scholarly journals Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pusheng Quan ◽  
Kai Wang ◽  
Shi Yan ◽  
Shirong Wen ◽  
Chengqun Wei ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Drug Candidates ◽  
Novel Drug

AbstractThis study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

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 Integrated lncRNA and mRNA Transcriptome Analyses in the Ovary of Cynoglossus semilaevis Reveal Genes and Pathways Potentially Involved in Reproduction

2021 ◽  
Vol 12 ◽  
Author(s):  
Yani Dong ◽  
Likang Lyu ◽  
Daiqiang Zhang ◽  
Jing Li ◽  
Haishen Wen ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Cynoglossus Semilaevis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Tongue Sole ◽  
Oocyte Meiosis

Long non-coding RNAs (lncRNAs) have been reported to be involved in multiple biological processes. However, the roles of lncRNAs in the reproduction of half-smooth tongue sole (Cynoglossus semilaevis) are unclear, especially in the molecular regulatory mechanism driving ovarian development and ovulation. Thus, to explore the mRNA and lncRNA mechanisms regulating reproduction, we collected tongue sole ovaries in three stages for RNA sequencing. In stage IV vs. V, we identified 312 differentially expressed (DE) mRNAs and 58 DE lncRNAs. In stage V vs. VI, we identified 1,059 DE mRNAs and 187 DE lncRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DE mRNAs were enriched in ECM-receptor interaction, oocyte meiosis and steroid hormone biosynthesis pathways. Furthermore, we carried out gene set enrichment analysis (GSEA) to identify potential reproduction related-pathways additionally, such as fatty metabolism and retinol metabolism. Based on enrichment analysis, DE mRNAs with a potential role in reproduction were selected and classified into six categories, including signal transduction, cell growth and death, immune response, metabolism, transport and catabolism, and cell junction. The interactions of DE lncRNAs and mRNAs were predicted according to antisense, cis-, and trans-regulatory mechanisms. We constructed a competing endogenous RNA (ceRNA) network. Several lncRNAs were predicted to regulate genes related to reproduction including cyp17a1, cyp19a1, mmp14, pgr, and hsd17b1. The functional enrichment analysis of these target genes of lncRNAs revealed that they were involved in several signaling pathways, such as the TGF-beta, Wnt signaling, and MAPK signaling pathways and reproduction related-pathways such as the progesterone-mediated oocyte maturation, oocyte meiosis, and GnRH signaling pathway. RT-qPCR analysis showed that two lncRNAs (XR_522278.2 and XR_522171.2) were mainly expressed in the ovary. Dual-fluorescence in situ hybridization experiments showed that both XR_522278.2 and XR_522171.2 colocalized with their target genes cyp17a1 and cyp19a1, respectively, in the follicular cell layer. The results further demonstrated that lncRNAs might be involved in the biological processes by modulating gene expression. Taken together, this study provides lncRNA profiles in the ovary of tongue sole and further insight into the role of lncRNA involvement in regulating reproduction in tongue sole.

scholarly journals Identification of Potential miRNA-mRNA Regulatory Network Contributing to Parkinson’s Disease

2021 ◽  
Author(s):  
Xi Yin ◽  
Miao Wang ◽  
Wei Wang ◽  
Tong Chen ◽  
Ge Song ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Rab Protein ◽  
Healthy Donors ◽  
Geo Database

Abstract Parkinson’s disease (PD) is a common neurodegenerative disease and the mechanism underlying PD pathogenesis is incompletely understood. Increasing evidence indicates that microRNA (miRNA) plays critical regulatory role in the pathogenesis of PD. This study aimed to determine the miRNA-mRNA regulatory network for PD. The differentially expressed miRNAs (DEmis) and genes (DEGs) between PD patients and healthy donors were screened from miRNA dataset GSE16658 and mRNA dataset GSE100054 downloaded from the Gene Expression Omnibus (GEO) database. Target genes of the DEmis were selected when predicted by 3 or 4 online databases and overlapped with DEGs from GSE100054. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted by Database for Annotation, Visualization and Integrated Discovery (DAVID) and Metascape analytic tool. The correlation between the screened genes and PD was evaluated by the online tool Comparative Toxicogenomics Database (CTD). The protein-protein interactions (PPI) network was built by STRING platform. Finally, we testify the expression of members of the miRNA-mRNA regulatory network in the blood samples collected from PD patients and healthy donors by using qRT-PCR. 1505 upregulated and 1302 downregulated DEGs, 77 upregulated DEmis and 112 downregulated DEmis were preliminarily screened from GEO database. Through further functional enrichment analysis, 10 PD-related hub genes were selected, including RAC1, IRS2, LEPR, PPARGC1A, CAMKK2, RAB10, RAB13, RAB27B, RAB11A and JAK2, which were mainly involved in Rab protein signaling transduction, AMPK signaling pathway and signaling by Leptin. The miRNA-mRNA regulatory network was constructed with 10 hub genes and their interacting miRNAs overlapped with DEmis, including miR-30e-5p, miR-142-3p, miR-101-3p, miR-32-3p, miR-508-5p, miR-642a-5p, miR-19a-3p and miR-21-5p. Analysis on clinical samples verified significant upregulation of LEPR and downregulation of miR-101-3p in PD patients compared with healthy donors. In the study, the potential miRNA-mRNA regulatory network was constructed in PD, which may provide novel insight into pathogenesis and treatment of PD.

