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Search Results (1,293)

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12 pages, 2277 KiB  
Article
Lymph Node Adiposity and Metabolic Dysfunction-Associated Steatotic Liver Disease
by Jessica M. Rubino, Natalie Yanzi Ring, Krishna Patel, Xiaoqing Xia, Todd A. MacKenzie and Roberta M. diFlorio-Alexander
Biomedicines 2025, 13(1), 80; https://doi.org/10.3390/biomedicines13010080 (registering DOI) - 1 Jan 2025
Viewed by 127
Abstract
Objective: Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as the most common chronic liver disease, is soon to be the leading indication for liver transplantation; however, the diagnosis may remain occult for decades. There is a need for biomarkers that identify [...] Read more.
Objective: Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as the most common chronic liver disease, is soon to be the leading indication for liver transplantation; however, the diagnosis may remain occult for decades. There is a need for biomarkers that identify patients at risk for MASLD and patients at risk for disease progression to optimize patient management and outcomes. Lymph node adiposity (LNA) is a novel marker of adiposity identified within axillary lymph nodes on screening mammography. Recent studies have demonstrated a correlation between LNA and cardiometabolic disease and cardiovascular disease risk. This study aimed to investigate the association between MASLD and LNA to evaluate the potential of mammographic LNA to serve as an imaging biomarker of MASLD. Methods: We identified women with pathology-proven MASLD who had a liver biopsy and a screening mammogram within 12 months of the liver biopsy. This resulted in a sample size of 161 women for final analysis that met the inclusion criteria. We evaluated lymph node adiposity through multiple measurements of the largest axillary lymph node visualized on mammography and correlated LNA with MASLD histology. Statistical analysis using univariable and multivariable logistic regression and odds ratios was performed using R version 4.1.0 (2021), the R Foundation for Statistical Computing Platform. Results: We found a significant association between MASLD and mammographic LNA, defined as lymph node (LN) length > 16 mm (p = 0.0004) that remained significant after adjusting for clinical factors, including body mass index (BMI). We additionally found a significant association between LNA and metabolic dysfunction-associated steatohepatitis (MASH), identified via liver biopsy (p = 0.0048). Conclusions: Mammographic lymph node adiposity may serve as a helpful imaging biomarker of MASLD in women who have an elevated risk for the development of MASH. Full article
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<p>Variable lymph node size and morphology on mammographic medio-lateral oblique (MLO) views of the axilla. (<b>A</b>) Normal axillary lymph nodes measuring 8–11 mm (dotted line) with small physiologic “fatty notch” of lucent hilar fat (circle). (<b>B</b>) Fat-enlarged axillary lymph nodes measuring 25–29 mm (dotted line) due to increased lucent hilar fat (circle).</p>
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<p>Data collection.</p>
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<p>Lymph node (LN) measurements obtained: a—LN length, b—Hilar length, c—LN width, d—hilar width.</p>
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<p>Performance of lymph node adiposity for predicting steatosis. (<b>A</b>) LN measurements alone yielded AUC of 61.9% to 68.7%. (<b>B</b>) LN measurements combined with clinical variables yielded AUC of 80.4% to 83.5%.</p>
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28 pages, 695 KiB  
Review
NAFLD and NAFLD Related HCC: Emerging Treatments and Clinical Trials
by Tripti Khare, Karina Liu, Lindiwe Oslee Chilambe and Sharad Khare
Int. J. Mol. Sci. 2025, 26(1), 306; https://doi.org/10.3390/ijms26010306 (registering DOI) - 1 Jan 2025
Viewed by 199
Abstract
Nonalcoholic fatty liver disease (NAFLD), recently renamed metabolic-associated fatty liver disease (MAFLD), is the most prevalent liver disease worldwide. It is associated with an increased risk of developing hepatocellular carcinoma (HCC) in the background of cirrhosis or without cirrhosis. The prevalence of NAFLD-related [...] Read more.
Nonalcoholic fatty liver disease (NAFLD), recently renamed metabolic-associated fatty liver disease (MAFLD), is the most prevalent liver disease worldwide. It is associated with an increased risk of developing hepatocellular carcinoma (HCC) in the background of cirrhosis or without cirrhosis. The prevalence of NAFLD-related HCC is increasing all over the globe, and HCC surveillance in NAFLD cases is not that common. In the present review, we attempt to summarize promising treatments and clinical trials focused on NAFLD, nonalcoholic steatohepatitis (NASH), and HCC in the past five to seven years. We categorized the trials based on the type of intervention. Most of the trials are still running, with only a few completed and with conclusive results. In clinical trial NCT03942822, 25 mg/day of milled chia seeds improved NAFLD condition. Completed trial NCT03524365 concluded that Rouxen-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) results in histological resolution of NASH without worsening of fibrosis, while NCT04677101 validated sensitivity/accuracy of blood biomarkers in predicting NASH and fibrosis stage. Moreover, trials with empagliflozin (NCT05694923), curcuvail (NCT06256926), and obeticholic acid (NCT03439254) were completed but did not provide conclusive results. However, trial NCT03900429 reported effective improvement in fibrosis by at least one stage, without worsening of NAFLD activity score (NAS), as well as improvement in lipid profile of the NASH patients by 80 or 100 mg MGL-3196 (resmetirom). Funded by Madrigal Pharmaceuticals, Rezdiffra (resmetirom), used in the clinical trial NCT03900429, is the first FDA-approved drug for the treatment of NAFLD/NASH. Full article
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<p>Disease progression of a healthy liver to HCC. Stages of progression of a healthy liver to HCC: The liver first experiences steatosis where fat cells become abundant, followed by fibrosis, where fibroblasts and collagen form large amounts of scar tissue; and ultimately, cirrhosis, where necrosis appears in addition to the fat cells and scar tissue, leading to cirrhotic HCC, where tumor cells are formed. Non-cirrhotic HCC can also occur after steatosis with the formation of tumor cells.</p>
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12 pages, 529 KiB  
Article
Targeted Plasma Bile Acid Metabolomic Analysis in Metabolic Dysfunction-Associated Steatohepatitis and Alcoholic Hepatitis
by Yuta Hirata, Yasunaru Sakuma, Hideo Ogiso, Ryozo Nagai and Kenichi Aizawa
Biomedicines 2025, 13(1), 78; https://doi.org/10.3390/biomedicines13010078 (registering DOI) - 31 Dec 2024
Viewed by 140
Abstract
Background: Even though many metabolic liver diseases can now be diagnosed using blood tests and diagnostic imaging, early diagnosis remains difficult. Understanding mechanisms contributing to the progression from Metabolic Dysfunction-Associated Steatohepatitis (MASH) and Alcoholic Hepatitis (AH) to cirrhosis is critical to reduce the [...] Read more.
Background: Even though many metabolic liver diseases can now be diagnosed using blood tests and diagnostic imaging, early diagnosis remains difficult. Understanding mechanisms contributing to the progression from Metabolic Dysfunction-Associated Steatohepatitis (MASH) and Alcoholic Hepatitis (AH) to cirrhosis is critical to reduce the burden of end-stage liver disease. Monitoring individual bile acids has been proposed as a way to distinguish various liver disorders. Methods: This study explored bile acid profiles in patients with MASH and AH. Plasma samples from patients with MASH, AH, and a control group were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify bile acid concentrations. Targeted metabolomic analysis was performed to compare bile acid levels between the hepatitis and control groups. Results: Concentrations of ursodeoxycholic acid (UDCA), chenodeoxycholic acid (CDCA), taurocholic acid (TCA), tauroursodeoxycholic acid (TUDCA), taurochenodeoxycholic acid (TCDCA), glycoursodeoxycholic acid (GUDCA), glycochenodeoxycholic acid (GCDCA), and glycocholic acid (GCA) were significantly elevated in the hepatitis group. Correlation analysis revealed strong positive relationships between the total and direct bilirubin levels and TUDCA and GCDCA. Aspartate aminotransferase (AST) showed strong positive correlations with TCDCA and GCDCA. Child–Pugh score, Fibrosis-4 index, and non-alcoholic fatty liver disease fibrosis score were positively correlated with GCA, whereas the aspartate aminotransferase-to-platelet ratio correlated with TCA, TCDCA, and GCA. The model for end-stage liver disease (MELD) score showed a strong positive correlation with GCDCA. Implications: GCDCA may serve as a predictive biomarker for liver damage, potentially enabling early diagnosis and targeted intervention in patients with MASH and AH. Full article
(This article belongs to the Special Issue Novel Insights into Liver Metabolism)
22 pages, 541 KiB  
Review
Retinopathy in Metabolic Dysfunction-Associated Steatotic Liver Disease
by Myrsini Orfanidou and Stergios A. Polyzos
Medicina 2025, 61(1), 38; https://doi.org/10.3390/medicina61010038 - 30 Dec 2024
Viewed by 271
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a multisystemic disease, i.e., influencing various organ systems beyond the liver and, thus, contributing to comorbidities. Characterized by excessive fat accumulation in the hepatocytes, MASLD is frequently linked to metabolic syndrome components, such as obesity, insulin [...] Read more.
