Characterizing Alzheimer's Disease with INSPECDS: Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes - PROJECT SUMMARY AND ABSTRACT
It is estimated that Alzheimer's and other neurodegenerative diseases causing dementia will surpass
cancer as the leading cause of death by the year 2040. Alzheimer's is the leading cause of dementia, followed
by synucleinopathies, including dementia with Lewy bodies (DLB) and Parkinson's disease with dementia
(PDD), Fronto-temporal dementia and Vascular dementia. Among clinical researchers focused on
investigating the varying etiologies, genetic associations, biomarkers, and treatment options for Alzheimer's
disease, there is an urgent need for effective tools to aid in the classification of dementia subtypes, in the
earliest detectable stages of the pathophysiological process. To address this unmet need Advanced Brain
Monitoring (ABM) proposes to leverage day and night assessment technologies to create an Integrated
Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes
(INSPECDS) to profile Alzheimer's and other dementias. The core components of the INSPECDS platform will
be the Alertness and Memory Profiler (AMP), the Sleep Profiler, and integrated machine-learning, classification
algorithms, hosted on a secure, cloud-based, infrastructure for automated data processing, analysis, and
reporting. The AMP was developed and validated intially for the purpose of detecting the neurocognitive effects
of sleep deprivation in adults diagnosed with obstructive sleep apnea but has more recently been applied to
assess Alzheimer's and Parkinson's disease. The AMP is unique among neurocognitive testing platforms in
that it is the only one which integrates advanced, electrophysiological measures (e.g., 24-channel, wireless
EEG and ECG) during the performance of computerized neurocognitive tasks and has proven effective in
characterizing cognitive decline in Alzheimer's. This advanced capability permits researchers to explore real-
time relations between fluctuations in alertness, discrete cognitive functions, and specific neural processes
believed to subserve observed performance deficits in Alzheimer's and other dementias. The Sleep Profiler is
an FDA-cleared, easily applied, wireless-EEG device that was developed and validated to measure sleep
architecture for in-home sleep studies with submental (chin) EMG and wireless accelerometers to monitor
head and limb movements to quantify the characteristics of REM-sleep behavior disorder (RBD), considered to
be a prodromal expression of synucleinopathy. Furthermore, the application of sophisticated, machine-
learning, classification algorithms will streamline the processing and analyses of these data to derive statistical
probabilities of Alzheimer's and other dementia subtypes. The overarching goal of the current, Direct-to-Phase
II, SBIR project is to finalize implementation of a secure, cloud-based infrastructure to compile the data
obtained from the AMP and Sleep Profiler, train classification algorithms to discriminate among Alzheimer's
and other dementia subtypes, validate diagnostic accuracy, and integrate optimized classifiers within the cloud-
based architecture. Once completed, the INSPECDS system will be the first clinical research tool of its kind
and find immediate application in both university-based research settings and pharmaceutical industry clinical
trials to aid in the endophenotypic stratification of Alzheimer's and other dementias.
