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Several population-based studies have reported that higher serum N-terminal pro-brain natriuretic peptide (NT-proBNP) levels are associated with brain morphological changes. However, no population-based studies have examined the relationship between serum NT-proBNP and various regional brain volumes in detail. We here analyzed the brain MRI data of 1 201 community-dwelling Japanese aged ≥65 years. Regional gray matter volumes (GMV) and intracranial volume (ICV) were estimated by applying voxel-based morphometry (VBM) methods. The associations of serum NT-proBNP with regional GMV/ICV were examined by analysis of covariance. The regional gray matter atrophy patterns associated with elevated serum NT-proBNP levels were investigated using VBM without a priori regions of interest. The multivariable-adjusted means of the frontal, temporal, hippocampal, parahippocampal, and entorhinal GMV/ICV decreased significantly with elevated serum NT-proBNP levels (all p for trend and q values of false discovery rate correction < .05). In VBM, elevated serum NT-proBNP levels were correlated with atrophy of the bilateral hippocampi, bilateral amygdalas, bilateral parahippocampal gyri, bilateral entorhinal areas, bilateral fusiform gyri, left middle temporal gyrus, left inferior temporal gyrus, right central operculum, right posterior orbital gyrus, bilateral middle frontal gyri, anterior cingulate gyrus and bilateral medial frontal cortices. In a sensitivity analysis excluding 254 participants with mild cognitive impairment or dementia, serum NT-proBNP levels were correlated with atrophy of the bilateral hippocampi, bilateral amygdalas, bilateral parahippocampal gyri, bilateral fusiform gyri, and left middle frontal gyrus. Our data suggest that elevated serum NT-proBNP levels are associated with gray matter atrophy in brain regions that play an important role in cognitive function. [ABSTRACT FROM AUTHOR]

Background: Autonomic nervous system dysfunction has been reported to be associated with impaired activities of daily living (ADL) among patients with chronic pain, but the association has not been fully addressed in general populations. This study cross‐sectionally investigated the association between autonomic nervous system function and the presence of subjective symptoms affecting ADL in community‐dwelling residents with chronic pain. Methods: A total of 888 residents with chronic pain, aged 40–79 years, who underwent a health examination in 2017–2018 were included. Based on heart rate variability measured by fingertip pulse wave, the standard deviation of normal‐to‐normal intervals (SDNN), root mean square of successive RR interval differences (RMSSD), low frequency (LF) power, and high frequency (HF) power were calculated. Symptoms affecting ADL were defined as those scoring ≥1 on the modified Rankin Scale. Odds ratios (ORs) and their 95% confidence intervals (CIs) for symptoms affecting ADL were estimated using a logistic regression analysis. Results: The overall prevalence of symptoms affecting ADL was 39.4%. The ORs for symptoms affecting ADL increased significantly per 1‐standard‐deviation decrement in log‐transformed SDNN (OR 1.23 [95% CI 1.06–1.44]), RMSSD (1.25 [1.08–1.45]), LF power (1.29 [1.11–1.52]), and HF power (1.29 [1.11–1.51]) after adjusting for age, sex, education, hypertension, diabetes, serum total cholesterol level, body mass index, past medical history, current smoking, current drinking, exercise, depressive symptoms, and pain intensity. Conclusions: Decreased heart rate variability was associated with the presence of symptoms affecting ADL among individuals with chronic pain in a Japanese community. Significance: Decrease in heart rate variability was associated with the presence of symptoms affecting ADL among individuals with chronic pain in a Japanese community. This article could help scientists understand the significance of autonomic nervous system dysfunction in the pathology of chronic pain. Approaches that target autonomic nervous system dysfunction may be an option to relieve or prevent symptoms affecting ADL for chronic pain sufferers. [ABSTRACT FROM AUTHOR]

