A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.

Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10-15% of people annually convert to AD. We aimed to investigate the most robust model and modality combination by combining multi-modality image features based on demographic characteristics in six machine learning models. A total of 196 subjects were enrolled from four hospitals and the Alzheimer's Disease Neuroimaging Initiative dataset. During the four-year follow-up period, 47 (24%) patients progressed from MCI to AD. Volumes of the regions of interest, white matter hyperintensity, and regional Standardized Uptake Value Ratio (SUVR) were analyzed using T1, T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRIs, and amyloid PET (αPET), along with automatically provided hippocampal occupancy scores (HOC) and Fazekas scales. As a result of testing the robustness of the model, the GBM model was the most stable, and in modality combination, model performance was further improved in the absence of T2-FLAIR image features. Our study predicts the probability of AD conversion in MCI patients, which is expected to be useful information for clinician's early diagnosis and treatment plan design.

Impact of Apolipoprotein E4 on the Locus Coeruleus Functional Connectivity in Preclinical Alzheimer's Disease.

Background: Recent interest has surged in the locus coeruleus (LC) for its early involvement in Alzheimer's disease (AD), notably concerning the apolipoprotein ɛ4 allele (APOE4). Objective: This study aimed to discern LC functional connectivity (FC) variations in preclinical AD subjects, dissecting the roles of APOE4 carrier status and amyloid-ß (Aß) deposition. Methods: A cohort of 112 cognitively intact individuals, all Aß-positive, split into 70 APOE4 noncarriers and 42 carriers, underwent functional MRI scans, neuropsychological assessments, and APOE genotyping. The research utilized seed to voxel analysis for illustrating LC rsFC discrepancies between APOE4 statuses and employed a general linear model to examine the interactive influence of APOE4 carrier status and Aß deposition on LC FC values. Results: The investigation revealed no significant differences in sex, age, or SUVR between APOE4 carriers and noncarriers. It found diminished LC FC with the occipital cortex in APOE4 carriers and identified a significant interaction between APOE4 carrier status and temporal lobe SUVR in LC FC with the occipital cortex. This interaction suggested a proportional increase in LC FC for APOE4 carriers. Additional notable interactions were observed affecting LC FC with various brain regions, indicating a proportional decrease in LC FC for APOE4 carriers. Conclusions: These findings confirm that APOE4 carrier status significantly influences LC FC in preclinical AD, showcasing an intricate relationship with regional Aß deposition. This underscores the critical role of genetic and pathological factors in early AD pathophysiology, offering insights into potential biomarkers for early detection and intervention strategies.

Development of Efficient Brain Age Estimation Method Based on Regional Brain Volume From Structural Magnetic Resonance Imaging.

OBJECTIVE: We aimed to create an efficient and valid predicting model which can estimate individuals' brain age by quantifying their regional brain volumes. METHODS: A total of 2,560 structural brain magnetic resonance imaging (MRI) scans, along with demographic and clinical data, were obtained. Pretrained deep-learning models were employed to automatically segment the MRI data, which enabled fast calculation of regional brain volumes. Brain age gaps for each subject were estimated using volumetric values from predefined 12 regions of interest (ROIs): bilateral frontal, parietal, occipital, and temporal lobes, as well as bilateral hippocampus and lateral ventricles. A larger weight was given to the ROIs having a larger mean volumetric difference between the cognitively unimpaired (CU) and cognitively impaired group including mild cognitive impairment (MCI), and dementia groups. The brain age was predicted by adding or subtracting the brain age gap to the chronological age according to the presence or absence of the atrophy region. RESULTS: The study showed significant differences in brain age gaps among CU, MCI, and dementia groups. Furthermore, the brain age gaps exhibited significant correlations with education level and measures of cognitive function, including the clinical dementia rating sum-of-boxes and the Korean version of the Mini-Mental State Examination. CONCLUSION: The brain age that we developed enabled fast and efficient brain age calculations, and it also reflected individual's cognitive function and cognitive reserve. Thus, our study suggested that the brain age might be an important marker of brain health that can be used effectively in real clinical settings.

Associations between Education Years and Resting-state Functional Connectivity Modulated by APOE ε4 Carrier Status in Cognitively Normal Older Adults.

