{
  "abstract": "Background\n\nExercise is often described as medicine, but exercise and pharmacological interventions cannot be treated as clinically equivalent. This study developed a Reference Signature Projection Framework (RSPF) to evaluate the directional relationship of external disease and exercise transcriptomic responses relative to a predefined disease-treatment reference axis. The empirical analysis in this study was restricted to the IAV-DI reference axis defined by dimethyl itaconate (DI) treatment in the context of influenza A virus (IAV) infection.Methods\n\n(1) Reference-signature construction: the IAV-DI reference direction was defined from transcriptional changes between DI-treated and untreated human peripheral blood mononuclear cells in the context of IAV infection. Drug-UP and Drug-DOWN directions were defined according to avg_log2FC, candidate genes were prioritized using random forest Mean Decrease Accuracy (MDA), and the MDA Top 100 was used as the main reference signature. (2) Reference-signature projection: Drug-UP and Drug-DOWN were projected separately onto complete gene-ranking lists for GSE243629 IA versus HC, cardiopulmonary exercise testing (CPX), and Marathon post- versus pre-exercise comparisons, and GSEA was used to calculate NES, nominal p, and FDR. (3) Robustness and supporting evaluation: gene-level similarity, TopN sensitivity, random gene-set negative controls, and pathway-level NES patterns were used to evaluate transcriptomic directionality, robustness, and interpretive boundaries.Results\n\n(1) Reference-signature composition: the MDA Top 100 contained 24 Drug-UP and 76 Drug-DOWN genes. (2) External disease-direction evaluation: in GSE243629 IA versus HC, Drug-DOWN was significantly enriched toward the upregulated end (NES = 1.724, FDR = 4.00 × 10⁻⁸), whereas Drug-UP did not reach FDR< 0.05, indicating a clear opposite relationship of the external disease state relative to the IAV-DI reference axis, with statistical support driven mainly by the Drug-DOWN reference gene set. (3) Overall exercise-direction results: neither Drug-UP nor Drug-DOWN reached FDR< 0.05 in CPX or Marathon; therefore, their direction scores were interpreted only as exploratory directional indicators. Gene-level analysis likewise showed a weak overall directional relationship between CPX and IAV-DI. (4) Pathway-level results: selected functional modules showed the same NES sign for IAV-DI and CPX and the opposite sign for Marathon, but none of the CPX pathways reached FDR < 0.05; these results therefore represent only module-specific exploratory directional patterns.Conclusion\n\nRSPF provides a computational framework for evaluating transcriptomic directional relationships relative to a predefined disease-treatment reference axis. In the current IAV-DI proof-of-concept analysis, the external influenza disease comparison showed a clear opposite relationship relative to the IAV-DI reference axis, whereas neither CPX nor Marathon showed statistically supported overall IAV-DI directional concordance; exploratory directional patterns were observed only in selected functional modules. Accordingly, the present findings apply only to the IAV-DI reference axis and cannot be generalized to a universal relationship between exercise and pharmacological interventions or used to infer therapeutic equivalence, drug substitution, or shared pharmacological mechanisms.",
  "abstract_shown": true,
  "affiliations": [
    "Center for Innovation in Sports-Medicine Integration, Capital University of Physical Education and Sports, Beijing, China.",
    "Beijing Key Laboratory of Interdisciplinary Intelligent Technology of Sports, Medicine and Engineering, Beijing, China.",
    "Department of Nephrology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Anli Zhou"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Min Zhang"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Cheng Zhang"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Jianjun Guo"
    },
    {
      "affs": [
        2
      ],
      "name": "Min Zhang"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Yan Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/b4sn4jyvrrk35.bib",
  "cited_by": 0,
  "doi": "10.3389/fphys.2026.1943015",
  "fulltext_url": "https://europepmc.org/articles/PMC13683089",
  "id": "b4sn4jyvrrk35",
  "issns": [
    "1664-042X"
  ],
  "landing_url": "https://europepmc.org/article/MED/42908769",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Bioinformatics and Genomic Networks"
    ]
  ],
  "openalex": "W7220852235",
  "pdf_url": "https://europepmc.org/articles/PMC13683089?pdf=render",
  "pmcid": "PMC13683089",
  "pmid": "42908769",
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/b4sn4jyvrrk35.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:14Z",
      "native_id": "MED:42908769",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42908769"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Bioinformatics and Genomic Networks",
      "subfield": "molecular-biology"
    }
  ],
  "title": "Reference-signature projection framework for exercise transcriptomic directionality based on the IAV-DI reference axis.",
  "title_text": "Reference-signature projection framework for exercise transcriptomic directionality based on the IAV-DI reference axis.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:14Z",
  "url": "https://research.draconitic.com/paper/b4sn4jyvrrk35",
  "venue": "Frontiers in physiology",
  "versions": []
}