scholarly journals Effect of Alzheimer's Disease Risk Variant rs3824968 at SORL1 on Regional Gray Matter Volume and Age-Related Interaction in Adult Lifespan

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Chu-Chung Huang ◽  
Mu-En Liu ◽  
Hung-Wen Kao ◽  
Kun-Hsien Chou ◽  
Albert C. Yang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gray Matter ◽  
Disease Risk ◽  
Gray Matter Volume ◽  
Risk Variant ◽  
Adult Lifespan ◽  
Matter Volume ◽  
Age Related

scholarly journals Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Malo Gaubert ◽  
Catharina Lange ◽  
Antoine Garnier-Crussard ◽  
Theresa Köbe ◽  
Salma Bougacha ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Glucose Metabolism ◽  
Corpus Callosum ◽  
Gray Matter ◽  
Fdg Pet ◽  
White Matter Hyperintensities ◽  
Gray Matter Volume ◽  
Matter Volume

Abstract Background White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction. Methods In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure. Results There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas. Conclusions This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.

Reproducibility of Brain Volume Changes in Longitudinal Voxel-Based Morphometry Between Non-Accelerated and Accelerated Magnetic Resonance Imaging

2021 ◽  
pp. 1-10
Author(s):  
Hidemasa Takao ◽  
Shiori Amemiya ◽  
Osamu Abe ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Elderly Subjects ◽  
Voxel Based Morphometry ◽  
Volume Changes ◽  
Matter Volume ◽  
Healthy Elderly

Background: Scan acceleration techniques, such as parallel imaging, can reduce scan times, but reliability is essential to implement these techniques in neuroimaging. Objective: To evaluate the reproducibility of the longitudinal changes in brain morphology determined by longitudinal voxel-based morphometry (VBM) between non-accelerated and accelerated magnetic resonance images (MRI) in normal aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Methods: Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2 database, comprising subjects who underwent non-accelerated and accelerated structural T1-weighted MRI at screening and at a 2-year follow-up on 3.0 T Philips scanners, we examined the reproducibility of longitudinal gray matter volume changes determined by longitudinal VBM processing between non-accelerated and accelerated imaging in 50 healthy elderly subjects, 54 MCI patients, and eight AD patients. Results: The intraclass correlation coefficient (ICC) maps differed among the three groups. The mean ICC was 0.72 overall (healthy elderly, 0.63; MCI, 0.75; AD, 0.63), and the ICC was good to excellent (0.6–1.0) for 81.4%of voxels (healthy elderly, 64.8%; MCI, 85.0%; AD, 65.0%). The differences in image quality (head motion) were not significant (Kruskal–Wallis test, p = 0.18) and the within-subject standard deviations of longitudinal gray matter volume changes were similar among the groups. Conclusion: The results indicate that the reproducibility of longitudinal gray matter volume changes determined by VBM between non-accelerated and accelerated MRI is good to excellent for many regions but may vary between diseases and regions.

scholarly journals Moderating Effect of Insulin Resistance on the Relationship between Gray Matter Volumes and Cognitive Function

2018 ◽  
Vol 7 (11) ◽  
pp. 413 ◽  
Author(s):  
Jiyeon Lee ◽  
Jihyeon Kim ◽  
Seong Shin ◽  
Soowon Park ◽  
Dong Yoon ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Insulin Resistance ◽  
Alzheimer's Disease ◽  
Cognitive Function ◽  
Cognitive Decline ◽  
Gray Matter ◽  
Structural Changes ◽  
Gray Matter Volume ◽  
Volume Loss ◽  
Matter Volume

Background: It is controversial whether exposure to insulin resistance accelerates cognitive deterioration. The present study aimed to investigate the association between insulin resistance and gray matter volume loss to predict the cognitive decline. Methods: We recruited 160 participants (78 with Alzheimer’s disease and 82 without Alzheimer’s disease). Insulin resistance, regional gray matter volume, and cognitive function were assessed. A hierarchical moderated multiple regression (MMR) model was used to determine any associations among insulin resistance, structural changes in the brain, and cognitive decline. Results: The volumes of 7 regions in the gray matter were negatively related to insulin resistance in Alzheimer’s disease (p =0.032). Hierarchical MMR analysis indicated that insulin resistance did not directly affect the cognitive decline but moderated the cognitive decline through the decrease in gray matter volume in the key brain regions, i.e., inferior orbitofrontal gyrus (left), middle cingulate gyrus (right), hippocampus (right), and precuneus (right) (p < 0.05 in each case). Conclusion: Insulin resistance appears to exacerbate the cognitive decline associated with several gray matter volume loss.

scholarly journals Gray matter volume and estimated brain age gap are not associated with sleep-disordered breathing in subjects from the ADNI cohort

2019 ◽  
Author(s):  
Bahram Mohajer ◽  
Nooshin Abbasi ◽  
Esmaeil Mohammadi ◽  
Habibolah Khazaie ◽  
Ricardo S. Osorio ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Gray Matter ◽  
Sleep Disordered Breathing ◽  
Brain Aging ◽  
Gray Matter Volume ◽  
Cognitive Status ◽  
Matter Volume ◽  
Disordered Breathing

AbstractAlzheimer’s disease (AD) and sleep-disordered breathing (SDB) are prevalent conditions with rising burden. It is suggested that SDB may contribute to cognitive decline and advanced aging. Here, we assessed the link between self-reported SDB and gray matter volume in patients with AD, mild cognitive impairment (MCI) and healthy controls (HC). We further investigated whether SDB was associated with advanced brain aging. We included a total of 330 participants, divided based on self-reported history of SDB, and matched across diagnoses for age, sex and presence of the ApoE4 allele, from the Alzheimer’s Disease Neuroimaging Initiative. Gray-matter volume was measured using voxel-wise morphometry and differences reflecting SDB, cognitive status, and their interaction were evaluated. Further, using an age-prediction model fitted on gray-matter data of external datasets, we predicted study participants’ age from their structural scans. Cognitive decline (MCI/AD diagnosis) and advanced age were associated with lower gray matter volume in various regions, particularly in the bilateral temporal lobes. BrainAGE was well predicted from the morphological data in HC and, as expected, elevated in MCI and particularly in AD. However, there was neither a significant difference between regional gray matter volume in any diagnostic group related to the SDB status nor an SDB-by-cognitive status interaction. Also, we found neither a significant difference in BrainAGE gap (estimated - chronological age) related to SDB nor an SDB-by-cognitive status interaction. In summary, contrary to our expectations, we were not able to find a general nor a diagnostic specific effect on either gray-matter volumetric or brain aging.Statement of significanceDementia syndromes including Alzheimer’s disease (AD), are a major global concern, and unraveling modifiable predisposing risk factors is indispensable. Sleep-disordered breathing (SDB) and its most prevalent form, obstructive sleep apnea, are suggested as modifiable risk factors of AD, but their contribution to AD hallmarks, like brain atrophy and advanced brain aging, is not clear to this day. While self-reported SDB is suggested to propagate aging process and cognitive decline to AD in clinical studies, here, we demonstrated that, SDB might not necessarily associate to brain atrophy and the advanced brain aging assessed by morphological data, in AD progession. However, multimodal longitudinal studies with polysomnographic assessment of SDB are needed to confirm such fundings.

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