Hepatology Communications

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is the fastest-growing etiology of hepatocellular carcinoma (HCC). A mechanistic understanding of the metabolic heterogeneity of MASLD-driven tumors is crucial to inform strategies for future treatment options. MethodsPaired tumor (n=8) and adjacent non-tumor tissue (n=8) were collected from patients with steatohepatitic HCC at the University of Kentucky Markey Cancer Center. Hematoxylin and eosin (H&E) staining was used for pathological determination of tumor and adjacent nontumor tissue by a board-certified pathologist. Lipidomic, metabolomic, and transcriptomic analyses were performed, and data were integrated across platforms to identify novel relationships across tumor and adjacent nontumor tissue. ResultsHistological analysis by H&E showed significant lipid vacuole accumulation and inflammatory foci in HCC tumors relative to nontumor tissue. Across omics platforms, we identified 1,679 genes, 1,696 metabolites, and 292 lipids that were significantly (padj<0.01) increased or decreased in tumors relative to nontumor tissue. We identified significant reductions in total ceramides and increases in fatty acyl chain saturation in tumor tissue. Furthermore, metabolites involved in amino acid and fatty acid metabolism were largely decreased in tumors relative to nontumor tissue. We also identified a total of 303 highly significant and novel transcript-metabolite associations (117 gene-metabolite; 186 gene-lipid) across tumor and nontumor tissue. ConclusionsTaken together, this integrative analysis reveals novel relationships between steady-state gene transcripts and specific metabolites in steatohepatitic tumors, thereby identifying new pharmacological targets that may be exploited for therapeutic benefit.

BackgroundLiver transplantation (LT) offers a curative option for early-stage hepatocellular carcinoma (HCC). Its role in intrahepatic cholangiocarcinoma (ICC) remains controversial, with limited comparative evidence on long-term outcomes, especially for early-stage disease. MethodsThis retrospective population-based study utilized the SEER database (2004-2015). Patients with AJCC 6th edition Stage I HCC or ICC who underwent LT were included. Cancer-specific survival (CSS) and overall survival (OS) were primary endpoints. Kaplan-Meier ana lysis, log-rank tests, and Cox proportional hazards regression were used for survival comparison and identification of prognostic factors. ResultsAmong 944 eligible patients, 925 had HCC and 19 had ICC. The 5-year OS and CSS rates were significantly higher for HCC patients (OS: 95.1%; CSS: 97.7%) compared to ICC patients (OS: 82.3%; CSS: 82.3%). Multivariate Cox analysis for HCC identified age and marital status as independent risk factors for OS, and tumor size for CSS. For ICC, only tumor size was associated with OS in univariate analysis; no independent risk factors for CSS were identified due to the small sample size. ConclusionsLT provides excellent long-term survival for patients with early-stage HCC. In contrast, outcomes for early-stage ICC patients after LT are significantly inferior. Prognostic factors differ between the two histological types, underscoring the need for distinct LT selection criteria and management strategies. The findings highlight the limited utility of LT for ICC based on current selection paradigms and emphasize the necessity for larger studies incorporating molecular pro filing to identify potential ICC subpopulations that may benefit from LT.

Background and ObjectivesBariatric surgery is a highly effective obesity treatment, yet it may predispose individuals to alcohol-related liver injury. While altered ethanol metabolism following procedures like Roux-en-Y gastric bypass (RYGB) is well described, the long-term hepatic consequences, particularly the risk of portal hypertension in patients who develop alcohol-related hepatitis (AH,) remain poorly defined. MethodsUsing the TriNetX US Collaborative Network, we identified adult patients diagnosed with AH or alcohol-related cirrhosis. We compared outcomes between patients with a history of RYGB or sleeve gastrectomy (SG) who subsequently developed AH (Bariatric+AH group) and those with AH and no history of bariatric surgery (AH-only group). Propensity score matching was performed on over 44 demographic, clinical, and laboratory variables. Cox proportional hazards models and Kaplan-Meier survival curves were used to estimate the risk of clinically significant portal hypertension (PH) events, liver transplantation, and all-cause mortality at three-, five-, and seven-year follow-ups. ResultsAfter matching, 772 patients were included in each cohort. At 7 years post-index event, the Bariatric + AH group exhibited a significantly higher risk of PH-related complications compared to the AH-only group (HR 1.519; 95% CI, 1.15-2.005; p = 0.003). No significant differences were observed in liver transplantation (HR 1.412; 95% CI, 0.850-2.346; p = 0.181) or all-cause mortality (HR 1.085; 95% CI, 0.904-1.303; p = 0.381). These findings were consistent across all follow-up intervals. ConclusionBariatric surgery is associated with an increased long-term risk of portal hypertension in patients who develop alcohol-related hepatitis despite similar mortality and transplantation rates. These findings underscore the need for targeted postoperative counseling, liver-focused surveillance strategies, and integration of hepatologic risk assessment into metabolic surgery care pathways.

