Evidence map›Paper›PMID 40671553›Full record

ArticleJournal of Alzheimer's disease : JAD2025

Neural flexibility is higher in Alzheimer's disease and predicts Alzheimer's disease transition.

Eleanna Varangis, Jun Liu, Yuqi Miao, Xi Zhu, Yaakov Stern, Seonjoo Lee, For Alzheimer's Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Eleanna VarangisSchool of Kinesiology University of Michigan, Ann Arbor, MI, USA.
Jun LiuMental Health Data Science, New York State Psychiatric Institute, New York, NY, USA.
Yuqi MiaoDepartment of Biostatistics, Columbia University, New York, NY, USA.
Xi ZhuMental Health Data Science, New York State Psychiatric Institute, New York, NY, USA.
Yaakov SternDepartment of Neurology, Columbia University, New York, NY, USA.ORCID 0000-0001-7542-3241
Seonjoo LeeMental Health Data Science, New York State Psychiatric Institute, New York, NY, USA.ORCID 0000-0003-3177-6357
For 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
Statistical method for neural mechanism mediating and moderating cognitive system in Alzheimer's disease and aging research.R01AG062578 · NIA · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI LEE, SEONJOO · 2020 to 2024
$2.1M
Identification of Distinct Multimodal Biotypes of PTSD Using Data Driven Approach: A Multisite Big Data StudyK01MH122774 · NIMH · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI ZHU, XI · 2021 to 2024
$705k
NIA NIH HHS R01 AG062578NIA NIH HHS U01 AG024904NIMH NIH HHS K01 MH122774
6 · The paper itself

Abstract

BackgroundNeural flexibility (NF), a measure of dynamic functional connectivity, was associated with psychiatric diseases but has not yet been studied in Alzheimer's disease (AD).ObjectiveWe aim to evaluate whether AD is associated with alterations in NF and probe its predictive utility for AD conversion.MethodThe study included 862 older adults (461 cognitively normal (CN), 294 mild cognitive impairment (MCI), 107 AD) with valid resting-state fMRI data from the Alzheimer's Disease Neuroimaging Initiative. We defined the NF of a node as the number of times that a node changed its community assignment across the sliding windows, normalized by the total number of possible changes. We computed global NF and 12 functional network-specific NFs, then performed linear mixed models on NFs separately to explore the differences in these measures between our three groups. Finally, we evaluated the predictive utility of NF on dementia transition using survival analysis.ResultsNF is significantly higher in AD than CN on global NF (β = 0.002, 95% CI 0.001 to 0.004), and NF in six networks, and NF is significantly higher in MCI than CN in the visual network. Among n = 617 non-demented participants at baseline, n = 53 (8.6%) participants converted to dementia during the follow-up visits. Higher NF in the visual network was positively associated with AD transition (HR = 1.323, 95%CI 1.002 to 1.747, p = 0.049, per 1 SD in NF), controlling for age, gender, and education.ConclusionsWe found that NF during rest was higher in AD patients and predicted dementia transition. Thus, NF may be a valuable biomarker of AD; however, more validation and mechanistic studies need to be performed.

Indexed as

Alzheimer DiseaseBrainCognitive DysfunctionAgedAged, 80 and overDisease ProgressionFemaleHumansMagnetic Resonance ImagingMaleAlzheimer's diseasedynamic functional connectivitygraph-theoryneural flexibility

Identifiers

PMID40671553
PMCPMC12823133

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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.