Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study

BACKGROUND

Liver cirrhosis complicated by portal vein thrombosis (PVT) is a fatal complication with no specific manifestations but often misdiagnosed, it crucially increases the mortality worldwide. This study aimed to identify risk factors and establish a predictive model for diagnosis of venous thrombosis clinical by routine blood tests and endoscopic characteristics.

METHODS

Patients from Gansu Provincial Hospital from October 2019 to December 2023 were enrolled. The retrospective modelling cohort was screened by propensity score matching (PSM) at a 1:1 ratio from the baseline characteristics before endoscopic diagnosis. Variables were collected from blood test and endoscopic signs using machine learning method (ML). Logistic regression determined risk factors. The predictive performance was evaluated by receiver operation curve (ROC), calibration curve, clinical decision analysis (DCA) and influence curve (CIC). Furthermore, external cohort was used for validation, an online nomogram was established.

RESULTS

A total of 1,058 patients were enrolled, and 470 patients were included after PSM 1: 1. The model identified 7 factors, including splenectomy, blood urea nitrogen (BUN), serum sodium, activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer, and degree of oesophageal varices. The area under the curve (AUC) was 0.907 (95% CI, 0.877-0.931). The calibration curve, decision and clinical impact curves showed the model demonstrated a good predictive accuracy and clinical benefits. The validation got an AUC of 0.890 (95% CI, 0.831-0.934), A nomogram tool was finally established for application.

CONCLUSION

Blood test combined endoscopic characters could preliminarily predict the liver cirrhosis with portal vein thrombosis for cirrhotic patients undergoing endoscopic examination.

Prognostic indicators and outcome in patients with acute liver failure, sepsis and with and without shock: a retrospective cohort study

BACKGROUND

Sepsis or septic shock is associated with severe morbidity and mortality in patients with acute liver failure (ALF). This study aimed to explore the potential prognostic value of common clinical indicators in patients with ALF, sepsis and with and without shock.

PATIENTS AND METHODS

The clinical, laboratory, and microbiological data of patients with ALF and sepsis or septic shock who were admitted to the intensive care unit from January 2014 to December 2019 were collected retrospectively. Clinical indicators, outcomes and the associations among them were analyzed and defined.

RESULTS

Of 150 patients, 64 (42.7%) and 86 (57.3%) were divided into the shock and non-shock groups, respectively. Plasma procalcitonin (PCT), C-reactive protein (CRP), and creatinine (Cre) levels, aspartate aminotransferase to alanine aminotransferase (AST/ALT) ratio, and prothrombin time (PT) in the shock group and plasma PCT and Cre levels in the non-shock group were positively correlated with 30-day, 60-day, and 90-day mortality. Furthermore, plasma ALT levels were positively correlated with 60-day and 90-day mortality, and PTA showed negative correlations with 30-day, 60-day, and 90-day mortality in both groups. Multivariate logistic regression analysis revealed that the combination of plasma PCT and CRP levels, the combination of plasma PCT and ALT levels, and the combination of plasma ALT levels and PTA were found to be associated with 90-day mortality.

CONCLUSIONS

Clinical indicators, especially plasma PCT, CRP, and ALT levels, PTA, and their combinations were associated with poor outcomes in patients with ALF, sepsis and with and without shock.

Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM

BACKGROUND

Chronic hepatitis B (CHB) is a common cause of liver cirrhosis (LC), a condition associated with an unfavourable prognosis. Therefore, timely diagnosis of LC in CHB patients is crucial.

OBJECTIVE

This study aimed to enhance the diagnostic accuracy of LC in CHB patients by integrating liver stiffness measurement (LSM) with traditional indicators.

METHODS

The study participants were randomly divided into training and internal validation sets. Employing the least absolute shrinkage and selection operator (LASSO) and random forest-recursive feature elimination (RF-RFE) for feature selection, we developed both traditional logistic regression and five machine learning models (k-nearest neighbors, random forest (RF), artificial neural network, support vector machine and eXtreme Gradient Boosting). Performance evaluation included receiver operating characteristic curves, calibration curves and decision curve analysis. Shapley additive explanations (SHAP) was employed to improve the interpretability of the optimal model.

RESULTS

We retrospectively included 1609 patients with CHB, among whom 470 were diagnosed with cirrhosis. Cirrhosis was diagnosed based on histological confirmation or clinical assessment, supported by characteristic findings on abdominal ultrasound and corroborative evidence such as thrombocytopenia, varices or imaging from CT/MRI. In the internal validation, the RF model achieved an accuracy above 0.80 and an AUC above 0.80, with outstanding calibration ability and clinical net benefit. Additionally, the model exhibited excellent predictive performance in an independent external validation set. The SHAP analysis indicated that LSM contributed the most to the model. The model still showed strong discriminative power when using only LSM or traditional indicators alone.

CONCLUSIONS

Machine learning models, especially the RF model, can effectively identify LC in CHB patients. Integrating LSM with traditional indicators can enhance diagnostic performance.

Novel prognostic scoring models for hepatitis B virus-related acute-on-chronic liver failure: A comparison with classical models

Early diagnosis and accurate prognostic evaluation are important for guiding clinical treatment and reducing mortality in patients with hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF). The present study established novel prognostic scoring models to guide the clinical treatment of patients with HBV-ACLF. We performed a retrospective analysis of clinical data from two cohorts of patients diagnosed with HBV-ACLF. By comparing differences in baseline characteristics and clinical indicators between the survival (n = 102) and dead (n = 64) groups in the derivation cohort(n = 166), four laboratory indicators (age, INR, TBIL, and HBeAg status) and three clinical signs (extrahepatic infection, ascites, and hepatic encephalopathy) were identified as independent risk factors. Logistic regression and nomogram models were used to construct three novel predictive models. By comparing the death and survival groups, we found that the three new models had higher predictions for AUROC (average of 0.856) than the three old models (average of 0.773). Model 1 had the strongest predictive power for the short-term survival rate of HBV-ACLF patients. Finally, we verified the predictive value of the new models for HBV-ACLF in a validation cohort (n = 42), and the Model 2 demonstrated good predictive accuracy for the 30-day survival rate of patients. The novel model based on seven predictors could accurately predict short-term mortality in patients with HBV-ACLF, which is promising for guiding clinical management and addressing the aetiological differences in Asian populations.

Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study

OBJECTIVES

Sufficient attention has not been given to machine learning (ML) models using longitudinal data for investigating important predictors of new onset of hypertension. We investigated the predictive ability of several ML models for the development of hypertension.

METHODS

A total of 15 965 Japanese participants (men/women: 9,466/6,499, mean age: 45 years) who received annual health examinations were randomly divided into a training group (70%, n = 11,175) and a test group (30%, n = 4,790). The predictive abilities of 58 candidates including fatty liver index (FLI), which is calculated by using body mass index, waist circumference and levels of γ-glutamyl transferase and triglycerides, were investigated by statistics analogous to the area under the curve (AUC) in receiver operating characteristic curve analyses using ML models including logistic regression, random forest, naïve Bayes, extreme gradient boosting and artificial neural network.

RESULTS

During a 10-year period (mean period: 6.1 years), 2,132 subjects (19.1%) in the training group and 917 subjects (19.1%) in the test group had new onset of hypertension. Among the 58 parameters, systolic blood pressure, age and FLI were identified as important candidates by random forest feature selection with 10-fold cross-validation. The AUCs of ML models were 0.765-0.825, and discriminatory capacity was significantly improved in the artificial neural network model compared to that in the logistic regression model.

CONCLUSIONS

The development of hypertension can be simply and accurately predicted by each ML model using systolic blood pressure, age and FLI as selected features. By building multiple ML models, more practical prediction might be possible.

From muscle quality to metabolic health: investigating the association between muscle quality index and metabolic syndrome in adults

OBJECTIVE

Metabolic syndrome (MetS) has a high prevalence in the United States (US); however, limited research comprehensively evaluates the relationship between muscle quality index (MQI) and MetS. This study aims to investigate the association between MQI and MetS.

METHODS

Adults aged 20-60 years from the 2011-2014 National Health and Nutrition Examination Survey were included. Handgrip strength (HGS) was measured using a dynamometer, and appendicular skeletal muscle mass (ASM) was assessed via dual-energy X-ray absorptiometry. MQI_total was calculated as the sum of HGS from both hands divided by ASM. Weighted multivariable logistic regression models and restricted cubic splines (RCS) were used to explore the association between MQI_total and MetS, and subgroup, interaction, and sensitivity analyses were conducted.

RESULTS

A total of 4,503 US residents were included in the study, with 1,165 diagnosed with MetS, yielding a prevalence of 25.9% (1,165/4,503). The weighted multivariable logistic regression model indicated that after adjusting for multiple covariates, MQI was negatively associated with the risk of MetS (odds ratio [OR] = 0.49, 95%CI: 0.32-0.73). Among the different components of MetS, MQI was negatively associated with elevated waist circumference (OR = 0.19, 95%CI: 0.12-0.28), elevated high-density lipoprotein cholesterol (OR = 0.66, 95%CI: 0.51-0.85), and elevated serum triglycerides (OR = 0.66, 95%CI: 0.51-0.85). RCS revealed a negative linear relationship between MQI and MetS (P < 0.001, Pnon-linear = 0.98).

CONCLUSION

Low MQI is associated with an increased risk of MetS, exhibiting a linear relationship. These findings suggest that improving muscle quality may be an effective strategy for the prevention of MetS.

