Heterogeneity in the links between sleep arousals, amyloid-β, and cognition.
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ABSTRACT:
SUBMITTER: Chylinski DO
PROVIDER: S-EPMC8783672 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background Sleep fragmentation induced by repetitive arousals is a hallmark of obstructive sleep apnea (OSA). Sleep fragmentation has been linked to hypertension in community-based studies, but it is unclear if this association is manifest in OSA. We aimed to explore whether frequent arousals from sleep modify the relationship between OSA and prevalent hypertension. Methods and Results A total of 10 102 patients with OSA and 1614 primary snorers were included in the study. Hypertension was defined on either direct blood pressure measures or diagnosis by a physician. Spontaneous, respiratory, and movement arousals were derived by polysomnography. Logistic regression models were used to estimate the associations between arousals and prevalent hypertension in patients with OSA and primary snorers. For every 10-unit increase of total arousal index, odds of hypertension significantly increased in both the total sample (odds ratio [OR], 1.08; 95% CI, 1.03-1.14; P=0.002) and patients with OSA (OR, 1.10; 95% CI, 1.04-1.16; P<0.001), but not in the primary snoring group. Total arousal index was significantly associated with systolic blood pressure and diastolic blood pressure in the total sample (β=0.05 and β=0.06; P<0.001) and in patients with (β=0.05 and β=0.06; P<0.01), but not in primary snorers. In addition, a greater influence of respiratory events with arousals than respiratory events without arousals on blood pressure in OSA was also noted. Results were independent of confounders, including apnea-hypopnea index and nocturnal hypoxemia. Conclusions We conclude that repetitive arousals from sleep are independently associated with prevalent hypertension in patients with OSA.
| S-EPMC9075207 | biostudies-literature
Project description:ImportanceDisrupted sleep is common in aging and is associated with cognition. Age-related changes to sleep are associated with multiple causes, including early Alzheimer disease pathology (amyloid β [Aβ]), depression, and cardiovascular disease.ObjectiveTo investigate the associations between self-reported sleep duration and brain Aβ burden as well as the demographic, cognitive, and lifestyle variables in adults with normal cognition.Design, setting, and participantsThis cross-sectional study obtained data from participants in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study, which is being conducted in 67 sites in the United States, Canada, Australia, and Japan. The sample for this analysis consisted of individuals aged 65 to 85 years who underwent an Aβ positron emission tomography (PET) scan, had complete apolipoprotein E (APOE) genotype data, and were identified as clinically normal (per a Clinical Dementia Rating score of 0) and cognitively unimpaired (per a Mini-Mental State Examination score of 25 to 30 and Logical Memory Delayed Recall test score of 6 to 18). Data were analyzed from April 3, 2020, to June 20, 2021.Main outcomes and measuresThe outcome was self-reported nightly sleep duration (grouped by short sleep duration: ≤6 hours, normal sleep duration: 7-8 hours, and long sleep duration: ≥9 hours) compared with demographic characteristics, Aβ burden (as measured with a fluorine 18-labeled-florbetapir PET scan), objective and subjective cognitive function measures, and lifestyle variables.ResultsThe 4417 participants in the study included 2618 women (59%) and had a mean (SD) age of 71.3 (4.7) years. Self-reported shorter sleep duration was linearly associated with higher Aβ burden (β [SE] = -0.01 [0.00]; P = .005), and short sleep duration was associated with reduced cognition that was mostly in memory domains. No difference in Aβ was found between long and normal sleep duration groups (β [SE] = 0.00 [0.01]; P = .99). However, compared with normal sleep duration, both short and long sleep durations were associated with higher body mass index (short vs normal sleep duration: β [SE] = 0.48 [0.17], P = .01; long vs normal sleep duration: β [SE] = 0.97 [0.31], P = .002), depressive symptoms (short vs normal sleep duration: β [SE] = 0.31 [0.05], P < .001; long vs normal sleep duration: β [SE] = 0.39 [0.09], P < .001), and daytime napping (short vs normal sleep duration: β [SE] = 2.66 [0.77], P = .001; long vs normal sleep duration: β [SE] = 3.62 [1.38], P = .01). Long sleep duration was associated with worse performance across multiple cognitive domains.Conclusions and relevanceIn this cross-sectional study, both short and long sleep durations were associated with worse outcomes for older adults, such as greater Aβ burden, greater depressive symptoms, higher body mass index, and cognitive decline, emphasizing the importance of maintaining adequate sleep.