Objective: : Cognitive reserve has emerged as a concept to explain the variable expression of clinical symptoms in the pathology of Alzheimer's disease (AD). The association between years of education, a proxy of cognitive reserve, and resting-state functional connectivity (rFC), a representative intermediate phenotype, has not been explored in the preclinical phase, considering risk factors for AD. We aimed to evaluate whether the relationship between years of education and rFC in cognitively preserved older adults differs depending on amyloid-beta deposition and APOE ε4 carrier status as effect modifiers. Methods: : A total of 121 participants underwent functional magnetic resonance imaging, [18F] flutemetamol positron emission tomography-computed tomography, APOE genotyping, and a neuropsychological battery. Potential interactions between years of education and AD risk factors for rFC of AD-vulnerable neural networks were assessed with whole-brain voxel-wise analysis. Results: : We found a significant education years-by-APOE ε4 carrier status interaction for the rFC from the seed region of the central executive (CEN) and dorsal attention networks. Moreover, there was a significant interaction of rFC between right superior occipital gyrus and the CEN seed region by APOE ε4 carrier status for memory performances and overall cognitive function. Conclusion: : In preclinical APOE ε4 carriers, higher years of education were associated with higher rFC of the AD vulnerable network, but this contributed to lower cognitive function. These results contribute to a deeper understanding of the impact of cognitive reserve on sensitive functional intermediate phenotypic markers in the preclinical phase of AD.

Increased Likelihood of Dementia with Coexisting Atrophy of Multiple Regions of Interest.

BACKGROUND: Brain volume is associated with cognitive decline in later life, and cortical brain atrophy exceeding the normal range is related to inferior cognitive and behavioral outcomes in later life. OBJECTIVE: To investigate the likelihood of cognitive decline, mild cognitive impairment (MCI), or dementia, when regional atrophy is present in participants' magnetic resonance imaging (MRI). METHODS: Multi-center MRI data of 2,545 adults were utilized to measure regional volumes using NEUROPHET AQUA. Four lobes (frontal, parietal, temporal, and occipital), four Alzheimer's disease-related regions (entorhinal, fusiform, inferior temporal, and middle temporal area), and the hippocampus in the left and right hemispheres were measured and analyzed. The presence of regional atrophy from brain MRI was defined as ≤1.5 standard deviation (SD) compared to the age- and sex-matched cognitively normal population. The risk ratio for cognitive decline was investigated for participants with regional atrophy in contrast to those without regional atrophy. RESULTS: The risk ratio for cognitive decline was significantly higher when hippocampal atrophy was present (MCI, 1.84, p < 0.001; dementia, 4.17, p < 0.001). Additionally, participants with joint atrophy in multiple regions showed a higher risk ratio for dementia, e.g., 9.6 risk ratio (95% confidence interval, 8.0-11.5), with atrophy identified in the frontal, temporal, and hippocampal gray matter, than those without atrophy. CONCLUSIONS: Our study showed that individuals with multiple regional atrophy (either lobar or AD-specific regions) have a higher likelihood of developing dementia compared to the age- and sex-matched population without atrophy. Thus, further consideration is needed when assessing MRI findings.

A regional brain volume-based age prediction model for neonates and the derived brain maturation index.

OBJECTIVE: To develop a postmenstrual age (PMA) prediction model based on segmentation volume and to evaluate the brain maturation index using the proposed model. METHODS: Neonatal brain MRIs without clinical illness or structural abnormalities were collected from four datasets from the Developing Human Connectome Project, the Catholic University of Korea, Hammersmith Hospital (HS), and Dankook University Hospital (DU). T1- and T2-weighted images were used to train a brain segmentation model. Another model to predict the PMA of neonates based on segmentation data was developed. Accuracy was assessed using mean absolute error (MAE), root mean square error (RMSE), and mean error (ME). The brain maturation index was calculated as the difference between the PMA predicted by the model and the true PMA, and its correlation with postnatal age was analyzed. RESULTS: A total of 247 neonates (mean gestation age 37 ± 4 weeks; range 24-42 weeks) were included. Thirty-one features were extracted from each neonate and the three most contributing features for PMA prediction were the right lateral ventricle, left caudate, and corpus callosum. The predicted and true PMA were positively correlated (coefficient = 0.88, p < .001). MAE, RMSE, and ME of the external dataset of HS and DU were 1.57 and 1.33, 1.79 and 1.37, and 0.37 and 0.06 weeks, respectively. The brain maturation index negatively correlated with postnatal age (coefficient = - 0.24, p < .001). CONCLUSION: A model that calculates the regional brain volume can predict the PMA of neonates, which can then be utilized to show the brain maturation degree. CLINICAL RELEVANCE STATEMENT: A brain maturity index based on regional volume of neonate's brain can be used to measure brain maturation degree, which can help identify the status of early brain development. KEY POINTS: • Neonatal brain MRI segmentation model could be used to assess neonatal brain maturation status. • A postmenstrual age (PMA) prediction model was developed based on a neonatal brain MRI segmentation model. • The brain maturation index, derived from the PMA prediction model, enabled the estimation of the neonatal brain maturation status.

