Sleep Spindle Dynamics as a Clinical Biomarker of Aging, Alzheimer's Disease, and Trisomy 21

点击翻译按钮获取中文摘要

PROJECT SUMMARY Nearly every psychiatric, neurodegenerative, and neurodevelopmental disorder has sleep dysfunction as a symptom. However, the specificity of biomarkers of sleep dysfunction for a given disease process is poorly un- derstood, due to the extreme heterogeneity observed within healthy populations and clinical cohorts. Of particular importance to neurological biomarker identification are sleep spindles—waxing-waning EEG waveforms of ~15Hz oscillatory activity that define NREM Stage 2 (N2) sleep. Spindle activity has been linked to memory consolidation during sleep and associated with numerous psychiatric, neurodegenerative, and neurodevelop- mental diseases, including Alzheimer's disease, trisomy 21, schizophrenia, and autism, as well as with natural aging. Recent work has shown that spindles have trait-like intrasubject stability, but also vast intersubject heter- ogeneity—the extent of which has yet to be characterized. Without characterizing spindle variability, we cannot understand the specificity of sleep EEG biomarkers. In this study, we develop a robust mathematical framework for understanding spindle temporal dynamics. Using this framework, we will characterize the variability in spindle activity across a multi-ethnic, heterogenous population of thousands of subjects across a wide age range. We will then use these normative distributions to evaluate the specificity of established and novel biomarkers of spindle dysfunction in trisomy 21 and Alzheimer's disease and mild cognitive impairment cohorts. In doing so, we fill an important gap essential to Alzheimer's disease biomarker development, providing a context and spec- ificity lacking in current approaches.