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“Metabolic dysfunction-associated fatty liver disease (MAFLD)” is the term suggested in 2020 to refer to fatty liver disease related to systemic metabolic dysregulation. The name change from nonalcoholic fatty liver disease (NAFLD) to MAFLD comes with a simple set of criteria to enable easy diagnosis at the bedside for the general medical community, including primary care physicians. Since the introduction of the term, there have been key areas in which the superiority of MAFLD over the traditional NAFLD terminology has been demonstrated, including for the risk of liver and extrahepatic mortality, disease associations, and for identifying high-risk individuals. Additionally, MAFLD has been adopted by a number of leading pan-national and national societies due to its concise diagnostic criterion, removal of the requirement to exclude concomitant liver diseases, and reduction in the stigma associated with this condition. The current article explores the differences between MAFLD and NAFLD diagnosis, areas of benefit, some potential limitations, and how the MAFLD terminology has opened up new fields of research.

Serum liver enzyme concentrations are the most frequently-used laboratory markers of liver disease, a major cause of mortality. We conduct a meta-analysis of genome-wide association studies of liver enzymes from UK BioBank and BioBank Japan. We identified 160 previously-unreported independent alanine aminotransferase, 190 aspartate aminotransferase, and 199 alkaline phosphatase genome-wide significant associations, with some affecting multiple different enzymes. Associated variants implicate genes that demonstrate diverse liver cell type expression and promote a range of metabolic and liver diseases. These findings provide insight into the pathophysiology of liver and other metabolic diseases that are associated with serum liver enzyme concentrations. Serum liver enzymes are used as markers of liver disease, their concentration influenced in part by genetic factors. Here the authors meta-analyse genome-wide association studies on the UK Biobank and BioBank Japan to evaluate the association of three liver enzymes with liver and other metabolic diseases.

In medical imaging diagnosis, the identification of normal liver, fatty liver, and cirrhosis is often challenging due to subtle morphological and density differences. Previous studies have used CNNs, MLPs or transformers to extract lesion features. However, CNN’s global representation is limited, while MLPs and transformers have insufficient local modeling, resulting in insufficient lesion information mining. Therefore, this article proposes a hybrid network CMT-Net, which unifies the local perception of CNNs, high-dimensional mapping of MLPs, and global dependencies of Transformers into a single architecture, significantly improving the accuracy of CT liver three classification. The core components of CMT-Net include an efficient transformer (ET) module, which focuses on extracting local feature details while progressively integrating global information, significantly enhancing the model feature representation and generalization capabilities. Additionally, this paper introduces a Hybrid MLP (HM) module that combines Token-Mixing MLP and Channel-Mixing MLP to achieve deep fusion of spatial and channel information, further improving feature extraction. To validate the proposed algorithm, extensive experiments were conducted on a dataset of three liver diseases collected from the Imaging Department of Urumqi People’s Hospital. The results demonstrate that CMT-Net achieves outstanding performance in classifying normal liver, fatty liver, and cirrhosis. These findings not only provide an effective tool for precise liver disease diagnosis but also offer new directions for deep learning model design in medical image classification tasks.

Non-alcoholic fatty liver disease (NAFLD) is the most common hepatic pathology in industrialized countries, affecting about 25% of the general population. NAFLD is a benign condition, however, it could evolve toward more serious diseases, including non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and finally, hepatocellular carcinoma (HCC). Liver biopsy is still the gold standard for NAFLD diagnosis. Due to the risks associated with liver biopsy and the impossibility to apply it on a large scale, it is now necessary to identify non-invasive biomarkers, which may reliably identify patients at higher risk of progression. Therefore, several lines of research have tried to address this issue by identifying novel biomarkers using omics approaches, including lipidomics, metabolomics and RNA molecules’ profiling. Thus, in this review, we firstly report the conventional biomarkers used in clinical practice for NAFL and NASH diagnosis as well as fibrosis staging, and secondly, we pay attention to novel biomarkers discovered through omics approaches with a particular focus on RNA biomarkers (microRNAs, long-noncoding RNAs), showing promising diagnostic performance for NAFL/NASH diagnosis and fibrosis staging.

