Evidence map›Paper›PMID 35604444›Full record

ReviewBrain structure & function2022

Aging and white matter microstructure and macrostructure: a longitudinal multi-site diffusion MRI study of 1218 participants.

Kurt G Schilling, Derek Archer, Fang-Cheng Yeh, Francois Rheault, Leon Y Cai, Colin Hansen, Qi Yang, Karthik Ramdass, Andrea T Shafer, Susan M Resnick and 7 more

Abstract readReview
In one paragraph

Review in Brain structure & function, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing 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

61 citing papers in PubMed.

  1. Article
  2. White matter reflects the childhood exposome.bioRxiv : the preprint server for biology · 2026
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  16. ArXiv · 2025
    Article
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1 more citing papers are in PubMed but not listed here.

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

17 authors.

Kurt G SchillingDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA. kurt.g.schilling.1@vumc.org.ORCID http://orcid.org/0000-0003-3686-7645
Derek ArcherVanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Fang-Cheng YehDepartment of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Francois RheaultDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Leon Y CaiDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Colin HansenDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Qi YangDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Karthik RamdassDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Andrea T ShaferLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Susan M ResnickLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Kimberly R PechmanVanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Katherine A GiffordVanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Timothy J HohmanVanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Angela JeffersonVanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Adam W AndersonDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
Hakmook KangDepartment of Biostatistics, Vanderbilt University, Nashville, TN, USA.
Bennett A LandmanDepartment of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.

Funding

VANDERBILT UNIVERSITY CTSA FOR PEDIATRIC RESEARCHUL1RR024975 · NCRR · VANDERBILT UNIVERSITY · PI BERNARD, GORDON RAPHAEL · 2007 to 2011
$45.7M
Neuroimaging Predictors of Cognitive Decline, Impairment, and ResilienceZIAAG000191 · NIA · NATIONAL INSTITUTE ON AGING · PI FERRUCCI, LUIGI · 2009 to 2025
$26.4M
Vanderbilt Memory & Aging ProjectR01AG034962 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI JEFFERSON, ANGELA L. · 2011 to 2025
$24.1M
Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRIR01EB017230 · NIBIB · VANDERBILT UNIVERSITY · PI LANDMAN, BENNETT A. · 2015 to 2024
$5.1M
Genetic Contributors to White Matter Microstructure in Aging and Alzheimer’s DiseaseK01AG073584 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ARCHER, DEREK B · 2021 to 2025
$601k
NCRR NIH HHS UL1 RR024975NIA NIH HHS K01 AG073584NIA NIH HHS L30 AG060964NIA NIH HHS R01 AG034962NIBIB NIH HHS R01 EB017230
6 · The paper itself

Abstract

Quantifying the microstructural and macrostructural geometrical features of the human brain's connections is necessary for understanding normal aging and disease. Here, we examine brain white matter diffusion magnetic resonance imaging data from one cross-sectional and two longitudinal data sets totaling in 1218 subjects and 2459 sessions of people aged 50-97 years. Data was drawn from well-established cohorts, including the Baltimore Longitudinal Study of Aging data set, Cambridge Centre for Ageing Neuroscience data set, and the Vanderbilt Memory & Aging Project. Quantifying 4 microstructural features and, for the first time, 11 macrostructure-based features of volume, area, and length across 120 white matter pathways, we apply linear mixed effect modeling to investigate changes in pathway-specific features over time, and document large age associations within white matter. Conventional diffusion tensor microstructure indices are the most age-sensitive measures, with positive age associations for diffusivities and negative age associations with anisotropies, with similar patterns observed across all pathways. Similarly, pathway shape measures also change with age, with negative age associations for most length, surface area, and volume-based features. A particularly novel finding of this study is that while trends were homogeneous throughout the brain for microstructure features, macrostructural features demonstrated heterogeneity across pathways, whereby several projection, thalamic, and commissural tracts exhibited more decline with age compared to association and limbic tracts. The findings from this large-scale study provide a comprehensive overview of the age-related decline in white matter and demonstrate that macrostructural features may be more sensitive to heterogeneous white matter decline. Therefore, leveraging macrostructural features may be useful for studying aging and could facilitate comparisons in a variety of diseases or abnormal conditions.

Indexed as

White MatterAgingBrainCross-Sectional StudiesDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingHumansLongitudinal StudiesAgingDiffusion MRITractographyVolumeWhite matter

Identifiers

PMID35604444
PMCPMC9648053

What OpenQuestion holds

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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.