scholarly journals Microarray Analysis of Transcriptome of Medulla Identifies Potential Biomarkers for Parkinson’s Disease

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xiao-Yang Liao ◽  
Wei-Wen Wang ◽  
Zheng-Hui Yang ◽  
Jun Wang ◽  
Hang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Motor Nucleus ◽  
Inferior Olivary Nucleus ◽  
Potential Biomarkers

To complement the molecular pathways contributing to Parkinson’s disease (PD) and identify potential biomarkers, gene expression profiles of two regions of the medulla were compared between PD patients and control. GSE19587 containing two groups of gene expression profiles [6 dorsal motor nucleus of the vagus (DMNV) samples from PD patients and 5 from controls, 6 inferior olivary nucleus (ION) samples from PD patients and 5 from controls] was downloaded from Gene Expression Omnibus. As a result, a total of 1569 and 1647 differentially expressed genes (DEGs) were, respectively, screened in DMNV and ION with limma package ofR. The functional enrichment analysis by DAVID server (the Database for Annotation, Visualization and Integrated Discovery) indicated that the above DEGs may be involved in the following processes, such as regulation of cell proliferation, positive regulation of macromolecule metabolic process, and regulation of apoptosis. Further analysis showed that there were 365 common DEGs presented in both regions (DMNV and ION), which may be further regulated by eight clusters of microRNAs retrieved with WebGestalt. The genes in the common DEGs-miRNAs regulatory network were enriched in regulation of apoptosis process via DAVID analysis. These findings could not only advance the understandings about the pathogenesis of PD, but also suggest potential biomarkers for this disease.

scholarly journals Therapeutic potential of methylxanthine drug on alpha synuclein protein in Parkinson's disease

2021 ◽  
Author(s):  
Nishant Kumar Rana ◽  
Neha Srivastava ◽  
Bhupendra Kumar ◽  
Abhishek Pathak ◽  
Vijay Nath Mishra
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neurodegenerative Disorder ◽  
Therapeutic Potential ◽  
Enrichment Analysis ◽  
Alpha Synuclein ◽  
Target Protein ◽  
Functional Enrichment ◽  
Glutamate Excitotoxicity ◽  
In Silico Docking

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer. It exists in sporadic (90 to 95%) and familial (5 to 10%) form. Its pathogenesis is due to oxidative stress, glutamate excitotoxicity, protein aggregation, neuroinflammation and neurodegeneration. There is currently no cure for this disease. The protein- protein interaction and gene ontology/functional enrichment analysis have been performed to find out the prominent interactor protein and shared common biological pathways, especially PD pathway. Further in silico docking analysis was performed on target protein to investigate the prominent drug molecule for PD. Through computational molecular virtual screening of small molecules from selected twelve natural compounds, and among these compounds methylxanthine was shown to be prominent inhibitor to SNCA protein that ultimately prevent PD. The interaction of methylxanthine compound with the target protein SNCA suggested that, it interacted with prominent binding site with good docking score and might be involved in blocking the binding of neuroinducing substances like: 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) to SNCA protein. Thus methylxanthine compounds can be explored as promising drugs for the prevention of Parkinson's disease.

scholarly journals Serum Exosomal miRNAs as Biomarkers of Early Diagnosis and Progression in Parkinson's Disease

2021 ◽  
Author(s):  
Qian Yang ◽  
Shulei He ◽  
Lu Huang ◽  
Ci Shao ◽  
Tiejian Nie ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Qrt Pcr ◽  
Exosomal Mirnas ◽  
Serum Exosomes