Sepsis in liver failure patients: Diagnostic challenges and recent advancements

Acute liver failure (ALF) and acute-on-chronic LF (ACLF) are prevalent hepatic emergencies characterized by an increased susceptibility to bacterial infections (BI), despite significant systemic inflammation. Literature indicates that 30%-80% of ALF patients and 55%-81% of ACLF patients develop BI, attributed to immunological dysregulation. Bacterial sepsis in these patients is associated with adverse clinical outcomes, including prolonged hospitalization and increased mortality. Early detection of bacterial sepsis is critical; however, distinguishing between sterile systemic inflammation and sepsis poses a significant challenge due to the overlapping clinical presentations of LF and sepsis. Conventional sepsis biomarkers, such as procalcitonin and C-reactive protein, have shown limited utility in LF patients due to inconsistent results. In contrast, novel biomarkers like presepsin and sTREM-1 have demonstrated promising discriminatory performance in this population, pending further validation. Moreover, emerging research highlights the potential of machine learning-based approaches to enhance sepsis detection and characterization. Although preliminary findings are encouraging, further studies are necessary to validate these results across diverse patient cohorts, including those with LF. This article provides a comprehensive review of the magnitude, impact, and diagnostic challenges associated with BI in LF patients, focusing on novel advancements in early sepsis detection and characterization.

Advancing the diagnosis and treatment of metabolic-associated steatotic liver disease: The transformative role of artificial intelligence

Metabolic-associated steatotic liver disease (MASLD), formerly referred to as non-alcoholic fatty liver disease, represents an escalating worldwide medical burden defined by hepatic steatosis, inflammation, fibrosis, and potential progression to cirrhosis or hepatocellular carcinoma. Artificial intelligence (AI) has emerged as a transformative tool in MASLD management, enhancing diagnostic accuracy, risk stratification, and treatment optimization. This review explores the integration of AI in MASLD diagnosis, including AI-based histopathological assessment, non-invasive screening models, imaging diagnostics, and gut microbiota-based approaches. Additionally, AI-driven treatment strategies facilitate personalized management, assess therapeutic response, and contribute to drug discovery. Despite its advantages, challenges such as data integration, model interpretability, and cost-effectiveness remain obstacles to widespread adoption. Future advancements in explainable AI, multi-modal data fusion, and cost-efficient implementations will be crucial for maximizing AI’s impact on MASLD care. AI-driven innovations hold great promise for improving early detection, guiding personalized treatment, and ultimately enhancing patient outcomes in MASLD.

Remnant cholesterol is associated with poor prognosis in patients with hepatitis B-related acute-on-chronic liver failure: a Chinese population-based study

BACKGROUND

Hepatitis B-related acute-on-chronic liver failure (HBV-ACLF) patients possess adverse lipid homeostatic alterations, subsequently affecting their treatment regimens and prognoses. However, the precise association between one lipid homeostasis indicator, remnant cholesterol (RC), and HBV-ACLF prognoses have not been fully elucidated. In this retrospective study, the relationship between RC with 28- and 90-day HBV-ACLF prognoses was delineated.

METHODS

595 HBV-ACLF patients were recruited, and data collected for laboratory parameters at admission, as well as whether poor 28- and 90-day prognoses occurred during the follow-up period, in the form of mortality, or liver transplantation. Patients were divided into 3 groups, based on RC tertiles (Q1-3), and 4 multivariate Cox regression analyses were conducted to identify the associations between RC levels and ACLF prognoses; these analyses excluded different confounding factors, based on the Strengthening the Reporting of Observational Studies in Epidemiology statement. Stratified analysis was conducted to investigate the association between RC and ACLF risk among different subgroups, based on age, sex as well as complications and artificial liver treatment. RC accuracy versus that of other lipid indicators to predict 28- and 90-day ACLF survival was evaluated by restricted cubic spline and receiver operating characteristic (ROC) curve analyses, while Kaplan-Meier curves measured cumulative 28- and 90-day mortality risks.

RESULTS

For all 4 regression models, higher RC were associated with worse liver function, coagulation, and HBV-ACLF prognoses. Restricted cubic spline analysis identified a non-linear relationship between RC and HBV-ACLF prognoses, in which the Q3 RC tertile had the lowest 28-day and 90-day HBV-ACLF survival rates; this was further confirmed by Kaplan-Meier analysis. Additionally, subgroup analysis found that higher RC correlated to worse ACLF prognoses among hypoproteinemia patients. Moreover, RC, compared to total cholesterol, triglycerides, high- and low-density lipoprotein cholesterol, as well as non-high density lipoprotein, was the most accurate in predicting poor 28- and 90-day ACLF prognoses.

CONCLUSIONS

Elevated RC was significantly associated with poorer 28- and 90-day HBV-ACLF prognoses, even after accounting for all other traditional risk factors. Therefore, monitoring RC, along with interventions to reduce their levels, could aid in improving ACLF patient outcomes.

Glucocorticoids accelerate the reduction of disease severity and biochemical parameters in drug-induced liver injury: Assess the causal relationship using the updated RUCAM scale

BACKGROUND

The efficacy and clinical application of glucocorticoids (GCs) in patients with drug-induced liver injury (DILI) remain controversial.

AIMS

To determine the efficacy and suitable population of GCs in patients with DILI.

METHODS

This was a single-center, retrospective study. Patients with moderate-to-severe DILI who met the diagnostic criteria from January 1, 2009 to December 31, 2024 were enrolled. Patients in the GC group and the non-GC group were matched 1:1 by propensity score-matched (PSM), and the reduction of disease severity and biochemical parameters were compared between the two groups. According to the level of TB, the patients with DILI were divided into three groups, and the efficacy of GCs in each subgroup was compared.

RESULTS

Patients with DILI in our study were evaluated by the updated RUCAM causality assessment scale. All patients had RUCAM scores≥6 and causal relationship graded as " probable" or " highly probable". The use of GC treatment differs according to the severity of patients, especially the baseline level of TB (% in patients with TB <5 ULN, % in patients with 5ULN≤TB≤10ULN, and % in TB≥10ULN). After PSM analysis, 163 patients were included in each group. After PSM, the time of severity reduction was faster in the GC group than the non-GC group (P=0.022). The adjusted cumulative rate of severity reduction was 62% in the GC group and 43.6% in the non-GC group. The cumulative rates of reaching 50% reduction in AST, ALP, TB level was higher in the GC group than in the non-GC group (P<0.001, P=0.0086 and P=0.003). Patients were divided into three subgroups according to baseline TB level. We found the cumulative rates of who achieved severity reduction and 50% reduction in liver biochemical parameters at discharge was higher in the GC group than in the non-GC group in patients with 5ULN≤ TB level ≤10ULN but not in patients with TB <5ULN and TB>10ULN. Multivariate analysis showed that sex, age, treatment group and severity were significantly associated with disease severity reduction of patients with DILI. After PSM, there were 56 patients with drug-induced autoimmune hepatitis (DI-AIH) and 270 patients with DILI with no autoimmune features cases in our cohort. The cumulative rate of severity reduction at discharge in the GC group was higher than that in the non-GC group in patients with DI-AIH (P=0.049). Although the incidence of side effects in the GC group was higher than that in the non-GC group, the adverse reactions were basically relieved with the withdrawal of GCs.

CONCLUSIONS

GCs accelerated the reduction of disease severity and liver biochemical parameters, especially in patients with 5ULN≤baseline TB level≤10ULN. Sex, age, treatment group and severity were significantly associated with disease severity reduction of patients with DILI.

AI model using CT-based imaging biomarkers to predict hepatocellular carcinoma in patients with chronic hepatitis B

BACKGROUND & AIMS

Various hepatocellular carcinoma (HCC) prediction models have been proposed for patients with chronic hepatitis B (CHB) using clinical variables. We aimed to develop an artificial intelligence (AI)-based HCC prediction model by incorporating imaging biomarkers derived from abdominal computed tomography (CT) images along with clinical variables.

METHODS

An AI prediction model employing a gradient-boosting machine algorithm was developed utilizing imaging biomarkers extracted by DeepFore, a deep learning-based CT auto-segmentation software. The derivation cohort (n = 5,585) was randomly divided into the training and internal validation sets at a 3:1 ratio. The external validation cohort included 2,883 patients. Six imaging biomarkers (i.e. abdominal visceral fat-total fat volume ratio, total fat-trunk volume ratio, spleen volume, liver volume, liver-spleen Hounsfield unit ratio, and muscle Hounsfield unit) and eight clinical variables were selected as the main variables of our model, PLAN-B-DF.

RESULTS

In the internal validation set (median follow-up duration = 7.4 years), PLAN-B-DF demonstrated an excellent predictive performance with a c-index of 0.91 and good calibration function (p = 0.78 by the Hosmer-Lemeshow test). In the external validation cohort (median follow-up duration = 4.6 years), PLAN-B-DF showed a significantly better discrimination function compared to previous models, including PLAN-B, PAGE-B, modified PAGE-B, and CU-HCC (c-index, 0.89 vs. 0.65-0.78; all p <0.001), and maintained a good calibration function (p = 0.42 by the Hosmer-Lemeshow test). When patients were classified into four groups according to the risk probability calculated by PLAN-B-DF, the 10-year cumulative HCC incidence was 0.0%, 0.4%, 16.0%, and 46.2% in the minimal-, low-, intermediate-, and high-risk groups, respectively.

CONCLUSION

This AI prediction model, integrating deep learning-based auto-segmentation of CT images, offers improved performance in predicting HCC risk among patients with CHB compared to previous models.

