World Journal of Hepatology最新文献

Steatotic liver disease (SLD) encompasses a group of disorders characterized by the excessive accumulation of fat in the liver. It is classified into four categories based on clinical manifestations: Metabolic dysfunction-associated SLD (MASLD), metabolic-alcohol-associated liver disease (ALD), ALD, and cryptogenic SLD. In the United States, its prevalence stands at 34.2%, making it the most common cause of cirrhosis and hepatocellular carcinoma (HCC). In addition to factors related to endocrine, nutrition, and medications, several genetic markers have been implicated in the disease's pathogenesis. Notable genes include PNPLA3, TM6SF2, GCKR, MBOAT7 and HSD17B13. These genetic polymorphisms can significantly impact prognosis and disease outcomes. For example, PNPLA3 is the most frequently associated gene with MASLD, increasing the risk of HCC by 12-fold and liver-related mortality by 18-fold. Furthermore, certain genetic markers are more prevalent in specific ethnic groups; for instance, PNPLA3 is common among Hispanics, while TM6SF2 is linked to higher fat content in African Americans. With a better understanding of the genetic factors involved in the pathogenesis of SLD, significant advancements have been made in diagnostics and therapeutics. This review explores the role of genetic factors in the disease's development, discusses current advancements in non-invasive diagnostic modalities, and examines therapeutic improvements based on these genetic insights to achieve better outcomes.

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease, represents a growing global health burden, contributing significantly to liver-related morbidity and mortality. Early detection and timely intervention are essential to prevent disease progression. Conventional diagnostic methods, which rely on specialized imaging and invasive liver biopsies, underscore the need for non-invasive, cost-effective alternatives. Artificial intelligence-particularly machine learning and deep learning-has emerged as a transformative tool in MASLD diagnostics, offering improved accuracy in risk prediction, imaging interpretation, and disease stratification. This review synthesizes recent advancements in AI-based MASLD diagnostics, highlighting key models, performance metrics, and clinical applications, while addressing ongoing challenges such as data standardization, interpretability, and clinical validation.

Hepatocellular carcinoma (HCC) is imposing a growing global health burden, with China accounting for nearly half of incident cases and mortality worldwide. Early screening is critical to improving survival in high-burden regions. However, the global standardized screening rate for high-risk populations is less than 24%, and HCC screening currently faces severe challenges. We synthesize recent advances in HCC screening, including optimized serum biomarkers, evolving imaging techniques, and validated models. Emerging liquid biopsy technologies and artificial intelligence further demonstrate considerable promise for enhancing noninvasive detection efficacy. Multifaceted collaboration among policymakers, healthcare systems, and communities is essential to implement effective screening programs and ultimately improve survival outcomes.

Background: The combination of immune checkpoint inhibitors and antiangiogenic drugs has shown promising efficacy in advanced hepatocellular carcinoma (HCC). However, tumor regression and progression-free survival (PFS) vary considerably among patients receiving this therapy.

Aim: To identify predictive biomarkers in HCC patients treated with sintilimab (programmed cell death protein-1 inhibitor) plus lenvatinib (tyrosine kinase inhibitor).

Methods: In this single-center study in China, patients with unresectable HCC received sintilimab every 21 days and daily oral lenvatinib. Treatment response was assessed by modified response evaluation criteria in solid tumors. Tumor biopsies underwent RNA sequencing, immune microenvironment profiling, and whole-exome sequencing. Differentially expressed genes (DEGs) and immune cell subsets between response groups were identified, followed by survival analyses. All potential predictors of PFS, together with clinical variables, were included in Cox regression to identify independent prognostic factors.

