A paradigm shift in fatty liver disease nomenclature has introduced steatotic liver disease (SLD) as an umbrella term, encompassing metabolic dysfunction–associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-related liver disease (MetALD), and alcohol-associated liver disease (ALD). These SLD subtypes exist along a dynamic continuum shaped by the synergistic interplay of metabolic dysfunction and alcohol exposure. Accumulating evidence indicates that SLD exhibits distinct outcome-based clusters reflecting heterogeneity in pathogenic drivers and clinical trajectories. Cardiometabolic clusters, most prominently observed in MASLD, are characterized by systemic metabolic dysfunction and confer increased risks of cardiovascular disease (CVD). In contrast, liver-specific clusters demonstrate progressive fibrosis and cirrhosis, hepatic decompensation, and hepatocellular carcinoma. In large-scale cohorts, CVD accounts for 40-50% of deaths in MASLD, while liver-related mortality predominates in ALD (>60%). The relative dominance of cardiometabolic versus liver-specific clusters shifts progressively across the MASLD-MetALD-ALD spectrum. While CVD remains a major driver of mortality, particularly in MASLD, hepatic outcomes increase stepwise with advancing fibrosis and greater alcohol exposure. Advanced fibrosis is the predominant shared determinant amplifying both CVD and hepatic risks across subtypes. This review synthesizes cardiovascular and hepatic outcome patterns across the MASLD-MetALD-ALD spectrum, highlighting the prognostic reorientation across the continuum, in which hepatic outcomes rise stepwise with alcohol exposure while cardiovascular risk remains an important but less subtype-differentiated burden. These findings advocate outcome-oriented risk stratification integrating noninvasive fibrosis assessment, alcohol biomarkers (PEth), and cardiovascular risk calculators within the Cardiovascular-Kidney-Metabolic framework. Understanding SLD as a modifiable continuum enables individualized management to optimize multisystem outcomes.
Reply to correspondence on “Comparative risk of fibrosis progression with sodium-glucose cotransporter-2 vs. dipeptidyl peptidase-4 inhibitors in metabolic dysfunction-associated steatotic liver disease and type 2 diabetes mellitus with low-to-intermediat Yang-Hsiang Lin, Ching-Chih Hu, Chih-Lang Lin Clinical and Molecular Hepatology.2026; 32(3): e434. CrossRef
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Liver cancer is one of the deadliest malignancies, with increasing incidence worldwide. Recent advances in immunotherapy have expanded the options for systemic therapy against advanced hepatocellular carcinoma (HCC), but there are no biomarkers currently available to predict which patients will respond, leading to suboptimal patient selection strategies. Understanding of the genetic and immunologic features of HCC is accelerating rapidly through the use of single cell and spatial transcriptomic techniques. However, there is a need to translate insights gained through these new studies to improve treatment options and improve patient selection. In this review we summarize knowledge of the immunogenomics of HCC, emphasizing recent advances, and discuss progress toward clinical translation.
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Alcohol-associated liver disease (ALD) is a leading cause of preventable cirrhosis, hepatocellular carcinoma (HCC), and liver-related mortality, yet current laboratory and imaging tools detect only late-stage disease. This narrative review synthesizes emerging evidence on novel biomarkers that capture the multidimensional pathophysiology of ALD and discusses their utility for routine clinical practice. Traditional serum-based liver fibrosis markers (e.g., cytokeratin-18 fragments, Pro-C3, the enhanced liver fibrosis test) improve non-invasive staging risk beyond aminotransferases, while elastography techniques, such as vibration-controlled transient elastography and magnetic resonance elastography, can also quantify liver stiffness with high precision. Among novel mechanistic biomarkers, genetic polymorphisms in PNPLA3, TM6SF2, MBOAT7, HSD17B13, and polygenic risk scores define lifetime risk, whereas sex-specific hormonal milieus also modify susceptibility and progression. Moreover, gut dysbiosis signatures, including reduced Faecalibacterium prausnitzii, Akkermansia muciniphila, and a lower Firmicutes/Bacteroidetes ratio, and their metabolites (short-chain fatty acids, and bile acids, trimethylamine N-oxide) correlate with liver inflammation and fibrosis. Endocrine imbalances of cortisol, testosterone, and thyroid hormones further stratify metabolic vulnerability. Ultimately, multi-omics platforms (i.e., transcriptomics, lipidomics, proteomics, metabolomics, and epigenomics) can reveal distinct molecular signatures that predict steatohepatitis, fibrogenesis, and early HCC. Integrating these biomarkers enables phase-specific enrichment strategies, earlier intervention windows, adaptive dose-finding, and mechanismbased endpoints in ALD trials. Remaining challenges include assay standardization, validation across diverse cohorts, and incorporation into regulatory frameworks. Future work could evaluate cost-effectiveness and feasibility in routine clinical practice. Widespread adoption promises earlier diagnosis, personalized risk reduction, and more efficient drug development for this globally prevalent disorder.
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Liver disease has emerged as a critical and escalating public health concern worldwide, with the Asia-Pacific region at the forefront of this challenge due to its vast population and diverse socioeconomic landscape. Over the coming five decades, this region will experience profound changes in liver disease patterns, shaped by rapid urbanization, lifestyle modifications, advancements in medical technologies, and evolving public health strategies. This article offers an in-depth analysis of six transformative areas defining the trajectory of liver disease in the region. First, it highlights the alarming rise of metabolic dysfunction-associated fatty liver disease and metabolic dysfunction-associated steatohepatitis, diseases driven by modern lifestyle factors and inherent metabolic susceptibilities. Concurrently, it celebrates the declining burden of viral hepatitis, underscoring the success of sustained public health interventions. However, new challenges are emerging, such as the growing impact of environmental and occupational exposures on liver health. Breakthroughs in genomic and epigenetic research promise to advance precision medicine, offering targeted therapeutic solutions. Additionally, the integration of artificial intelligence, big data, and telemedicine is poised to revolutionize liver disease management, improving accessibility and personalized care. Finally, the article emphasizes the critical role of robust health policies, preventive strategies, and cross-border collaboration in shaping a healthier future. By synthesizing these insights, the study aims to guide innovative and effective responses to the evolving liver disease landscape in the Asia-Pacific region.
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Metabolic dysfunction-associated steatotic liver disease (MASLD) is a significant global health issue, affecting over 30% of the population worldwide due to the rising prevalence of metabolic risk factors such as obesity and type 2 diabetes mellitus. This spectrum of liver disease ranges from isolated steatosis to more severe forms such as steatohepatitis, fibrosis, and cirrhosis. Recent studies highlight the role of gut microbiota in MASLD pathogenesis, showing that dysbiosis significantly impacts metabolic health and the progression of liver disease. This review critically evaluates current microbiome-centered therapies in MASLD management, including prebiotics, probiotics, synbiotics, fecal microbiota transplantation, and emerging therapies such as engineered bacteria and bacteriophage therapy. We explore the scientific rationale, clinical evidence, and potential mechanisms by which these interventions influence MASLD. The gut-liver axis is crucial in MASLD, with notable changes in microbiome composition linked to disease progression. For instance, specific microbial profiles and reduced alpha diversity are associated with MASLD severity. Therapeutic strategies targeting the microbiome could modulate disease progression by improving gut permeability, reducing endotoxin-producing bacteria, and altering bile acid metabolism. Although promising, these therapies require further research to fully understand their mechanisms and optimize their efficacy. This review integrates findings from clinical trials and experimental studies, providing a comprehensive overview of microbiome-centered therapies’ potential in managing MASLD. Future research should focus on personalized strategies, utilizing microbiome features, blood metabolites, and customized dietary interventions to enhance the effectiveness of these therapies.
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Nutrition and dietary interventions are a central component in the pathophysiology, but also a cornerstone in the management of patients with non-alcoholic fatty liver disease (NAFLD). Summarizing our rapidly advancing understanding of how our diet influences our metabolism and focusing on specific effects on the liver, we provide a comprehensive overview of dietary concepts to counteract the increasing burden of NAFLD. Specifically, we emphasize the importance of dietary calorie restriction independently of the macronutrient composition together with adherence to a Mediterranean diet low in added fructose and processed meat that seems to exert favorable effects beyond calorie restriction. Also, we discuss intermittent fasting as a type of diet specifically tailored to decrease liver fat content and increase ketogenesis, awaiting future study results in NAFLD. Finally, personalized dietary recommendations could be powerful tools to increase the effectiveness of dietary interventions in patients with NAFLD considering the genetic background and the microbiome, among others.
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Molecular tests are necessary to stratify cancer patients for targeted therapy. However, high cost and technical barriers limit the application of these tests, hindering optimal treatment. Recently, deep learning (DL) has been applied to predict molecular test results from digitized images of tissue slides. Furthermore, treatment response and prognosis can be predicted from tissue slides using DL. In this review, we summarized DL-based studies regarding the prediction of genetic mutation, microsatellite instability, tumor mutational burden, molecular subtypes, gene expression, treatment response, and prognosis directly from hematoxylin- and eosin-stained tissue slides. Although performance needs to be improved, these studies clearly demonstrated the feasibility of DL-based prediction of key molecular features in cancer tissues. With the accumulation of data and technical advances, the performance of the DL system could be improved in the near future. Therefore, we expect that DL could provide cost- and time-effective alternative tools for patient stratification in the era of precision oncology.
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