{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T05:48:59Z","timestamp":1782280139017,"version":"3.54.5"},"posted":{"date-parts":[[2024,12,13]]},"group-title":"Neuroscience","reference-count":0,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2024,12,13]],"date-time":"2024-12-13T00:00:00Z","timestamp":1734048000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2024,12,13]]},"abstract":"<jats:p>The deposition of amyloid-beta protein in the human brain is a hallmark of Alzheimer's disease and is related to cognitive decline. However, the relationship between early amyloid-beta deposition and future cognitive impairment remains poorly understood, particularly concerning its spatial distribution and network-level effects. Here, we employed a cross-validated machine learning approach and investigated whether integrating subject-specific brain connectome information with amyloid-beta burden measures improves predictive validity for subsequent cognitive decline. Baseline regional amyloid-beta pathology measures from positron emission tomography (PET) imaging predicted prospective cognitive decline. Incorporating structural connectome, but not functional connectome, information into the amyloid-beta measures improved predictive performance. We further identified a neuropathological signature pattern linked to future cognitive decline, which was validated in an independent cohort. These findings advance our understanding of how amyloid-beta pathology relates to brain networks and highlight the potential of network-based metrics for amyloid-beta-PET imaging to identify individuals at higher risk of cognitive decline.<\/jats:p>","DOI":"10.1101\/2024.12.10.627818","type":"posted-content","created":{"date-parts":[[2024,12,14]],"date-time":"2024-12-14T04:25:13Z","timestamp":1734150313000},"source":"Crossref","is-referenced-by-count":1,"title":["Network-based amyloid-beta pathology predicts subsequent cognitive decline in cognitively normal older adults"],"prefix":"10.64898","author":[{"given":"Hengda","family":"He","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9588-8062","authenticated-orcid":false,"given":"Qolamreza R","family":"Razlighi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunglin","family":"Gazes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Habeck","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaakov","family":"Stern","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"the Alzheimer's Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1101\/2024.12.10.627818","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T04:57:46Z","timestamp":1782277066000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.1101\/2024.12.10.627818"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,13]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1101\/2024.12.10.627818","relation":{"is-preprint-of":[{"id-type":"doi","id":"10.1038\/s43856-025-01170-5","asserted-by":"subject"}]},"subject":[],"published":{"date-parts":[[2024,12,13]]},"subtype":"preprint"}}