Sex differences in the association of sleep spindle density and cognitive performance among community-dwelling middle-aged and older adults with obstructive sleep apnea.

Recent studies have found associations between obstructive sleep apnea and cognitive decline. The underlying mechanisms are still unclear. Here, we investigate the associations between changes in micro-architecture, specifically sleep spindles, and cognitive function in community-dwelling middle-aged and older adults, some with obstructive sleep apnea, with a focus on sex differences. A total of 125 voluntary participants (mean age 66.0 ± 6.4 years, 64 females) from a larger cohort (participants of the Brain in Motion Studies I and II) underwent 1 night of in-home polysomnography and a neuropsychological battery (sleep and cognitive testing were conducted within 2 weeks of each other). A semi-automatic computerized algorithm was used to score polysomnography data and detect spindle characteristics in non-rapid eye movement Stages 2 and 3 in both frontal and central electrodes. Based on their apnea-hypopnea index, participants were divided into those with no obstructive sleep apnea (apnea-hypopnea index < 5 per hr, n = 21), mild obstructive sleep apnea (5 ≥ apnea-hypopnea index < 15, n = 47), moderate obstructive sleep apnea (15 ≥ apnea-hypopnea index < 30, n = 34) and severe obstructive sleep apnea (apnea-hypopnea index ≥ 30, n = 23). There were no significant differences in spindle characteristics between the four obstructive sleep apnea severity groups. Spindle density and percentage of fast spindles were positively associated with some verbal fluency measures on the cognitive testing. Sex might be linked with these associations. Biological sex could play a role in the associations between spindle characteristics and some verbal fluency measures. Obstructive sleep apnea severity was not found to be a contributing factor in this non-clinical community-dwelling cohort.

Association of sleep spindle characteristics with executive functioning in healthy sedentary middle-aged and older adults.

To determine the relationship between sleep spindle characteristics (density, power and frequency), executive functioning and cognitive decline in older adults, we studied a convenience subsample of healthy middle-aged and older participants of the Brain in Motion study. Participants underwent a single night of unattended in-home polysomnography with neurocognitive testing carried out shortly afterwards. Spectral analysis of the EEG was performed to derive spindle characteristics in both central and frontal derivations during non-rapid eye movement (NREM) Stage 2 and 3. Multiple linear regressions were used to examine associations between spindle characteristics and cognitive outcomes, with age, body mass index (BMI), periodic limb movements index (PLMI) and apnea hypopnea index (AHI) as covariates. NREM Stage 2 total spindle density was significantly associated with executive functioning (central: ß = .363, p = .016; frontal: ß = .408, p = .004). NREM Stage 2 fast spindle density was associated with executive functioning (central: ß = .351, p = .022; frontal: ß = .380, p = .009) and Montreal Cognitive Assessment score (MoCA, central: ß = .285, p = .037; frontal: ß = .279, p = .032). NREM Stage 2 spindle frequency was also associated with MoCA score (central: ß = .337, p = .013). Greater spindle density and fast spindle density were associated with better executive functioning and less cognitive decline in our study population. Our cross-sectional design cannot infer causality. Longitudinal studies will be required to assess the ability of spindle characteristics to predict future cognitive status.

White matter tract microstructure and cognitive performance after transient ischemic attack.

