Nonalcoholic Steatohepatitis Group Research Articles

PSIV-23 Transcriptomic analysis revealed the mechanisms of resilience and susceptibility to nonalcoholic steatohepatitis in dairy goats under high-concentrate diet

Abstract Liver health is vital for growth and health of ruminants, which can directly affect their performance. High-concentrate diet (HCD) feeding, a common practice to meet the energy requirements for animal production and growth, has been known to induce liver damage, including nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH) in ruminants. To date, the regulatory mechanisms of liver metabolic dysfunctions in ruminants induced by HCD are not well defined. To elucidate molecular regulatory mechanisms underlying liver dysfunction in ruminants, we compared liver transcriptome and single-cell transcriptome of dairy goats that had varied responses to the HCD, aiming to underpin the key mechanisms behind resilience and susceptibility to NASH in ruminants. After feeding 30 dairy goats with low-concentrate diet (LCD, n = 15, defined as Con) or high-concentrate diet (HCD, n = 15) for 6 wk, 10 of them developed NASH (defined as NASH), while the other 5 did not showed any NASH symptom (defined as NASH-tolerance, NASH-T) under HCD. Liver tissues were collected to extract RNA. The paired-end RNA-seq library was sequenced with a NovaSeq6000 sequencer (Illumina). Real-time quantitative PCR was conducted to verify the significantly different genes among groups. Liver single-cell transcriptome was performed using 10×Genomics Chromium system. Liver transcriptome analysis revealed that the expression level of genes involved in the interleukin (IL)-17 signaling pathway, including IL-17A (P = 0.035; 0.001), Act1 (P = 0.036; 0.002), FOSB (P = 0.041; 0.048) and IL-1β (P = 0.022; 0.002) in the NASH group were significantly greater than those in the Con and NASH-T groups. Hepatic single-cell RNA sequencing identified seven cell types in the liver, including hepatocytes, macrophages, T cells, endothelial cell, natural killer (NK) cell, hepatic stellate cells (HSCs), B cells. In T cell subset, significantly decreased T helper 17 (TH17) cells and increased regulatory T (Treg) cells were detected in the NASH group compared with Con and NASH-T groups. In TH17 cell, the expression levels of IL-17A (P = 0.004; 0.009) and IL-23R (P = 0.007; 0.01; the surface antibodies of TH17 cells) in NASH group were significantly greater than those in the Con and NASH-T groups. The expression levels of Foxp3 (P < 0.001; 0.013), IL-2R (P < 0.001; 0.001), CTLA-4 (P = 0.005; 0.017) and CD127 (P = 0.004; 0.009; the surface antibodies of Treg cells) in NASH group were significantly less than those in the Con and NASH-T groups. Our results revealed the role of liver immune cells in maintaining tolerance to NASH in dairy goats under HCD, which provides new understanding in pathogenesis of NASH under HCD. Further studies are needed to identify major factors that drive the changes of ratio of TH17/Treg cell.

MiR-378a-3p and miR-181b-5p as nonalcoholic steatohepatitis non-invasive diagnostic biomarkers and their correlations with liver fibrosis

Nonalcoholic steatohepatitis (NASH) is one of the most common liver diseases that is diagnosed by biopsy and, therefore, requires the development of non-invasive tests for diagnosis. Serum levels of microRNAs were shown to correlate with the severity of various liver diseases, but the role of miR-378a and miR-181b-5p in NASH remains unclear. The current study aims to assess the serum expression level of miR-378a-3p and miR-181b-5p in patients with NASH and to find out the correlation of these indices with liver fibrosis. The case-control research was carried out on 60 patients with confirmed NASH relative to 50 healthy subjects. Extraction and reverse transcription of micro RNAs was performed using miRCURY LNA RT Kit (Qiagen, Maryland, USA) Detection of miR-378a-3p and miR-181b-5p was done using qPCR. It was shown that serum expression level of miR-378a-3p in NASH patients was downregulated with a median range fold change 0.29, while that of miR-181b-5p was upregulated with a median range fold change 13.08. The ROC curve was constructed to discriminate the NASH group from the healthy group. The optimal cut-off value of miR-378a-3p was ≤0.031 with a sensitivity of 65%, the optimal cut-off value of miR-181b-5p was ≥ 0.063 with a sensitivity of 93.3%. Statistically significant positive correlation between miR-181b-5p level and fibroscan data was demonstrated. The present study showed that serum miR-378a-3p and miR-181b-5p could be used as biomarkers of NASH. Keywords: liver fibrosis, miR-181b-5p, miR-378a-3p, nonalcoholic steatohepatitis (NASH)

Liver biopsy in patients with gall stone disease and concomitant non-alcoholic fatty liver disease undergoing cholecystectomy: A prospective observational study