Background & AimsClonal hematopoiesis of indeterminate potential (CHIP) has been linked to chronic liver disease progression, yet its role across the full spectrum of metabolic dysfunction-associated steatotic liver disease (MASLD), from its initial development to end-stage complications, remains unclear. We aimed to comprehensively investigate the association of CHIP and its major subtypes with both the incidence and progression of MASLD. MethodsWe conducted a prospective cohort study of 353,218 UK Biobank participants, stratified into a healthy cohort free of MASLD at baseline (Cohort 1; n=230,270) and a prevalent MASLD cohort (Cohort 2; n=122,948). CHIP was ascertained from whole-exome sequencing data. We used multivariable Cox regression, competing risk models, and mediation analyses to assess the associations of CHIP (overall, by driver gene, and by clone size) with incident MASLD, cirrhosis, hepatocellular carcinoma (HCC), and liver-related death. ResultsIn Cohort 1, CHIP was associated with an increased risk of incident MASLD (HR 1.25, 95% CI 1.08-1.44) and cirrhosis (HR 1.57, 95% CI 1.10-2.25). These associations were driven by non-DNMT3A mutations, particularly TET2, and showed a linear dose-response relationship with clone size. In Cohort 2, non-DNMT3A CHIP was associated with progression to cirrhosis (HR 1.82, 95% CI 1.28-2.58). The associations were more pronounced in males and in individuals without obesity or diabetes. C-reactive protein partially mediated the CHIP-MASLD association. ConclusionCHIP, driven predominantly by non-DNMT3A mutations (particularly TET2) is an independent risk factor for both the development and progression of MASLD. These findings position CHIP as a novel player in the pathophysiology of MASLD and suggest potential avenues for risk stratification and targeted anti-inflammatory intervention. Impact and ImplicationsThis large-scale, prospective study establishes clonal hematopoiesis of indeterminate potential (CHIP) as a novel and independent risk factor for the entire spectrum of metabolic dysfunction-associated steatotic liver disease (MASLD), from its initial development to its progression to cirrhosis and liver-related death. For hepatologists and hematologists, these findings identify a genetically defined, high-risk subpopulation, particularly individuals with non-DNMT3A mutations, who may benefit from enhanced liver surveillance. The identification of systemic inflammation as a partial mediator of the CHIP-MASLD association suggests that anti-inflammatory therapies currently under development for liver disease could represent a targeted treatment strategy for this growing patient population.

Background and AimsHighly aggressive hepatobiliary tumours include gallbladder cancer (GBC), hepatocellular carcinoma (HCC), intrahepatic and extrahepatic cholangiocarcinoma (iCCA, eCCA) and ampulla of Vater cancer (AoV). We aimed to identify plasma biomarkers for the early diagnosis of hepatobiliary cancer by leveraging the metabolomic signatures of established clinical risk factors. MethodBased on 273,190 participants from the UK Biobank, we (1) identified metabolites associated with gallstone-related conditions (e.g. cholecystitis), primary sclerosing cholangitis (PSC) and metabolic liver diseases (e.g. cirrhosis), and (2) evaluated the relationship between the identified metabolites and the risk of GBC, HCC, iCCA, eCCA and AoV. Findings were validated in an independent group of 227,809 participants from the UK Biobank. We also derived metabolomic scores summarizing the three risk-factor signatures and evaluated their ability to stratify cancer risk. ResultsWe identified 27 metabolites associated with gallstone-related conditions, 11 with PSC, and 34 with metabolic liver diseases, some of which showed associations with inconsistent directions across risk factors, suggesting distinct pathogenic processes. Several metabolites were associated with cancer risk in both the discovery and validation datasets, independently of established risk factors, predominantly for HCC (16 signals) and for iCCA (4), with one for GBC and none for eCCA and AoV. Metabolomic scores clearly distinguished individuals at high risk for HCC and iCCA. ConclusionThe preselection of plasma metabolites associated with established risk factors facilitated the subsequent identification and validation of biomarkers for early cancer detection. The identified metabolites suggest specific pathogenic pathways for each type of hepatobiliary cancer. Wider replication is urgently needed to advance toward clinical implementation. What you need to knowO_ST_ABSBACKGROUND AND CONTEXTC_ST_ABSClinical risk factors for hepatobiliary cancers often progress silently, making early identification of high-risk individuals difficult and highlighting the need for biological markers detectable before clinical diagnosis. NEW FINDINGSRisk-factor-based serum metabolomic profiling identified circulating metabolites that predict specific hepatobiliary cancers years before diagnosis, with strongest and most consistent signals for hepatocellular and intrahepatic cholangiocarcinoma. LIMITATIONSClinical risk factors were assumed to be frequently underdiagnosed in UK Biobank, and event numbers were relatively small for some cancers, which may have reduced power and attenuated associations for less common endpoints. CLINICAL RESEARCH RELEVANCEThis study shows that serum metabolic profiles can identify individuals at increased risk for hepatobiliary cancers long before symptoms appear, particularly for hepatocellular and intrahepatic cholangiocarcinoma. These findings support the development of precision risk-stratification strategies that may ultimately enable earlier surveillance. BASIC RESEARCH RELEVANCEBy first identifying metabolites linked to specific liver and biliary clinical conditions, the study clarifies which metabolites are indirectly associated with hepatobiliary cancers through known disease pathways. Testing these metabolites again while adjusting for diagnoses of those conditions then reveals which ones also show direct, pathway-independent associations with individual hepatobiliary cancers, providing clearer insight into cancer-specific metabolic mechanisms.

