Search

Objective: Smartphone-based cognitive assessments can provide unique information about cognition that is difficult or impossible with traditional cognitive assessments. Using high-frequency measurement "burst" designs, we have shown that older adults are capable and willing to participate in smartphone-based research, that this method dramatically improves between-subject reliability compared to traditional methods and demonstrates extraordinary test-retest reliabilities, and that high-frequency measurement can reveal time of day effects that are increased in those with elevated Alzheimer's disease biomarkers. In this symposium session, we will provide an overview of our current work in older adults at risk for AD and highlight new analyses on the interaction between day to day variability in sleep and cognition. We will also cover our approach for measuring smartphone latencies, a critical aspect of bring-your-own-device (BYOD) studies. Participants and Methods: The Ambulatory Research in Cognition (ARC) smartphone application for iOS and Android administers custom-designed tests of associate memory, processing speed, and spatial working memory. ARC uses a measurement burst design in which very brief (typically 60s or less) tests are completed at random times several times per day for up to one week. Measurement burst designs rely on principles from ecological momentary assessment, and can be described with a simple formula: 1. Test often and everywhere, 2. Keep assessments brief, and 3. Combine the data across sessions to increase reliability. At the Knight Alzheimer's Disease Research Center at Washington University in St Louis, we have enrolled over 400 participants (ages 60-99 years) at risk for AD in ARC studies. These participants are comprehensively assessed with traditional cognitive tests, clinical examinations, neuroimaging, and fluid biomarkers. ARC also assesses sleep with the Pittsburgh Sleep Quality Index that captures essential sleep parameters, which are assessed daily during each 7-day measurement burst. Analyses of sleep and cognition focused on parameters including total sleep time, number of awakenings, sleep quality ratings, and an extremes analysis comparing cognition after nights with more sleep and after nights with less sleep. Results: Overall, participants reporting less total sleep time and more awakenings had lower memory and processing speed scores. This remained significant after modeling covariates including age, self-reported gender, education, and APOE ε4 status. Compared to nights with the most sleep, memory was worse after the nights with the poorest sleep. Conclusions: When considering AD biomarkers in these analyses, participants with elevated AD biomarkers, including neurofilament light chain (NfL) and phosphorylated-tau181 (p-tau181), demonstrated more impacts of poor sleep on cogntion, such that the nights with the least sleep tended to impact cognition more than in those with normal biomarker levels, suggesting an important role for sleep in maintaining cognition in preclinical and early symptomatic AD. Interestingly, self-reported sleep quality was not associated with ARC cognitive tests, consistent with studies emphasizing the need for more quantitative assessments of sleep quality. In addition to these sleep data, we will review publications using the ARC platform, including a recently accepted manuscript in JINS (Nicosia et al., 2022). [ABSTRACT FROM AUTHOR]

Objective: The purpose of the present study was to study the clinical significance of fluctuations in cognitive impairment status in longitudinal studies of normal aging and dementia. Several prior studies have shown fluctuations in cognition in longitudinal studies is associated with greater risk of conversion to dementia. The present study defines "reverters" as participants who revert between cognitive normality and abnormality according to the Clinical Dementia Rating (CDRTM). A defining feature of the CDR at the Knight Alzheimer's Disease Research Center (Knight ADRC) at Washington University in St. Louis is that the CDR is calculated by clinicians blinded to cognitive data and any prior assessments so that conclusions are drawn free of circularity and examiner bias. We hypothesized reverters, when compared to cognitively normal participants who remain unimpaired, would have worse cognition, abnormal biomarkers, and would eventually progress to a stable diagnosis of cognitive impairment. Participants and Methods: From ongoing studies of aging and dementia at the Knight ADRC, we selected cognitively normal participants with at least three follow-up visits. Participants fell into three categories: stable cognitively normal ("stable CN"), converters to stable dementia ("converters"), and reverters. Cognitive scores at each visit were z-scored for comparison between groups. A subset of participants had fluid biomarker data available including cerebrospinal fluid (CSF) amyloid and phosphorylated-tau species, and plasma neurofilament light chain (NfL). Mixed effect models evaluated group relationships between biomarker status, APOE £4 status, and CDR progression. Results: 930 participants were included in the study with an average of 5 years of follow-up (Table 1). 661 participants remained cognitively normal throughout their participation while 142 progressed to stable dementia and 127 participants had at least one instance of reversion. Compared to stable CN, reverters had more abnormal biomarkers at baseline, were more likely to carry an APOE £4 allele, and had better cognitive performance at baseline (Table 2, Figure 1). Compared to converters, reverters had less abnormal biomarkers at baseline, were less likely to carry an APOE £4 allele, and had overall better cognitive performance at baseline. In longitudinal analyses, cognitive trajectories of reverters exhibited a larger magnitude of decline compared to stable CNs but the magnitude of decline was not as steep as converters. Conclusions: Our results confirm prior studies that showed reversion in cognitive status, when compared to stable cognitive normality, is associated with worse overall genetic, biomarker and cognitive outcomes. Longitudinal analyses demonstrated reverters show significantly more decline than stable participants and a higher likelihood of eventual conversion to a stable dementia diagnosis. Reverters' cognitive trajectories appear to occupy a transitional phase in disease progression between that of cognitive stability and more rapid and consistent progression to stable dementia. Identifying participants in the preclinical phase of AD who are most likely to convert to symptomatic AD is critical for secondary prevention clinical trials. Our results suggest that examining intraindividual variability in cognitive impairment using unbiased, longitudinal CDR scores may be a good indicator of preclinical AD and predict eventual conversion to symptomatic AD. [ABSTRACT FROM AUTHOR]