scholarly journals The Bioinformatic Analysis of the Dysregulated Genes and MicroRNAs in Entorhinal Cortex, Hippocampus, and Blood for Alzheimer’s Disease

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaocong Pang ◽  
Ying Zhao ◽  
Jinhua Wang ◽  
Qimeng Zhou ◽  
Lvjie Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules ◽  
Entorhinal Cortex ◽  
Drug Targets ◽  
Target Genes ◽  
Bioinformatic Analysis ◽  
Hub Genes ◽  
Pathway Enrichment

Aim. The incidence of Alzheimer’s disease (AD) has been increasing in recent years, but there exists no cure and the pathological mechanisms are not fully understood. This study aimed to find out the pathogenesis of learning and memory impairment, new biomarkers, potential therapeutic targets, and drugs for AD. Methods. We downloaded the microarray data of entorhinal cortex (EC) and hippocampus (HIP) of AD and controls from Gene Expression Omnibus (GEO) database, and then the differentially expressed genes (DEGs) in EC and HIP regions were analyzed for functional and pathway enrichment. Furthermore, we utilized the DEGs to construct coexpression networks to identify hub genes and discover the small molecules which were capable of reversing the gene expression profile of AD. Finally, we also analyzed microarray and RNA-seq dataset of blood samples to find the biomarkers related to gene expression in brain. Results. We found some functional hub genes, such as ErbB2, ErbB4, OCT3, MIF, CDK13, and GPI. According to GO and KEGG pathway enrichment, several pathways were significantly dysregulated in EC and HIP. CTSD and VCAM1 were dysregulated significantly in blood, EC, and HIP, which were potential biomarkers for AD. Target genes of four microRNAs had similar GO_terms distribution with DEGs in EC and HIP. In addtion, small molecules were screened out for AD treatment. Conclusion. These biological pathways and DEGs or hub genes will be useful to elucidate AD pathogenesis and identify novel biomarkers or drug targets for developing improved diagnostics and therapeutics against AD.

scholarly journals Bioinformatics analysis of differentially expressed genes and identification of an miRNA–mRNA network associated with entorhinal cortex and hippocampus in Alzheimer’s disease

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Haoming Li ◽  
Linqing Zou ◽  
Jinhong Shi ◽  
Xiao Han
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Differentially Expressed Genes ◽  
Entorhinal Cortex ◽  
Molecular Mechanisms ◽  
Kegg Pathway ◽  
Neurodegenerative Disorder ◽  
Early Stage ◽  
Differentially Expressed ◽  
Hub Genes

Abstract Background Alzheimer’s disease (AD) is a fatal neurodegenerative disorder, and the lesions originate in the entorhinal cortex (EC) and hippocampus (HIP) at the early stage of AD progression. Gaining insight into the molecular mechanisms underlying AD is critical for the diagnosis and treatment of this disorder. Recent discoveries have uncovered the essential roles of microRNAs (miRNAs) in aging and have identified the potential of miRNAs serving as biomarkers in AD diagnosis. Methods We sought to apply bioinformatics tools to investigate microarray profiles and characterize differentially expressed genes (DEGs) in both EC and HIP and identify specific candidate genes and pathways that might be implicated in AD for further analysis. Furthermore, we considered that DEGs might be dysregulated by miRNAs. Therefore, we investigated patients with AD and healthy controls by studying the gene profiling of their brain and blood samples to identify AD-related DEGs, differentially expressed miRNAs (DEmiRNAs), along with gene ontology (GO) analysis, KEGG pathway analysis, and construction of an AD-specific miRNA–mRNA interaction network. Results Our analysis identified 10 key hub genes in the EC and HIP of patients with AD, and these hub genes were focused on energy metabolism, suggesting that metabolic dyshomeostasis contributed to the progression of the early AD pathology. Moreover, after the construction of an miRNA–mRNA network, we identified 9 blood-related DEmiRNAs, which regulated 10 target genes in the KEGG pathway. Conclusions Our findings indicated these DEmiRNAs having the potential to act as diagnostic biomarkers at an early stage of AD.

Gene Expression Profiles of Entorhinal Cortex in Alzheimer’s Disease

2014 ◽  
Vol 29 (6) ◽  
pp. 526-532 ◽  
Author(s):  
Bingqian Ding ◽  
Yan Xi ◽  
Ming Gao ◽  
Zhenjiang Li ◽  
Chenyang Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Entorhinal Cortex ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

PLoS Genetics ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. e1009224
Author(s):  
Denis A. Baird ◽  
Jimmy Z. Liu ◽  
Jie Zheng ◽  
Solveig K. Sieberts ◽  
Thanneer Perumal ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Targets ◽  
Causal Effect ◽  
Brain Diseases ◽  
Psychiatric Disease ◽  
Monogenic Disease ◽  
Psychiatric Diseases ◽  
Neuropsychiatric Diseases

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer’s Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer’s disease, 6 genes with Parkinson’s disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.

scholarly journals Sleep and Alzheimer’s Disease: Shared Genetic Risk Factors, Drug Targets, Molecular Mechanisms, and Causal Effects

2021 ◽  
Author(s):  
Dongze Chen ◽  
Xinpei Wang ◽  
Jinzhu Jia ◽  
Tao Huang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Study ◽  
Sleep Duration ◽  
Drug Target ◽  
Drug Targets ◽  
Target Genes ◽  
Lipoprotein Particle ◽  
Level Data ◽  
Particle Clearance