Abstract BackgroundBlood-based test for disease progression and early diagnosis of Parkinson’s disease (PD) is a long awaited but unsolved key problem in the clinic. The profiles of microRNAs (miRNAs) are regarded as potential diagnostic biomarkers in human diseases whereas the miRNAs in the periphery are susceptible to the influence of various components. MiRNAs enriched in serum exosomes have revealed disease-specific advantages for the diagnosis due to their high abundance, stability and resistant to degradation. This study aimed to screen differentially expressed exosomal miRNAs between healthy controls and PD patients to aid in diagnosis. MethodsA total of 103 healthy controls and diagnosed PD patients at different Hoehn and Yahr (H&Y) stages in Tangdu Hospital were included. In total, 185 differentially expressed miRNAs were obtained through miRNA sequencing of serum exosomes as well as edgeR and t-test analyses. Subsequently, the weighted gene co-expression network analysis (WGCNA) was utilized to identify the commonly expressed miRNAs in all stages of PD by constructing connections between modules and specifically expressed miRNAs in each stage of PD by functional enrichment analysis. The obtained miRNAs were further validated by quantitative real-time polymerase chain reaction (qRT-PCR) with peripheral blood exosomes from 30 more participants. ResultsUsing WGCNA, it was found that 4 miRNAs were commonly associated with all the stages of PD and 13 miRNAs were specifically associated with different stages of PD. Among the 17 miRNAs, 2 were commonly expressed in all the stages of PD and 5 were specifically expressed in different stages of PD via qRT-PCR; 5 were also specifically expressed in different stages of PD by WGCNA, but validation by qRT-PCR showed inconsistent results; the remaining 5 miRNAs did not exhibit significant differences by qRT-PCR. ConclusionsThis study revealed that the 7 serum exosomal miRNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-199a-3p, hsa-miR-195-5p, hsa-miR-28-5p, hsa-miR-22-5p and hsa-miR-151a-5p) we screened out may potentially be used as biomarkers for progression and early grading diagnosis of PD in the population.

scholarly journals Transcriptomic profiling of differentially expressed genes and related pathways in different brain regions of Parkinson’s disease

2019 ◽  
Author(s):  
Qinyu Ge ◽  
Erteng Jia ◽  
Min Pan ◽  
Zhiyu Liu ◽  
Ying Zhou ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Brain Regions ◽  
Therapeutic Strategies ◽  
Differentially Expressed ◽  
Control Group ◽  
Transcriptomic Data ◽  
Potential Use

Abstract BackgroundParkinson’s disease (PD) is the second most common neurodegenerative disease and many studies have researched its complex pathophysiological processes. However, it is unclear how PD affects the structure of transcripts in different brain regions and how changes in the transcriptomes in different brain regions affect the pathogenesis of PD.ResultsWe generated a PD mouse model by injecting with MPTP solution. RNA sequencing was performed in the cerebral cortex, hippocampus, striatum, and cerebellum regions of the PD mouse. Compared with the control group, these four brain regions showed significant transcriptomic alterations, with the most differentially expressed genes (DEGs) found in the striatum region. The main DEGs were Lrrk2, Mtor, Gxylt1, C920006o11Rik, Vdac1, Ano3, Drd4, and Ncan. DEGs were enriched using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis methods, which identified significant GO and molecular pathways. In addition, we used network biology methods to analyze protein–protein relationships, which can accelerate the identification of new PD drugs. The results showed that LRRK2, DRD2, IGF-1, GNAI1, GNAI3, PRKACA, PPP2R5C, and PIK3R1 played a major role in protein regulation.ConclusionsOur analysis showed that these DEGs and proteins play an important role in the occurrence and development of PD. Our study also highlighted the potential use of this transcriptomic data for therapeutic strategies and treatment of PD.

scholarly journals Immune System and Neuroinflammation in Idiopathic Parkinson’s Disease: Association Analysis of Genetic Variants and miRNAs Interactions

2021 ◽  
Vol 12 ◽  
Author(s):  
Claudia Strafella ◽  
Valerio Caputo ◽  
Andrea Termine ◽  
Francesca Assogna ◽  
Clelia Pellicano ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Immune Response ◽  
Parkinson's Disease ◽  
Target Genes ◽  
Brain Regions ◽  
Control Group ◽  
Idiopathic Parkinson’S Disease ◽  
Novel Treatments ◽  
Idiopathic Parkinson's Disease ◽  
Significant Expression