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a multisystemic disease, i.e., influencing various organ systems beyond the liver and, thus, contributing to comorbidities. Characterized by excessive fat accumulation in the hepatocytes, MASLD is frequently linked to metabolic syndrome components, such as obesity, insulin resistance, dyslipidemia, and hypertension. Therefore, exploring the intricate connection between MASLD and other organ systems, including the eyes, seems to be essential. In this context, retinopathy has been investigated for its potential association with MASLD, since both conditions share common pathogenetic pathways. Chronic low-grade inflammation, oxidative stress, insulin resistance, and endothelial dysfunction are only some of those mechanisms contributing to disease progression and, possibly, determining the bidirectional interplay between the liver and retinal pathology. This narrative review aims to summarize data concerning the multisystemicity of MASLD, primarily focusing on its potential association with the eyes and, particularly, retinopathy. Identifying this possible association may emphasize the need for early screening and integrated management approaches that address the liver and eyes as interconnected components within the framework of a systemic disease. Further research is necessary to delineate the precise mechanisms and develop targeted interventions to mitigate the bidirectional impact between the liver and eyes, aiming to reduce the overall burden of disease and improve patient outcomes. Full article
(This article belongs to the Special Issue Retinal and Choroidal Vascular Disease)
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<p>The potential association between MASLD and retinopathy. Insulin resistance and hyperglycemia, which are common in MASLD, promote oxidative stress and glycation end-product formation, thus breaking down the blood–retinal barrier and increasing the risk of retinopathy. MASLD also contributes to endothelial dysfunction, by reducing nitric oxide availability and increasing retinal vascular stiffness, thus leading to features of retinopathy, like capillary leakage and neovascularization. Additionally, chronic inflammation and lipid dysmetabolism exacerbate microvascular damage through pro-inflammatory cytokines, dyslipidemia, and lipid peroxidation, further linking MASLD to retinal disease. Abbreviations: CRP, C-reactive protein; DR, diabetic retinopathy; HDL, high-density lipoprotein; IL-6, interleukin-6; LDL, low-density lipoprotein; MASLD, metabolic dysfunction-associated steatotic liver disease; TG, triglycerides; TNF-a, tumor necrosis factor-a.</p>
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15 pages, 5489 KiB  
Article
Lethal Arrhythmogenic Role of Left Ventricular Myocardial Interstitial Fibrosis in Apolipoprotein E/Low-Density Lipoprotein Receptor Double-Knockout Mice with Metabolic Dysfunction-Associated Steatohepatitis
by Jinyao Liu, Yumiko Oba, Yosuke Kondo, Ryo Nakaki and Seiko Yamano
Int. J. Mol. Sci. 2025, 26(1), 144; https://doi.org/10.3390/ijms26010144 - 27 Dec 2024
Viewed by 247
Abstract
The combination of alcohol and a low-carbohydrate, high-protein, high-fat atherogenic diet (AD) increases the risk of lethal arrhythmias in apolipoprotein E/low-density lipoprotein receptor double-knockout (AL) mice with metabolic dysfunction-associated steatotic liver disease (MASLD). This study investigates whether left ventricular (LV) myocardial interstitial fibrosis [...] Read more.
The combination of alcohol and a low-carbohydrate, high-protein, high-fat atherogenic diet (AD) increases the risk of lethal arrhythmias in apolipoprotein E/low-density lipoprotein receptor double-knockout (AL) mice with metabolic dysfunction-associated steatotic liver disease (MASLD). This study investigates whether left ventricular (LV) myocardial interstitial fibrosis (MIF), formed during the progression of metabolic dysfunction-associated steatohepatitis (MASH), contributes to this increased risk. Male AL mice were fed an AD with or without ethanol for 16 weeks, while age-matched AL and wild-type mice served as controls. Liver and heart tissues were analyzed, and susceptibility to lethal arrhythmias was assessed through histopathology, fluorescence immunohistochemistry, RNA-Seq, RT-PCR, and lethal arrhythmia-evoked test. Ethanol combined with an AD significantly induced LV MIF in MASH-affected AL mice, as shown by increased fibrosis-related gene expression, Sirius-Red staining, and elevated collagen 1a1 and 3a1 mRNA levels, alongside a higher incidence of lethal arrhythmias. Cardiac myofibroblasts exhibited sympathetic activation and produced elevated levels of fibrosis-promoting factors. This study highlights the role of cardiac myofibroblasts in LV MIF, contributing to an increased incidence of lethal arrhythmias in MASH-affected AL mice fed ethanol and AD, even after the alcohol was fully metabolized on the day of consumption. Full article
(This article belongs to the Special Issue Molecular Mechanism and Pathogenesis of Cardiac Disease)
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<p>The key characteristics of the animals. Representative results for body weight (BW) (<b>A</b>), liver weight (<b>B</b>), and LV weight (<b>C</b>). The data are presented as mean values with standard deviations (SDs). Statistical significance (* <span class="html-italic">p</span> &lt; 0.05 vs. WT+SCD, Et (−); <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+SCD, EtOH (−); <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+AD, EtOH (−)) was determined using ANOVA followed by Bonferroni–Dunn post hoc test.</p>
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<p>The effects of a co-diet of ethanol and AD on hepatic fat accumulation, inflammation, and fibrosis. Examples of Oil-Red-O staining, CD68 immunostaining, and Sirius-Red staining of liver sections (<b>A</b>). The scale bars are 200 μm for Oil-Red-O and Sirius-Red staining and 30 μm for CD68 immunostaining. Representative results of hepatic Oil-Red-O content (<b>B</b>), CD68-positive area (<b>C</b>), <span class="html-italic">Cd68</span> mRNA expression (<b>D</b>), Sirius-Red content (<b>E</b>), and <span class="html-italic">Col 1a1</span> mRNA expression (<b>F</b>). The data are presented as mean values with standard deviations (SDs). Statistical significance (* <span class="html-italic">p</span> &lt; 0.05 vs. WT+SCD, Et (−); <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+SCD, EtOH (−); <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+AD, EtOH (−)) was determined using ANOVA followed by Bonferroni–Dunn post hoc test.</p>
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<p>Sudden cardiac death resulting from the lethal arrhythmia-evoked test. Shown are representative electrocardiograms (ECGs) depicting the occurrence of complete atrioventricular block (CAVB), ventricular tachycardia (VT), and asystole induced by acute restraint stress (ARS) in AL mice fed with a co-diet of ethanol and AD. Each panel displays a 2 min ECG and 15 s zoomed-in lethal arrhythmia-evoked test, with an arrow indicating the onset of ARS.</p>
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<p>Ethanol and AD changed gene expression related to fibrosis in LV. Cellular components of the genes significantly changed in the gene ontology (GO) enrichment analysis: to assess the results of the RNA-Seq analysis in terms of cellular components, the genes that changed in mice LV myocardium were matched to the genes related to each GO term, and the 10 terms with the lowest <span class="html-italic">p</span>-value were listed (<b>A</b>). The heatmap shows the gene expression changes related to fibrosis in the LV, ranked by the lowest <span class="html-italic">p</span>-values as determined by RNA-Seq analysis (<b>B</b>).</p>
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<p>LV MIF resulting from the co-diet of ethanol and AD. Examples of LV sections stained with Sirius-Red (<b>A</b>), with a scale bar of 100 μm. Representative data of LV Sirius-Red content (<b>B</b>), LV <span class="html-italic">Col 1a1</span> mRNA expression (<b>C</b>), and LV <span class="html-italic">Col 3a1</span> mRNA expression (<b>D</b>). The data are presented as mean values with standard deviations (SDs). Statistical significance (* <span class="html-italic">p</span> &lt; 0.05 vs. WT+SCD, Et (−); <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+SCD, EtOH (−); <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+AD, EtOH (−)) was determined using ANOVA followed by Bonferroni–Dunn post hoc test.</p>
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<p>The combination diet of ethanol and AD increased the co-localization of TH (sympathetic activation marker) and α-SMA (activated cardiac myofibroblast marker) and the co-localization of α-SMA and TGF-β1 (associated with fibrotic diseases) in the immunostained LV sections. Examples merging nuclear (DAPI, blue), TH, and α-SMA appear as pink and merging nuclear (DAPI, blue), α-SMA, and TGF-β1 appear as yellow (<b>A</b>) alongside measurements of the LV-TH-positive area (<b>B</b>), α-SMA-positive area (<b>C</b>), and TGF-β1-positive area (<b>D</b>) within the same visual field of immunostained LV sections. The scale bar denotes 30 μm. Results are presented as mean ± SD. Statistical significance was determined as * <span class="html-italic">p</span> &lt; 0.05 compared to WT+SCD, Et (−), <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 compared to AL+SCD, EtOH (−), and <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared to AL+AD, EtOH (−) using ANOVA followed by Bonferroni–Dunn post hoc test.</p>
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<p>The impact of a co-diet of ethanol and AD on the mRNA expressions in the LV as determined by RT-PCR. The mRNA levels of <span class="html-italic">Npy</span> (<b>A</b>), <span class="html-italic">Acta2</span> (<b>B</b>), and <span class="html-italic">Tgfb1</span> (<b>C</b>) in mice subjected to the lethal arrhythmia-evoked test. The data are presented as mean values with standard deviations (SDs). Statistical significance (* <span class="html-italic">p</span> &lt; 0.05 vs. WT+SCD, Et (−); <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+SCD, EtOH (−); <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. AL+AD, EtOH (−)) was determined using ANOVA followed by Bonferroni–Dunn post hoc test.</p>
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19 pages, 2335 KiB  
Article
Alpinetin Exhibits Antioxidant and Anti-Inflammatory Effects in C57BL/6 Mice with Alcoholic Liver Disease Induced by the Lieber–DeCarli Ethanol Liquid Diet
by Tatjana Radosavljevic, Milica Brankovic, Jasmina Djuretić, Jelica Grujic-Milanovic, Marijana Kovacic, Jovan Jevtic, Sanja Stankovic, Janko Samardzic, Danijela Vucevic and Vladimir Jakovljevic
Int. J. Mol. Sci. 2025, 26(1), 86; https://doi.org/10.3390/ijms26010086 - 26 Dec 2024
Viewed by 204
Abstract
Alcohol-associated liver disease (ALD) is a common non-communicable chronic liver disease characterized by a spectrum of conditions ranging from steatosis and alcohol-associated steatohepatitis (AH) to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The pathogenesis of ALD involves a complex interplay of various molecular, biochemical, [...] Read more.
