Insights on Alzheimer’s disease etiology from network approaches in healthy aging
The etiology of Alzheimer’s disease involves the presymptomatic development and progression of amyloid-β and tau in healthy aging. Amyloid-β and tau are naturally occurring proteins that can form abnormal aggregates – amyloid-β plaques and neurofibrillary tangles – which constitute the pathological hallmarks of Alzheimer’s disease. The initial formation of these aggregates occurs decades before the onset of cognitive symptoms, in individuals otherwise considered to be healthy and unimpaired. This dissertation hinges on in-vivo PET imaging of amyloid-β and tau in humans using PIB-PET and AV1451-PET to explore this presymptomatic phase of Alzheimer’s disease – when pathology is present without detectable symptoms. I place particular emphasis on amyloid-β pathology – understanding the factors that underlie vulnerability to amyloid-β as well as identifying the initial sources and progressive spread of amyloid-β pathology in healthy aging. My focus on amyloid-β is consistent with the predominant framework for Alzheimer’s disease, the amyloid cascade hypothesis, which contends that amyloid-β initiates a slow and ultimately deadly chain of events that results, decades later, in deteriorating memory and breakdown of cognition. In recognition that Alzheimer’s disease does not reflect a focal disorder, but rather network failure of large-scale brain systems, I adapt a network-based framework to account for the role of the complex interdependencies between distributed brain regions – of glucose metabolism from FDG-PET, of brain activity from resting-state functional MRI, and of amyloid-β from PIB-PET. Examining metabolic brain networks, I reveal widespread, highly systematic reorganization of glucose metabolism in old age – well beyond what has been revealed using other methods – that is more heterogeneous in those possessing both substantial amyloid-β and genetic risk for Alzheimer’s disease. Further, I demonstrate that the topology of early-life “metabolic inefficiency” – a novel metric that removes the potential association of glucose metabolism with highly connected hubs – explains the topology of amyloid-β in healthy aging. Finally, I provide evidence that very early amyloid-β accumulation, in those without substantial amyloid-β pathology, is multifocal and broadly distributed across brain networks – consistent with shared tissue vulnerability, not transneuronal spread, being the driving force of accumulation of amyloid-β pathology. These findings support the notion that shared tissue vulnerability of a metabolic origin drives widespread, systematic accumulation of amyloid-β in healthy aging. Future work should uncover the nature and origin of metabolic tissue vulnerability to amyloid-β, exploring the complex chain of events that drive widespread age-related reorganization – especially of cerebral glucose metabolism – and its links other age-related changes and the onset of pathological accumulation of amyloid-β.