{
  "abstract": "Background: Graph attention networks (GATs) are increasingly applied to transcriptomic data because they integrate gene-network structure while producing attention weights that are often interpreted as indicators of biological importance. However, whether attention-derived explanations reliably reflect biologically meaningful signals has received little systematic evaluation, particularly in the small, heterogeneous cohorts common in psychiatric transcriptomics. Methods: We systematically re-evaluated a GAT using peripheral blood RNA-sequencing data from 76 individuals (39 ADHD, 37 controls), including 16 discordant monozygotic twin pairs. To maximize analytical rigor, we implemented a leakage-aware pipeline, incorporating twin-aware group-stratified cross-validation, fold-wise gene selection, corrected transcript-to-gene mapping, and validation through repeated cross-validation, permutation testing, three complementary feature-importance methods, orthogonal differential-expression and pathway analyses, and data-quality controls. Results: Across 20 repeated cross-validation splits, GAT achieved a slightly higher mean AUC than a graph convolutional network (mean AUC 0.624 vs. 0.599) and outperformed five classical machine-learning models on a prespecified split. However, GAT performance was not statistically distinguishable from a rigorously matched permutation-derived null distribution (p = 0.327), while an exploratory sample-size calculation indicated that roughly twice the current sample size would be needed to detect an effect this size at conventional power. Independent validation analyses converged on the same conclusion: attention-derived gene rankings were significantly negatively correlated with both SHAP and permutation importance, whereas differential-expression analyses---including discordant twin-pair comparisons---and pathway enrichment identified no reproducible biological signals after multiple-testing correction. Recovery of established co-expression modules and the absence of blood-cell marker differences supported pipeline validity. Conclusions: Graph-based models may show modest predictive gains, but predictive performance and biological interpretation are distinct scientific questions. Our findings demonstrate that attention-derived importance should be regarded as hypothesis-generating rather than mechanistic evidence unless independently validated, illustrating why rigorous, multi-level validation is essential before biological conclusions are drawn from graph neural networks in transcriptomic research.",
  "abstract_shown": true,
  "affiliations": [
    "School of Information Technology, Newgiza University, Cairo, Egypt"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Nehal M. Ali"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ejn95g9e9y2hm.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0359656",
  "fulltext_url": null,
  "id": "ejn95g9e9y2hm",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0359656",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Bioinformatics and Genomic Networks"
    ],
    [
      "plos",
      "/Biology and life sciences/Anatomy/Body fluids/Blood"
    ],
    [
      "plos",
      "/Biology and life sciences/Computational biology/Genome analysis/Transcriptome analysis"
    ],
    [
      "plos",
      "/Biology and life sciences/Developmental biology/Twins"
    ],
    [
      "plos",
      "/Biology and life sciences/Genetics"
    ],
    [
      "plos",
      "/Biology and life sciences/Genetics/Gene expression"
    ],
    [
      "plos",
      "/Biology and life sciences/Genetics/Genomics/Genome analysis/Transcriptome analysis"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Developmental neuroscience/Neurodevelopmental disorders/ADHD"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Body fluids/Blood"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Physiological parameters/Body weight"
    ],
    [
      "plos",
      "/Medicine and health sciences/Anatomy/Body fluids/Blood"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Neurodevelopmental disorders/ADHD"
    ],
    [
      "plos",
      "/Medicine and health sciences/Mental health and psychiatry/Neuropsychiatric disorders/ADHD"
    ],
    [
      "plos",
      "/Medicine and health sciences/Neurology/Neurodevelopmental disorders/ADHD"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Discrete mathematics/Combinatorics/Permutation"
    ]
  ],
  "openalex": "W7220395650",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0359656&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-05",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/ejn95g9e9y2hm.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:37Z",
      "native_id": "10.1371/journal.pone.0359656",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0359656"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:genetics",
      "subfield": "genetics-genomics"
    },
    {
      "field": "medicine",
      "origin": "plos:anatomy",
      "subfield": "physiology"
    }
  ],
  "title": "Rigorous validation of graph-based network analysis reappraises biologically coherent ADHD-associated transcriptomic modules in peripheral blood",
  "title_text": "Rigorous validation of graph-based network analysis reappraises biologically coherent ADHD-associated transcriptomic modules in peripheral blood",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:37Z",
  "url": "https://research.draconitic.com/paper/ejn95g9e9y2hm",
  "venue": "PLOS One",
  "versions": []
}