alterations associated with GDM development and highlight the potential mediating role of MASLD. This comprehensive metabolomic approach may contribute to the development of improved risk prediction models and targeted interventions for GDM prevention.

Dataset Information

Hepatic transcriptome profiling reveals early signatures associated with disease transition from non-alcoholic steatosis to steatohepatitis.

Background and aim

Materials and methods

Results

Conclusions

Publications

Hepatic transcriptome profiling reveals early signatures associated with disease transition from non-alcoholic steatosis to steatohepatitis.

Similar Datasets

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