Automatic segmentation of white matter hyperintensities in T2-FLAIR with AQUA: A comparative validation study against conventional methods.

White matter hyperintensities (WMHs) are lesions in the white matter of the brain that are associated with cognitive decline and an increased risk of dementia. The manual segmentation of WMHs is highly time-consuming and prone to intra- and inter-variability. Therefore, automatic segmentation approaches are gaining attention as a more efficient and objective means to detect and monitor WMHs. In this study, we propose AQUA, a deep learning model designed for fully automatic segmentation of WMHs from T2-FLAIR scans, which improves upon our previous study for small lesion detection and incorporating a multicenter approach. AQUA implements a two-dimensional U-Net architecture and uses patch-based training. Additionally, the network was modified to include Bottleneck Attention Module on each convolutional block of both the encoder and decoder to enhance performance for small-sized WMH. We evaluated the performance and robustness of AQUA by comparing it with five well-known supervised and unsupervised methods for automatic segmentation of WMHs (LGA, LPA, SLS, UBO, and BIANCA). To accomplish this, we tested these six methods on the MICCAI 2017 WMH Segmentation Challenge dataset, which contains MRI images from 170 elderly participants with WMHs of presumed vascular origin, and assessed their robustness across multiple sites and scanner types. The results showed that AQUA achieved superior performance in terms of spatial (Dice = 0.72) and volumetric (logAVD = 0.10) agreement with the manual segmentation compared to the other methods. While the recall and F1-score were moderate at 0.49 and 0.59, respectively, they improved to 0.75 and 0.82 when excluding small lesions (≤ 6 voxels). Remarkably, despite being trained on a different dataset with different ethnic backgrounds, lesion loads, and scanners, AQUA's results were comparable to the top 10 ranked methods of the MICCAI challenge. The findings suggest that AQUA is effective and practical for automatic segmentation of WMHs from T2-FLAIR scans, which could help identify individuals at risk of cognitive decline and dementia and allow for early intervention and management.

Modulation of associations between education years and cortical volume in Alzheimer's disease vulnerable brain regions by Aß deposition and APOE ε4 carrier status in cognitively normal older adults.

Background: Education years, as a measure of cognitive reserve, have been shown to affect the progression of Alzheimer's disease (AD), both pathologically and clinically. However, inconsistent results have been reported regarding the association between years of education and intermediate structural changes in AD-vulnerable brain regions, particularly when AD risk factors were not considered during the preclinical phase. Objective: This study aimed to examine how Aß deposition and APOE ε4 carrier status moderate the relationship between years of education and cortical volume in AD-vulnerable regions among cognitively normal older adults. Methods: A total of 121 participants underwent structural MRI, [18F] flutemetamol PET-CT imaging, and neuropsychological battery assessment. Multiple regression analysis was conducted to examine the interaction between years of education and the effects of potential modifiers on cortical volume. The associations between cortical volume and neuropsychological performance were further explored in subgroups categorized based on AD risk factors. Results: The cortical volume of the left lateral occipital cortex and bilateral fusiform gyrus demonstrated a significant differential association with years of education, depending on the presence of Aß deposition and APOE ε4 carrier status. Furthermore, a significant relationship between the cortical volume of the bilateral fusiform gyrus and AD-nonspecific cognitive function was predominantly observed in individuals without AD risk factors. Conclusion: AD risk factors exerted varying influences on the association between years of education and cortical volume during the preclinical phase. Further investigations into the long-term implications of these findings would enhance our understanding of cognitive reserves in the preclinical stages of AD.

Sex-Related Disparities in the Resting State Functional Connectivity of the Locus Coeruelus and Salience Network in Preclinical Alzheimer's Disease.