Background and aimsPopulation screening for liver disease in high-risk groups is recommended. Community diagnosis of liver disease is a challenge due to the asymptomatic nature of disease until very advanced stages. Moreover, regional variation in testing availability can result in people with clinically significant liver disease being missed. Machine learning (ML) has been proposed as a method to reduce diagnostic error and automate screening. We present a novel machine learning derived algorithm (ID LIVER-ML) designed to predict the risk of clinically significant liver disease in a high-risk community population to identify those needing further investigations or specialist referral. MethodsUsing data from 2039 patients recruited to two UK cohorts, we created a parsimonious model using investigations that would be available in primary care using liver stiffness measurement as reference standard. The performance of ID LIVER-ML was compared against FIB-4 score in a second unseen hold out cohort (n=327). ResultsID LIVER-ML performed well at identifying patients at risk of clinically significant liver fibrosis (sensitivity 0.90, Specificity 0.43, PPV 0.54, NPV 0.86, AUC 0.83) and outperformed conventional risk scoring systems (FIB-4: AUC 0.65; NAFLD Fibrosis Score: AUC 0.66; APRI: AUC 0.53; BARD: AUC 0.58). ConclusionMachine learning derived algorithms can help screen high risk populations in a community setting for liver fibrosis. ClinicalTrials.gov ID: NCT04666402 Impact and ImplicationsThe prevalence of steatotic liver disease is rising globally and is an increasingly significant challenge for healthcare systems. Existing risk stratification scores are not validated in a real-world cohort where patients have risk factors for multiple aetiologies of liver disease. Our work shows that a machine learning model can predict the risk of clinically significant liver disease using routine primary care data, better than existing non-invasive risk stratification tools in a real-world cohort. This highlights a potential role for machine learning in the automation of fibrosis risk assessment in primary care. Highlights- Machine learning derived algorithms can predict the risk of clinically significant liver disease in an at risk community population with a mixed aetiology of liver diseases. - The performance of the ML algorithm (ID LIVER-ML) is not affected by metabolic, alcohol, or mixed aetiologies. - ID LIVER-ML outperforms traditional risk stratification scoring systems such as FIB-4 and NAFLD fibrosis scores. - Compared to the FIB-4 score, the use of Machine Learning can reduce the need for secondary care investigations by 59%.