Objective: Gallstone disease (GSD) and non-alcoholic fatty liver disease (NAFLD) share common risk factors. NAFLD can progress to non-alcoholic steatohepatitis (NASH), which may lead to severe liver conditions. This study aimed to assess the prevalence of NASH and associated factors in patients with GSD and fatty liver undergoing cholecystectomy. Material and Methods: This prospective observational study was conducted from March 2021 to June 2023 and included 134 patients diagnosed with GSD and fatty liver based on preoperative ultrasound. Core liver biopsies were obtained during cholecystectomy. Preoperatively, clinical, anthropometric, demographic, biochemical variables, and FibroScan parameters were recorded. Results: NASH was found in 21 (15.67%) patients, while 50 (37.31%) patients had probable NASH, and 63 (47.01%) had non-NASH scores. Metabolic syndrome was present in 63.6% of the patients. Univariate analysis revealed significant differences in AST and ALT values between the NASH and nonNASH groups. In multivariate analysis, AST was statistically significant (p= 0.041). Mean controlled attenuation parameter in patients with non-NASH was 219.40 ± 60.44 dB/m, and in patients with NASH, it was 265.48 ± 63.47 dB/m (p= 0.006). Fibrosis was present in 33 of the 82 slides examined, with 17 patients having grade 2 and two patients with grade 3 fibrosis. Conclusion: The high prevalence of NASH among GSD patients highlights a significant public health issue, prompting consideration for liver biopsy in individuals with NAFLD and GSD undergoing laparoscopic cholecystectomy.

Nonalcoholic steatohepatitis increases plasma retention of sorafenib-glucuronide in a mouse model by altering hepatocyte hopping

Hepatocyte hopping is the hepatocyte-to-sinusoid-to-hepatocyte shuttling that increases the efficiency of hepatic elimination of xenobiotics. This phenomenon is mediated via efflux of hepatic metabolites by Mrp3 and reuptake by Oatp transporters in sequential hepatocytes until eventual biliary efflux by Mrp2. Sorafenib-glucuronide (SFB-G), the major metabolite of sorafenib (SFB), undergoes hepatocyte hopping, leading to efficient biliary elimination. Nonalcoholic steatohepatitis (NASH) alters the functioning of transporters involved in hepatocyte hopping. The purpose of this study was to quantify the effect of NASH on the three drug disposition processes of hepatocyte hopping. Male FVB and C57BL/6 wild-type (WT), Oatp1a/1b cluster knockout (O−/−), and Mrp2 knockout (Mrp2−/−) mice were fed a methionine and choline deficient (MCD) diet to induce NASH. Mice were administered 10 mg/kg SFB via oral gavage and concentrations of SFB and SFB-G in plasma quantified using liquid-chromatography tandem mass spectrometry. Compared to WT, plasma area under the concentration-time curve (AUC) of SFB-G increased by 108-fold in the O–/–-C group and by 345-fold in the Mrp2–/–-C group. In the WT-NASH group, up-regulation of Mrp3 and decreased Mrp2 function, along with reduced Oatp uptake, elevated SFB-G AUC by 165-fold. SFB-G AUC in the O–/–-NASH group increased by 108-fold compared to WT-C (3.2-fold compared to O–/–-C). SFB-G AUC in the Mrp2–/– -NASH group increased by 450-fold (1.2-fold compared to Mrp2–/–-C). Taken together, the mislocalization of Mrp2 in NASH is a major contributor to the decrease in SFB-G biliary efflux, but decreased Oatp uptake and enhanced sinusoidal efflux also limit the contribution of downstream hepatocytes, resulting in plasma retention that recapitulates the altered pharmacokinetics observed in human NASH.

Single and Mixed Strains of Probiotics Reduced Hepatic Fat Accumulation and Inflammation and Altered Gut Microbiome in a Nonalcoholic Steatohepatitis Rat Model.

As gut dysbiosis has been implicated in the pathogenesis of nonalcoholic steatohepatitis (NASH), probiotic supplementation might be a potential treatment for this condition. The aim of this study was to evaluate the effects of single- and mixed-strain probiotics on the severity of NASH induced by a high-fat, high-fructose (HFHF) diet and their mechanisms of action. Male Sprague-Dawley rats were divided into four groups (n = 7 per group): control group, NASH group, NASH + single-strain group, and NASH + mixed-strain group. In the single-strain and mixed-strain groups, rats received Lactobacillus plantarum B7 and Lactobacillus rhamnosus L34 + Lactobacillus paracasei B13 by oral gavage once daily, respectively. The duration of the study was 6 weeks. Liver tissue was used for histopathology, hepatic fat content was assessed by Oil Red O staining and hepatic free fatty acid (FFA), and hepatic TLR4 and CD14 expression were assessed by immunohistochemistry. Fresh feces was collected for gut microbiota analysis. Liver histology revealed a higher degree of fat accumulation, hepatocyte ballooning, and lobular inflammation in the NASH group, which improved in probiotics-treated groups. The amounts of hepatic fat droplets and hepatic FFA levels were more pronounced in the NASH group than in the control and treatment groups. Serum TNF- α levels were significantly higher in the NASH group than in control and probiotic groups. The expression of CD14 and TLR4 increased in the NASH group as compared with the control and probiotics-treated groups. Alpha diversity was reduced in the NASH group, but increased in both treatment groups. The relative abundance of Lactobacillus significantly decreased in the NASH group, but increased in both treatment groups. The relative abundance of Akkermansia significantly increased in the NASH group, but decreased in both treatment groups. In conclusion, both single-strain and mixed-strain probiotics could improve NASH histology by suppressing inflammatory responses in the liver, with this improvement potentially being associated with changes in the gut microbiota.