Recent studies have demonstrated the pivotal role of locus coeruleus (LC) and salience network (SN) resting state functional connectivity (rsFC) changes in the early stage of Alzheimer's disease (AD). Moreover, sex has been a crucial point of discussion in understanding AD pathology. We aimed to demonstrate the sex-related disparities in the functional connectivity (FC) of the SN and LC in preclinical AD. A total of 89 cognitively normal patients with evidence of amyloid beta (Aß) accumulation ([18F] flutemetamol +) were recruited in the study. A seed-to-voxel analysis was conducted to measure the LC and SN rsFC differences between sexes. In addition, sex by Aß interactive effects on FC values were analyzed with a general linear model. There were statistically significant sex by regional standardized uptake value ratio (SUVR) interactions in the LC FC with the parietal, frontal, and occipital cortices. Moreover, there was a significant sex by global SUVR interaction in the SN FC with the temporal cortex. The findings suggest that there are differential patterns of LC FC and SN FC in males and females with preclinical AD, which interact with regional Aß deposition.

Cognitive Normal Older Adults with APOE-2 Allele Show a Distinctive Functional Connectivity Pattern in Response to Cerebral Aß Deposition.

The ε2 allele of apolipoprotein E (ε2) has neuroprotective effects against beta-amyloid (Aß) pathology in Alzheimer's disease (AD). However, its impact on the functional connectivity and hub efficiency in cognitively normal older adults (CN) with ε2 is unclear. We investigated the functional connectivity differences in the default mode network (DMN), salience network, and central executive network (CEN) between A-PET-negative (N = 29) and A-PET-positive (N = 15) CNs with ε2/ε2 or ε2/ε3 genotypes. The A-PET-positive CNs exhibited a lower anterior DMN functional connectivity, higher posterior DMN functional connectivity, and increased CEN functional connectivity compared to the A-PET-negative CNs. Cerebral Aß retention was negatively correlated with anterior DMN functional connectivity and positively correlated with posterior DMN and anterior CEN functional connectivity. A graph theory analysis showed that the A-PET-positive CNs displayed a higher betweenness centrality in the middle frontal gyrus (left) and medial fronto-parietal regions (left). The betweenness centrality in the middle frontal gyrus (left) was positively correlated with Aß retention. Our findings reveal a reversed anterior-posterior dissociation in the DMN functional connectivity and heightened CEN functional connectivity in A-PET-positive CNs with ε2. Hub efficiencies, measured by betweenness centrality, were increased in the DMN and CEN of the A-PET-positive CNs with ε2. These results suggest unique functional connectivity responses to Aß pathology in CN individuals with ε2.

Effect of physical activity on the change in carotid intima-media thickness: An 8-year prospective cohort study.

BACKGROUND AND AIMS: There is a demand for longitudinal studies that use both objective and subjective measures of physical activity to investigate the association of physical activity with the change in carotid intima-media thickness (CIMT). In order to investigate such association, we conducted an 8-year follow-up study that used both objective and subjective measures of physical activity. METHODS: This cohort study used subsamples of the ongoing Korean Genome and Epidemiology Study (KoGES). Included participants were between 49 to 79 years of age at baseline. Exclusion criteria included incomplete assessments of pedometer/accelerometer, international physical activity questionnaire (IPAQ), and baseline CIMT. Participants with a history of cardiovascular diseases were further excluded. Linear regression models were used for the main analysis. Age differences were assessed by stratifying the participants into < 60 years and ≥ 60 years. RESULTS: After removing excluded participants, 835 participants were included in the final analysis (age, 59.84 ± 6.53 years; 326 (39.04%) males). 453 participants were < 60 years and 382 participants were ≥ 60 years. The daily total step count was inversely associated with the percent change in overall CIMT over 8-years (ß = -0.015, standard error = 0.007, P = 0.034). This association was present among participants in the < 60-year-old group (ß = -0.026, standard error = 0.010, P = 0.006), but not among participants in the ≥ 60-year-old group (ß = -0.010, standard error = 0.011, P = 0.38). CONCLUSIONS: The findings suggest that taking preemptive actions of increasing physical activity may prevent the incidence of atherosclerosis.

A Fully Automated Visual Grading System for White Matter Hyperintensities of T2-Fluid Attenuated Inversion Recovery Magnetic Resonance Imaging.

