Relationship Between Risk Factors and Brain Reserve in Late Middle Age: Implications for Cognitive Aging

Abstract

Background: Brain reserve can be defined as the individual variation in the brain structural characteristics that later in life are likely to modulate cognitive performance. Late midlife represents a point in aging where some structural brain imaging changes have become manifest but the effects of cognitive aging are minimal, and thus may represent an ideal opportunity to determine the relationship between risk factors and brain imaging biomarkers of reserve.

Objective: We aimed to assess neuroimaging measures from multiple modalities to broaden our understanding of brain reserve, and the late midlife risk factors that may make the brain vulnerable to age related cognitive disorders.

Methods: We examined multimodal [structural and diffusion Magnetic Resonance Imaging (MRI), FDG PET] neuroimaging measures in 50-65 year olds to examine the associations between risk factors (Intellectual/Physical Activity: education-occupation composite, physical, and cognitive-based activity engagement; General Health Factors: presence of cardiovascular and metabolic conditions (CMC), body mass index, hemoglobin A1c, smoking status (ever/never), CAGE Alcohol Questionnaire (>2, yes/no), Beck Depression Inventory score), brain reserve measures [Dynamic: genu corpus callosum fractional anisotropy (FA), posterior cingulate cortex FDG uptake, superior parietal cortex thickness, AD signature cortical thickness; Static: intracranial volume], and cognition (global, memory, attention, language, visuospatial) from a population-based sample. We quantified dynamic proxies of brain reserve (cortical thickness, glucose metabolism, microstructural integrity) and investigated various protective/risk factors.

Results: Education-occupation was associated with cognition and total intracranial volume (static measure of brain reserve), but was not associated with any of the dynamic neuroimaging biomarkers. In contrast, many general health factors were associated with the dynamic neuroimaging proxies of brain reserve, while most were not associated with cognition in this late middle aged group.

Conclusion: Brain reserve, as exemplified by the four dynamic neuroimaging features studied here, is itself at least partly influenced by general health status in midlife, but may be largely independent of education and occupation.

Keywords: brain reserve; cognitive aging; dynamic; multimodal imaging; resilience.

FIGURE 1

Model of brain reserve throughout the lifespan. Dotted line: Various factors may decrease brain reserve making likelihood of age-related cognitive disorders more likely. Solid line: Normal trajectory without onset of clinical symptoms. It would be ideal to study and intervene on factors that negatively influence brain reserve prior to onset of decline, with hopes of preventing or delaying onset of clinical disease.

FIGURE 2

(A) Regression Heatmap for Protective/Risk Factors × Brain Reserve Measures. Adjusted analyses shown in figure. Shades of green indicate positive relationships between Protective/Risk Factors and Brain Reserve Measures. Shades of red indicate negative relationships between Protective/Risk Factors and Brain Reserve Measures. Complete regression output with Beta and SE can be found in Table 3A. (B) Regression Heatmap for Brain Reserve Measures × Cognitive Measures. Adjusted analyses shown in figure. Shades of green indicate positive relationships between Brain Reserve Measures and Cognitive Measures. There were no negative relationships between Brain Reserve and Cognitive Measures. Complete regression output with Beta and SE can be found in Table 3B. (C) Regression Heatmap for Protective/Risk Factors × Cognitive Measures. Adjusted analyses shown in figure. Shades of green indicate positive relationships between Protective/Risk Factors and Cognitive Measures. Shades of red indicate negative relationships between Protective/Risk Factors and Cognitive Measures. Complete regression output with Beta and SE can be found in Table 3C.

FIGURE 3

Hypothetical depiction of connections between protective/risk factors, brain reserve measures, and cognitive measures. All depicted relationships were significant in our analyses. Note: the cross-sectional design of our study limits the ability to directly connect each protective/risk factor to cognitive measures as mediated by individual brain reserve measures.