Construction of Long Noncoding RNA-Associated ceRNA Networks Reveals Potential Biomarkers in Alzheimer’s Disease

2021 ◽  
pp. 1-15
Author(s):  
Guan-yong Ou ◽  
Wen-wen Lin ◽  
Wei-jiang Zhao
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Noncoding Rna ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Brain Regions ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Potential Biomarkers

Background: Alzheimer’s disease (AD) is a chronic neurodegenerative disease that seriously impairs both cognitive and memory functions mainly in the elderly, and its incidence increases with age. Recent studies demonstrated that long noncoding RNAs (lncRNAs) play important roles in AD by acting as competing endogenous RNAs (ceRNAs). Objective: In this study, we aimed to construct lncRNA-associated ceRNA regulatory networks composed of potential biomarkers in AD based on the ceRNA hypothesis. Methods: A total of 20 genes (10 upregulated genes and 10 downregulated genes) were identified as the hub differentially expressed genes (DEGs). The functional enrichment analysis showed that the most significant pathways of DEGs involved include retrograde endocannabinoid signaling, synaptic vesicle circle, and AD. The upregulated hub genes were mainly enriched in the cytokine-cytokine receptor interaction pathway, whereas downregulated hub genes were involved in the neuroactive ligand-receptor interaction pathway. After convergent functional genomic (CFG) ranks and expression level analysis in different brain regions of hub genes, we found that CXCR4, GFAP, and GNG3 were significantly correlated with AD. We further identified crucial miRNAs and lncRNAs of targeted genes to construct lncRNA-associated ceRNA regulatory networks. Results: The results showed that two lncRNAs (NEAT1, MIAT), three miRNAs (hsa-miR-551a, hsa-miR-133b and hsa-miR-206), and two mRNA (CXCR4 and GNG3), which are highly related to AD, were preliminarily identified as potential AD biomarkers. Conclusion: Our study provides new insights for understanding the pathogenic mechanism underlying AD, which may potentially contribute to the ceRNA mechanism in AD.

scholarly journals Identification of the Hub Genes in Alzheimer’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Huiwen Gui ◽  
Qi Gong ◽  
Jun Jiang ◽  
Mei Liu ◽  
Huanyin Li
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Elderly ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Geo Database

Purpose. Alzheimer’s disease (AD) is considered to be the most common neurodegenerative disease and also one of the major fatal diseases affecting the elderly, thus bringing a huge burden to society. Therefore, identifying AD-related hub genes is extremely important for developing novel strategies against AD. Materials and Methods. Here, we extracted the gene expression profile GSE63061 from the National Center for Biotechnology Information (NCBI) GEO database. Once the unverified gene chip was removed, we standardized the microarray data after quality control. We utilized the Limma software package to screen the differentially expressed genes (DEGs). We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DEGs. Subsequently, we constructed a protein-protein interaction (PPI) network using the STRING database. Result. We screened 2169 DEGs, comprising 1313 DEGs with upregulation and 856 DEGs with downregulation. Functional enrichment analysis showed that the response of immune, the degranulation of neutrophils, lysosome, and the differentiation of osteoclast were greatly enriched in DEGs with upregulation; peptide biosynthetic process, translation, ribosome, and oxidative phosphorylation were dramatically enriched in DEGs with downregulation. 379 nodes and 1149 PPI edges were demonstrated in the PPI network constructed by upregulated DEGs; 202 nodes and 1963 PPI edges were shown in the PPI network constructed by downregulated DEGs. Four hub genes, including GAPDH, RHOA, RPS29, and RPS27A, were identified to be the newly produced candidates involved in AD pathology. Conclusion. GAPDH, RHOA, RPS29, and RPS27A are expected to be key candidates for AD progression. The results of this study can provide comprehensive insight into understanding AD’s pathogenesis and potential new therapeutic targets.

scholarly journals Unearthing of Key Genes Driving the Pathogenesis of Alzheimer’s Disease via Bioinformatics

2021 ◽  
Vol 12 ◽  
Author(s):  
Xingxing Zhao ◽  
Hongmei Yao ◽  
Xinyi Li
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Temporal Cortex ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Machine Learning Algorithms ◽  
Functional Enrichment ◽  
Control Group ◽  
Hub Genes ◽  
Expression Levels

