Evidence map›Paper›PMID 41862396›Full record

ArticleThe American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry2026

Longitudinal Changes in White Matter Hypointensities in Recurrent Late-Life Depression.

Leigh B Pearcy, Ana Paula Costa, Meryl A Butters, Robert Krafty, Brian D Boyd, Layla Banihashemi, Sarah M Szymkowicz, Bennett A Landman, Olusola Ajilore, Warren D Taylor and 2 more

Abstract readMulticenter Study
In one paragraph

Article in The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry, 2026. 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

12 authors.

Leigh B PearcyDepartment of Psychiatry (LBP, APC, MAB, LB, CA, HTK), University of Pittsburgh, Pittsburgh, PA.
Ana Paula CostaDepartment of Psychiatry (LBP, APC, MAB, LB, CA, HTK), University of Pittsburgh, Pittsburgh, PA.
Meryl A ButtersDepartment of Psychiatry (LBP, APC, MAB, LB, CA, HTK), University of Pittsburgh, Pittsburgh, PA.
Robert KraftyDepartment of Biostatistics and Bioinformatics (RF), Emory University, Atlanta, GA.
Brian D BoydCenter for Cognitive Medicine (BDB, SMS, WDT), Department of Psychiatry and Behavioral Science, Vanderbilt University Medical Center, Nashville, TN.
Layla BanihashemiDepartment of Psychiatry (LBP, APC, MAB, LB, CA, HTK), University of Pittsburgh, Pittsburgh, PA; Department of Bioengineering (LB, HTK), University of Pittsburgh, Pittsburgh, PA.
Sarah M SzymkowiczCenter for Cognitive Medicine (BDB, SMS, WDT), Department of Psychiatry and Behavioral Science, Vanderbilt University Medical Center, Nashville, TN.
Bennett A LandmanDepartments of Computer Science, Electrical Engineering, and Biomedical Engineering (B.A.L.), Vanderbilt University, Nashville, TN; Department of Radiology and Radiological Sciences (B.A.L.), Vanderbilt University Medical Center, Nashville, TN.
Olusola AjiloreDepartment of Psychiatry (OA), University of Illinois-Chicago, Chicago, IL.
Warren D TaylorCenter for Cognitive Medicine (BDB, SMS, WDT), Department of Psychiatry and Behavioral Science, Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN.
Carmen AndreescuDepartment of Psychiatry (LBP, APC, MAB, LB, CA, HTK), University of Pittsburgh, Pittsburgh, PA.
Helmet T KarimDepartment of Psychiatry (LBP, APC, MAB, LB, CA, HTK), University of Pittsburgh, Pittsburgh, PA; Department of Bioengineering (LB, HTK), University of Pittsburgh, Pittsburgh, PA. Electronic address: karimht@upmc.edu.

Funding

Vanderbilt Institute for Clinical and Translational Research (VICTR) -Identifying correlates of functional immunity in SARS-CoV-2 convalescent plasmaUL1TR002243 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Paul A. Harris, Wesley H Self · 2017 to 2026
$130.7M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
CLINICAL RESEARCH TRAINING IN LATE-LIFE MOOD DISORDERST32MH019986 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOWARD J AIZENSTEIN, Carmen Andreescu · 1997 to 2026
$6.9M
1/3-Recurrence Markers, Cognitive Burden and Neurobiological Homeostasis in Late-life Depression (Rembrandt)R01MH121620 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI TAYLOR, WARREN D · 2020 to 2024
$5.3M
Recurrence markers, cognitive burden and neurobiological homeostasis in latelife depression (REMBRANDT) - SupplementR01MH121619 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ANDREESCU, CARMEN · 2020 to 2024
$5.1M
3/3-Recurrence markers, cognitive burden and neurobiological homeostasis in late-life depressionR01MH121384 · NIMH · UNIVERSITY OF ILLINOIS AT CHICAGO · PI AJILORE, OLUSOLA A. · 2020 to 2024
$3.0M
NCATS NIH HHS UL1 TR000445NCATS NIH HHS UL1 TR002243NIMH NIH HHS R01 MH121384NIMH NIH HHS R01 MH121619NIMH NIH HHS R01 MH121620NIMH NIH HHS T32 MH019986
6 · The paper itself

Abstract

backgroundWhite matter hypointensities (WMhs) on T1 and white matter hyperintensities (WMH) on T2-FLAIR are highly correlated and indicate elevated vascular risk in late-life depression (LLD). While larger baseline WMH are associated with depression recurrence, the literature is sparse regarding the longitudinal accumulation of WMh and its association with relapse in older adults.

methodsWe investigated the relationship between WMh and LLD recurrence over a 2-year multi-site study. T1 images were collected every 8 months from N = 223 participants, 157 with remitted LLD and 66 comparison participants (mean age 67.5 ± 4.92 years; 67.3% female). A total of 52% of participants in remission experienced relapse. WMh accumulation rates were analyzed across groups defined on relapse status using mixed effects modeling. We extracted individual measures of WMh and divided participants into four groups: baseline WMh load (low, high) x WMh accumulation (slow, rapid) to estimate differences in relapse risk using a Cox model.

resultsThe relapse groups were associated with greater baseline WMh than the non-depressed comparison group. WMh accumulation did not differ between non-depressed and remitted LLD participants (β = 0.009, 95% CI: -0.04 to 0.06). Compared to individuals with low baseline WMh and slow accumulation, individuals with high baseline WMh and rapid accumulation had a higher risk of relapse (HR = 2.92, 95% CI: 1.31-6.47).

conclusionGreater baseline WMh was associated with relapse after remission in LLD, but the rate of WMh progression was not. Patients with high baseline and rapidly accumulating WMh may warrant closer clinical monitoring due to increased risk of depression relapse.

Indexed as

White MatterAgedFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMaleRecurrencelate-life depressionmedical burdenrelapsesmall vessel diseaseWMH

Identifiers

PMID41862396
PMCPMC13290296

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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.