IMPACT AND IMPLICATIONS

The novel predictive model PLAN-B-DF, employing an automated computed tomography segmentation algorithm, significantly improves predictive accuracy and risk stratification for hepatocellular carcinoma in patients with chronic hepatitis B (CHB). Using a gradient-boosting algorithm and computed tomography metrics, such as visceral fat volume and myosteatosis, PLAN-B-DF outperforms previous models based solely on clinical and demographic data. This model not only shows a higher c-index compared to previous models, but also effectively classifies patients with CHB into different risk groups. This model uses machine learning to analyze the complex relationships among various risk factors contributing to hepatocellular carcinoma occurrence, thereby enabling more personalized surveillance for patients with CHB.

Differential HBV RNA and HBcrAg patterns in untreated patients with chronic hepatitis delta

BACKGROUND & AIMS

Serum HBV RNA and hepatitis B core-related antigen (HBcrAg) levels have been proposed as useful biomarkers in the management of patients with HBV; however, their role in chronic hepatitis delta (CHD) is currently unknown.

METHODS

Consecutive untreated patients with CHD were enrolled in a cross-sectional study in three EU centers. Clinical and virological characteristics were collected. Serum HBV RNA and HBcrAg levels were quantified by an automated real-time investigational assay (Cobas® 6800, Roche Diagnostics, Pleasanton, Ca, USA) and by LUMIPULSE® G HBcrAg assay (Fujirebio Europe), respectively. In 18 patients with available liver biopsies, intrahepatic analyses were performed.

RESULTS

Overall, 240 patients with HDV were enrolled: median age 46 years, 62% male, 53% with cirrhosis, 57% nucleos(t)ide analogue treated, median ALT 70 U/L, median HBsAg 3.8 log10 IU/ml, 88% HBeAg negative, and median HDV RNA 4.9 log10 IU/ml. HBV RNA was positive (>10 copies/ml) in only 8% of patients (median 40 [13-82,000] copies/ml), whereas HBcrAg was ≥3 log10 U/ml in 77% (median 4.2 [3.0-8.0] log10 U/ml). By combining these biomarkers, three categories were identified: 23% double negative (HBV RNA/HBcrAg), 9% double positive (HBV RNA/HBcrAg) and 68% HBV RNA negative/HBcrAg positive. HBV RNA levels positively correlated with male sex and detectable HBV DNA, while positive HBcrAg correlated with higher HBsAg levels. Double-positive patients were younger, non-European, with elevated ALT and HDV RNA levels and detectable HBV DNA. Intrahepatic HDV RNA and HBV RNA were positive in most samples, while intrahepatic levels of covalently closed circular DNA were low.

CONCLUSIONS

In untreated CHD, most patients had undetectable HBV RNA but quantifiable HBcrAg ("divergent pattern") in the absence of HBeAg. Additional studies aiming to unravel the molecular mechanisms underlying these findings are warranted.

IMPACT AND IMPLICATIONS

Serum HBV RNA and HBcrAg (hepatitis B core-related antigen) are promising biomarkers of the transcriptional activity of covalently closed circular DNA in chronic HBV infection; however, their role in patients with HBV-HDV coinfection is unknown. At variance with what is commonly observed in HBV-monoinfected patients, HBV RNA was undetectable and HBcrAg detectable in the serum of most patients with HDV ("divergent pattern"). The understanding of the viral interplay between HBV and HDV is crucial to dissect the pathogenic mechanisms associated with the distinct phenotypes of patients with HDV.

Impaired mitochondrial degradation of CHCHD2 promotes metabolic dysfunction-associated steatohepatitis-related hepatocellular carcinoma by upregulating VEGFA

Metabolic dysfunction-associated steatohepatitis (MASH) is the fastest-growing cause of liver cancer. The liver microenvironment of patients with MASH supports the development of hepatocellular carcinoma (HCC). Coiled-coil-helix-coiled-coil-helix domain-containing 2 (CHCHD2), which is located in both the mitochondria and nucleus, is increased in MASH liver. Its role in the development of MASH-HCC remain unknown. In this study, we found CHCHD2 protein levels were elevated in both tumor and para-tumor tissues of patients with MASH-HCC and diethylnitrosamine- and high-fat diet-induced MASH-HCC mice. Chchd2-knockout mice were generated. CHCHD2 was overexpressed in hepatocytes using AAV with TBG promoter. Chchd2 knockout inhibited the progression of MASH-HCC in mice. CHCHD2 protein-targeted ChIP-sequencing data revealed that CHCHD2 target genes encoding secretory proteins were enriched in cancer pathways. Among these genes, vascular endothelial growth factor A (VEGFA) level increased in CHCHD2-overexpressing livers and hepatocytes. Chchd2 knockdown reduced palmitate-induced VEGFA expression. Palmitate-treated hepatocyte increased the angiogenic activity of endothelial cells in a paracrine manner, and this was suppressed by Chchd2 knockdown in hepatocytes. CHCHD2-overexpressing hepatocytes promoted the angiogenic activity of endothelial cells. We futher employed an orthotopic murine model of HCC to demonstrate that elevated CHCHD2 protein levels in para-tumor tissues support HCC growth. In addition, we found that the degradation of CHCHD2 was primarily mediated by mitochondrial protease ClpXP, which was repressed in the MASH liver. In conclusion, the mitochondrial degradation of CHCHD2 is impaired in MASH, and elevated CHCHD2 levels in hepatocytes promote VEGFA transcription and support the growth of HCC.

The role of cyclic adenosine monophosphate (cAMP) in pathophysiology of fibrosis

Fibrosis, the excessive production and disorganised deposition of extracellular matrix proteins, can occur in any organ system, disrupting functionality and causing fatality. The number, efficacy and safety of antifibrotic drugs are incredibly limited. Therapeutics which elevate intracellular cyclic adenosine monophosphate (cAMP) offer a potential solution. In this review, we present the signalling mechanisms involved in fibrosis pathophysiology, how cAMP and its effectors might interact with these pathways, and the current preclinical and clinical efforts in this field. cAMP elevating agents have the potential to be future antifibrotic drug candidates, but further studies are required, particularly to develop tissue specific therapeutics.

Integration of bioinformatics and identification of the role of m6A genes in NAFLD

Non-alcoholic fatty liver disease (NAFLD) is prevalent worldwide and seriously affects health. M6A methylation is crucial in its pathogenesis. In this study, a thorough analysis of three gene expression datasets identified nine key differentially expressed genes DEGs associated with m6A methylation in NAFLD that are involved in important biological processes. Subsequently, functional enrichment analysis, weighted gene co-expression network analysis (WGCNA), gene set variation analysis (GSVA) and immune infiltration analysis were conducted to explore the molecular mechanism and gene expression patterns. The LASSO risk model contains a total of 5 m6A-related differentially expressed genes (m6A-RDEGs)(RBM15, IGF2BP2, EIF3B, YTHDC1, WTAP), and the diagnostic model based on these key genes has high accuracy. Among them, YTHDC1 and WTAP are used as prominent biomarkers. In addition, an interaction network between mRNA and miRNA, RNA-binding protein (RBP), transcription factor (TF) and drugs is also constructed. Finally, the animal model of NAFLD was successfully established and validated by RT-qPCR and western blot. This study provides a valuable tool for clinical diagnosis and drives the progress of NAFLD research.

Lenvatinib Is Highly Effective in Patients with Hepatocellular Carcinoma Related to Both Metabolic Dysfunction-Associated Steatohepatitis and Alcoholic Etiology: A Propensity Score Analysis

Background and aims: Metabolic dysfunction-associated steatotic liver disease (MASLD)-related hepatocellular carcinoma (HCC) may have distinct biological characteristics influencing systemic treatment response. However, the prognostic impact of MASLD vs. alcohol-related HCC in patients receiving lenvatinib remains unclear. This study aimed to assess lenvatinib's effectiveness and safety in these populations. Methods: A multicenter cohort of 378 HCC patients treated with lenvatinib (2019-2024) was analyzed. Propensity score matching was performed based on age, sex, tumoral stage, alpha-fetoprotein levels and Child-Pugh class. Survival was estimated using Kaplan-Meier analysis and compared with the log-rank test. Results were expressed as HR and 95% CI. Results: After matching, 115 patients per group were compared. Median OS was 21 months (95% CI: 20-23) in the group with metabolic dysfunction-associated steatohepatitis (MASH) and 19 months (95% CI: 18-21) in the group with alcohol etiology (p = 0.18). In multivariate analysis, only Child-Pugh class (HR 2.67, 95% CI: 1.84-5.41) and tumor stage (HR 2.18, 95% CI: 1.57-6.93) resulted as significant predictors of OS. Median PFS was 9 months (95% CI: 8-9) in patients with MASH and 9 months (95% CI: 7-10) in patients with alcohol etiology (p = 0.33). Only the Child-Pugh class was a significant predictor of PFS in univariate analysis (HR 1.56, 95% CI: 1.15-3.41; p = 0.03). No difference in terms of adverse event rate was observed between the two groups. Conclusions: Lenvatinib is effective in patients with both MASH- and alcohol-related HCC, with no difference in oncological outcomes between the two groups.

What determines survival in autoimmune liver disease overlap syndromes: A critical commentary

Recently, Jayabalan et al published an important study. The authors defined the liver outcome score as a novel biomarker for predicting liver-related mortality in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome. After thoroughly reviewing their work, we offer insights that primarily relate to their study design to enhance the medical community’s understanding of this complex disease.