| S-EPMC8406215 | biostudies-literature
Project description:IntroductionCognitive decline in Alzheimer's disease is associated with amyloid beta (Aβ) accumulation, neurodegeneration, and cerebral small vessel disease, but the temporal relationships among these factors is not well established.MethodsData included white matter hyperintensity (WMH) load, gray matter (GM) atrophy and Alzheimer's Disease Assessment Scale-Cognitive-Plus (ADAS13) scores for 720 participants and cerebrospinal fluid amyloid (Aβ1-42) for 461 participants from the Alzheimer's Disease Neuroimaging Initiative. Linear regressions were used to assess the relationships among baseline WMH, GM, and Aβ1-42 to changes in WMH, GM, Aβ1-42, and cognition at 1-year follow-up.ResultsBaseline WMHs and Aβ1-42 predicted WMH increase and GM atrophy. Baseline WMHs and Aβ1-42 predicted worsening cognition. Only baseline Aβ1-42 predicted change in Aβ1-42.DiscussionBaseline WMHs lead to greater future GM atrophy and cognitive decline, suggesting that WM damage precedes neurodegeneration and cognitive decline. Baseline Aβ1-42 predicted WMH increase, suggesting a potential role of amyloid in WM damage.
| S-EPMC7552231 | biostudies-literature
Project description:Amyloid-β (Aβ) accumulation is a hallmark of Alzheimer's disease, although Aβ alone may be insufficient to cause impairments. Modifiable health factors, including sleep, may mitigate functional symptoms of neurodegeneration. We assessed whether sleep moderated the relationship between Aβ and cognitive performance in 41 older adults, mean age 83 years. Sleep measures included actigraphy-assessed wake after sleep onset and total sleep time. Cognitive performance was assessed with memory recall, cognitive flexibility, and verbal fluency. Memory recall was assessed with the Rey-Osterrieth Complex Figure task, cognitive flexibility with the Trail Making test, and verbal fluency with FAS word generation. Aβ was assessed with a global measure of Pittsburgh Compound B. Wake after sleep onset moderated the relationship between Aβ and memory, with a stronger positive association for Aβ and forgetting in those with poorer sleep. These results suggest a possible protective role of sleep in preclinical Alzheimer's disease.
| S-EPMC6416050 | biostudies-literature
Project description:BackgroundStage 1 of the National Institute on Aging-Alzheimer's Association's proposed Alzheimer's disease continuum is defined as amyloid-β (Aβ) positive but cognitively normal. Identifying at-risk individuals before Aβ reaches pathological levels could have great benefits for early intervention. Although Aβ levels become abnormal long before severe cognitive impairments appear, increasing evidence suggests that subtle cognitive changes may begin early, potentially before Aβ surpasses the threshold for abnormality. We examined whether baseline cognitive performance would predict progression from normal to abnormal levels of Aβ.MethodsWe examined the association of baseline cognitive composites (Preclinical Alzheimer Cognitive Composite, Alzheimer's Disease Neuroimaging Initiative (ADNI) memory factor composite) with progression to Aβ positivity in 292 nondemented, Aβ-negative ADNI participants. Additional analyses included continuous cerebrospinal fluid biomarker levels to examine the effects of subthreshold pathology.ResultsForty participants progressed to Aβ positivity during follow-up. Poorer baseline performance on both cognitive measures was significantly associated with increased odds of progression. More abnormal levels of baseline cerebrospinal fluid phosphorylated tau and subthreshold Aβ were associated with increased odds of progression to Aβ positivity. Nevertheless, baseline ADNI memory factor composite performance predicted progression even after controlling for baseline biomarker levels and APOE genotype (Preclinical Alzheimer Cognitive Composite was trend level). Survival analyses were largely consistent: controlling for baseline biomarker levels, baseline Preclinical Alzheimer Cognitive Composite still significantly predicted progression time to Aβ positivity (ADNI memory factor composite was trend level).ConclusionsThe possibility of intervening before Aβ reaches pathological levels is of obvious benefit. Low-cost, noninvasive cognitive measures can be informative for determining who is likely to progress to Aβ positivity, even after accounting for baseline subthreshold biomarker levels.
