UC Riverside

This dissertation aimed to investigate the complex associations between sleep and cognition, shedding light on how sleep may serve as a modifiable factor impacting cognitive functioning and cognitive aging. Through macro and micro perspectives, the research offered a comprehensive understanding of sleep-cognition dynamics. In Study 1, cross-sectional data from mid-to late-life twins within the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium were leveraged to examine the sleep and cognition relationship while additionally including a polygenic score for Alzheimer’s disease (AD) to elucidate the moderating roles both sleep and genetic risk for AD on etiological associations underlying differences in cognitive performance. Findings revealed no statistically significant moderation of sleep disturbances on genetic variance. However, patterns suggested heightened genetic influences with reduced sleep duration or increasing sleep disturbances. Sleep disturbances may moderate common environmental influences for tasks related to attention and working memory. Principally, Study 1 found higher genetic risk for AD was generally associated with weaker individual-specific environmental influences. In Study 2, we explored micro-level sleep and cognition associations over a two-week period in individuals approaching midlife. Leveraging ambulatory smartphone data from the Colorado Adoption/Twin Study of Lifespan behavioral development and cognitive aging (CATSLife), Study 2 revealed that the between-person average sleep quality (SQ) component exhibited the most influence on performance across episodic memory, working memory, and executive functioning compared to within-person fluctuations in daily SQ. However, variations in daily SQ dynamics exhibited task-specific effects, particularly for working memory and executive functioning tasks. Interactions between SQ and APOE genotype indicated momentary improvements in cognitive performance, particularly for executive functioning and working memory, among individuals with increasing scores indexing 4 dosage experiencing higher-than-usual sleep quality. Together, the dissertation examines both macro-level (Study 1) and micro-level (Study 2) sleep-cognition associations through biometrical twin models that leverage data from IGEMS, comprising data from individuals in mid- to late-life, and from applications of longitudinal time-varying covariate models that leverage ambulatory burst data from CATSLife, comprising data from individuals approaching midlife. Further work is necessary to understand the nuanced relationship between sleep and cognition, particularly with an emphasis on examinations of gene-environment interplay.