A new dietary rat model fully recapitulates metabolic dysfunction-associated steatotic liver disease pathophysiology and mimics human disease with advanced liver fibrosis and portal hypertension

A new dietary rat model fully recapitulates metabolic dysfunction-associated steatotic liver disease pathophysiology and mimics human disease with advanced liver fibrosis and portal hypertension | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A new dietary rat model fully recapitulates metabolic dysfunction-associated steatotic liver disease pathophysiology and mimics human disease with advanced liver fibrosis and portal hypertension Joan Genescà, Maria Martinez, Aurora Barberá, Imma Raurell, M Serra Cusidó, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6376882/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Apr, 2026 Read the published version in Lab Animal → Version 1 posted You are reading this latest preprint version Abstract Background and Aims: For decades, investigators have pursued the development of a comprehensive rodent model that fully recapitulates the pathophysiology of metabolic dysfunction-associated steatotic liver disease (MASLD) pathophysiology and mimics human disease. Dietary models are considered the most reliable in terms of reproducing human disease; however, no dietary rodent model has been reported in the proximity of human MASLD, allowing the study of the pathophysiology and treatment strategies for advanced fibrosis and portal hypertension. Approach and Results: We conducted a multistep process of continuous sequential refinement of our MASLD model in rats until we achieved a comprehensive model that reproduced the clinical features of metabolic syndrome, steatohepatitis, advanced fibrosis, and portal hypertension with a transcriptomic profile resembling human MASLD. The final model consisted of a 20-week high-fat diet with high concentrations of cholesterol (2%) and a glucose-fructose beverage, to which adding cholic acid at low concentrations (0.1%) substantially increased the percentage of individuals achieving significant fibrosis at the endpoint. Conclusions Owing to its short duration, simplicity, versatility, and proximity to human MASLD, the proposed model could potentially serve a wide range of investigators working in the field of metabolism and liver disease, allowing significant advances in mechanistic insights into drug development. Health sciences/Gastroenterology/Hepatology/Liver diseases/Non-alcoholic fatty liver disease Health sciences/Diseases/Gastrointestinal diseases/Liver diseases/Liver fibrosis animal models metabolic dysfunction-associated liver disease MASLD steatohepatitis MASH liver fibrosis portal hypertension Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. INTRODUCTION Steatotic liver disease (SLD) is an emerging form of chronic liver disease that is growing rapidly worldwide and is largely driven by epidemics of metabolic syndrome 1 . Metabolic dysfunction-associated SLD (MASLD), the most common form of SLD, is currently reaching an estimated prevalence of 38% in the global adult population 2 . The more advanced form of MASLD, known as metabolic dysfunction-associated steatohepatitis (MASH), is associated with liver inflammation and hepatocellular injury 3 . Individuals with MASH are at a significantly higher risk of developing progressive liver fibrosis and cirrhosis, liver and non-liver clinical events, and hepatocellular carcinoma 4 . The use of animal models is crucial for understanding the underlying mechanisms involved in the onset and progression of MASLD and for developing innovative therapeutic strategies 5 . However, most current models do not accurately reproduce advanced human liver diseases, including significant liver fibrosis, portal hypertension, and associated metabolic factors, such as obesity and dyslipidemia 6 . Consequently, the available animal models for MASLD serve different purposes and have varying degrees of clinical relevance 7 . The ability of genetic and toxic models to investigate the pathophysiology of MASLD in a relatively physiological manner is impaired 8 – 10 . To achieve a clinical representation of MASLD, dietary interventions mimicking Western diets are currently the most effective approach 6 . Diet-induced models involve a wide range of dietary regimens, including variations in fat content, sources of fat, cholesterol levels, and additional supplements like cholic acid 11 . Diets with moderately elevated fat, high fructose, and dietary cholesterol can closely replicate human western diets and induce MASLD 12 . Accordingly, our research group developed an 8-week rat model using a high-fat diet combined with a glucose-fructose beverage (HFGFD) 13 . This model exhibited all histological characteristics of MASLD and metabolic syndrome features, including obesity and insulin resistance, in addition to mild portal hypertension. However, a significant drawback is the absence of liver fibrosis, which limits its applicability for advanced MASLD research. Since then, we have undertaken several steps to modify and improve our model to accurately replicate the full MASLD phenotype observed in human diseases. Herein, we present a summary of the sequential models developed and tested to generate a translational model of MASLD that encompasses all relevant features of MASLD, advanced fibrosis, and portal hypertension. 2. MATERIALS AND METHODS 2.1. Animals and diet The study was conducted following the ARRIVE guidelines for reporting in vivo experiments (Supplementary Data). Three rat models of MASLD were developed sequentially with variations in diet and additional factors until the ultimate model encompassed metabolic syndrome, steatohepatitis, advanced fibrosis, and portal hypertension (Fig. 1). All three study models were developed using male Sprague-Dawley rats (Charles River Laboratories, L´Abresle, France) weighing 200-220 g at the beginning of the experiments. Animals were housed under a 12-hour light/dark cycle at constant temperature (24 ± 1 °C) and relative humidity (55 ± 10%). Body weight, and food and drink consumption were monitored weekly. In STUDY-1, all rats were fed a high-fat glucose/fructose diet (HFGFD) for 24 weeks, comprising 30% fat (butter, coconut oil, palm oil, beef tallow) with mainly saturated fatty acids (5.73 kcal/g; Ssniff Spezialdiäten GmbH, Soest, Germany), supplemented with 1 g/kg (0.1%) Chol and combined with a glucose-fructose beverage (110 g/L, 45% glucose and 55% fructose). From weeks 4 to 24, the rats were divided into two groups (Fig. 1): the double-hit group, which received additional intraperitoneal injections of 0.5 mg/kg LPS twice a week (D1-MASLD+LPS, n = 8), and a group that received only the HFGFD (D1-MASLD, n = 13). In STUDY-2, rats had ad libitum access to a new diet for 16 and 24 weeks (D2-MASLD, n = 12 and n = 8, respectively), consisting of 30% fat (including butter, coconut oil, palm oil, and beef tallow), predominantly composed of saturated fatty acids, supplemented with 20 g/kg (2%) Chol and 5 g/kg (0.5%) CA (5.62 kcal/g; Ssniff Spezialdiäten GmbH, Soest, Germany). This diet was combined with a glucose-fructose beverage (110 g/L, 45% glucose, and 55% fructose) to providing 438.48 kcal/L. Rats in the control group (CD, n = 6) were fed a 4% fat grain-based chow (Teklad 2014; Harlan Laboratories, Indianapolis, IN, USA) with a caloric intake of 2.89 kcal/g, and tap water (Fig. 1). Finally, in STUDY-3, we aimed to determine the optimal Chol and CA concentrations to achieve all the features of metabolic syndrome alongside advanced liver fibrosis while maintaining a physiological state. Rats were fed for 20 weeks with three different diets based on the diet used in STUDY-2 but modified Chol and CA content: 5 g/kg (0.5%) Chol + 5 g/kg (0.5%) CA (D3-MASLD, n = 12); 20 g/kg Chol (2%) + 0 g/kg CA (D4-MASLD, n = 11); and 20 g/kg (2%) Chol + 1 g/kg (0.1%) CA (D5-MASLD, n = 10). The average caloric intake for these diets was 5.66 kcal/g, 5.61 kcal/g and 5.61 kcal/g, respectively (Ssniff Spezialdiäten GmbH, Soest, Germany). The glucose-fructose beverage was the same as that in STUDY-2, providing 438.48 kcal/L. The rats in the control group were also fed the same grain-based diet as in STUDY-2, with a caloric intake of 2.89 kcal/g, and had access to tap water (CD, n = 8) (Fig. 1). All procedures were conducted following the European Union Guidelines for Ethical Care of Experimental Animals (EC Directive 86/609/EEC for animal experiments) and were approved (file numbers: 11376 and 12060) by the Animal Care Committee of the Vall d’Hebron Institut de Recerca, in which animal facilities were used for the experiments. 2.2. Transcriptome profiling Transcriptome profiling of 15 rat liver tissue samples from STUDY-3 (CD, n = 5; D4-MASLD, n = 5; D5-MASLD, n = 5) was performed using RNA-Seq. Briefly, 20 mg of liver tissue was weighed and RNA was isolated using the miRNeasy Mini Kit (217004; Qiagen, Hilden, Germany) following the manufacturer’s instructions. The sequencing library was prepared by Novogene Co., Ltd. (Cambridge, UK) using 1000 ng of total RNA. The resulting data were analyzed at the Vall d’Hebron Biostatistics Unit, using different software available according to a pre-processing pipeline. The dataset is available from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus database (accession number GSE282001). Overall similarities between samples, in a 2-dimention reduction, were assessed by Principal Component Analysis (PCA); Venn diagrams and heatmaps were used to represent multiple comparisons between differentially expressed genes. 2.3. Analysis of the biological significance and comparison with human samples We analyzed the biological significance of differential gene expression caused by D4 -MASLD and D5-MASLD compared to the control diet. Gene Set Enrichment Analysis (GSEA) was performed to determine the pathways in which these genes were involved based on Gene Ontology (Biological Process category, GO-BP). Human liver transcriptome datasets from the GSE48452 database were used to identify the commonly dysregulated pathways between human stages of the disease, patients with MASLD (STEAT, n = 9), and patients with MASH (n = 17) vs. healthy individuals (CTL, n = 12). Common molecular pathway dysregulation in rat and human liver tissues was determined by GSEA, in previously transformed human genes to rat gene orthologs to obtain comparable biological terms using the Molecular Signatures Database package msigdbr 14 . 2.4. Statistical analysis Statistical analyses were performed using the GraphPad Prism software (GraphPad Software, San Diego, CA, USA). Continuous variables were tested using the Shapiro-Wilk test. Unpaired Student’s t-test was used to compare means between two groups and one-way ANOVA with Tukey’s HSD for multiple comparisons. For non-parametric data, the Mann-Whitney U test or Kruskal-Wallis test was applied. Statistical significance was set at P < 0.05. The statistical analysis for the differential expression analysis and the biological significance of the transcriptomic profile was performed using the statistical language “R” (R version 4.2.0) 15 .Enrichment analyses were performed using the clusterProfiler R package v4.0.5 16 . 3. RESULTS 3.1. Models in STUDY-1 exhibited metabolic syndrome, portal hypertension, and histological features of MASH, but not advanced fibrosis The rationale for this double-hit model was to assess whether increasing the total amount of glucose and fructose in drinking water and administration of LPS would induce fibrosis. Accordingly, all comparisons were made relative to the same diet without LPS (D1-MASLD) and the no-chow-diet control group was included (Fig. 1). After 24 weeks, both groups in the STUDY-1 model exhibited high values of body weight, showing a significant but small decrease in rats fed with the diet supplemented with LPS (Suppl. Fig. 1). Both groups showed elevated fasting glucose, total cholesterol, and TG levels. Although the D1-MASLD+LPS group had substantially higher fasting glucose and TG levels than the D1-MASLD group, these differences were not statistically significant (Suppl. Table 2). The HOMA-IR values remained very similar between the groups (Suppl. Fig. 2). The two-hit D1-MASLD+LPS group displayed higher average values of PP compared to the D1-MASLD group (12.07 vs 10.5 mmHg) alongside higher IHVR values, although differences were not significant (Fig. 2). Histological assessments revealed high steatosis scores in both groups, with at least 50% of the individuals showing inflammation. The group without LPS exhibited the highest percentage of individuals with steatosis (100%) and lobular inflammation (69%, with a few individuals scoring 3) (Suppl. Fig. 3). Fibrosis at week 24 was either mild or absent in both groups (Fig. 3A). Given the lack of clinically relevant findings, further assessments of this model in STUDY-1 are deemed unnecessary. 