Dietary Supplementation of Lactobacillus reuteri Modulates Amino Acid Metabolism and Extracellular Matrix in the Gut-Liver Axis of Weaned Piglets

Weaning stress leads to intestinal dysfunction and impaired growth performance and intestinal development in piglets. This study aims to investigate the effects of Lactobacillus reuteri LR1 on growth performance and amino acid metabolism in the gut-liver axis of weaned piglets. A total of 48 weaned piglets (Duroc × Landrace × Yorkshire, 21 days old) were randomly assigned to the CON group (fed a basal diet) and the LR1 group (fed the basal diet supplemented with 5 × 1010 CFU/kg of Lactobacillus reuteri LR1) with six pens per group and 4 piglets each pen. The results demonstrated that LR1 significantly increased average daily gain (ADG), average daily feed intake (ADFI), and final body weight (p < 0.05). Additionally, LR1 significantly enhanced the villus height of the ileum (p < 0.05) and upregulated the expression of SLC6A19 in the jejunum, as well as SLC6A19, SLC7A1, and SLC38A9 in the ileum (p < 0.05). Amino acid analysis revealed that LR1 elevated the serum concentrations of glycine and hydroxyproline, along with increased taurine in the liver. Masson staining indicated LR1 reduced ileum fiber deposition, with COL3A1 identified as a key component. Furthermore, untargeted metabolomic analysis identified 27 amino acid-related differential metabolites and 11 significantly up-regulated in the plasma of the hepatic portal vein, including L-asparagine, L-citrulline, His-Cys, N-acetyltryptophan, 4-hydroxy-l-isoleucine, Gly-Arg, creatine, ornithine, ectoine, 3-methyl-l-histidine, and stachydrine. Correlation analysis suggested that COL1A2 and COL3A1 were closely associated with these metabolic changes. Overall, these findings suggest that LR1 supplementation promotes growth, improves intestinal morphology, reduces fiber deposition, and enhances amino acid metabolism in the gut-liver axis of weaned piglets.

Infection risk and management in patients with cirrhosis: A critical overview

In this paper, we analyze the article published by El Labban et al, which explores the impact of cirrhosis on patients with necrotizing fasciitis. The authors conclude that cirrhosis is a significant risk factor for increased in-hospital morbidity and mortality in this patient population. Building upon their final observation regarding the importance of understanding this association, we will delve into the topic of infections in patients with liver cirrhosis. These patients exhibit intrinsic characteristics that make them particularly susceptible to infections, both bacterial and fungal. This heightened risk not only increases the likelihood of severe infections but also makes them a common trigger for acute decompensations, including the development of acute-on-chronic liver failure, which markedly worsens prognosis and mortality. Infections in patients with cirrhosis often require a more aggressive and rapid diagnostic and therapeutic approach due to the higher risk of nosocomial infections, multidrug-resistant organisms, and atypical clinical presentations. Delayed or inadequate management can lead to unfavorable outcomes, further complicating the course of their underlying liver disease. The aim of this article is to emphasize the importance of early and appropriate management in patients with cirrhosis with infections. Evidence supports that timely and tailored interventions not only improve clinical outcomes but also reduce mortality. By raising awareness among clinicians about the complexity of these cases, we hope to contribute to optimizing the care of this high-risk population.

Open questions on how metabolic dysfunction-associated steatotic liver disease shapes the course of drug-induced liver injury

In this article, we discuss the article recently published by Zhao et al. This study focused on the intersection of metabolic dysfunction-associated steatotic liver disease (MASLD) and drug-induced liver injury (DILI), two major contributors to the global burden of liver disease. By analyzing clinical characteristics, metabolic parameters, immune profiles, and liver pathology, Zhao et al comprehensively explored how MASLD influences the presentation, severity, and prognosis of DILI. Additionally, this study underscores the importance of structured diagnostic tools, such as the Roussel Uclaf Causality Assessment Method, to accurately assess the causality of DILI within the MASLD population. Although this study provides valuable insights, limitations such as its retrospective design and cohort heterogeneity underscore the need for future prospective research to refine diagnostic approaches and therapeutic strategies.

CD45+ erythroid progenitor cells as potential biomarkers for disease progression in hepatitis B virus-related acute-on-chronic liver failure

BACKGROUND

Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is characterized by immune dysregulation and systemic inflammation, which lead to high mortality. Although immunosuppressive CD45+ erythroid progenitor cells (EPCs) percentages are elevated in chronic hepatitis B (CHB) and are associated with disease progression, their role in HBV-ACLF remains unclear. This study aims to evaluate the impact of CD45+ EPCs on disease progression in patients with HBV-ACLF.

METHODS

In this retrospective study, we analyzed the data of 102 patients with CHB and 65 patients with HBV-ACLF receiving standard drugs treatment from the Third Affiliated Hospital of Sun Yat-sen University between January 2021 and December 2023. HBV-ACLF diagnosis followed the Chinese Group on the Study of Severe Hepatitis B-Acute-on-Chronic Liver Failure criteria, with strict exclusion of comorbidities. Peripheral blood mononuclear cells (PBMCs) were isolated via density gradient centrifugation, and CD45+ EPCs (CD45+ CD71+ CD235a+) were quantified using flow cytometry. Liver tissue EPCs were assessed by immunofluorescence in biopsy/transplant specimens. Receiver operating characteristic (ROC) and multivariable logistic regression analyses identified prognostic factors associated with disease progression.

RESULTS

Our findings revealed that patients with HBV-ACLF had significantly elevated percentages of CD45+ EPCs compared with those with CHB. We also observed strong correlations between CD45+ EPC percentages and creatinine concentration, leukocyte count, and neutrophil-to-lymphocyte ratio (NLR). The area under the ROC curve for CD45+ EPCs was 0.718, indicating a significant predictive value [95% confidence interval (CI): 0.586-0.851, p = 0.004]. High CD45+ EPC percentage was associated with a greater incidence of hepatic encephalopathy (30.8% vs. 10.3%, p = 0.037) and higher rates of disease progression (73.1% vs. 35.9%, p = 0.003). Multivariate logistic regression analysis identified international normalized ratio (INR) and NLR as independent predictors of poor 28-day outcomes (INR odds ratio [OR] = 6.098, p < 0.001; NLR OR = 1.354, p = 0.005).

CONCLUSIONS

The percentage of CD45+ EPCs in PBMCs may be a potential biomarker for predicting 28-day disease progression in patients with HBV-ACLF. These findings highlight their possible clinical utility for risk stratification.

Mechanism-guided drug development and treatment for liver fibrosis: a clinical perspective

Liver fibrosis is a common response to chronic liver injury due to multiple etiologies and plays a crucial in the progression of chronic liver disease to cirrhosis, hepatocellular carcinoma, and other liver-related clinical outcomes. Currently, available treatments to block liver fibrosis are designed to eliminate the underlying causes of liver disease. The lack of truly effective drugs to regress or reverse fibrosis is a major unmet clinical need. In this context, this article briefly describes the pathological process of hepatic fibrosis and focuses on reviewing the progress of clinical studies on mechanism-based anti-fibrotic drug development and therapy, highlighting that the positive effect of thyroid hormone receptor-β (THR-β) analogs, fibroblast growth factor 21 (FGF21) analogues, Glucagon-like peptide 1 receptor (GLP-1R) agonists, pan-peroxisome proliferator-activated receptor (pan-PPAR) agonists, fatty acid synthase (FASN) inhibitors, and hydronidone in reducing liver fibrosis caused by specific etiologies. Moreover, multi-pathway guided combination therapy or traditional Chinese medicine demonstrate significant advantages in combating liver fibrosis. Finally, new technologies and approaches affecting the clinical development of anti-hepatic fibrosis drugs were discussed.

A novel prognostic model based on portal vein diameter for patients with acute-on-chronic liver failure

The prompt and accurate prognostication of acute-on-chronic liver failure (ACLF) patients is crucial for clinical intervention and reducing mortality. This study aimed to develop a novel prognostic model based on pathological changes, with a specific focus on portal vein which is correlated with hepatic pathology. A cohort of 127 ACLF patients was enrolled to develop the prognostic model for 90-day mortality, which was validated in a prospective cohort of 105 ACLF patients. Demographic characteristics, laboratory indicators, and imaging factor portal vein diameter (PVD) were screened, and a nomogram prognostic model was developed using logistic regression. Patients with PVD ≥ 13.4 mm had significantly higher mortality (P = 0.047). PVD, age, neutrophil percentage, sex and total bilirubin were identified as independent predictors for the new PVD-based nomogram prognostic model, PANST. The C-index (0.878) of PANST score was higher than Chronic Liver Failure-Consortium-ACLF (CLIF-C ACLF), end-stage liver disease (MELD) and Child-Turcotte-Pugh (CTP) scores (0.691, 0.687, 0.639, respectively; P < 0.001). The ROC and decision curves demonstrated that the PANST score was superior to CLIF-C ACLF, MELD and CTP scores. Furthermore, after subgroup analysis, the C-indices of PANST score for hepatitis B virus-related ACLF (HBV-ACLF) and non-HBV-ACLF patients (0.842,0.950) were significantly higher than those of CLIF-C ACLF score (0.772, 0.750; P < 0.05), MELD score (0.730, 0.608; all P < 0.05) and CTP score (0.701,0.513; all P < 0.05). These results were confirmed in the validation cohort. PVD was an independent predictor, and the PANST score, a novel prognostic model based on PVD can accurately predict 90-day mortality in ACLF patients.