Alzheimer’s disease (AD) is a neurodegenerative disease with unelucidated molecular pathogenesis. Herein, we aimed to identify potential hub genes governing the pathogenesis of AD. The AD datasets of GSE118553 and GSE131617 were collected from the NCBI GEO database. The weighted gene coexpression network analysis (WGCNA), differential gene expression analysis, and functional enrichment analysis were performed to reveal the hub genes and verify their role in AD. Hub genes were validated by machine learning algorithms. We identified modules and their corresponding hub genes from the temporal cortex (TC), frontal cortex (FC), entorhinal cortex (EC), and cerebellum (CE). We obtained 33, 42, 42, and 41 hub genes in modules associated with AD in TC, FC, EC, and CE tissues, respectively. Significant differences were recorded in the expression levels of hub genes between AD and the control group in the TC and EC tissues (P < 0.05). The differences in the expressions of FCGRT, SLC1A3, PTN, PTPRZ1, and PON2 in the FC and CE tissues among the AD and control groups were significant (P < 0.05). The expression levels of PLXNB1, GRAMD3, and GJA1 were statistically significant between the Braak NFT stages of AD. Overall, our study uncovered genes that may be involved in AD pathogenesis and revealed their potential for the development of AD biomarkers and appropriate AD therapeutics targets.

scholarly journals Analysis of Shared Genetic Regulatory Networks for Alzheimer’s Disease and Epilepsy

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiao-Dan Wang ◽  
Shuai Liu ◽  
Hui Lu ◽  
Yalin Guan ◽  
Hao Wu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Studies ◽  
Genetic Regulatory Networks ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Genome Wide Association Studies ◽  
Hub Genes ◽  
Gene Coexpression ◽  
Shared Genetic

Alzheimer’s disease (AD) and epilepsy are neurological disorders that affect a large cohort of people worldwide. Although both of the two diseases could be influenced by genetic factors, the shared genetic mechanism underlying the pathogenesis of them is still unclear. In this study, we aimed to identify the shared genetic networks and corresponding hub genes for AD and epilepsy. Firstly, the gene coexpression modules (GCMs) were constructed by weighted gene coexpression network analysis (WGCNA), and 16 GCMs were identified. Through further integration of GCMs, genome-wide association studies (GWASs), and expression quantitative trait loci (eQTLs), 4 shared GCMs of AD and epilepsy were identified. Functional enrichment analysis was performed to analyze the shared biological processes of these GCMs and explore the functional overlaps between these two diseases. The results showed that the genes in shared GCMs were significantly enriched in nervous system-related pathways, such as Alzheimer’s disease and neuroactive ligand-receptor interaction pathways. Furthermore, the hub genes of AD- and epilepsy-associated GCMs were captured by weighted key driver analysis (wKDA), including TRPC1, C2ORF40, NR3C1, KIAA0368, MMT00043109, STEAP1, MSX1, KL, and CLIC6. The shared GCMs and hub genes might provide novel therapeutic targets for AD and epilepsy.

scholarly journals Integrated Analysis of lncRNAs, mRNAs, and TFs to Identify Regulatory Networks Underlying MAP Infection in Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Maryam Heidari ◽  
Abbas Pakdel ◽  
Mohammad Reza Bakhtiarizadeh ◽  
Fariba Dehghanian
Keyword(s):  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Johne's Disease ◽  
Johne’S Disease ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Complex Nature ◽  
Hub Genes ◽  
Cis And Trans

Johne’s disease is a chronic infection of ruminants that burdens dairy herds with a significant economic loss. The pathogenesis of the disease has not been revealed clearly due to its complex nature. In order to achieve deeper biological insights into molecular mechanisms involved in MAP infection resulting in Johne’s disease, a system biology approach was used. As far as is known, this is the first study that considers lncRNAs, TFs, and mRNAs, simultaneously, to construct an integrated gene regulatory network involved in MAP infection. Weighted gene coexpression network analysis (WGCNA) and functional enrichment analysis were conducted to explore coexpression modules from which nonpreserved modules had altered connectivity patterns. After identification of hub and hub-hub genes as well as TFs and lncRNAs in the nonpreserved modules, integrated networks of lncRNA-mRNA-TF were constructed, and cis and trans targets of lncRNAs were identified. Both cis and trans targets of lncRNAs were found in eight nonpreserved modules. Twenty-one of 47 nonpreserved modules showed significant biological processes related to the immune system and MAP infection. Some of the MAP infection’s related pathways in the most important nonpreserved modules comprise “positive regulation of cytokine-mediated signaling pathway,” “negative regulation of leukocyte migration,” “T-cell differentiation,” “neutrophil activation,” and “defense response.” Furthermore, several genes were identified in these modules, including SLC11A1, MAPK8IP1, HMGCR, IFNGR1, CMPK2, CORO1A, IRF1, LDLR, BOLA-DMB, and BOLA-DMA, which are potentially associated with MAP pathogenesis. This study not only enhanced our knowledge of molecular mechanisms behind MAP infection but also highlighted several promising hub and hub-hub genes involved in macrophage-pathogen interaction.

scholarly journals Soluble Amyloid-Beta Isoforms Predict Downstream Alzheimer’s Disease Pathology

