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Epigenetic regulation of NAFLD: A preclinical study
For correspondence: Prof Vijay Kumar, Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110 070, India e-mail: vijaykumar98@gmail.com
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Received: ,
Accepted: ,
Abstract
Background & objectives
Non-alcoholic fatty liver disease (NAFLD) is considered as the most prevalent chronic metabolic disease, characterised by steatosis, inflammation, and metabolic dysfunctions with impaired functions of liver enzymes. The fat mass and obesity-associated gene (FTO) plays an important role in fat accumulation in hepatocytes. We investigated how FTO regulated the expression of its target genes via m6A modification leading to the pathophysiology of NAFLD.
Methods
A NAFLD mouse model was developed by feeding C57Bl/6 male mice on high-fat, high-carbohydrate (HFHC) diet supplemented with fructose and sucrose up to 24 wk. Changes in the liver histology were examined in serial sections by microscopy and immunohistochemistry, the serum parameters were monitored by bioanalyser and ELISA. Expression of hepatic murine FTO (mFTO) and metabolic gene transcripts were quantified by qPCR and mRNA sequencing. mFTO protein expression was analysed by immunohistochemistry and western blotting.
Results
The NAFLD mouse model developed steatosis, inflammation, and fibrosis at 19-24 wk, along with elevated liver enzyme levels, altered lipid profiles, and increased mFTO expression. Transcriptomic analysis identified differentially expressed genes and pathways associated with NAFLD progression. Pharmacological inhibition of mFTO by entacapone restored m6A marks on gene transcripts and reversed the NAFLD phenotype.
Interpretation & conclusions
Gene expression profiling identified key metabolic pathways and molecular targets associated with NAFLD progression. It underscored the role of mFTO in altering the m6A methylation landscape essential for establishing NAFLD and highlighted its therapeutic potential for NAFLD-associated morbidities.
Keywords
Differentially expressed genes
FTO
liver fibrosis
m6A modification
metabolic gene expression
NAFLD
Excessive nutrient intake is known to impair glucose and fat metabolism in the liver, often resulting in fat accumulation in hepatocytes which marks the onset of non-alcoholic fatty liver disease (NAFLD)1,2. It affects nearly 30.2 per cent of world population colligating with increasing obesity and other metabolic disorders3,4. NAFLD can initiate from simple steatosis, which may progress to non alcoholic steatohepatitis (NASH) with hepatocellular injury and fibrosis2,5. NASH potentially advances to cirrhosis and hepatocellular carcinoma (HCC)5. Obesity is a major risk factor for NAFLD pathogenesis1,6. As NAFLD is associated with metabolic dysfunction, it is also known as metabolic associated fatty liver disease (MAFLD)7.
NAFLD is a multifactorial disorder manifested by liver and adipose tissue dysfunction, insulin resistance, gut microbiome, environment, comorbidities, epigenetic and genetic risk factors6,8,9. Of late, m6A RNA modification has gained attention in NAFLD pathogenesis as this regulates mRNA stability, splicing, and translation of genes involved in lipid metabolism, inflammation, and fibrosis10,11. The fat mass and obesity-associated protein (FTO) has been implicated in mRNA demethylation resulting in altered gene expression and disease progression12,13.
Though NAFLD mouse models have been found useful in recapitulating the stages of NAFLD progression, the associated molecular mechanisms have eluded the researchers14-16. The present study focused on the development of a diet-induced NAFLD mouse model, validation of various anatomical and pathophysiological changes and understanding the role of FTO RNA demethylase activity in the development and progression of NAFLD.
Materials & Methods
This study was conducted by the department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi, India. All procedures involving animals were conducted during 2019 to 2022 after approval from the Institutional Animal Ethics Committee.
Development of NAFLD model and sample collection
The C57Bl/6J male mice of 5-6 wk age and weighing 17-20 g were divided into two groups: Control Group 1 (n=24) received a standard chow diet containing 11 per cent kcal fat (D12328; Open Research Diets); Experimental Group 2 was fed a high-fat, high-carbohydrate (HFHC) diet (n=30) containing 58 per cent kcal fat (Open Research Diets, USA, d - (−) - fructose (RM196), and Sucrose Hi cert (HiMedia Laboratories), supplemented with regular drinking water. Body weight was recorded on a weekly basis. The G*Power 3 software was used for calculating the number of animals to be used in our experiments work and for reproducibility of our findings.
Liver, adipose tissue and blood samples from tail vein were collected at 8, 19 and 24 wk of diet intake to cover the early, mid, and late stages of disease progression.