BACKGROUND: The Fazekas scale is one of the most commonly used visual grading systems for white matter hyperintensity (WMH) for brain disorders like dementia from T2-fluid attenuated inversion recovery magnetic resonance (MR) images (T2-FLAIRs). However, the visual grading of the Fazekas scale suffers from low-intra and inter-rater reliability and high labor-intensive work. Therefore, we developed a fully automated visual grading system using quantifiable measurements. METHODS: Our approach involves four stages: (1) the deep learning-based segmentation of ventricles and WMH lesions, (2) the categorization into periventricular white matter hyperintensity (PWMH) and deep white matter hyperintensity (DWMH), (3) the WMH diameter measurement, and (4) automated scoring, following the quantifiable method modified for Fazekas grading. We compared the performances of our method and that of the modified Fazekas scale graded by three neuroradiologists for 404 subjects with T2-FLAIR utilized from a clinical site in Korea. RESULTS: The Krippendorff's alpha across our method and raters (A) versus those only between the radiologists (R) were comparable, showing substantial (0.694 vs. 0.732; 0.658 vs. 0.671) and moderate (0.579 vs. 0.586) level of agreements for the modified Fazekas, the DWMH, and the PWMH scales, respectively. Also, the average of areas under the receiver operating characteristic curve between the radiologists (0.80 ± 0.09) and the radiologists against our approach (0.80 ± 0.03) was comparable. CONCLUSIONS: Our fully automated visual grading system for WMH demonstrated comparable performance to the radiologists, which we believe has the potential to assist the radiologist in clinical findings with unbiased and consistent scoring.

Earlier chronotype in midlife as a predictor of accelerated brain aging: a population-based longitudinal cohort study.

STUDY OBJECTIVES: Evidence suggests that sleep-wake cycle disruption could be an early manifestation of neurodegeneration and might even be a risk factor for developing diseases in healthy adults. We investigated the impact of circadian phase change on structural and functional brain deterioration in a late-adulthood population. METHODS: We analyzed the data of 1874 participants (mean age 58.6 ± 6.3 years, 50.3% female) from the Korean Genome and Epidemiology Study, who were identified as cognitively unimpaired. The mid-sleep time on free days corrected for sleep debt on workdays (MSFsc) at baseline was adopted as an indicator of the chronotype and used to categorize the participants into three groups. The relationships between the chronotype and longitudinal changes in the gray matter volume (GMV) and cognitive function were investigated (mean interval: 4.2 ± 0.5 years). RESULTS: The mean MSFsc of the participants was 2:45 am. The earlier MSFsc was linearly associated with smaller right entorhinal GMV (ß [SE] = 0.02 [0.01]; p = .001) and lower visual memory function test scores at baseline. Longitudinally, the earlier MSFsc at baseline was only significantly associated with more rapid atrophy in the temporal lobe (ß [SE] = 0.18 [0.07]; p = .018) and not with other brain lobes or subregions. Moreover, the earlier MSFsc was associated with more deteriorated verbal learning and visual memory function test scores. CONCLUSIONS: An earlier chronotype in midlife, measured using a questionnaire, can be a valuable indicator for individuals who should be closely monitored for the development of neurodegenerative disorders.

Effects of education mediated by brain size on regional brain volume in adults.

BACKGROUND AND PURPOSE: Brain structure and function change with age. Both educational attainments, a proxy for cognitive reserve, and intracranial volume (ICV), a proxy for brain reserve, could contribute to resilience against degenerative change in the brain with aging. Whether the effect of educational attainment on regional brain volume in adults is mediated by ICV is yet unclear. We aimed to investigate the direct and indirect effects (mediated through ICV) of education in early life on regional brain volume in later life. MATERIALS AND METHOD: We investigated the association between ICV and education level and regional brain volume in adults using magnetic resonance imaging scans of 1,731 individuals from multicenter studies. The mediation effect of ICV was analyzed to determine the association between educational attainment at an earlier age and regional brain volume in adults. RESULTS: Our results showed that the effect of education on regional brain volume was significantly mediated by ICV in both men and women. The indirect (mediated via ICV) effect of education on brain volume amounted to 75% of the total effect in the hippocampus (p < 0.001) and 100% in the frontal and insular gray matter (p < 0.001). CONCLUSION: Our study demonstrated that the association between educational attainment in early life and regional brain volume in later life was largely mediated by ICV. Attention should be given to the effect of educational attainment and ICV on regional brain size in adults as a measurable resilience effect in brain aging.