2021 ◽  
Author(s):  
Guilherme Povala ◽  
Bruna Bellaver ◽  
Marco Antônio De Bastiani ◽  
Wagner S. Brum ◽  
Pamela C. L. Ferreira ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Amyloid Beta ◽  
Area Under The Curve ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Proteomics Data ◽  
Proteomics Analysis ◽  
Significant Enrichment

Abstract Background: Changes in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer's disease (AD). However, whether Aβ levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With this in mind, we aimed at investigating whether a combination of soluble Aβ isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity. Methods: We used CSF measurements of three soluble Aβ peptides (Aβ1‑38, Aβ1‑40 and Aβ1‑42) in CU individuals (n = 318) as input features in machine learning (ML) models aiming at predicting T+ and N+. Input data was used for building 2046 tuned predictive ML models with a nested cross-validation technique. Additionally, proteomics data was employed to investigate the functional enrichment of biological processes altered in T+ and N+ individuals. Results: Our findings indicate that Aβ isoforms can predict T+ and N+ with an area under the curve (AUC) of 0.929 and 0.936, respectively. Additionally, proteomics analysis identified 17 differentially expressed proteins (DEPs) in individuals wrongly classified by our ML algorithm. More specifically, enrichment analysis of gene ontology biological processes revealed an upregulation in myelinization and glucose metabolism-related processes in CU individuals wrongly predicted as T+. A significant enrichment of DEPs in pathways including biosynthesis of amino acids, glycolysis/gluconeogenesis, carbon metabolism, cell adhesion molecules and prion disease was also observed. Conclusions: Our results demonstrate that, by applying a refined ML analysis, a combination of Ab isoforms can predict T+ and N+ with a high AUC. CSF proteomics analysis highlighted a promising group of proteins that can be further explored for improving T+ and N+ prediction.

scholarly journals The Important Role of Perituberal Tissue in Epileptic Patients with Tuberous Sclerosis Complex by the Transcriptome Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shuqiang Li ◽  
Huijie Shao ◽  
Liansheng Chang
Keyword(s):  
Tuberous Sclerosis ◽  
Tuberous Sclerosis Complex ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Genes ◽  
R Language ◽  
Protein Protein Interaction

Epilepsy is most common in patients with tuberous sclerosis complex (TSC). However, in addition to the challenging treatment, the pathogenesis of epilepsy is still controversial. To determine the transcriptome characteristics of perituberal tissue (PT) and clarify its role in the pathogenesis of epilepsy, GSE16969 was downloaded from the GEO database for further study by comprehensive bioinformatics analysis. Identification of differentially expressed genes (DEGs), functional enrichment analysis, construction of protein-protein interaction (PPI) network, and selection of Hub genes were performed using R language, Metascape, STRING, and Cytoscape, respectively. Comparing with cortical tuber (CT), 220 DEGs, including 95 upregulated and 125 downregulated genes, were identified in PT and mainly enriched in collagen-containing extracellular matrix and positive regulation of receptor-mediated endocytosis, as well as the pathways of ECM-receptor interaction and neuroactive ligand-receptor interaction. As for normal cortex (NC), 1549 DEGs, including 30 upregulated and 1519 downregulated genes, were identified and mainly enriched in presynapse, dendrite and axon, and also the pathways of dopaminergic synapse and oxytocin signaling pathway. In the PPI network, 4 hub modules were found between PT and CT, and top 5 hub modules were selected between PT and NC. C3, APLNR, ANXA2, CD44, CLU, CP, MCHR2, HTR1E, CTSG, APP, and GNG2 were identified as Hub genes, of which, C3, CD44, ANXA2, HTR1E, and APP were identified as Hub-BottleNeck genes. In conclusion, PT has the unique characteristics different from CT and NC in transcriptome and makes us further understand its importance in the TSC-associated epilepsy.

Screening novel drug candidates for Alzheimer’s disease by an integrated network and transcriptome analysis

2020 ◽  
Vol 36 (17) ◽  
pp. 4626-4632
Author(s):  
Yonglin Peng ◽  
Meng Yuan ◽  
Juncai Xin ◽  
Xinhua Liu ◽  
Ju Wang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Supplementary Information ◽  
Integrated Network ◽  
Drug Candidates ◽  
Novel Drug