3.2. Models in STUDY-2 exhibited MASH-related fibrosis and portal hypertension but did not lead to complete metabolic syndrome The models in STUDY-2 had two different durations, 16 and 24 weeks, and included a higher concentration of Chol (2%) and 0.5% CA (Fig. 1). We anticipated that the disease features would worsen at 24 weeks; however, this was not the case, as most parameters showed no significant differences between the two time points. Therefore, our results focused primarily on the 16-week intervention, with the 24-week groups mentioned to stress the lack of difference in important parameters. Animals fed the 16-week D2-MASLD diet showed a trending increase in body weight compared to the CD group (Suppl. Fig. 1). The 16-week D2-MASLD diet was associated with significant increases in fasting blood concentrations of ALT, AST, and total cholesterol, but not triglycerides, compared to the CD diet (Suppl. Table 2). Moreover, D2-MASLD did not affect serum glucose and insulin levels or HOMA-IR values at either 16 or 24 weeks (Suppl. Fig. 2 and Suppl. Fig. 4). Hemodynamic measurements revealed a significant increase in PP in the D2-MASLD group (52% increase) at 16 weeks compared with that in the CD group (Fig. 2). The presence of portal hypertension was accompanied by a significant increase in the IHVR. There were no significant differences in the PP values between the 16- and 24-week time points (Suppl. Fig. 4). At 16 weeks, all individuals in the D2-MASLD group had a steatosis score of 3, and most (70%) had an inflammation score of 2 (70%) (Suppl. Fig. 3). Histological fibrosis assessment using the NASH-CRN system revealed that higher Chol content and the addition of CA in the diet led to significant liver fibrosis in most D2-MASLD individuals, with 78% (7/9) reaching F2 or greater. Cirrhosis (F4) was observed in one individual from the D2-MASLD group at 16 weeks (Suppl. Table 3). Accordingly, the percentage of the area occupied by collagen deposition, as measured by image analysis, was significantly higher in the D2-MASLD group than in the control group at 16 weeks (Fig. 3). A slight non-significant increase in fibrosis was observed over time at 24 weeks (Suppl. Fig. 4C). In addition, exploring the ductular reaction by CK-7 labelling revealed a significant increase in CK-7-stained areas in the livers of D2-MASLD rats compared to controls, indicating ongoing liver injury and ductular proliferation (Suppl. Fig. 5). Protein analysis by western blotting revealed a significant decrease in intrahepatic protein expression levels of P-eNOS/eNOS and P-AKT/AKT, along with a trend towards decreased KLF2 levels in the D2-MASLD group compared to controls (Suppl. Fig. 6). These findings suggest that in addition to fibrosis, endothelial dysfunction represents another underlying mechanism contributing to the increased IHVR caused by this diet model. The role of the hepatic insulin-signaling pathway was also addressed through the expression of genes encoding the insulin receptor substrates IRS-1 and IRS-2. Although D2-MASLD animals did not exhibit features associated with systemic insulin resistance, namely fasting hyperglycemia and hyperinsulinemia, significant repression of both genes was found in the livers of these rats compared to the CD group (Fig. 4). Thus, impairment of the IRS/PI3K/AKT pathway indicated the presence of hepatic insulin resistance in this model. Furthermore, the possible contribution of adipokines in the development of hepatic insulin resistance was examined. For this purpose, hepatic expression of AdipoR2 and LepR was analyzed. Gene expression analysis revealed a significant decrease in the hepatic mRNA expression of AdipoR2 in the D2-MASLD group compared to that in the CD group, whereas LepR was significantly overexpressed (Fig. 4). These findings also indicate altered hepatic insulin sensitivity in this model. 3.3. Models in STUDY-3 recapitulate key features of MASLD with metabolic syndrome, including both systemic and hepatic insulin resistance, as well as advanced fibrosis and portal hypertension The aim of STUDY-3 was to reduce the concentrations of Chol or CA to identify a combination that preserves the characteristics of the STUDY-2 model, using a more physiologically relevant amount of these components in the diet, while still maintaining key metabolic features such as obesity. Additionally, because extending the model to 24 weeks did not significantly worsen its outcomes, the duration of this model was set at 20 weeks (Fig. 1). Animals fed the D4-MASLD and D5-MASLD diets, containing no or low CA concentrations (2% Chol + 0% CA and 2% Chol + 0.1% CA, respectively), showed significant increases in body weight compared to the CD group (Suppl. Fig. 1). In contrast, the D3-MASLD group, which had the highest CA concentration (2% Chol + 0.5% CA), exhibited a body weight similar to that of the CD group. (Suppl. Fig. 1). All diet groups showed elevated levels of AST, ALT, total cholesterol, and albumin compared to those in the CD group (Suppl. Table 2). Evaluation of the HOMA-IR index revealed a significant increase only in the groups with low or no CA in the diet (i.e., D4-MASLD and D5-MASLD), whereas no systemic insulin resistance was observed in the D3-MASLD group, which contained high CA concentrations (Suppl. Fig. 2). Hemodynamic measurements revealed significantly elevated PP values in all dietary groups compared with the controls (Fig. 2). Notably, those supplemented with CA demonstrated higher PP values than those supplemented with CD. In contrast, IHVR did not show significant differences in any of the dietary groups compared with the controls. Histological examination revealed high steatosis scores across all dietary groups, with more than 50% of the individuals showing severe steatosis (Suppl. Fig. 3). Additionally, more than 25% of individuals in all dietary groups exhibited an inflammation score of at least 1, with over 25% reaching a score of 2 (Suppl. Fig. 3). As for fibrosis, in the D3-MASLD group, 16.7% of individuals had significant fibrosis (stages F2-F3) and 83.3% showed F1 or no fibrosis. The diet without CA, D4-MASLD, yielded advanced fibrosis (≥ F3) in 36.4% of the individuals, but 63.6% had F1 or no fibrosis. In the D5-MASLD group, 30% of the individuals had advanced fibrosis and 50% exhibited significant fibrosis, whereas the other half exhibited either mild (F1) or no fibrosis (Suppl. Table 3). Quantitative analysis of the fibrotic area in liver tissues showed that all diets led to a significant increase in the percentage of fibrotic area compared to that in the CD group at 20 weeks (Fig. 3). All dietary groups showed a significant increase in CK-7-stained areas, thus underlining the potential role of the ductular reaction, characterized by bile duct hyperplasia (Suppl. Fig. 5). Endothelial dysfunction analysis showed that the D5-MASLD group exhibited lower P-AKT/AKT and P-eNOS/eNOS ratio values than the CD group, although these differences were not statistically significant. Additionally, KLF2 expression was significantly lower in all groups than in the control group (Suppl. Fig. 6). Similar to STUDY-2, intrahepatic insulin resistance was assessed by analyzing the expression of IRS-1 and IRS-2 in the liver using RT-qPCR. A significant reduction in the mRNA expression of both genes was observed in all three dietary groups compared with that in the CD group. To further support the presence of intrahepatic insulin resistance, AdipoR2 and LepR gene expressions were also examined. All dietary groups in STUDY-3 showed a significant downregulation of AdipoR2 and upregulation of LepR. These findings, along with the reduced expression of insulin receptors, indicate altered insulin sensitivity in the liver across dietary groups (Fig. 4). 3.4. The transcriptional profile of D4-MASLD and D5-MASLD diets from STUDY-3 underline pathway changes in the proximity to human MASLD Differential gene expression The transcriptional profiles of the D4-MASLD, D5-MASLD, and CD groups from STUDY-3 were analyzed. Principal component analysis revealed distinct clustering of rat samples, (Suppl. Fig. 7A). suggesting significant differences between the diet groups and controls, while also indicating a high degree of similarity between the two diets. Differential expression analysis comparing the effects of the diets with their controls at an adjusted p value ≤ 0.01, is represented in the heatmap in Fig. 5, demonstrating a clear distinction in the expression patterns between the CD samples and the D4-MASLD and D5-MASLD groups. Using a less restrictive non-adjusted p-value allowed the identification of only 39 differentially expressed genes between the diets (Suppl. Fig. 7B). Biological significance According to the GSEA analysis, the most significant effects caused by D4-MASLD and D5-MASLD, compared to their controls, involved the activation of various pathways related to inflammation and immune response (Suppl. Fig. 8). The top 15 GO-BP terms from the comparison between D5-MASLD versus D4-MASLD diets also indicated the activation of inflammation, suggesting a stronger effect of D5-MASLD on immune response alterations than D4-MASLD. Additionally, comparison between the two diets revealed increased activation of pathways related to microbiota alterations, intestinal wall dysfunction, and bacterial translocation in the D5-MASLD group. These pathways modulate responses to external stimuli, such as bacteria, xenobiotics, and cellular processes including cell death and apoptosis. The analysis of the top five GO-BP networks presented in Fig. 6 further reinforces these findings by showing that an important number of differentially expressed genes are connected to just five categories: leukocyte cell adhesion and regulation, response to polysaccharides, response to molecules of bacterial origin, and cell killing. Similarity with human samples We compared the rat and human transcriptomic profiles to identify significant pathways shared between the MASLD diet models and different stages of human disease. Venn diagrams in Suppl. Fig. 9 illustrates the shared elements for the four types of comparisons: D4-MASLD with human MASLD or MASH and D5-MASLD with human MASLD or MASH. The GO terms shared between rats and humans represent various pathways, many of which are redundant and contain slightly different terms that can be grouped into broader categories. Redundancy reduction analysis clustered these pathways into 13-18 groups, which were very similar across the comparisons between D4-MASLD and D5-MASLD and showed minimal differences in the stages of the disease in humans. These results are presented in the bar plot of the redundancy reduction analysis, highlighting the top shared pathways for the four comparisons (Fig. 7). The analysis showed that the most significantly associated pathways affected by D4-MASLD and D5-MASLD were shared by the disease in humans, underscoring the importance of these altered biological processes in the MASLD/MASH spectrum. Key pathways include inflammation, activated immune response, dysbiosis, bacterial translocation, and the activation of responses to external stimuli. Additionally, pathways related to calcium ion activation, the emergence of external structural organization related to fibrosis, and the suppression of pathways involved in cholesterol biosynthesis and fatty acid metabolism are also represented. 