Translating neuronal network hyperexcitability in Alzheimer's disease

Despite recent advances in the efficacy of anti-amyloid therapies, no widely available disease-modifying therapies for Alzheimer’s disease (AD) currently exist. Recent findings suggest that neuronal network dysfunction and hyperexcitability are early signs of AD, driven by an imbalance between excitatory and inhibitory neurotransmission. This neuronal network hyperexcitability has been associated with accelerated cognitive decline and is a potentially modifiable risk factor. Hyperexcitability can in principle be detected using non-invasive, quantitative neurophysiological measures, however, robust macroscale quantitative markers of excitation-inhibition imbalance are not yet available and the neurophysiological changes in preclinical stages of human AD remain uncertain. To address the need for early diagnosis and intervention in AD, we aimed to enhance our understanding of functional neuronal network changes in the preclinical stages of AD. We adopted a translational approach that integrates neurophysiological findings from various species, including Alzheimer patients and transgenic mice, as well as computational models. We investigated how quantitative measures, such as local oscillatory activity, interregional connectivity and hub vulnerability, could inform us about the underlying excitation-inhibition (im)balance.
This thesis provides evidence for abnormal neuronal function from very early stages of the disease in both AD mice and humans carrying mutations in the APP or PSEN1 gene, albeit with possible distinct underlying mechanisms. Quantitative measures like spectral power and a novel functional connectivity measure can infer excitation-inhibition ratios from short resting-state neurophysiological recordings when taking various factors into account, such as time-scale and relative importance of a region in the network. We observed similar spectral power and functional connectivity changes - possibly reflecting neuronal network hyperexcitability - in cognitively unimpaired mutation carriers and sporadic AD dementia patients. However, we found conflicting results in amyloid-positive mild cognitively impaired patients. To provide definitive conclusions regarding mechanisms and progression of neuronal network hyperexcitability in individuals with AD, future studies should validate the quantitative measures and examine them collectively in larger sample sizes and in longitudinal studies.
We conclude that neuronal network hyperexcitability is detectable in non-invasive resting-state neurophysiological activity and is a continuous and evolving feature throughout the progression of human AD. Ultimately, these insights pave the way for development of alternative early treatment targets to reduce the cognitive decline and manage the rising burden of AD on families and society.