Abstract Motivation Alzheimer’s disease (AD) is a serious degenerative brain disease and the most common cause of dementia. The current available drugs for AD provide symptomatic benefit, but there is no effective drug to cure the disease. The emergence of large-scale genomic, pharmacological data provides new opportunities for drug discovery and drug repositioning as a promising strategy in searching novel drug for AD. Results In this study, we took advantage of our increasing understanding based on systems biology approaches on the pathway and network levels and perturbation datasets from the Library of Integrated Network-Based Cellular Signatures to introduce a systematic computational process to discover new drugs implicated in AD. First, we collected 561 genes that have reported to be risk genes of AD, and applied functional enrichment analysis on these genes. Then, by quantifying proximity between 5595 molecule drugs and AD based on human interactome, we filtered out 1092 drugs that were proximal to the disease. We further performed an Inverted Gene Set Enrichment analysis on these drug candidates, which allowed us to estimate effect of perturbations on gene expression and identify 24 potential drug candidates for AD treatment. Results from this study also provided insights for understanding the molecular mechanisms underlying AD. As a useful systematic method, our approach can also be used to identify efficacious therapies for other complex diseases. Availability and implementation The source code is available at https://github.com/zer0o0/drug-repo.git. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The Genetic and Epigenetic Mechanisms Involved in Irreversible Pulp Neural Inflammation

2021 ◽  
Vol 2021 ◽  
pp. 1-26
Author(s):  
Xiaoxi Xi ◽  
Yihong Ma ◽  
Yuzhen Xu ◽  
Anthony Chukwunonso Ogbuehi ◽  
Xiangqiong Liu ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Noncoding Rna ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Epigenetic Mechanisms ◽  
Cerna Network ◽  
Epigenetic Biomarkers ◽  
Irreversible Pulpitis

Aim. To identify the critical genetic and epigenetic biomarkers by constructing the long noncoding RNA- (lncRNA-) related competing endogenous RNA (ceRNA) network involved in irreversible pulp neural inflammation (pulpitis). Materials and Methods. The public datasets regarding irreversible pulpitis were downloaded from the gene expression omnibus (GEO) database. The differential expression analysis was performed to identify the differentially expressed genes (DEGs) and DElncRNAs. Functional enrichment analysis was performed to explore the biological processes and signaling pathways enriched by DEGs. By performing a weighted gene coexpression network analysis (WGCNA), the significant gene modules in each dataset were identified. Most importantly, DElncRNA-DEmRNA regulatory network and DElncRNA-associated ceRNA network were constructed. A transcription factor- (TF-) DEmRNA network was built to identify the critical TFs involved in pulpitis. Result. Two datasets (GSE92681 and GSE77459) were selected for analysis. DEGs involved in pulpitis were significantly enriched in seven signaling pathways (i.e., NOD-like receptor (NLR), Toll-like receptor (TLR), NF-kappa B, tumor necrosis factor (TNF), cell adhesion molecules (CAMs), chemokine, and cytokine-cytokine receptor interaction pathways). The ceRNA regulatory relationships were established consisting of three genes (i.e., LCP1, EZH2, and NR4A1), five miRNAs (i.e., miR-340-5p, miR-4731-5p, miR-27a-3p, miR-34a-5p, and miR-766-5p), and three lncRNAs (i.e., XIST, MIR155HG, and LINC00630). Six transcription factors (i.e., GATA2, ETS1, FOXP3, STAT1, FOS, and JUN) were identified to play pivotal roles in pulpitis. Conclusion. This paper demonstrates the genetic and epigenetic mechanisms of irreversible pulpitis by revealing the ceRNA network. The biomarkers identified could provide research direction for the application of genetically modified stem cells in endodontic regeneration.

scholarly journals The three-dimensional landscape of chromatin accessibility in Alzheimer’s disease

2021 ◽  
Author(s):  
Jaroslav Bendl ◽  
Mads E. Hauberg ◽  
Kiran Girdhar ◽  
Eunju Im ◽  
James M. Vicari ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Regulatory Networks ◽  
3D Structure ◽  
Three Dimensional ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Chromatin Accessibility ◽  
Regulatory Sequences ◽  
3D Genome

AbstractMuch is still unknown about the neurobiology of Alzheimer’s disease (AD). To better understand AD, we generated 636 ATAC-seq libraries from cases and controls to construct detailed genomewide chromatin accessibility maps of neurons and non-neurons from two AD-affected brain regions, the entorhinal cortex and superior temporal gyrus. By analyzing a total of 19.6 billion read pairs, we expanded the known repertoire of regulatory sequences in the human brain. Multi-omic data integration associated global patterns of chromatin accessibility with gene expression and identified cell-specific enhancer-promoter interactions. Using inter-individual variation in chromatin accessibility, we define cis-regulatory domains capturing the 3D structure of the genome. Multifaceted analyses uncovered disease associated perturbations impacting chromatin accessibility, transcription factor regulatory networks and the 3D genome, and implicated transcriptional dysregulation in AD. Overall, we applied a systematic approach to understand the role of the 3D genome in AD and to illuminate novel disease biology that can advance diagnosis and therapy.

Sign in / Sign up

Export Citation Format

Share Document