4. DISCUSSION In this study, we conducted a multistep process of continuous sequential refining of our MASLD model in rats 13 until a comprehensive model that reproduces metabolic syndrome features, steatohepatitis, advanced fibrosis, and portal hypertension with a transcriptomic profile that resembles human MASLD was developed. The final model consisted of a 20-week high-fat diet with high concentrations of cholesterol (2%) and a glucose-fructose beverage, to which the addition of cholic acid (CA) at low concentrations (0.1%) substantially increased the percentage of individuals achieving significant fibrosis. In a thorough comparative study of MASLD murine models, Vacca et al. evaluated and ranked these models (dietary, genetic, and toxic) based on their alignment with three critical features of MASLD in humans: clinical metabolic phenotype, liver histopathology, and liver transcriptome benchmarked against human transcriptomic changes 6 . After assessing data from 509 mice and 89 rats over 39 models, the authors did not find a single model that fully replicated all aspects of human MASLD. The desired components of the clinical metabolic phenotype include obesity, dyslipidemia, and increased ALT and AST levels, along with the desired histopathological changes in steatohepatitis and significant fibrosis (≥ F2). Our model deviates from some of the criteria utilized by Vacca et al. 6 First, we did not consider that transaminase elevation was a robust indicator of clinically relevant metabolic phenotype (which was present in our models). Besides obesity and dyslipidemia, we relied on glucose metabolism disturbances to evaluate whether each tested model achieved the “metabolic triad.” We assessed three aspects of glucose metabolism derangement: hyperglycemia, systemic insulin resistance, and intrahepatic insulin resistance. The latter was considered mandatory, as it is one of the earlier steps in MASLD pathophysiology 3 , whereas the other two served as markers of type 2 diabetes, which is not develop in all patients with MASLD. Second, we placed special emphasis on achieving advanced fibrosis to recapitulate as much as possible the full spectrum of MASLD natural history, with the ultimate goal of generating a model that allows studying its pathophysiology and assessing the efficacy of therapeutic interventions against advanced chronic disease. Third, we used a rat model primarily to study portal hypertension, and in later phases, to investigate its mechanisms and response to treatment. Fourth, we did not consider that genetic or toxic models could reliably mimic human disease because of their great differences in inducing disease compared to MASLD pathophysiology. Thus, we relied on a dietary model that might be enhanced in terms of achieving more advanced stages of the disease by adding low concentrations of biliary salt (CA) that is already present in the body. Our study suggests that when the priority of the model is to fully develop a clinically significant metabolic phenotype leading to metabolic disturbances that mimic MASLD in humans, rather than achieving significant or advanced fibrosis, the use of CA should be carefully considered. For dyslipidemia, we used a high cholesterol concentration (2%) in our model. By binding to the farnesoid X receptor (FXR), CA increases the absorption of dietary cholesterol from the intestine and may repress CYP7A1 (a key enzyme in bile acid biosynthesis), thereby promoting cholesterol accumulation in the liver 17 . In addition, bile acids such as CA lower serum TG levels by reducing SREBP-1c gene expression 18 . This is consistent with our results showing hypercholesterolemia, but not hypertriglyceridemia. Moreover, the potential dose-dependent effects of CA on weight gain and glucose metabolism were noteworthy. Previous studies have shown that Sprague-Dawley rats fed a high-cholesterol diet supplemented with high-dose CA developed the histopathological features of MASH but lacked obesity and insulin resistance 19 , 20 . In our study, body weight gain over 20 weeks decreased in a dose-dependent manner, with rats receiving 0.5% CA maintaining a body weight comparable to that of controls. Regarding insulin resistance, rats receiving 0.5% CA did not develop systemic insulin resistance, whereas those receiving either 0.1% or none did. High concentrations of CA have been shown to improve insulin resistance and obesity in MASLD models via multiple mechanisms. CA activates bile acid receptors, such as FXR and TGR5, which regulate metabolism, enhance lipid breakdown, and reduce glucose and TG synthesis in the liver 21 . It also alters gene expression related to lipid metabolism, decreases liver fat accumulation, and improving insulin sensitivity 22 , 23 . Additionally, it modulates the gut microbiota, promoting beneficial bacteria that improve metabolic health, reduce inflammation, and enhance gut barrier function 24 . Therefore, developing a MASLD model that captures both advanced fibrosis and metabolic syndrome features requires balancing CA concentrations low enough to promote advanced fibrosis but high enough to maintain metabolic alterations, as seen in the D5-MASLD diet (2% Chol + 0.1% CA). With regard to liver fibrosis, the rationale for developing a model that achieves both significant and advanced fibrosis can be succinctly summarized into two points. First, although MASLD is the most rapidly growing cause of cirrhosis, hepatocellular carcinoma, and liver transplantation globally, the pathophysiology and natural history of advanced MASLD are still largely unknown 25 . The second reason, equally relevant, is that despite dozens of clinical trials conducted in the field, we still lack licensed treatments for more advanced stages of the disease, cirrhosis in particular 26 . Therefore, we consider our model to be a milestone for translational research in the field. To the best of our knowledge, no prior murine model has achieved advanced fibrosis based on dietary intervention. In their study, Vacca et al. highlighted that significant fibrosis can be induced through three strategies, alone or combined, using a high cholesterol content (2%), extending the duration of the model (over 40 weeks), and genetic modifications 6 . We obtained advanced fibrosis in a 20-week model that was neither genetically modified nor used significant amounts of toxic substances. Using low concentrations of CA, our model yielded significant fibrosis in 50% of subjects, with 30% exhibiting advanced fibrosis. Portal hypertension is critical in MASLD advanced disease as it becomes increasingly important as a driver of complications during disease progression. Hence, the importance of a MASLD model that develops portal hypertension in the absence of cirrhosis has been reported in humans 27 . Sinusoidal endothelial dysfunction precedes inflammation and fibrosis in MASLD 28 , which is in line with our findings of alterations in the hepatic protein expression of P-eNOS/eNOS, P-AKT/AKT, and KLF2. Reduced eNOS phosphorylation is likely due to the impaired vasoprotective function of KLF2, which may explain the diminished vasodilation capacity of the sinusoidal endothelium, resulting in decreased nitric oxide production and subsequent endothelial dysfunction 29 . However, preliminary evidence points to distinct mechanisms of portal hypertension in MASLD that go beyond the already well-known association between liver fibrosis and endothelial dysfunction 30 . Notably, severe steatosis might induce portal hypertension at the sinusoidal level, and other inflammatory and mechanotransduction cues could be involved in the mechanisms of presinusoidal portal hypertension 31 , 32 . The potential impact of CA on portal hypertension is likely indirect, possibly through the modulation of liver metabolism, inflammation, or fibrosis 21 . In summary, our model offers a promising tool for comprehensively studying the various mechanisms involved in portal hypertension in MASLD, including the key role of immune responses. In the transcriptomic characterization of our models, we found that the addition of low-dose CA induced subtle yet non-negligible differences in gene expression and biological processes, despite the high overall similarity between the two diets. Various studies have shown that CA can induce inflammatory responses and alter the gut-liver axis, contributing to disease progression. Specifically, CA has been found to disrupt the integrity of the intestinal barrier, increase permeability, and promote the translocation of gut bacteria and their metabolites (e.g., LPS) into the liver. This triggers hepatic inflammation through the activation of toll-like receptors and nucleotide-binding oligomerization domain-like receptors, promoting liver fibrosis through pathways such as NF-κB and inflammasome signalling 33 . Furthermore, CA’s impact of CA on the gut-liver axis is linked to its interaction with bile acid receptors, such as FXR and TGR5 34 . This is consistent with what has been previously discussed regarding both protective and pathological effects upon activation of these receptors, depending on the context and the CA concentrations used. This dual effect can either reduce or exacerbate liver inflammation and fibrosis. Our findings suggest that CA not only enhances inflammation but also alters the gut-liver axis, potentially increasing vulnerability to external stimuli, such as bacteria and xenobiotics. When comparing the transcriptomic profiles caused by these diets in rats with a database of patients with MASLD/MASH, key pathways, such as inflammation, immune response activation, dysbiosis, bacterial translocation, and fibrosis-related processes, are consistently implicated in both humans and rats. This strong overlap underscores the utility of these rat models for understanding human MASLD and MASH, as the biological processes involved appear to be highly conserved, particularly in terms of inflammation and immune response mechanisms. The ductal reaction is a hallmark of ongoing liver injury that suggests an inefficient regenerative response by hepatocytes, leading to the activation of hepatic progenitor cells as a secondary proliferative pathway in MASLD 35 . These cells contribute to the formation of new hepatocytes, cholangiocytes, and ductules, and are believed to play a role in fibrosis activation and progression of MASLD 36 , 37 . Whether the signs of ductular reaction observed in our model are due to the use of CA or inherent to MASLD pathophysiology and associated with disease progression, including the mechanisms of liver fibrosis and portal hypertension, warrants further studies. This study had several limitations that deserve consideration. First, we only analyzed male rats. Sex differences are a definite feature of MASLD, and sexual dimorphism in disease progression and metabolic response is increasingly recognized 38 . Another limitation arises from the STUDY-1 model, as it did not include a chow diet control group and several analyses were omitted. This was because the primary objective was to determine whether a more concentrated glucose-fructose HFGFD, either alone or in combination with LPS, would be sufficient to induce fibrosis. As this was not achieved, we concluded that the model lacked clinical relevance, and further studies were deemed unnecessary. Finally, varying durations across models make it difficult to compare the histological impact, limiting the interpretation of fibrosis progression over time. In conclusion, through a multi-step sequential process, we developed and characterized a dietary model of MASLD that fully recapitulates the most relevant clinical, histopathological, and transcriptomic aspects of human disease, while allowing the study of the pathophysiology and treatment of advanced fibrosis and portal hypertension. Declarations Acknowledgements We wish to thank our colleagues at the Statistics and Bioinformatics Unit (UEB) Vall d’Hebron Hospital Research Institute (VHIR) for their support in using the bioinformatics pipeline to analyze RNA-seq data and to discover biological significance. Funding This work was supported by grants PI21/00691 and PI22/01770 from Instituto de Salud Carlos III (ISCIII), as well as by the Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd, CB06/04/0007), and cofounded by European Union (ERDF/ESF, “A way to make Europe” “Investing in your future”). JMP received a grant from the Vall d’Hebron University