Transcriptome Changes in the Alzheimer’s Disease Middle Temporal Gyrus: Importance of RNA Metabolism and Mitochondria-Associated Membrane Genes

2019 ◽  
Vol 70 (3) ◽  
pp. 691-713 ◽  
Author(s):  
Ignazio S. Piras ◽  
Jonida Krate ◽  
Elaine Delvaux ◽  
Jennifer Nolz ◽  
Diego F. Mastroeni ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Rna Metabolism ◽  
Middle Temporal Gyrus ◽  
Middle Temporal

scholarly journals Spatially resolved transcriptomics reveals gene signatures underlying the vulnerability of human middle temporal gyrus in Alzheimer's disease

2021 ◽  
Author(s):  
Shuo Chen ◽  
Yuzhou Chang ◽  
Liangping Li ◽  
Diana Acosta ◽  
Cody Morrison ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Molecule ◽  
Brain Region ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Middle Temporal Gyrus ◽  
Middle Temporal ◽  
Spatially Resolved ◽  
Early Alzheimer’S Disease

Abstract Human middle temporal gyrus (MTG) is a vulnerable brain region in early Alzheimer's disease (AD); however, little is known about the molecular mechanisms underlying this regional vulnerability. Here we use the 10x Visium platform to define the spatial topography of gene expression in the MTG from both early AD and control cases. We identify differentially expressed genes (DEGs) and enriched pathways that may contribute to the layer-specific vulnerability of AD pathology. Also, gene co-expression analyses reveal four gene modules, which significantly change their co-expression patterns in the presence of variations of AD pathology. Furthermore, we validate the changes of key representative DEGs that are associated with AD pathology using single-molecule fluorescent in situ hybridization. In summary, we provide a rich resource for the spatial transcriptomic profile of the human MTG, which will contribute to our understanding of the complex architecture and AD pathology of this vulnerable brain region.

scholarly journals Impaired Expression of GABA Signaling Components in the Alzheimer’s Disease Middle Temporal Gyrus

2020 ◽  
Vol 21 (22) ◽  
pp. 8704
Author(s):  
Karan Govindpani ◽  
Clinton Turner ◽  
Henry J. Waldvogel ◽  
Richard L. M. Faull ◽  
Andrea Kwakowsky
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gabab Receptor ◽  
Neurodegenerative Disorder ◽  
Middle Temporal Gyrus ◽  
Post Mortem ◽  
Gaba Transporter ◽  
Middle Temporal ◽  
Gaba Signaling ◽  
Signaling Components

γ-aminobutyric acid (GABA) is the primary inhibitory neurotransmitter, playing a central role in the regulation of cortical excitability and the maintenance of the excitatory/inhibitory (E/I) balance. Several lines of evidence point to a remodeling of the cerebral GABAergic system in Alzheimer’s disease (AD), with past studies demonstrating alterations in GABA receptor and transporter expression, GABA synthesizing enzyme activity and focal GABA concentrations in post-mortem tissue. AD is a chronic neurodegenerative disorder with a poorly understood etiology and the temporal cortex is one of the earliest regions in the brain to be affected by AD neurodegeneration. Utilizing NanoString nCounter analysis, we demonstrate here the transcriptional downregulation of several GABA signaling components in the post-mortem human middle temporal gyrus (MTG) in AD, including the GABAA receptor α1, α2, α3, α5, β1, β2, β3, δ, γ2, γ3, and θ subunits and the GABAB receptor 2 (GABABR2) subunit. In addition to this, we note the transcriptional upregulation of the betaine-GABA transporter (BGT1) and GABA transporter 2 (GAT2), and the downregulation of the 67 kDa isoform of glutamate decarboxylase (GAD67), the primary GABA synthesizing enzyme. The functional consequences of these changes require further investigation, but such alterations may underlie disruptions to the E/I balance that are believed to contribute to cognitive decline in AD.

A SOFTWARE APPLICATION FOR PREDICTING ALZHEIMER'S DISEASE BASED ON THE LEVEL OF GENE EXPRESSION

2017 ◽  
Author(s):  
Sofiia Yefremova ◽  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gene Expression Data ◽  
Middle Temporal Gyrus ◽  
Expression Data ◽  
Middle Temporal ◽  
Software Application ◽  
The Brain

This article discusses the process of creating a software application that predicts Alzheimer's disease based on gene expression data in healthy and sick patients. The object of the study is the expression samples of genes taken from the study, which used the side of the middle temporal gyrus of the brain of frozen samples.

