scholarly journals Impairment of the Missing Fundamental Phenomenon in Individuals with Alzheimer’s Disease: A Neuropsychological and Voxel-Based Morphometric Study

2018 ◽  
Vol 8 (1) ◽  
pp. 23-32 ◽  
Author(s):  
Makiko Abe ◽  
Ken-ichi Tabei ◽  
Masayuki Satoh ◽  
Mari Fukuda ◽  
Hironobu Daikuhara ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Inferior Frontal Gyrus ◽  
Gray Matter Volume ◽  
Brain Regions ◽  
Pitch Perception ◽  
Magnetic Resonance Images ◽  
Morphometric Study ◽  
Fundamental Phenomenon ◽  
Missing Fundamental

Background/Aims: The missing fundamental phenomenon (MFP) is a universal pitch perception illusion that occurs in animals and humans. In this study, we aimed to determine whether the MFP is impaired in patients with Alzheimer’s disease (AD) using an auditory pitch perception experiment. We further examined anatomical correlates of the MFP in patients with AD by measuring gray matter volume (GMV) on magnetic resonance images via voxel-based morphometric analysis. Methods: We prospectively enrolled 29 patients with AD and 20 healthy older adults. Auditory stimuli included 12 melodies of Japanese nursery songs that were expected to be familiar to participants. We constructed the melodies using pure and missing fundamental tones (MFTs). Results: Patients with AD exhibited significantly poorer performance on the MFT task than healthy controls. MFT scores were positively correlated with GMV in the bilateral insula and temporal poles, left inferior frontal gyrus, right entorhinal cortex, and right cerebellum. Conclusions: These results suggest that impairments in the MFP represent a manifestation of the degeneration of auditory-related brain regions in AD. Further studies are required to more fully elucidate the neural mechanisms underlying auditory impairments in patients with AD and related dementia disorders.

scholarly journals Linking the association between circRNAs and Alzheimer’s disease progression by multi-tissue circular RNA characterization

2020 ◽  
Author(s):  
IJu Lo ◽  
Jamie Hill ◽  
Bjarni J. Vilhjálmsson ◽  
Jørgen Kjems
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Inferior Frontal Gyrus ◽  
Circular Rna ◽  
Brain Regions ◽  
Parahippocampal Gyrus ◽  
Circular Rnas ◽  
Cognitive Disability ◽  
Anterior Prefrontal Cortex ◽  
Progressive Course

AbstractAlzheimer’s Disease (AD) has devastating consequences for patients during its slow, progressive course. It is important to understand the pathology of AD onset. Recently, circular RNAs (circRNAs) have been found to participate in many human diseases including cancers and neurodegenerative conditions. In this study, we mined the published dataset on the AMP-AD Knowledge Portal from the Mount Sinai Brain Bank (MSBB) to describe the circRNA profiles at different AD stage in brain samples from four AD patients brain regions, anterior prefrontal cortex, superior temporal lobe, parahippocampal gyrus, and inferior frontal gyrus. We found in total 147 circRNAs to be differentially expressed (DE) during AD progression in the four regions. We also characterized the mRNA-circRNA co-expression network and annotated the potential function of circRNAs based on the co-expressed modules. Based on our results, we propose that parahippocampal gyrus is the most circRNA-regulated region during the AD progression. The strongest negatively AD stage-correlated module in parahippocampal gyrus were enriched in cognitive disability and pathological-associated pathways such as synapse organization and regulation of membrane potential. Finally, the regression model based on the expression pattern of DE circRNAs in the module could help to distinguish the disease severity of patients, further supported the importance of circRNAs in AD pathology. In conclusion, our finding indicates that circRNAs in parahippocampal gyrus are possible regulators of AD progression and potentially be a therapeutic target or of AD.

scholarly journals ADAS-viewer: web-based application for integrative analysis of multi-omics data in Alzheimer’s disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Seonggyun Han ◽  
Jaehang Shin ◽  
Hyeim Jung ◽  
Jane Ryu ◽  
Habtamu Minassie ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Inferior Frontal Gyrus ◽  
Temporal Cortex ◽  
Brain Regions ◽  
Biological Data ◽  
Omics Data ◽  
Molecular Architecture ◽  
Web Based

AbstractsAlzheimer’s disease (AD) is a neurodegenerative disorder and is represented by complicated biological mechanisms and complexity of brain tissue. Our understanding of the complicated molecular architecture that contributes to AD progression benefits from performing comprehensive and systemic investigations with multi-layered molecular and biological data from different brain regions. Since recently different independent studies generated various omics data in different brain regions of AD patients, multi-omics data integration can be a useful resource for better comprehensive understanding of AD. Here we present a web platform, ADAS-viewer, that provides researchers with the ability to comprehensively investigate and visualize multi-omics data from multiple brain regions of AD patients. ADAS-viewer offers means to identify functional changes in transcript and exon expression (i.e., alternative splicing) along with associated genetic or epigenetic regulatory effects. Specifically, it integrates genomic, transcriptomic, methylation, and miRNA data collected from seven different brain regions (cerebellum, temporal cortex, dorsolateral prefrontal cortex, frontal pole, inferior frontal gyrus, parahippocampal gyrus, and superior temporal gyrus) across three independent cohort datasets. ADAS-viewer is particularly useful as a web-based application for analyzing and visualizing multi-omics data across multiple brain regions at both transcript and exon level, allowing the identification of candidate biomarkers of Alzheimer’s disease.