Tissue histology, NAFLD scoring and metabolic parameters
The formalin-fixed tissue samples were paraffin embedded, and thin section were stained with H&E to assess inflammation, steatosis, and ballooning by microscopy. Liver fibrosis was examined after staining with Sirius Red and Masson’s trichrome blue. The NAFLD activity score (NAS) and fibrosis staging of the liver was done as per Kleiner et al17 (Supplementary Table I). Serum ALT, AST, triglyceride and total cholesterol levels were determined by bioanalyser. Blood glucose levels were measured after 6 h of fasting whereas insulin levels were measured by ELISA (Elabscience, USA).
Western Blotting and immunoprecipitation
Liver tissues were lysed in RIPA buffer containing HaltTM protease inhibitor cocktail (Thermo Fisher, USA) and protein samples (∼100 g) were processed for Western blotting and immunoprecipitation as described previously18.
RNA isolation and RT-qPCR
Total RNA was extracted from the liver using TRIzol reagent (G-Biosciences, USA) and RT-qPCR was performed18 using specific oligonucleotide primers (Supplementary Table II). The m6A content in total RNA using an m6A RNA methylation quantification kit (Epigentek, USA) and its relative abundance of m6A mRNAs was determined by qRT-PCR.
Transcriptomic analysis
Total hepatic RNA was used for preparing mRNA library using the Qiagen mRNA library kit (Qiagen, Germany) and sequenced on the IlluminaHiseq 4500/Novaseq platform. The RNA-seq read alignment was carried out using the STAR aligner (version 2.7.10b) against the reference mouse genome assembly from NCBI. The Benjamini-Hochberg false discovery rate (FDR) correction was applied to all RNA-seq differential expression analyses to control for multiple hypothesis testing. Further, genes with an adjusted P-value (FDR) <0.05 were considered statistically significant and used for pathway enrichment analyses.
Statistical analyses
All datasets were assumed to follow a normal distribution, and all physiological parameters were analysed by GraphPad Prism 8.0 Software. One-way ANOVA corrected for multiple comparisons (Tukey’s test) was used to evaluate blood glucose and insulin concentrations whereas two-way ANOVA corrected for multiple comparisons (Sidak’s test) was used to analyse changes in gene expression between groups. All data are presented as mean±SEM and Student’s t-test was used to find the significance level at P<0.05.
Results
HFHC diet induces hepatic injury and metabolic dysfunctions in mice
Mice fed on HFHC diet were obese with white adipose tissue around the lower abdominal region and had enlarged liver as compared to control mice. The body weight and liver index score of HFHC-fed mice showed a significant progressive increase (Supplementary Figs. 1A and B). The animals also exhibited glucose intolerance at 16 and 21 wk (Fig. 1A) with impaired insulin sensitivity at 17 and 22 wk (Fig. 1B). The liver enzymes ALT and AST, triglycerides, and total cholesterol were high in peripheral blood (Figs. 1C-F), whereas adiponectin level was low and leptin and FTO levels were elevated (Fig. 1G).
- Metabolic and biochemical parameters of the NAFLD model. C57/BL6J mice were fed on chow diet (n=24) or HFHC diet (n=30) and changes in (A) fasting blood glucose and (B) insulin were measured at indicated weeks. Changes in the serum levels of (C) ALT, (D) AST, (E) triglycerides and (F) cholesterol, were measured at 8, 19 and 24 wk. The plasma levels of (G) mFTO were also measured in both groups of mice. Data are expressed as the mean±SEM. One-way ANOVA followed by Tukey’s post-hoc analysis was used for group comparisons. Level of significance: ns, non-significant; non-significant. P *< 0.05; ***< 0.001; ****< 0.0001.
Sequential progression of steatosis, steatohepatitis, and fibrosis in the HFHC mice
Long-term HFHC diet intake induced significant metabolic, biochemical, and histological changes in the liver and adipose tissue. Liver sections showed grade 1steatosis and inflammation at 8 wk, moderate (20-60%, grade 2) at 19 wk and severe (>60%, grade 3) at 24 wk, accompanied by hepatocyte ballooning, indicative of NASH (Figs. 2A-C).The progressive fat accumulation was confirmed by Oil Red O staining whereas pericellular fibrosis was revealed by Picrosirius Red staining at 19 and 24 wk. White adipose tissue exhibited inflamed and dysfunctional adipocytes, and immune cell infiltration (data not shown). The NAFLD activity scores indicated NAFL (scores 1-2) at 8 wk, NASH (scores 2-5) at 19 wk, and advanced NASH (scores 4-8) at 24 wk (Fig. 2D). The fibrosis scores were 1a and 1b at 19 and 24 wk, respectively (Fig. 2E) suggesting disease progression from steatosis to advanced NASH as observed in NAFLD patients.
