Evidence map›Paper›PMID 40832377›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Axonal Degeneration Across the Alzheimer's Disease Spectrum: A Longitudinal MRI and Fluid Biomarker Study.

Zhaoyuan Gong, John P Laporte, Alexander Y Guo, Jonghyun Bae, Noam Y Fox, Angelique de Rouen, Nathan Zhang, Aaliya Taranath, Rafael de Cabo, Josephine M Egan and 3 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Zhaoyuan GongNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
John P LaporteNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Alexander Y GuoNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Jonghyun BaeNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Noam Y FoxNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Angelique de RouenNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Nathan ZhangNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Aaliya TaranathNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Rafael de CaboNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Josephine M EganNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Luigi FerrucciNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Mustapha BouhraraNational Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Alzheimer’s Disease Neuroimaging Initiative

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

With global dementia rates rising sharply, there is an urgent need for sensitive biomarkers to detect cognitive changes and predict dementia risk. White matter degeneration, especially axonal loss, is increasingly recognized as an early hallmark of Alzheimer's disease (AD), but its temporal trajectory and its relationship with cognition have not been established. We utilized a novel MRI-derived Axonal Density Index (ADI) to longitudinally investigate axonal degeneration and cognitive decline in the ADNI cohort. Linear mixed-effects models showed cognitively impaired individuals had lower baseline ADI and faster axonal degeneration compared to cognitively normal subjects. In cognitively impaired individuals, higher baseline ADI predicted slower prospective cognitive deterioration and lower dementia risk, while greater longitudinal ADI declines correlated with cognitive worsening and increased dementia risk. Notably, ADI outperformed cerebrospinal fluid biomarkers of AD pathology in predicting cognitive outcomes. Our original findings position axonal degeneration as an early AD feature and ADI as a promising biomarker for early detection, disease phenotyping and monitoring, and intervention targets.

Identifiers

PMID40832377
PMCPMC12363713

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.