Evidence map›Paper›PMID 40894794›Full record

ArticlebioRxiv : the preprint server for biology2025

White matter microstructure changes across the lifespan: a meta-analysis of longitudinal diffusion MRI studies.

Karis Colyer-Patel, Jalmar Teeuw, Vivien Maes, Vera Goossens, Rachel M Brouwer, Neda Jahanshad, Paul M Thompson, Hilleke E Hulshoff Pol

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Karis Colyer-PatelUniversity Medical Center Utrecht, UMC Brain Center, Department of Psychiatry, Utrecht, The Netherlands.ORCID 0000-0002-6093-1507
Jalmar TeeuwUniversity Medical Center Utrecht, UMC Brain Center, Department of Psychiatry, Utrecht, The Netherlands.ORCID 0000-0002-1637-888X
Vivien MaesUtrecht University, Department of Experimental Psychology, Helmholtz Institute, Utrecht, The Netherlands.
Vera GoossensUtrecht University, Department of Experimental Psychology, Helmholtz Institute, Utrecht, The Netherlands.ORCID 0009-0001-9374-3086
Rachel M BrouwerDepartment of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, The Netherlands.ORCID 0000-0002-7466-1544
Neda JahanshadImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.ORCID 0000-0003-4401-8950
Paul M ThompsonImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.ORCID 0000-0002-4720-8867
Hilleke E Hulshoff PolUniversity Medical Center Utrecht, UMC Brain Center, Department of Psychiatry, Utrecht, The Netherlands.ORCID 0000-0002-2038-5281

Funding

ENIGMA World Aging CenterR01AG058854 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2021 to 2025
$3.3M
NIA NIH HHS R01 AG058854
6 · The paper itself

Abstract

Background: White matter in the human brain is known to play a critical role in facilitating communication between different brain regions. White matter microstructure is often quantified using fractional anisotropy (FA) derived from diffusion-weighted MRI and is often considered a key measure of neural efficiency that is positively associated with motor and cognitive functioning. While lifespan trajectories of FA have been well studied in cross-sectional designs, it remains less clear how FA changes longitudinally with age across the lifespan, and whether the rates of change are influenced by genetic variation. Methods: We systematically reviewed the evidence of white matter changes, as measured by fractional anisotropy (FA) with diffusion magnetic resonance imaging longitudinally across the lifespan, and the genetic influences on this change. Searches were conducted in Medline, PsycInfo, and EMBASE up to August 2023 with terms related to DTI/FA and longitudinal/change. Following this, genetic-related search terms were applied to the results, and the search was broadened to include other measures of white matter change. Our systematic search resulted in 29 studies that met our criteria. In addition, 14 studies investigated genetic influences on FA change rates across the lifespan. A meta-regression using a thin-plate spline model was conducted to examine annual whole-brain FA change as a function of age. Results: Across childhood and adolescence, FA increased, and the rate of increase slowed into early adulthood. Between ages 20 and 35, changes in FA were not statistically significant. This was followed by a significant decline in FA between ages 36 and 50. The decreases plateaued between ages 51 and 61 and then continued at a slightly slower rate towards the upper end of the age range assessed (77 years). Average FA change per year relative to baseline assessment reached a maximum of +1.1% during development, and -0.6% per year, during ageing. Significant heritability was found for Conclusions: In conclusion, there are changes in white matter microstructure within individuals across the lifespan, with increases during childhood, adolescence and early adulthood, followed by a period of relative stability during early to mid-adulthood, and subsequent gradual declines from midlife onwards. Evidence is emerging for genetic influences on white matter changes over time, shaping individual trajectories.

Indexed as

braincandidate genediffusion tensor imagingfractional anisotropygeneticGWASheritabilitylongitudinalmeta-analysisnetwork connectivitysystematic reviewwhite matter

Identifiers

PMID40894794
PMCPMC12393443

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Registered trials

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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.