Fine-grained brain tissue segmentation for brain modeling of stroke patient.

Brain segmentation of stroke patients can facilitate brain modeling for electrical non-invasive brain stimulation, a therapy for stimulating brain function using an electric current. However, it remains challenging owing to its time-consuming, labor-dependent, and complicated pipeline. In addition, conventional tools that define lesions into one region rather than distinguishing between the stroke-affected regions and cerebrospinal fluid can lead to inaccurate treatment results. In this study, we first define a novel stroke-affected region as a detailed sub-region of the conventionally defined lesion. Subsequently, a novel comprehensive framework is proposed to segment head-brain and fine-level stroke-affected regions for normal controls and chronic stroke patients. The proposed framework consists of a time-efficient and precise deep learning-based segmentation model. The experiment results indicate that the proposed method perform better than the conventional deep learning-based segmentation model in terms of the evaluation metrics. The proposed method would be a valuable addition to brain modeling for non-invasive neuromodulation.

Association of long-term hyperglycaemia and insulin resistance with brain atrophy and cognitive decline: A longitudinal cohort study.

AIM: To investigate the longitudinal changes in brain volume and cognitive function associated with diabetes at midlife, and to examine whether long-term hyperglycaemia, insulin resistance or secretory function is associated with brain atrophy and cognitive decline. MATERIALS AND METHODS: We used data from 2377 participants with both baseline and 4-year follow-up brain magnetic resonance images and neuropsychological measures from the Ansan cohort of the Korean Genome Epidemiology Study. Time-weighted mean glycaemic values were calculated using all measurements over an average duration of 10.6 years from cohort initiation to baseline visits. RESULTS: Type 2 diabetes was associated with greater white matter volume reduction (adjusted volume difference = -1.96 ml, 95% CI: -3.73, -0.18) and executive function decline (adjusted Z score difference = -0.14, 95% CI: -0.23, -0.05) during the follow-up period of 4.2 years. Decline of verbal and visual memory or verbal fluency was not associated with diabetes. Greater executive function decline was associated with higher time-weighted mean HbA1c level over the preceding 10.6 years (P < .001), but not with insulin resistance markers in the diabetes group. Participants with diabetes, whose time-weighted average HbA1c level was maintained above 6.5% over the previous decade, showed greater decline in executive function and global cognition than the normal glucose group. CONCLUSIONS: Long-term hyperglycaemia was a major independent factor associated with rapid cognitive decline in middle-aged adults with diabetes. Maintaining ideal glucose levels in diabetes at midlife might prevent later rapid cognitive decline.

The Effect of Hearing Loss on Cognitive Function in Subjective Cognitive Decline.

INTRODUCTION: Subjective cognitive decline (SCD) is a self-reported cognitive decline without objective cognitive impairment. The relationship between audiometric hearing loss (HL) and cognitive function has not been reported in SCD. The purpose of this study was to investigate whether HL affects cognition-related indexes in SCD individuals. METHODS: This is a cross-sectional study that used the baseline data of a multicenter cohort study that monitors clinical progression from SCD to dementia. Individuals aged ≥60 years who reported cognitive decline but had no objective cognitive impairment on comprehensive neuropsychological tests were recruited. Participants were grouped into the normal-hearing (NH) and bilateral HL groups. The demographics, clinical characteristics, dementia biomarkers, global cognition, questionnaire scores, neuropsychological test scores, and segmental brain volumes from MRI were compared between the groups. RESULTS: Of a total of 120 participants, one hundred and two had NH (n = 57) or bilateral HL (n = 45). There were no group differences in the demographic and clinical data except the age. The biomarkers, global cognition, and questionnaire scores were not different between the groups. The HL group performed worse (the z-score of -0.06) in the Stroop Color Word Test than the NH group (0.27) (p = 0.025). Brain volumetric analysis revealed that the HL group had reduced gray matter volumes in four brain subregions: left temporal pole, left caudal middle frontal gyrus, left hippocampus, and right isthmus of the cingulate gyrus. CONCLUSION: In SCD, HL exerted an adverse effect on cognitive function, primarily frontal executive function tested in the Stroop task. HL was also related to gray matter volume reductions in brain subregions, although causality needs further investigation. This study may provide evidence for a potential link between hearing and cognition in SCD, an emerging clinical entity.

Night blood pressure variability, brain atrophy, and cognitive decline.

