White Matter Integrity Declined Over 6-Months, but Dance Intervention Improved Integrity of the Fornix of Older Adults
Article written by Agnieszka Z. Burzynska, Yuqin Jiao, Anya M. Knecht, Jason Fanning, Elizabeth A. Awick, Tammy Chen, Neha Gothe, Michelle W. Voss, Edward McAuley, and Arthur F. Kramer Frontiers in Aging Neuroscience on 16 March 2017.
Degeneration of cerebral white matter (WM), or structural disconnection, is one of the major neural mechanisms driving age-related decline in cognitive functions, such as processing speed. Past cross-sectional studies have demonstrated beneficial effects of greater cardiorespiratory fitness, physical activity, cognitive training, social engagement, and nutrition on cognitive functioning and brain health in aging. Here, we collected diffusion magnetic resonance (MRI) imaging data from 174 older (age 60–79) adults to study the effects of 6-months lifestyle interventions on WM integrity. Healthy but low-active participants were randomized into Dance, Walking, Walking + Nutrition, and Active Control (stretching and toning) intervention groups (NCT01472744 on ClinicalTrials.gov). Only in the fornix there was a time × intervention group interaction of change in WM integrity: integrity declined over 6 months in all groups but increased in the Dance group.
Integrity in the fornix at baseline was associated with better processing speed, however, change in fornix integrity did not correlate with change in processing speed. Next, we observed a decline in WM integrity across the majority of brain regions in all participants, regardless of the intervention group. This suggests that the aging of the brain is detectable on the scale of 6-months, which highlights the urgency of finding effective interventions to slow down this process. Magnitude of WM decline increased with age and decline in prefrontal WM was of lesser magnitude in older adults spending less time sedentary and more engaging in moderate-to-vigorous physical activity. In addition, our findings support the anterior-to-posterior gradient of greater-to-lesser decline, but only in the in the corpus callosum. Together, our findings suggest that combining physical, cognitive, and social engagement (dance) may help maintain or improve WM health and more physically active lifestyle is associated with slower WM decline. This study emphasizes the importance of a physically active and socially engaging lifestyle among aging adults.
Disruption of (WM) microstructure—degeneration or loss of axons and myelin—is considered one of the primary mechanisms underlying age-related cognitive slowing and memory decline (Gunning-Dixon and Raz, 2000; Madden et al., 2012). Therefore, preventing age-related “structural disconnection” (Raz and Rodrigue, 2006) or improving WM integrity is key in preserving cognitive performance necessary for independent functioning in older individuals.
WM microstructure can be studied non-invasively with diffusion magnetic resonance imaging (MRI). Diffusion imaging provides voxel-wise estimation of magnitude and directionality of water diffusion in WM. Fractional anisotropy (FA), is a measure of the directional dependence of diffusion (Basser, 1995), and reflects fiber orientation, density and coherence within a voxel (Beaulieu, 2002). Lowered FA has been observed in various conditions in which loss of fiber integrity occurs (Beaulieu, 2002), such as Alzheimer's disease (Medina et al., 2006). Radial diffusivity (RD) represents diffusivity perpendicular to the main fiber direction (Basser, 1995; Song et al., 2002). Increases in RD have been linked to degeneration or loss of myelin (Song et al., 2003, 2005). Axial diffusivity (AD) represents diffusion parallel to the axon fibers and is related to axonal integrity (Basser, 1995; Song et al., 2002). Finally, mean diffusivity (MD) reflects the magnitude of total water diffusion within a voxel, which depends on the density of physical obstructions such as cellular membranes (Beaulieu, 2002; Sen and Basser, 2005). Increased MD, paralleled by increases in both RD and AD, was observed in conditions of WM degeneration (Beaulieu et al., 1996; Beaulieu, 2002; Concha et al., 2006).
