Evidence map›Paper›PMID 38517788›Full record

ArticleJournal of Alzheimer's disease : JAD2024

Longitudinal Relationship Between Brain Atrophy Patterns, Cognitive Decline, and Cerebrospinal Fluid Biomarkers in Alzheimer's Disease Explored by Orthonormal Projective Non-Negative Matrix Factorization.

Lan Shui, Dean Shibata, Kwun Chuen Gary Chan, Wenbo Zhang, Junhyoun Sung, David R Haynor, Alzheimer’s Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. From Stress to Synapse: The Neuronal Atrophy Pathway to Mood Dysregulation.International journal of molecular sciences · 2025
    Review
  3. 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 at 3 institutions in 1 country.

Lan ShuiDepartment of Biostatistics, University of Washington, Seattle, WA, USA.
Dean ShibataDepartment of Radiology, University of Washington, Seattle, WA, USA.
Kwun Chuen Gary ChanDepartment of Biostatistics, University of Washington, Seattle, WA, USA.
Wenbo ZhangDepartment of Statistics, University of California Irvine, CA, USA.
Junhyoun SungDepartment of Biostatistics, University of Washington, Seattle, WA, USA.
David R HaynorDepartment of Biostatistics, MD Anderson Cancer Center, Houston, TX, USA.
Alzheimer’s Disease Neuroimaging Initiative
University of Washington · USThe University of Texas MD Anderson Cancer Center · USUniversity of California, Irvine · US

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
CIHRNIA NIH HHS U01 AG024904NIA NIH HHS U24 AG072122
6 · The paper itself

Abstract

Background: Longitudinal magnetic resonance imaging (MRI) has been proposed for tracking the progression of Alzheimer's disease (AD) through the assessment of brain atrophy. Objective: Detection of brain atrophy patterns in patients with AD as the longitudinal disease tracker. Methods: We used a refined version of orthonormal projective non-negative matrix factorization (OPNMF) to identify six distinct spatial components of voxel-wise volume loss in the brains of 83 subjects with AD from the ADNI3 cohort relative to healthy young controls from the ABIDE study. We extracted non-negative coefficients representing subject-specific quantitative measures of regional atrophy. Coefficients of brain atrophy were compared to subjects with mild cognitive impairment and controls, to investigate the cross-sectional and longitudinal associations between AD biomarkers and regional atrophy severity in different groups. We further validated our results in an independent dataset from ADNI2. Results: The six non-overlapping atrophy components represent symmetric gray matter volume loss primarily in frontal, temporal, parietal and cerebellar regions. Atrophy in these regions was highly correlated with cognition both cross-sectionally and longitudinally, with medial temporal atrophy showing the strongest correlations. Subjects with elevated CSF levels of TAU and PTAU and lower baseline CSF Aβ42 values, demonstrated a tendency toward a more rapid increase of atrophy. Conclusions: The present study has applied a transferable method to characterize the imaging changes associated with AD through six spatially distinct atrophy components and correlated these atrophy patterns with cognitive changes and CSF biomarkers cross-sectionally and longitudinally, which may help us better understand the underlying pathology of AD.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAmyloid beta-PeptidesAtrophyBiomarkersBrainCross-Sectional StudiesHumansMagnetic Resonance ImagingNeuropsychological Teststau ProteinsAmyloid beta-PeptidesBiomarkerstau ProteinsAlzheimer’s diseasebiomarkersbrain atrophylongitudinal studiesmagnetic resonance imaging

Identifiers

PMID38517788
PMCPMC13183833
OpenAlexW4393080606

What OpenQuestion holds

Textmetadata
LicenceTDM
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.