Gamma-glutamyltransferase (GGT) is a predictor of NAFLD activity score for diagnosing non- alcoholic steatohepatitis (NASH)

Nonalcoholic fatty liver disease (NAFLD) encompasses a spectrum of conditions ranging from simple steatosis to steatohepatitis, advanced fibrosis and end stage liver disease. Despite the high prevalence and severity of hepatic illness, NAFLD remains underdiagnosed, because of few symptoms, lack of accurate laboratory markers. The study was aimed at to evaluate a bio-chemical score for diagnosing non-alcoholic steatohepatitis. A hospital based cross-sectional observational study was carried out for a period of two years from July 2013 to June 2015 in the Department of Hepatology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh. The study was conducted among 50 patients of NAFLD attending at department of Hepatology and underwent for biochemical investigations and liver biopsy with NAFLD Activity Score (NAS). All data were presented as mean ± SD and analyzed by SPSS (version 16). Qualitative data were analyzed by Chi-square test and quantitative data were analyzed by student’s t-test. Performance of the test were assessed by sensitivity and specificity test. Statistically significant result were considered when p value < 0.05. Total patients were divided into two groups 25 were NASH and 25 were non- NASH. Mean GGT was found 73.6±48.6 U/L in NASH group and 49.9±25.4 U/L in non-NASH group. There was significant difference in the NAFLD activity score for diagnosing NASH between elevated and normal GGT (P value 0.035). Higher GGT values correlated with higher specificity. The Gamma-lutamyltransferase (GGT) has been proposed as a noninvasive and available marker for assessment of NASH. Bangladesh Med J. 2023 May; 52(2): 6-10

Association between paravertebral muscle radiological parameter alterations and non-alcoholic fatty liver disease.

To assess changes in laboratory indices, paravertebral muscle (PVM) fat infiltration and multi b-value DWI parameters and their potential correlation with NAFLD. This retrospective analysis included 178 patients with histopathologically confirmed NAFLD, incluiding 76 with non-alcoholic steatohepatitis (NASH). Differences in PVM fat infiltration ratio (FIR), DWI parameters, and laboratory indices were compared between two groups. The correlation between FIR and NAFLD activity score (NAS) was also analysed. Binary logistic regression was used to identify the independent risk factors for NASH. The clinical utility of PVM fat infiltration, DWI parameters, and laboratory indices for diagnosing NASH in patients with NAFLD was evaluated using receiver operating characteristic (ROC) curves. The FIRs at the L2 and L3 levels were significantly higher in the with NASH group than those in the without NASH group. The heterogeneity index (α) and perfusion fraction (f) values at the L3 level of PVM were lower in the with NASH group. Moreover, the FIR at the L3 level was positively correlated with NAS. FIR at the L3 level was an independent risk factor for NASH along with alanine aminotransferase level. The area under the ROC curve (AUC) using L3 level PVM radiological parameters and laboratory indices for diagnosing NASH in patients with NAFLD was significantly higher than that using the degree of PVM fat infiltration, DWI parameters, or laboratory indices alone. Radiological parameters of the PVM were correlated with NAFLD. An integrated curve combining PVM radiological parameters may help distinguish NASH from NAFLD, thereby offering novel insights into the diagnosis of NASH.

Liver Fatty Acid-binding Protein Is a More Reliable Biomarker for Liver Injury in Nonalcoholic Steatohepatitis than Other Etiologies of Hepatitis.