The present study investigated the association of SNPs involved in the regulation of immune response, cellular degenerative and neuroinflammatory pathways with the susceptibility and progression of idiopathic Parkinson’s Disease (PD). In particular, 342 PD patients were subjected to a genotyping analysis of a panel of 120 SNPs by Open Array Technology. As control group, 503 samples representative of the European general population were utilized. The genetic analysis identified 26 SNPs associated with PD susceptibility. Of them, 12 SNPs were described as significant expression Quantitative Loci (eQTL) variants in different brain regions associated with motor and non-motor PD phenomenology. Moreover, the study highlighted 11 novel susceptibility genes for PD, which may alter multiple signaling pathways critically involved in peripheral immune response, neuroinflammation, neurodegeneration and dopaminergic neurons wiring. The study of miRNA-target genes highlighted a possible role of miR-499a, miR-196a2, and miR-29a in the modulation of multiple neuroinflammatory and neurodegenerative mechanisms underlying PD physiopathology. The study described a network of interconnected genes (APOE, CLU, IL6, IL7R, IL12B, INPP5D, MAPK1, MEF2C, MIF, and TNFSF14), which may act as upstream regulators in the modulation of biological pathways relevant to PD. Intriguingly, IL6 stands out as a master gene regulator since it may indirectly regulate the network of interconnected genes. The study highlighted different genes and miRNAs interactions potentially involved in PD physiopathology, which are worth to be further explored to improve the knowledge of disease and the research of novel treatments strategies.

scholarly journals Identification of Potential Core Genes in Parkinson’s Disease Using Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wei Quan ◽  
Jia Li ◽  
Xiya Jin ◽  
Li Liu ◽  
Qinghui Zhang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Metabolic Pathways ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Potential Core ◽  
Core Genes

Purpose. This study aimed to explore new core genes related to the occurrence of Parkinson’s disease (PD) and core genes that can lead to the progression of PD. Methods. The expression profile data of GSE42966, which contained six substantia nigra tissues isolated from normal individuals and nine substantia nigra tissues isolated from patients with PD, were obtained from Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, followed by functional enrichment analysis and protein-protein interaction (PPI) network construction. We then identified 10 hub genes and analyzed their expression in different Braak stages. Results. A total of 773 DEGs were identified that were significantly enriched in metabolic pathways. Ten hub genes were identified through the PPI network, namely, GNG3, MAPK1, FPR1, ATP5B, GNG2, PRKACA, HRAS, HSPA8, PSAP, and GABBR2. The expression of HRAS was different in patients with PD with Braak stages 3 and 4. Conclusion. These 10 hub genes and the metabolic pathways they are enriched in may be involved in the pathogenesis of PD. HRAS may have potential value in predicting the progression of PD.

scholarly journals A metabolism-related 4-lncRNA prognostic signature and corresponding mechanisms in intrahepatic cholangiocarcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenbo Zou ◽  
Zizheng Wang ◽  
Fei Wang ◽  
Lincheng Li ◽  
Rong Liu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Clinical Data ◽  
Intrahepatic Cholangiocarcinoma ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Potential Mechanism ◽  
Prognostic Signature ◽  
Predictive Capability

Abstract Background Long non-coding RNA (lncRNA) plays a critical role in the malignant progression of intrahepatic cholangiocarcinoma (iCCA). This study aimed to establish a 4-lncRNA prognostic signature and explore corresponding potential mechanisms in patients with iCCA. Methods The original lncRNA-seq and clinical data were collected from the TCGA and GEO databases. Overlapping and differentially expressed lncRNAs (DE-lncRNAs) were further identified from transcriptome data. Univariate regression analysis was performed to screen survival-related DE-lncRNAs, which were further selected to develop an optimal signature to predict prognosis using multivariate regression analysis. The Kaplan-Meier survival curve visualized the discrimination of the signature on overall survival (OS). The area under the curve (AUC) and C-index were used to verify the predictive accuracy of the signature. Combined with clinical data, multivariate survival analysis was used to reveal the independent predictive capability of the signature. In addition, a prognostic nomogram was constructed. Finally, the common target genes of 4 lncRNAs were predicted by the co-expression method, and the corresponding functions were annotated by GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was also performed to explore the potential mechanism of the signature. Quantitative real-time PCR was used to evaluated the expression of 4 lncRNAs in an independent cohort. Results We identified and constructed a 4-lncRNA (AC138430.1, AGAP2-AS1, AP001783.1, and AP005233.2) prognostic signature using regression analysis, and it had the capability to independently predict prognosis. The AUCs were 0.952, 0.909, and 0.882 at 1, 2, and 3 years, respectively, and the C-index was 0.808, which showed good predictive capability. Subsequently, combined with clinical data, we constructed a nomogram with good clinical application. Finally, 252 target genes of all four lncRNAs were identified by the co-expression method, and functional enrichment analysis showed that the signature was strongly correlated with metabolism-related mechanisms in tumourigenesis. The same results were also validated via GSEA. Conclusion We demonstrated that a metabolism-related 4-lncRNA prognostic signature could be a novel biomarker and deeply explored the target genes and potential mechanism. This study will provide a promising therapeutic strategy for patients with intrahepatic cholangiocarcinoma.

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