- Histological assessment of the liver and adipose tissues of NAFLD model. Haematoxylin and eosin (H&E) staining of (A) liver tissue sections of corresponding mice at 0, 8, 19 and 24 wk. Liver sections of different time points were also stained with (B) oil red O or (C) Sirius red. Red arrows show micro and macro vesicular steatosis in hepatocytes with lobular ballooning whereas the black arrows show hepatocellular infiltration of inflammatory cells. Outlines of the pericellular or perivenular or perisinusoidal fibrosis are shown at 19 and 24 wk after Sirius red staining. The (D) NAFLD activity score and (E) fibrosis staging of the liver from the above images were also recorded. All images were captured at 200x magnification. Level of significance=ns, non-significant. P ****< 0.0001.
HFHC diet-induced the expression of FTO gene in mice
As epigenetic mechanisms may have a role in NAFLD, we next analysed the hepatic expression of epigenetic regulator FTO (m6A eraser) in the HFHC mice. There was a significant increase in the expression of mFTO mRNA at 19 and 24 wk as compared to control group (P<0.0001, Fig. 3A). Western blot and immunohistochemical analyses also confirmed increased expression of mFTO protein in the liver (Figs. 3B and C). These observations suggested the involvement of FTO in NAFLD progression.
- Hepatic expression of mFTO gene in the NAFLD model. (A) Paraffin sections of the control (n=8 per time point) and HFHC mouse liver (n=10 per time point) collected at 8, 19 and 24 wk and staining with anti-FTO antibody and images were captured at 200x magnification. (B) Western blot analysis of hepatic expression of mFTO protein expression at indicated time points. Fold change in protein levels was quantified using the ImageJ software and are shown below in the upper panel. Beta-actin was used as internal control. (C) Total RNA was isolated from the liver tissues of both control and HFHC mice were collected at different time periods and the expression of mFTO mRNA was measured by RT-qPCR. Data are expressed as bar graph±SEM and analysed using one-way ANOVA (Dunnett’s multiple comparisons test). Level of significance: ns, non-significant. P ****< 0.0001.
Identification and clustering of differentially expressed genes (DEGs)
We next performed high throughput transcriptomic profiling of hepatic genes expressed during NAFLD progression and also identify potential therapeutic targets. Liver samples of four age groups of HFHC mice, viz., control (baseline), early stage (8 wk, Group 8), mid-stage (19 wk, Group 19), and late-stage (24 wk, Group 24) were used for data acquisition. Principal component analysis (PCA) showed four distinct clusters of differentially expressed genes (DEGs) (Supplementary Fig. 2A). Hierarchical clustering corroborated PCA findings and showed separate clusters for each group (Supplementary Fig. 2B). The number of DEGs increased with disease progression, viz., Group 8 had 1,015 DEGs (553 upregulated, 462 downregulated), Group 19 showed 1,109 DEGs (641 up, 468 down), and Group 24 displayed 1,840 DEGs (1,126 up, 714 down) suggesting the complexity of NAFLD-associated changes during disease progression (Supplementary Fig. 2C). These results emphasised the temporal dynamics of NAFLD progression and increasing complexity of transcriptomic alterations.
Analysis of the enriched DEGs and their biochemical pathways
Unsupervised clustering of DEGs at 24-wk (Supplementary Fig. 3) showed deregulation of pathways linked to glucose metabolism (IRS2, PCK1, ADIPOQ, LEP), lipid transport (PPARγ, CD36, and LEP), insulin signalling (IRS2, PCK1, G6PC, LEP, IL-1, and CD36) and cholesterol metabolism (CD36, APOC3, APOA4, and APOB) underscoring the multifactorial progression of NAFLD and suggested a positive correlation between metabolic gene dysregulation and the pathophysiology of NAFLD. The KEGG pathway analysis of 24 wk RNAseq data identified 31 altered pathways including upregulation of PPAR, phospholipase D, phosphatidylinositol, Ras, chemokine, metabolic pathways, lipids and atherosclerosis, and downregulation of ribosomal pathways, cholesterol metabolism, AMPK and FOXO signalling (data no shown).