Association between Triglyceride-Glucose index and onset of type 2 diabetes in metabolic Dysfunction-Associated steatotic liver disease population

Previous studies have demonstrated a strong correlation between the Triglyceride-Glucose Index(TyG) index and diabetes mellitus; however, limited research has focused on the relationship between the TyG index and the incidence of diabetes mellitus in the Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) population. This study aims to investigate the association between the TyG index and the occurrence of diabetes mellitus in the MASLD population in Japan. This retrospective cohort study included 2,741 patients with MASLD from Murakami Memorial Hospital in Japan, spanning the years 2004 to 2015. The primary method employed to investigate the relationship between the TyG index and the occurrence of diabetes was Cox proportional hazards regression. Additionally, a Generalized Additive Model and a two-piecewise linear regression model were utilized to assess whether a linear relationship exists between the TyG index and the development of diabetes, as well as to calculate threshold effects. After adjusting for variables that may potentially influence the occurrence of diabetes, we found that the TyG index was positively correlated with diabetes incidence (HR = 1.43, 95% CI: 1.03, 1.98) in MASLD population overall. Further in-depth analysis revealed a nonlinear relationship between the TyG index and the occurrence of diabetes. When the TyG index was less than 7.95, it exhibited a negative correlation (HR = 0.22, 95% CI: 0.07, 0.66); however, when the TyG index exceeded 7.95, it showed a positive correlation (HR = 1.68, 95% CI: 1.20, 2.36). Additionally, we conducted a subject working curve analysis on the TyG index and the two components used to calculate it, fasting blood glucose and triglycerides, and found that the TyG index demonstrated higher sensitivity and specificity in predicting the occurrence of diabetes in the MASLD population. TyG index exhibits a nonlinear relationship with the incidence of diabetes in the MASLD population, and its sensitivity and specificity are superior to those of fasting blood glucose and triglycerides.

The Role of Extracellular Vesicles in the Pathogenesis of Metabolic Dysfunction-Associated Steatotic Liver Disease and Other Liver Diseases

The increasing prevalence of liver diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD), presents considerable medical challenges, particularly given the absence of approved pharmacological treatments, which underscores the necessity to comprehend its underlying mechanisms. Extracellular vesicles (EVs), which are tiny particles released by cells, play a crucial role in facilitating communication and can transport harmful molecules that promote inflammation and tissue damage. These EVs are involved in the progression of various types of liver disorders since they aggravate inflammation and oxidative stress. Because of their critical role, it is believed that EVs are widely involved in the initiation and progression of MASLD, as well as in viral hepatitis, alcoholic liver disease, drug-induced liver injury, and hepatocellular carcinoma. This review emphasizes recent findings regarding the functions of EVs in the above liver pathologies and underscores their potential as new therapeutic targets, paving the way for innovative approaches to address those detrimental liver conditions.

Immunological mechanisms and emerging therapeutic targets in alcohol-associated liver disease

Alcohol-associated liver disease (ALD) is a major global health challenge, with inflammation playing a central role in its progression. As inflammation emerges as a critical therapeutic target, ongoing research aims to unravel its underlying mechanisms. This review explores the immunological pathways of ALD, highlighting the roles of immune cells and their inflammatory mediators in disease onset and progression. We also examine the complex interactions between inflammatory cells and non-parenchymal liver cells, as well as their crosstalk with extra-hepatic organs, including the gut, adipose tissue, and nervous system. Furthermore, we summarize current clinical research on anti-inflammatory therapies and discuss promising therapeutic targets. Given the heterogeneity of ALD-associated inflammation, we emphasize the need for precision medicine to optimize treatment strategies and improve patient outcomes.

Developing and validating a predictive model for all-cause mortality in patients with metabolic dysfunction-associated steatotic liver disease

OBJECTIVE

This study aimed to construct a scientific, accurate, and readily applicable clinical all-cause mortality prediction model for patients with metabolic dysfunction-associated steatotic liver disease (MASLD) to enhance the efficiency of disease management and improve patient prognosis.

METHODS

This study was a retrospective cohort study based on the National Health and Nutrition Examination Survey database. The 17,861 participants diagnosed with MASLD were randomly assigned to either a training cohort (n = 12,503) or a validation cohort (n = 5358). Potential predictors were subjected to LASSO regression analysis, and independent risk factors were subsequently identified through multivariate Cox regression analysis. An all-cause mortality prediction model was constructed based on the significant predictors, and a nomogram was generated to illustrate the survival probability of patients at various time points. The model's performance was evaluated using receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) curves.

RESULTS

A multiple Cox regression analysis identified several independent predictors significantly influencing all-cause mortality in patients with MASLD. These included gender, age, smoking status, hypertension, red blood cell count, albumin, glutamyl transpeptidase, glycosylated hemoglobin, and creatinine. The constructed predictive model demonstrated high accuracy in the training and validation cohorts, with AUC values approaching 0.85 at 3, 5, and 10 years, respectively. Calibration and DCA curves were employed to verify the stability and generalizability of the model.

CONCLUSIONS

We successfully constructed and validated an all-cause mortality prediction model for MASLD patients. This model provides a powerful tool for clinical risk assessment and treatment decision-making.

Microbiome and fragmentation pattern of blood cell-free DNA and fecal metagenome enhance colorectal cancer micro-dysbiosis and diagnosis analysis: a proof-of-concept study

Colorectal cancer (CRC) is the third most common cancer, and it can be prevented by performing early screening. As a hallmark of cancer, the human microbiome plays important roles in the occurrence and development of CRC. Recently, the blood microbiome has been proposed as an effective diagnostic tool for various diseases, yet its performance on CRC deserves further exploration. In this study, 133 human feces and 120 blood samples are collected, including healthy individuals, adenoma patients, and CRC patients. The blood cfDNA and fecal genome are subjected to shotgun metagenome sequencing. After removing human sequences, the microbial sequences in blood are analyzed. Based on the differential microbes and functions, random forest (RF) models are constructed for adenoma and CRC diagnosis. The results show that alterations of blood microbial signatures can be captured under low coverage (even at 3×). RF diagnostic models based on blood microbial markers achieve high area under the curve (AUC) values for adenoma patients (0.8849) and CRC patients (0.9824). When the fragmentation pattern is combined with microbial and KEGG markers, higher AUC values are obtained. Furthermore, compared to the blood microbiome, the fecal microbiome shows a different community composition, whereas their changes in KEGG pathways are similar. Pathogenic bacteria Fusobacterium nucleatum (F. nucleatum) in feces increased gradually from the healthy group to the adenoma and CRC groups. Additionally, F. nucleatum in feces and blood shows a positive correlation in CRC patients. Cumulatively, the integration of blood microbiome and fragmentation pattern is promising for CRC diagnosis.IMPORTANCEThe cell-free DNA of the human microbiome can enter the blood and can be used for cancer diagnosis, whereas its diagnostic potential in colorectal cancer and association with gut microbiome has not been explored. The microbial sequences in blood account for less than 1% of the total sequences. The blood microbial composition, KEGG functions, and fragmentation pattern are different among healthy individuals, adenoma patients, and CRC patients. Machine learning models based on these differential characteristics achieve high diagnostic accuracy, especially when they are integrated with fragmentation patterns. The great difference between fecal and blood microbiomes indicates that microbial sequences in blood may originate from various organs. Therefore, this study provides new insights into the community composition and functions of the blood microbiome of CRC and proposes an effective non-invasive diagnostic tool.

Long-Term Dynamic Changes of Alanine Aminotransferase Levels Are Associated With Liver-Related Events in Nucleos(t)ide Analogue-Treated Chronic Hepatitis B Patients in China

BACKGROUND

The role of alanine aminotransferase (ALT) dynamics during nucleos(t)ide analogue (NA) therapy in chronic hepatitis B (CHB) is unclear. We aimed to evaluate the correlation between ALT dynamics and liver-related events (LRE), and explore the optimal threshold of ALT during NA treatment.

METHODS

We enrolled 18,129 NA-treated patients, comprising 3104 patients from the Search-B study (NCT02167503) and 15,025 patients from a real-world cohort in Hong Kong. Latent-class mixed model (LCMM) was adopted to identify trajectory patterns of ALT during treatment. ALT value at the 95th percentile of the trajectory group with the lowest LRE risk was obtained as the optimal threshold.

RESULTS

During a median follow-up of 53.3 months, 1164 patients developed LRE with a 7-year cumulative incidence of 9.9%. In the Search-B cohort, LCMM recognised 3 trajectory groups with progressively increasing ALT levels, which were positively associated with LRE risk. Subsequently, the optimal thresholds for ALT were obtained as 23 U/L for men and 16 U/L for women. The 7-year cumulative incidence of LRE was 5.5% for ALT ≤ 23 or 16 U/L, significantly lower than that for ALT > 23 or 16 U/L but ≤ 40 U/L (10.8%; aHR = 2.0, p < 0.001), and ALT > 40 U/L (15.1%; aHR = 3.4, p < 0.001). Similarly, in the Hong Kong cohort, ALT > 23 or 16 U/L but < 40 U/L and ALT > 40 U/L also increased the LRE risk, with aHRs of 2.0 (p = 0.003) and 6.1 (p < 0.001), respectively.

CONCLUSION

On-treatment ALT levels were significantly correlated with the prognosis of CHB. ALT ≤ 23 U/L for men and ≤ 16 U/L for women were identified as the optimal thresholds during NA treatment, suggesting that CHB patients should strive for a lower ALT level beyond the traditional normal range.

