{
  "abstract": "Metabolic dysfunction-associated steatotic liver disease (MASLD) is biologically heterogeneous and lacks sufficiently validated molecular biomarkers for disease characterization. Post-translational modification (PTM)-related genes may link metabolic stress to lipid dysregulation and inflammation, but their relevance remains unclear. We integrated liver transcriptomic datasets and PTM-related gene annotation with machine-learning prioritization, cell-resolved analysis, and experimental validation. PELI1, VPS41, and TRIM32 were prioritized as potential diagnostic candidates based on their disease-associated expression and discriminative performance in the examined transcriptomic cohorts, with concordant expression changes observed in an independent local liver cohort. Single-nucleus RNA sequencing suggested that disease-associated VPS41 upregulation was most prominent in hepatocytes. VPS41 expression also increased in livers from a diet-induced mouse model of MASLD and in lipid-loaded hepatocytes. In primary mouse hepatocytes, Vps41 knockdown aggravated lipid accumulation, lipogenic gene expression, and inflammatory responses, whereas VPS41 overexpression attenuated these changes. These findings distinguish the expression-based evidence supporting the diagnostic potential of PELI1 and TRIM32 from the functional evidence for VPS41 and support a protective role for VPS41 under hepatocellular lipid stress. Prospective clinical validation and in vivo gain- and loss-of-function studies are required to establish diagnostic utility and the causal and therapeutic relevance of VPS41.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "name": "Qingrong Yao"
    },
    {
      "name": "Xuan Zhong"
    },
    {
      "name": "Jiawei Chen"
    },
    {
      "name": "Wenbin An"
    },
    {
      "name": "Jiamian Wang"
    },
    {
      "name": "Hong Tang"
    },
    {
      "name": "Zhenyu Liu"
    },
    {
      "name": "Jiajia Chen"
    },
    {
      "name": "Lina Zhao"
    },
    {
      "name": "Sha Li"
    },
    {
      "name": "Liying Shi"
    },
    {
      "name": "Bei Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/acra4nqxyeawp.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-72903-2",
  "fulltext_url": null,
  "id": "acra4nqxyeawp",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-72903-2",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2713|Liver Disease Diagnosis and Treatment"
    ]
  ],
  "openalex": "W7214897504",
  "pdf_url": "https://www.nature.com/articles/s41598-026-72903-2_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-30",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/acra4nqxyeawp.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:19Z",
      "native_id": "10.1038/s41598-026-72903-2",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-72903-2"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2713|Liver Disease Diagnosis and Treatment",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Multi-omics and machine learning-driven identification of PTM-related potential biomarkers and therapeutic insights in MASLD",
  "title_text": "Multi-omics and machine learning-driven identification of PTM-related potential biomarkers and therapeutic insights in MASLD",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:19Z",
  "url": "https://research.draconitic.com/paper/acra4nqxyeawp",
  "venue": "Scientific Reports",
  "versions": []
}