Hospital Campus to intensify his research activities (2024-2025). Authors’ contributions M.M., J.G., and J. M. P. conceived and designed the initial study. A.B., M.M.G., I.R., and M.S.C. conducted in vitro and animal studies. M.M.G., I.R., and M.M. approved the ethics of the rats. M.T.S. performed the histological analysis. A.B., M.M.G., I.R., M.T.S., and M.M. analyzed the data. M. M. G., A.B., M.M., and J. M. P. wrote the manuscript. M.M.G. and M.M. drafted the manuscript S.C.P., S.A., M.V.C., and J.G. have revised the manuscript. All authors have provided intellectual contributions and approved the final manuscript. Competing interests J.M.P. reports having received consulting fees from the MSD, Madrigal, Boehringer-Ingelheim, and Novo Nordisk. He has received speaking fees from Madrigal, Gilead, Intercept, and Novo Nordisk and travel expenses from Gilead, Rubió, Pfizer, Astellas, MSD, CUBICIN, and Novo Nordisk. He received educational and research support from Madrigal, Boehringer-Ingelheim, Gilead, Pfizer, Astellas, Accelerate, Novartis, Abbvie, ViiV, and MSD. All other authors have no conflicts of interest. References Rinella, M. E. et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. Journal of Hepatology vol. 79 1542–1556 Preprint at https://doi.org/10.1016/j.jhep.2023.06.003 (2023). Younossi, Z. M. et al. The global epidemiology of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH): a systematic review. Hepatology 77 , 1335–1347 (2023). Loomba, R., Friedman, S. L. & Shulman, G. I. Mechanisms and disease consequences of nonalcoholic fatty liver disease. Cell vol. 184 2537–2564 Preprint at https://doi.org/10.1016/j.cell.2021.04.015 (2021). Powell, E. E., Wong, V. W. S. & Rinella, M. Non-alcoholic fatty liver disease. Lancet 397 , 2212–2224 (2021). Yulia A. Nevzorova, Zoe Boyer-Diaz, Francisco Javier Cubero, J. G.-S. Animal models for liver disease – A practical approach for translational research. J Hepatol 73 , 423–440 (2020). Vacca, M. et al. An unbiased ranking of murine dietary models based on their proximity to human metabolic dysfunction-associated steatotic liver disease (MASLD). Nat Metab (2024) doi:10.1038/s42255-024-01043-6. 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Restoration of a healthy intestinal microbiota normalizes portal hypertension in a rat model of nonalcoholic steatohepatitis. Hepatology 67 , 1485–1498 (2018). Benjamini, Y. & Hochberg, Y. Controlling The False Discovery Rate - A Practical And Powerful Approach To Multiple Testing. J. Royal Statist. Soc., Series B 57 , 289–300 (1995). R Core Team (2018) R A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. - References - Scientific Research Publishing. https://www.scirp.org/reference/ReferencesPapers?ReferenceID=2342186. Yu, G., Wang, L. G., Han, Y. & He, Q. Y. ClusterProfiler: An R package for comparing biological themes among gene clusters. OMICS 16 , 284–287 (2012). De Aguiar Vallim, T. Q., Tarling, E. J. & Edwards, P. A. Pleiotropic roles of bile acids in metabolism. Cell Metab 17 , 657–669 (2013). Watanabe, M. et al. Bile acids lower triglyceride levels via a pathway involving FXR, SHP, and SREBP-1c. 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Global epidemiology of cirrhosis - aetiology, trends and predictions. Nat Rev Gastroenterol Hepatol 20 , 388–398 (2023). Pericàs, J. M. et al. A roadmap for clinical trials in MASH-related compensated cirrhosis. Nat Rev Gastroenterol Hepatol 21 , (2024). Rodrigues, S. G. et al. Patients With Signs of Advanced Liver Disease and Clinically Significant Portal Hypertension Do Not Necessarily Have Cirrhosis. Clin Gastroenterol Hepatol 17 , 2101-2109.e1 (2019). Pasarín, M. et al. Sinusoidal Endothelial Dysfunction Precedes Inflammation and Fibrosis in a Model of NAFLD. PLoS One 7 , e32785 (2012). Felli, E. et al. Mechanobiology of portal hypertension. JHEP Reports 5 , 100869 (2023). Mitten, E. K., Portincasa, P. & Baffy, G. Portal Hypertension in Nonalcoholic Fatty Liver Disease: Challenges and Paradigms. J Clin Transl Hepatol 11 , 1201–1211 (2023). Francque, S. et al. Noncirrhotic human nonalcoholic fatty liver disease induces portal hypertension in relation to the histological degree of steatosis. Eur J Gastroenterol Hepatol 22 , 1449–1457 (2010). Barberá, A. et al. Steatosis as main determinant of portal hypertension through a restriction of hepatic sinusoidal area in a dietary rat nash model. Liver Int 40 , 2732–2743 (2020). Bruneau, A., Hundertmark, J., Guillot, A. & Tacke, F. Molecular and Cellular Mediators of the Gut-Liver Axis in the Progression of Liver Diseases. Front Med (Lausanne) 8 , 725390 (2021). Xue, R. et al. Bile Acid Receptors and the Gut–Liver Axis in Nonalcoholic Fatty Liver Disease. Cells 10 , 2806 (2021). Roskams, T. et al. Oxidative stress and oval cell accumulation in mice and humans with alcoholic and nonalcoholic fatty liver disease. Am J Pathol 163 , 1301–1311 (2003). Richardson, M. M. et al. Progressive fibrosis in nonalcoholic steatohepatitis: association with altered regeneration and a ductular reaction. Gastroenterology 133 , 80–90 (2007). Rygiel, K. A. et al. Epithelial-mesenchymal transition contributes to portal tract fibrogenesis during human chronic liver disease. Lab Invest 88 , 112–123 (2008). Cherubini, A., Della Torre, S., Pelusi, S. & Valenti, L. Sexual dimorphism of metabolic dysfunction-associated steatotic liver disease. Trends Mol Med 30 , (2024). Table Additional Declarations There is NO Competing Interest. Juan M.Pericàs reports having received consulting fees from the MSD, Madrigal, Boehringer-Ingelheim, and Novo Nordisk. He has received speaking fees from Madrigal, Gilead, Intercept, and Novo Nordisk and travel expenses from Gilead, Rubió, Pfizer, Astellas, MSD, CUBICIN, and Novo Nordisk. He received educational and research support from Madrigal, Boehringer-Ingelheim, Gilead, Pfizer, Astellas, Accelerate, Novartis, Abbvie, ViiV, and MSD. All other authors have no conflicts of interest. Supplementary Files SupplementaryLabAnimal.docx Supplementary Material: A new dietary rat model fully recapitulates metabolic dysfunction-associated steatotic liver disease pathophysiology and mimics human disease with advanced liver fibrosis and p Cite Share Download PDF Status: Published Journal Publication published 03 Apr, 2026 Read the published version in Lab Animal → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6376882","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":453852439,"identity":"fd955370-9a91-4663-b5c4-44fd3bc52530","order_by":0,"name":"Joan Genescà","email":"data:image/png;base64,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","orcid":"","institution":"Vall d'Hebron Hospital","correspondingAuthor":true,"prefix":"","firstName":"Joan","middleName":"","lastName":"Genescà","suffix":""},{"id":453852440,"identity":"4d12640c-aa00-4f33-b873-e76ed59e1f58","order_by":1,"name":"Maria Martinez","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Martinez","suffix":""},{"id":453852441,"identity":"0f6eb1e8-a737-49bf-8135-7fe2ebfd61c5","order_by":2,"name":"Aurora Barberá","email":"","orcid":"https://orcid.org/0000-0002-6201-2643","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"Aurora","middleName":"","lastName":"Barberá","suffix":""},{"id":453852442,"identity":"174d921e-53f2-4625-95af-4cd9c37f2502","order_by":3,"name":"Imma Raurell","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"Imma","middleName":"","lastName":"Raurell","suffix":""},{"id":453852443,"identity":"a0109fd8-e1b9-42e0-be11-c81eba40a3a9","order_by":4,"name":"M Serra Cusidó","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"Serra","lastName":"Cusidó","suffix":""},{"id":453852444,"identity":"774ccbea-7de1-4759-b2f7-d094cac0665c","order_by":5,"name":"Sophia C Parks","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"Sophia","middleName":"C","lastName":"Parks","suffix":""},{"id":453852445,"identity":"e29d3be4-0d50-46a5-85da-906c473eb26a","order_by":6,"name":"M Teresa Salcedo","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"Teresa","lastName":"Salcedo","suffix":""},{"id":453852446,"identity":"a91b3f3b-d421-4fda-af21-0388c84c9102","order_by":7,"name":"Salvador Augustin","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"Salvador","middleName":"","lastName":"Augustin","suffix":""},{"id":453852447,"identity":"c072bc02-53a1-43cb-8511-d6a2985dae24","order_by":8,"name":"Meritxell Ventura-Cots","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"Meritxell","middleName":"","lastName":"Ventura-Cots","suffix":""},{"id":453852448,"identity":"c37afcac-7d9e-42d7-b637-823ba1ccdb86","order_by":9,"name":"María Martell","email":"","orcid":"https://orcid.org/0000-0002-0935-0029","institution":"Hospital Universitari Vall d'Hebron","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"","lastName":"Martell","suffix":""},{"id":453852449,"identity":"4997af54-43fb-4550-8d17-0de36d73a5c5","order_by":10,"name":"Juan M. Pericàs","email":"","orcid":"","institution":"Vall d'Hebron Institute for Research","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"M.","lastName":"Pericàs","suffix":""}],"badges":[],"createdAt":"2025-04-04 14:20:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6376882/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6376882/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41684-026-01710-z","type":"published","date":"2026-04-03T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85379791,"identity":"1e61e207-bde6-4455-9c96-8b560a28b91f","added_by":"auto","created_at":"2025-06-25 09:03:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":142044,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSummary of the main steps in developing the MASLD model and outstanding results. \u003c/strong\u003eCD, control diet; HFGFD, high-fat glucose and fructose diet; LPS, lypopolisaccaride; MASLD, metabolic dysfunction-associated steatotic liver disease.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/e12d2707fa5609ea0697233f.png"},{"id":85379072,"identity":"720cda79-0c0f-4641-b9c1-36eddb37e5aa","added_by":"auto","created_at":"2025-06-25 08:55:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":71915,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHemodynamic measurements after dietary interventions. \u003c/strong\u003e(A) Portal pressure, PP, among different groups in the three studies. (B) Intrahepatic vascular resistance, IHVR, calculated as PP/Portal blood flow. Values are expressed as mean ± SEM. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 \u003cem\u003eversus\u003c/em\u003e CD. CD: Control; HFGFD: High Fat Glucose Fructose Diet; LPS: Lipopolysaccharide; Chol: Cholesterol; CA: Colic acid; D1-MASLD: HFGFD; D1-MASLD + LPS: HFGFD + LPS; D2-MASLD: HFGFD + 2% Chol + 0.5% CA; D3-MASLD: HFGFD + 0.5% Chol + 0.5% CA; D4-MASLD: HFGFD + 2% Chol; D5-MASLD: HFGFD + 2% Chol + 0.1% CA.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/72c1da67ba406a9c517613f2.png"},{"id":85381160,"identity":"ee7e3605-c13c-49d0-a349-fbc762f1b846","added_by":"auto","created_at":"2025-06-25 09:11:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":390744,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHistological evaluation of liver fibrosis after dietary interventions. \u003c/strong\u003e(A) Representative images of Sirius Red stained rat liver parenchyma of the different studies (10X magnification). (B) Bar diagrams showing quantification of fibrotic area (%) assessed on Sirius Red stained liver sections of rats from each group. Values are expressed as mean ± SEM. *P ≤ 0.05; **P ≤ 0.01 \u003cem\u003eversus\u003c/em\u003e CD. CD: Control; HFGFD: High Fat Glucose Fructose Diet; Chol: Cholesterol; CA: Colic acid; D2-MASLD: HFGFD + 2% Chol + 0.5% CA; D3-MASLD: HFGFD + 0.5% Chol + 0.5% CA; D4-MASLD: HFGFD + 2% Chol; D5-MASLD: HFGFD + 2% Chol + 0.1% CA.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/b6348f6993fe21447cd664e3.png"},{"id":85377865,"identity":"2a11bbe0-655e-44c1-8da6-9c975c1b382d","added_by":"auto","created_at":"2025-06-25 08:47:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":53861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssessment of intrahepatic insulin resistance. \u003c/strong\u003eRelative quantification of hepatic AdipoR2, Irs1, Irs2 and LepR mRNA expression determined by qRT-PCR, expressed as log2 ratio. β-Actin was used as an endogenous control, and results were normalized to the control group. Values are expressed as mean ± SEM. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 \u003cem\u003eversus\u003c/em\u003e CD.\u003cstrong\u003e \u003c/strong\u003eCD: Control; HFGFD: High Fat Glucose Fructose Diet; Chol: Cholesterol; CA: Colic acid; D2-MASLD: HFGFD + 2% Chol + 0.5% CA; D3-MASLD: HFGFD + 0.5% Chol + 0.5% CA; D4-MASLD: HFGFD + 2% Chol; D5-MASLD: HFGFD + 2% Chol + 0.1% CA; AdipoR2: Adiponectin receptor 2; IRS: Insulin receptor substrate; LepR: Leptin receptor.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/0e84d2c7a7be2050f1cf02f0.png"},{"id":85377869,"identity":"9010f87d-1c9d-4074-bbca-f23c6929f2e0","added_by":"auto","created_at":"2025-06-25 08:47:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":509122,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiet effect: changes in the transcriptional profile. \u003c/strong\u003eThe Heatmap shows the differentially expressed genes between control group and both dietary groups D4-MASLD and D5-MASLD. Genes were selected from a multiple comparison with an adjusted p-value ≤ 0.01 and absolute log fold change \u0026gt; 2. CD: Control; HFGFD: High Fat Glucose Fructose Diet; D4-MASLD: HFGFD + 2% Chol; D5-MASLD: HFGFD + 2% Chol + 0.1% CA. CD: Control; HFGFD: High Fat Glucose Fructose Diet; LPS: Lipopolysaccharide; Chol: Cholesterol; CA: Colic acid; D4-MASLD: HFGFD + 2% Chol; D5-MASLD: HFGFD + 2% Chol + 0.1% CA.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/01428deff3d1282bb41461c0.png"},{"id":85379077,"identity":"97d84bb3-101f-4849-88cf-811f7400821e","added_by":"auto","created_at":"2025-06-25 08:55:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":823194,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential gene expression between diets: analysis of biological significance.\u003c/strong\u003e Network plot representation of differentially expressed genes between D5-MASLD \u003cem\u003eversus\u003c/em\u003e D4-MASLD, significantly associated with top 5 GO-BP terms.\u003cstrong\u003e \u003c/strong\u003eEnriched GO terms were selected with an adjusted p-value \u0026lt; 0.15. The size of the GO term nodes is related to the number of genes found in that category, the colour of the gene nodes refers to their logFC and the colour of the edges links each gene with its GO term. GO-BP: Gene Ontology-Biological Process; D4-MASLD: HFGFD + 2% Chol; D5-MASLD: HFGFD + 2% Chol + 0.1% CA.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/05e88cc4dd0d9d4acf450984.png"},{"id":85381161,"identity":"bd0d698c-5a81-48fd-8dfa-a1c698f92901","added_by":"auto","created_at":"2025-06-25 09:11:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":196599,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMASLD diet models share significant altered pathways with human MASLD\u003c/strong\u003e. Bar plot of the redundancy reduction analysis with the top shared clustered pathways for the four comparisons. The GO terms for each comparison were filtered using a p-value threshold of ≤ 0.01. CD: Control; HFGFD: High Fat Glucose Fructose Diet; Chol: Cholesterol; CA: Colic acid; D4-MASLD: HFGFD + 2%Chol; D5-MASLD: HFGFD + 2% Chol + 0.1% CA.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/d2228e76658900390b670169.png"},{"id":106138060,"identity":"7f88fde5-7a9d-4664-a6ed-ba8cc266b0af","added_by":"auto","created_at":"2026-04-04 07:06:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3186251,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/94462f02-67cf-461f-bc84-bd3aed38daa5.pdf"},{"id":85377862,"identity":"003f5590-6beb-4f99-8316-61156d457391","added_by":"auto","created_at":"2025-06-25 08:47:31","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2203950,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Material: A new dietary rat model fully recapitulates metabolic dysfunction-associated steatotic liver disease pathophysiology and mimics human disease with advanced liver fibrosis and p\u003c/p\u003e","description":"","filename":"SupplementaryLabAnimal.docx","url":"https://assets-eu.researchsquare.com/files/rs-6376882/v1/a5860729e0dcaff753ae6769.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.\nJuan M.Pericàs reports having received consulting fees from the MSD, Madrigal, Boehringer-Ingelheim, and Novo Nordisk. He has received speaking fees from Madrigal, Gilead, Intercept, and Novo Nordisk and travel expenses from Gilead, Rubió, Pfizer, Astellas, MSD, CUBICIN, and Novo Nordisk. He received educational and research support from Madrigal, Boehringer-Ingelheim, Gilead, Pfizer, Astellas, Accelerate, Novartis, Abbvie, ViiV, and MSD. \r\nAll other authors have no conflicts of interest.","formattedTitle":"A new dietary rat model fully recapitulates metabolic dysfunction-associated steatotic liver disease pathophysiology and mimics human disease with advanced liver fibrosis and portal hypertension","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eSteatotic liver disease (SLD) is an emerging form of chronic liver disease that is growing rapidly worldwide and is largely driven by epidemics of metabolic syndrome\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Metabolic dysfunction-associated SLD (MASLD), the most common form of SLD, is currently reaching an estimated prevalence of 38% in the global adult population\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The more advanced form of MASLD, known as metabolic dysfunction-associated steatohepatitis (MASH), is associated with liver inflammation and hepatocellular injury \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Individuals with MASH are at a significantly higher risk of developing progressive liver fibrosis and cirrhosis, liver and non-liver clinical events, and hepatocellular carcinoma \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe use of animal models is crucial for understanding the underlying mechanisms involved in the onset and progression of MASLD and for developing innovative therapeutic strategies\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, most current models do not accurately reproduce advanced human liver diseases, including significant liver fibrosis, portal hypertension, and associated metabolic factors, such as obesity and dyslipidemia\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Consequently, the available animal models for MASLD serve different purposes and have varying degrees of clinical relevance \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe ability of genetic and toxic models to investigate the pathophysiology of MASLD in a relatively physiological manner is impaired \u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. To achieve a clinical representation of MASLD, dietary interventions mimicking Western diets are currently the most effective approach\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Diet-induced models involve a wide range of dietary regimens, including variations in fat content, sources of fat, cholesterol levels, and additional supplements like cholic acid \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Diets with moderately elevated fat, high fructose, and dietary cholesterol can closely replicate human western diets and induce MASLD \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAccordingly, our research group developed an 8-week rat model using a high-fat diet combined with a glucose-fructose beverage (HFGFD) \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. This model exhibited all histological characteristics of MASLD and metabolic syndrome features, including obesity and insulin resistance, in addition to mild portal hypertension. However, a significant drawback is the absence of liver fibrosis, which limits its applicability for advanced MASLD research. Since then, we have undertaken several steps to modify and improve our model to accurately replicate the full MASLD phenotype observed in human diseases. Herein, we present a summary of the sequential models developed and tested to generate a translational model of MASLD that encompasses all relevant features of MASLD, advanced fibrosis, and portal hypertension.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003e2.1.\u0026nbsp;\u0026nbsp;\u003c/strong\u003eAnimals and diet\u003c/p\u003e\n\u003cp\u003eThe study was conducted following the ARRIVE guidelines for reporting in vivo experiments (Supplementary Data). Three rat models of MASLD were developed sequentially with variations in diet and additional factors until the ultimate model encompassed metabolic syndrome, steatohepatitis, advanced fibrosis, and portal hypertension (Fig. 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll three study models were developed using male Sprague-Dawley rats (Charles River Laboratories, L\u0026acute;Abresle, France) weighing 200-220 g at the beginning of the experiments. Animals were housed under a 12-hour light/dark cycle at constant temperature (24 \u0026plusmn; 1 \u0026deg;C) and relative humidity (55 \u0026plusmn; 10%). Body weight, and food and drink consumption were monitored weekly.\u003c/p\u003e\n\u003cp\u003eIn STUDY-1, all rats were fed a high-fat glucose/fructose diet (HFGFD) for 24 weeks, comprising 30% fat (butter, coconut oil, palm oil, beef tallow) with mainly saturated fatty acids (5.73 kcal/g; Ssniff Spezialdi\u0026auml;ten GmbH, Soest, Germany), supplemented with 1 g/kg (0.1%) Chol and combined with a glucose-fructose beverage (110 g/L, 45% glucose and 55% fructose). From weeks 4 to 24, the rats were divided into two groups (Fig. 1): the double-hit group, which received additional intraperitoneal injections of 0.5 mg/kg LPS twice a week (D1-MASLD+LPS, n = 8), and a group that received only the HFGFD (D1-MASLD, n = 13).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn STUDY-2, rats had ad\u003cem\u003e\u0026nbsp;libitum\u003c/em\u003e access to a new diet for 16 and 24 weeks (D2-MASLD, n = 12 and n = 8, respectively), consisting of 30% fat (including butter, coconut oil, palm oil, and beef tallow), predominantly composed of saturated fatty acids, supplemented with 20 g/kg (2%) Chol and 5 g/kg (0.5%) CA (5.62 kcal/g; Ssniff Spezialdi\u0026auml;ten GmbH, Soest, Germany). This diet was combined with a glucose-fructose beverage (110 g/L, 45% glucose, and 55% fructose) to providing 438.48 kcal/L. Rats in the control group (CD, n = 6) were fed a 4% fat grain-based chow (Teklad 2014; Harlan Laboratories, Indianapolis, IN, USA) with a caloric intake of 2.89 kcal/g, and tap water (Fig. 1).\u003c/p\u003e\n\u003cp\u003eFinally, in STUDY-3, we aimed to determine the optimal Chol and CA concentrations to achieve all the features of metabolic syndrome alongside advanced liver fibrosis while maintaining a physiological state. Rats were fed for 20 weeks with three different diets based on the diet used in STUDY-2 but modified Chol and CA content: 5 g/kg (0.5%) Chol + 5 g/kg (0.5%) CA (D3-MASLD, n = 12); 20 g/kg Chol (2%) + 0 g/kg CA (D4-MASLD, n = 11); and 20 g/kg (2%) Chol + 1 g/kg (0.1%) CA (D5-MASLD, n = 10). The average caloric intake for these diets was 5.66 kcal/g, 5.61 kcal/g and 5.61 kcal/g, respectively (Ssniff Spezialdi\u0026auml;ten GmbH, Soest, Germany). The glucose-fructose beverage was the same as that in STUDY-2, providing 438.48 kcal/L. The rats in the control group were also fed the same grain-based diet as in STUDY-2, with a caloric intake of 2.89 kcal/g, and had access to tap water (CD, n = 8) (Fig. 1).\u003c/p\u003e\n\u003cp\u003eAll procedures were conducted following the European Union Guidelines for Ethical Care of Experimental Animals (EC Directive 86/609/EEC for animal experiments) and were approved (file numbers: 11376 and 12060) by the Animal Care Committee of the Vall d\u0026rsquo;Hebron Institut de Recerca, in which animal facilities were used for the experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.