Piezo1 deficiency alleviates acute liver failure by inhibiting CpG-ODN induced inflammatory responses

Macrophages play a critical role in the progression of acute liver failure (ALF), a life-threatening clinical syndrome characterized by the rapid onset of liver injury. Recent research suggests that mechanosensation signaling may be pivotal in modulating acute inflammation. However, its involvement in ALF pathogenesis remains poorly understood. In this study, we found that Piezo1 was highly expressed in liver macrophages during liver injury in both humans and mice. Mice with macrophage-specific Piezo1 depletion were resistant to CpG-ODN/D-GalN-induced ALF, whereas mice pretreated with Yoda1 showed increased susceptibility. Furthermore, Piezo1-deficient macrophages exhibited reduced secretion of inflammatory cytokines upon CpG-ODN stimulation in vitro, while Yoda1 treatment enhanced cytokine secretion. Mechanistically, Piezo1 activation promotes the phosphorylation of CaMKII, which further enhances CpG-ODN-induced NF-κB activation. Additionally, Piezo1 activation promotes the endosomal translocation of TLR9 through the cytoskeleton remodeling. These findings suggest that Piezo1-mediated mechanosensation contributes to the development of CpG-ODN/D-GalN-induced ALF and may serve as a potential therapeutic target.

Biomarker guided immunomodulatory precision medicine to improve prognostic, predictive and adaptive enrichment strategies in sepsis trials

INTRODUCTION

The aim of this review is to summarize the advances of the last 5 years in the field of biomarker-guided therapeutic approach in sepsis through prognostic, predictive, and adaptive enrichment strategies.

AREAS COVERED

A thorough search of the literature was done based on the existing biomarkers for which clinical trials of integration in the inclusion criteria are available. The authors reviewed the accessible completed and ongoing studies, which use IL-6, ferritin, IL-7, sTREM-1, IL-15, HLA-DR, DPP-3 and/or bioADM for diagnosis of sepsis or septic shock, prognosis of outcome of interest or/and personalized treatment tailored to each patient's endotype classification.

EXPERT OPINION

Inconclusive sepsis trial outcomes highlight the need for strategic protocol design, patient stratification, and biomarker-guided immunomodulatory therapies. Future advancements should focus on real-time biomarker monitoring, personalized treatment, and point-of-care diagnostics to optimize therapeutic efficacy and patient outcomes.

Causal relationship between metabolic dysfunction-associated fatty liver disease and endotoxin biomarkers: A Mendelian randomization study

Although the relationship among lipopolysaccharides (LPS), LPS-binding proteins, and metabolic dysfunction-associated fatty liver disease (MAFLD) is widely studied, no conclusive evidence is available. In this study, we used mendelian randomization (MR) to study the causal relationship of LPS, LPS-binding proteins, and MAFLD. Using bidirectional two-sample MR method, we evaluated data from the genome wide association study; for this analysis, nonalcoholic fatty liver disease (NAFLD), liver fat percentage, and other metabolic syndromes were employed as outcomes. Furthermore, MR analysis mainly involved the inverse variance weighted method. Heterogeneity and pleiotropy tests were also conducted. LPS was found to have a causal relationship with NAFLD, obesity, high density lipoprotein cholesterol, and TG levels. Furthermore, TG levels and LBP had significant causal relationships. This study mainly concluded that LPS is a risk factor for NAFLD, obesity, high density lipoprotein cholesterol, and TG, corroborating it's the LPS role in MAFLD pathogenesis. Hence, optimizing the gut microbiota using proper diet, probiotics, or fecal microbiota transplantation may help to reduce inflammation and (IR), thereby improving lipid and glucose metabolism disorders. Although a causal relationship between TG and LBP was observed, further studies are required to determine a specific mechanism.

Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES

BACKGROUND

The mortality burden of metabolic dysfunction-associated fatty liver disease (MAFLD) is rising, making it crucial to predict mortality and identify the factors influencing it. While advanced machine learning algorithms are gaining recognition as effective tools for clinical prediction, their ability to predict all-cause mortality of MAFLD individuals remains uncertain. This study aimed to develop different machine learning models to predict all-cause mortality of MAFLD individuals, compare the predictive performance of these models, and identify the risk factors contributing all-cause mortality, which is crucial for management of MAFLD individuals.

METHODS

We included 3921 MAFLD individuals in NHANES III. After a median follow-up time of 310 months, 1815 (46.3%) deaths were recorded. The data (demographic, behavioral factors and laboratory indicators) were utilized to construct machine learning models (Coxnet, RSF, GBS) after feature selection. Time-dependent AUC, time-dependent brier and C-index were then evaluated the performance of models. We identified the top five factors that contributed significantly to all-cause mortality and further explore the association with all-cause mortality using RCS and Kaplan-Meier survival curves.

RESULTS

Coxnet showed the best performance in short-term and long-term predictions with time-dependent AUC of 0.82 at 5 years and 0.88 at 25 years. Age, FORNS, waist circumstance, AAR, FLI were associated positively with all-cause mortality. Compared to the individuals who smoked more than 100 cigarettes, those below 100 had better survival outcome (P < 0.0001).

CONCLUSIONS

Machine learning has a promising application in predicting all-cause mortality in MAFLD individuals. Combined the results of interpretable machine learning and association analyses, we found risk factors which contributing to the all-cause mortality. These findings provide insights for community health practitioners to intervene in modifiable risk factors, thereby improving the survival and quality of life of MAFLD individuals.

Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation

BACKGROUND

Most forms of obesity are associated with chronic diseases that remain a global public health challenge.

AIMS

Despite significant advancements in understanding its pathophysiology, effective management of obesity is hindered by the persistence of knowledge gaps in epidemiology, phenotypic heterogeneity and policy implementation.

MATERIALS AND METHODS

This consensus statement by the European Society for Clinical Investigation identifies eight critical areas requiring urgent attention. Key gaps include insufficient long-term data on obesity trends, the inadequacy of body mass index (BMI) as a sole diagnostic measure, and insufficient recognition of phenotypic diversity in obesity-related cardiometabolic risks. Moreover, the socio-economic drivers of obesity and its transition across phenotypes remain poorly understood.

RESULTS

The syndemic nature of obesity, exacerbated by globalization and environmental changes, necessitates a holistic approach integrating global frameworks and community-level interventions. This statement advocates for leveraging emerging technologies, such as artificial intelligence, to refine predictive models and address phenotypic variability. It underscores the importance of collaborative efforts among scientists, policymakers, and stakeholders to create tailored interventions and enduring policies.

DISCUSSION

The consensus highlights the need for harmonizing anthropometric and biochemical markers, fostering inclusive public health narratives and combating stigma associated with obesity. By addressing these gaps, this initiative aims to advance research, improve prevention strategies and optimize care delivery for people living with obesity.

CONCLUSION

This collaborative effort marks a decisive step towards mitigating the obesity epidemic and its profound impact on global health systems. Ultimately, obesity should be considered as being largely the consequence of a socio-economic model not compatible with optimal human health.

Nonlinear association between AST/ALT ratio and 28-day all-cause mortality following ICU admission in critically ill cirrhotic patients: a retrospective cohort study

BACKGROUND

The AST/ALT ratio is a biochemical marker associated with poor clinical outcomes in various patients, but its role in severe cirrhosis is unclear. This study investigated the relationship between the AST/ALT ratio and mortality in the intensive care unit (ICU) patients with cirrhosis.

METHODS

This retrospective cohort study analyzed 2,090 liver cirrhosis patients from the MIMIC-IV database, focusing on their first ICU admission between 2008 and 2019. The AST/ALT ratio, measured within 24 h of admission, was the exposure variable, and the main outcome was 28-day mortality. A multivariable logistic regression model evaluated the link between the AST/ALT ratio and mortality. Nonlinear relationships were explored using smooth curve fitting and saturation effect analyses. Stratified analyses and interaction tests were also performed based on demographic and clinical characteristics.

RESULTS

The study involved 2,090 critically ill liver cirrhosis patients, averaging 59.1 years old, with 65% male and a 28-day post-ICU admission mortality rate of 29%. The AST/ALT ratio was linked to mortality risk (adjusted odds ratio (OR) 1.1, 95% confidence interval (CI) 1.0-1.2; p = 0.015), showing a nonlinear pattern with a critical point at 3.6. Below this, each unit increase raised mortality risk by 40% (adjusted OR 1.4, 95% CI 1.2-1.6, p < 0.001), but the effect plateaued beyond this level (adjusted OR 1.0, 95% CI 0.8-1.1, p = 0.600). Subgroup analyses confirmed the consistent association, with interaction P values over 0.05.

CONCLUSIONS

The AST/ALT ratio is an independent predictor of 28-day mortality in critically ill cirrhotic patients, with a nonlinear relationship (risk increases up to a ratio of ~ 3.6, then plateaus). This marker could enhance ICU risk stratification and inform clinical decision-making.