The interaction network of DEGs identified 37 metabolic biomarkers strongly associated with five major metabolic disorders, viz., hyperglycaemia, hyperinsulinemia, lipodystrophy, fatty liver disease, and metabolic acidosis involved in NAFLD (Supplementary Fig. 4). Transcription factor (TF) enrichment analysis based on TRRUST v2 (https://www.grnpedia.org/trrust)19 identified specific TFs that drive the expression of genes involved in lipid metabolism, de novo lipogenesis, and fatty acid oxidation such as SREBF1, HNF4A, FOXO1, NFKB1, ETS2, SIRT1, FOSL1, NR1I3, RUNX3, HNF1A, USF2, NFE2L2, RXRA, ATF2, NRF1, and ETV2 (Supplementary Fig. 5).
Validation of DEGs
TheRNA-seq data were also validated by RT-qPCR using hepatic RNA samples isolated at 8, 19 and 24 wk. There was a progressive increase in gluconeogenesis-related genes20,21 with G6PC and PCK1 showing nearly 6- and 4-fold increase, respectively at 24 wk whereas FOXO1, a key regulator of gluconeogenesis and adipocyte differentiation22, was overexpressed at 19 and 24 wk (Fig. 4A and data not shown). Expression of PPARγ - a key regulator of adipogenesis and adipocyte function23, showed no change. Among lipid metabolism-related genes, FABP1 and FABP4 expressions were consistently high at 8 wk whereas SCP-2 expression, a cholesterol transporter24, remained unchanged (data not shown). Other fat metabolism genes, including DGAT1, DGAT2, CD36, and CPT1a, were significantly upregulated at 24 wk (Fig. 4B). Among pro-inflammatory mediators, TNF-α expression was significantly elevated at 24 wk whereas NF-κB was elevated at 8 wk, but declined later on (Fig. 4C and data not shown). These findings suggest that high fat diet significantly influenced the expression of metabolism-associated genes in the NAFLD model.
- Validation of differentially expressed genes in the liver of NAFLD mouse model. Liver tissues of both control (n=8 per time point) and HFHC mice (n=10 per time point) were collected at 24 wk and the total RNA was isolated and the expression of genes associated with (A) gluconeogenesis, (B) fat metabolism, (C) liver-specific transcription factors, inflammation, and liver fibrosis were measured by RT-qPCR. The relative gene expression was normalised with GAPDH levels. Data are expressed as bar graph±SEM and analysed using two-way ANOVA (Sidak’s multiple comparison tests). Level of significance=ns, non-significant. P ***<0.001; ****<0.0001.
Downregulation of m6A marks in the metabolic gene transcripts
As m6A modification in gene transcripts plays an important role in disease processes25,26, we also measured the levels of m6A marks after immunoprecipitating hepatocellular RNA. As shown in Fig. 5A, the global m6A level was significantly downregulated at 8, 19, and 24 wk which apparently correlated with elevated mFTO expression (Fig. 3). As expected, there was a significant reduction in m6A levels in transcripts of key metabolic and fibrotic genes including FATP5, CD36, DGAT1, DGAT2, FABP1, CPT1a and CPT1b (Fig. 5B) known to facilitate fatty liver disease. A significant reduction in m6A mark was also observed in the transcripts of gluconeogenesis and inflammatory genes G6PC, PKC1, FBP1, SREBP1, PPARg, IL-1beta and TNF-a and transcription factors (FOXO1 and STAT3) (Figs. 5C and D). Pharmacological inhibition with entacapone27 normalised the pathophysiology of NAFLD (Supplementary Figs. 6A and B), reduced FTO expression (Supplementary Fig. 6C), and restored global m6A modification (Supplementary Fig. 6D). Under these conditions, no toxicity in the liver or other major organs of the NAFLD mice, such as kidney, lung, kidney, heart and spleen was observed (Supplementary Fig. 7). These observations established the role of FTO in metabolic gene expression associated with NAFLD progression via m6A modification.
- m6A methylation in the hepatic gene transcripts of the NAFLD model. Liver tissues of both control (n=8 per time point) and HFHC mice (n=10 per time point) were collected at 8, 19 and 24 wk and the total RNA was isolated. Total m6A level was measured by (A) colorimetric quantification method and m6A specific mRNA was isolated using m6A antibody. RT-qPCR was done using specific gene primer sets and SYBR green PCR master mix to detect the relative expression of (B) fat metabolism genes, (C) gluconeogenesis genes and (D) inflammation and fibrosis-related genes and liver-specific transcription factors. The relative RNA expression was normalised with input levels. Data are expressed as bar graph±SEM and analysed using ordinary one-way ANOVA (Dunnett’s multiple comparisons test) in case of A or two-way ANOVA (Sidak’s multiple comparison tests) for B-D. Level of significance=ns, non-significant. P *<0.01; ***<0.001; ****<0.0001.
