scholarly journals Sex-Dependent Age Trajectories of Subcortical Brain Structures: Analysis of Large-Scale Percentile Models and Shape Morphometry

2020 ◽  
Author(s):  
Christopher R. K. Ching ◽  
Zvart Abaryan ◽  
Vigneshwaran Santhalingam ◽  
Alyssa H. Zhu ◽  
Joanna K. Bright ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Spatial Distribution ◽  
Large Scale ◽  
Brain Aging ◽  
Brain Structures ◽  
Large Sample Size ◽  
Subcortical Brain ◽  
Subcortical Brain Structures ◽  
Subcortical Volumes

ABSTRACTModeling of structural brain variation over the lifespan is important to better understand factors contributing to healthy aging and risk for neurological conditions such as Alzheimer’s disease. Even so, we lack normative data on brain morphometry across the adult lifespan in large, well-powered samples. Here, in a large population-based sample of 26,440 adults from the UK Biobank (age: 44-81 yrs.), we created normative percentile charts for MRI-derived subcortical volumes. Next, we investigated associations between these morphometric measures and the strongest known genetic risk factor for late-onset Alzheimer’s disease (APOE genotype) and mapped the spatial distribution of age-by-sex interactions using computational surface mesh modeling and shape analysis. Vertex-wise shape mapping supplements traditional gross volumetric approaches to reveal finer-grained variations across functionally important brain subcompartments. Normative curves revealed volumetric loss with age, as expected, for all subcortical brain structures except for the lateral ventricles, which expanded with age. Surprisingly, no volumetric associations with APOE genotype were detected, despite the very large sample size. Age-related trajectories for volumes differed in women versus men, and surface-based statistical maps revealed the spatial distribution of the age-by-sex interaction. Subcortical volumes declined faster in men than women over the full age range, but after age 60, fewer structures showed sex-dependent trajectories, indicating similar volumetric changes in older men and women. Large-scale statistical modeling of age effects on brain structures may drive new insights into individual differences in brain aging and help to identify factors that promote healthy brain aging and risk for disease.

scholarly journals Cortical and Subcortical Structural Segmentation in Alzheimer’s Disease

2019 ◽  
Author(s):  
Jafar Zamani ◽  
Ali Sadr ◽  
Amir-Homayoun Javadi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Amyloid Beta ◽  
Clinical Symptoms ◽  
Brain Area ◽  
Brain Structures ◽  
Hippocampal Volume ◽  
Resonance Imaging ◽  
Brain Hemispheres ◽  
Subcortical Brain

Purpose: Alzheimer’s disease is a neurodegenerative disease that begins before clinical symptoms emerge. Amyloid-beta plaques and tau neurofibrillary tangles are the hallmark lesions of Alzheimer’s Disease (AD). Amyloid-beta plaques deposition is associated with increased hippocampal volume loss. The tissue volume measures reflect multiple underlying pathologies contributing to neurodegeneration, of which are the most characteristics of AD. Anatomical atrophy, as evidenced using Magnetic Resonance Imaging (MRI), is one of the most validated, easily accessible and widely used biomarkers of AD. Measurements of whole brain and hippocampal atrophy rates from serial structural MRI are potential markers of the underlying neuroaxonal damage and disease progression in AD. In this study, we extract automatically subcortical brain structures in AD and control subjects. Materials and Methods: In this study we used 20 images (10 AD patients and 10 controls) taken from the Minimal Interval Resonance Imaging in Alzheimer's Disease (MIRIAD) dataset. We obtained volumes of Cerebrospinal Fluid (CSF), White Matter (WM), Grey Matter (GM), brain hemispheres, cerebellum and brainstem using volBrain pipeline. Subcortical brain structure segments and related volumes and label maps information were extracted. We compared left and right sides of some of the important brain area in AD for obtaining a biomarker with brain atrophy. Amygdala, caudate and hippocampus have shown to be undergone atrophy in AD. Results: We provided volume information of some intracranial areas such as brain hemispheres, cerebellum and brainstem. Conclusion: The results showed smaller hippocampal volume in AD patients compared to the controls. In addition to hippocampus, similar atrophy is also observable in amygdala and caudate.

scholarly journals Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide

2017 ◽  
Author(s):  
Claudia L Satizabal ◽  
Hieab HH Adams ◽  
Derrek P Hibar ◽  
Charles C White ◽  
Jason L Stein ◽  
...  
Keyword(s):  
Drug Targets ◽  
Brain Structures ◽  
Association Analyses ◽  
Subcortical Brain ◽  
Genome Wide ◽  
Evolutionarily Conserved ◽  
Subcortical Brain Structures ◽  
The Uk ◽  
Potential Drug Targets ◽  
Subcortical Volumes

AbstractSubcortical brain structures are integral to motion, consciousness, emotions, and learning. We identified common genetic variation related to the volumes of nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus, using genome-wide association analyses in over 40,000 individuals from CHARGE, ENIGMA and the UK-Biobank. We show that variability in subcortical volumes is heritable, and identify 25 significantly associated loci (20 novel). Annotation of these loci utilizing gene expression, methylation, and neuropathological data identified 62 candidate genes implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

scholarly journals Transcranial Magnetic Stimulation Studies in Alzheimer's Disease

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Andrea Guerra ◽  
Federica Assenza ◽  
Federica Bressi ◽  
Federica Scrascia ◽  
Marco Del Duca ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Transcranial Magnetic Stimulation ◽  
Motor Cortex ◽  
Magnetic Stimulation ◽  
Large Scale ◽  
Primary Motor Cortex ◽  
Brain Aging ◽  
Cortical Excitability ◽  
Neuronal Degeneration