Synergistic Toxicity of Combined Exposure to Acrylamide and Polystyrene Nanoplastics on the Gut-Liver Axis in Mice

Acrylamide (AA) and nanoplastics (NPs) are common food toxicants. However, their combined toxicity and health risks call for further studies. This study aimed to investigate the combined toxicity of AA and polystyrene NPs (PS-NPs) in mice through drinking water exposure. Co-exposure to AA and PS-NPs aggravated colon and liver damage, including more severe inflammatory infiltration, higher levels of colonic and hepatic pro-inflammatory cytokines, and elevated serum content of lipopolysaccharide and activities of diamine oxidase, alanine aminotransferase, and aspartate aminotransferase compared to single exposures. Co-exposure also significantly downregulated the expression of colonic tight-junction genes ZO-1 and Claudin-5. Metabolomics revealed that co-exposure induced more profound metabolic disorders in the liver, particularly affecting amino acid and carbohydrate metabolism. 16S amplicon sequencing showed that co-exposure caused more drastic gut microbiota dysbiosis, characterized by a decrease in beneficial bacteria (unclassified_f__Oscillospiraceae, Roseburia, UCG-005, Ruminiclostridium, unclassified_o__Clostridia_UCG-014, Fournierella, and Acetatifactor) and an increase in pathogenic bacteria (Eubacterium_xylanophilum_group and Eubacterium_nodatum_group). Correlation analysis indicated a negative correlation between beneficial bacteria and intestinal-liver toxicity indicators and a positive correlation between pathogenic bacteria and these indicators. Overall, our findings showed that AA and PS-NPs exerted synergistic toxicity to the gut-liver axis in mammals, highlighting the higher health risks of their combined ingestion.

EASL Clinical Practice Guidelines on the management of hepatitis B virus infection

The updated EASL Clinical Practice Guidelines on the management of hepatitis B virus (HBV) infection provide comprehensive, evidence-based recommendations for its management. Spanning ten thematic sections, the guidelines address diagnostics, treatment goals, treatment indications, therapeutic options, hepatocellular carcinoma surveillance, management of special populations, HBV reactivation prophylaxis, post-transplant care, HBV prevention strategies, and finally address open questions and future research directions. Chronic HBV remains a global health challenge, with over 250 million individuals affected and significant mortality due to cirrhosis and hepatocellular carcinoma. These guidelines emphasise the importance of early diagnosis, risk stratification based on viral and host factors, and tailored antiviral therapy. Attention is given to simplified algorithms, vaccination, and screening to support global HBV elimination targets. The guidelines also discuss emerging biomarkers and evolving definitions of functional and partial cure. Developed through literature review, expert consensus, and a Delphi process, the guidelines aim to equip healthcare providers across disciplines with practical tools to optimise HBV care and outcomes worldwide.

Serum hepatitis B virus RNA in low-level viremia of chronic hepatitis B: clinical features and association with virological response

BACKGROUND

The role of hepatitis B virus (HBV) RNA in the management of patients with chronic hepatitis B (CHB) experienced with low-level viremia (LLV) remains poorly defined. This study was designed to evaluate the prognostic utility of serum HBV RNA as a biomarker for predicting treatment outcomes in this population.

METHODS

A retrospective cohort analysis was conducted on 117 pediatric patients with LLV (mean age: 13.14 years; 34% female) treated with continuous entecavir (ConT) or modified regimens (switching to or combining with tenofovir disoproxil fumarate) for ≥ 120 weeks. Virological response was defined as HBV DNA < 10 IU/mL at week 120.

RESULTS

No significant baseline differences existed between ConT and modified regimen groups. Compared to ConT, modified regimens achieved greater reductions in serum HBV DNA, HBV RNA, and quantitative HBsAg, with higher cumulative undetectable rates at week 120 (HBV DNA: ≥ 80.0%; HBV RNA: ≥ 54.8%; P < 0.05). Notably, qHBsAg levels remained elevated in most patients, with only 3 individuals achieving undetectable levels (< 0.05 IU/mL). Multivariate analysis identified higher HBV RNA levels at week 48 as an independent risk factor for non-virological response (adjusted odds ratio: 5.86; 95% confidence interval: 1.40-24.62; P = 0.016). Although HBV RNA alone was less predictive than HBV DNA (area under the receiver operating characteristic curve [AUC]: 0.76 vs. 0.80; P = 0.459), combining both markers improved prediction accuracy (AUC: 0.82; P < 0.05 vs. single markers).

CONCLUSIONS

In children with LLV, serum HBV RNA level is an independent risk factor for non-virological response and may serve as a complementary biomarker to HBV DNA for guiding antiviral therapy adjustments.

Reduction of Bacteroides fragilis in Gut Microbiome of Chronic Hepatitis B Patients Promotes Liver Injury

In chronic hepatitis B (CHB) patients under antiviral treatment, liver injury, as evidenced by elevated alanine transaminase (ALT), is associated with unfavorable outcomes and needs effective treatment. The interaction between gut microbiota and liver injury in CHB patients remains unclear. Using a case-control design, 28 cases with elevated ALT and 28 matched controls with normal ALT were randomly selected from CHB patients with viral control. Clinical characteristics were comparable between groups. Metagenomic sequencing revealed that Bacteroides fragilis was decreased in cases and exhibited the greatest disparity between cases and controls. Mice colonized by gut microbiota from cases exhibited more severe liver damage in both LPS-induced and MCD diet-induced liver injury models, and had a lower abundance of B. fragilis compared to mice colonized by gut microbiota from controls. Oral gavage of B. fragilis improved both LPS-induced and MCD diet-induced liver injury. Metabolomics analysis revealed that the levels of 7-Ketolithocholic acid (7-Keto-LCA) were positively correlated with B. fragilis and significantly increased in the cultural supernatant of B. fragilis. Consistently, 7-Keto-LCA exerted protective effects against both LPS-induced and MCD diet-induced liver damage. Targeting gut microbiota might be a promising therapeutic treatment for alleviation residual liver inflammation in CHB patients with viral control.

Blood markers for type-1, -2, and -3 inflammation are associated with severity of acutely decompensated cirrhosis

BACKGROUND & AIMS

In patients with acutely decompensated cirrhosis (ADC) who present with clinically apparent precipitants (i.e., infections, acute liver injury), alterations in blood markers of inflammation associate with progression toward severe phenotypes (e.g., acute-on-chronic liver failure [ACLF]). However, it is unclear whether alterations in blood inflammatory markers associate with progression of ADC independently of precipitants.

METHODS

We prospectively enrolled 394 patients admitted for ADC who were classified into four phenotypes of increasing severity: no organ dysfunction (n = 168), organ dysfunction alone (n = 72), organ failure without ACLF (n = 91), and ACLF (n = 63). Clinical blood cell counts and serum levels of inflammatory markers (including soluble markers related to type-1, type-2, and type-3 inflammation) were obtained at enrollment. Ordinal regression with adjacent categories logit model adjusted for confounders (including precipitants) was used to analyze associations between changes in each blood inflammatory marker and the worsening of ADC.

RESULTS

Inflammatory markers that were associated with a higher risk of progressing to the next more severe stage were as follows: increasing neutrophil counts (adjusted common odds ratio [cOR] 1.17, 95% CI 1.06-1.28); increasing levels of the type-2 cytokine interleukin (IL)-25 (cOR 1.21, 95% CI 1.06-1.39), type-3 cytokines IL-6 (cOR 1.15, 95% CI 1.02-1.28) and IL-22 (cOR 1.16, 95% CI 1.03-1.30), or anti-inflammatory soluble CD163 (cOR 1.94, 95% CI 1.58-2.38); decreasing lymphocyte counts (cOR 0.77, 95% CI 0.68-0.87); or decreasing levels of the type-1 cytokine IFN-γ (cOR 0.85, 95% CI 0.75-0.95).

CONCLUSIONS

Among patients with ADC, alterations in blood levels of cytokines related to type-1, type-2 and type-3 inflammation, together with neutrophilia, lymphopenia and elevated anti-inflammatory signals were individually associated with an increased risk of progressing toward ACLF, independently of the presence of clinically apparent precipitants.

IMPACT AND IMPLICATIONS

This study reveals that among patients with acutely decompensated cirrhosis, alterations in blood levels of cytokines related to type-1, type-2 and type-3 inflammation, together with neutrophilia, lymphopenia and elevated anti-inflammatory signals were individually associated with increased risk of progressing toward acute-on-chronic liver failure, independently of the presence of clinically apparent precipitants. These findings raise questions about the role of impaired barrier tissues and dysregulated production of blood immune cells in the pathophysiology of severe phenotypes of acutely decompensated cirrhosis, stimulating research to identify potential new biomarkers and targets for novel therapeutic approaches.

Recent prevalence and trends of obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) among US adolescents: 1999 to 2020

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is understudied among US adolescents despite rising obesity rates.

METHODS

This study analysed the prevalence and trends of obesity and MASLD among US adolescents aged 12-17 using data from the National Health and Nutrition Examination Survey (NHANES). We developed a new screening model utilizing FibroScan-measured controlled attenuation parameter (CAP) scores, body measurements and blood chemistry data from 2017 to 2020 to assist in analysing MASLD trends from 1999 to 2020.

RESULTS

Between 2017 and 2020, the prevalence of obesity and MASLD was approximately 20%, with about 70% of obese adolescents affected by MASLD. The condition was more common in boys, particularly among Mexican American adolescents. Additionally, 97.2% of those with NAFLD also had MASLD. Adolescents with MASLD had significantly higher body weight, waist circumference, triglyceride levels and alanine transaminase (ALT) levels, along with lower high-density lipoprotein (HDL) cholesterol and an increased risk of liver fibrosis. Insufficient physical activity and poor diet quality were key risk factors for developing MASLD. From 1999 to 2020, the prevalence of MASLD rose significantly, paralleling the increasing rates of obesity.

