Accelerated changes in white matter microstructure during aging: a longitudinal diffusion tensor imaging study - PubMed (original) (raw)
Accelerated changes in white matter microstructure during aging: a longitudinal diffusion tensor imaging study
Claire E Sexton et al. J Neurosci. 2014.
Abstract
It is well established that human brain white matter structure changes with aging, but the timescale and spatial distribution of this change remain uncertain. Cross-sectional diffusion tensor imaging (DTI) studies indicate that, after a period of relative stability during adulthood, there is an accelerated decline in anisotropy and increase in diffusivity values during senescence; and, spatially, results have been discussed within the context of several anatomical frameworks. However, inferring trajectories of change from cross-sectional data can be challenging; and, as yet, there have been no longitudinal reports of the timescale and spatial distribution of age-related white matter change in healthy adults across the adult lifespan. In a longitudinal DTI study of 203 adults between 20 and 84 years of age, we used tract-based spatial statistics to characterize the pattern of annual change in fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity and examined whether there was an acceleration of change with age. We found extensive and overlapping significant annual decreases in fractional anisotropy, and increases in axial diffusivity, radial diffusivity, and mean diffusivity. Spatially, results were consistent with inferior-to-superior gradients of lesser-to-greater vulnerability. Annual change increased with age, particularly within superior regions, with age-related decline estimated to begin in the fifth decade. Charting white matter microstructural changes in healthy aging provides essential context to clinical studies, and future studies should compare age trajectories between healthy participants and at-risk populations and also explore the relationship between DTI rates of change and cognitive decline.
Keywords: DTI; aging; lifespan; longitudinal; white matter.
Copyright © 2014 the authors 0270-6474/14/3415425-12$15.00/0.
Figures
Figure 1.
ROIs and anatomy of slice-by-slice profiles. Top, ROIs for the frontal (blue), parietal (pink), occipital (green), and temporal (yellow) ROI are displayed, overlaid on a white skeleton. Bottom, The center of gravity across each coronal and axial slice is plotted for global (black), frontal (blue), parietal (pink), occipital (green), and temporal (yellow) ROI.
Figure 2.
Slice-by-slice profiles of annual change. Annual change in FA, AD, RD, and MD is plotted for each coronal and axial slice within global (black), frontal (blue), parietal (pink), occipital (green), and temporal (yellow) ROI. FA values are × 10−3; AD, RD, and MD values are mm2 s−1 × 10−6.
Figure 3.
Pattern of annual change: decrease in FA and increase in AD, RD, and MD. Voxels displaying a significant (p < 0.05, after correction for multiple comparisons across space) annual decrease in FA (blue), increase in AD (yellow), increase in RD (red), and increase in MD (gray), dilated for illustrative purposes, are overlaid on a green skeleton. x, y, and z coordinates in MNI space are indicated at the top of each column.
Figure 4.
Pattern of annual change: slice-by-slice profiles of mean t statistic. The mean, uncorrected, t statistic for analyses of annual change in FA, AD, RD, and MD is plotted for each coronal and axial slice within global (black), frontal (blue), parietal (pink), occipital (green), and temporal (yellow) ROI.
Figure 5.
Overlap of voxels showing significant change. Overlap of significant voxels. A, Pattern of annual change in DTI parameters. Overlap between voxels displaying a significant (p < 0.05, after correction for multiple comparisons across space) annual decrease in FA, increase in AD, or increase in RD is illustrated. Different segments indicate proportion of voxels showing change in FA only (blue), FA and RD (purple), RD only (red), RD and AD (yellow), AD only (green), and FA, RD, and AD (white). Voxels that did not display a significant decrease in FA, increase in AD, or increase in RD (30% of all skeleton voxels) are not represented in this figure. B, Acceleration of annual change in DTI parameters. Overlap between voxels displaying a significant correlation between age and annual decrease in FA, increase in AD, or increase in RD is shown, with color coding as for A. Voxels that did not display a significant correlation with FA, AD, or RD (37% of all skeleton voxels) are not represented in this figure.
Figure 6.
Pattern of annual change: increase in FA and decrease in AD, RD, and MD. Regions with a significant (p < 0.05, after correction for multiple comparisons across space) annual increase in FA (blue), decrease in AD (yellow), decrease in RD (red), and decrease in MD (gray) are overlaid on a green skeleton. Significant regions are dilated for illustrative purposes.
Figure 7.
Acceleration of annual change with age: annual difference and percentage change in significant voxels. Mean annual difference (top) and equivalent percentage change (bottom) are plotted against age for FA, AD, RD, and MD. FA values are × 10−3; AD, RD, and MD values are mm2 s−1 × 10−6.
Figure 8.
Acceleration of annual change with age. Voxels displaying a significant correlation (p < 0.05, after correction for multiple comparisons across space) between age and annual decrease in FA (blue), increase in AD (yellow), increase in RD (red), and increase in MD (gray) dilated for illustrative purposes, are overlaid on a green skeleton. x, y, and z coordinates in MNI space are indicated at the top of each column.
Figure 9.
Acceleration of annual change with age: mean t statistic. The mean, uncorrected, t statistic for analyses examining acceleration of annual change with age for FA, AD, RD, and MD is plotted for each coronal and axial slice within global (black), frontal (blue), parietal (pink), occipital (green), and temporal (yellow) ROI.
Figure 10.
Acceleration of change with age: spaghetti plots. Individual participant change in FA, AD, RD, and MD with age is illustrated for global, frontal, parietal, occipital, and temporal ROI. For each measure, an assumption-free general additive model as a function of age was fitted to accurately describe changes across the age range. Diffusivity values are mm2 s−1 × 10−3.
Figure 11.