BackgroundHepatocellular carcinoma (HCC) arises from diverse etiologies, but the balance between conserved and specific transcriptomic programs remains unclear. MethodsHBV and HCV cohorts were analyzed using GSVA to quantify Hallmark shifts. Biology was distilled into proliferation (ProlifHub) and hepatocyte-loss (HepLoss) modules, forming a composite HCCStateScore. An HBV injury axis was adjusted for proliferative state (E2F/G2M). Validation was performed using GSE14520 and GEPIA3. ResultsHallmark analysis revealed conserved proliferative activation and hepatocyte function suppression across etiologies. In HBV-HCC, the injury axis remained significantly elevated after adjusting for proliferation (p{approx}0.0147), indicating an injury component independent of the cell cycle. HCCStateScore robustly separated tumor from non-tumor tissue (AUC{approx}0.986, p=0). GEPIA3 confirmed concordant expression and survival associations for module genes. ConclusionsHCC features conserved opposing proliferation and hepatocyte-loss programs. HBV-associated tumors retain a distinct injury-linked component not fully explained by cell division. This validated score provides a framework for cross-cohort analysis and mechanistic prioritization in liver cancer research.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent condition that progresses from simple steatosis to advanced fibrosis, significantly affecting liver function and systemic health. Despite its widespread impact, therapeutic options are limited, highlighting the urgent need for comprehensive exploration to identify potential therapeutic targets. In this study, we created an analysis pipeline anchored on liver gene expression, integrating differential meta-analysis of transcriptomic data across three MASLD stages, transcriptome-wide Mendelian randomization (MR), and transcriptome-wide association studies (TWAS), to identify 39 candidate genes potentially involved in MASLD progression. Furthermore, we prioritized these genes using a scoring system that incorporated gene expression-clinical phenotype correlation meta-analysis, proteome-wide association studies (PWAS), and external genetic data from the GWAS Catalog and ExPheWAS. Single-nucleus RNA sequencing (snRNA-seq) analysis of liver cells from healthy to cirrhotic stages revealed stage- and cell-type-specific expression patterns of these prioritized genes. Through experimental validation in a lipid overload hepatocyte model, we confirmed the role of MLIP in lipid metabolism. These findings, available through an interactive web portal (masldportal.net), provide valuable insights into MASLD mechanisms and offer an easy-accessible resource for the research community. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/706502v2_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@1cec9f8org.highwire.dtl.DTLVardef@12df220org.highwire.dtl.DTLVardef@1734cecorg.highwire.dtl.DTLVardef@bf5b52_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is challenging to study in vivo in humans and in vitro models are limited. Although primary human hepatocytes (PHHs) are considered the gold-standard, immortalized hepatic cell lines are utilised due to scalability. This study compared the metabolic responses of PHHs with our Huh7-based model cultured in physiologically-relevant fatty acid (FA) mixtures. MethodsPHH and Huh7 cells were treated with 2% human serum, sugars and FAs enriched in either unsaturated (OPLA) or saturated (POLA) FAs for 4 or 7 days, respectively. Stable isotope tracers investigated basal metabolic changes in response to treatment. Cell viability, media biochemistry, intracellular metabolism, lipid droplet morphology and gene expression were quantified. ResultsHuh7 cells had greater viability than PHHs, while NEFA uptake and triglyceride secretion were similar. OPLA and POLA increased large lipid droplets in Huh7 cells, whereas only OPLA produced comparable effects in PHHs. Despite higher baseline TG in PHHs, both models showed similar lipid composition, de novo lipogenic responses, and glycogen levels. Compared to Huh7 cells, PHHs exhibited higher 3-hydroxybutyrate, lower lactate, reduced glucose uptake, and donor-dependent transcriptomic variability. ConclusionsHuh7 cells are metabolically adaptable and when cultured in physiologically-relevant media, produce metabolic readouts similar PHH cells.

Background & AimsIntrahepatic biliary epithelial cell (BEC) heterogeneity remains challenging to define. Here, we sought to identify BEC subpopulations and biomarkers in mouse liver. MethodsWe performed scRNA-seq on Sox9EGFP+ liver epithelium from mice subjected to bile duct ligation (BDL) and sham controls. A machine learning algorithm, NSForest, identified minimal, multi-gene signatures for BEC subpopulations. These "metagenes" were validated using hybridization chain reaction (HCR) FISH in tissue sections from wild-type mice and on primary BECs expanded in vitro. Metagenes were used to match BDL subpopulations to their corresponding sham subpopulations for differential gene expression (DGE) analysis. ResultsWe identified 4 BEC subpopulations in sham controls, each associated with 1-2 gene metagenes. Spatial localization of metagene-defined BEC subpopulations by HCR FISH revealed heterogeneous cellular composition of intrahepatic bile ducts. BECs belonging to a given subpopulation were most likely to have neighbors of the same identity, forming homogenous cellular compartments within ducts. BDL downregulated subpopulation-specific genes and upregulated a damage-associated gene set. BDL samples also included a proliferative subpopulation not found in sham controls, which contained populations enriched for three of the four metagenes. All BEC subpopulations were also found in monolayers in vitro, where they clustered spatially with BECs of the same subtype. ConclusionsNovel metagene biomarkers of BEC subpopulations facilitated spatial localization of BECs in situ, identified subpopulation specific injury responses, and confirmed that BEC heterogeneity is preserved in vitro. The presence of locally homogenous BEC "neighborhoods" in vitro suggests some degree of BEC organization may be epithelial-autonomous.

