Reciprocal Interactions Linking Cognitive Performance, Aβ aggregation, and Transcriptional Processing with Sleep Disruption in an Alzheimer's Disease Model

Sleep/wake disruption in Alzheimer’s disease patients significantly affects their quality of life, is a major contributing factor for institutionalization, and may represent a proximal cause of neurodegeneration and cognitive decline. Aging remains the biggest known risk factor for Alzheimer’s disease, and poor sleep patterns, which are often associated with aging, can also increase dementia and Alzheimer’s disease risk. Clinical studies have suggested a bidirectional relationship between sleep disruption and deposition of β-amyloid (Aβ), a small peptide associated with plaque formation in Alzheimer’s disease. Exactly how these protein aggregates influence molecular and cellular mechanisms to affect Alzheimer’s etiology are incompletely understood but may target changes in transcriptional processing. This study leverages a multifaceted approach to unravel the complex interactions between aging, transcriptional processing, protein aggregation, sleep disturbance, and cognitive decline using an APP/PS1 Alzheimer's disease rat model. We aim to investigate these interactions by incorporating innovative techniques, such as the use of single-chain variable fragments (scFvs) for evaluating protein oligomerization of Aβ, tau, α-syn, and TDP-43, proteins known to aggregate neurodegenerative diseases, alongside advanced transcriptomic analyses, to identify differentially expressed genes and pathways associated with protein deposition. We propose to integrate complementary RNA sequencing (RNA-seq), whole-transcriptome sequencing (WTTS-seq), and capped small RNA sequencing (csRNA-seq), to explore the transcriptomic landscape of Tg-AD and wild-type rats following changes in sleep pressure associated with cognitive decline using the Vibration Actuating Search Task (VAST) cognitive assay. By integrating these methodologies, we aim to provide a holistic view of cognitive and molecular predictors in the severity of Alzheimer's disease pathology. The results could provide significant insights into the molecular links between protein aggregation, sleep disturbances, and cognitive impairments, offering avenues for the development of novel treatment strategies for Alzheimer's disease.