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 ◽  
...  
2020 ◽  
Vol 375 (1811) ◽  
pp. 20190619 ◽  
Author(s):  
Melissa K. Edler ◽  
Emily L. Munger ◽  
Richard S. Meindl ◽  
William D. Hopkins ◽  
John J. Ely ◽  
...  

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’.


2021 ◽  
Author(s):  
Shuo Chen ◽  
Yuzhou Chang ◽  
Liangping Li ◽  
Diana Acosta ◽  
Cody Morrison ◽  
...  

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.


Author(s):  
Longxiu Yang ◽  
Yuan Qin ◽  
Chongdong Jian

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.


2020 ◽  
Vol 21 (22) ◽  
pp. 8704
Author(s):  
Karan Govindpani ◽  
Clinton Turner ◽  
Henry J. Waldvogel ◽  
Richard L. M. Faull ◽  
Andrea Kwakowsky

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.


Author(s):  
Sofiia Yefremova ◽  

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.


2020 ◽  
Author(s):  
Shahan Mamoor

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).


2019 ◽  
Vol 70 (3) ◽  
pp. 691-713 ◽  
Author(s):  
Ignazio S. Piras ◽  
Jonida Krate ◽  
Elaine Delvaux ◽  
Jennifer Nolz ◽  
Diego F. Mastroeni ◽  
...  

2020 ◽  
Vol 29 (5) ◽  
pp. 817-833 ◽  
Author(s):  
Masataka Kikuchi ◽  
Michiko Sekiya ◽  
Norikazu Hara ◽  
Akinori Miyashita ◽  
Ryozo Kuwano ◽  
...  

Abstract The molecular biological mechanisms of Alzheimer’s disease (AD) involve disease-associated crosstalk through many genes and include a loss of normal as well as a gain of abnormal interactions among genes. A protein domain network (PDN) is a collection of physical bindings that occur between protein domains, and the states of the PDNs in patients with AD are likely to be perturbed compared to those in normal healthy individuals. To identify PDN changes that cause neurodegeneration, we analysed the PDNs that occur among genes co-expressed in each of three brain regions at each stage of AD. Our analysis revealed that the PDNs collapsed with the progression of AD stage and identified five hub genes, including Rac1, as key players in PDN collapse. Using publicly available as well as our own gene expression data, we confirmed that the mRNA expression level of the RAC1 gene was downregulated in the entorhinal cortex (EC) of AD brains. To test the causality of these changes in neurodegeneration, we utilized Drosophila as a genetic model and found that modest knockdown of Rac1 in neurons was sufficient to cause age-dependent behavioural deficits and neurodegeneration. Finally, we identified a microRNA, hsa-miR-101-3p, as a potential regulator of RAC1 in AD brains. As the Braak neurofibrillary tangle (NFT) stage progressed, the expression levels of hsa-miR-101-3p were increased specifically in the EC. Furthermore, overexpression of hsa-miR-101-3p in the human neuronal cell line SH-SY5Y caused RAC1 downregulation. These results highlight the utility of our integrated network approach for identifying causal changes leading to neurodegeneration in AD.


2021 ◽  
pp. 1-10
Author(s):  
Douglas Barthold ◽  
Laura E. Gibbons ◽  
Zachary A. Marcum ◽  
Shelly L. Gray ◽  
C. Dirk Keene ◽  
...  

Background: Diabetes is a risk factor for Alzheimer’s disease and related dementias (ADRD). Epidemiologic evidence shows an association between diabetes medications and ADRD risk; cell and mouse models show diabetes medication association with AD-related neuropathologic change (ADNC). Objective: This hypothesis-generating analysis aimed to describe autopsy-measured ADNC for individuals who used diabetes medications. Methods: Descriptive analysis of ADNC for Adult Changes in Thought (ACT) Study autopsy cohort who used diabetes medications, including sulfonylureas, insulin, and biguanides; total N = 118. ADNC included amyloid plaque distribution (Thal phasing), neurofibrillary tangle (NFT) distribution (Braak stage), and cortical neuritic plaque density (CERAD score). We also examined quantitative measures of ADNC using the means of standardized Histelide measures of cortical PHF-tau and Aβ 1–42. Adjusted analyses control for age at death, sex, education, APOE genotype, and diabetes complication severity index. Results: Adjusted analyses showed no significant association between any drug class and traditional neuropathologic measures compared to nonusers of that class. In adjusted Histelide analyses, any insulin use was associated with lower mean levels of Aβ 1–42 (–0.57 (CI: –1.12, –0.02)) compared to nonusers. Five years of sulfonylureas and of biguanides use was associated with lower levels of Aβ 1–42 compared to nonusers (–0.15 (CI: –0.28, –0.02), –0.31 (CI: –0.54, –0.07), respectively). Conclusion: Some evidence exists that diabetes medications are associated with lower levels of Aβ 1–42, but not traditional measures of neuropathology. Future studies are needed in larger samples to build understanding of the mechanisms between diabetes, its medications, and ADRD, and to potentially repurpose existing medications for prevention or delay of ADRD.


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