Background and AimMASLD affects 30-38% of Indian adults, yet the contribution of genetic risk variants to disease susceptibility and fibrosis progression remains poorly characterised. We investigated the association of 12 candidate SNPs with MASLD susceptibility and fibrosis severity in North Indian patients, benchmarking allele frequencies against IndiGenomes and global populations. MethodsSixty-nine MASLD patients (75.4% male; median BMI 29.8 kg/m{superscript 2}) from a tertiary care liver clinic in New Delhi were genotyped for 12 SNPs using Illumina custom BeadChip array and Sanger sequencing. Patients were stratified by liver stiffness measurement (LSM): significant fibrosis ([&ge;]8 kPa, n=38) versus no significant fibrosis (<8 kPa, n=31). Allele frequencies were compared with IndiGenomes ([~]1,020 Indian individuals) and 1000 Genomes populations. ResultsPNPLA3 rs738409 G allele was the strongest within-cohort predictor of significant fibrosis (allelic OR 2.89, 95% CI 1.35-6.19, P=0.006; dominant model OR 3.94, P=0.008), with carriers demonstrating higher LSM (median 15.6 vs. 7.5 kPa, P=0.005). SAMM50 rs3761472 (OR 2.12, P=0.065) and FTO rs9939609 (OR 2.08, P=0.089) showed non-significant trends. In the population-level comparison, APOC3 rs2854116 T allele was the only variant significantly enriched after Bonferroni correction (64.0% vs. 47.9%; OR 1.93, 95% CI 1.35-2.77, P<0.001), followed by PNPLA3 (33.3% vs. 24.1%, OR 1.57, P=0.019) and SAMM50 (31.2% vs. 22.6%, OR 1.55, P=0.028). Notably, APOC3 showed no association with fibrosis (OR 0.96, P=1.000), suggesting a role in susceptibility rather than progression. All SNPs were in Hardy-Weinberg equilibrium. ConclusionsThis study reveals a dissociation between genetic determinants of MASLD susceptibility and fibrosis progression in North Indian patients. APOC3 rs2854116 predisposes to MASLD at the population level, while PNPLA3 rs738409 drives fibrosis severity within established disease, underscoring the need for ancestry-specific genetic risk stratification. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/26347059v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@a07808org.highwire.dtl.DTLVardef@12882adorg.highwire.dtl.DTLVardef@9b33a1org.highwire.dtl.DTLVardef@15aa5e8_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background & Aims: People with HIV (PWH) who achieve hepatitis C virus (HCV) cure may retain persistent metabolic alterations, particularly those with advanced fibrosis or cirrhosis. This study aimed to characterize plasma metabolomic and lipidomic profiles associated with cirrhosis in PWH at one and five years post-HCV therapy. Methods: Two cross-sectional studies evaluated PWH one (n=48) and five (n=30) years post-HCV therapy. Cirrhosis was defined as a liver stiffness measurement (LSM)[&ge;]12.5 kPa. Metabolomics and lipidomics were performed using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS), respectively. Data were analyzed using orthogonal partial least squares discriminant analysis (OPLS-DA) and generalized linear models (GLM), adjusting for relevant covariates. Results: At one and five years, 32 (66.7%) and 10 (33.3%) participants, respectively, had cirrhosis. OPLS-DA identified 235 and 229 metabolites with variable importance in projection (VIP)scores >1. At one year, cirrhosis was associated with elevated levels of glycerophospholipids, sphingomyelins, and amino acids, and lower levels of triglycerides. At five years, cirrhotic PWH exhibited higher levels of glycerophospholipids and acyl-carnitines, together with lower levels of triglycerides and amino acids. Conclusions: PWH with cirrhosis post-HCV cure exhibits a persistently altered metabolic profile stable for five years, suggesting ongoing liver disease progression. These findings underscore the need for continued long-term monitoring of this population.

Mast cells (MCs) are myeloid cells of the innate immune system. As a first line of defence they fulfill effector functions and immune modulatory properties. Upon activation they release pro-inflammatory mediators such as cytokines and proteases. It has been suggested that MCs may contribute to the development of liver fibrosis. However, investigating hepatic MC biology in mice is challenging due to low MC numbers and a lack of suitable detection techniques relying on MC proteins and their modifications. Here, we evaluated whether the expression strength of MC markers correlates with the degree of liver fibrosis in mice and aimed to determine the frequency and localization of hepatic MCs. We applied both a toxic (DEN/CCl4 treatment) and a genetic (Mdr2-/- mice) liver fibrosis model in C57BL/6 mice and found a significant correlation between fibrosis grade and the expression of several established mast cell markers. This correlation was further supported in patients with fibrosis and hepatocellular carcinoma (HCC) using publicly available transcriptomics datasets. We used FACS to purify and isolate MCs from fibrotic mouse livers and verified MC signatures by qPCR analysis of MC-specific gene expression. Hepatic MCs were predominantly negative for Mast-Cell-Protease 5 (Mcpt5) and occurred at a low frequency (approximately 1-2% of leukocytes). Using Molecular CartographyTM of fibrotic liver sections, we determined the spatial localization, expression signature, abundance (approximately 2 cells/mm2) and cellular environment of murine hepatic MCs. In summary, we demonstrated the existence of MCs in murine fibrotic livers and defined an MC expression signature that correlates with the strength of liver fibrosis. These findings will help to study MC biology in murine models of liver disease more effectively in the future.

