Sex-based Disparities in Liver Transplantation for Hepatocellular Carcinoma and the Impact of the Growing Burden of NASH.

Background: The cause of liver disease is changing, but its impact on liver transplantation (LT) for hepatocellular carcinoma (HCC) in women and men is unclear. We performed a nationwide study to assess the prevalence and posttransplant survival outcomes of the various causes of liver disease in women and men with HCC. Methods: Data were obtained from the United Network for Organ Sharing database from 2000 to 2022. Data related to the listing, transplant, waitlist mortality, and posttransplant mortality for HCC were extracted. The proportion of HCC related to the various causes of liver disease among LT candidates and recipients and posttransplant survival were compared between women and men. Results: A total of 51 721 individuals (39 465 men, 12 256 women) with HCC were included. From 2000 to 2022, nonalcoholic steatohepatitis (NASH) was the fastest-growing cause of liver disease among female LT candidates with HCC (P < 0.01), followed by alcohol-associated liver disease. NASH overtook chronic hepatitis C as the leading cause of liver disease in 2020 and 2022 among waitlisted women and men with HCC, respectively. Female patients with HCC spent a significantly longer time on the LT waitlist compared with male patients (ß: 8.73; 95% confidence interval [CI], 2.91-14.54). Female patients with HCC from alcohol-associated liver disease also have a lower probability of receiving LT (subdistribution hazard ratio: 0.90; 95% CI, 0.82-0.99). Among transplant recipients with NASH HCC, female sex was associated with lower posttransplant mortality compared with male sex (hazard ratio: 0.79; 95% CI, 0.70-0.89; P < 0.01). Conclusions: Women have a significantly longer waitlist duration compared with men. NASH is now the leading cause of liver disease among both female and male LT candidates and recipients with HCC.

Hepatocyte-macrophage crosstalk via the PGRN-EGFR axis modulates ADAR1-mediated immunity in the liver.

ADAR1-mediated RNA editing establishes immune tolerance to endogenous double-stranded RNA (dsRNA) by preventing its sensing, primarily by MDA5. Although deleting Ifih1 (encoding MDA5) rescues embryonic lethality in ADAR1-deficient mice, they still experience early postnatal death, and removing other MDA5 signaling proteins does not yield the same rescue. Here, we show that ablation of MDA5 in a liver-specific Adar knockout (KO) murine model fails to rescue hepatic abnormalities caused by ADAR1 loss. Ifih1;Adar double KO (dKO) hepatocytes accumulate endogenous dsRNAs, leading to aberrant transition to a highly inflammatory state and recruitment of macrophages into dKO livers. Mechanistically, progranulin (PGRN) appears to mediate ADAR1 deficiency-induced liver pathology, promoting interferon signaling and attracting epidermal growth factor receptor (EGFR)+ macrophages into dKO liver, exacerbating hepatic inflammation. Notably, the PGRN-EGFR crosstalk communication and consequent immune responses are significantly repressed in ADAR1high tumors, revealing that pre-neoplastic or neoplastic cells can exploit ADAR1-dependent immune tolerance to facilitate immune evasion.

Machine learning improves the prediction of significant fibrosis in Asian patients with metabolic dysfunction-associated steatotic liver disease - The Gut and Obesity in Asia (GO-ASIA) Study.

BACKGROUND: The precise estimation of cases with significant fibrosis (SF) is an unmet goal in non-alcoholic fatty liver disease (NAFLD/MASLD). AIMS: We evaluated the performance of machine learning (ML) and non-patented scores for ruling out SF among NAFLD/MASLD patients. METHODS: Twenty-one ML models were trained (N = 1153), tested (N = 283), and validated (N = 220) on clinical and biochemical parameters of histologically-proven NAFLD/MASLD patients (N = 1656) collected across 14 centres in 8 Asian countries. Their performance for detecting histological-SF (≥F2fibrosis) were evaluated with APRI, FIB4, NFS, BARD, and SAFE (NPV/F1-score as model-selection criteria). RESULTS: Patients aged 47 years (median), 54.6% males, 73.7% with metabolic syndrome, and 32.9% with histological-SF were included in the study. Patients with SFvs.no-SF had higher age, aminotransferases, fasting plasma glucose, metabolic syndrome, uncontrolled diabetes, and NAFLD activity score (p < 0.001, each). ML models showed 7%-12% better discrimination than FIB-4 to detect SF. Optimised random forest (RF) yielded best NPV/F1 in overall set (0.947/0.754), test set (0.798/0.588) and validation set (0.852/0.559), as compared to FIB4 in overall set (0.744/0.499), test set (0.722/0.456), and validation set (0.806/0.507). Compared to FIB-4, RF could pick 10 times more patients with SF, reduce unnecessary referrals by 28%, and prevent missed referrals by 78%. Age, AST, ALT fasting plasma glucose, and platelet count were top features determining the SF. Sequential use of SAFE < 140 and FIB4 < 1.2 (when SAFE > 140) was next best in ruling out SF (NPV of 0.757, 0.724 and 0.827 in overall, test and validation set). CONCLUSIONS: ML with clinical, anthropometric data and simple blood investigations perform better than FIB-4 for ruling out SF in biopsy-proven Asian NAFLD/MASLD patients.