Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 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.
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
17 authors.
Jack F V HuntDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.ORCID 0000-0002-5719-9028
Erik J BuchholzDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.
Carol E FranzDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.ORCID 0000-0002-8987-1755
Chandra A ReynoldsInstitute for Behavioral Genetics and Department of Psychology & Neuroscience, University of Colorado, Boulder, Colorado, United States.ORCID 0000-0001-6502-7173
Matthew S PanizzonDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.
McKenna E WilliamsDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.
Tyler R BellDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.ORCID 0000-0001-5702-5995
Rongxiang TangCenter for Behavior Genetics of Aging, University of California, La Jolla, San Diego, California, United States.ORCID 0000-0003-0406-9024
Donald J HaglerDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.
Nathan GillespieVirginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Virginia, United States.ORCID 0000-0001-8655-2823
Jeremy A ElmanDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.ORCID 0000-0002-5840-1769
Michael C NealeVirginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Virginia, United States.
Stephen DorrosDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.
Anders M DaleCenter for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California, United States.
William S KremenDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.ORCID 0000-0002-8629-5609
Christine Fennema-NotestineDepartment of Psychiatry, University of California San Diego, La Jolla, California, United States.
Vietnam Era Twin Study of Aging
Funding
The VETSA Longitudinal Twin Study of Cognition and Aging (VETSA 4)R01AG050595 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELMAN, JEREMY A, FRANZ, CAROL ELAINE · 2015 to 2024
$28.0M
Urban Air Pollution and Pathological Brain Aging: A Nationwide Twin Study in MenP01AG055367 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MACK, WILLIAM J · 2018 to 2022
$11.5M
The VETSA Longitudinal MRI Twin Study of Aging (VETSA MRI 4)R01AG076838 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE, Jeremy A Elman · 2022 to 2026
$8.7M
Genetic Predictors, Transcriptomic Biomarkers, & Neurobiological Signatures of Resilience to Alzheimer's DiseaseR01AG064955 · NIA · UPSTATE MEDICAL UNIVERSITY · PI FENNEMA-NOTESTINE, CHRISTINE, GLATT, STEPHEN J · 2019 to 2023
$3.8M
Gene-Environment Interplay of Social Contexts and Aging-Related OutcomesR01AG037985 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PEDERSEN, NANCY L · 2010 to 2014
$3.2M
Psychiatry Research Residency Training TrackR25MH101072 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NEAL R SWERDLOW · 2013 to 2026
$2.8M
Linking genetic subtypes of Alzheimer's disease to biological and cognitive heterogeneityK01AG063805 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELMAN, JEREMY A · 2021 to 2024
$516k
Chronic Pain and Risk of Alzheimer's-Related NeurodegenerationK01AG081559 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Tyler Reed Bell · 2023 to 2026
$505k
Brain Connectomics of Cognitive Aging and Vulnerability to Alzheimer's DiseaseK01AG084815 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI RONGXIANG TANG · 2024 to 2026
$385k
National Institute on Aging, National Institutes of HealthNIA NIH HHS K01 AG063805NIA NIH HHS K01 AG081559NIA NIH HHS K01 AG084815NIA NIH HHS P01 AG055367NIA NIH HHS R01 AG037985NIA NIH HHS R01 AG050595NIA NIH HHS R01 AG064955NIA NIH HHS R01 AG076838NIMH NIH HHS R25 MH101072Veteran's Administration
6 · The paper itself
Abstract
backgroundCumulative deficit frailty (CDF) is a syndrome characterized by the accumulation of negative physical, functional and psychosocial insults. Accumulation of CDF and changes in brain structure both occur during the transition to older age and are associated with the development of Alzheimer's disease (AD) and related dementias. However, how these phenomena are temporally related to each other during the aging process is not well understood.
methodsWe examined bidirectional relationships between CDF and brain structure using structural MRI-based brain-predicted age difference and an AD brain signature. Longitudinal MRI and questionnaire-based data were collected from men in the Vietnam Era Twin Study of Aging at three study waves (average ages 56, 62, and 68).
resultsBest-fitting longitudinal random intercepts cross-lagged panel models support the strong overall association between CDF and brain structural integrity with significant covariance between random intercepts for CDF and brain-predicted age difference (r = 0.36, p < .001) and between CDF and AD brain signature (r = -0.16, p = .005) after controlling for chronological age, smoking, race/ethnicity, and education. Significant bidirectional negative cross-lagged associations suggested attenuation over time of the association between CDF and nonspecific brain aging (βs = -0.33 to -0.23, p ≤ .012) but not between CDF and AD brain signature.
conclusionsCDF was associated with age-related brain structure via strong time-invariant common variance as well as weaker across-time factors. By contrast, the association between CDF and AD-related brain structure was via moderate common variance and was not temporally dynamic. Together, this suggests that CDF is differentially associated with age-related and AD-related brain changes and may be a clinically relevant risk factor for pathological brain aging.
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.
Association of cumulative deficit frailty with brain age and Alzheimer's disease-related brain structure starting in late-middle age. · full record | OpenQuestion