Liver fatty acid-binding protein (LFABP) controls hepatocyte lipid metabolism and can be a biomarker in liver diseases. We compared the correlation of LFABP levels with liver histology in viral hepatitis and nonalcoholic fatty liver disease (NAFLD) and investigated the utility of serum LFABP as a biomarker for liver damage. We included 142 patients (60 chronic viral hepatitis B [CHB], 35 chronic viral hepatitis C [CHC], 47 NAFLD) and 40 healthy controls. LFABP levels were determined in all participants, and a liver biopsy was performed on patients. The nonalcoholic steatohepatitis (NASH) activity score (NAS), hepatosteatosis, liver inflammation, and fibrosis were evaluated for NAFLD patients. Ishak's histological scores were used for viral hepatitis. The correlation between LFABP levels and histologic scores was assessed in each group. Serum LFABP levels in CHB, CHC, NAFLD, and control groups were 2.2, 3.5, 7.6, and 2.1 ng/mL, respectively. LFABP levels were significantly higher in the NAFLD group compared to the control, CHC, and CHB groups. LFABP was significantly higher in the NASH group than in nonalcoholic steatohepatitis, 8 ng/mL and 5.4 ng/mL, respectively (P = .001). In the NAFLD group, LFABP levels showed a moderate positive correlation with NAS score (r = 0.58, P <.001), ballooning degeneration (r = 0.67, P <.001), and lobular inflammation (r = 0.62, P <.001). A logistic regression study showed that the level of LFABP was predictive of NASH independent of age, gender, homeostasis model of IR, body mass index, aspartate aminotransferase, and alanine aminotransferase (OR = 1.869, P = .01). LFABP specifically correlates with liver histology in NAFLD compared to viral hepatitis. Additionally, it can distinguish NASH from simple steatosis. LFABP may be a valuable biomarker for hepatocyte injury in NASH.

Key factor screening in mouse NASH model using single-cell sequencing combined with machine learning

AimsTo identify and analyze genes closely related to the progression of nonalcoholic steatohepatitis (NASH) by employing a combination of single-cell RNA sequencing and machine-learning algorithms. Main methodsSingle-cell RNA sequencing (scRNA-seq) analysis was performed to find the cell population with the most significant differences between the Chow and NASH groups. This approach was used to validate the developmental trajectory of this cell population and investigate changes in cellular communication and important signaling pathways among these cells. Subsequently, high dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA) was used to find the key modules in NASH. Machine learning analyses were performed to further identify core genes. Deep learning techniques were applied to elucidate the correlation between core genes and immune cells. The accuracy of this correlation was further confirmed using deep learning techniques, specifically Convolutional Neural Networks. Key findingsBy comparing scRNA-seq data between the Chow and NASH groups, we have observed a notable distinction existing in the Kupffer cell population. Signaling interactions between hepatic macrophages and other cells were significantly heightened in the NASH group. Through subsequent analysis of macrophage subtypes and key modules, we identified 150 genes tightly associated with NASH. Finally, we highlighted the 16 most significant core genes using multiple iterations of machine learning. Furthermore, we pointed out the close relationship between core genes and immune cells. SignificancesUsing scRNA-seq analysis and machine learning, we can distinguish NASH-related genes from large genetic datasets, providing theoretical support in finding potential targets for the development of novel therapies.

Amino acid metabolomics and machine learning for assessment of post-hepatectomy liver regeneration

ObjectiveAmino acid (AA) metabolism plays a vital role in liver regeneration. However, its measuring utility for post-hepatectomy liver regeneration under different conditions remains unclear. We aimed to combine machine learning (ML) models with AA metabolomics to assess liver regeneration in health and non-alcoholic steatohepatitis (NASH).MethodsThe liver index (liver weight/body weight) was calculated following 70% hepatectomy in healthy and NASH mice. The serum levels of 39 amino acids were measured using ultra-high performance liquid chromatography–tandem mass spectrometry analysis. We used orthogonal partial least squares discriminant analysis to determine differential AAs and disturbed metabolic pathways during liver regeneration. The SHapley Additive exPlanations algorithm was performed to identify potential AA signatures, and five ML models including least absolute shrinkage and selection operator, random forest, K-nearest neighbor (KNN), support vector regression, and extreme gradient boosting were utilized to assess the liver index.ResultsEleven and twenty-two differential AAs were identified in the healthy and NASH groups, respectively. Among these metabolites, arginine and proline metabolism were commonly disturbed metabolic pathways related to liver regeneration in both groups. Five AA signatures were identified, including hydroxylysine, L-serine, 3-methylhistidine, L-tyrosine, and homocitrulline in healthy group, and L-arginine, 2-aminobutyric acid, sarcosine, beta-alanine, and L-cysteine in NASH group. The KNN model demonstrated the best evaluation performance with mean absolute error, root mean square error, and coefficient of determination values of 0.0037, 0.0047, 0.79 and 0.0028, 0.0034, 0.71 for the healthy and NASH groups, respectively.ConclusionThe KNN model based on five AA signatures performed best, which suggests that it may be a valuable tool for assessing post-hepatectomy liver regeneration in health and NASH.

Serum miR‑29 is increased in mice with early liver fibrosis.

