Accelerated changes in white matter microstructure during aging: a longitudinal diffusion tensor imaging study

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.

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.