Results: Between August 2019 and November 2021, 33 patients with hepatitis-B-virus-related HCC were enrolled; by January 2024, 13 had undergone potentially curative surgery or ablation. RNA sequencing identified 94 DEGs between responders (n = 22) and non-responders (n = 11) using Fisher's exact test or Wilcoxon rank-sum test (all P < 0.05). High long intergenic non-protein coding RNA 01554 (LINC01554) and whirlin expression were associated with longer PFS in Kaplan-Meier analysis (P < 0.05). DEG-immune cell analysis showed positive correlations with pro-B and plasma cells in responders, and negative correlations with CD4+ central memory T (Tcm), T helper 1, and natural killer T cells in non-responders; none significantly predicted PFS, although CD4+ Tcm cells approached significance (P < 0.10). Whole-exome sequencing revealed Fanconi anemia complementation group D2 mutations enriched in non-responders (P < 0.05), while cut-like homeobox 1 mutations predicted poorer PFS (P = 0.011). Cox regression identified solitary tumor [P = 0.02, hazard ratio (HR) = 0.31], high LINC01554 (P = 0.01, HR = 0.16), and elevated CD4+ Tcm cells (P = 0.05, HR = 0.29) as independent predictors of prolonged PFS.

Conclusion: Sintilimab plus lenvatinib showed heterogeneous efficacy in HCC. High LINC01554 expression, elevated CD4+ Tcm cells, and solitary tumors may serve as predictive biomarkers for prolonged disease control.

Background: Alcohol can cause alcoholic fatty liver, alcoholic steatohepatitis, alcoholic liver cirrhosis (ALC), and hepatocellular carcinoma. China has become the second-largest country in the world in terms of alcohol consumption, lacking national epidemiological data on alcoholic liver disease (ALD).

Aim: To understand the incidence and characteristics of ALD in Hainan Province of China.

Methods: From October 2022 to April 2023, a stratified proportional multi-stage whole population sampling method was adopted to select permanent residents of Haikou, Sanya, Qionghai, Dongfang, and Wuzhishan in Hainan Province to carry out questionnaire surveys, blood tests, and ultrasound examinations of the liver.

Results: A total of 2704 valid questionnaires were obtained from residents aged 15-93 years old. The rates of drinking, hazardous drinking, and harmful drinking were 31.73%, 14.53%, and 5.03%, respectively. The above rates were higher for males than for females, increasing with income, and the rates for ethnic minorities, such as Li, were higher than for Han Chinese (P < 0.05). Drinking rates increased with literacy (P < 0.05). Drinking rate and hazardous drinking rate decreased with age, were higher for residents of agricultural households than non-agricultural households, and higher for married than unmarried individuals (P < 0.05). The total number of patients with ALD was 142, with a detection rate of 5.25%. ALD detection rate was higher for males than females, decreased with age, and higher with income (P < 0.05). Patients with ALD included 48 (33.8%) cases of mild ALD, 64 (45.1%) cases of alcoholic fatty liver, 18 (12.7%) cases of alcoholic steatohepatitis, and 12 (8.5%) cases of ALC. The proportion of those who consumed more than 80 g of alcohol per day increased as they progressed from mild ALD to ALC stage. Diabetes mellitus and hyperlipidemia were easily combined in some cases, accounting for 25 (17.6%) and 80 (56.3%), respectively. The average daily alcohol consumption of ALD patients of Li ethnicity ≥ 80 g was significantly more than that of Han ethnicity (χ ² = 5.652, P = 0.02), and was predominantly among those who drank large amounts of alcohol intermittently (χ ² = 89.093, P < 0.001).

Conclusion: The rates of drinking, hazardous drinking, harmful drinking, and detection of ALD in Hainan Province need to be paid attention to by advocating a healthy lifestyle, such as abstinence and limiting alcohol consumption.

