Aging and Alzheimer's Disease: Multimodal Investigation of Image-derived Biomarkers

Aging is an inevitable process in life and the primary risk factor for most neurodegenerative diseases including Alzheimer’s disease (AD), the most common form of dementia. As life expectancy continues to increase, AD prevalence is expected to rise. AD-related pathological processes unfold decades before the emergence of clinical signs of cognitive decline and involve brain changes such as atrophy, accumulation of amyloid-beta plaques and tau neurofibrillary tangles (NFT), synaptic and neuronal loss, demyelination, and iron accumulation that would eventually lead to cognitive impairment.
Here, to assess brain myelin and iron content in vivo, quantitative MRI (qMRI) maps like magnetization transfer saturation (MTsat), Effective transverse relaxation rate (R2*), and proton density (PD) were used. And synaptic density was measured using the total volume distribution map (Vt) of [F18] UCB-H PET images.
In this thesis, we examined the simultaneous occurrence of these brain changes in aging and AD, identifying significant differences in the hippocampus and amygdala. Demyelination emerged as a key distinguishing factor between AD and healthy groups. The effects of age on various brain characteristics were re-evaluated in a multivariate model, with proton density being the most age-related factor in healthy aging.
Finally, we attempted to examine the association of cognitive performance and the rate of cognitive decline with qMRI maps and GM and WM volume. The univariate regression analyses at baseline revealed correlations between different cognitive scores and brain tissue properties within the cerebellum, hippocampus, middle temporal, and medial orbitofrontal cortex. Moreover, the multivariate analysis shows that cognitive performance was related to combined tissue properties in the middle frontal gyrus, insula, and cerebellum. There were only a few results for the rate of cognitive decline, with univariate correlations within the left fusiform between longitudinal relaxation rate (R1) maps in GM and attention and memory decline.
To conclude, our findings shed light on the complex relationships between changes in aging and AD brains. Furthermore, we emphasize the importance of multivariate analysis for detecting subtle microstructural changes associated with aging that may motivate interventions to mitigate cognitive decline in older adults.