To date, numerous neuroimaging studies described age-related differences in WM properties using cross-sectional comparisons (Burzynska et al., 2010; Madden et al., 2012). There are, however, two critical obstacles in understanding the age-related changes in WM and, subsequently, in slowing down or reversing these age-related changes in the human brain. First, there are still few studies describing age-related change in WM integrity in a longitudinal design. Specifically, there are only five studies that described changes in WM over time and across numerous WM regions or tracts1. Sexton et al. (2014) and Storsve et al. (2016) followed 203 adults between 20 and 84 years of age over on average 3.5 years. They found extensive and overlapping, significant annual decreases in FA, paralleled by increases in RD, AD, and MD. Rieckmann et al. (2016) followed up 108 older adults over on average 2.6 years and found significant declines in FA and increases in RD, AD, and MD. Bender et al. (2016b) found changes in FA and RD over periods of time of 1 to 7 years in healthy adults of age 50–84. Barrick et al. (2010) observed significant decline in FA in healthy adults 50–90 years old over 2 years.
Some of these studies reported acceleration of microstructural decline in older age (Sexton et al., 2014; Bender et al., 2016b; Storsve et al., 2016), but other did not (Barrick et al., 2010). Some argued the superior-to-inferior gradient of greater-to-lesser decline (Sexton et al., 2014; Storsve et al., 2016), while longitudinal data (Barrick et al., 2010) did not support “last-in-first-out” hypothesis of anterior-to-posterior decline suggested in cross-sectional studies (Bartzokis et al., 2010).
Together, these studies show consistent decline in WM integrity represented by increases in RD, AD, and MD, and decreases in FA. However, there is no consensus on the spatial gradient of decline and WM decline has not been observed over periods shorter than a year. Knowing short-term dynamics of WM decline would be useful in assessing the outcomes of typically short-term interventions (months) as well as in differentiating between normal and abnormal speed of decline in patients presenting first cognitive symptoms. Finally, there is little evidence for the ability to improve WM integrity in older adults. Cross-sectional studies suggest that lifestyle factors such as physical activity (PA) and cardiorespiratory fitness (CRF) are protective against cognitive and neural decline. For example, we have shown that greater PA and CRF are associated with greater WM integrity (Burzynska et al., 2014; Oberlin et al., 2016) and that older aerobically trained athletes have greater brain structural integrity and cognitive performance than their sedentary low-fit peers (Tseng et al., 2013; Burzynska et al., 2015; Young et al., 2016). However, a recent meta-analysis showed only modest cross-sectional effects of CRF and aerobic PA on WM in aging (Sexton et al., 2016). The longitudinal evidence for positive effect of exercise on WM is still very scarce. Voss et al. (2010) demonstrated in 70 adults (55–80 years old) that increases in CRF as a result of 1-year the aerobic walking intervention was associated with fronto-temporal increase in FA and enhanced short-term memory. However, there was no difference between the walking and the active control group (stretching and toning) in their changes of WM integrity over 1-year.
In the current study we address these two critical limitations of the existing studies: short-term dynamics in WM change in different diffusivity parameters, and the effects of lifestyle interventions to improve WM integrity in aging.
To this aim, we collected diffusion, cognitive, CRF and PA data from 174 healthy, non-demented (MMSE>26) adults 60–79 years old at baseline2, and after a 6-months lifestyle intervention (randomized clinical trial, NCT01472744 on ClinicalTrials.gov). The interventions included aerobic exercise (Walking) and an Active Control group (stretching and toning, not aimed to increase CRF). In addition, we included a group that combined aerobic PA, cognitive, and social stimulation (Dance), and an aerobic Walking that also received a nutritional supplement (Walking + Nutrition).
We expected to observe a time × group interaction, with Walking and Dance groups showing maintenance or increase in WM integrity as compared to the decline in the Active Control group. We expected to observe this effect especially in the frontal and temporal regions (Colcombe et al., 2006; Voss et al., 2010). Next, we expected to observe declines in FA and increases in MD, RD, and AD across the WM and that this decline will be accelerated in the oldest, more sedentary, less active, and less fit (lower CRF) adults. However, given the shorter time scale, we expected these changes to be of smaller magnitude and more spatially restricted than in the existing studies with time lags greater than a year. Finally, we expected that change in FA in the Walking or Dance groups would be behaviorally relevant, i.e., be related to change in cognitive performance, especially in the speed and memory domains (Lövdén et al., 2014; Wang et al., 2015; Bender et al., 2016a) as compared to crystallized and fluid abilities (Virginia Cognitive Aging Project Battery; Salthouse and Ferrer-Caja, 2003; Salthouse, 2004, 2005, 2010)3.