{
  "abstract": "The microbiome-gut-brain axis (MGBA) is a bidirectional communication network that contributes to organismal homeostasis through neural, endocrine, immune, and microbial metabolic signaling. The gut microbiota influences central nervous system (CNS) function through pathways involving the vagus nerve and circulation, with metabolites such as short-chain fatty acids and tryptophan derivatives regulating neurogenesis, barrier integrity, and immune responses. Conversely, the CNS modulates the intestinal environment through the autonomic nervous system and the hypothalamic-pituitary-adrenal axis, thereby influencing gut barrier function and microbial composition. Disruption of this regulatory network may initiate a cascade of pathological changes, linking microbial metabolic alterations and cellular dysfunction to intestinal barrier impairment, systemic inflammation, blood-brain barrier disruption, and altered brain function. Such MGBA disturbances have been associated with CNS disorders. This review synthesizes five core communication mechanisms of the MGBA and examines how their interactions across molecular, cellular, tissue, organ, and systemic levels may contribute to CNS pathology. By framing CNS disorders as dynamic processes involving cross-scale network imbalance, this review provides an integrated perspective on MGBA-related disease mechanisms and highlights directions for targeted intervention.",
  "abstract_shown": true,
  "affiliations": [
    "School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine",
    "Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences",
    "State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Liying Liu"
    },
    {
      "affs": [
        1
      ],
      "name": "Mengru Cai"
    },
    {
      "affs": [
        2
      ],
      "name": "Yu Yin"
    },
    {
      "affs": [
        0
      ],
      "name": "Yongjian Song"
    },
    {
      "affs": [
        0
      ],
      "name": "Jue Zhuang"
    },
    {
      "affs": [
        0
      ],
      "name": "Bingyue Shen"
    },
    {
      "affs": [
        0
      ],
      "name": "Yanan Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "Yi Liu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7xz8mckz6fymt.bib",
  "cited_by": 0,
  "doi": "10.3389/fimmu.2026.1995842",
  "fulltext_url": null,
  "id": "7xz8mckz6fymt",
  "issns": [
    "1664-3224"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1995842/full",
  "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": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-09",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/7xz8mckz6fymt.ris",
  "sources": [
    {
      "first_seen": "2026-11-10T00:21:33Z",
      "native_id": "10.3389/fimmu.2026.1995842",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1995842/full"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "issn:1664-3224",
      "subfield": "immunology"
    }
  ],
  "title": "Research on the multilevel pathogenesis and cross-scale correlation networks of the microbiota-gut-brain axis in mediating central nervous system disorders",
  "title_text": "Research on the multilevel pathogenesis and cross-scale correlation networks of the microbiota-gut-brain axis in mediating central nervous system disorders",
  "type": "peer-reviewed",
  "updated_at": "2026-11-10T00:21:33Z",
  "url": "https://research.draconitic.com/paper/7xz8mckz6fymt",
  "venue": "Frontiers in Immunology",
  "versions": []
}