scholarly journals The middle temporal gyrus is transcriptionally altered in patients with Alzheimer’s Disease.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Transcriptional Repression ◽  
Zinc Finger Protein ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Middle Temporal Gyrus ◽  
Middle Temporal

We sought to understand, at the systems level and in an unbiased fashion, how gene expression was most different in the brains of patients with Alzheimer’s Disease (AD) by mining published microarray datasets (1, 2). Comparing global gene expression profiles between patient and control revealed that a set of 84 genes were expressed at significantly different levels in the middle temporal gyrus (MTG) of patients with Alzheimer’s Disease (1, 2). We used computational analyses to classify these genes into known pathways and existing gene sets, and to describe the major differences in the epigenetic marks at the genomic loci of these genes. While a portion of these genes is computationally cognizable as part of a set of genes up-regulated in the brains of patients with AD (3), many other genes in the gene set identified here have not previously been studied in association with AD. Transcriptional repression, both pre- and post-transcription appears to be affected; nearly 40% of these genes are transcriptional targets of MicroRNA-19A/B (miR-19A/B), the zinc finger protein 10 (ZNF10), or of the AP-1 repressor jun dimerization protein 2 (JDP2).

Association of AEBP1 and NRN1 RNA expression with Alzheimer’s disease and neurofibrillary tangle density in middle temporal gyrus

2019 ◽  
Vol 1719 ◽  
pp. 217-224
Author(s):  
Ignazio S. Piras ◽  
Jonida Krate ◽  
Elaine Delvaux ◽  
Jennifer Nolz ◽  
Matthew D. De Both ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurofibrillary Tangle ◽  
Middle Temporal Gyrus ◽  
Rna Expression ◽  
Middle Temporal

scholarly journals A Machine Learning Approach to Unmask Novel Gene Signatures and Prediction of Alzheimer’s Disease Within Different Brain Regions

2021 ◽  
Author(s):  
Abhibhav Sharma ◽  
Pinki Dey
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Non Coding Rna ◽  
Machine Learning Approach ◽  
Microarray Datasets ◽  
Rna Genes

AbstractAlzheimer’s disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies achieved by these studies remained unsatisfactory, reducing their clinical significance. Here, we employ the ensemble of random-forest and regularized regression model (LASSO) to the AD-associated microarray datasets from four brain regions - Prefrontal cortex, Middle temporal gyrus, Hippocampus, and Entorhinal cortex- to discover novel genetic biomarkers through a machine learning-based feature-selection classification scheme. The proposed scheme unrevealed the most optimum and biologically significant classifiers within each brain region, which achieved by far the highest prediction accuracy of AD in 5-fold cross-validation (99% average). Interestingly, along with the novel and prominent biomarkers including CORO1C, SLC25A46, RAE1, ANKIB1, CRLF3, PDYN, numerous non-coding RNA genes were also observed as discriminator, of which AK057435 and BC037880 are uncharacterized long non-coding RNA genes.

scholarly journals Neuron loss associated with age but not Alzheimer's disease pathology in the chimpanzee brain

2020 ◽  
Vol 375 (1811) ◽  
pp. 20190619 ◽  
Author(s):  
Melissa K. Edler ◽  
Emily L. Munger ◽  
Richard S. Meindl ◽  
William D. Hopkins ◽  
John J. Ely ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurofibrillary Tangle ◽  
Cell Loss ◽  
Tau Proteins ◽  
Middle Temporal Gyrus ◽  
Neuron Death ◽  
Neuron Loss ◽  
Neuron Density ◽  
Age Related

In the absence of disease, ageing in the human brain is accompanied by mild cognitive dysfunction, gradual volumetric atrophy, a lack of significant cell loss, moderate neuroinflammation, and an increase in the amyloid beta (A β ) and tau proteins. Conversely, pathologic age-related conditions, particularly Alzheimer's disease (AD), result in extensive neocortical and hippocampal atrophy, neuron death, substantial A β plaque and tau-associated neurofibrillary tangle pathologies, glial activation and severe cognitive decline. Humans are considered uniquely susceptible to neurodegenerative disorders, although recent studies have revealed A β and tau pathology in non-human primate brains. Here, we investigate the effect of age and AD-like pathology on cell density in a large sample of postmortem chimpanzee brains ( n = 28, ages 12–62 years). Using a stereologic, unbiased design, we quantified neuron density, glia density and glia:neuron ratio in the dorsolateral prefrontal cortex, middle temporal gyrus, and CA1 and CA3 hippocampal subfields. Ageing was associated with decreased CA1 and CA3 neuron densities, while AD pathologies were not correlated with changes in neuron or glia densities. Differing from cerebral ageing and AD in humans, these data indicate that chimpanzees exhibit regional neuron loss with ageing but appear protected from the severe cell death found in AD. This article is part of the theme issue ‘Evolution of the primate ageing process’.

