Evidence map›Paper›PMID 41222140›Full record

SynthesisHuman brain mapping2025

Spatial Dissociation of Atrophy and Hypophysiology in Alzheimer's Disease: Implications for Biomarkers.

Annie Dang, Di Wang, Jonathan M Towne, Sudha Seshadri, Mohamad Habes, Peter T Fox

Abstract readReviewMeta-Analysis
In one paragraph

Synthesis in Human brain mapping, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 2 pooled it
–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

2 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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

6 authors.

Annie DangResearch Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.ORCID 0000-0003-2968-5990
Di WangResearch Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Jonathan M TowneResearch Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.ORCID 0000-0002-2551-1566
Sudha SeshadriSouth Texas Medical Scientist Training Program, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Mohamad HabesResearch Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Peter T FoxResearch Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.ORCID 0000-0002-0465-2028

Funding

South Texas Alzheimer's Disease Research CenterP30AG066546 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Claudia Kimie Suemoto · 2021 to 2026
$24.0M
Institute for Integration of Medicine & Science: A Partnership to Improve HealthUM1TR004538 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI ROBERT A CLARK, Kenneth M Hargreaves · 2023 to 2026
$22.3M
Meta-anaylsis in human brain mappingR01MH074457 · NIMH · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FOX, PETER THORNTON · 2006 to 2024
$10.5M
South Texas Medical Scientist Training Program (STX-MSTP)T32GM145432 · NIGMS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Jose E Cavazos, Ratna K Vadlamudi · 2023 to 2026
$2.3M
South Texas Medical Scientist Training Program (STX-MSTP)T32GM113896 · NIGMS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI CAVAZOS, JOSE E · 2018 to 2022
$1.1M
CTSA Predoctoral T32 at The University of Texas Health Science Center at San AntonioT32TR004545 · NCATS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Yong-Hee Patricia Chun, Christopher R. Frei · 2023 to 2026
$1.1M
South Texas Alzheimer’s and Neurodegenerative Disorders Training ProgramT32AG082661 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Jose E Cavazos, PETER Thornton FOX · 2023 to 2026
$676k
Development and evaluation of neuroimaging biomarkers of structural and functional network degeneration in Alzheimer’s diseaseF30AG087698 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Annie Dang · 2025 to 2026
$83k
Establishing an Atrophy-Based Functional Network Model as a Biomarker for Seizure-Onset LateralityF31NS131025 · NINDS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI TOWNE, JONATHAN MICHAEL · 2023 to 2025
$76k
American Epilepsy SocietyNCATS NIH HHS T32 TR004545NCATS NIH HHS UM1 TR004538NIA NIH HHS F30 AG087698NIA NIH HHS P30 AG066546NIA NIH HHS T32 AG082661NIGMS NIH HHS T32 GM113896NIGMS NIH HHS T32 GM145432NIH HHS F30 AG087698NIH HHS F31NS131025NIH HHS P30 AG066546NIH HHS R01 MH074457NIH HHS T32 AG082661NIH HHS T32 GM113896NIH HHS T32 GM145432NIH HHS T32 TR004545NIMH NIH HHS R01 MH074457NINDS NIH HHS F31 NS131025
6 · The paper itself

Abstract

The Amyloid/Tau/Neurodegeneration (A/T/N) biomarker framework is used for in vivo pathological profiling of Alzheimer's disease. A binary (+/-) label is assigned for each pathology (A, T, N) based on its presence or absence as determined by imaging or fluid biomarkers. Using imaging, neurodegeneration is confirmed by either structural MRI (indicating atrophy) or 18F-FDG PET (indicating hypometabolism), implicitly assuming that both modalities identify equivalent pathology. Preliminary evidence suggests that atrophy and hypometabolism do not spatially co-localize and are likely caused by distinct underlying pathologies. Further, while MRI is widely available, many sites lack access to PET. Recent evidence indicates that hemodynamic indices, identified via functional MRI or SPECT, may be spatially concordant with hypometabolism identified by 18F-FDG-PET and able to serve as reliable proxies. Coordinate-based meta-analyses of voxel-based morphometry and voxel-based physiology reports in Alzheimer's disease, collectively analyzing 139 articles (4218 individuals) were performed to test the following hypotheses: (1) that atrophy and hypometabolism in AD are spatially dissociated; (2) that hemodynamic indices exhibit the same spatial distributions as hypometabolism identified by PET; (3) that regions of atrophy and hypometabolism involve different functional systems and cognitive operations. Results confirmed all three hypotheses. Separation of atrophy and hypometabolism into two distinct subcategories of neurodegeneration as well as the development of regionally specific biomarkers for each are in order.

Indexed as

Alzheimer DiseaseAtrophyBiomarkersHumansMagnetic Resonance ImagingNeuroimagingPositron-Emission TomographyBiomarkers

Identifiers

PMID41222140
PMCPMC12606587

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.