Cardiorespiratory fitness is differentially associated with cortical thickness in young and older adults

Abstract

Aging is associated with reductions in gray matter volume and cortical thickness. One factor that may play a role in mitigating age-associated brain decline is cardiorespiratory fitness (CRF). Although previous work has identified a positive association between CRF and gray matter volume, the relationship between CRF and cortical thickness, which serves as a more sensitive indicator of gray matter integrity, has yet to be assessed in healthy young and older adults. To address this gap in the literature, 32 young and 29 older adults completed treadmill-based progressive maximal exercise testing to assess CRF (peak VO2), and structural magnetic resonance imaging (MRI) to determine vertex-wise surface-based cortical thickness metrics. Results indicated a significant CRF by age group interaction such that Peak VO2 was associated with thicker cortex in older adults but with thinner cortex in young adults. Notably, the majority of regions demonstrating a positive association between peak VO2 and cortical thickness in older adults overlapped with brain regions showing significant age-related cortical thinning. Further, when older adults were categorized as high or low fit based on normative data, we observed a stepwise pattern whereby cortex was thickest in young adults, intermediate in high fit older adults and thinnest in low fit older adults. Overall, these results support the notion that CRF-related neuroplasticity may reduce although not eliminate age-related cortical atrophy.

FMRI activity during associative encoding is correlated with cardiorespiratory fitness and source memory performance in older adults

“…That is, among this sample of OA, we have previously reported positive associations between CRF and white matter microstructure (Hayes, Salat, et al, 2015) and cortical thickness (Williams et al, 2016). Moreover, these studies have shown that HFOA exhibit structural metrics more similar to YA than the LFOA.…”

“…Neuropsychological and face-name memory retrieval accuracy (Hayes, Alosco, et al, 2015; Hayes et al, 2016), diffusion tensor imaging data (Hayes, Salat, et al, 2015), and cortical thickness data (Williams et al, 2016) from this sample are reported elsewhere, with minor differences in the number of subjects in the analysis sample dependent on the integrity of the particular data points of interest (e.g., a subject may have completed the DTI scan, but not the fMRI scan). All participants gave written informed consent and received financial compensation.…”

Contributions of polygenic risk for obesity to PTSD-related metabolic syndrome and cortical thickness

“…The third model examined the association between the interaction of obesity PRS and MetS factor scores on cortical thickness, controlling for the main effects of latent MetS and obesity PRS as well as age, sex, population substructure, and PTSD factor scores. In all of these analyses, the vertex-wise significance threshold was set at p < .05, following recent research (Williams et al, 2017). …”

Toward valid and reliable brain imaging results in eating disorders

“…Research in noneating disorder populations has shown that some of these behaviors can significantly affect brain structure and function (Boraxbekk et al, 2015;Freund et al, 2012;Hadjikhani et al, 2015;Stice, Burger, & Yokum, 2013). Although exercise has the potential to increase brain volumes in old age, the opposite may be the case in young adults, and the amount of exercise also plays an important role (Williams et al, 2017;Wobrock, Hasan, & Falkai, 2012). For example, extreme exercise in ultramarathon runners was associated with reductions in temporal, occipito-parietal and anterior cingulate gray matter volumes, as well as reduced brain volume in the caudate nucleus (Freund et al, 2014); these alterations normalized on follow-up after 8 months.…”