| S-EPMC7166153 | biostudies-literature
Project description:ObjectiveSerotoninergic neurotransmission may modulate β-amyloid peptide (Aβ) metabolism through upregulation of α-secretase. Early Parkinson disease (PD) shows variable serotoninergic denervation, which may impact Aβ deposition.MethodsWe conducted 3 analyses to explore associations between serotoninergic neurotransmission and cerebral Aβ burden in PD. The first was a cross-sectional imaging study of PD subjects (n = 23) using the serotoninergic transporter positron emission tomography (PET) ligand [11 C]3-amino-4-(2-dimethylaminomethyl-phenylsulfaryl)-benzonitrile (DASB) and amyloid PET Pittsburgh compound B ([11 C]PiB). The second was a baseline study of Parkinson's Progression Markers Initiative (PPMI) subjects exploring the influence of serotoninergic medications on cerebrospinal fluid (CSF) Aβ-42 levels (n = 389), controlling for age, sex, Geriatric Depression Scale, disease duration, and education. Third, we fit an interval censored proportional hazard model with longitudinal PPMI data (n = 367) to test whether serotoninergic medication use associates with reduced risk of PD cognitive decline, defined as time to reach a Montreal Cognitive Assessment score ≤ 20, adjusting for baseline caudate dopamine transporter [123 I]ioflupane single photon emission computed tomography and CSF Aβ-42 levels.ResultsSerotoninergic DASB distribution volume ratio (DVR) inversely associated with PiB DVR in the cerebral cortex (Pearson r = -0.478, p = 0.021) but not the striatum (r = -0.264, p = 0.224). In the baseline PPMI analysis, serotoninergic medication use for ≥6 months associated with a lower level of CSF Aβ-42 (t = -2.20, p = 0.029). In the longitudinal PPMI model, baseline serotoninergic medication use associated with a reduced risk of cognitive decline (t = -2.03, p = 0.043) after controlling for covariates.InterpretationCortical Aβ burden in PD associates inversely with serotoninergic innervation. Serotoninergic medications may alter Aβ metabolism and reduce the risk of PD cognitive decline. Ann Neurol 2018;83:994-1002.
| S-EPMC6021203 | biostudies-literature
Project description:ObjectivesTo investigate spatial heterogeneity of white matter lesions or hyperintensities (WMH).MethodsMRI scans of 1,836 participants (median age 52.2 ± 13.16 years) encompassing a wide age range (22-84 years) from the cross-sectional Study of Health in Pomerania (Germany) were included as discovery set identifying spatially distinct components of WMH using a structural covariance approach. Scans of 307 participants (median age 73.8 ± 10.2 years, with 747 observations) from the Baltimore Longitudinal Study of Aging (United States) were included to examine differences in longitudinal progression of these components. The associations of these components with vascular risk factors, cortical atrophy, Alzheimer disease (AD) genetics, and cognition were then investigated using linear regression.ResultsWMH were found to occur nonuniformly, with higher frequency within spatially heterogeneous patterns encoded by 4 components, which were consistent with common categorizations of deep and periventricular WMH, while further dividing the latter into posterior, frontal, and dorsal components. Temporal trends of the components differed both cross-sectionally and longitudinally. Frontal periventricular WMH were most distinctive as they appeared in the fifth decade of life, whereas the other components appeared later in life during the sixth decade. Furthermore, frontal WMH were associated with systolic blood pressure and with pronounced atrophy including AD-related regions. AD polygenic risk score was associated with the dorsal periventricular component in the elderly. Cognitive decline was associated with the dorsal component.ConclusionsThese results support the hypothesis that the appearance of WMH follows age and disease-dependent regional distribution patterns, potentially influenced by differential underlying pathophysiologic mechanisms, and possibly with a differential link to vascular and neurodegenerative changes.
| S-EPMC6139818 | biostudies-literature
Project description:Sleep restriction alters food intake, but less is known about how dietary patterns affect sleep. Current goals were to determine whether: (1) sleep is different after consumption of a controlled diet vs. an ad libitum diet, and (2) dietary intake during ad libitum feeding is related to nocturnal sleep.Twenty-six normal weight adults (30-45 y), habitually sleeping 7-9 h/night, participated in a randomized-crossover inpatient study with 2 phases of 5 nights: short (4 h in bed) or habitual (9 h in bed) sleep. Only data from the habitual sleep phase were used for the present analyses. During the first 4 days, participants consumed a controlled diet; on day 5, food intake was self-selected. Linear regression was used to determine relations between daytime food intake and nighttime sleep on day 5.Sleep duration did not differ after 3 days of controlled feeding vs. a day of ad libitum intake. However, sleep after ad libitum eating had less slow wave sleep (SWS, P = 0.0430) and longer onset latency (P = 0.0085). Greater fiber intake predicted less stage 1 (P = 0.0198) and more SWS (P = 0.0286). Percent of energy from saturated fat predicted less SWS (P = 0.0422). Higher percent of energy from sugar and other carbohydrates not considered sugar or fiber was associated with arousals (P = 0.0320 and 0.0481, respectively).Low fiber and high saturated fat and sugar intake is associated with lighter, less restorative sleep with more arousals. Diet could be useful in the management of sleep disorders but this needs to be tested.http://www.clinicaltrials.gov, #NCT00935402.
