Today's open access paper discusses recent data on age-related changes in brain structure, assessed in older people with varying degrees of physical fitness, though all were described as inactive. Brain atrophy is characteristic of aging; loss of volume proceeds steadily year after year in the latter half of life, accompanied by chances in structure and distribution of tissues. This is one part of the processes that lead to loss of cognitive function and dementia. It is known that physical fitness, and the exercise needed to maintain that fitness, slows this progression.
Many different mechanisms are likely involved in the ways in which fitness can slow the aging of the brain. For example, exercise boosts BDNF levels, which encourage neurogenesis, the production of new neurons in the brain. Further, both exercise and the state of fitness improve blood flow to the brain, in the short term and the long term. Brain tissue requires a great deal of energy to perform its functions, and a flow of nutrients and oxygen is essential. That exercise can improve cognitive function very quickly, on the same timeframe as increased cerebral blood flow, suggests that the brain has evolved to operate at the upper limit of its energy supply. Any loss from the peak will affect tissue over the long term.
Late adulthood is marked by a host of physical changes and brain atrophy is one of the most ubiquitous. Specifically, after the age of forty, brain volume declines at a rate of about 5% per decade. Furthermore, ageing-related shifts in brain morphology are associated with concomitant declines in cognitive performance. As our population ages, there is paramount interest in strategies to potentially mitigate the brain tissue loss that occurs with ageing. In recent research, cardiorespiratory fitness (CRF) has been described to be neuroprotective in older adults. As CRF can be influenced through exercise intervention, there may be future potential for these therapies in mitigating neurodegeneration.
However, the influence of CRF on brain tissue has not been fully characterized quantitatively. Tissue atrophies in the ageing brain non-uniformly across multiple regions. Multiple studies have demonstrated that both ageing and decreased CRF are associated with non-uniform declines. Yet, prior studies investigating associations with CRF have not characterized differential atrophy and degeneration across the brain. First, conventional statistical methods comparing regional volumes and voxelwise metrics are insufficiently sensitive to the spatial interdependence in brain tissue, and its nonlinearity. Indeed, regional volumes have led to varying reports of the degree to which tissue shifts dependent on age and those dependent on CRF overlap. In contrast, new techniques that measure spatial variation in brain tissue as mathematical distributions can directly measure these diffuse, non-linear processes. Second, while regional volumes and voxelwise metrics are basic statistical descriptors, they do not correspond to any biophysical properties of brain tissue.
In recent work, the authors developed an automated approach to discover discriminant phenotypic patterns from brain images by directly measuring the spatial tissue distribution. This approach enabled biophysical properties of the brain to be modelled as mass transport. The technique is called 3D transport-based morphometry (TBM). This paper applies the novel TBM approach to extract the perturbations in brain phenotype statistically explainable by CRF. The goal of this research is to discover and visualize the shifts in brain tissue distribution that are most strongly associated with CRF in an automated manner using the TBM technique. Furthermore, this study aims to determine the degree to which the pattern of tissue distribution with higher CRF overlaps with the distribution of ageing-related losses.
In this study of 172 inactive older adults aged 58-81 (66.5 ± 5.7) years, cardiorespiratory fitness was determined by VO2 peak (ml/kg/min) during graded exercise and brain morphology was assessed through structural magnetic resonance imaging. After correcting for covariates including age (in the fitness model), gender, and level of education, we compared dependent tissue shifts with age to those due to VO2 peak. We found a significant association between cardiorespiratory fitness and brain tissue distribution. A strong statistical correlation was found between brain tissue changes related to ageing and those associated with lower cardiorespiratory fitness. In both cases, frontotemporal regions shifted the most while basal ganglia shifted the least. Our results highlight the importance of cardiorespiratory fitness in maintaining brain health later in life.