CONCLUSIONS

The study underscores the pressing need to screen at-risk adolescents for metabolic issues associated with steatotic liver diseases, given the rising obesity rates among adolescents. The high overlap between MASLD and NAFLD diagnoses indicates that the transition from NAFLD to MASLD can be effectively integrated into paediatric practice.

Real-World Trends and Future Projections of the Prevalence of Cirrhosis and Hepatic Encephalopathy Among Commercially and Medicare-Insured Adults in the United States

INTRODUCTION

Describing cirrhosis and hepatic encephalopathy (HE) burden over time can inform clinical management and resource allocation. Using healthcare claims data, this observational study examined recent trends in the prevalence of cirrhosis and HE and associated healthcare resource utilization among commercially and Medicare-insured adults in the United States.

METHODS

Data from the MarketScan Commercial Claims and Encounters Database and 100% Medicare Research Identifiable Files were analyzed (2007-2020). Annual prevalence of cirrhosis, HE, overt HE (OHE) hospitalizations, and rifaximin ± lactulose use, and costs per hospitalization per year were calculated. Average year-over-year changes in prevalence of cirrhosis, and HE were estimated. Trends were extrapolated to 2030 using ordinary least-squares regression.

RESULTS

From 2007 to 2020, the prevalence of cirrhosis increased by an average of 4.6% year-over-year in the Commercial population and 8.1% in the Medicare population; the prevalence of HE increased by 4.3% and 2.5%, respectively. Rates of OHE hospitalizations decreased from 27.5% to 5.5% (Commercial) and from 26.2% to 9.5% (Medicare), and rates of liver transplantation increased. Average payer costs (Commercial) and provider charges (Medicare) per OHE hospitalization increased (from $40,881 to $77,699 and from $45,913 to $74,894, respectively). Use of rifaximin ± lactulose showed an increasing trend during the observation period, whereas lactulose use declined steadily.

DISCUSSION

The healthcare burden of cirrhosis and HE in the United States is increasing. Trends are projected to continue unless action is taken, such as improving medication access and developing policies addressing the contributing factors.

Development and validation of a clinical risk score nomogram for predicting voriconazole trough concentration above 5 mg/L: a retrospective cohort study

The therapeutic range of voriconazole (VRC) is narrow, this study aimed to explore factors influencing VRC plasma concentrations > 5 mg/L and to construct a clinical risk score nomogram prediction model. Clinical data from 221 patients with VRC prophylaxis and treatment were retrospectively analyzed. The patients were randomly divided into a training cohort and a validation cohort at a 7:3 ratio. Univariate and binary logistic regression analysis was used to select independent risk factors for VRC plasma concentration above the high limit (5 mg/L). Four indicators including age, weight, CYP2C19 genotype, and albumin were selected to construct the nomogram prediction model. The area under the curve values of the training cohort and the validation cohort were 0.841 and 0.802, respectively. The decision curve analysis suggests that the nomogram model had good clinical applicability. In conclusion, the nomogram provides a reference for early screening and intervention in a high-risk population.

Role of liposomal amphotericin B in intensive care unit: an expert opinion paper

INTRODUCTION

Invasive fungal infections (IFI) are frequent in patients admitted to the intensive care unit (ICU). The use of first-line antifungals like triazoles or echinocandins may be limited by the global spread of multi-drug resistance species, drug-drug interactions, low organ penetration, and some safety concerns in case of multi-organ failure. Liposomal amphotericin B (L-AmB) is a polyene drug with a broad activity against mold and yeast and an acceptable safety profile. To outline the role of L-AmB in the treatment of IFI in critically ill patients, a panel of experts was invited to draw up an expert opinion paper on the appropriate place in therapy of L-AmB in different clinical scenarios of patients admitted to ICU.

METHODS

A multidisciplinary group of 16 specialists in infectious disease, microbiology, pharmacology, and intensive care elaborated an expert opinion document through a multi-step approach: (1) the scientific panel defined the items and wrote the statements on the management of IFI in ICU, (2) a survey was submitted to an external panel to express agreement or disagreement on the statements, and (3) the panel reviewed the survey and implemented the final document.

RESULTS

The final document included 35 statements that focused on epidemiology and microbiological rationale of the use of systemic L-AmB in critically ill patients and its potential role in specific clinical scenarios in the ICU.

CONCLUSION

Systemic L-AmB may represent an appropriate therapeutic choice for IFI in ICU patients with different underlying conditions, especially when the use of first-line agents is undermined. This expert opinion paper may provide a useful guide for clinicians.

Clinical significance of platelet-to-white blood cell ratio in patients with Wilson disease: a retrospective cohort study

Objective

To assess the correlation between the platelet-to-white blood cell ratio (PWR) and the severity of liver dysfunction, hepatic complications, and prognosis in Wilson disease (WD) patients.

Methods

A retrospective analysis was conducted on medical records from January 1, 2016, to March 30, 2022. Both univariate and multivariate analyses were performed to examine the impact of a low PWR (<26.3) on WD severity, liver complications, and disease progression. Additionally, the effect of splenectomy on PWR was evaluated.

Results

The study included 315 patients with WD, among whom 105 had a low PWR and 210 had a high PWR. Those with low PWR exhibited significantly elevated levels of bilirubin, international normalized ratio, prothrombin time, procollagen type-III N-terminal propeptide, type IV collagen, hyaluronic acid, and portal vein diameter. Conversely, they had lower levels of albumin, total cholesterol, low-density lipoprotein cholesterol, and triglycerides (all P < 0.05). A low PWR correlated with a greater incidence of splenomegaly/hypersplenism, esophagogastric varices, and ascites (all P < 0.05). Furthermore, low PWR independently predicted hepatic decompensation (P < 0.05), and splenectomy led to a marked increase in PWR among WD patients (P < 0.001).

Conclusion

A low PWR in WD patients is linked to heightened disease severity, increased risk of liver complications, and rapid progression to decompensation. The results imply that splenectomy, by enhancing PWR, may serve as a viable strategy to slow WD progression.

Association between cardiometabolic index and infertility among American women aged 20-45 years: a cross-sectional analysis from 2013-2020 NHANES data

BACKGROUND

While metabolic syndrome and obesity are established risk factors for infertility, previous studies have neglected age-specific analyses and nonlinear associations, particularly in women aged 20-45 years, a critical demographic for fertility and metabolic health. Therefore, this study aimed to examine the nonlinear relationship between Cardiometabolic Index(CMI) and infertility risk in US women of reproductive age (20-45 years) using nationally representative the National Health and Nutrition Examination Survey(NHANES) data (2013-2020).

METHODS

Cross-sectional data from the 2013-2020 NHANES were used to analyse 3,613 women aged 20-45 years with complete CMI and infertility data. Infertility is defined as the inability to conceive after at least 12 months of regular unprotected intercourse.The CMI was calculated using waist circumference(WC), height, triglyceride(TG), and high-density lipoprotein cholesterol (HDL-C). Multivariate logistic regression analysis, supplemented by smooth curve fitting and threshold effect analysis, was used to assess the association between CMI and infertility.

RESULTS

The mean age of the subjects was (32.8 ± 7.5) years and 488 (13.51%) of them reported infertility. CMI < 0.59 were highly correlated with risk of infertility(OR = 4.47, 95%CI: 2.19-9.15, P < 0.0001), whereas CMI ≥ 0.59 was not significantly associated with the risk of infertility (OR = 1.01, 95%CI: 0.81-1.24, P = 0.9621).

CONCLUSION

Our results show a significant positive non-linear relationship between CMI and infertility risk in US women aged 20-45, with a threshold effect.

Correlation between the interleukin-36 subfamily and gut microbiota in patients with liver cirrhosis: Implications for gut-liver axis imbalance

BACKGROUND

Liver cirrhosis (LC) affect millions of people worldwide. The pathogenesis of cirrhosis involves complex interactions between immune responses and gut microbiota. Recent studies have highlighted the role of the interleukin-36 (IL-36) subfamily in inflammation and immune regulation. However, the relationship between serum IL-36 subfamily levels and gut microbiota in cirrhosis patients remains unclear. This study aimed to explore the clinical significance of serum IL-36 subfamily levels and their association with gut microbiota in cirrhosis patients.

AIM

To explore the clinical significance of serum IL-36 subfamily levels and their relationship with gut microbiota among cirrhosis patients.

METHODS

Sixty-one cirrhosis patients were enrolled from Lihuili Hospital of Ningbo University from May 2022 to November 2023 as the LC group and 29 healthy volunteers as the healthy control (HC) group. The serum expressions of IL-36α, IL-36β, IL-36γ, IL-36Ra, and IL-38 were measured through ELISA, while 16S rRNA gene sequencing was employed to rate microbial community in human fecal samples.

RESULTS

The serum levels of IL-36α, IL-36γ, IL-36Ra, and IL-38 in the LC group remarkably exceeded those in the HC group (P < 0.05). IL-36α, IL-36γ, and IL-38 were related positively to the Child-Pugh score (P < 0.05) and prominently exceeded those in the Child-Pugh C group (P < 0.05). The absolute abundance of harmful bacteria (Bacteroides, Bifidobacterium, Faecalibacterium) remarkably rose, while the beneficial bacteria (Firmicutes, Bacteroides, Escherichia-Shigella) notably decreased in the LC group (P < 0.05). IL-36α, IL-36γ, and IL-38 related positively to Lactobacillus (P < 0.05), while IL-38 negatively related to Fusicatenibacter (P < 0.05).

CONCLUSION

IL-36γ and IL-38 show promise as potential biomarkers for LC progression, but further validation is required.