| S-EPMC4702189 | biostudies-literature
Project description:See Coulthard and Knight (doi:10.1093/aww335) for a scientific commentary on this article.Individuals with mild cognitive impairment and Alzheimer's disease clinical diagnoses can display significant phenotypic heterogeneity. This variability likely reflects underlying genetic, environmental and neuropathological differences. Characterizing this heterogeneity is important for precision diagnostics, personalized predictions, and recruitment of relatively homogeneous sets of patients into clinical trials. In this study, we apply state-of-the-art semi-supervised machine learning methods to the Alzheimer's disease Neuroimaging cohort (ADNI) to elucidate the heterogeneity of neuroanatomical differences between subjects with mild cognitive impairment (n = 530) and Alzheimer's disease (n = 314) and cognitively normal individuals (n = 399), thereby adding to an increasing literature aiming to establish neuroanatomical and neuropathological (e.g. amyloid and tau deposition) dimensions in Alzheimer's disease and its prodromal stages. These dimensional approaches aim to provide surrogate measures of heterogeneous underlying pathologic processes leading to cognitive impairment. We relate these neuroimaging patterns to cerebrospinal fluid biomarkers, white matter hyperintensities, cognitive and clinical measures, and longitudinal trajectories. We identified four such atrophy patterns: (i) individuals with largely normal neuroanatomical profiles, who also turned out to have the least abnormal cognitive and cerebrospinal fluid biomarker profiles and the slowest clinical progression during follow-up; (ii) individuals with classical Alzheimer's disease neuroanatomical, cognitive, cerebrospinal fluid biomarkers and clinical profile, who presented the fastest clinical progression; (iii) individuals with a diffuse pattern of atrophy with relatively less pronounced involvement of the medial temporal lobe, abnormal cerebrospinal fluid amyloid-β1-42 values, and proportionally greater executive impairment; and (iv) individuals with notably focal involvement of the medial temporal lobe and a slow steady progression, likely representing in early Alzheimer's disease stages. These four atrophy patterns effectively define a 4-dimensional categorization of neuroanatomical alterations in mild cognitive impairment and Alzheimer's disease that can complement existing dimensional approaches for staging Alzheimer's disease using a variety of biomarkers, which offer the potential for enabling precision diagnostics and prognostics, as well as targeted patient recruitment of relatively homogeneous subgroups of subjects for clinical trials.
| S-EPMC5837514 | biostudies-literature
Project description:Study Objectives:The current definition of sleep arousals neglects to address the diversity of arousals and their systemic cohesion. Autonomic arousals (AA) are autonomic activations often associated with cortical arousals (CA), but they may also occur in relation to a respiratory event, a leg movement event or spontaneously, without any other physiological associations. AA should be acknowledged as essential events to understand and explore the systemic implications of arousals. Methods:We developed an automatic AA detection algorithm based on intelligent feature selection and advanced machine learning using the electrocardiogram. The model was trained and tested with respect to CA systematically scored in 258 (181 training size/77 test size) polysomnographic recordings from the Wisconsin Sleep Cohort. Results:A precision value of 0.72 and a sensitivity of 0.63 were achieved when evaluated with respect to CA. Further analysis indicated that 81% of the non-CA-associated AAs were associated with leg movement (38%) or respiratory (43%) events. Conclusions:The presented algorithm shows good performance when considering that more than 80% of the false positives (FP) found by the detection algorithm appeared in relation to either leg movement or respiratory events. This indicates that most FP constitute autonomic activations that are indistinguishable from those with cortical cohesion. The proposed algorithm provides an automatic system trained in a clinical environment, which can be utilized to analyze the systemic and clinical impacts of arousals.
| S-EPMC5914410 | biostudies-literature