Evidence map›Paper›PMID 38961512›Full record

ArticleAlzheimer's research & therapy2024

Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration.

Rory Boyle, Diana L Townsend, Hannah M Klinger, Catherine E Scanlon, Ziwen Yuan, Gillian T Coughlan, Mabel Seto, Zahra Shirzadi, Wai-Ying Wendy Yau, Roos J Jutten and 19 more

Abstract read
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In one paragraph

Article in Alzheimer's research & therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Post-awakening cortisol and resilience: unravelling their impact on cognitive decline.Journal of neural transmission (Vienna, Austria : 1996) · 2025
    Article
  6. Article
  7. 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

29 authors.

Rory BoyleDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Diana L TownsendDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Hannah M KlingerDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Catherine E ScanlonDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Ziwen YuanDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Gillian T CoughlanDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Mabel SetoDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Zahra ShirzadiDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Wai-Ying Wendy YauDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Roos J JuttenDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Christoph SchneiderDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Michelle E FarrellDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Bernard J HanseeuwDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Elizabeth C MorminoDepartment of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Hyun-Sik YangDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Kathryn V PappDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Rebecca E AmariglioDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Heidi I L JacobsDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Julie C PriceDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Jasmeer P ChhatwalDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Aaron P SchultzDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Michael J ProperziDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Dorene M RentzDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Keith A JohnsonDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Reisa A SperlingDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Timothy J HohmanDepartment of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA.
Michael C DonohueAlzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA.
Rachel F BuckleyDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. rfbuckley@mgh.harvard.edu.
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
Vascular factors, physical activity, and inflammation as modulators of neurodegenerative and cognitive trajectories (Project 2)P01AG036694 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Hyun-Sik Yang · 2010 to 2026
$50.2M
MVP Data Integration into the ADSP Phenotype Harmonization ConsortiumU24AG074855 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CUCCARO, MICHAEL L, HOHMAN, TIMOTHY J · 2021 to 2025
$37.5M
Building predictive algorithms to identify resilience and resistance to Alzheimer's diseaseR01AG079142 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Rachel Frances Buckley, Michael C Donohue · 2023 to 2026
$4.0M
The inactive X: discovering sex genes that influence female vulnerability to Alzheimer's diseaseDP2AG082342 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Rachel Frances Buckley · 2022 to 2026
$2.5M
Elevated systolic blood pressure, body mass index, and amyloid as drivers of tau and cognitive decline in preclinical Alzheimers disease: critical windows in mid- to late-lifeK23AG084868 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Wai-Ying Wendy Yau · 2024 to 2026
$587k
National Institute on Aging,United States R01AG079142NIA NIH HHS K23 AG084868NIA NIH HHS P01 AG036694NIA NIH HHS P01AG036694NIA NIH HHS R01 AG079142NIA NIH HHS U01AG024904NIA NIH HHS U24 AG074855U.S. Department of Defense W81XWH-12-2-0012
6 · The paper itself

Abstract

backgroundLeveraging Alzheimer's disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomarkers of amyloid, tau and neurodegeneration, to a sample of cognitively unimpaired older adults to identify longitudinal trajectories of CR.

methodsWe identified 200 Harvard Aging Brain Study (HABS) participants (mean age = 71.89 years, SD = 9.41 years, 59% women) who were cognitively unimpaired at baseline with 2 or more timepoints of cognitive assessment following a single amyloid-PET, tau-PET and structural MRI. We examined latent class mixture models with longitudinal cognition as the dependent variable and time from baseline, baseline age, sex, neocortical Aβ, entorhinal tau, and adjusted hippocampal volume as independent variables. We then examined group differences in CR-related factors across the identified subgroups from a favored model. Finally, we applied our favored model to a dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 160, mean age = 73.9 years, SD = 7.6 years, 60% women).

resultsThe favored model identified 3 latent subgroups, which we labelled as Normal (71% of HABS sample), Resilient (22.5%) and Declining (6.5%) subgroups. The Resilient subgroup exhibited higher baseline cognitive performance and a stable cognitive slope. They were differentiated from other groups by higher levels of verbal intelligence and past cognitive activity. In ADNI, this model identified a larger Normal subgroup (88.1%), a smaller Resilient subgroup (6.3%) and a Declining group (5.6%) with a lower cognitive baseline.

conclusionThese findings demonstrate the value of data-driven approaches to identify longitudinal CR groups in preclinical AD. With such an approach, we identified a CR subgroup who reflected expected characteristics based on previous literature, higher levels of verbal intelligence and past cognitive activity.

Indexed as

Magnetic Resonance ImagingPositron-Emission Tomographytau ProteinsAgedAged, 80 and overAlzheimer DiseaseAmyloid beta-PeptidesBiomarkersBrainCognitionCognitive DysfunctionCognitive ReserveCross-Sectional StudiesFemaleHumansLongitudinal StudiesAmyloid beta-PeptidesBiomarkerstau ProteinsAlzheimer’s diseaseAmyloidCognitionCognitive ReserveCognitive ResilienceLongitudinal analysisMRIPETTau

Identifiers

PMID38961512
PMCPMC11220971

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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.