ObjectiveGlucokinase Regulatory Protein (GKRP) controls the activity of Glucokinase (GCK) to regulate liver glucose uptake and storage. Coding variants in GCKR, the gene encoding GKRP, strongly associate with fatty liver disease, hypertriglyceridemia, and hypercholesterolemia. Here, we sought to investigate the mechanisms by which a common GKRP variant affects hepatic lipid and cholesterol metabolism. MethodsWe developed mouse models to examine how the human GKRP P446L variant influences liver and systemic metabolism. Endogenous Gckr expression was ablated in adult mouse hepatocytes, together with re-expression of either human GKRP P446L or the reference GKRP protein. We assessed body weight, adiposity, systemic glucose homeostasis, and hepatic metabolites in mice expressing reference GKRP or GKRP P446L under multiple metabolic conditions. To determine whether the effects of GKRP P446L may result from reduced GCK activity, we analyzed mice with liver-specific deletion of Gck. ResultsHepatic expression of GKRP P446L resulted in reduced GKRP and GCK protein levels and elevated serum cholesterol. Hepatic deletion of Gck in mice recapitulated several effects of GKRP P446L, including increased hepatic cholesterol and triglyceride content. The elevated cholesterol was associated with increased cholesterogenic gene expression and cholesterol synthesis. Hepatic expression of an alternative hexokinase (HKII) normalized the effects of GCK-deficiency, suggesting that impaired glucose phosphorylation underlies the phenotype. ConclusionsThe GKRP P446L variant reduced GKRP protein abundance, and diminished GCK activity while increasing cholesterol levels. Loss of GCK elevated cholesterol and hepatic triglyceride levels. Collectively, these findings demonstrate that GCK suppresses hepatic cholesterol synthesis and lipid accumulation, suggesting that reduced GCK activity underlies the metabolic abnormalities associated with the GKRP P446L variant. HighlightsO_LIThe GKRP P446L variant reduces GKRP protein abundance and diminishes GCK activity. C_LIO_LIExpression of GKRP P446L in mouse hepatocytes increases serum cholesterol levels. C_LIO_LIHepatic GCK activity suppresses cholesterogenic gene expression and cholesterol synthesis. C_LI

BackgroundHepatocellular carcinoma (HCC) is a leading cause of cancer-related death in sub-Saharan Africa (SSA). Differentiating primary HCC from metastatic liver tumors remains a significant diagnostic challenge. Understanding the prevalence and clinical predictors of HCC is crucial for improving diagnosis and patient care. This study examined the prevalence of hepatitis B virus (HBV), hepatitis C virus (HCV), and HCC, and clinical predictors of HCC. MethodsWe used immunohistochemical markers on archived liver tumor biopsies and analyzed the data using descriptive and logistic regression analysis. ResultsAmong 58 liver carcinoma cases, 37.9% had HCC, and 62% had metastatic liver carcinoma (MLC). HCC was most common (61.5%) among middle-aged adults (50-59 years). HCC was more frequent in males (47.2%) than in females (22.7%). Over half of the patients (51.7%) tested positive for HBV. HCC was more prevalent in HBV-positive patients than HBV-negative ones (43.3% vs 32.1%). Hepatic fibrosis was identified in 27.6% of cases. HCC was more common in patients with fibrosis (56.2%) than in those without (31%). HCV infection was rare (6.9%) in this study. In multivariable logistic regression analysis, none of the examined predictors reached statistical significance (P>0.05). Patients aged 50-59 years, males, those with HBV infection, and hepatic fibrosis showed higher odds of HCC. Hepatocyte Paraffin-1 (Hep Par-1) demonstrated 97% specificity and a 95% positive predictive value (PPV) for differentiating HCC from MLC. The combined marker pattern of Hep Par-1 positive and AE1/AE3 negative was highly predictive of HCC (100% specificity, 100% PPV, and 93.2% diagnostic accuracy). ConclusionsOur findings indicate that while the assessed risk factors tend to show directional association with HCC, as expected, larger studies are needed to determine their independent effects. The combined Hep Par-1 AE1/AE3 immunophenotype is more accurate than either marker alone. Therefore, this combined test is a valuable diagnostic tool for confirming HCC in resource-limited settings.

Regeneration depends on tightly coordinated transcriptional programs governed by a dynamic epigenetic landscape to regulate cell identity, proliferation, and tissue remodelling following injury. The livers highly regenerative due to the ability to rapidly upregulate genes that drive the cell cycle and other genes important for regeneration. Trimethylation of histone 3 lysine 27 (H3K27me3) is deposited by the polycomb repressive complex 2 (PRC2) and many genes occupied by H3K27me3 in their promoters in uninjured livers become induced following PH. Here we test the hypothesis that depleting H3K27me3 by hepatocyte-specific deletion of Embryonic Ectoderm Development (EedHepKO), a key component of PRC2, changes the regenerative response in the liver. We show that Eed eliminates H3K27me3 in hepatocytes, resulting in reduced liver size, increased hepatocyte death, proliferation and fibrosis associated with upregulation of cell cycle and fibrogenic genes. Though these mice are less likely to survive two-thirds partial hepatectomy than wildtype controls, those that do survive increase liver mass faster than WTs. Importantly the genes that are occupied by H3K27me3 in control uninjured livers are upregulated in EEDHepKO and become further induced following PH. These data show that modulation of PRC2 activity disrupts epigenetic patterning, induces liver injury, and alters regenerative outcomes, suggesting that precise control of PRC2 function could be harnessed to enhance regenerative capacity.