\u0026nbsp;\u0026nbsp;\u003c/strong\u003eTranscriptome profiling\u003c/p\u003e\n\u003cp\u003eTranscriptome profiling of 15 rat liver tissue samples from STUDY-3 (CD, n = 5; D4-MASLD, n = 5; D5-MASLD, n = 5) was performed using RNA-Seq. Briefly, 20 mg of liver tissue was weighed and RNA was isolated using the miRNeasy Mini Kit (217004; Qiagen, Hilden, Germany) following the manufacturer\u0026rsquo;s instructions. The sequencing library was prepared by Novogene Co., Ltd. (Cambridge, UK) using 1000 ng of total RNA. The resulting data were analyzed at the Vall d\u0026rsquo;Hebron Biostatistics Unit, using different software available according to a pre-processing pipeline. The dataset is available from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus database (accession number GSE282001). Overall similarities between samples, in a 2-dimention reduction, were assessed by Principal Component Analysis (PCA); Venn diagrams and heatmaps were used to represent multiple comparisons between differentially expressed genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.\u0026nbsp;\u0026nbsp;\u003c/strong\u003eAnalysis of the biological significance and comparison with human samples\u003c/p\u003e\n\u003cp\u003eWe analyzed the biological significance of differential gene expression caused by D4 -MASLD and D5-MASLD compared to the control diet. Gene Set Enrichment Analysis (GSEA) was performed to determine the pathways in which these genes were involved based on Gene Ontology (Biological Process category, GO-BP).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHuman liver transcriptome datasets from the GSE48452 database were used to identify the commonly dysregulated pathways between human stages of the disease, patients with MASLD (STEAT, n = 9), and patients with MASH (n = 17) vs. healthy individuals (CTL, n = 12). Common molecular pathway dysregulation in rat and human liver tissues was determined by GSEA, in previously transformed human genes to rat gene orthologs to obtain comparable biological terms using the Molecular Signatures Database package \u003cem\u003emsigdbr \u003csup\u003e14\u003c/sup\u003e\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.\u0026nbsp;\u0026nbsp;\u003c/strong\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using the GraphPad Prism software (GraphPad Software, San Diego, CA, USA). Continuous variables were tested using the Shapiro-Wilk test. Unpaired Student\u0026rsquo;s t-test was used to compare means between two groups and one-way ANOVA with Tukey\u0026rsquo;s HSD for multiple comparisons. For non-parametric data, the Mann-Whitney U test or Kruskal-Wallis test was applied. Statistical significance was set at P \u0026lt; 0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe statistical analysis for the differential expression analysis and the biological significance of the transcriptomic profile was performed using the statistical language \u0026ldquo;R\u0026rdquo; (R version 4.2.0) \u003csup\u003e15\u003c/sup\u003e.Enrichment analyses were performed using the clusterProfiler R package v4.0.5 \u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e\u003cstrong\u003e3.1.\u0026nbsp;\u0026nbsp;Models in STUDY-1\u003c/strong\u003e \u003cstrong\u003eexhibited metabolic syndrome, portal hypertension, and histological features of MASH, but not advanced fibrosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe rationale for this double-hit model was to assess whether increasing the total amount of glucose and fructose in drinking water and administration of LPS would induce fibrosis. Accordingly, all comparisons were made relative to the same diet without LPS (D1-MASLD) and the no-chow-diet control group was included (Fig. 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter 24 weeks, both groups in the STUDY-1 model exhibited high values of body weight, showing a significant but small decrease in rats fed with the diet supplemented with LPS (Suppl. Fig. 1). Both groups showed elevated fasting glucose, total cholesterol, and TG levels. Although the D1-MASLD+LPS group had substantially higher fasting glucose and TG levels than the D1-MASLD group, these differences were not statistically significant (Suppl. Table 2). The HOMA-IR values remained very similar between the groups (Suppl. Fig. 2).\u003c/p\u003e\n\u003cp\u003eThe two-hit D1-MASLD+LPS group displayed higher average values of PP compared to the D1-MASLD group (12.07 \u003cem\u003evs\u003c/em\u003e 10.5 mmHg) alongside higher IHVR values, although differences were not significant (Fig. 2).\u003c/p\u003e\n\u003cp\u003eHistological assessments revealed high steatosis scores in both groups, with at least 50% of the individuals showing inflammation. The group without LPS exhibited the highest percentage of individuals with steatosis (100%) and lobular inflammation (69%, with a few individuals scoring 3) (Suppl. Fig. 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFibrosis at week 24 was either mild or absent in both groups (Fig. 3A). Given the lack of clinically relevant findings, further assessments of this model in STUDY-1 are deemed unnecessary.\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.\u0026nbsp;\u0026nbsp;Models in STUDY-2 exhibited MASH-related fibrosis and portal hypertension but did not lead to complete metabolic syndrome\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe models in STUDY-2 had two different durations, 16 and 24 weeks, and included a higher concentration of Chol (2%) and 0.5%\u0026nbsp;CA\u0026nbsp;(Fig. 1). We anticipated that\u0026nbsp;the disease features would worsen at 24 weeks; however,\u0026nbsp;this was not the case, as most parameters showed no significant differences between the two time points. Therefore, our results focused\u0026nbsp;primarily on the 16-week intervention, with the 24-week groups mentioned to stress the lack of difference in important parameters.\u003c/p\u003e\n\u003cp\u003eAnimals fed the 16-week\u0026nbsp;D2-MASLD diet showed a trending increase in body weight compared to the CD group (Suppl. Fig. 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe 16-week D2-MASLD diet was associated with significant increases in fasting blood concentrations of ALT, AST, and total cholesterol, but not triglycerides, compared to the CD diet (Suppl. Table 2). Moreover, D2-MASLD did not affect serum glucose and insulin levels or HOMA-IR values at either 16 or 24 weeks (Suppl. Fig. 2 and Suppl. Fig. 4).\u003c/p\u003e\n\u003cp\u003eHemodynamic measurements revealed a significant increase in PP in the D2-MASLD group (52% increase) at 16 weeks compared with that in the CD group (Fig. 2).\u0026nbsp;The presence of portal hypertension was accompanied by a significant increase in the IHVR. There were no significant differences in the PP values between the 16- and 24-week time points (Suppl. Fig. 4).\u003c/p\u003e\n\u003cp\u003eAt 16 weeks, all individuals in the D2-MASLD group had a steatosis score of 3, and most (70%) had an inflammation score of 2 (70%) (Suppl. Fig. 3). Histological fibrosis assessment using the NASH-CRN system revealed that higher Chol content and the addition of CA in the diet led to significant liver fibrosis in most D2-MASLD individuals, with 78% (7/9) reaching F2 or greater. Cirrhosis (F4) was observed in one individual from the D2-MASLD group at 16 weeks (Suppl. Table 3).\u0026nbsp;Accordingly, the percentage of\u0026nbsp;the area occupied by collagen deposition, as measured by image analysis, was significantly higher in the D2-MASLD group than in\u0026nbsp;the control\u0026nbsp;group at 16 weeks (Fig. 3). A slight non-significant increase in fibrosis was observed over time at 24 weeks (Suppl. Fig. 4C).\u003c/p\u003e\n\u003cp\u003eIn addition, exploring the ductular reaction by CK-7 labelling revealed a significant increase in CK-7-stained areas in the livers of D2-MASLD rats compared to controls, indicating ongoing liver injury and ductular proliferation (Suppl. Fig. 5).\u003c/p\u003e\n\u003cp\u003eProtein analysis by western blotting revealed a significant decrease in intrahepatic protein expression levels of P-eNOS/eNOS and P-AKT/AKT, along with a trend towards decreased KLF2 levels in the D2-MASLD group compared to controls (Suppl. Fig. 6). These findings suggest that in addition to fibrosis, endothelial dysfunction represents another underlying mechanism contributing to the increased IHVR caused by this diet model.\u003c/p\u003e\n\u003cp\u003eThe role of the hepatic insulin-signaling pathway was also addressed through the expression of genes encoding the insulin receptor substrates IRS-1 and IRS-2. Although D2-MASLD animals did not exhibit features associated with systemic insulin resistance, namely fasting hyperglycemia and hyperinsulinemia, significant repression of both genes was found in the livers of these rats compared to the CD group (Fig. 4).\u0026nbsp;Thus, impairment of the IRS/PI3K/AKT pathway indicated the presence of hepatic insulin resistance in this model.\u003c/p\u003e\n\u003cp\u003eFurthermore, the possible contribution of adipokines in the development of hepatic insulin resistance was examined. For this purpose, hepatic expression of AdipoR2 and LepR was analyzed. Gene expression analysis revealed a significant decrease in the hepatic mRNA expression of AdipoR2 in the D2-MASLD group compared to that in the CD group, whereas LepR was significantly overexpressed (Fig. 4).\u0026nbsp;These findings also indicate altered hepatic insulin sensitivity in this model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.\u0026nbsp;\u0026nbsp;Models in STUDY-3 recapitulate key features of MASLD with metabolic syndrome, including both systemic and hepatic insulin resistance, as well as advanced fibrosis and portal hypertension\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe aim of STUDY-3 was to reduce the concentrations of Chol or CA to identify a combination that preserves the characteristics of the STUDY-2 model, using a more physiologically relevant amount of these components in the diet, while still maintaining key metabolic features such as obesity. Additionally, because extending the model to 24 weeks did not significantly worsen its outcomes, the duration of this model was set at 20 weeks (Fig. 1).\u003c/p\u003e\n\u003cp\u003eAnimals fed the D4-MASLD and D5-MASLD diets, containing no or low CA concentrations (2% Chol + 0% CA and 2% Chol + 0.1% CA, respectively), showed significant increases in body weight compared to the CD group (Suppl. Fig. 1). In contrast, the D3-MASLD group, which had the highest CA concentration (2% Chol + 0.5% CA), exhibited a body weight similar to that of the CD group. (Suppl. Fig. 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll diet groups showed elevated levels of AST, ALT, total cholesterol, and albumin compared to those in the CD group (Suppl. Table 2). Evaluation of the\u0026nbsp;HOMA-IR index revealed a significant increase only in the groups with low or no CA in the diet (i.e., D4-MASLD and D5-MASLD), whereas no systemic insulin resistance was observed in the D3-MASLD group, which contained high CA concentrations (Suppl. Fig. 2).\u003c/p\u003e\n\u003cp\u003eHemodynamic measurements revealed significantly elevated PP values in all dietary groups compared with the controls (Fig. 2). Notably, those supplemented with CA demonstrated higher PP values than those supplemented with CD. In contrast,\u0026nbsp;IHVR did not show significant differences in any of the dietary groups compared with the controls.\u003c/p\u003e\n\u003cp\u003eHistological examination revealed high steatosis scores across all dietary groups, with more than 50% of the individuals showing severe steatosis (Suppl. Fig. 3). Additionally, more than 25% of individuals in all dietary groups exhibited an inflammation score of at least 1, with over 25% reaching a score of 2 (Suppl. Fig. 3).\u003c/p\u003e\n\u003cp\u003eAs for fibrosis, in the D3-MASLD group, 16.7% of individuals had significant fibrosis (stages F2-F3) and 83.3% showed F1 or no fibrosis. The diet without CA, D4-MASLD, yielded advanced fibrosis (\u0026ge; F3) in 36.4% of the individuals, but 63.6% had F1 or no fibrosis. In the D5-MASLD group, 30% of the individuals had advanced fibrosis and 50% exhibited significant fibrosis, whereas the other half exhibited either mild (F1) or no fibrosis (Suppl. Table 3). Quantitative analysis of the fibrotic area in liver tissues showed that all diets led to a significant increase in the percentage of fibrotic area compared to that in the CD group at 20 weeks (Fig. 