Discussion
Epigenetic modifications of mRNAs, particularly N6-methyladenosine (m6A) methylation, are increasingly recognised as critical regulators of transcript stability, splicing, and translation in various biological processes, including lipid metabolism, inflammation, and fibrogenesis10,11. Given the complexity and heterogeneity of NAFLD, the understanding of epitranscriptomic regulation of genes involved in disease progression is crucial for developing precise therapeutic interventions. In this study, we developed a NAFLD mouse model using HFHC diet. The animals exhibited obesity, liver injury, dyslipidaemia, and insulin resistance and closely mimicked the human NAFLD/NASH pathophysiology. The model showed a significant increase in body weight, liver index scores, and metabolic impairments (Fig. 1 and Supplementary Fig. 1), suggesting a profound metabolic impact of long-term consumption of HFHC diet. Liver histology revealed progression from mild to severe steatosis, lobular inflammation, and hepatocyte ballooning, culminating in liver damage with development of perisinusoidal fibrosis within 24 wk. Adipose tissue inflammation further indicated systemic metabolic dysfunction associated with diet (Fig. 2).
The hepatic transcriptomic analysis of the NAFLD model provided a deeper insight into disease pathophysiology and identified both stable and dynamic differences in gene expression that occur during NAFLD progression. Further, it suggested a dynamic nature of disease progression since the DEGs were majorly associated with metabolic pathways, including fatty acid synthesis, cholesterol metabolism, insulin signalling, glucose metabolism, inflammation, collagen formation, and m6A demethylation (Supplementary Figs. 2 and 3). We also observed marked upregulation of mFTO-1 both at protein and mRNA levels (Fig. 3) suggesting its epigenetic regulatory role in NAFLD pathogenesis through m6A demethylation10,11. The published RNA-seq data from the human NAFLD cohorts (e.g., the NASH Clinical Research Network) also suggest dysregulation of RNA methylation-related pathways, including altered FTO expression and m6A methylation patterns, which align with our findings in the NAFLD model. As reported earlier, FTO suppressed the PPARα mRNA levels and impaired fatty acid oxidation which contributed to hepatic steatosis28. FTO also enhanced transcription factor SREBP1C to promote lipid droplet formation in adipocytes29. FTO is known to regulate adipogenesis through transcription factor RUNX1T1 in an m6A-dependent manner30. Heatmap and KEGG analyses of DEGs in the NAFLD model revealed upregulation of several pathways involved in NAFLD progression (Supplementary Figs. 3-5). It is well recognised that fatty acid translocase CD36 facilitates free fatty acid uptake and regulates the hepatic lipogenic programme via SREBP1, contributing to NAFLD pathogenesis31. The FTO-regulated genes such as SREBP1, CD36, and PPARα are also reported to be up-regulated in transcriptomic datasets from the human NASH liver biopsies and have been cited as biomarkers of disease severity and progression32. Genes involved in glucose, insulin and lipid metabolism and their transport exhibited enhanced expression (Supplementary Fig. 3). Transcription factors such as FOXO1 and NF-κB1 (Fig. 4) are also involved in lipid metabolism, inflammation, and fibrosis, highlighting their critical roles in NAFLD progression33. The elevated expression of lipid metabolism and gluconeogenesis genes, such as FABP1, FABP4, CD36, CPT1a, CPT1b G6PC, PCK1. DGAT1 and DGAT2 at 24 wk (Figs. 4 and 5) suggested a transition to NASH with more hepatic inflammation and fibrosis potentially exacerbating liver pathology34.
To conclude, our data provide compelling evidence that the FTO-m6A regulatory axis plays a central role in NAFLD/NASH pathogenesis. Pharmacological inhibition of FTO using entacapone effectively reversed the metabolic and histological abnormalities in our model27 (Supplementary Fig. 8), highlighting its therapeutic potential. These results highlight FTO not only as a mechanistic driver of NAFLD progression but also as a clinical therapeutic target, with FTO-linked m6A signatures offering promise as novel non-invasive biomarkers for the diagnosis, disease monitoring, and treatment stratification of NAFLD/NASH.
Financial support & sponsorship
This study received funding support from J.C. Bose National Fellowship, Department of Science and Technology, Government of India, New Delhi (Grant No. SR/S2/JCB-80)/2012) granted to corresponding author (VK)
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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