Alcohol-associated liver disease (ALD) is a common non-communicable chronic liver disease characterized by a spectrum of conditions ranging from steatosis and alcohol-associated steatohepatitis (AH) to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The pathogenesis of ALD involves a complex interplay of various molecular, biochemical, genetic, epigenetic, and environmental factors. While the mechanisms are well studied, therapeutic options remain limited. Alpinetin, a natural flavonoid with antioxidant and anti-inflammatory properties, has shown potential hepatoprotective effects, though its efficacy in ALD remains unexplored. This study investigated the hepatoprotective effects of alpinetin using a Lieber–DeCarli ethanol liquid diet model of ALD in C57BL/6 mice. Mice were divided into three groups: the control group, the ethanol group, and the ethanol group treated with alpinetin. Serum activity of ALT, AST, γ-GT, and ALP was measured to assess liver function, along with antioxidative and oxidative/nitrosative stress markers in liver tissue. Pro-inflammatory cytokines and endoplasmic reticulum (ER) stress parameters in liver tissue were also evaluated. Histological assessment of disease activity was performed using the SALVE grading and staging system. Treatment with alpinetin significantly reduced serum levels of ALT, AST, γ-GT, and oxidative/nitrosative stress markers while increasing antioxidative markers. The levels of pro-inflammatory cytokines and ER stress parameters were significantly decreased. Histological analysis demonstrated reduced steatosis, hepatocyte ballooning, and inflammation. These findings suggest that alpinetin holds promise as a potential therapeutic agent for managing ALD. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Atherosclerosis)
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<p>The effects of alpinetin on oxidative/nitrosative stress parameters: (<b>a</b>) MDA, (<b>b</b>) AOPP, (<b>c</b>) O<sub>2</sub><sup>−</sup>, (<b>d</b>) NO<sub>2</sub><sup>−</sup>, (<b>e</b>) PAB. The values are represented by mean ± SD; *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05. Abbreviations: MDA—malondialdehyde; AOPP—advanced oxidation protein product; (<b>c</b>) O<sub>2</sub><sup>−</sup> superoxide anion radical; (<b>d</b>) NO<sub>2</sub>—nitrite; (<b>e</b>) PAB—pro-oxidant–antioxidant balance; C—control group; E—ethanol group; E+Alp—ethanol + alpinetin group.</p>
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<p>The effects of alpinetin on antioxidative parameters: (<b>a</b>) CAT, (<b>b</b>) SOD, (<b>c</b>) total glutathione, (<b>d</b>) GSH, (<b>e</b>) GSSG, (<b>f</b>) GPx, (<b>g</b>) GSH/GSSG ratio. The values are represented by mean ± SD; *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, respectively. Abbreviations: CAT—catalase; SOD—superoxide dismutase; GSH—reduced glutathione; GSSG—oxidized glutathione; GPx—glutathione peroxidase; C—control group; E—ethanol group; E+Alp—ethanol + alpinetin group.</p>
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<p>The effects of alpinetin on (<b>a</b>) IFN-γ, (<b>b</b>) IL-4, and (<b>c</b>) MPO activity. The values are represented by mean ± SD; *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01. Abbreviations: IFN-γ—interferon-gamma; IL-4—interleukin 4; MPO—myeloperoxidase; C—control group; E—ethanol group; E+Alp—ethanol + alpinetin group.</p>
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<p>The effects of alpinetin on the expression of the ER stress proteins (<b>a</b>) GADD153, (<b>b</b>) GRP 78, (<b>c</b>) ATF-4, (<b>d</b>) Western blot analyses of GADD153, GRP 78, ATF-4, and β-actin in liver tissue (n = 6) (<a href="#app1-ijms-26-00086" class="html-app">Figure S2</a>). Abbreviations: GADD—growth arrest and DNA damage-inducible gene 153; GRP 78—glucose-regulated protein 78; ATF 4—activating transcription factor 4; C—control group; E—ethanol group; E+Alp—ethanol + alpinetin group. The values are represented by mean ± SD; *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>(<b>A</b>) Normal liver histology (<b>A</b>(a)); liver histology of mice in the E group (<b>A</b>(b,c,e,g)); liver histology of mice in the E+Alp group (<b>A</b>(d,f,h)). (<b>A</b>(b)) hepatocellular injury (ballooning). Numerous hepatocytes are ballooned, showing cytoplasmic clearing (arrows). The image also shows a central vein (asterisk). H&amp;E stain, magnification ×200; (A(c)) Numerous hepatocytes are ballooned, showing cytoplasmic clearing, with some exhibiting Mallory bodies (arrows). H&amp;E stain, magnification ×400; (<b>A</b>(g)) Steatosis. Numerous hepatocytes exhibit fatty changes, with fat vacuoles observed in the cytoplasm (arrows). The image also shows a central vein (asterisk). H&amp;E stain, magnification ×400; (<b>A</b>(e)) lobular neutrophils. Numerous neutrophils are present between hepatocytes (arrow). H&amp;E stain, magnification ×400. (<b>A</b>(d)) The depicted hepatocytes do not show ballooning. H&amp;E stain, magnification ×200; (<b>A</b>(h)) A few hepatocytes exhibit fatty changes with sparse microdroplets (arrows). H&amp;E stain, magnification ×400; (<b>A</b>(f)) Scattered neutrophils are present between hepatocytes. H&amp;E stain, magnification ×400. (<b>B</b>) Histology score of hepatocellular injury, lobular neutrophils (activity grade), and steatosis in the E and E+Alp groups (*** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05 vs. E group).</p>
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12 pages, 6235 KiB  
Article
Hepatic Steatosis Analysis in Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Artificial Intelligence
by Xiao-Xiao Wang, Yu-Yun Song, Rui Jin, Zi-Long Wang, Xiao-He Li, Qiang Yang, Xiao Teng, Fang-Fang Liu, Nan Wu, Yan-Di Xie, Hui-Ying Rao and Feng Liu
Diagnostics 2024, 14(24), 2889; https://doi.org/10.3390/diagnostics14242889 - 23 Dec 2024
Viewed by 343
Abstract
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of fat in the liver, excluding excessive alcohol consumption and other known causes of liver injury. Animal models are often used to explore different pathogenic mechanisms and therapeutic targets of MASLD. [...] Read more.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of fat in the liver, excluding excessive alcohol consumption and other known causes of liver injury. Animal models are often used to explore different pathogenic mechanisms and therapeutic targets of MASLD. The aim of this study is to apply an artificial intelligence (AI) system based on second-harmonic generation (SHG)/two-photon-excited fluorescence (TPEF) technology to automatically assess the dynamic patterns of hepatic steatosis in MASLD mouse models. Methods: We evaluated the characteristics of hepatic steatosis in mouse models of MASLD using AI analysis based on SHG/TPEF images. Six different models of MASLD were induced in C57BL/6 mice by feeding with a western or high-fat diet, with or without fructose in their drinking water, and/or by weekly injections of carbon tetrachloride. Results: Body weight, serum lipids, and liver enzyme markers increased at 8 and 16 weeks in each model compared to baseline. Steatosis grade showed a steady upward trend. However, the non-alcoholic steatohepatitis (NASH) Clinical Research Network (CRN) histological scoring method detected no significant difference between 8 and 16 weeks. In contrast, AI analysis was able to quantify dynamic changes in the area, number, and size of hepatic steatosis automatically and objectively, making it more suitable for preclinical MASLD animal experiments. Conclusions: AI recognition technology may be a new tool for the accurate diagnosis of steatosis in MASLD, providing a more precise and objective method for evaluating steatosis in preclinical murine MASLD models under various experimental and treatment conditions. Full article
(This article belongs to the Special Issue Artificial Intelligence in Metabolic Diseases)
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<p>Flowchart of the imaging process and detection of fat vacuoles. (<b>A</b>) Images of unstained liver tissue samples were obtained using an SHG/TPEF imaging device (Genesis <sup>®</sup> 200). (<b>B</b>) All holes in the input images were detected in the TPE channel and classified using a pre-trained decision tree.</p>