Background & AimsEarly identification of decompensation in patients with cirrhosis is important to enable timely detection, management of complications and for effective treatment. This study investigates the biology of decompensation and aim to identify protein biomarkers for identification of high-risk patients. MethodsThe primary analysis included plasma samples from 46 patients with metabolic dysfunction associated steatotic liver disease (MASLD) related cirrhosis. Plasma samples were depleted for the top 14 most abundant proteins and the proteome was measured by liquid chromatography tandem mass spectrometry. The dataset was divided into a training (14 compensated, 10 decompensated) and a test cohort of compensated patients (11 progressing to decompensation, 11 remaining compensated). Changes in protein levels were determined by ANCOVA and a prognostic model was developed using logistic regression. External validation was performed in an independent cohort of 120 patients with alcohol-related cirrhosis. Time-to-event analyses were conducted in this cohort using Cox regression. Results52 proteins involved in impaired hepatic function, fibrogenesis, immune activation, and metabolic changes were significantly different between compensated and decompensated patients. A prognostic model with four proteins (NBL1, LTBP4, APOC4, GHR), demonstrated predictive ability for future decompensation (AUC=0.93, 73% sensitivity, 100% specificity). In the external validation cohort, the model demonstrated generalizability (AUC=0.78, 72% sensitivity, 82% specificity). Validation cohort time-to-event analyses showed that higher baseline scores were associated with shorter time to liver-related events (HR 1.32; log-rank p = 0.027), underscoring the panels prognostic value. ConclusionOur study indicates that patients with decompensated cirrhosis are characterized by proteomic signatures of fibrogenesis and metabolic dysfunction. Capturing these signatures could help identify patients at risk of complications and potentially those eligible for aetiology directed treatment. Impact and ImplicationsAddressing a critical unmet need for early detection of cirrhosis decompensation, our proteomic study identifies a four-protein panel with predictive ability for decompensation. These findings hold significant implications for hepatologists, clinical researchers, and healthcare systems, offering a novel tool to enhance prognostication and refine treatment strategies, potentially facilitating targeted patient monitoring. However, considering the small discovery sample size and the distinct aetiology of the external validation cohort, further validation is essential before broad clinical integration. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=183 SRC="FIGDIR/small/709475v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@6620e2org.highwire.dtl.DTLVardef@f8dfe4org.highwire.dtl.DTLVardef@1331101org.highwire.dtl.DTLVardef@1a195ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background & aimsConstitutive activation of the {beta}-catenin pathway is a determining feature in the pathogenesis of two primary liver cancers, namely HCC and hepatoblastoma (HB). Activating alterations in CTNNB1 gene and, to a lesser extent, inhibiting alterations in APC gene are observed in 30 to 40% of HCC cases and 80 to 90% of HB cases. For both tumours, therapeutic management is far from optimal. Therefore, relevant experimental models are needed to increase our knowledge and test new therapeutic approaches. MethodsOrganoids and tumouroids were established from APC{Delta}hep and {beta}cat{Delta}ex3 mouse models, which are clinically relevant models for {beta}-catenin-activated HCC and mesenchymal HB. We developed a new methodological approach based on a dynamic suspension culture in a rotating bioreactor. Morphological and molecular characteristics and sensitivity to WNTinib, a treatment already successfully tested on human HCC and HB tumouroids, were evaluated by histology, immunohistochemistry, immunofluorescence, and RT-qPCR. ResultsThis easy-to-implement methodology allows for the rapid generation of a large number of organoids and tumouroids that are uniform in size and show no signs of cell death in their core. The robustness of the methodology is illustrated by the maintenance of the histological architecture, cell diversity and gene expression in organoids and tumouroids in comparison with the native liver tissues. In addition, the value of the HCC-derived tumouroids for evaluating cancer treatment was assessed based on their responsiveness to the {beta}-catenin antagonist WNTinib. ConclusionsThe organoids and tumouroids that we present here are new reliable in vitro cancer models, recapitulating the main features of {beta}-catenin-driven HCC and mesenchymal HB. They can be integrated into an appropriate platform for drug screening and could enable the development of "a la carte" therapies that are urgently needed for these indications. Impact and implicationsThis study addresses the critical need for representative in vitro models to investigate {beta}-catenin-driven liver cancers. The organoids and tumouroids developed here are particularly valuable for researchers seeking robust, reproducible models that accurately reflect the cellular diversity and gene expression profiles of native liver tumours. These findings have practical applications in exploring cancer mechanisms, screening new drugs, optimizing personalized treatment strategies, and reducing reliance on animal models, which ultimately benefits patients. HighlightsO_LIEasy and rapid generation of mouse liver organoids and tumouroids from {beta}-catenin activated tumours using culture in a bioreactor C_LIO_LITumouroids preserve histology, cell diversity, and gene expression of native tissue C_LIO_LIHCC-derived tumouroids respond to {beta}-catenin inhibitor WNTinib C_LIO_LIThese reliable 3D models reduce reliance on animal experiments for drug testing C_LI