Abstract Background: Alzheimer’s disease (AD) was associated with sleep-related phenotypes (SRPs). Whether they share common genetic etiology remains largely unknown. We explored the shared genetics and causality between AD and SRPs by using high-definition likelihood (HDL), cross phenotype association study (CPASSOC), transcriptome wide association study (TWAS), and bidirectional Mendelian randomization (MR) in summary-level data for AD (n = 79145) and summary-level data for seven SRPs (sample size ranges from 345552 to 386577). Results: AD shared strong genetic basis with insomnia (rg = 0.20; P = 9.70×10-5), snoring (rg = 0.13; P = 2.45×10-3), and sleep duration (rg = -0.11; P = 1.18×10-3). CPASSOC identifies 31 independent loci shared between AD and SRPs, including four novel shared loci. Functional analysis and TWAS showed shared genes were enriched in liver, brain, breast, and heart tissues, and highlighted the regulatory role of immunological disorders, very-low-density lipoprotein particle clearance, triglyceride-rich lipoprotein particle clearance, chylomicron remnant clearance and positive regulation of T cell mediated cytotoxicity pathways. Protein-protein interaction analysis provided three potential drug target genes (APOE, MARK4 and HLA-DRA) that interacted with known FDA-approved drug target genes. CPASSOC and TWAS demonstrated three regions 11p11.2, 6p22.3 and 16p11.2 may account for the shared basis between AD and sleep duration or snoring. MR showed AD had causal effect on sleep duration (βIVW = -0.056, PIVW = 1.03×10-3). Conclusion: Our findings provide strong evidence of shared genetics and causation between AD and sleep, and advance our understanding the genetic overlap between them. Identifying shared drug targets and molecular pathways can be beneficial to treat AD and sleep disorders more efficiently.

CDK5 and MAPT Gene Expression in Alzheimer's Disease Brain Samples

2018 ◽  
Vol 15 (2) ◽  
pp. 182-186 ◽  
Author(s):  
Josianne T. Fukasawa ◽  
Roger W. de Labio ◽  
Lucas T. Rasmussen ◽  
Lucieni C. de Oliveira ◽  
Elizabeth Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Cell Cycle ◽  
Alzheimer's Disease ◽  
Entorhinal Cortex ◽  
Neurodegenerative Disorder ◽  
Elderly Subjects ◽  
Main Challenge ◽  
Mapt Gene ◽  
The Brain

Background: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by extracellular amyloid plaque and neurofibrillary tangles in the brain. Studies have shown that neurons are able to re-enter the cell cycle, but not enough to enable full replication. This leads to cell death and consequent neurodegeneration. Objective: This study aimed to characterize the expression of the MAPT gene and CDK5 (the gene involved in cell cycle regulation) in brain samples from patients with AD and controls. Method: The real-time-PCR technique was used to characterize 150 samples from three areas of the brain (entorhinal cortex, auditory cortex, and hippocampus) of 26 AD patients and 24 healthy elderly subjects. Results: When the brain samples were analyzed collectively, a decrease in CDK5 and MAPT gene expression was found in AD patients. When each groups' samples were separated by area of the brain and compared, significant differences were found in CDK5 expression in the hippocampus and the entorhinal cortex. In both cases, mRNA was lower in the AD group (p=0.0001); however, the same analysis using the MAPT gene revealed no significant statistical differences. No statistical differences were found when gene expression was compared between the different regions of the brain within each group. Conclusion: These results may contribute to a better understanding of the involvement of CDK5 and MAPT genes in AD in that they consider different areas of the brain that are affected differently based on disease progression. The main challenge is to establish an effective therapy for this debilitating disease in the future.

scholarly journals Dysregulated expression levels of APH1B in peripheral blood are associated with brain atrophy and amyloid-β deposition in Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Young Ho Park ◽  
Jung-Min Pyun ◽  
Angela Hodges ◽  
Jae-Won Jang ◽  
Paula J. Bice ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Target Genes ◽  
Linear Regression Analysis ◽  
Amyloid Β ◽  
Imaging Biomarkers ◽  
Eqtl Analysis ◽  
Expression Levels

Abstract Background The interaction between the brain and periphery might play a crucial role in the development of Alzheimer’s disease (AD). Methods Using blood transcriptomic profile data from two independent AD cohorts, we performed expression quantitative trait locus (cis-eQTL) analysis of 29 significant genetic loci from a recent large-scale genome-wide association study to investigate the effects of the AD genetic variants on gene expression levels and identify their potential target genes. We then performed differential gene expression analysis of identified AD target genes and linear regression analysis to evaluate the association of differentially expressed genes with neuroimaging biomarkers. Results A cis-eQTL analysis identified and replicated significant associations in seven genes (APH1B, BIN1, FCER1G, GATS, MS4A6A, RABEP1, TRIM4). APH1B expression levels in the blood increased in AD and were associated with entorhinal cortical thickness and global cortical amyloid-β deposition. Conclusion An integrative analysis of genetics, blood-based transcriptomic profiles, and imaging biomarkers suggests that APH1B expression levels in the blood might play a role in the pathogenesis of AD.

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