{
  "abstract": "Neuroimaging is a widely used modality for characterizing neurodegeneration in various health conditions. Brain age gap has emerged as a promising biomarker for monitoring brain health from neuroimaging data using machine learning algorithms. Recent studies have leveraged coVariance neural networks (VNN)-driven pipelines based on the advancements in graph signal processing for relatively transparent construction of brain age gap from neuroimaging data. In this paper, we focus on a longitudinal study of VNN-based brain age gap in conjunction with Alzheimer's Progression Score (APS) in individuals that are at a higher risk of neurodegeneration due to family history of Alzheimer's disease. APS is a multimodal marker of disease progression. The longitudinal analysis of APS and VNN-derived brain age gap metrics revealed that a higher risk of disease progression at baseline predicted a larger rate of increase in brain age gap in follow-up visits. Thus, our findings revealed potential stratification in the brain age gap modulated by clinical/biological risks of AD in the at-risk population.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.18794",
  "author_total": 2,
  "authors": [
    {
      "name": "Jason Scheffel"
    },
    {
      "name": "Saurabh Sihag"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7bwcsqgqjbqxp.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.18794",
  "fulltext_url": null,
  "id": "7bwcsqgqjbqxp",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.18794",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "q-bio.QM"
    ],
    [
      "openalex",
      "2738|Dementia and Cognitive Impairment Research"
    ]
  ],
  "openalex": "W7221748199",
  "pdf_url": "https://arxiv.org/pdf/2610.18794",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-13",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7bwcsqgqjbqxp.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:21Z",
      "native_id": "2610.18794",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.18794"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "arxiv:q-bio.QM",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Brain Age Gap Progression in Individuals at Risk for Neurodegeneration",
  "title_text": "Brain Age Gap Progression in Individuals at Risk for Neurodegeneration",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:21Z",
  "url": "https://research.draconitic.com/paper/7bwcsqgqjbqxp",
  "venue": "arXiv",
  "versions": []
}