PurposePortal hypertension, a major complication of chronic liver disease, leads to significant morbidity and mortality. While portal vein diameter measured on imaging has long been proposed as a non-invasive marker of portal hypertension, normative CT-based reference values and population-level associations remain incompletely characterized. Here, we aim to define contemporary reference values for portal vein diameter on clinically obtained CT and evaluate its associations with demographic, clinical, and imaging factors, as well as its diagnostic performance for portal hypertension. MethodsWe conducted a retrospective analysis of 20,225 clinically obtained CT scans at a single academic medical center. The main portal vein was automatically segmented using Total Segmentator, and maximum diameter extracted using the Vascular Modeling Toolkit. Associations with demographic and imaging factors were evaluated using linear mixed-effects models; prevalent liver disease and portal hypertension using logistic regression; risk of incident ascites and esophageal varices among participants with liver disease using Cox regression; and invasive hepatic venous pressures using correlation analysis and linear regression. ResultsThe mean portal vein diameter was 12.4 mm (95% CI, 12.37-12.45). Larger diameter was independently associated with male sex (+1.4 mm), higher BMI (+0.11 mm/kg/m2), greater height (+0.04 mm/cm), and older age (+0.05 mm/10 years) (all p <0.001), and was substantially larger on contrast-enhanced abdomen/pelvis CT (+2.4 mm, p <0.001). Each 1-mm increase in portal vein diameter was associated with higher odds of prevalent liver disease (OR 1.06; 95% CI, 1.04-1.08) and portal hypertension (OR 1.18; 95% CI, 1.12-1.28). Among individuals with liver disease, greater diameter predicted higher risk of incident esophageal varices (baseline diameter HR 1.50; 95% CI, 1.14-2.08) and ascites (HR per mm increase in diameter 1.06; 95% CI, 1.003-1.12). However, portal vein diameter demonstrated weak to no association with invasively measured hepatic venous pressures. ConclusionIn this large, EHR-linked imaging cohort, the mean portal vein diameter on CT was 12.4 mm and varied with demographic and imaging factors. Larger diameter was associated with liver disease, portal hypertension, and subsequent development of varices and ascites, supporting use of portal vein diameter as a pragmatic screening or enrichment tool within multimodal clinical frameworks. Key ResultsO_LIMean portal vein diameter on routine clinical CT was 12.4 mm (95% CI, 12.37-12.45) and varied with sex, height, BMI, exam type, contrast use, and clinical setting. C_LIO_LIEach 1-mm increase in portal vein diameter was associated with higher odds of prevalent liver disease (OR 1.06) and portal hypertension (OR 1.18). C_LIO_LIAmong individuals with liver disease, larger portal vein diameter predicted higher risk of incident esophageal varices and ascites, independent of demographic and imaging factors. C_LI

Background & Aims: Per- and polyfluoroalkyl substances (PFAS) are persistent endocrine-disrupting chemicals associated with metabolic dysfunction, including metabolic dysfunction-associated steatotic liver disease (MASLD). While PFAS perturb lipid and bile acid (BA) metabolism in a sex-specific manner, the underlying mechanisms remain unclear. We tested whether steroid hormones mediate PFAS-associated metabolic alterations. Methods: In 104 patients with biopsy-characterized MASLD, we performed sex-stratified analyses applied liquid chromatography coupled to mass spectrometry (LC-MS) for chemical analysis, integrating circulating steroids, PFAS exposure, hepatic lipidomics and BA profiles. Results: Steroid hormones were associated with MASLD severity in a sexually-dimorphic manner. Dihydrotestosterone showed consistent inverse associations with steatosis, fibrosis, necroinflammation and insulin resistance, particularly in females. PFAS exposure was associated with altered steroid profiles, predominantly indicating suppressed steroidogenesis in females. These PFAS-associated hormonal changes were linked to downstream alterations in hepatic lipids and BAs. Mediation analysis supported indirect effects of PFAS on metabolic pathways via steroids, including testosterone/epi-testosterone-mediated effects on ether phospholipids and estradiol-mediated effects on lithocholic acid. Females exhibited stronger PFAS-steroid-BA associations, whereas males showed weaker, lipid-centric effects. Conclusions: PFAS exposure is associated with sex-specific disruption of steroid hormone pathways that may link environmental exposure to lipid and BA dysregulation in MASLD. These findings identify steroid hormones as potential key mediators of PFAS-associated metabolic dysfunction and highlight sex as a critical determinant in environmental liver disease.