Distinct Gut Microbial Signature and Host Genetic Variants in Association with Liver Fibrosis Severity in Patients with MASLD.

Gut microbiota might affect the severity and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to characterize gut dysbiosis and clinical parameters regarding fibrosis stages assessed by magnetic resonance elastography. This study included 156 patients with MASLD, stratified into no/mild fibrosis (F0-F1) and moderate/severe fibrosis (F2-F4). Fecal specimens were sequenced targeting the V4 region of the 16S rRNA gene and analyzed using bioinformatics. The genotyping of PNPLA3, TM6SF2, and HSD17B13 was assessed by allelic discrimination assays. Our data showed that gut microbial profiles between groups significantly differed in beta-diversity but not in alpha-diversity indices. Enriched Fusobacterium and Escherichia_Shigella, and depleted Lachnospira were found in the F2-F4 group versus the F0-F1 group. Compared to F0-F1, the F2-F4 group had elevated plasma surrogate markers of gut epithelial permeability and bacterial translocation. The bacterial genera, PNPLA3 polymorphisms, old age, and diabetes were independently associated with advanced fibrosis in multivariable analyses. Using the Random Forest classifier, the gut microbial signature of three genera could differentiate the groups with high diagnostic accuracy (AUC of 0.93). These results indicated that the imbalance of enriched pathogenic genera and decreased beneficial bacteria, in association with several clinical and genetic factors, were potential contributors to the pathogenesis and progression of MASLD.

Distinct alterations of gut microbiota between viral- and non-viral-related hepatocellular carcinoma.

Altered gut microbiota has been connected to hepatocellular carcinoma (HCC) occurrence and advancement. This study was conducted to identify a gut microbiota signature in differentiating between viral-related HCC (Viral-HCC) and non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). Fecal specimens were obtained from 16 healthy controls, 33 patients with viral-HCC (17 and 16 cases with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, respectively), and 18 patients with NBNC-HCC. Compositions of fecal microbiota were assessed by 16S rRNA sequencing. Bioinformatic analysis was performed by the DADA2 pipeline in the R program. Significantly different genera from the top 50 relative abundance were used to classify between subgroups of HCC by the Random Forest algorithm. Our data demonstrated that the HCC group had a significantly decreased alpha-diversity and changed microbial composition in comparison with healthy controls. Within the top 50 relative abundance, there were 11 genera including Faecalibacterium, Agathobacter, and Coprococcus that were significantly enhanced in Viral-HCC, while 5 genera such as Bacteroides, Streptococcus, Ruminococcus gnavus group, Parabacteroides, and Erysipelatoclostridium were enhanced in NBNC-HCC. Compared to Viral-HCC, the NBNC-HCC subgroup significantly reduced various short-chain fatty acid-producing bacteria, as well as declined fecal butyrate but elevated plasma surrogate markers of microbial translocation. Based on the machine learning algorithm, a high diagnostic accuracy to classify HCC subgroups was achieved with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.94. Collectively, these data revealed that gut dysbiosis was distinct according to etiological factors of HCC, which might play an essential role in hepatocarcinogenesis. These findings underscore the possible use of a gut microbiota signature for the diagnosis and therapeutic approaches regarding different subgroups of HCC. KEY POINTS: • Gut dysbiosis is connected to hepatocarcinogenesis and can be used as a novel biomarker. • Gut microbiota composition is significantly altered in different etiological factors of HCC. • Microbiota-based signature can accurately distinguish between Viral-HCC and NBNC-HCC.

Circulating Extracellular Vesicle-Derived microRNAs as Novel Diagnostic and Prognostic Biomarkers for Non-Viral-Related Hepatocellular Carcinoma.

Extracellular vesicle-derived microRNAs (EV-miRNAs) are promising circulating biomarkers for chronic liver disease. In this study, we explored the potential significance of plasma EV-miRNAs in non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). We compared, using the NanoString method, plasma EV-miRNA profiles between NBNC-HCC and control groups including patients with non-alcoholic fatty liver disease (NAFLD) and healthy controls. The differentially expressed EV-miRNAs were validated in another set of plasma samples by qRT-PCR. A total of 66 significantly differentially expressed EV-miRNAs between the HCC and the control groups were identified in the discovery set. In the validation cohort, including plasma samples of 70 NBNC-HCC patients, 70 NAFLD patients, and 35 healthy controls, 5 plasma EV-miRNAs were significantly elevated in HCC, which included miR-19-3p, miR-16-5p, miR-223-3p, miR-30d-5p, and miR-451a. These miRNAs were found to participate in several cancer-related signaling pathways based on bioinformatic analysis. Among them, EV-miR-19-3p exhibited the best diagnostic performance and displayed a high sensitivity for detecting alpha-fetoprotein-negative HCC and early-stage HCC. In multivariate analysis, a high EV-miR-19-3p level was demonstrated as an independently unfavorable predictor of overall survival in patients with NBNC-HCC. In conclusion, our data have indicated, for the first time, that EV-miR-19-3p could serve as a novel circulating biomarker for the diagnosis and prognosis of NBNC-HCC.