Influence of sex on acceleration of annual change with age. Regions in which the linear relationship between age and FA was significantly greater in men compared with women (p < 0.05, after correction for multiple comparisons across space) is displayed in blue, dilated for illustrative purposes, and overlaid on a green skeleton.
Similar articles
- White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction.
Beck D, de Lange AG, Maximov II, Richard G, Andreassen OA, Nordvik JE, Westlye LT. Beck D, et al. Neuroimage. 2021 Jan 1;224:117441. doi: 10.1016/j.neuroimage.2020.117441. Epub 2020 Oct 9. Neuroimage. 2021. PMID: 33039618 - White matter structural decline in normal ageing: a prospective longitudinal study using tract-based spatial statistics.
Barrick TR, Charlton RA, Clark CA, Markus HS. Barrick TR, et al. Neuroimage. 2010 Jun;51(2):565-77. doi: 10.1016/j.neuroimage.2010.02.033. Epub 2010 Feb 21. Neuroimage. 2010. PMID: 20178850 - Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects.
Jovicich J, Marizzoni M, Bosch B, Bartrés-Faz D, Arnold J, Benninghoff J, Wiltfang J, Roccatagliata L, Picco A, Nobili F, Blin O, Bombois S, Lopes R, Bordet R, Chanoine V, Ranjeva JP, Didic M, Gros-Dagnac H, Payoux P, Zoccatelli G, Alessandrini F, Beltramello A, Bargalló N, Ferretti A, Caulo M, Aiello M, Ragucci M, Soricelli A, Salvadori N, Tarducci R, Floridi P, Tsolaki M, Constantinidis M, Drevelegas A, Rossini PM, Marra C, Otto J, Reiss-Zimmermann M, Hoffmann KT, Galluzzi S, Frisoni GB; PharmaCog Consortium. Jovicich J, et al. Neuroimage. 2014 Nov 1;101:390-403. doi: 10.1016/j.neuroimage.2014.06.075. Epub 2014 Jul 12. Neuroimage. 2014. PMID: 25026156 - Longitudinal study of callosal microstructure in the normal adult aging brain using quantitative DTI fiber tracking.
Sullivan EV, Rohlfing T, Pfefferbaum A. Sullivan EV, et al. Dev Neuropsychol. 2010;35(3):233-56. doi: 10.1080/87565641003689556. Dev Neuropsychol. 2010. PMID: 20446131 Free PMC article. Review. - Heritability of white matter in twins: A diffusion neuroimaging review.
Videtta G, Colli C, Squarcina L, Fagnani C, Medda E, Brambilla P, Delvecchio G. Videtta G, et al. Phys Life Rev. 2024 Sep;50:126-136. doi: 10.1016/j.plrev.2024.07.003. Epub 2024 Jul 6. Phys Life Rev. 2024. PMID: 39079258 Review.
Cited by
- The effects of a six-month exercise intervention on white matter microstructure in older adults at risk for diabetes.
Lien R, Furlano JA, Witt ST, Xian C, Nagamatsu LS. Lien R, et al. Cereb Circ Cogn Behav. 2024 Sep 14;7:100369. doi: 10.1016/j.cccb.2024.100369. eCollection 2024. Cereb Circ Cogn Behav. 2024. PMID: 39345304 Free PMC article. - Association between seated trunk control and cortical sensorimotor white matter brain changes in patients with chronic low back pain.
Gilliam JR, Sahu PK, Vendemia JMC, Silfies SP. Gilliam JR, et al. PLoS One. 2024 Aug 29;19(8):e0309344. doi: 10.1371/journal.pone.0309344. eCollection 2024. PLoS One. 2024. PMID: 39208294 Free PMC article. - Cortical Network Disruption Is Minimal in Early Stages of Psychosis.
Van Dyken PC, MacKinley M, Khan AR, Palaniyappan L. Van Dyken PC, et al. Schizophr Bull Open. 2024 Apr 22;5(1):sgae010. doi: 10.1093/schizbullopen/sgae010. eCollection 2024 Jan. Schizophr Bull Open. 2024. PMID: 39144115 Free PMC article. - Towards a neurodevelopmental cognitive perspective of temporal processing.
Buzi G, Eustache F, Droit-Volet S, Desaunay P, Hinault T. Buzi G, et al. Commun Biol. 2024 Aug 14;7(1):987. doi: 10.1038/s42003-024-06641-4. Commun Biol. 2024. PMID: 39143328 Free PMC article. Review. - Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer's Disease in the UK Biobank.
Korbmacher M, van der Meer D, Beck D, Askeland-Gjerde DE, Eikefjord E, Lundervold A, Andreassen OA, Westlye LT, Maximov II. Korbmacher M, et al. Biol Psychiatry Glob Open Sci. 2024 Apr 26;4(4):100323. doi: 10.1016/j.bpsgos.2024.100323. eCollection 2024 Jul. Biol Psychiatry Glob Open Sci. 2024. PMID: 39132576 Free PMC article.
References
- Andersson J, Jenkinson M, Smith S. Non-linear optimisation. FMRIB Tech Rep TR07JA1. 2007a
- Andersson J, Jenkinson M, Smith S. Non-linear registration, aka spatial normalisation. FMRIB Tech Rep TR07JA2. 2007b
- Bartzokis G, Lu PH, Heydari P, Couvrette A, Lee GJ, Kalashyan G, Freeman F, Grinstead JW, Villablanca P, Finn JP, Mintz J, Alger JR, Altshuler LL. Multimodal magnetic resonance imaging assessment of white matter aging trajectories over the lifespan of healthy individuals. Biol Psychiatry. 2012;72:1026–1034. doi: 10.1016/j.biopsych.2012.07.010. - DOI - PubMed
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical