Evidence map›Paper›PMID 35142033›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2022

Race, sex, and mid-life changes in brain health: Cardia MRI substudy.

Justine E F Moonen, Ilya M Nasrallah, John A Detre, Sudipto Dolui, Guray Erus, Christos Davatzikos, Osorio Meirelles, R Nick Bryan, Lenore J Launer

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Posterior communicating artery variation is linked to compromised cerebral hemodynamics in middle-aged and older adults.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
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  12. Race, sex, and mid-life changes in brain health: Cardia MRI substudy.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2022
    Article
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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

9 authors.

Justine E F MoonenNational Institute on Aging, National Institute of Health, LEPS/IRP/NIA/NIH, Laboratory of Epidemiology and Population Sciences, Baltimore, Maryland, USA.ORCID 0000-0001-8260-8762
Ilya M NasrallahDepartment of Radiology, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA.ORCID 0000-0003-2346-7562
John A DetreDepartment of Radiology, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA.ORCID 0000-0002-8115-6343
Sudipto DoluiDepartment of Radiology, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA.ORCID 0000-0002-9035-3795
Guray ErusDepartment of Radiology, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA.ORCID 0000-0001-6633-4861
Christos DavatzikosCenter for Biomedical Image Computing and Analytics, Perelman School for Advanced Medicine, Philadelphia, Pennsylvania, USA.ORCID 0000-0002-1025-8561
Osorio MeirellesNational Institute on Aging, National Institute of Health, LEPS/IRP/NIA/NIH, Laboratory of Epidemiology and Population Sciences, Baltimore, Maryland, USA.ORCID 0000-0002-1124-5113
R Nick BryanDepartment of Radiology, University of Texas Medical Branch, Galveston, Texas, USA.ORCID 0000-0002-2327-4579
Lenore J LaunerNational Institute on Aging, National Institute of Health, LEPS/IRP/NIA/NIH, Laboratory of Epidemiology and Population Sciences, Baltimore, Maryland, USA.ORCID 0000-0002-3238-7612

Funding

statistics coreP30NS045839 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DETRE, JOHN A · 2003 to 2017
$10.1M
Machine Learning and Large-scale Imaging analytics for dimensional representations of brain trajectories in aging and preclinical Alzheimer's Disease: The brain aging chart and the iSTAGING consortiumRF1AG054409 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVATZIKOS, CHRISTOS · 2017 to 2023
$6.3M
CLINICAL PROJECT: Age, Gene/Environment Susceptibility Study on the Multi-omics of Aging: A clinical epidemiologic prospective studyZIAAG007380 · NIA · NATIONAL INSTITUTE ON AGING · PI LAUNER, LENORE J · 2009 to 2025
$6.1M
CARDIA Year 35 Brain MRI RenewalR01AG062819 · NIA · UNIVERSITY OF PENNSYLVANIA · PI BRYAN, R N · 2019 to 2022
$4.8M
Neurologic Clinical Epidemiology Training ProgramT32NS061779 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Andrea Lauren Christman Schneider, Allison Willis · 2008 to 2026
$4.6M
Health, Aging and Body Composition StudyZIAAG007390 · NIA · NATIONAL INSTITUTE ON AGING · PI LAUNER, LENORE J · 2009 to 2024
$4.0M
Perfusion MRI for Multi-site Studies of Brain FunctionR01MH080729 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI ALSOP, DAVID CHARLES, DETRE, JOHN A · 2007 to 2017
$3.8M
Novel Biomarkers of Small Vessel Contributions to Vascular Cognitive Impairment and Dementia (VCID)R01NS111115 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DETRE, JOHN A, WANG, JIANHUA · 2019 to 2023
$3.7M
Research Training Program in Disease Oriented Neuroscience (R25)R25NS065745 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DETRE, JOHN A · 2009 to 2023
$3.0M
Genetic Markers of Brain AgingZIAAG007270 · NIA · NATIONAL INSTITUTE ON AGING · PI LAUNER, LENORE J · 2009 to 2025
$2.7M
Brain aging and cardiovascular risk factors and diseaseZIAAG007480 · NIA · NATIONAL INSTITUTE ON AGING · PI LAUNER, LENORE J · 2011 to 2025
$2.7M
Diabetes and the brainZIAAG007420 · NIA · NATIONAL INSTITUTE ON AGING · PI LAUNER, LENORE J · 2009 to 2021
$2.1M
Intramural NIH HHS Z01 AG007230Intramural NIH HHS Z01 AG007270Intramural NIH HHS Z01 AG007280Intramural NIH HHS Z01 AG007380Intramural NIH HHS Z01 AG007420Intramural NIH HHS ZIA AG000521Intramural NIH HHS ZIA AG001050Intramural NIH HHS ZIA AG001057Intramural NIH HHS ZIA AG006000Intramural NIH HHS ZIA AG007260Intramural NIH HHS ZIA AG007270Intramural NIH HHS ZIA AG007280Intramural NIH HHS ZIA AG007380Intramural NIH HHS ZIA AG007390Intramural NIH HHS ZIA AG007420Intramural NIH HHS ZIA AG007470Intramural NIH HHS ZIA AG007480NIA NIH HHS N01 AG032124NIA NIH HHS R01 AG062819NIA NIH HHS R03 AG063213NIA NIH HHS R21 AG070434NIA NIH HHS RF1 AG054409NIDA NIH HHS R01 DA015149NIH HHS S10 OD023495NIMH NIH HHS R01 MH080729NINDS NIH HHS F30 NS046103NINDS NIH HHS K24 NS058386NINDS NIH HHS P30 NS045839NINDS NIH HHS R01 NS037488NINDS NIH HHS R01 NS111115NINDS NIH HHS R25 NS065745NINDS NIH HHS T32 NS054575NINDS NIH HHS T32 NS061779
6 · The paper itself

Abstract

objectiveTo examine longitudinal race and sex differences in mid-life brain health and to evaluate whether cardiovascular health (CVH) or apolipoprotein E (APOE) ε4 explain differences.

methodsThe study included 478 Black and White participants (mean age: 50 years). Total (TBV), gray (GMV), white (WMV), and white matter hyperintensity (WMH) volumes and GM-cerebral blood flow (CBF) were acquired with 3T-magnetic resonance imaging at baseline and 5-year follow-up. Analyses were based on general linear models.

resultsThere were race x sex interactions for GMV (P-interaction = .004) and CBF (P-interaction = .01) such that men showed more decline than women, and this was most evident in Blacks. Blacks compared to Whites had a significantly greater increase in WMH (P = .002). All sex-race differences in change were marginally attenuated by CVH and APOE ε4.

conclusionRace-sex differences in brain health emerge by mid-life. Identifying new environmental factors beyond CVH is needed to develop early interventions to maintain brain health.

Indexed as

CardiaWhite MatterApolipoprotein E4BrainFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedQuality of LifeApolipoprotein E4brain healthcardiovascular healthmagnetic resonance imagingracesex

Identifiers

PMID35142033
PMCPMC9360196

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.