Non-alcoholic steatohepatitis (NASH) is a fatty liver disease that is not caused by alcohol consumption and is characterized by fatty degeneration, inflammation and hepatocellular damage. Therefore, predicting future fibrosis is critical in the early stages of NASH to prevent disease progression. The present study examined histological changes in the liver as well as microRNA (miR/miRNA) expression changes in the liver and serum of NASH mice model to identify potential biomarker candidates that could predict early fibrosis. This study used 6-week-old C57BL/6NJcl male mice and fed the control with a standard solid diet (CE-2) for breeding and propagation and NASH groups with a high-fat diet [choline-deficient high-fat and 0.1% (w/v) methionine supplemented diet], respectively. Agilent Technologies miRNA microarray was used to investigate microRNA expression in the liver and serum. Hematoxylin and eosin staining of the livers of the NASH group mice during the second week of feeding revealed fatty degeneration, balloon-like degeneration and inflammatory cell infiltration, confirming that the mice were in a state of NASH. The livers of the NASH group mice at 6 weeks of feeding showed fibrosis. Microarray analysis revealed that miRNAs were upregulated and 47 miRNAs were downregulated in the liver of the NASH group. Pathway analysis using OmicsNet predicted miR-29 to target collagen genes. Furthermore, miR-29 was downregulated in the livers of NASH-induced mice but upregulated in serum. These findings suggested that lower miR-29 expression in NASH-induced liver would increase collagen expression and fibrosis. Early liver fibrosis suggests that miR-29 leaks from the liver into the bloodstream, and elevated serum miR-29 levels may be a predictive biomarker for early liver fibrosis.

Influence of nonalcoholic fatty liver disease severity on carotid adventitial vasa vasorum.

Nonalcoholic fatty liver disease (NAFLD) affects a quarter of the world's population and encompasses a spectrum of liver conditions, from non-alcoholic steatohepatitis (NASH) to inflammation and fibrosis. In addition, NAFLD also links to extrahepatic conditions like diabetes or obesity. However, it remains unclear if NAFLD independently correlates with the onset and progression of atherosclerosis. This cross-sectional study aimed to explore the relationship between NAFLD severity, assessed via liver biopsy, and early atherosclerosis using adventitial vasa vasorum (VV) density. It included 44 patients with obesity (33 with steatosis, 11 with NASH) undergoing bariatric surgery. Results revealed no significant differences in adventitial VV density between steatosis and NASH groups, neither in the mean values [0.759 ± 0.104 vs. 0.780 ± 0.043, P=0.702] nor left-right sides. Similarly, carotid intima-media thickness (cIMT) did not vary between these groups. Additionally, no linear correlation existed between VV density and cIMT. Only gender showed an association with VV density. These findings suggest that NASH severity doesn't independently drive early atherosclerosis or affects cIMT. Gender might play a role in early atherosclerotic disease in NAFLD, impacting VV density and cIMT. This highlights the need to consider other risk factors when evaluating cardiovascular risk in NAFLD patients.

Inflammatory Protein Signatures as Predictive Disease-Specific Markers for Non-Alcoholic Steatohepatitis (NASH).

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic disease worldwide, consisting of a broad spectrum of diseases such as simple steatosis (NAFL), non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma. Hepatic inflammation plays a key role in the pathophysiology of NAFLD. Inflammatory mediators such as cytokines and chemokines are considered as contributing factors to NAFLD development and progression. In the present study, we aimed to investigate the inflammatory protein signatures as predictive disease-specific markers for non-alcoholic fatty liver disease (NAFLD). This cross-sectional study included healthy control (n = 64), NAFL (n = 109), and NASH (n = 60) human subjects. Serum concentrations of various cytokines and chemokines were evaluated using sensitive multiplex assays. We used principal component analysis (PCoA) to reveal distinct differences in the levels of cytokines and chemokines between each of the study groups. Further, a random forest classification model was developed to identify the panel of markers that could predict diseases. The protein-protein network analysis was performed to determine the various signaling pathways associated with the disease-specific panel of markers. Serum concentrations of TNF-α, IL-1β, IL-1ra, G-CSF, PDGF-BB, MCP-1, MIP-1a, MIP-1b, RANTES, eotaxin, IL-8 and IP-10 were significantly increased in NASH group as compared to control group. Furthermore, serum concentrations of IL-9 and IL-13 were significantly lower in the NASH group, whereas IL-2 levels were significantly decreased in the NAFL group when compared to the control group. PCoA results demonstrated statistically significant differences in cytokines and chemokines between each of the study groups (PERMANOVA p = 0.001; R2 = 0.102). RANTES, IL-1ra, MIP-1b, IL-2, and G-CSF could differentiate the NAFL group from the controls; G-CSF, IL-1ra, TNF-α, RANTES, and IL-9 could differentiate the NASH group from the controls; and G-CSF, IL-9, IL-13, eotaxin, and TNF- α could differentiate the NASH group from the NAFL group. Our protein-protein network revealed that these markers are involved in cytokine-cytokine receptor interaction, Th1 and Th2 cell differentiation, TNF, chemokine, JAK/STAT, P13K/Akt, TLR, NOD-like receptor, NF-kB, and adipocytokine signaling pathways which might be responsible for disease pathogenesis.Our study findings revealed a set of distinct cytokine and chemokine markers and they might be considered as biomarkers in distinguishing NASH from NAFL. Future multicentre studies with larger sample size are recommended to determine the potential utility of these panels of markers.