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<p>Average body weight (<b>A</b>) and liver weight-to-body weight ratio (<b>B</b>) of the control group and six MASLD mouse models at different time points (0, 8, and 16 weeks; <span class="html-italic">n</span> = 5 at each time point). Note: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001; ****, <span class="html-italic">p</span> &lt; 0.0001; w, week; CCl4, Carbon tetrachloride; WD, Western diet; WDF, WD with high-fructose drinking water; WDF + CCl<sub>4</sub>, WDF plus intraperitoneal injection of CCl<sub>4</sub>; HFD, high-fat diet; HFDF, HFD with high-fructose drinking water; HFDF + CCl<sub>4</sub>, HFD plus intraperitoneal injection of CCl<sub>4</sub>.</p>
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<p>Serum levels of ALT (<b>A</b>), AST (<b>B</b>), cholesterol (CHO) (<b>C</b>), and low-density lipoprotein (LDL) (<b>D</b>) at different time points (0, 8, and 16 weeks) in the control group and six MASLD mouse models (<span class="html-italic">n</span> = 5 at each time point). Note: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ****, <span class="html-italic">p</span> &lt; 0.0001; w, week; CCl<sub>4</sub>, Carbon tetrachloride; WD, Western diet; WDF, WD with high-fructose drinking water; WDF + CCl<sub>4</sub>, WDF plus intraperitoneal injection of CCl<sub>4</sub>; HFD, high-fat diet; HFDF, HFD with high-fructose drinking water; HFDF + CCl<sub>4</sub>, HFD plus intraperitoneal injection of CCl<sub>4</sub>.</p>
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<p>Representative images of H and E staining and SHG/TPEF at 8 and 16 weeks in the control group and six MASLD mouse models. In the H and E staining image, the percentages of vacuole area were shown as the percentages of steatosis, while in the SHG/TPEF image, the red channel represents TPEF, and the green channel represents SHG (collagen structure); the percentages of black fat vacuoles and surrounding affected areas were identified as the percentages of steatosis. H and E, Hematoxylin and eosin; SHG/TPEF, second-harmonic generation/two-photon-excited fluorescence; w, week; CCl<sub>4</sub>, Carbon tetrachloride; WD, Western diet; WDF, WD with high-fructose drinking water; WDF + CCl<sub>4</sub>, WDF plus intraperitoneal injection of CCl<sub>4</sub>; HFD, high-fat diet; HFDF, HFD with high-fructose drinking water; HFDF + CCl<sub>4</sub>, HFD plus intraperitoneal injection of CCl<sub>4</sub>; Bar: 200 μm.</p>
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<p>Steatosis quantification in the control group and six MASLD mouse model groups at different time points (0, 8, and 16 weeks). Quantitative parameters of steatosis (fat vacuoles and affected cell area) based on SHG/TPEF images. Note: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001; ****, <span class="html-italic">p</span> &lt; 0.0001; the number of samples in each group was 5; w, week; CCl<sub>4</sub>, Carbon tetrachloride; WD, Western diet; WDF, WD with high-fructose drinking water; WDF + CCl<sub>4</sub>, WDF plus intraperitoneal injection of CCl<sub>4</sub>; HFD, high-fat diet; HFDF, HFD with high-fructose drinking water; HFDF + CCl<sub>4</sub>, HFD plus intraperitoneal injection of CCl<sub>4</sub>.</p>
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<p>Fat vacuole distribution at different time points (0, 8, and 16 weeks) among the control group and six MASLD mouse models. The x-axis represents the diameter of the fat vacuoles (µm), whereas the y-axis represents the number of fat vacuoles per unit area (mm<sup>2</sup>), corresponding to the diameter of the fat vacuoles. Note: The comparison between different weeks of the same model is based on the difference in fat vacuole distribution according to their diameter per unit area. The <span class="html-italic">p</span>-value of the KS test is shown in the figure. w, week; CCl<sub>4</sub>, Carbon tetrachloride; WD, Western diet; WDF, WD with high-fructose drinking water; WDF + CCl<sub>4</sub>, WDF plus intraperitoneal injection of CCl<sub>4</sub>; HFD, high-fat diet; HFDF, HFD with high-fructose drinking water; HFDF + CCl<sub>4</sub>, HFD plus intraperitoneal injection of CCl<sub>4</sub>.</p>
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21 pages, 1759 KiB  
Review
Extracellular Vesicles from Mesenchymal Stem Cells: Potential as Therapeutics in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)
by Xue Zou and David Brigstock
Biomedicines 2024, 12(12), 2848; https://doi.org/10.3390/biomedicines12122848 - 14 Dec 2024
Viewed by 570
Abstract
Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of triglycerides within hepatocytes, which can progress to more severe conditions, such as metabolic dysfunction-associated steatohepatitis (MASH), which may include progressive fibrosis, leading to cirrhosis, cancer, and death. This goal of [...] Read more.
Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of triglycerides within hepatocytes, which can progress to more severe conditions, such as metabolic dysfunction-associated steatohepatitis (MASH), which may include progressive fibrosis, leading to cirrhosis, cancer, and death. This goal of this review is to highlight recent research showing the potential of mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) in reducing the key pathogenic pathways of MASLD or MASH. Methods: Relevant published studies were identified using PubMed with one or more of the following search terms: MASLD, MASH, NAFLD, NASH, exosome, extracellular vesicle (EV), therapy, and/or mesenchymal stem cells (MSC). The primary literature were subsequently downloaded and summarized. Results: Using in vitro or in vivo models, MSC-EVs have been found to counteract oxidative stress, a significant contributor to liver injury in MASH, and to suppress disease progression, including steatosis, inflammation, and, in a few instances, fibrosis. Some of these outcomes have been attributed to specific EV cargo components including microRNAs and proteins. Thus, MSC-EVs enriched with these types of molecules may have improved the therapeutic efficacy for MASLD/MASH and represent a novel approach to potentially halt or reverse the disease process. Conclusions: MSC-EVs are attractive therapeutic agents for treating MASLD/MASH. Further studies are necessary to validate the clinical applicability and efficacy of MSC-EVs in human MASH patients, focusing on optimizing delivery strategies and identifying the pathogenic pathways that are targeted by specific EV components. Full article
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<p>Schematic depiction of the principal EV subtypes.</p>
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<p>EV biogenesis, release, and uptake. Internal budding of early endosomes results in the formation of intraluminal vesicles (ILVs) that contain cytosolic components (proteins, mRNAs, miRs). ILVs are contained within multivesicular bodies (MVBs) that may fuse with the plasma membrane, resulting in the liberation of their vesicles into the extracellular space, at which point the vesicles become exosomes. Microvesicles (MVs) are formed by the budding of the plasma membrane, resulting in the vesicular entrapment of free cytoplasmic components and the liberation of the MVs into the extracellular space. Both populations of vesicles (exosomes, MVs) are collectively termed EVs and are challenging to discriminate from each other once they have been released from the producer cells. The molecular cargo in EVs may be delivered to target cells by a variety of mechanisms that may involve fusion, endocytosis and/or receptor–ligand interactions.</p>
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<p>(<b>A</b>) Tissue sources of therapeutic MSC-EVs and (<b>B</b>) actions on different hepatic cell types of MSC-EVs in livers with MASLD/MASH.</p>
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11 pages, 487 KiB  
Article
Statin Use in Metabolic Dysfunction-Associated Steatotic Liver Disease and Effects on Vibration-Controlled Transient Elastography-Derived Scores—A Population-Based Inverse Probability Treatment Weighting Analysis
by Natchaya Polpichai, Sakditad Saowapa, Aunchalee Jaroenlapnopparat, Leandro Sierra, Pojsakorn Danpanichkul, Panisara Fangsaard, Phuuwadith Wattanachayakul and Apichat Kaewdech
Livers 2024, 4(4), 677-687; https://doi.org/10.3390/livers4040046 - 12 Dec 2024
Viewed by 403
Abstract
Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease globally. The impact of statins on liver fibrosis severity in MASLD individuals remains uncertain, despite their known cardiovascular benefits. Methods: A cross-sectional study was performed utilizing the National [...] Read more.
Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease globally. The impact of statins on liver fibrosis severity in MASLD individuals remains uncertain, despite their known cardiovascular benefits. Methods: A cross-sectional study was performed utilizing the National Health and Nutrition Examination Survey (NHANES) database from 2017 to 2018. MASLD was defined by hepatic steatosis (controlled attenuation parameter [CAP] score ≥ 288 dB/m) without other etiologies. Using inverse probability treatment weighting to minimize confounding, we examined the association between statin use and MASLD outcomes, including at-risk steatohepatitis (FibroScan-aspartate aminotransferase [AST] [FAST] score ≥ 0.67), significant and advanced fibrosis (liver stiffness measurement [LSM] ≥ 8.8 kilopascals [kPa] and ≥ 11.7 kPa), and advanced fibrosis (AGILE 3+ score ≥ 0.68). Results: Of 1283 MASLD patients, 376 were prescribed statins within the past 30 days. After adjustment for confounders, statin use was significantly associated with reduced risks of at-risk steatohepatitis, significant fibrosis, and high AGILE 3+ scores, with odds ratios (ORs) of 0.29 (95% CI: 0.01 to 0.87), 0.54 (95% CI: 0.31 to 0.95), and 0.41 (95% CI: 0.22 to 0.75), respectively. However, a subgroup analysis showed this effect persisted only with lipophilic statins. Conclusions: Statin use was associated with reduced steatohepatitis and fibrosis in patients with MASLD, supported by robust causal inference and vibration-controlled transient elastography-derived scores. Full article
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<p>Comparison of the effects of hydrophilic and lipophilic statins on at-risk NASH/MASH and fibrosis severity outcomes. The ORs and 95% CIs are displayed for each outcome. Hydrophilic statins are represented in blue, and lipophilic statins are represented in pink. The p-values for the effects of lipophilic statins are less than 0.05 (<span class="html-italic">p</span> = 0.04 for at-risk NASH/MASH (FAST ≥ 0.67), <span class="html-italic">p</span> = 0.03 for significant fibrosis, and <span class="html-italic">p</span> &lt; 0.01 for high AGILE 3+ scores). NASH: Non-alcoholic steatohepatitis; MASH: Metabolic-dysfunction associated steatohepatitis; FAST: FibroScan-AST score; OR: Odds ratio; CI: Confidence interval.</p>
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16 pages, 2357 KiB  
Article
The Effect of Quercetin on Non-Alcoholic Fatty Liver Disease (NAFLD) and the Role of Beclin1, P62, and LC3: An Experimental Study
by Ioannis Katsaros, Maria Sotiropoulou, Michail Vailas, Fotini Papachristou, Paraskevi Papakyriakopoulou, Marirena Grigoriou, Nikolaos Kostomitsopoulos, Alexandra Giatromanolaki, Georgia Valsami, Alexandra Tsaroucha and Dimitrios Schizas
Nutrients 2024, 16(24), 4282; https://doi.org/10.3390/nu16244282 - 11 Dec 2024
Viewed by 731
Abstract
Background/Objectives: Non-alcoholic fatty liver disease (NAFLD) is a major metabolic disorder with no established pharmacotherapy. Quercetin, a polyphenolic flavonoid, demonstrates potential hepatoprotective effects but has limited bioavailability. This study evaluates the impact of quercetin on NAFLD and assesses the roles of autophagy-related proteins [...] Read more.
Background/Objectives: Non-alcoholic fatty liver disease (NAFLD) is a major metabolic disorder with no established pharmacotherapy. Quercetin, a polyphenolic flavonoid, demonstrates potential hepatoprotective effects but has limited bioavailability. This study evaluates the impact of quercetin on NAFLD and assesses the roles of autophagy-related proteins in disease progression. Methods: Forty-seven male C57BL/6J mice were fed a high-fat diet (HFD) for 12 weeks to induce NAFLD, followed by quercetin treatment for 4 weeks. Mice were divided into baseline, control, and two quercetin groups, receiving low (10 mg/kg) and high (50 mg/kg) doses. Liver histology was scored using the NAFLD Activity Score (NAS). Immunohistochemistry and immunoblotting were performed to analyze autophagy markers. Results: Quercetin-treated groups showed significant reductions in NAS compared to controls (p = 0.011), mainly in steatosis and steatohepatitis. Immunohistochemistry indicated increased expression of autophagy markers LCA and p62 in quercetin groups. Western blot analysis revealed significant elevations in LC3A in the treated groups, suggesting improved autophagic activity and lipid degradation. Conclusions: Quercetin effectively reduces NAFLD severity and modulates autophagy-related proteins. These findings suggest that quercetin enhances autophagic flux, supporting its therapeutic potential for NAFLD. Additional research is needed to clarify the molecular mechanisms of quercetin and to determine the optimal dosing for clinical application. Full article
(This article belongs to the Special Issue Fruits and Vegetable Bioactive Substances and Nutritional Value)
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<p>Steatohepatitis prevalence was stratified by each experimental group ((<b>A</b>) Baseline, (<b>B</b>) Control, (<b>C</b>) QUE 1, (<b>D</b>) QUE 2). Orange segments indicate the prevalence of steatohepatitis, while blue segments represent the prevalence of fatty liver. QUE 1—low-dose quercetin, QUE 2—high-dose quercetin.</p>
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<p>Representative immunoblotting images and densitometric analysis of p62 expression. The P fraction contains autophagy-related vesicles, and the SP fraction contains cytoplasmic soluble proteins. The bold horizontal lines in the graphs represent the geometric means. Where #, <span class="html-italic">p</span> &lt; 0.05 vs. the corresponding P fraction. QUE 1—low-dose quercetin, QUE 2—high-dose quercetin, CON—control, BSL—baseline.</p>
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<p>Representative immunoblotting images and densitometric analysis of p62 expression. The P fraction contains autophagy-related vesicles, and the SP fraction contains cytoplasmic soluble proteins. The bold horizontal lines in the graphs represent the geometric means. Where #, <span class="html-italic">p</span> &lt; 0.05 vs. the corresponding P fraction. QUE 1—low-dose quercetin, QUE 2—high-dose quercetin, CON—control, BSL—baseline.</p>
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<p>Representative immunoblotting images and densitometric analysis of LC3A-I expression. In general, LC3A-II was undetectable. The P fraction contains autophagy-related vesicles, and the SP fraction contains cytoplasmic soluble proteins. The bold horizontal lines in the graphs represent the geometric means. Where #, <span class="html-italic">p</span> &lt; 0.05 vs. the corresponding P fraction. QUE 1—low-dose quercetin, QUE 2—high-dose quercetin, CON—control, BSL—baseline.</p>
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<p>Representative immunoblotting images and densitometric analysis of LC3A-I expression. In general, LC3A-II was undetectable. The P fraction contains autophagy-related vesicles, and the SP fraction contains cytoplasmic soluble proteins. The bold horizontal lines in the graphs represent the geometric means. Where #, <span class="html-italic">p</span> &lt; 0.05 vs. the corresponding P fraction. QUE 1—low-dose quercetin, QUE 2—high-dose quercetin, CON—control, BSL—baseline.</p>
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<p>Representative immunoblotting images and densitometric analysis of LC3B-I and -II expression. The P fraction contains autophagy-related vesicles, and the SP fraction contains cytoplasmic soluble proteins. The bold horizontal lines in the graphs represent the geometric means. Where #, <span class="html-italic">p</span> ≤ 0.05 vs. the corresponding P fraction. QUE 1—low-dose quercetin, QUE 2—high-dose quercetin, CON—control, BSL—baseline.</p>
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<p>Representative immunoblotting images and densitometric analysis of LC3B-I and -II expression. The P fraction contains autophagy-related vesicles, and the SP fraction contains cytoplasmic soluble proteins. The bold horizontal lines in the graphs represent the geometric means. Where #, <span class="html-italic">p</span> ≤ 0.05 vs. the corresponding P fraction. QUE 1—low-dose quercetin, QUE 2—high-dose quercetin, CON—control, BSL—baseline.</p>
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18 pages, 2313 KiB  
Review
Inappropriate Diet Exacerbates Metabolic Dysfunction-Associated Steatotic Liver Disease via Abdominal Obesity
by Minghui Xiang, Xiaoli Tian, Hui Wang, Ping Gan and Qian Zhang
Nutrients 2024, 16(23), 4208; https://doi.org/10.3390/nu16234208 - 5 Dec 2024
Viewed by 796
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a refined categorization of non-alcoholic fatty liver disease (NAFLD), highlighting the intricate relationship between hepatic steatosis and metabolic dysfunction. Abdominal obesity (AO), a key diagnostic criterion for metabolic dysfunction, predominantly results from inappropriate diet and unhealthy [...] Read more.
Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a refined categorization of non-alcoholic fatty liver disease (NAFLD), highlighting the intricate relationship between hepatic steatosis and metabolic dysfunction. Abdominal obesity (AO), a key diagnostic criterion for metabolic dysfunction, predominantly results from inappropriate diet and unhealthy dietary habits. To comprehensively investigate which dietary factors contribute to MASLD through AO and to understand the underlying biological mechanisms, we initially conducted a systematic review of meta-analysis articles in the PubMed database from the past decade, summarizing dietary factors that affect AO. Subsequently, we conducted targeted searches in the PubMed database for these dietary factors and provided a narrative review of the mechanisms of how these dietary factors lead to AO and how AO exacerbates MASLD. A diet characterized by excessive intake of energy, carbohydrates, fructose, or ultra-processed foods (UPFs) is considered inappropriate. Inappropriate diet leads to the formation of MASLD and AO by enhancing pathways such as de novo lipid synthesis (DNL) in the liver, insulin resistance (IR), gut–liver dysfunction, and inflammation. Dietary interventions for inappropriate diets can effectively intervene in and improve MASLD and AO. The mechanism of inappropriate diet on abdominal fat deposition is through excessive energy or the activation of the enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD-1) to increase endocortisol secretion. Then, the excessive accumulation of visceral fat facilitates a rapid and augmented flux of free fatty acids (FFAs) to the liver and initiates a series of deleterious effects, including oxidative stress (OS), endoplasmic reticulum stress (ERS), activation of protein kinase C (PKC) pathways, and inflammation. Additionally, FFAs may mediate excessive lipid deposition and hepatocellular damage through the action of hormones. These pathways to liver damage exacerbate MASLD and progression to metabolic dysfunction-associated steatohepatitis (MASH) and fibrosis. Furthermore, investigating other potential mechanisms by which AO may influence MASLD could offer new recommendations for the treatment guidelines of MASLD. Full article
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<p>Forest map of dietary patterns for improving waist circumference. The size of the points is proportional to the standard error. DASH: Dietary Approaches to Stop Hypertension [<a href="#B16-nutrients-16-04208" class="html-bibr">16</a>,<a href="#B17-nutrients-16-04208" class="html-bibr">17</a>,<a href="#B18-nutrients-16-04208" class="html-bibr">18</a>,<a href="#B19-nutrients-16-04208" class="html-bibr">19</a>,<a href="#B20-nutrients-16-04208" class="html-bibr">20</a>,<a href="#B21-nutrients-16-04208" class="html-bibr">21</a>,<a href="#B23-nutrients-16-04208" class="html-bibr">23</a>,<a href="#B24-nutrients-16-04208" class="html-bibr">24</a>,<a href="#B25-nutrients-16-04208" class="html-bibr">25</a>].</p>
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<p>Forest map of foods for improving waist circumference. The size of the points is proportional to the standard error [<a href="#B26-nutrients-16-04208" class="html-bibr">26</a>,<a href="#B27-nutrients-16-04208" class="html-bibr">27</a>,<a href="#B28-nutrients-16-04208" class="html-bibr">28</a>,<a href="#B29-nutrients-16-04208" class="html-bibr">29</a>,<a href="#B30-nutrients-16-04208" class="html-bibr">30</a>,<a href="#B31-nutrients-16-04208" class="html-bibr">31</a>,<a href="#B32-nutrients-16-04208" class="html-bibr">32</a>,<a href="#B33-nutrients-16-04208" class="html-bibr">33</a>,<a href="#B34-nutrients-16-04208" class="html-bibr">34</a>].</p>
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<p>Forest map of diets associated with abdominal obesity and general obesity. The size of the points is proportional to the standard error. AO: abdominal obesity [<a href="#B35-nutrients-16-04208" class="html-bibr">35</a>,<a href="#B36-nutrients-16-04208" class="html-bibr">36</a>,<a href="#B38-nutrients-16-04208" class="html-bibr">38</a>].</p>
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<p>Mechanisms of excess free fatty acids cause oxidative stress and endoplasmic reticulum stress in hepatocyte. FFA: free fatty acid. TG: triglyceride. PKC: protein kinase C. OS: oxidative stress. ROS: reactive oxygen species. ER: endoplasmic reticulum. ERS: endoplasmic reticulum stress. UPR: unfolded protein response. Mito: mitochondria. Red arrows: activate; black arrows: metabolic pathway.</p>
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<p>Mechanism of hepatocyte injury induced by free fatty acids via the protein kinase c pathway. p-IRS: phosphorylated insulin receptor substrate. PKC: protein kinase C. FFA: free fatty acid. DAG: diacylglycerol. Mito: mitochondria. ROS: reactive oxygen species. TG: triglyceride. Red arrows: activate; black arrows: metabolic pathway; blue arrows: translocate.</p>
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<p>Mechanisms of excess free fatty acids cause inflammation in hepatocytes. FFA: free fatty acid. TG: triglyceride. Red arrows: activate; blue arrows: translocate.</p>
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<p>Mechanisms of excess free fatty acids exacerbating metabolic dysfunction-associated steatotic liver disease in hepatocyte. FFA: free fatty acid. TG: triglyceride. GH: growth hormone. TH: thyroid hormones. PKC: protein kinase C. p-IRS: phosphorylated insulin receptor substrate. DAG: diacylglycerol. OS: oxidative stress. Mito: mitochondria. ROS: reactive oxygen species. ER: endoplasmic reticulum. UPR: unfolded protein response. ERS: endoplasmic reticulum stress. IR: insulin resistance. MASLD: metabolic dysfunction-associated steatotic liver disease. MASH: metabolic dysfunction-associated steatohepatitis.</p>
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20 pages, 2385 KiB  
Article
A Comprehensive Analysis of Liver Lipidomics Signature in Adults with Metabolic Dysfunction-Associated Steatohepatitis—A Pilot Study
by Thomai Mouskeftara, Georgios Kalopitas, Theodoros Liapikos, Konstantinos Arvanitakis, Eleni Theocharidou, Georgios Germanidis and Helen Gika
Int. J. Mol. Sci. 2024, 25(23), 13067; https://doi.org/10.3390/ijms252313067 - 5 Dec 2024
Viewed by 821
Abstract
Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is the most common chronic liver disorder in Western countries, encompassing a range of conditions from steatosis to Metabolic Dysfunction-Associated Steatohepatitis (MASH), which can potentially progress to cirrhosis. Lipidomics approaches have revealed significant alterations in the hepatic [...] Read more.
Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is the most common chronic liver disorder in Western countries, encompassing a range of conditions from steatosis to Metabolic Dysfunction-Associated Steatohepatitis (MASH), which can potentially progress to cirrhosis. Lipidomics approaches have revealed significant alterations in the hepatic lipidome associated with both steatosis and steatohepatitis, with these changes correlating with disease manifestation. While the transition from steatosis to MASH remains poorly understood, recent research indicates that both the quantity and quality of deposited lipids play a pivotal role in MASLD progression. In our study, we utilized untargeted and targeted analyses to identify intact lipids and fatty acids in liver biopsies from healthy controls and MASLD patients, categorized based on their histological findings. In total, 447 lipid species were identified, with 215 subjected to further statistical analysis. Univariate and multivariate analyses revealed alterations in triglyceride species and fatty acids, including FA 16:0, FA 16:1, FA 18:3 n6, the sum of MUFA, and the Δ9-desaturase activity ratio. This research provides insights into the connection between dysregulated lipid metabolism in the progression of MASLD, supporting previous findings. Further studies on lipid metabolism could improve risk assessment methods, particularly given the current limited understanding of the transition from steatosis to MASH. Full article
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<p>Lipid subclasses identified in liver biopsies of NAFLD patients and healthy controls based on targeted and untargeted analyses of fatty acids and esterified lipids. Abbreviations: FA: fatty acids, Cer: ceramides, SM: sphingomyelins, LPC: monoacylglycerophosphocholines, LPE: monoacylglycerophosphoethanolamines, PC: diacylglycerophosphocholines, PE: diacylglycerophosphoethanolamines, PE-O: 1-alkyl,2-acylglycerophosphoethanolamines, PG: diacylglycerophosphoglycerols, PI: diacylglycerophosphoinositols, PS: diacylglycerophosphoserines, CE: cholesterol esters, DG: diglycerides, and TG: triglycerides.</p>
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<p>Lipid class composition (in normalized peak areas; log10 scaled) of liver biopsies in the three main groups of the study. The total abundance of each lipid class was calculated by adding up peak areas of lipid species. Boxes highlight the values between 25% and 75% quartiles; vertical lines connect minimum and maximum values. Statistically significant difference was observed in the class of TGs between controls and NASH (** <span class="html-italic">p</span>-value = 5.2 × 10<sup>−6</sup>) and in NAFL–NASH patients (** <span class="html-italic">p</span>-value = 4.25 × 10<sup>−4</sup>).</p>
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<p>Lipid class composition (in normalized peak areas; log10 scaled) of liver biopsies in the three main groups of the study. The total abundance of each lipid class was calculated by adding up peak areas of lipid species. Boxes highlight the values between 25% and 75% quartiles; vertical lines connect minimum and maximum values. Statistically significant difference was observed in the class of TGs between controls and NASH (** <span class="html-italic">p</span>-value = 5.2 × 10<sup>−6</sup>) and in NAFL–NASH patients (** <span class="html-italic">p</span>-value = 4.25 × 10<sup>−4</sup>).</p>
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<p>(<b>a</b>) Unsupervised PCA model depicting the studied groups in the liver biopsy, where healthy controls are depicted with green dots, patients with NAFL with purple dots and patients with NASH with blue dots (R<sup>2</sup>X = 0.823, Q<sup>2</sup> = 0.736). (<b>b</b>) Supervised OPLS-DA model depicting the differentiation between samples of healthy controls and patients with NASH (R<sup>2</sup>X = 0.823, R<sup>2</sup>Y = 0.942, Q<sup>2</sup> = 0.871, CV ANOVA <span class="html-italic">p</span>-value = 1.25 × 10<sup>−3</sup>). (<b>c</b>) Supervised OPLS-DA model depicting the differentiation between patients with NAFL and patients with NASH (R<sup>2</sup>X = 0.797, R<sup>2</sup>Y = 0.897, Q<sup>2</sup> = 0.782, CV ANOVA <span class="html-italic">p</span>-value = 1.81 × 10<sup>−2</sup>). Pareto scaling was used in all models.</p>
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<p>(<b>a</b>) Unsupervised PCA model depicting the studied groups in the liver biopsy, where healthy controls are depicted with green dots, patients with NAFL with purple dots and patients with NASH with blue dots (R<sup>2</sup>X = 0.823, Q<sup>2</sup> = 0.736). (<b>b</b>) Supervised OPLS-DA model depicting the differentiation between samples of healthy controls and patients with NASH (R<sup>2</sup>X = 0.823, R<sup>2</sup>Y = 0.942, Q<sup>2</sup> = 0.871, CV ANOVA <span class="html-italic">p</span>-value = 1.25 × 10<sup>−3</sup>). (<b>c</b>) Supervised OPLS-DA model depicting the differentiation between patients with NAFL and patients with NASH (R<sup>2</sup>X = 0.797, R<sup>2</sup>Y = 0.897, Q<sup>2</sup> = 0.782, CV ANOVA <span class="html-italic">p</span>-value = 1.81 × 10<sup>−2</sup>). Pareto scaling was used in all models.</p>
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<p>Boxplots showing the distribution of the 19 TG species, FA 16:0, FA 16:1, FA 18:3 ω6, and MUFA across the studied groups. These lipids were common to both healthy controls–NASH patients and NAFL–NASH patient comparisons. <span class="html-italic">p</span> values ≤ 0.05 are highlighted **.</p>
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<p>Boxplots showing the distribution of the 19 TG species, FA 16:0, FA 16:1, FA 18:3 ω6, and MUFA across the studied groups. These lipids were common to both healthy controls–NASH patients and NAFL–NASH patient comparisons. <span class="html-italic">p</span> values ≤ 0.05 are highlighted **.</p>
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<p>Boxplots showing the distribution of the 19 TG species, FA 16:0, FA 16:1, FA 18:3 ω6, and MUFA across the studied groups. These lipids were common to both healthy controls–NASH patients and NAFL–NASH patient comparisons. <span class="html-italic">p</span> values ≤ 0.05 are highlighted **.</p>
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15 pages, 5598 KiB  
Article
An Integrated Analysis of the Role of Gut Microbiome-Associated Metabolites in the Detection of MASH-Related Cirrhosis
by Feixiang Xiong, Xuejie Zhang, Yuyong Jiang, Peipei Meng, Yang Zhou, Xiaomin Ji, Jialiang Chen, Tong Wu and Yixin Hou
Metabolites 2024, 14(12), 681; https://doi.org/10.3390/metabo14120681 - 4 Dec 2024
Viewed by 610
Abstract
Background and aim: The prevalence and adverse outcomes of metabolic dysfunction associated with steatotic liver disease (MAFLD) are increasing. The changes in the gut microbiota and metabolites associated with metabolic dysfunction-associated steatohepatitis (MASH) are regarded as an essential part of the progression of [...] Read more.
Background and aim: The prevalence and adverse outcomes of metabolic dysfunction associated with steatotic liver disease (MAFLD) are increasing. The changes in the gut microbiota and metabolites associated with metabolic dysfunction-associated steatohepatitis (MASH) are regarded as an essential part of the progression of MAFLD. This study aimed to identify the gut microbiota and metabolites involved in the development of MAFLD in patients. Method: This study enrolled 90 patients (healthy controls, HC: n = 30; MASH: n = 30; MASH-related cirrhosis, MC: n = 30), and their fecal samples were collected for 16S rRNA sequencing and non-targeted LC–MS/MS metabolomics analysis. Data preprocessing and statistical analyses were performed using QIIME2 software, Pynast, QIIME2 package, Progenesis QI, and R program. Results: The abundance of Prevotellaceae at the family level and Prevotella at the genus level was lower in the MASH and NC samples than in the HC samples. Both Prevotellaceae and Prevotella showed the strongest correlation with MASH progression via random forest analysis. Untargeted metabolomics was used to quantitatively screen for discrepant metabolites in the stool samples from the three groups. Linolenic acid (LA)-related metabolite levels were significantly lower in MASH and NC samples. Associations between Prevotella- or LA-related metabolites and liver function were discovered. A high abundance of Prevotella was associated with LA-related metabolites and MASH. Conclusion: This study identified that gut microbiota and metabolites are associated with MASH-related metabolic dysfunction. LA and Prevotella are depleted during MASH progression, and additional supplementation with Prevotella may be a potential strategy for the future treatment of MAFLD. Full article
(This article belongs to the Section Lipid Metabolism)
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<p>(<b>A</b>) ACE index boxplot in three groups; (<b>B</b>) Chao1 index boxplot in three groups; (<b>C</b>) Shannon index boxplot in three groups; (<b>D</b>) Simpson index boxplot in three groups; (<b>E</b>) Principal Coordinates Analysis (PCoA) between MASH and HC patients; (<b>F</b>) PCoA analysis between NC and HC patients; (<b>G</b>) the abundance of the top 15 gut microbiota in three groups at family level; (<b>H</b>) the abundance of the top 15 gut microbiota in three groups at genus level; (<b>I</b>) the importance of decreased gut microbiota in three groups at the family level via RF analysis; (<b>J</b>) the importance of decreased gut microbiota in three groups at the genus level via RF analysis. *, <span class="html-italic">p</span> &lt; 0.05; ns, <span class="html-italic">p</span> &gt; 0.05. Abbreviations: HC, healthy control; MASH, nonalcoholic steatohepatitis; NC, nonalcoholic steatohepatitis cirrhosis; RF, random forest.</p>
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<p>(<b>A</b>) OPLS-DA analysis between HC and MASH patients; (<b>B</b>) OPLS-DA analysis between HC and NC patients; (<b>C</b>) filtering out the metabolites identified through both univariate and multivariate statistical analyses via volcano plots in MASH patients (VIP &gt; 2, <span class="html-italic">p</span> &lt; 0.05, |log2FC| &gt; 1); (<b>D</b>) filtering out the metabolites identified through both univariate and multivariate statistical analyses via volcano plots in NC patients (VIP &gt; 2, <span class="html-italic">p</span> &lt; 0.05, |log2FC| &gt; 1); (<b>E</b>) the main gut metabolites between HC and MASH patients; (<b>F</b>) the main gut metabolites between HC and NC patients. Abbreviations: HC, healthy control; MASH, non-alcoholic steatohepatitis; NC, non-alcoholic steatohepatitis cirrhosis; VIP, variable importance in projection; FC, fold change.</p>
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<p>(<b>A</b>) Upregulation and downregulation of lipid gut metabolites in MASH patients; (<b>B</b>) upregulation and downregulation of lipid gut metabolites in NC patients; (<b>C</b>) the KEGG enrichment via lipid gut metabolites in MASH patients; (<b>D</b>) the KEGG enrichment via lipid gut metabolites in NC patients; (<b>E</b>–<b>I</b>) LA-related metabolites level in three groups. Abbreviations: HC, healthy control; MASH, nonalcoholic steatohepatitis; NC, nonalcoholic steatohepatitis cirrhosis; LA, linolenic acid. *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>(<b>A</b>) The heatmap of the correlation between reduced gut microbiota and liver function in MASH patients; (<b>B</b>) the heatmap of the correlation between reduced gut microbiota and liver function in NC patients; (<b>C</b>) the heatmap of the correlation between lipid gut microbiota and liver function in MASH patients; (<b>D</b>) the heatmap of the correlation between lipid gut microbiota and liver function in NC patients. Abbreviations: HC, healthy control; MASH, non-alcoholic steatohepatitis; NC, non-alcoholic steatohepatitis cirrhosis. *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>(<b>A</b>) Incidence of MASH and cirrhosis in the high- and low-abundance groups of <span class="html-italic">Prevotella</span> in three groups; (<b>B</b>) LA-related gut microbiota level of three groups in the low-abundance group of <span class="html-italic">Prevotella</span>; (<b>C</b>) LA-related gut microbiota level of three groups in the high-abundance group of <span class="html-italic">Prevotella</span>; (<b>D</b>) the bubble diagram of the correlation between LA-related gut microbiota and a low abundance of <span class="html-italic">Prevotellaa</span>; (<b>E</b>) the bubble diagram of the correlation between LA-related gut microbiota and a high abundance of <span class="html-italic">Prevotella.</span> Abbreviations: HC, healthy control; MASH, non-alcoholic steatohepatitis; NC, non-alcoholic steatohepatitis cirrhosis; LA, linolenic acid. *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001. ns, <span class="html-italic">p</span> &gt; 0.05.</p>
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10 pages, 620 KiB  
Systematic Review
MRI-PDFF Assessment of Intrahepatic Fat Changes Post-Bariatric Surgery: A Systematic Literature Review
by Danut Dejeu, Paula Dejeu, Anita Muresan, Paula Bradea and Viorel Dejeu
Medicina 2024, 60(12), 2003; https://doi.org/10.3390/medicina60122003 - 4 Dec 2024
Viewed by 481
Abstract
Background and Objectives: Non-alcoholic fatty liver disease (NAFLD) is prevalent among obese individuals and can progress to non-alcoholic steatohepatitis (NASH). Bariatric surgery is known to induce significant weight loss and may improve NAFLD. This systematic review uniquely synthesizes current evidence on the [...] Read more.
