0645 Associations of Objective Sleep Parameters and Gray Matter Microstructure in community dwelling cognitive normal older adults. (25th May 2022)

• Record Type: Journal Article
• Authors: Bubu, Omonigho; Zanetta, Kovbasyuk; Mbah, Alfred; Korey, Kam; Anna, Mullins; Parekh, Ankit; Umasabor-Bubu, Ogie; Rapoport, David; Ayappa, Indu; Jean-Louis, Girardin; Varga, Andrew; Osorio, Ricardo
• Is Part Of: Sleep. Volume 45(2022)Supplement 1
• Page Start: A283
• Page End: A284
• Publication Date: 2022-05-25
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsac079.642
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Disturbed sleep measures differentially alter white-matter microstructure. We examined whether obstructive sleep apnea (OSA)-severity, sleep fragmentation and duration measures were associated with gray-matter diffusion tensor-imaging metrics (DTI) (i.e., fractional anisotropy [FA], mean diffusivities [MD] and kurtoses [MK]) in community-dwelling cognitive-normal older-adults. Methods: Gray-matter DTI metrics from MRI including mean FA, MD and MK measures of the hippocampus, thalamus, medial prefrontal-cortex (mPC) and Alzheimer's Disease (AD) vulnerable regions (temporal [inferior, middle, and superior], parietal [inferior and superior], entorhinal cortex, and precuneus) were determined from 85 subjects. OSA-severity measures included AHI3a and AHI4%. Other sleep measures included sleep efficiency (SE), non-rapid eye movement (NREM) slow wave sleep (SWS) duration, percent time spent in SWS (%SWS), slow wave activity (SWA), total sleep time (TST), and wake after sleep onset (WASO). To analyze the data, first, we utilized factor analysis using varimax rotation to account for the DTI metrics as multivariate outcomes. Using factor loadings, we anticipated a two or three-factor model was sufficient to explain the variance of the DTI metrics. Second, we investigated predictive associations between the sleep parameters and the loaded DTI factors, and explored age, sex, BMI, education and APOE4 as covariates underlying any differences. Results: Of the 85 participants, 60 (70.6%) were women, 67 (78.8%) were non-Hispanic Whites. Mean (SD) age, BMI and education was 66.7 (5.3) years, 27.9 (6.1) kg/m2 and 16.8 (2.4) years respectively. We selected the two primary loadings' factor model based on AIC criteria. FA metrics of the investigated brain regions except thalamus, loaded on one factor, conceptualized as manifest indicators for FA. MD and MK metrics of all the investigated brain regions loaded on the second factor, conceptualized as manifest indicators for MD/MK. SWS, %SWS, TST were predictors of FA (P ≤0.01 for all). AHI3a, AHI4%, and SWA were predictors of MD/MK (P ≤0.05 for all). Additionally, sex, age, APOE4 and education were predictors of FA (P ≤0.01 for all). Conclusion: In this limited sample of cognitively-normal older-adults, sleep duration measures predicted gray-matter FA, OSA-severity measures predicted gray matter MD and MK. Demographic, genetic and SES factors explained the differences in these relationships. Support (If Any): AASM 231-BS-20, AARGD-21-8488397, NIH/NIA/NHLBI (K23AG068534, L30-AG064670, CIRAD P30AG059303 Pilot, NYU ADRC P30AG066512 Developmental Grant, R25HL105444, SRG, R01AG12101, R01AG022374, R01AG13616, RF1AG057570, R01HL118624, R01AG056031)