We aimed to investigate the association of pineal gland volume with the risk of isolated rapid eye movement (REM) sleep behavior disorder (RBD). We enrolled 245 community-dwelling cognitively normal elderly individuals without major psychiatric or neurological disorders at the baseline evaluation, of whom 146 completed the 2-year follow-up evaluation. We assessed RBD symptoms using the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) and defined probable RBD (pRBD) as an RBDSQ score of ≥ 5. We manually segmented the pineal gland on 3T T1-weighted brain magnetic resonance imaging and estimated its volume. The smaller the baseline pineal gland volume, the more severe the RBD symptoms at baseline. The individuals with isolated pRBD showed smaller pineal gland volumes than those without isolated pRBD. The larger the baseline pineal gland volume, the lower the risks of prevalent isolated pRBD at the baseline evaluation and incident isolated pRBD at the 2-year follow-up evaluation. Pineal gland volume showed good diagnostic accuracy for prevalent isolated pRBD and predictive accuracy for incident isolated pRBD in the receiver operator characteristic analysis. Our findings suggest that pineal gland volume may be associated with the severity of RBD symptoms and the risk of isolated RBD in cognitively normal elderly individuals.

Our findings suggest that high lifetime coffee consumption may reduce VPP, and that this reduction in VPP may impair the quality of sleep in late life.

Background To investigate the association between pineal gland volume and symptoms of rapid eye movement (REM) sleep behavior disorder (RBD) in Alzheimer’s disease (AD) patients without any feature of dementia with Lewy bodies. Methods We enrolled 296 community-dwelling probable AD patients who did not meet the diagnostic criteria for possible or probable dementia with Lewy bodies. Among them, 93 were amyloid beta (Aβ) positive on 18F-florbetaben amyloid brain positron emission tomography. We measured RBD symptoms using the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) and defined probable RBD (pRBD) as the RBDSQ of 5 or higher. We manually segmented pineal gland on 3T structural T1-weighted brain magnetic resonance imaging. Results The participants with pRBD had smaller pineal parenchyma volume (VPP) than those without pRBD (p <  0.001). The smaller the VPP, the more severe the RBD symptoms (p <  0.001). VPP was inversely associated with risk of prevalent pRBD (odds ratio = 0.909, 95% confidence interval [CI] = 0.878–0.942, p <  0.001). Area under the receiver operator characteristic curve for pRBD of VPP was 0.80 (95% CI = 0.750–0.844, p <  0.0001). These results were not changed when we analyzed the 93 participants with Aβ-positive AD separately. Conclusions In AD patients, reduced pineal gland volume may be associated with RBD.

Coffee consumption is associated with cerebral hypoperfusion that may contribute to the development of cerebral white matter hyperintensities (WMH). We investigated the effect of lifetime coffee consumption on the volume of WMH (VWMH) in late life, and compared the effect between men and women since caffeine clearance may be different between sexes. We enrolled 492 community-dwelling cognitively normal elderly individuals (73.4 ± 6.7 years old on average) from the Korean Longitudinal Study on Cognitive Aging and Dementia. We evaluated their patterns and amounts of coffee consumption using a study-specific standardized interview and estimated cerebral VWMH by automatic segmentation of brain fluid-attenuated inversion recovery sequence magnetic resonance images. Higher cumulative lifetime coffee consumption was associated with higher logVWMH in both sexes (p = 0.030). The participants who consumed more than 2 cups of coffee per day on average in their lifetime showed higher logVWMH in late life than those who consumed less. When both sexes were analyzed separately, these coffee-logVWMH associations were found only in women, although the volumes of brain and white matter of women were smaller than those of men. Our findings suggest that prolonged high coffee consumption may be associated with the risk of WMH in late life.

Background and Objectives:Gait changes are potential markers of cognitive disorders (CD). We developed a model for classifying older adults with CD from those with normal cognition using gait speed and variability captured from a wearable inertia sensor and compared its diagnostic performance for CD with that of the model using the Mini-Mental State Examination (MMSE).Methods:We enrolled community-dwelling older adults with normal gait from the Korean Longitudinal Study on Cognitive Aging and Dementia and measured their gait features using a wearable inertia sensor placed at the center of body mass while they walked on a 14-m long walkway thrice at comfortable paces. We randomly split our entire dataset into the development (80%) and validation (20%) datasets. We developed a model for classifying CD using logistic regression analysis from the development dataset and validated it in the validation dataset. In both datasets, we compared the diagnostic performance of the model with that using the MMSE. We estimated optimal cutoff score of our model using receiver operator characteristics analysis.Results:In total, 595 participants were enrolled, 101 of them had CD. Our model included both gait speed and temporal gait variability and exhibited good diagnostic performance for classifying CD from normal cognition in both the development (area under the receiver operator characteristic curve [AUC] = 0.788, 95% confidence interval [CI] = 0.748–0.823, p < 0.001) and validation datasets (AUC = 0.811, 95% CI = 0.729–0.877, p < 0.001). Our model showed comparable diagnostic performance for CD to that of the model using the MMSE in both the development (difference in AUC = 0.026, standard error [SE] = 0.043, z statistic = 0.610, p = 0.542) and validation datasets (difference in AUC = 0.070, SE = 0.073, z statistic = 0.956, p = 0.330). The optimal cutoff score of the gait-based model was > -1.56.Discussion:Our gait-based model using a wearable inertia sensor may be a promising diagnostic marker of CD in older adults.Classification of Evidence:This study provides Class III evidence that gait analysis can accurately distinguish cognitive disorders from healthy controls in older adults.