From gut to liver: unveiling the differences of intestinal microbiota in NAFL and NASH patients.

Non-alcoholic fatty liver disease (NAFLD) is increasingly recognized for its global prevalence and potential progression to more severe liver diseases such as non-alcoholic steatohepatitis (NASH). The gut microbiota plays a pivotal role in the pathogenesis of NAFLD, yet the detailed characteristics and ecological alterations of gut microbial communities during the progression from non-alcoholic fatty liver (NAFL) to NASH remain poorly understood. Methods: In this study, we conducted a comparative analysis of gut microbiota composition in individuals with NAFL and NASH to elucidate differences and characteristics. We utilized 16S rRNA sequencing to compare the intestinal gut microbiota among a healthy control group (65 cases), NAFL group (64 cases), and NASH group (53 cases). Random forest machine learning and database validation methods were employed to analyze the data. Results: Our findings indicate a significant decrease in the diversity of intestinal flora during the progression of NAFLD (p < 0.05). At the phylum level, high abundances of Bacteroidetes and Fusobacteria were observed in both NAFL and NASH patients, whereas Firmicutes were less abundant. At the genus level, a significant decrease in Prevotella expression was seen in the NAFL group (AUC 0.738), whereas an increase in the combination of Megamonas and Fusobacterium was noted in the NASH group (AUC 0.769). Furthermore, KEGG pathway analysis highlighted significant disturbances in various types of glucose metabolism pathways in the NASH group compared to the NAFL group, as well as notably compromised flavonoid and flavonol biosynthesis functions. The study uncovers distinct microbiota characteristics and microecological changes within the gut during the transition from NAFL to NASH, providing insights that could facilitate the discovery of novel biomarkers and therapeutic targets for NAFLD.

Expression of immune related genes and possible regulatory mechanisms in different stages of non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD), which includes simple steatosis (SS) and non-alcoholic steatohepatitis (NASH), is a significant contributor to liver disease on a global scale. The change of immunity-related genes (IRGs) expression level leads to different immune infiltrations. However, the expression of IRGs and possible regulatory mechanisms involved in NAFLD remain unclear. The objective of our research is to investigate crucial genes linked to the development of NAFLD and the transition from SS to NASH. Dataset GSE89632, which includes healthy controls, SS patients, and NASH patients, was obtained using the GEO database. To examine the correlation between sets of genes and clinical characteristics, we employed weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Hub genes were extracted using a network of protein-protein interactions (PPI) and three different machine learning algorithms. To validate the findings, another dataset that is publicly accessible and mice that were subjected to a high-fat diet (HFD) or MCD diet were utilized. Furthermore, the ESTIMATE algorithm and ssGSEA were employed to investigate the immune landscape in the normal versus SS group and SS versus NASH group, additionally, the relationship between immune infiltration and the expression of hub genes was also examined. A total of 28 immune related key genes were selected. Most of these genes expressed reverse patterns in the initial and progressive stages of NAFLD. GO and KEGG analyses showed that they were focused on the cytokine related pathways and immune cell activation and chemotaxis. After screening by various algorithms, we obtained two hub genes, including JUN and CCL20. Validation of these findings was confirmed by analyzing gene expression patterns in both the validation dataset and the mouse model. Ultimately, two hub genes were discovered to have a significant correlation with the infiltration of immune cells. We proposed that there were dynamic changes in the expression levels of IRGs in different stages of NAFLD disease, which led to different immune landscapes in SS and NASH. The findings of our research could serve as a guide for the accurate management of various phases of NAFLD.

The relationship and diagnostic efficacy of N-terminal propeptide type III collagen in pathological changes associated with non-alcoholic steatohepatitis.

