Age-related alterations in white matter microstructure measured by diffusion tensor imaging. Neurobiol Aging

MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129-2060, USA.
Neurobiology of Aging (Impact Factor: 5.01). 08/2005; 26(8):1215-27. DOI: 10.1016/j.neurobiolaging.2004.09.017
Source: PubMed


Cerebral white matter (WM) undergoes various degenerative changes with normal aging, including decreases in myelin density and alterations in myelin structure. We acquired whole-head, high-resolution diffusion tensor images (DTI) in 38 participants across the adult age span. Maps of fractional anisotropy (FA), a measure of WM microstructure, were calculated for each participant to determine whether particular fiber systems of the brain are preferentially vulnerable to WM degeneration. Regional FA measures were estimated from nine regions of interest in each hemisphere and from the genu and splenium of the corpus callosum (CC). The results showed significant age-related decline in FA in frontal WM, the posterior limb of the internal capsule (PLIC), and the genu of the CC. In contrast, temporal and posterior WM was relatively preserved. These findings suggest that WM alterations are variable throughout the brain and that particular fiber populations within prefrontal region and PLIC are most vulnerable to age-related degeneration.

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Available from: Anders M Dale, Oct 04, 2015
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    • "Effects of aging on white matter integrity are pronounced and have been well-documented in the literature (Abe et al., 2008; Hsu et al., 2008; Nusbaum et al., 2001; Pfefferbaum et al., 2000; Salat et al., 2005; Sullivan et al., 2001). Fractional anisotropy (FA) tends to decrease in most brain regions while mean diffusivity (MD) and radial diffusivity (RD) tend to increase with advancing age. "
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    ABSTRACT: Non-linear effects of age on white matter integrity are ubiquitous in the brain and indicate that these effects are more pronounced in certain brain regions at specific ages. Box-Cox analysis is a technique to increase the log-likelihood of linear relationships between variables by means of monotonic non-linear transformations. Here we employ Box-Cox transformations to flexibly and parsimoniously determine the degree of non-linearity of age-related effects on white matter integrity by means of model comparisons using a voxel-wise approach. Analysis of white matter integrity in a sample of adults between 20 and 89 years of age (n = 88) revealed that considerable portions of the white matter in the corpus callosum, cerebellum, pallidum, brainstem, superior occipito-frontal fascicle and optic radiation show non-linear effects of age. Global analyses revealed an increase in the average non-linearity from fractional anisotropy to radial diffusivity, axial diffusivity, and mean diffusivity. These results suggest that Box-Cox transformations are a useful and flexible tool to investigate more complex non-linear effects of age on white matter integrity and extend the functionality of the Box-Cox analysis in neuroimaging. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 08/2015; DOI:10.1016/j.neuroimage.2015.08.003 · 6.36 Impact Factor
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    • "Evidence from structural MRI study has shown that the frontal lobe is among the first to become impaired in aging (Raz, 2000). Several DTI studies have also suggested that the anterior WM composed of small, thinly myelinated fibers (Bartzokis et al., 2012; Glasser and Van Essen, 2011) are more susceptible to aging than the posterior WM (e.g., through myelin loss or damage) (Ota et al., 2006; Pfefferbaum et al., 2000; Salat et al., 2005a). Moreover, an anterior-posterior gradient for GM shrinkage and WM degeneration with aging has been consistently reported (Raz et al., 1997; Salat et al., 2005b). "
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    ABSTRACT: Lifespan is a dynamic process with remarkable changes in brain structure and function. Previous neuroimaging studies have indicated age-related microstructural changes in specific white matter tracts during development and aging. However, the age-related alterations in the topological architecture of the white matter structural connectome across the human lifespan remain largely unknown. Here, a cohort of 113 healthy individuals (ages 9-85) with both diffusion and structural MRI acquisitions were examined. For each participant, the high-resolution white matter structural networks were constructed by deterministic fiber tractography among 1024 parcellation units and were quantified with graph theoretical analyses. The global network properties, including network strength, cost, topological efficiency, and robustness, followed an inverted U-shaped trajectory with a peak age around the third decade. The brain areas with the most significantly nonlinear changes were located in the prefrontal and temporal cortices. Different brain regions exhibited heterogeneous trajectories: the posterior cingulate and lateral temporal cortices displayed prolonged maturation/degeneration compared with the prefrontal cortices. Rich-club organization was evident across the lifespan, whereas hub integration decreased linearly with age, especially accompanied by the loss of frontal hubs and their connections. Additionally, age-related changes in structural connections were predominantly located within and between the prefrontal and temporal modules. Finally, based on the graph metrics of structural connectome, accurate predictions of individual age were obtained (r = 0.77). Together, the data indicated a dynamic topological organization of the brain structural connectome across human lifespan, which may provide possible structural substrates underlying functional and cognitive changes with age. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
    Human Brain Mapping 07/2015; DOI:10.1002/hbm.22877 · 5.97 Impact Factor
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    • "Specifically, we assessed effects on task-switch performance, a cognitive task largely susceptible to age-related shifts in performance speed and accuracy (Salthouse et al., 1998; Kray and Lindenberger, 2000; Cepeda et al., 2001; Jimura and Braver, 2010; Gazes et al., 2012). This task is considered a measure of executive control and is supported primarily by the prefrontal and parietal cortices (Sohn et al., 2000; Braver et al., 2003; Aron et al., 2004; Gold et al., 2010), regions that experience preferential degeneration with advancing age (Sowell et al., 2003; Salat et al., 2005; Driscoll et al., 2009). Because BDNF levels decline with age (Lommatzsch et al., 2005; Burke and Barnes, 2006; Ziegenhorn et al., 2007), and is found in cortical regions that likely support task-switch performance (Podewils et al., 2005; Aguiar et al., 2011; Diógenes et al., 2011), we reasoned that age might be an important moderator of the effects of exercise on BDNF and task-switch performance. "
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    ABSTRACT: These authors have contributed equally to this work. Executive function declines with age, but engaging in aerobic exercise may attenuate decline. One mechanism by which aerobic exercise may preserve executive function is through the up-regulation of brain-derived neurotropic factor (BDNF), which also declines with age. The present study examined BDNF as a mediator of the effects of a 1-year walking intervention on executive function in 90 older adults (mean age = 66.82). Participants were randomized to a stretching and toning control group or a moderate intensity walking intervention group. BDNF serum levels and performance on a task-switching paradigm were collected at baseline and follow-up. We found that age moderated the effect of intervention group on changes in BDNF levels, with those in the highest age quartile showing the greatest increase in BDNF after 1-year of moderate intensity walking exercise (p = 0.036). The mediation analyses revealed that BDNF mediated the effect of the intervention on task-switch accuracy, but did so as a function of age, such that exercise-induced changes in BDNF mediated the effect of exercise on task-switch performance only for individuals over the age of 71. These results demonstrate that both age and BDNF serum levels are important factors to consider when investigating the mechanisms by which exercise interventions influence cognitive outcomes, particularly in elderly populations.
    Frontiers in Human Neuroscience 12/2014; 8. DOI:10.3389/fnhum.2014.00985 · 2.99 Impact Factor
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