Background. In inflammatory bowel disease (IBD) patients there are reports of the occurrence of hepatobiliary manifestations, so the aim of this study was to evaluate the hepatobiliary manifestations in patients with Crohn’s disease (CD) and ulcerative colitis (UC) from an IBD reference center. Methods. Cross-sectional study in an IBD reference center, with interviews and review of medical charts, between July 2015 and August 2016. A questionnaire addressing epidemiological and clinical characteristics was used. Results. We interviewed 306 patients, and the majority had UC (53.9%) and were female (61.8%). Hepatobiliary manifestations were observed in 60 (19.6%) patients with IBD. In the greater part of the patients (56.7%) hepatobiliary disorders were detected after the diagnosis of IBD. In UC (18.2%) patients, the hepatobiliary disorders identified were 11 (6.7%) non-alcoholic fatty liver disease, 9 (5.5%) cholelithiasis, 6 (3.6%) primary sclerosing cholangitis (PSC), 3 (1.8%) hepatotoxicity associated with azathioprine, 1 (0.6%) hepatitis B, and 1 (0.6%) hepatic fibrosis. In CD (21.3%) patients, 11 (7.8%) had cholelithiasis, 11 (7.8%) non-alcoholic fatty liver disease, 4 (2.8%) PSC, 3 (2.1%) hepatotoxicity, 1 (0.7%) hepatitis B, (0.7%) hepatitis C, 1 (0.7%) alcoholic liver disease, and 1 (0.7%) autoimmune hepatitis (AIH). There was one case of PSC/AIH overlap syndrome. Conclusion. The frequency of hepatobiliary disorders was similar in both forms of IBD in patients evaluated. The most common nonspecific hepatobiliary manifestations in IBD patients were non-alcoholic liver disease and cholelithiasis. The most common specific hepatobiliary disorder was PSC in patients with extensive UC or ileocolonic CD involvement; this was seen more frequently in male patients.

Metabolic dysfunction-associated steatotic liver disease (MASLD) diagnosis and management have evolved rapidly alongside the increasing prevalence of obesity and related complications. Hepatology has expanded its focus beyond late-stage cirrhosis and portal hypertension to earlier, complex MASLD cases in younger patients, necessitating closer collaboration with endocrinology. The renaming of nonalcoholic fatty liver disease (NAFLD) to MASLD reflects its pathophysiology, reduces stigma, and has prompted new research directions. Noninvasive tests such as liver stiffness measurement now play a crucial role in diagnosis, reducing reliance on invasive liver biopsies. However, advanced omics technologies, despite their potential to enhance diagnostic precision and patient stratification, remain underutilized in routine clinical practice. Behavioral factors, including posttraumatic stress disorder (PTSD) and lifestyle choices, influence disease outcomes and must be integrated into patient management strategies. Primary care settings are critical for early screening to prevent progression to advanced disease, yet sizable challenges remain in implementing effective screening protocols. This Review explores these evolving aspects of MASLD diagnosis and management, emphasizing the need for improved diagnostic tools, multidisciplinary collaboration, and holistic care approaches to address existing gaps and ensure comprehensive patient care across all healthcare levels.

The following medical subject headings were used: \"Diabetes Mellitus, type 2\"; \"Fatty Liver\"; \"Hepatitis, Toxic\"; \"Sulfonylurea Compounds\"; \"Thiazolidinediones\"; \"Rosiglitazone\"; \"Pioglitazone\"; \"Troglitazone\"; \"Hydroxymethylglutaryl-CoA Reductase Inhibitors\"; \"Metformin\"; \"Acarbose\"; and \"Gemfibrozil\" and free-text terms: \"fatty liver\", \"steatohepatitis\", \"nonalcoholic steatohepatitis\", \"nonalcoholic fatty liver disease\", \"drug-induced hepatitis\", each drug name and \"hepat*\", and each drug name. SUMMARY - Type 2 diabetes is associated with a large number of liver disorders including elevated liver enzymes, fatty liver disease, cirrhosis, hepatocellular carcinoma, and acute liver failure.

The Polycystic Kidney Disease (PKD) is characterized by progressive renal cyst development and other extrarenal manifestation including Polycystic Liver Disease (PLD). Phenotypical characterization of animal models mimicking human diseases are commonly used, in order to, study new molecular mechanisms and identify new therapeutic approaches. The main biomarker of disease progression is total volume of kidney and liver in both human and mouse, which correlates with organ function. For this reason, the estimation of the number and area of the tissue occupied by cysts, is critical for the understanding of physiological mechanisms underlying the disease. In this regard, cystic index is a robust parameter commonly used to quantify the severity of the disease. To date, the vast majority of biomedical researchers use ImageJ as a software tool to estimate the cystic index by quantifying the cystic areas of histological images after thresholding. This tool has imitations of being inaccurate, largely due to incorrectly identifying non-cystic regions. We have developed a new software, named CystAnalyser (register by Universidade de Santiago de Compostela-USC, and Fundación Investigación Sanitaria de Santiago-FIDIS), that combines automatic image processing with a graphical user friendly interface that allows investigators to oversee and easily correct the image processing before quantification. CystAnalyser was able to generate a cystic profile including cystic index, number of cysts and cyst size. In order to test the CystAnalyser software, 795 cystic kidney, and liver histological images were analyzed. Using CystAnalyser there were no differences calculating cystic index automatically versus user input, except in specific circumstances where it was necessary for the user to distinguish between mildly cystic from non-cystic regions. The sensitivity and specificity of the number of cysts detected by the automatic quantification depends on the type of organ and cystic severity, with values 76.84-78.59% and 76.96-89.66% for the kidney and 87.29-93.80% and 63.42-86.07% for the liver. CystAnalyser, in addition, provides a new tool for estimating the number of cysts and a more specific measure of the cystic index than ImageJ. This study proposes CystAnalyser is a new robust and freely downloadable software tool for analyzing the severity of disease by quantifying histological images of cystic organs for routine biomedical research. CystAnalyser can be downloaded from https://citius.usc.es/transferencia/software/cystanalyser (for Windows and Linux) for research purposes.

BackgroundNon-invasive scores, such as the non-alcoholic fatty liver disease (NAFLD) Fibrosis Score (NFS), are increasingly used for liver fibrosis assessment in patients with NAFLD. The aim of this study was to assess the applicability and reliability of non-invasive fibrosis scores in NAFLD patients with and without morbid obesity.MethodsThree hundred sixty-eight patients with biopsy-proven NAFLD identified between January 2012 and December 2015 were studied; 225 with morbid obesity (biopsy obtained during bariatric surgery) and 143 patients without (termed as “conventional”).ResultsMedian age was 47 years, 57% were female. Median body mass index (BMI) was 42.9 kg/m2 with significant differences between our conventional and morbidly obese patients (BMI 29.0 vs. 50.8 kg/m2, p < 0.001). Overall, 42% displayed mild/moderate and 16% advanced liver fibrosis (stage III/IV). All tested scores were significantly linked to fibrosis stage (p < 0.001 for all). FIB-4 (AUROC 0.904), APRI (AUROC 0.848), and NFS (AUROC 0.750) were identified as potent predictors of advanced fibrosis, although NFS overestimated fibrosis stage in morbid obesity. Limiting BMI to a maximum of 40 kg/m2 improved NFS’ overall performance (AUROC 0.838). FIB-4 > 1.0 indicated high probability of advanced fibrosis (OR = 29.1). FIB-4 predicted advanced fibrosis independently from age, sex, BMI, and presence of morbid obesity.ConclusionsOur data suggest that FIB-4 score is an accurate predictor of advanced fibrosis in NAFLD throughout all BMI stages. Without adjustment, NFS tends to overestimate fibrosis in morbidly obese NAFLD patients. This problem may be solved by implementation of an upper BMI limit (for NFS) or adjustment of diagnostic thresholds.

The terminology and diagnostic criteria for fatty liver disease have undergone recent evolution, from non-alcoholic fatty liver disease (NAFLD) to metabolic dysfunction-associated fatty liver disease (MAFLD), and more recently to metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to compare the estimated prevalence of FLD with that of NAFLD, MAFLD, and MASLD using different definitions. Data were analyzed from 10,520 participants in the first phase of the Guilan Persian Cohort Study, part of the nationwide PERSIAN Cohort. Participants were classified based on NAFLD, MAFLD, and MASLD. Of 10,520 participants, 5,025 (47.8%) had a fatty liver index (FLI) ≥ 60 and were diagnosed with SLD. The prevalence of MASLD, MAFLD, and NAFLD was 33.7%, 47.6%, and 33.7%, respectively, while 4.5% ( n  = 471) were classified as metabolic dysfunction-associated alcohol-related liver disease (MetALD). Among those with NAFLD, 99.7% also met MAFLD criteria, and all met MASLD criteria. MAFLD was associated with the highest adjusted odds of elevated FIB-4 (OR: 1.27; 95% CI: 1.24–1.30) and hepatic steatosis index (OR: 2.01; 95% CI: 1.82–2.21). NAFLD and MASLD had a similar, lower prevalence compared to MAFLD. MetALD was not included under MASLD but was encompassed by MAFLD.