scholarly journals Screening for Core Genes Related to Pathogenesis of Alzheimer’s Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Longxiu Yang ◽  
Yuan Qin ◽  
Chongdong Jian
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Nearest Neighbor ◽  
Core Gene ◽  
Middle Temporal Gyrus ◽  
Support Vector ◽  
Rna Expression ◽  
K Nearest Neighbor ◽  
System Disease ◽  
Core Genes

Alzheimer’s disease (AD), a nervous system disease, lacks effective therapies at present. RNA expression is the basic way to regulate life activities, and identifying related characteristics in AD patients may aid the exploration of AD pathogenesis and treatment. This study developed a classifier that could accurately classify AD patients and healthy people, and then obtained 3 core genes that may be related to the pathogenesis of AD. To this end, RNA expression data of the middle temporal gyrus of AD patients were firstly downloaded from GEO database, and the data were then normalized using limma package following a supplementation of missing data by k-Nearest Neighbor (KNN) algorithm. Afterwards, the top 500 genes of the most feature importance were obtained through Max-Relevance and Min-Redundancy (mRMR) analysis, and based on these genes, a series of AD classifiers were constructed through Support Vector Machine (SVM), Random Forest (RF), and KNN algorithms. Then, the KNN classifier with the highest Matthews correlation coefficient (MCC) value composed of 14 genes in incremental feature selection (IFS) analysis was identified as the best AD classifier. As analyzed, the 14 genes played a pivotal role in determination of AD and may be core genes associated with the pathogenesis of AD. Finally, protein-protein interaction (PPI) network and Random Walk with Restart (RWR) analysis were applied to obtain core gene-associated genes, and key pathways related to AD were further analyzed. Overall, this study contributed to a deeper understanding of AD pathogenesis and provided theoretical guidance for related research and experiments.

scholarly journals Characterization of lysosomal proteins Progranulin and Prosaposin and their interactions in Alzheimer’s disease and aged brains: increased levels correlate with neuropathology

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Anarmaa Mendsaikhan ◽  
Ikuo Tooyama ◽  
Jean-Pierre Bellier ◽  
Geidy E. Serrano ◽  
Lucia I. Sue ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Amyloid Beta ◽  
Cortical Neurons ◽  
Middle Temporal Gyrus ◽  
Early Event ◽  
Single Mutation ◽  
Lysosomal Function ◽  
Cellular Expression ◽  
Plaque Pathology

AbstractProgranulin (PGRN) is a protein encoded by the GRN gene with multiple identified functions including as a neurotrophic factor, tumorigenic growth factor, anti-inflammatory cytokine and regulator of lysosomal function. A single mutation in the human GRN gene resulting in reduced PGRN expression causes types of frontotemporal lobar degeneration resulting in frontotemporal dementia. Prosaposin (PSAP) is also a multifunctional neuroprotective secreted protein and regulator of lysosomal function. Interactions of PGRN and PSAP affect their functional properties. Their roles in Alzheimer’s disease (AD), the leading cause of dementia, have not been defined. In this report, we examined in detail the cellular expression of PGRN in middle temporal gyrus samples of a series of human brain cases (n = 45) staged for increasing plaque pathology. Immunohistochemistry showed PGRN expression in cortical neurons, microglia, cerebral vessels and amyloid beta (Aβ) plaques, while PSAP expression was mainly detected in neurons and Aβ plaques, and to a limited extent in astrocytes. We showed that there were increased levels of PGRN protein in AD cases and corresponding increased levels of PSAP. Levels of PGRN and PSAP protein positively correlated with amyloid beta (Aβ), with PGRN levels correlating with phosphorylated tau (serine 205) levels in these samples. Although PGRN colocalized with lysosomal-associated membrane protein-1 in neurons, most PGRN associated with Aβ plaques did not. Aβ plaques with PGRN and PSAP deposits were identified in the low plaque non-demented cases suggesting this was an early event in plaque formation. We did not observe PGRN-positive neurofibrillary tangles. Co-immunoprecipitation studies of PGRN from brain samples identified only PSAP associated with PGRN, not sortilin or other known PGRN-binding proteins, under conditions used. Most PGRN associated with Aβ plaques were immunoreactive for PSAP showing a high degree of colocalization of these proteins that did not change between disease groups. As PGRN supplementation has been considered as a therapeutic approach for AD, the possible involvement of PGRN and PSAP interactions in AD pathology needs to be further considered.

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