BACKGROUND AND PURPOSE: Patients with transient ischemic attack (TIA) show evidence of cognitive impairment but the reason is not clear. Measurement of microstructural changes in white matter (WM) using diffusion tensor imaging (DTI) may be a useful outcome measure. We report WM changes using DTI and the relationship with neuropsychological performance in a cohort of transient ischemic attack (TIA) and non-TIA subjects. METHODS: Ninety-five TIA subjects and 51 non-TIA subjects were assessed using DTI and neuropsychological batteries. Fractional anisotropy (FA) and mean diffusivity (MD) maps were generated and measurements were collected from WM tracts. Adjusted mixed effects regression modelled the relationship between groups and DTI metrics. RESULTS: Transient ischemic attack subjects had a mean age of 67.9 ± 9.4 years, and non-TIA subjects had a mean age 64.9 ± 9.9 years. The TIA group exhibited higher MD values in the fornix (0.36 units, P < 0.001) and lower FA in the superior longitudinal fasciculus (SLF) (-0.29 units, P = 0.001), genu (-0.22 units, P = 0.016), and uncinate fasciculus (UF) (-0.26 units, P = 0.004). Compared to non-TIA subjects, subjects with TIA scored lower on the Addenbrooke's Cognitive Assessment-Revised (median score 95 vs 91, P = 0.01) but showed no differences in scores on the Montreal Cognitive Assessment (median 27 vs 26) or the Mini-Mental State Examination (median 30). TIA subjects had lower scores in memory (median 44 vs 52, P < 0.01) and processing speed (median 45 vs 62, P < 0.01) but not executive function, when compared to non-TIA subjects. Lower FA and higher MD in the fornix, SLF, and UF were associated with poorer performance on tests of visual memory and executive function but not verbal memory. Lower FA in the UF and fornix were related to higher timed scores on the TMT-B (P < 0.01), and higher SLF MD was related to higher scores on TMT-B (P < 0.01), confirming worse executive performance in the TIA group. CONCLUSIONS: DTI scans may be useful for detecting microstructural disease in TIA subjects before cognitive symptoms develop. DTI parameters, white matter hyperintensities, and vascular risk factors underly some of the altered neuropsychological measures in TIA subjects.

A longitudinal magnetic resonance imaging study of neurodegenerative and small vessel disease, and clinical cognitive trajectories in non demented patients with transient ischemic attack: the PREVENT study.

BACKGROUND: Late-life cognitive decline, caused by progressive neuronal loss leading to brain atrophy years before symptoms are detected, is expected to double in Canada over the next two decades. Cognitive impairment in late life is attributed to vascular and lifestyle related risk factors in mid-life in a substantial proportion of cases (50%), thereby providing an opportunity for effective prevention of cognitive decline if incipient disease is detected earlier. Patients presenting with transient ischemic attack (TIA) commonly display some degree of cognitive impairment and are at a 4-fold increased risk of dementia. In the Predementia Neuroimaging of Transient Ischemic Attack (PREVENT) study, we will address what disease processes (i.e., Alzheimer's vs. vascular disease) lead to neurodegeneration, brain atrophy, and cognitive decline, and whether imaging measurements of brain iron accumulation using quantitative susceptibility mapping predicts subsequent brain atrophy and cognitive decline. METHODS: A total of 440 subjects will be recruited for this study with 220 healthy subjects and 220 TIA patients. Early Alzheimer's pathology will be determined by cerebrospinal fluid samples (including tau, a marker of neuronal injury, and amyloid ß1-42) and by MR measurements of iron accumulation, a marker for Alzheimer's-related neurodegeneration. Small vessel disease will be identified by changes in white matter lesion volume. Predictors of advanced rates of cerebral and hippocampal atrophy at 1 and 3 years will include in vivo Alzheimer's disease pathology markers, and MRI measurements of brain iron accumulation and small vessel disease. Clinical and cognitive function will be assessed annually post-baseline for a period of 5-years using a clinical questionnaire and a battery of neuropsychological tests, respectively. DISCUSSION: The PREVENT study expects to demonstrate that TIA patients have increased early progressive rates of cerebral brain atrophy after TIA, before cognitive decline can be clinically detected. By developing and optimizing high-level machine learning models based on clinical data, image-based (quantitative susceptibility mapping, regional brain, and white matter lesion volumes) features, and cerebrospinal fluid biomarkers, PREVENT will provide a timely opportunity to identify individuals at greatest risk of late-life cognitive decline early in the course of disease, supporting future therapeutic strategies for the promotion of healthy aging.