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll dietary groups showed a significant increase in CK-7-stained areas, thus underlining the potential role of\u0026nbsp;the ductular reaction, characterized by bile duct hyperplasia (Suppl. Fig. 5).\u003c/p\u003e\n\u003cp\u003eEndothelial dysfunction analysis showed that the D5-MASLD group exhibited lower P-AKT/AKT and P-eNOS/eNOS ratio values than the CD group, although these differences were not statistically significant. Additionally, KLF2 expression was significantly lower in all groups than in the control group (Suppl. Fig. 6).\u003c/p\u003e\n\u003cp\u003eSimilar to STUDY-2, intrahepatic insulin resistance was assessed by analyzing the expression of IRS-1 and IRS-2 in the liver using RT-qPCR. A significant reduction in the mRNA expression of both genes was observed in all three dietary groups compared with that in the CD group. To further support the presence of intrahepatic insulin resistance, AdipoR2 and LepR gene expressions were also examined. All dietary groups in STUDY-3 showed a significant downregulation of AdipoR2 and upregulation of LepR. These findings, along with the reduced expression of insulin receptors, indicate altered insulin sensitivity in the liver across dietary groups (Fig. 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe transcriptional profile of D4-MASLD and D5-MASLD diets from STUDY-3 underline pathway changes in the proximity to human MASLD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDifferential gene expression \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe transcriptional profiles of the D4-MASLD, D5-MASLD, and CD groups from STUDY-3 were analyzed. Principal component analysis revealed distinct clustering of rat samples, (Suppl. Fig. 7A). suggesting significant differences between the diet groups and controls, while also indicating a high degree of similarity between the two diets.\u003c/p\u003e\n\u003cp\u003eDifferential expression analysis comparing the effects of the diets with their controls at an adjusted p value \u0026le; 0.01, is represented in the heatmap in Fig. 5, demonstrating a clear distinction in the expression patterns between the CD samples and the D4-MASLD and D5-MASLD groups. Using a less restrictive non-adjusted p-value allowed the identification of only 39 differentially expressed genes between the diets (Suppl. Fig. 7B).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBiological significance\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the GSEA analysis, the most significant effects caused by D4-MASLD and D5-MASLD, compared to their controls, involved the activation of various pathways related to inflammation and immune response (Suppl. Fig. 8). The top 15 GO-BP terms from the comparison between D5-MASLD \u003cem\u003eversus\u003c/em\u003e D4-MASLD diets also indicated the activation of inflammation, suggesting a stronger effect of D5-MASLD on immune response alterations than D4-MASLD. Additionally, comparison between the two diets revealed increased activation of pathways related to microbiota alterations, intestinal wall dysfunction, and bacterial translocation in the D5-MASLD group. These pathways modulate responses to external stimuli, such as bacteria, xenobiotics, and cellular processes including cell death and apoptosis.\u0026nbsp;The analysis of the top five GO-BP networks presented in Fig. 6 further reinforces these findings by showing that an important number of differentially expressed genes are connected to just five categories: leukocyte cell adhesion and regulation, response to polysaccharides, response to molecules of bacterial origin, and cell killing.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSimilarity with human samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe compared the rat and human transcriptomic profiles to identify significant pathways shared between the MASLD diet models and different stages of human disease. Venn diagrams in Suppl. Fig. 9\u0026nbsp;illustrates the shared elements for the four types of comparisons: D4-MASLD with human MASLD or MASH and D5-MASLD with human MASLD or MASH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe GO terms shared between rats and humans represent various pathways, many of which are redundant and contain slightly different terms that can be grouped into broader categories. Redundancy reduction analysis clustered these pathways into 13-18 groups, which were very similar across the comparisons between D4-MASLD and D5-MASLD and showed minimal differences in the stages of the disease in humans. These results are presented in the bar plot of the redundancy reduction analysis, highlighting the top shared pathways for the four comparisons (Fig. 7). The analysis showed that the most significantly associated pathways affected by D4-MASLD and D5-MASLD were shared by the disease in humans, underscoring the importance of these altered biological processes in the MASLD/MASH spectrum. Key pathways include inflammation, activated immune response, dysbiosis, bacterial translocation, and the activation of responses to external stimuli. Additionally, pathways related to calcium ion activation, the emergence of external structural organization related to fibrosis, and the suppression of pathways involved in cholesterol biosynthesis and fatty acid metabolism are also represented.\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eIn this study, we conducted a multistep process of continuous sequential refining of our MASLD model in rats \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e until a comprehensive model that reproduces metabolic syndrome features, steatohepatitis, advanced fibrosis, and portal hypertension with a transcriptomic profile that resembles human MASLD was developed. The final model consisted of a 20-week high-fat diet with high concentrations of cholesterol (2%) and a glucose-fructose beverage, to which the addition of cholic acid (CA) at low concentrations (0.1%) substantially increased the percentage of individuals achieving significant fibrosis.\u003c/p\u003e \u003cp\u003eIn a thorough comparative study of MASLD murine models, Vacca et al. evaluated and ranked these models (dietary, genetic, and toxic) based on their alignment with three critical features of MASLD in humans: clinical metabolic phenotype, liver histopathology, and liver transcriptome benchmarked against human transcriptomic changes \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. After assessing data from 509 mice and 89 rats over 39 models, the authors did not find a single model that fully replicated all aspects of human MASLD. The desired components of the clinical metabolic phenotype include obesity, dyslipidemia, and increased ALT and AST levels, along with the desired histopathological changes in steatohepatitis and significant fibrosis (\u0026ge;\u0026thinsp;F2).\u003c/p\u003e \u003cp\u003eOur model deviates from some of the criteria utilized by Vacca et al. \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e First, we did not consider that transaminase elevation was a robust indicator of clinically relevant metabolic phenotype (which was present in our models). Besides obesity and dyslipidemia, we relied on glucose metabolism disturbances to evaluate whether each tested model achieved the \u0026ldquo;metabolic triad.\u0026rdquo; We assessed three aspects of glucose metabolism derangement: hyperglycemia, systemic insulin resistance, and intrahepatic insulin resistance. The latter was considered mandatory, as it is one of the earlier steps in MASLD pathophysiology \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, whereas the other two served as markers of type 2 diabetes, which is not develop in all patients with MASLD. Second, we placed special emphasis on achieving advanced fibrosis to recapitulate as much as possible the full spectrum of MASLD natural history, with the ultimate goal of generating a model that allows studying its pathophysiology and assessing the efficacy of therapeutic interventions against advanced chronic disease. Third, we used a rat model primarily to study portal hypertension, and in later phases, to investigate its mechanisms and response to treatment. Fourth, we did not consider that genetic or toxic models could reliably mimic human disease because of their great differences in inducing disease compared to MASLD pathophysiology. Thus, we relied on a dietary model that might be enhanced in terms of achieving more advanced stages of the disease by adding low concentrations of biliary salt (CA) that is already present in the body.\u003c/p\u003e \u003cp\u003eOur study suggests that when the priority of the model is to fully develop a clinically significant metabolic phenotype leading to metabolic disturbances that mimic MASLD in humans, rather than achieving significant or advanced fibrosis, the use of CA should be carefully considered. For dyslipidemia, we used a high cholesterol concentration (2%) in our model. By binding to the farnesoid X receptor (FXR), CA increases the absorption of dietary cholesterol from the intestine and may repress CYP7A1 (a key enzyme in bile acid biosynthesis), thereby promoting cholesterol accumulation in the liver \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In addition, bile acids such as CA lower serum TG levels by reducing SREBP-1c gene expression \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This is consistent with our results showing hypercholesterolemia, but not hypertriglyceridemia. Moreover, the potential dose-dependent effects of CA on weight gain and glucose metabolism were noteworthy. Previous studies have shown that Sprague-Dawley rats fed a high-cholesterol diet supplemented with high-dose CA developed the histopathological features of MASH but lacked obesity and insulin resistance \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In our study, body weight gain over 20 weeks decreased in a dose-dependent manner, with rats receiving 0.5% CA maintaining a body weight comparable to that of controls. Regarding insulin resistance, rats receiving 0.5% CA did not develop systemic insulin resistance, whereas those receiving either 0.1% or none did. High concentrations of CA have been shown to improve insulin resistance and obesity in MASLD models via multiple mechanisms. CA activates bile acid receptors, such as FXR and TGR5, which regulate metabolism, enhance lipid breakdown, and reduce glucose and TG synthesis in the liver \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. It also alters gene expression related to lipid metabolism, decreases liver fat accumulation, and improving insulin sensitivity \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Additionally, it modulates the gut microbiota, promoting beneficial bacteria that improve metabolic health, reduce inflammation, and enhance gut barrier function \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Therefore, developing a MASLD model that captures both advanced fibrosis and metabolic syndrome features requires balancing CA concentrations low enough to promote advanced fibrosis but high enough to maintain metabolic alterations, as seen in the D5-MASLD diet (2% Chol\u0026thinsp;+\u0026thinsp;0.1% CA).\u003c/p\u003e \u003cp\u003eWith regard to liver fibrosis, the rationale for developing a model that achieves both significant and advanced fibrosis can be succinctly summarized into two points. First, although MASLD is the most rapidly growing cause of cirrhosis, hepatocellular carcinoma, and liver transplantation globally, the pathophysiology and natural history of advanced MASLD are still largely unknown \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The second reason, equally relevant, is that despite dozens of clinical trials conducted in the field, we still lack licensed treatments for more advanced stages of the disease, cirrhosis in particular \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Therefore, we consider our model to be a milestone for translational research in the field. To the best of our knowledge, no prior murine model has achieved advanced fibrosis based on dietary intervention. In their study, Vacca et al. highlighted that significant fibrosis can be induced through three strategies, alone or combined, using a high cholesterol content (2%), extending the duration of the model (over 40 weeks), and genetic modifications \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. We obtained advanced fibrosis in a 20-week model that was neither genetically modified nor used significant amounts of toxic substances. Using low concentrations of CA, our model yielded significant fibrosis in 50% of subjects, with 30% exhibiting advanced fibrosis.