Background and Objectives: Non-alcoholic fatty liver disease (NAFLD) is prevalent among obese individuals and can progress to non-alcoholic steatohepatitis (NASH). Bariatric surgery is known to induce significant weight loss and may improve NAFLD. This systematic review uniquely synthesizes current evidence on the effects of bariatric surgery on intrahepatic fat content, measured by magnetic resonance imaging proton density fat fraction (MRI-PDFF), and assesses study quality using the Newcastle–Ottawa Scale (NOS). Materials and Methods: The literature search was conducted across the PubMed, Scopus, and Web of Science databases up to October 2024, identifying 12 prospective cohort studies involving 613 patients who underwent bariatric surgery. Inclusion criteria included adult patients with NAFLD undergoing bariatric surgery, assessment of liver fat changes using MRI-PDFF before and after surgery, and studies reporting quantitative data on liver fat fraction and relevant clinical parameters. Data extraction focused on patient demographics, surgical procedures, specific weight loss outcomes (delta BMI), changes in intrahepatic fat content (delta MRI-PDFF), and quality assessment scores based on the NOS. Results: Significant reductions in intrahepatic fat content were observed across all studies, with delta MRI-PDFF reductions ranging from 6.9% to 14%. Weight loss outcomes varied, with excess weight loss percentages up to 81.3% and BMI reductions up to 12 kg/m². The quality assessment scores ranged from six to nine out of nine, indicating generally high-quality studies. Correlations were noted between the degree of weight loss and reduction in liver fat content. Several studies reported high rates of resolution of steatosis and NASH post-operatively. Conclusions: Bariatric surgery leads to significant reductions in intrahepatic fat content and improvements in NAFLD among obese patients. The degree of weight loss correlates with the reduction in liver fat. These findings underscore the clinical utility of bariatric surgery as a strategic intervention for managing NAFLD in obese individuals, potentially influencing clinical practice guidelines by integrating bariatric surgery as a viable treatment option for NAFLD-related hepatic conditions. Full article
(This article belongs to the Section Surgery)
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<p>PRISMA flow diagram.</p>
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18 pages, 1866 KiB  
Article
An 8-Week Very Low-Calorie Ketogenic Diet (VLCKD) Alters the Landscape of Obese-Derived Small Extracellular Vesicles (sEVs), Redefining Hepatic Cell Phenotypes
by Francesco Balestra, Maria De Luca, Giorgia Panzetta, Nicoletta Depalo, Federica Rizzi, Rita Mastrogiacomo, Sergio Coletta, Grazia Serino, Emanuele Piccinno, Dolores Stabile, Pasqua Letizia Pesole, Valentina De Nunzio, Giuliano Pinto, Nicole Cerabino, Martina Di Chito, Maria Notarnicola, Endrit Shahini, Giovanni De Pergola and Maria Principia Scavo
Nutrients 2024, 16(23), 4189; https://doi.org/10.3390/nu16234189 - 4 Dec 2024
Viewed by 773
Abstract
Background. Very low-calorie ketogenic diets (VLCKD) are an effective weight-loss strategy for obese individuals, reducing risks of liver conditions such as non-alcoholic steatohepatitis and fibrosis. Small extracellular vesicles (sEVs) are implicated in liver fibrosis by influencing hepatic cell phenotypes and contributing to liver [...] Read more.
Background. Very low-calorie ketogenic diets (VLCKD) are an effective weight-loss strategy for obese individuals, reducing risks of liver conditions such as non-alcoholic steatohepatitis and fibrosis. Small extracellular vesicles (sEVs) are implicated in liver fibrosis by influencing hepatic cell phenotypes and contributing to liver damage. This study investigates sEVs derived from serum of 60 obese adults categorized into low fibrosis risk (LR) and intermediate/high fibrosis risk (IHR) groups based on FibroScan elastography (FIB E scores, limit value 8 kPa) and all participants underwent an 8-week VLCKD intervention. Methods. The study examines the impact of these sEVs on fibrosis markers, inflammation, and autophagy in a hepatocyte cell line (HEPA-RG) using bioinformatics, RNA sequencing, lipidomics, RT-PCR, and Western blotting before (T0) and after (T1) VLCKD. Results. sEVs from LR patients post-VLCKD reduced fibrosis related gene expression (e.g., ACTA2) and enhanced proteins associated with regeneration and inflammation (e.g., HDAC6). Conversely, sEVs from IHR patients increased fibrosis and inflammation related gene expression (PIK3CB, AKT1, ACTA2) in hepatocytes, raising concerns about VLCKD suitability for IHR patients. IHR sEVs also decreased expression of HDAC10, HDAC6, HDAC3, MMP19, and MMP2, while increasing modulation of p-AKT, α-SMA, and VIM. Conclusion. These findings underscore the critical role of sEVs in regulating inflammation, remodeling, and hepatic stress responses, particularly in IHR patients, and suggest sEVs could complement instrumental evaluations like FibroScan in fibrosis assessment. Full article
(This article belongs to the Special Issue Dietary Advice and Guidance on Liver Metabolism)
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<p>Flow diagram of patients enrolment. Of 200 potential participants, 70 met the inclusion criteria. Of these, 9 declined to participate, and another 1 withdrew at the beginning after the start of the treatment. In the end, 60 patients, 37 patients were classified as LR and 23 as IHR, were enrolled and successfully completed the treatment.</p>
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<p>sEVs were isolated from plasma of LR and IHR patients, prior to the dietary intervention (T0) and following 8 weeks of VLCKD (T1): TEM micrographs, scale bar 100 nm (<b>A</b>) and table reporting the intensity-weighted average hydrodynamic diameter and corresponding polydispersity index (PDI) obtained by DLS analysis, along with ζ-potential values (<b>B</b>).</p>
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<p>Lipidomic evaluation. Chemical structures of palmitic and oleic acid (<b>A</b>). Comparison of oleic/palmitic acid ratio obtained by GC-FID chromatography of fatty acid extracted from cell membranes of HEPA-RG treated with sEVs from patients with LR and patients with IHR prior to the dietary intervention (T0) and following 8 weeks of VLCKD (T1) (<b>B</b>) (* <span class="html-italic">p</span> &lt; 0.05). Area % of palmitic acid and oleic acid determined by GC-FID chromatography in cell membranes of HEPA-RG treated with sEVs from patients with LR and patients with IHR (<b>C</b>,<b>D</b>) (** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Gene expression analysis of HEPA-RG after stimulation with patient-derived sEVs before (T0) and after (T1) treatment for 8 weeks of VLCKD, using samples from both LR (<b>A</b>) and IHR (<b>B</b>) patients. Each row represents a gene, while each column corresponds to a sample. Relative expression levels are depicted using a color-coded scale, with red indicating high expression and green indicating low expression, as shown in the scale provided at the top. An interaction network (<b>C</b>) was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). In this network, nodes represent proteins, and edges indicate predicted functional associations based on seven distinct sources of evidence: fusion events, neighborhood relationships, co-occurrence, experimental data, text mining, database information, and co-expression patterns. The color scheme is as follows: light blue indicates curated databases; light pink denotes experimentally determined interactions; gray represents co-expression; yellow signifies gene neighborhood; orange indicates gene fusions; blue denotes gene co-occurrence; green represents text mining; and purple indicates protein homology.</p>
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<p>Gene expression of PIK3CB, AKT1, HDAC10, HDAC6, HDAC3, MMP19, MMP2, MMP9, ACTA2, and VIM in HEPA–RG cells treated with serum-derived sEVs from obese patients after VLCKD for 8 weeks. Patients with LR and patients with IHR at T0 (before the VLCKD) and after 8 weeks of VLCKD (T1). For the HEPA-RG expression, the fold change values for PIK3CB and AKT1 are reported in (<b>A</b>). The fold change values for HDAC 10, HDAC 6, and HDAC 3 are reported in (<b>B</b>). The fold change values for MMP19, MMP9, and MMP3 are reported in (<b>C</b>). The fold change values for VIM and ACTA2 are reported in (<b>D</b>). (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.001, and *** <span class="html-italic">p</span> &lt; 0.0001 for T1 vs. T0).</p>
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<p>Evaluation of proteins regulating hepatocyte degeneration and liver fibrosis was conducted in HEPA-RG cell lines treated with sEVs isolated from patients with LR and patients with IHR, both before (T0) and after (T1) 8 weeks of VLCKD. Representative Western blots of various proteins (PIK3CB, AKT, pAKT, HDAC3, HDAC6, α-SMA, and VIM) and the housekeeping protein GAPDH (<b>A</b>). A semi-quantitative evaluation of protein expression levels was performed using video-densitometry analysis of PIK3CB, AKT, and pAKT1 (<b>B</b>), HDAC6 and HDAC3 (<b>C</b>), MMP2 and MMP9 (<b>D</b>), and α-SMA and VIM (<b>E</b>) bands on the Western blots. The GAPDH protein band was used to normalize the protein bands for each subject. (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.001 for T1 vs. T0).</p>
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<p>HEPA-RG cells line viability evaluation. Cell viability was evaluated by MTS assay, after incubation with sEVs derived from patients with LR and patients with IHR before (T0) and after (T1) 8 weeks of VLCKD. Negative controls were untreated cells (CTRL). (** <span class="html-italic">p</span> &lt; 0.001 IHR vs. CTRL).</p>
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