Kei Fujiwara

Background: Lean metabolic dysfunction‐associated steatotic liver disease (MASLD) is increasingly recognized. Whether it represents a distinct entity or a phenotype within the MASLD spectrum remains unclear. We examined differences in risk factor contribution and metabolic trajectories. Methods: In a longitudinal health checkup cohort (2017–2025), we included individuals without hepatic steatosis at baseline and excluded those with alcohol intake at or above the MetALD threshold. Incident MASLD was classified at diagnosis as Obese or Lean MASLD based on obesity status (BMI/WC). Baseline risk factors were evaluated using time‐to‐event and competing‐risk models with interaction testing. Longitudinal metabolic changes were assessed using logistic regression, and repeated trajectories were examined using linear mixed‐effects models. Results: Among 13,624 participants, 1865 developed incident MASLD (Obese MASLD, n = 1469; Lean MASLD, n = 396). Male sex, baseline obesity, glycemic abnormality/diabetes, hypertension, hypertriglyceridemia, and higher baseline ALT were independently associated with incident MASLD. Interaction analyses showed a stronger contribution of male sex and weaker contributions of hypertension and low HDL‐C in Lean MASLD. Longitudinal analyses showed Δtriglycerides and ΔALT were consistently associated with incident MASLD in both phenotypes, whereas ΔBMI showed a stronger association with Obese MASLD. Conclusions: Lean MASLD shared a broadly similar cardiometabolic risk structure with Obese MASLD, whereas the relative contribution of risk factors differed between phenotypes. Male sex showed a stronger association with Lean MASLD, whereas longitudinal changes in triglycerides and ALT were consistently associated with incident MASLD across both phenotypes. These findings provide exploratory evidence of phenotype‐specific metabolic associations requiring validation before clinical application.

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Background: Recent genome sequence technology has revealed a novel type of genetic rearrangement referred to as complex structural variations (SVs). Previous studies have elucidated the complex SVs in human hepatitis B viruses (HBVs). In this study, we investigated the existence of complex SVs in HBVs from non-human primates (NHPs). Methods: Searches for nucleotide sequences of NHP HBV were conducted using the PubMed, and genetic sequences were retrieved from databases. The candidate genetic sequences harboring complex SVs were analyzed using the CLUSTALW program and MAFFT. Additional bioinformatical analyses were performed to determine strains with complex SVs and to elucidate characteristics of NHP HBV strains. Results: One hundred and fifty-four HBV strains from NHPs were identified from databases. SVs and complex SVs were observed in 11 (7.1%) strains. Three gibbon HBV (GiHBV) strains showed complex SVs consisting of an insertion and a deletion in the pre-S1 region. One GiHBV strain possessed a 6-nt insertion, which are normally specific to human HBV genotype A (HBV/A) in the Core region, and further analyses clarified that the 6-nt insertion was not caused by recombination, but rather by simple insertion. Another chimpanzee HBV strain showed complex SVs in the pre-S1 region, which were composed of human HBV/E, G-specific polymorphic SV, and an additional 6-nt insertion. Conclusions: In this study, complex SVs were observed in HBV strains from NHPs, in addition to human HBV strains, as shown in previous studies. These data suggest that complex SVs could also be found in other members of hepadnaviruses, and may play a role in their genetic diversity.

Background & Aims: We recently analysed and reported the features of the micro biome under hepatitis C virus (HCV) infection, but the effect of HCV infection on bile acid (BA) metabolism in the gut‐liver axis remains poorly understood. The aim of this study was to clarify the characteristics of the gut‐liver axis in HCV‐infected patients.Methods: The faecal BAs composition and gut microbiota from 100 chronic hepatitis C (CHC) patients were compared with those from 23 healthy individuals. For transcriptional analysis of the liver, 22 mild CHC (fibrosis stages [F] 0‐2) and 42 advanced CHC (F3‐4) cases were compared with 12 healthy individuals. The findings were confirmed using chimeric mice with human hepatocytes infected with HCV HCR6.Results: Chronic hepatitis C patients, even at earlier disease stages, showed BA profiles distinct from healthy individuals, in which faecal deoxycholic acid (DCA) was significantly reduced and lithocholic acid or ursodeoxycholic acid became dominant. The decrease in faecal DCA was correlated with reduction in commensal Clostridiales and increase in oral Lactobacillales. Impaired biosynthesis of cholic acid (CA) was observed as a reduction in the transcription level of cytochrome P450 8B1 (CYP8B1), a key enzyme in CA biosynthesis. The reductions in faecal DCA and liver CYP8B1 were also observed in HCV‐infected chimeric mice.Conclusions: Chronic hepatitis C alters the intestinal BA profile, in association with the imbalance of BA biosynthesis, which differs from the pattern in NAFLD. These imbalances appear to drive disease progression through the gut‐microbiome‐liver axis.

In this special issue, we present collected updated data on the hepatitis viruses

Chronic hepatitis B virus (HBV) causes serious clinical problems, such as liver cirrhosis and hepatocellular carcinoma. Current antiviral treatments suppress HBV; however, the clinical cure rate remains low. Basic research on HBV is indispensable to eradicate and cure HBV. Genetic alterations are defined by nucleotide substitutions and canonical forms of structural variations (SVs), such as insertion, deletion and duplication. Additionally, genetic changes inconsistent with the canonical forms have been reported, and these have been termed complex SVs. Detailed analyses of HBV using bioinformatical applications have detected complex SVs in HBV genomes. Sequence gaps and low sequence similarity have been observed in the region containing complex SVs. Additionally, insertional motif sequences have been observed in HBV strains with complex SVs. Following the analyses of complex SVs in the HBV genome, the role of SVs in the genetic diversity of orthohepadnavirus has been investigated. SV polymorphisms have been detected in comparisons of several species of orthohepadnaviruses. As mentioned, complex SVs are composed of multiple SVs. On the contrary, SV polymorphisms are observed as insertions of different SVs. Up to a certain point, nucleotide substitutions cause genetic differences. However, at some point, the nucleotide sequences are split into several particular patterns. These SVs have been observed as polymorphic changes. Different species of orthohepadnaviruses possess SVs which are unique and specific to a certain host of the virus. Studies have shown that SVs play an important role in the HBV genome. Further studies are required to elucidate their virologic and clinical roles.

The genetic diversity of orthohepadnaviruses is not yet fully understood. This study was conducted to investigate the role of structural variations (SVs) in their diversity. Genetic sequences of orthohepadnaviruses were retrieved from databases. The positions of sequence gaps were investigated, since they were found to be related to SVs, and they were further used to search for SVs. Then, a combination of pair-wise and multiple alignment analyses was performed to analyze the genomic structure. Unique patterns of SVs were observed; genetic sequences at certain genomic positions could be separated into multiple patterns, such as no SV, SV pattern 1, SV pattern 2, and SV pattern 3, which were observed as polymorphic changes. We provisionally referred to these genetic changes as SV polymorphisms. Our data showed that higher frequency of sequence gaps and lower genetic identity were observed in the pre-S1-S2 region of various types of HBVs. Detailed examination of the genetic structure in the pre-S region by a combination of pair-wise and multiple alignment analyses showed that the genetic diversity of orthohepadnaviruses in the pre-S1 region could have been also induced by SV polymorphisms. Our data showed that novel genetic rearrangements provisionally termed SV polymorphisms were observed in various orthohepadnaviruses.