scholarly journals ANALYSES OF BRAIN CORTICAL CHANGES OF ALZHEIMER’S DISEASE

2021 ◽  
pp. 2140025
Author(s):  
YUTING LV ◽  
WENSHUO ZHAO ◽  
XUFENG YAO ◽  
SONG XU ◽  
ZHIXIAN TANG ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Brain Regions ◽  
Morphological Description ◽  
Gyrification Index ◽  
Morphological Differences ◽  
The Brain ◽  
Normal Controls

Alzheimer’s disease (AD) produces complicated cortical changes in gray matter (GM) of the human brain. However, alterations in the brain cortex have not been clearly addressed. In our study, a cohort of 236 cases MR data enrolled from the ADNI database was categorized into three groups of normal controls (NCs), mild cognitive impairment (MCI) and AD. The GM morphological differences were investigated among the three groups using the magnetic resonance (MR) GM characteristics of gray matter volume (GMV), cortical thickness (CT), cortical surface area (CSA) and local gyrification index (LGI) at the three levels of whole brain, bilateral hemispheres and critical brain regions. Totally, there were six critical brain regions for GMV, 11 for CT, 2 for CSA and 59 for LGI among the three groups for the no-division groups. Also, there were 11 critical brain regions for GMV, 15 for CT, 8 for CSA, 3 for LGI for female sub-groups and 4 critical brain regions for GMV, 11 for CT, 1 for CSA, 3 for LGI for male sub-groups. The four measured cortical characteristics showed reliable capability in the morphological description of GM changes of AD. In conclusion, the cortical characteristics of GMV, CT, CSA and LGI of critical brain regions showed valuable indications for GM changes of AD, and those characteristics could be used as imaging markers for AD prediction.

Brain structural and cognitive correlates of clock drawing performance in Alzheimer's disease

1999 ◽  
Vol 5 (6) ◽  
pp. 502-509 ◽  
Author(s):  
DEBORAH A. CAHN-WEINER ◽  
EDITH V. SULLIVAN ◽  
PAULA K. SHEAR ◽  
ROSEMARY FAMA ◽  
KELVIN O. LIM ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gray Matter Volume ◽  
Temporal Cortex ◽  
Brain Regions ◽  
Receptive Language ◽  
Semantic Knowledge ◽  
Clock Drawing Test ◽  
Clock Drawing ◽  
The Right

The Clock Drawing Test (CDT) is widely used in the assessment of dementia and is known to be sensitive to the detection of deficits in neurodegenerative disorders such as Alzheimer's disease (AD). CDT performance is dependent not only on visuospatial and constructional abilities, but also on conceptual and executive functioning; therefore, it is likely to be mediated by multiple brain regions. The purpose of the present study was to identify component cognitive processes and regional cortical volumes that contribute to CDT performance in AD. In 29 patients with probable AD, CDT performance was significantly related to right-, but not left-hemisphere, regional gray matter volume. Specifically, CDT score correlated significantly with the right anterior and posterior superior temporal lobe volumes. CDT scores showed significant relationships with tests of semantic knowledge, executive function, and visuoconstruction, and receptive language. These results suggest that in AD patients, CDT performance is attributable to impairment in multiple cognitive domains but is related specifically to regional volume loss of right temporal cortex. (JINS, 1999, 5, 502–509.)

scholarly journals Integrated miRNA-Seq and mRNA-Seq Study to Identify miRNAs Associated With Alzheimer’s Disease Using Post-mortem Brain Tissue Samples

2021 ◽  
Vol 15 ◽  
Author(s):  
Qingqin S. Li ◽  
Diana Cai
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Immune System ◽  
Inferior Frontal Gyrus ◽  
Wnt Signaling Pathway ◽  
Amyloid Β ◽  
Brain Regions ◽  
Differentially Expressed ◽  
Post Mortem ◽  
Post Mortem Brain

Alzheimer’s disease (AD), the leading form of dementia, is associated with abnormal tau and β-amyloid accumulation in the brain. We conducted a miRNA-seq study to identify miRNAs associated with AD in the post-mortem brain from the inferior frontal gyrus (IFG, n = 69) and superior temporal gyrus (STG, n = 81). Four and 64 miRNAs were differentially expressed (adjusted p-value < 0.05) in AD compared to cognitively normal controls in the IFG and STG, respectively. We observed down-regulation of several miRNAs that have previously been implicated in AD, including hsa-miR-212-5p and hsa-miR-132-5p, in AD samples across both brain regions, and up-regulation of hsa-miR-146a-5p, hsa-miR-501-3p, hsa-miR-34a-5p, and hsa-miR-454-3p in the STG. The differentially expressed miRNAs were previously implicated in the formation of amyloid-β plaques, the dysregulation of tau, and inflammation. We have also observed differential expressions for dozens of other miRNAs in the STG, including hsa-miR-4446-3p, that have not been described previously. Putative targets of these miRNAs (adjusted p-value < 0.1) were found to be involved in Wnt signaling pathway, MAPK family signaling cascades, sphingosine 1-phosphate (S1P) pathway, adaptive immune system, innate immune system, and neurogenesis. Our results support the finding of dysregulated miRNAs previously implicated in AD and propose additional miRNAs that appear to be dysregulated in AD for experimental follow-up.

A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials

2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Latent Variable ◽  
Brain Regions ◽  
Disease Assessment ◽  
Latent Variable Analysis ◽  
The Relationship ◽  
Selection Of

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.

scholarly journals Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Neurological Disorders ◽  
Magnetic Resonance Images ◽  
Future Research ◽  
Comparative Performance

Abstract Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided.

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.

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