This study delves into the role of N-terminal propeptide type III collagen (PIIINP) in the diagnosis and management of liver pathological changes associated with non-alcoholic steatohepatitis (NASH). We collected baseline information, pathological data, and serum PIIINP levels of 168 patients diagnosed with non-alcoholic fatty liver disease (NAFLD) via ultrasound imaging in our hospital. Based on the non-alcoholic fatty liver disease activity score (NAS), patients with different NAFLD patterns were divided into a Definite NASH group and a Not/borderline group. Differences in PIIINP levels and pathological features between the two groups were compared and analyzed. The diagnostic value of PIIINP for NASH was evaluated using the receiver operating characteristic (ROC) curve. Patients with NASH exhibited significantly higher values of homeostatic model assessment for insulin resistance (HOMA-IR), fibrosis biomarker fibrosis-4 (FIB-4), aminotransferase-to-platelet ratio index (APRI), and serum PIIINP levels than those classified as Not/borderline. A marked increase in the serum concentrations of PIIINP was observed with the severity of fatty degeneration, lobular inflammation, and hepatocellular ballooning. The AUC of PIIINP for diagnosing definite NASH was 0.766 (95% CI: 0.694, 0.839), APRI was 0.634 (95% CI: 0.549, 0.718), and FIB-4 was 0.621 (95% CI: 0.534, 0.708). The AUC of PIIINP for diagnosing definite NASH was significantly higher than that of APRI and FIB-4 (all p<0.05). Utilizing the predetermined threshold values for diagnostic parameters, the PIIINP measure demonstrated a sensitivity of 71.6% and a specificity of 73.6% in diagnosing definitive NASH when its value exceeded 7.72 ng/dL. This yielded a Youden index of 0.45. Similarly, when the APRI measure exceeded 0.21, it exhibited a sensitivity of 60.5% and a specificity of 63.2%, resulting in a Youden index of 0.24. Moreover, when the FIB-4 index surpassed 0.26, it showed a sensitivity of 46.9% and a specificity of 79.3%, culminating in a Youden index of 0.26. NASH patients in this study exhibited significantly elevated PIIINP serum levels, which were closely associated with hepatocyte pathological changes. PIIINP demonstrated superior competence in diagnosing NASH than APRI and FIB-4 and thus offers a viable alternative for the clinical diagnosis of NASH.

Sequential ultrasound molecular imaging for noninvasive identification and assessment of non-alcoholic steatohepatitis in mouse models

Background and objectiveNoninvasive non-alcoholic steatohepatitis (NASH) assessment is a clinical challenge to the management of non-alcoholic fatty liver disease. We aim to develop diagnostic models based on sequential ultrasound molecular imaging (USMI) for the noninvasive identification of NASH in mouse models. MethodsAnimal experiments were approved by the Animal Ethics Committee of South China Agricultural University. Forty-nine C57BL/6 mice were divided into normal control, non-alcoholic fatty liver, NASH, and hepatitis groups. Sequential USMI was implemented using CD36-targeted microbubbles (MBs-CD36) and intercellular adhesion molecule-1 (ICAM-1)-targeted microbubbles (MBs-ICAM-1) to visualize hepatic steatosis and inflammation. The targeting signal of USMI was quantified as the normalized intensity difference (NID) with the destruction-replenishment method. Correlation analysis was conducted between the NID-MBs-CD36 and pathological steatosis score and between the NID-MBs-ICAM-1 and pathological inflammation score. Finally, diagnostic models combining NID-MBs-CD36 with NID-MBs-ICAM-1 were established for NASH diagnosis. ResultsMBs-CD36 and MBs-ICAM-1 were successfully prepared and used for sequential USMI in all mice. NID-MBs-CD36 values increased with the progression of steatosis, while NID-MBs-ICAM-1 values increased in parallel with the progression of inflammation. A strong positive correlation was identified between NID-MBs-CD36 and pathological steatosis grade (rs = 0.9078, P < 0.0001) and between NID-MBs-ICAM-1 and pathological inflammation grade (rs = 0.9071, P < 0.0001). Among various sequential USMI-based diagnostic models, the serial testing model showed high diagnostic performance in detecting NASH, with 95% sensitivity, 97% specificity, 95% positive predictive values, 97% negative predictive values, and 96% accuracy. ConclusionsSequential USMI using MBs-CD36 and MBs-ICAM-1 allows noninvasive grading of hepatic steatosis and inflammation. Sequential USMI-based diagnostic models hold great potential in the noninvasive identification of NASH.

Involvement of essential trace elements in the pathogenesis of hepatitis C virus‑related chronic liver disease and nonalcoholic steatohepatitis.