Gestational diabetes mellitus (GDM) is increasingly recognized not only for its immediate obstetric complications but also for its long-term metabolic consequences in both mothers and their offspring. Traditionally, research has emphasized the roles of pancreatic β-cell dysfunction and placental dysregulation in GDM. However, emerging evidence highlights the maternal liver as a central metabolic hub during pregnancy coordinating glucose, lipid, and hormonal adaptations essential for fetal development. This review synthesizes current findings on how GDM disrupts the maternal liver's adaptive roles, transforming it from a metabolic coordinator into a source of maladaptive endocrine, inflammatory, and nutrient signals. It outlines key mechanistic pathways through which maternal hepatic dysfunction may increase offspring susceptibility to non-alcoholic fatty liver disease and type 2 diabetes mellitus. These include hepatokine dysregulation, altered lipid metabolism, impaired insulin signaling, inflammatory and oxidative stress pathways, and epigenetic and transcriptomic reprogramming. In addition, it explores novel axes such as the gut-liver-placenta interplay, bile acid signaling disruptions, endoplasmic reticulum stress responses, and extracellular vesicle-mediated communication. By reframing the maternal liver's role in GDM pathophysiology, this review identifies critical windows for early clinical intervention and highlights the potential for liver-focused strategies to prevent the intergenerational transmission of metabolic disease.

While splenectomy has been associated with hepatocellular carcinoma (HCC) in cirrhotic patients, its role as a direct carcinogenic factor remains controversial. This letter argues that the primary risk of HCC stems from the underlying liver disease rather than the surgical removal of the spleen itself. Current literature is based mostly on retrospective analyses lacking randomized controlled trials. Moreover, there is insufficient evidence to suggest that splenectomy in non-cirrhotic patients increases HCC risk. Prospective multicenter studies are needed to clarify the causal relationship.

Background: Telerehabilitation can help overcome geographic barriers and expand access to physical rehabilitation for patients with chronic liver disease.

Aim: To evaluate the impact of adherence to a videoconference-supervised telerehabilitation programme on frailty, functional capacity, and quality of life in pre-frail or frail cirrhotic patients awaiting liver transplantation.

Methods: We conducted a non-randomised controlled clinical trial involving patients listed for liver transplantation from January 2021 to May 2023. Frailty was assessed using the Liver Frailty Index (LFI). Participants were enrolled in a 12-week telerehabilitation programme and classified as adherent (≥ 50% sessions) or non-adherent. Functional capacity was measured using the 4-minute step test (4MST), and quality of life was evaluated with the 36-Item Short Form Health Survey (SF-36) questionnaire.

Results: Fifty-seven pre-frail or frail patients were included in the study and enrolled in the telerehabilitation programme. Adherence was observed in 29.8% of participants. At baseline, non-adherent patients had higher mean LFI scores (4.24 vs 4.03, P < 0.001). Over time, the LFI score increased by 0.11 in non-adherent patients, while adherent patients experienced a mean score reduction of 0.54 (final mean LFI score: 3.2). Adherent patients also demonstrated enhanced heart rate responses in the 4MST (P < 0.001) and greater improvements in the physical functioning, vitality, and mental health domains of the SF-36. No serious adverse events were reported.

Conclusion: The videoconference-supervised telerehabilitation programme was safe and effective in reducing frailty and improving functional outcomes and quality of life in adherent cirrhotic patients on the liver transplant waitlist.

Liver diseases are among the most insidious and life-threatening conditions due to their progressive nature and late symptom onset. Cirrhosis and hepatocellular carcinoma account for most liver-related deaths, often following the progression from fibrosis. Fibrosis creates a hostile microenvironment, characterized by portal hypertension, vascular capillarization, intrahepatic vasoconstriction, and extracellular matrix deposition, which severely limits drug efficacy. Advances in pharmaceutical science have prompted efforts to develop liver-targeted drug delivery systems to prevent or reduce the progression of fibrosis, a central feature of many liver diseases. Fibrosis often reduces the in vivo efficacy of both approved and experimental drugs, underscoring the need for improved delivery strategies focused on stability, controlled release, and precise targeting. Nanoparticle (NP)-based systems show promise, either by delivering therapeutic agents, or in some cases, by contributing directly to the therapeutic effects. This review summarizes the main types of NPs explored for liver disease treatment, especially those aiming to reverse fibrosis or prevent its progression, a critical therapeutic target in chronic liver diseases. Additionally, it examines gene delivery and ultrasound-guided microbubble strategies, which can be combined with NPs to improve cell-specific targeting and boost therapeutic effects. Together, these approaches have the potential to address current therapeutic challenges and accelerate the development of liver-targeted treatments for clinical application.