Although motor deficits affect patients with Alzheimer's disease (AD) only at later stages, recent studies demonstrated that primary motor cortex is precociously affected by neuronal degeneration. It is conceivable that neuronal loss is compensated by reorganization of the neural circuitries, thereby maintaining motor performances in daily living. Effectively several transcranial magnetic stimulation (TMS) studies have demonstrated that cortical excitability is enhanced in AD and primary motor cortex presents functional reorganization. Although the best hypothesis for the pathogenesis of AD remains the degeneration of cholinergic neurons in specific regions of the basal forebrain, the application of specific TMS protocols pointed out a role of other neurotransmitters. The present paper provides a perspective of the TMS techniques used to study neurophysiological aspects of AD showing also that, based on different patterns of cortical excitability, TMS may be useful in discriminating between physiological and pathological brain aging at least at the group level. Moreover repetitive TMS might become useful in the rehabilitation of AD patients. Finally integrated approaches utilizing TMS together with others neuro-physiological techniques, such as high-density EEG, and structural and functional imaging as well as biological markers are proposed as promising tool for large-scale, low-cost, and noninvasive evaluation of at-risk populations.

scholarly journals Transcriptomic changes highly similar to Alzheimer's disease are observed in a subpopulation of individuals during normal brain aging

2021 ◽  
Author(s):  
Shouneng Peng ◽  
Lu Zeng ◽  
Jean-vianney Haure-mirande ◽  
Minghui Wang ◽  
Derek M. Huffman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Healthy Aging ◽  
Brain Aging ◽  
Late Onset ◽  
Normal Aging ◽  
Normal Brain ◽  
Older Individuals

Aging is a major risk factor for late-onset Alzheimer's disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examine multiple large-scale human brain transcriptomic data from both normal aging and LOAD to understand the molecular interconnection between aging and LOAD. We find that shared gene expression changes between aging and LOAD are mostly seen in the hippocampus and several cortical regions. In the hippocampus, phosphoprotein, alternative splicing and cytoskeleton are the commonly dysregulated biological pathways in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also find that normal aging brains from relatively young donors (45-70 years old) cluster into subgroups and some subgroups show gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptome data from older individuals (>70 years), we find that samples from cognitive normal older individuals cluster with the "healthy aging" subgroup while AD samples mainly cluster with the AD similar subgroups. This implies that individuals in the healthy aging subgroup will likely remain cognitive normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitive normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the "normal brain aging" in a subgroup of individuals in their 40s-60s to identify the very early events in LOAD development.

Longitudinal Changes in Individual BrainAGE in Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease

GeroPsych ◽  
2012 ◽  
Vol 25 (4) ◽  
pp. 235-245 ◽  
Author(s):  
Katja Franke ◽  
Christian Gaser
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Healthy Aging ◽  
Brain Aging ◽  
Elderly Subjects ◽  
Additional Increase ◽  
Longitudinal Changes ◽  
Novel Method ◽  
The Brain

We recently proposed a novel method that aggregates the multidimensional aging pattern across the brain to a single value. This method proved to provide stable and reliable estimates of brain aging – even across different scanners. While investigating longitudinal changes in BrainAGE in about 400 elderly subjects, we discovered that patients with Alzheimer’s disease and subjects who had converted to AD within 3 years showed accelerated brain atrophy by +6 years at baseline. An additional increase in BrainAGE accumulated to a score of about +9 years during follow-up. Accelerated brain aging was related to prospective cognitive decline and disease severity. In conclusion, the BrainAGE framework indicates discrepancies in brain aging and could thus serve as an indicator for cognitive functioning in the future.

Dehydroepiandrosterone (DHEA) and its Sulphate (DHEAS) in Alzheimer’s Disease

2020 ◽  
Vol 17 (2) ◽  
pp. 141-157 ◽  
Author(s):  
Dubravka S. Strac ◽  
Marcela Konjevod ◽  
Matea N. Perkovic ◽  
Lucija Tudor ◽  
Gordana N. Erjavec ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Therapeutic Potential ◽  
Relevant Literature ◽  
Comprehensive Overview ◽  
Brain Functions ◽  
Specific Effects ◽  
And Behavior

Background: Neurosteroids Dehydroepiandrosterone (DHEA) and Dehydroepiandrosterone Sulphate (DHEAS) are involved in many important brain functions, including neuronal plasticity and survival, cognition and behavior, demonstrating preventive and therapeutic potential in different neuropsychiatric and neurodegenerative disorders, including Alzheimer’s disease. Objective: The aim of the article was to provide a comprehensive overview of the literature on the involvement of DHEA and DHEAS in Alzheimer’s disease. Method: PubMed and MEDLINE databases were searched for relevant literature. The articles were selected considering their titles and abstracts. In the selected full texts, lists of references were searched manually for additional articles. Results: We performed a systematic review of the studies investigating the role of DHEA and DHEAS in various in vitro and animal models, as well as in patients with Alzheimer’s disease, and provided a comprehensive discussion on their potential preventive and therapeutic applications. Conclusion: Despite mixed results, the findings of various preclinical studies are generally supportive of the involvement of DHEA and DHEAS in the pathophysiology of Alzheimer’s disease, showing some promise for potential benefits of these neurosteroids in the prevention and treatment. However, so far small clinical trials brought little evidence to support their therapy in AD. Therefore, large-scale human studies are needed to elucidate the specific effects of DHEA and DHEAS and their mechanisms of action, prior to their applications in clinical practice.

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