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 Correcting differential gene expression analysis for cyto-architectural alterations in substantia nigra of Parkinson's disease patients reveals known and potential novel disease-associated genes and pathways

2021 ◽  
Author(s):  
Federico Ferraro ◽  
Christina Fevga ◽  
Vincenzo Bonifati ◽  
Wim Mandemakers ◽  
Ahmed Mahfouz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Substantia Nigra Pars Compacta ◽  
Ammonium Transport ◽  
Protein Interaction Data

Several studies have analyzed gene expression profiles in the substantia nigra to better understand the pathological mechanisms causing Parkinson's disease (PD). However, the concordance between the identified gene signatures in these individual studies was generally low. This might be caused by a change in cell type composition as loss of dopaminergic neurons in the substantia nigra pars compacta is a hallmark of PD. Through an extensive meta-analysis of nine previously published microarray studies, we demonstrated that a big proportion of the detected differentially expressed genes was indeed caused by cyto-architectural alterations due to the heterogeneity in the neurodegenerative stage and/or technical artifacts. After correcting for cell composition, we identified a common signature that deregulated the previously unreported ammonium transport, as well as known biological processes including bioenergetic pathways, response to proteotoxic stress, and immune response. By integrating with protein-interaction data, we shortlisted a set of key genes, such as LRRK2, PINK1, and PRKN known to be related to PD; others with compelling evidence for their role in neurodegeneration, such as GSK3β, WWOX, and VPC; as well as novel potential players in the PD pathogenesis, including NTRK1, TRIM25, ELAVL1. Together, these data showed the importance of accounting for cyto-architecture in these analyses and highlight the contribution of multiple cell types and novel processes to PD pathology providing potential new targets for drug development.

scholarly journals Correcting Differential Gene Expression Analysis for Cyto—Architectural Alterations in Substantia Nigra of Parkinson’s Disease Patients Reveals Known and Potential Novel Disease—Associated Genes and Pathways

Cells ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 198
Author(s):  
Federico Ferraro ◽  
Christina Fevga ◽  
Vincenzo Bonifati ◽  
Wim Mandemakers ◽  
Ahmed Mahfouz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Substantia Nigra Pars Compacta ◽  
Ammonium Transport ◽  
Protein Interaction Data

Several studies have analyzed gene expression profiles in the substantia nigra to better understand the pathological mechanisms causing Parkinson’s disease (PD). However, the concordance between the identified gene signatures in these individual studies was generally low. This might have been caused by a change in cell type composition as loss of dopaminergic neurons in the substantia nigra pars compacta is a hallmark of PD. Through an extensive meta-analysis of nine previously published microarray studies, we demonstrated that a big proportion of the detected differentially expressed genes was indeed caused by cyto-architectural alterations due to the heterogeneity in the neurodegenerative stage and/or technical artefacts. After correcting for cell composition, we identified a common signature that deregulated the previously unreported ammonium transport, as well as known biological processes such as bioenergetic pathways, response to proteotoxic stress, and immune response. By integrating with protein interaction data, we shortlisted a set of key genes, such as LRRK2, PINK1, PRKN, and FBXO7, known to be related to PD, others with compelling evidence for their role in neurodegeneration, such as GSK3β, WWOX, and VPC, and novel potential players in the PD pathogenesis. Together, these data show the importance of accounting for cyto-architecture in these analyses and highlight the contribution of multiple cell types and novel processes to PD pathology, providing potential new targets for drug development.

scholarly journals Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3484
Author(s):  
Jisun Lim ◽  
Yeon Bi Han ◽  
Soo Young Park ◽  
Soyeon Ahn ◽  
Hyojin Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Killer Cell ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Stepwise Change

Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.

scholarly journals Understanding the Modus Operandi of MicroRNA Regulatory Clusters

Cells ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1103 ◽  
Author(s):  
Arthur C. Oliveira ◽  
Luiz A. Bovolenta ◽  
Lucas Alves ◽  
Lucas Figueiredo ◽  
Amanda O. Ribeiro ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Modus Operandi ◽  
Wide Range

MicroRNAs (miRNAs) are non-coding RNAs that regulate a wide range of biological pathways by post-transcriptionally modulating gene expression levels. Given that even a single miRNA may simultaneously control several genes enrolled in multiple biological functions, one would expect that these tiny RNAs have the ability to properly sort among distinctive cellular processes to drive protein production. To test this hypothesis, we scrutinized previously published microarray datasets and clustered protein-coding gene expression profiles according to the intensity of fold-change levels caused by the exogenous transfection of 10 miRNAs (miR-1, miR-7, miR-9, miR-124, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a) in a human cell line. Through an in silico functional enrichment analysis, we discovered non-randomic regulatory patterns, proper of each cluster identified. We demonstrated that miRNAs are capable of equivalently modulate the expression signatures of target genes in regulatory clusters according to the biological function they are assigned to. Moreover, target prediction analysis applied to ten vertebrate species, suggest that such miRNA regulatory modus operandi is evolutionarily conserved within vertebrates. Overall, we discovered a complex regulatory cluster-module strategy driven by miRNAs, which relies on the controlled intensity of the repression over distinct targets under specific biological contexts. Our discovery helps to clarify the mechanisms underlying the functional activity of miRNAs and makes it easier to take the fastest and most accurate path in the search for the functions of miRNAs in any distinct biological process of interest.

scholarly journals Monozygotic Twins Discordant for Immunoglobulin A Nephropathy Display Differences in DNA Methylation and Gene Expression