Altruistic social activity, such as giving support to others, has shown protective benefits on dementia risk and cognitive decline. However, the pathological mechanism is unclear. In the present study, we investigated the association between altruistic social activity and brain regional gray matter. Furthermore, to explore the psychological interplay in altruistic social activity, we tested mediating effect of depressive symptoms on brain regional gray matter. We performed a cross-sectional voxel-based morphology (VBM) analysis including 8 695 old adults (72.9 ± 6.1 years) from Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) Cohort. We measured altruistic social activities by self-report questionnaires, depressive symptoms by Geriatric Depression Scale (GDS)-short version. We employed the whole-brain VBM method to detect relevant structural properties related to altruistic social activity. We then performed multiple regression models to detect the mediating effect of depressive symptoms on particular brain regional gray matter volume while adjusting possible physical and social lifestyle covariables. We found that altruistic social activity is associated with larger gray matter volume in posterior insula, middle cingulate gyrus, hippocampus, thalamus, superior temporal gyrus, anterior orbital gyrus, and middle occipital gyrus. Depressive symptoms mediated over 10% on altruistic social activity and hippocampus volume, over 20% on altruistic social activity and cingulate gyrus volume. Our results indicated that altruistic social activity might preserve brain regional gray matter which are sensitive to aging and cognitive decline. Meanwhile, this association may be explained by indirect effect on depressive symptoms, suggesting that altruistic social activity may mitigate the neuropathology of dementia. [ABSTRACT FROM AUTHOR]

White matter lesions (WML) commonly occur in older brains and are quantifiable on MRI, often used as a biomarker in Aging research. Although algorithms are regularly proposed that identify these lesions from T2‐fluid‐attenuated inversion recovery (FLAIR) sequences, none so far can estimate lesions directly from T1‐weighted images with acceptable accuracy. Since 3D T1 is a polyvalent and higher‐resolution sequence, it could be beneficial to obtain the distribution of WML directly from it. However a serious difficulty, both for algorithms and human, can be found in the ambiguities of brain signal intensity in T1 images. This manuscript shows that a cross‐domain ConvNet (Convolutional Neural Network) approach can help solve this problem. Still, this is non‐trivial, as it would appear to require a large and varied dataset (for robustness) labelled at the same high resolution (for spatial accuracy). Instead, our model was taught from two‐dimensional FLAIR images with a loss function designed to handle the super‐resolution need. And crucially, we leveraged a very large training set for this task, the recently assembled, multi‐sites Japan Prospective Studies Collaboration for Aging and Dementia (JPSC‐AD) cohort. We describe the two‐step procedure that we followed to handle such a large number of imperfectly labeled samples. A large‐scale accuracy evaluation conducted against FreeSurfer 7, and a further visual expert rating revealed that WML segmentation from our ConvNet was consistently better. Finally, we made a directly usable software program based on that trained ConvNet model, available at https://github.com/bthyreau/deep-T1-WMH. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To examine the association between diabetes and gray matter atrophy patterns in a general older Japanese population. RESEARCH DESIGN AND METHODS: In 2012, a total of 1,189 community-dwelling Japanese aged ≥65 years underwent brain MRI scans. Regional gray matter volumes (GMV) and intracranial volume (ICV) were measured by applying voxel-based morphometry (VBM) methods. The associations of diabetes and related parameters with the regional GMV/ICV were examined using an ANCOVA. The regional gray matter atrophy patterns in the subjects with diabetes or elevated fasting plasma glucose (FPG) or 2-h postload glucose (2hPG) levels were investigated using VBM. RESULTS: Subjects with diabetes had significantly lower mean values of GMV/ICV in the frontal lobe, temporal lobe, insula, deep gray matter structures, and cerebellum than subjects without diabetes after adjusting for potential confounders. A longer duration of diabetes was also significantly associated with lower mean values of GMV/ICV in these brain regions. The multivariable-adjusted mean values of the temporal, insular, and deep GMV/ICV decreased significantly with elevating 2hPG levels, whereas higher FPG levels were not significantly associated with GMV/ICV of any brain regions. In the VBM analysis, diabetes was associated with gray matter atrophy in the bilateral superior temporal gyri, right middle temporal gyrus, left inferior temporal gyrus, right middle frontal gyrus, bilateral thalami, right caudate, and right cerebellum. CONCLUSIONS: The current study suggests that a longer duration of diabetes and elevated 2hPG levels are significant risk factors for gray matter atrophy in various brain regions. [ABSTRACT FROM AUTHOR]