\u003c/p\u003e \u003cp\u003ePortal hypertension is critical in MASLD advanced disease as it becomes increasingly important as a driver of complications during disease progression. Hence, the importance of a MASLD model that develops portal hypertension in the absence of cirrhosis has been reported in humans \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Sinusoidal endothelial dysfunction precedes inflammation and fibrosis in MASLD \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, which is in line with our findings of alterations in the hepatic protein expression of P-eNOS/eNOS, P-AKT/AKT, and KLF2. Reduced eNOS phosphorylation is likely due to the impaired vasoprotective function of KLF2, which may explain the diminished vasodilation capacity of the sinusoidal endothelium, resulting in decreased nitric oxide production and subsequent endothelial dysfunction \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. However, preliminary evidence points to distinct mechanisms of portal hypertension in MASLD that go beyond the already well-known association between liver fibrosis and endothelial dysfunction \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Notably, severe steatosis might induce portal hypertension at the sinusoidal level, and other inflammatory and mechanotransduction cues could be involved in the mechanisms of presinusoidal portal hypertension \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The potential impact of CA on portal hypertension is likely indirect, possibly through the modulation of liver metabolism, inflammation, or fibrosis \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In summary, our model offers a promising tool for comprehensively studying the various mechanisms involved in portal hypertension in MASLD, including the key role of immune responses.\u003c/p\u003e \u003cp\u003eIn the transcriptomic characterization of our models, we found that the addition of low-dose CA induced subtle yet non-negligible differences in gene expression and biological processes, despite the high overall similarity between the two diets. Various studies have shown that CA can induce inflammatory responses and alter the gut-liver axis, contributing to disease progression. Specifically, CA has been found to disrupt the integrity of the intestinal barrier, increase permeability, and promote the translocation of gut bacteria and their metabolites (e.g., LPS) into the liver. This triggers hepatic inflammation through the activation of toll-like receptors and nucleotide-binding oligomerization domain-like receptors, promoting liver fibrosis through pathways such as NF-κB and inflammasome signalling \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Furthermore, CA\u0026rsquo;s impact of CA on the gut-liver axis is linked to its interaction with bile acid receptors, such as FXR and TGR5 \u003csup\u003e34\u003c/sup\u003e. This is consistent with what has been previously discussed regarding both protective and pathological effects upon activation of these receptors, depending on the context and the CA concentrations used. This dual effect can either reduce or exacerbate liver inflammation and fibrosis. Our findings suggest that CA not only enhances inflammation but also alters the gut-liver axis, potentially increasing vulnerability to external stimuli, such as bacteria and xenobiotics. When comparing the transcriptomic profiles caused by these diets in rats with a database of patients with MASLD/MASH, key pathways, such as inflammation, immune response activation, dysbiosis, bacterial translocation, and fibrosis-related processes, are consistently implicated in both humans and rats. This strong overlap underscores the utility of these rat models for understanding human MASLD and MASH, as the biological processes involved appear to be highly conserved, particularly in terms of inflammation and immune response mechanisms.\u003c/p\u003e \u003cp\u003eThe ductal reaction is a hallmark of ongoing liver injury that suggests an inefficient regenerative response by hepatocytes, leading to the activation of hepatic progenitor cells as a secondary proliferative pathway in MASLD \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. These cells contribute to the formation of new hepatocytes, cholangiocytes, and ductules, and are believed to play a role in fibrosis activation and progression of MASLD \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Whether the signs of ductular reaction observed in our model are due to the use of CA or inherent to MASLD pathophysiology and associated with disease progression, including the mechanisms of liver fibrosis and portal hypertension, warrants further studies.\u003c/p\u003e \u003cp\u003eThis study had several limitations that deserve consideration. First, we only analyzed male rats. Sex differences are a definite feature of MASLD, and sexual dimorphism in disease progression and metabolic response is increasingly recognized \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Another limitation arises from the STUDY-1 model, as it did not include a chow diet control group and several analyses were omitted. This was because the primary objective was to determine whether a more concentrated glucose-fructose HFGFD, either alone or in combination with LPS, would be sufficient to induce fibrosis. As this was not achieved, we concluded that the model lacked clinical relevance, and further studies were deemed unnecessary. Finally, varying durations across models make it difficult to compare the histological impact, limiting the interpretation of fibrosis progression over time.\u003c/p\u003e \u003cp\u003eIn conclusion, through a multi-step sequential process, we developed and characterized a dietary model of MASLD that fully recapitulates the most relevant clinical, histopathological, and transcriptomic aspects of human disease, while allowing the study of the pathophysiology and treatment of advanced fibrosis and portal hypertension.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe wish to thank our colleagues at the Statistics and Bioinformatics Unit (UEB) Vall d’Hebron Hospital Research Institute (VHIR) for their support in using the bioinformatics pipeline to\u0026nbsp;analyze RNA-seq\u0026nbsp;data and to discover biological significance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants PI21/00691 and PI22/01770 from Instituto de Salud Carlos III (ISCIII), as well as by the Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd, CB06/04/0007), and cofounded by European Union (ERDF/ESF, “A way to make Europe” “Investing in your future”). JMP received a grant from\u0026nbsp;the Vall\u0026nbsp;d’Hebron University Hospital Campus to intensify his research activities (2024-2025).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.M., J.G., and\u0026nbsp;J. M. P. conceived and designed the initial study. A.B., M.M.G., I.R., and M.S.C. conducted in vitro and animal studies. M.M.G., I.R., and M.M. approved the ethics\u0026nbsp;of the rats. M.T.S. performed the histological analysis. A.B., M.M.G., I.R., M.T.S., and M.M. analyzed the data.\u0026nbsp;M. M. G., A.B., M.M., and J. M. P. wrote the manuscript. M.M.G. and M.M. drafted the manuscript S.C.P., S.A., M.V.C., and J.G.\u0026nbsp;have revised the manuscript. All\u0026nbsp;authors\u0026nbsp;have provided\u0026nbsp;intellectual contributions and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.M.P. reports having received consulting fees from\u0026nbsp;the\u0026nbsp;MSD, Madrigal, Boehringer-Ingelheim, and Novo Nordisk. He has received speaking fees from Madrigal, Gilead, Intercept, and Novo Nordisk and travel expenses from Gilead, Rubió, Pfizer, Astellas, MSD, CUBICIN, and Novo Nordisk. He received educational and research support from Madrigal, Boehringer-Ingelheim, Gilead, Pfizer, Astellas, Accelerate, Novartis, Abbvie, ViiV, and MSD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll other authors have no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRinella, M. 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Sexual dimorphism of metabolic dysfunction-associated steatotic liver disease. \u003cem\u003eTrends Mol Med\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, (2024).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cimg 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liver fibrosis, portal hypertension","lastPublishedDoi":"10.21203/rs.3.rs-6376882/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6376882/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground and Aims:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFor decades, investigators have pursued the development of a comprehensive rodent model that fully recapitulates the pathophysiology of metabolic dysfunction-associated steatotic liver disease (MASLD) pathophysiology and mimics human disease. Dietary models are considered the most reliable in terms of reproducing human disease; however, no dietary rodent model has been reported in the proximity of human MASLD, allowing the study of the pathophysiology and treatment strategies for advanced fibrosis and portal hypertension.\u003c/p\u003e\u003cp\u003e\u003cb\u003eApproach and Results:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe conducted a multistep process of continuous sequential refinement of our MASLD model in rats until we achieved a comprehensive model that reproduced the clinical features of metabolic syndrome, steatohepatitis, advanced fibrosis, and portal hypertension with a transcriptomic profile resembling human MASLD. The final model consisted of a 20-week high-fat diet with high concentrations of cholesterol (2%) and a glucose-fructose beverage, to which adding cholic acid at low concentrations (0.1%) substantially increased the percentage of individuals achieving significant fibrosis at the endpoint.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOwing to its short duration, simplicity, versatility, and proximity to human MASLD, the proposed model could potentially serve a wide range of investigators working in the field of metabolism and liver disease, allowing significant advances in mechanistic insights into drug development.\u003c/p\u003e","manuscriptTitle":"A new dietary rat model fully recapitulates metabolic dysfunction-associated steatotic liver disease pathophysiology and mimics human disease with advanced liver fibrosis and portal hypertension","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 08:47:26","doi":"10.21203/rs.3.rs-6376882/v1","editorialEvents":[],"status":"published","journal":{"display":false,"email":"[email protected]","identity":"lab-animal","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"laban","sideBox":"Learn more about [Lab Animal](http://www.nature.com/laban/)","snPcode":"","submissionUrl":"","title":"Lab Animal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"bdc41bfb-426f-45c9-b24a-f2f874da9ed6","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":48263244,"name":"Health sciences/Gastroenterology/Hepatology/Liver diseases/Non-alcoholic fatty liver disease"},{"id":48263245,"name":"Health sciences/Diseases/Gastrointestinal diseases/Liver diseases/Liver fibrosis"}],"tags":[],"updatedAt":"2026-04-04T07:06:05+00:00","versionOfRecord":{"articleIdentity":"rs-6376882","link":"https://doi.org/10.1038/s41684-026-01710-z","journal":{"identity":"lab-animal","isVorOnly":false,"title":"Lab Animal"},"publishedOn":"2026-04-03 04:00:00","publishedOnDateReadable":"April 3rd, 2026"},"versionCreatedAt":"2025-06-25 08:47:26","video":"","vorDoi":"10.1038/s41684-026-01710-z","vorDoiUrl":"https://doi.org/10.1038/s41684-026-01710-z","workflowStages":[]},"version":"v1","identity":"rs-6376882","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6376882","identity":"rs-6376882","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}