Evidence mapPaperPMID 41530554Full record

ReviewNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2026

Remission is insufficient: predictors and mechanistic models of recurrence in late-life depression.

Warren D Taylor, Andrew R Gerlach, Sarah M Szymkowicz, Swathi Gujral, Carmen Andreescu

Abstract readReview
In one paragraph

Review in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2026. 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. Neuropsychiatric illness in the later years of life: summary and synthesis.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Review
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

5 authors.

Warren D TaylorCenter for Cognitive Medicine, Department of Psychiatry and Behavioral Science, Vanderbilt University Medical Center, Nashville, TN, USA. warren.d.taylor@vumc.org.ORCID http://orcid.org/0000-0002-9975-3082
Andrew R GerlachDepartment of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0002-4022-1356
Sarah M SzymkowiczCenter for Cognitive Medicine, Department of Psychiatry and Behavioral Science, Vanderbilt University Medical Center, Nashville, TN, USA.
Swathi GujralDepartment of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
Carmen AndreescuDepartment of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0003-3767-5127

Funding

Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR002243 · VANDERBILT UNIVERSITY MEDICAL CENTER · 2025 to 2025
$10.7M
1/3-Recurrence Markers, Cognitive Burden and Neurobiological Homeostasis in Late-life Depression (Rembrandt)R01MH121620 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Patricia Serrano Andrews · 2022 to 2024
$2.8M
2/3: Recurrence markers, cognitive burden and neurobiological homeostasis in late-life depression (REMBRANDT)R01MH121619 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Carmen Andreescu · 2022 to 2024
$2.8M
Nicotinic Modulation of the Cognitive Control System in Late-Life DepressionR33MH122464 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · 2023 to 2025
$2.8M
The RAW Brain - The Effect of Rumination, Anxiety and Worry on Aging and Dementia RiskR01MH108509 · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2025 to 2025
$1.5M
Aerobic Exercise for Optimizing Cognitive and Brain Health In Remitted Late-Life DepressionK23MH125074 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2022 to 2025
$657k
Individual Multimodal Pathway Statistics for Predicting Treatment Response in Late-life DepressionK01MH133913 · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2025 to 2025
$177k
NCATS NIH HHS UL1 TR000445NCATS NIH HHS UL1 TR002243NIMH NIH HHS K01 MH133913NIMH NIH HHS K23 MH125074NIMH NIH HHS R01 MH108509NIMH NIH HHS R01 MH121619NIMH NIH HHS R01 MH121620NIMH NIH HHS R01 MH123662NIMH NIH HHS R33 MH122464
6 · The paper itself

Abstract

While achieving remission is the goal of acute antidepressant treatment, recurrence of new depressive episodes following remission is unfortunately common in clinical populations with Major Depressive Disorder, including older adults with Late-Life Depression (LLD). The neurobiological factors underlying this risk are poorly understood, limiting our ability to identify potential preventive mechanistic targets. Beyond the limited prognostic utility achieved from individual psychiatric history, it remains challenging to clinically stratify individual risk. This review examines factors influencing the recurrence of depressive episodes following remission in LLD, focusing on cognitive, behavioral, social, and environmental aspects. It additionally considers neuroimaging-based biomarkers related to recurrence risk as well as discussing evidence for and limits of maintenance treatment to prevent recurrence. The paper proposes possible mechanisms contributing to recurrence, including physiological and behavioral responses to stressors, the influence of Alzheimer's disease neuropathology, and conceptualizing repeat depressive episodes within the accelerated aging hypothesis of LLD. A dynamical landscape model of depression recurrence is proposed to elucidate the interplay between different mood states, resilience, and treatment response. This synthesis then highlights avenues for future research, focusing on areas of potential significance ranging from risk stratification to tertiary prevention efforts that may improve both long-term affective and cognitive symptoms.

Identifiers

PMID41530554
PMCPMC12888046

What Socratic 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 Socratic graph.