Essential trace elements are involved in the pathogenesis of chronic liver disease (CLD), which causes hepatic inflammation, steatosis and fibrosis. The present study investigated the roles of essential trace elements in the pathogenesis of hepatitis C virus-related CLD (CLD-C) and nonalcoholic steatohepatitis (NASH), and compared the levels of these trace elements between the two groups. Serum zinc (Zn), selenium (Se), copper (Cu) and ferritin levels were measured in patients with CLD-C (n=66) and NASH (n=26). Subsequently, the correlations between the levels of these essential trace elements in patient sera and the biochemical or pathological parameters of patients with CLD-C and NASH were determined. The results demonstrated that the serum ferritin levels were significantly correlated with serum alanine aminotransferase levels in both the CLD-C and NASH groups. In both groups, the serum Zn and Se levels were significantly associated with serum albumin levels, and inversely associated with the stages of hepatic fibrosis. Furthermore, serum ferritin levels were positively associated, and serum Zn levels were inversely correlated with the grades of hepatic steatosis in patients with CLD-C, whereas serum Se levels were closely associated with the grades of hepatic steatosis only in patients with NASH. In both groups, serum ferritin levels were positively correlated, and serum Zn levels were inversely correlated with homeostasis model for the assessment of insulin resistance (HOMA-IR) values, and serum Se was negatively correlated with the HOMA-IR values in patients with CLD-C only. In conclusion, these results indicated that the involvement of essential trace elements in insulin resistance and hepatic steatosis may differ slightly between patients with CLD-C and those with NASH.

Abstract 12321: Discordant Association of Nonalcoholic Fatty Liver Disease With Lipoprotein(a) and Markers of Atherogenic Dyslipidemia

Background: Nonalcoholic fatty liver disease (NAFLD) is associated with atherogenic dyslipidemia and an increased risk of cardiovascular events. Previous studies have suggested a paradoxical inverse relationship between NAFLD severity and Lp(a) level, an independent cardiovascular risk factor. However, contemporary data in patients with biopsy-proven NAFLD in the U.S. are lacking. Hypothesis: NAFLD severity on liver biopsy has a discordant association with Lp(a) and other markers of atherogenic dyslipidemia. Methods: Lp(a), traditional lipid profile, apolipoproteins, and nuclear magnetic resonance-based lipoprotein particle concentration were measured in 151 patients with NAFLD. Levels were compared between those with nonalcoholic fatty liver (NAFL) on histology and non-alcoholic steatohepatitis (NASH), the clinically aggressive NAFLD variant. Results: Median age was 55 [48, 62] years, 67% of patients were women, 83% were White, 43% had NAFL, and 57% had NASH. Demographic characteristics were similar among those with NAFL and NASH. Triglyceride level was higher and High-Density Lipoprotein-cholesterol (HDL-C) was lower among those with NASH as compared with NAFL. Circulating concentration of two key markers of atherogenic dyslipidemia, Apolipoprotein-B (apoB) and Low-Density Lipoprotein particle concentration (LDL-P) was 9% and 17% higher in the NASH group as compared with NAFL, respectively. Contrastingly, Lp(a) concentration was 50% lower in NASH relative to NAFL group (Figure). Hepatocyte ballooning, lobular inflammation, and fibrosis on histology were inversely associated with Lp(a) concentration, while steatosis severity was not. Conclusions: NAFLD severity has a discordant association with Lp(a) and markers of atherogenic dyslipidemia. The mechanistic basis of this relationship may have implications for prognosticating cardiovascular disease risk and determining the safety of targeted Lp(a) lowering in patients with NAFLD.

Metabonomics Application on Screening Serum Biomarkers of Golden Hamsters with Nonalcoholic Steatohepatitis Induced by High-Fat Diet.

Nonalcoholic steatohepatitis (NASH) is a common liver injury which will develop into advanced fibrosis and cirrhosis. This study was designed to identify the different serum metabolites of NASH hamsters and predict the diagnosis biomarkers for NASH. Golden hamsters were randomly divided into a control group that received a normal diet and a NASH group that received a high-fat diet (HFD). After 12 weeks of feeding, the body and liver weight of the hamsters were monitored. Serum biochemical parameters and liver histopathological changes were analyzed. Moreover, an untargeted metabolomics analysis based on a GCTOF/ MS system was performed to identify the serum differential metabolites between the NASH and control groups. The liver weight was increased in the NASH group, accompanied by significantly higher levels of serum TC, TG, ALT, AST, LDL-C, and lower HDL-C. HE, Masson, and oil red O staining showed the hepatocyte structure destroyed, lipid droplets accumulated, and fibers proliferated in the NASH group. Furthermore, 63 differential metabolites were identified by metabolomic analysis. Lipids and fatty acids were significantly up-regulated in the NASH group. The top 9 differential metabolites included cholesterol, methyl phosphate, taurine, alpha-tocopherol, aspartic acid, etc. Metabolites were mainly involved in amino acid metabolism (glycine, cysteine, taurine), spermine, fatty acid biosynthesis, urea cycle, bile acid metabolism pathways, etc. Conclusion: Metabonomics analysis identified 63 differential metabolites in the serum of NASH hamsters; among them, lipids and fatty acids had a key role and may be used as biomarkers for the early diagnosis of NASH.