Background: Although blood pressure variability (BPV) has emerged as a novel risk factor for Alzheimer's disease, few studies have examined the effects of night BPV on brain structure and function. This study investigated the association of night BPV with brain atrophy and cognitive function changes. Methods: The analysis included 1,398 participants with valid ambulatory blood pressure (BP) monitoring at baseline and both baseline and 4-year follow-up brain magnetic resonance images who were recruited from the Korean Genome and Epidemiology Study. Participants underwent a comprehensive neuropsychological test battery. BPV was derived from ambulatory BP monitoring and calculated as a standard deviation (SD) of 24-h and daytime and nighttime BP. Results: During the median follow-up of 4.3 years, increased SD of night systolic or diastolic BP was an indicator of total brain volume reduction, while daytime BPV or night average BP was not associated with total brain volume changes. High SD of night systolic BP was associated with reduced gray matter (GM) volume, independent of average night BP, and use of antihypertensive drugs. It also was associated with a reduction of temporal GM volume, mostly driven by atrophy in the left entorhinal cortex and the right fusiform gyrus. In cognitive performance, high variability of night systolic BP was associated with a decrease in visual delayed recall memory and verbal fluency for the category. Conclusion: Increased night BPV, rather than night mean BP, was associated with reduced brain volume and cognitive decline. High night BPV could be an independent predictor for rapid brain aging in a middle-aged population.

Association of Obstructive Sleep Apnea With White Matter Integrity and Cognitive Performance Over a 4-Year Period in Middle to Late Adulthood.

Importance: Obstructive sleep apnea (OSA) is associated with cognitive impairment and brain structural alterations, but longitudinal outcomes are understudied. Objective: To examine the associations of OSA with cognition and white matter (WM) integrity over a 4-year period. Design, Setting, and Participants: This prospective cohort study was conducted in a community-based adult population among participants who had both baseline (2011-2014) and 4-year follow-up (2015-2018) polysomnography, diffusion tensor imaging, and cognitive assessment data. Participants with neurological disorders, anomalous findings on brain magnetic resonance imaging, or inadequate quality of the evaluations were excluded. Data were analyzed from March to November 2021. Exposures: Participants were categorized depending on the presence vs absence of OSA at baseline and follow-up polysomnographic analysis. Main Outcomes and Measures: The main outcomes were proportional changes over a 4-year period in neuropsychological performance and WM integrity. The neuropsychological assessment battery included verbal and visual memory, verbal fluency, Digit Symbol-coding, Trail Making Test-A, and Stroop Test. WM integrity was assessed by fractional anisotropy, axial, and radial diffusivity. To examine interactions with age and sex, participants were subgrouped by age older than 60 years vs 60 years or younger and men vs women. Results: A total of 1998 individuals were assessed for eligibility, and 888 were excluded based on exclusion criteria, leaving 1110 participants (mean [SD] age, 58.0 [6.0] years; 517 [46.6%] men) for analysis, including 458 participants grouped as OSA-free, 72 participants with resolved OSA, 163 participants with incident OSA, and 417 participants with persistent OSA. Incident OSA was associated with altered WM integrity and with concomitant changes in sustained attention compared with participants without OSA (eg, change in Digit Symbol-coding test score, -3.2% [95% CI, -5.2% to -1.2%]). Participants with resolved OSA showed better visual recall at the follow-up (change in Visual Reproduction-immediate recall test, 17.5% [95% CI, 8.9% to 26.1%]; change in Visual Reproduction-delayed recall test, 33.1% [95% CI, 11.3% to 54.9%]), with concordant changes in diffusion parameters at the relevant anatomic areas. In the older group only (age >60 years), persistent OSA was associated with altered WM integrity and cognition (eg, Visual Reproduction-recognition test: ß = -24.2 [95% CI, -40.7 to -7.7]). Sex also was associated with modifying the association of OSA with WM integrity of the left posterior internal capsule, the left genu of corpus callosum, and the right middle cerebellar peduncle only in men and with cognition only in women (eg, Visual Reproduction-immediate recall test: ß = 33.4 [95% CI, 19.1 to 47.7]). Conclusions and Relevance: These findings suggest that dynamic changes in OSA status were significantly associated with WM integrity and cognition, which varied by age and sex. It is possible that adequate interventions for OSA could better preserve brain health in middle to late adulthood.