2020 ◽  
pp. 1-10
Author(s):  
Min Wei ◽  
Sijun Meng ◽  
Sufang Shi ◽  
Lijun Liu ◽  
Xujie Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Expression Profiles ◽  
Immunoglobulin A ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Genome Wide ◽  
Mz Twins

<b><i>Introduction:</i></b> Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis. It involves both genetic and environmental factors, among which DNA methylation, the most studied epigenetic modification, was shown to play a role. Here, we assessed genome-wide DNA methylation and gene expression profiles in 2 pairs of IgAN-discordant monozygotic (MZ) twins, in order to characterize methylation changes and their potential influences on gene expression in IgAN. <b><i>Methods:</i></b> Genome-wide DNA methylation and gene expression profiles were evaluated in peripheral blood mononuclear cells obtained from 2 IgAN-discordant MZ twins. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were detected, and an integrated analysis was performed. Finally, functional enrichment analysis was done for DMR-associated genes and DEGs. <b><i>Results:</i></b> Totally 521 DMRs were detected for 2 IgAN-discordant MZ twins. Among them, 9 DMRs were found to be mapped to genes that differentially expressed in 2 MZ twins, indicating the potential regulatory mechanisms of expression for these 9 genes (<i>MNDA</i>, <i>DYSF</i>, <i>IL1R2</i>, <i>TLR6</i>, <i>TREML2</i>, <i>TREM1</i>, <i>IL32</i>, <i>S1PR5</i>, and <i>ADGRE3</i>) in IgAN. Biological process analysis of them showed that they were mostly involved in the immune system process. Functional enrichment analysis of DEGs and DMR-associated genes both identified multiple pathways relevant to inflammatory and immune responses. And DMR-associated genes were significantly enriched in terms related to T-cell function. <b><i>Conclusions:</i></b> Our findings indicate that changes in DNA methylation patterns were involved in the pathogenesis of IgAN. Nine target genes detected in our study may provide new ideas for the exploration of molecular mechanisms of IgAN.

scholarly journals Identification of Key Candidate Biomarkers and Pathways in Atherosclerosis

2020 ◽  
Author(s):  
Zhijun Meng ◽  
Jia Gao ◽  
Hongping Liang ◽  
Caihong Liu ◽  
Jianli Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Early Stage ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Effective Prevention ◽  
Diagnostic Indicator

Abstract Background Atherosclerosis is the leading cause of cardiovascular disease worldwide for which lacks effective prevention and therapeutic strategy. Therefore, clinical indicators for early diagnosis and screening are in great need. The present study aimed to elucidate the key genetic signatures and pathways identifying the key candidate biomarker in atherosclerosis by integrative bioinformatics analysis combining with experimental assay. Methods The gene expression profiles (GSE30169, GSE6584) were achieved from the Gene Expression Omnibus database. Functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to examine the biological functions of identified differentially expressed genes (DEGs). A protein-protein interaction (PPI) network was mapped using Cytoscape software. Results 91 DEGs were identified, including 68 up-regulated genes and 23 down-regulated genes. Functional enrichment analysis indicated that DEGs genes were significantly enriched in ferroptosis, TNF signaling pathway, IL-17 signaling pathway. 12 nodes with the highest degrees were selected as hub genes. CCL2, CXCL1, IL6, and DUSP1 can serve as a sensitive diagnostic indicator for the early stage of atherosclerosis; CEBPB and HMOX1 can serve as a diagnostic indicator for diabetic atherosclerosis; TRIB3 is a sensitive marker indicating atherosclerosis risks in diabetic women group.Conclusions In conclusion, we have identified key candidate genes that indicate the diagnosis of patients with atherosclerosis, and these genes may serve as potential therapeutic or drug development targets for atherosclerosis.

Identify Key Genes by Weighted Gene Co-Expression Network Analysis for Lung Adenocarcinoma

Nano LIFE ◽  
2019 ◽  
Vol 09 (01n02) ◽  
pp. 1940002
Author(s):  
Jichen Xu ◽  
Xianchun Zong ◽  
Qianshu Ren ◽  
Hongyu Wang ◽  
Lijuan Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Lung Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Oocyte Meiosis ◽  
Key Genes

The aim of this paper is to identify key genes in lung adenocarcinoma (LUAD) through weighted gene co-expression network analysis (WGCNA), and to further understand the molecular mechanism of LUAD. 107 gene expression profiles were downloaded from GSE10072 in the GEO database. We performed rigorous processing of the initial gene expression profile data. Subsequently, we used WGCNA to identify disease-driven modules and enforced functional enrichment analysis. The key genes were defined as the most connected genes in the driver module and were validated using the GSE75037 and TCGA database. GSE10072 removed 41 unpaired lung samples and 4 outliers. By analyzing the 62 samples using WGCNA, we obtained 26 modules and identified the brown and magenta modules as the driving modules for the LUAD. We found that the “Cell cycle”, “Oocyte meiosis” and “Progesterone-mediated oocyte maturation” pathways may be related to the occurrence of LUAD. GSE75037 removed 8 outlier and obtained 2909 differentially expressed genes (DEGs), 26 genes (9 genes in the brown module, 17 genes in the magenta module) overlap with key genes in the driver module. The results of the survival analysis suggest that 19 genes were significantly correlated with the patient’s survival time, including KPNA2, FEN1, RRM2, TOP2A, CENPF, MCM4, BIRC5, MELK, MAD2L1, CCNB1, CCNA2, KIF11, CDKN3, NUSAP1, CEP55, AURKA, NEK2, KIF14 and CDCA8, which may be potential biomarkers or therapeutic targets for LUAD. In this study, we provide a theoretical basis for further understanding the biological mechanism of LUAD through bioinformatics analysis of LUAD.

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