Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Comprehensive identification of RNA transcripts and construction of RNA networks in chronic obstructive pulmonary disease

ABSTRACT: Here, we report a comprehensive analysis of dysregulated mRNAs, lncRNAs, miRNAs and circRNAs in peripheral blood of COPD patients with high-throughput RNA sequencing. We mapped about 50~80 million sequence reads per sample to the human genome. GSEA analysis showed that these dysregulated RNAs correlate with several critical biological processes such as RNA modification, and RNA metabolism. RT-qPCR (SYBR Green assays) with more clinical COPD samples were used for the validation of some dysregulated RNAs. We have also constructed the co-expression network between lncRNA and mRNA, and established the circRNA-miRNA-mRNA in CAC based on this data. This study provides valuable insights to understand the RNA involvement and regulation in COPD, assisting future COPD investigations.

ORGANISM(S): Homo sapiens

PROVIDER: GSE198740 | GEO | 2022/06/15

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Comprehensive identification of RNA transcripts and construction of RNA networks in coronary arterial calcification

Project description:Here, we report a comprehensive analysis of dysregulated mRNAs, lncRNAs, miRNAs and circRNAs in peripheral blood of CAC patients with high-throughput RNA sequencing. We mapped about 50 million sequence reads per sample to the human genome. GSEA analysis showed that these dysregulated RNAs correlate with several critical biological processes such as RNA modification, and RNA metabolism. RT-qPCR (SYBR Green assays) with more clinical CAC samples were used for the validation of some dysregulated RNAs. We have also constructed the co-expression network between lncRNA and mRNA, and established the circRNA-miRNA-mRNA in CAC based on this data. This study provides valuable insights to understand the RNA involvement and regulation in CAC, assisting future CAC investigations.

2022-07-01 | GSE194304 | GEO

Construction of a ceRNA network and screening of potential biomarkers and molecular targets in male smokers with chronic obstructive pulmonary disease

Project description:Background. Circular RNAs (circRNAs) play an important role in the occurrence and development of diseases. However, the role of circRNAs in male smokers with chronic obstructive pulmonary disease (COPD) remains unclear. Methods. Stable COPD patients and healthy controls were recruited. Peripheral blood mononuclear cells (PBMCs) were extracted. After high-throughput RNA sequencing (RNA-Seq) of PBMCs, a bioinformatics method was used to analyse differentially expressed (DE) circRNAs (DEcircRNAs) and mRNAs (DEmRNAs). Results. Total of 114 DEcircRNAs and 58 DEmRNAs were identified. Functional enrichment analysis showed that processes related to COPD include the regulation of interleukin (IL)-18, IL-5 and the NLRP3 inflammasome; differentiation of T helper type 1 (Th1), Th2, and Th17 cells, and the AMPK, Wnt, JAK-STAT, and PI3K-Akt signalling pathways. In the protein–protein interaction (PPI) network, the core genes were MYO16, MYL4, SCN4A, NRCAM, HMCN1, MYOM2, and IQSEC3. Small-molecule prediction results revealed potential drugs for the COPD treatment. Additionally, the circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory network was constructed. Conclusion. This study identified a set of dysregulated circRNAs and mRNAs and revealed potentially important genes, pathways, new small-molecule drugs and ceRNA regulatory networks in male smokers with COPD. These circRNAs might be prospective biomarkers or potential molecular targets of the ceRNA mechanism for COPD.

2024-06-09 | GSE268499 | GEO

Identification and Bioinformatic Analysis of CircRNAs in the Plasma of Patients with Very Severe Chronic Obstructive Pulmonary Disease

Project description:The differential expression of circular RNAs (circRNAs) in individuals with very severe chronic obstructive pulmonary disease (COPD) and healthy individuals was screened using microarray technology. The related functions and mechanisms were analyzed using bioinformatic methods to explore the potential of target circRNAs as biomarkers of COPD and provide insights for future pathogenesis.

2022-12-30 | GSE221812 | GEO

Lung proteomic biomarkers associated with chronic obstructive pulmonary disease

Project description:Identifying protein biomarkers for chronic obstructive pulmonary disease (COPD) has been challenging. Most previous studies have utilized individual proteins or pre-selected protein panels measured in blood samples. To identify COPD protein biomarkers by applying comprehensive mass spectrometry proteomics in lung tissue samples. We utilized mass spectrometry proteomic approaches to identify protein biomarkers from 152 lung tissue samples representing COPD cases and controls.

2022-01-07 | PXD024124 | Pride

Multi-Omic Molecular Profiling of Lung Cancer Risk in Chronic Obstructive Pulmonary Disease

Project description:Chronic obstructive pulmonary disease (COPD) is a known risk factor for developing lung cancer suggesting that the COPD stroma contains factors supporting tumorigenesis. Since cancer initiation is complex we used a multi-omic approach to identify gene expression patterns that distinguish COPD stroma in patients with or without lung cancer. We obtained lung tissue from patients with COPD and lung cancer (tumor and adjacent non-malignant tissue) and those with COPD without lung cancer for proteomic and mRNA (cytoplasmic and polyribosomal) profiling. We used the joint and individual variation explained (JIVE) method to integrate and analysis across the three datasets. JIVE identified eight latent patterns that robustly distinguished and separated the three groups of tissue samples. Predictive variables that associated with the tumor, compared to adjacent stroma, were mainly represented in the transcriptomic data, whereas, predictive variables associated with adjacent tissue compared to controls was represented at the translatomic level. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis revealed extracellular matrix (ECM) and PI3K-Akt signaling pathways as important signals in the pre-malignant stroma. COPD stroma adjacent to lung cancer is unique and differs from non-malignant COPD tissue and is distinguished by the extracellular matrix and PI3K-Akt signaling pathways.

2018-10-05 | GSE106899 | GEO

Integrative DNA, RNA and protein evidence connects TREML4 to coronary artery calcification

Project description:Peripheral blood RNA-Seq from human coronary artery calcification cases and controls; Coronary artery calcification (CAC) is a heritable and definitive morphologic marker of atherosclerosis that strongly predicts risk for future cardiovascular events. To search for genes involved in CAC, we used an integrative transcriptomic, genomic, and protein expression strategy using next-generation DNA sequencing in the discovery phase with follow-up studies using traditional molecular biology and histopathology techniques. Eight cases and eight controls (matched for gender, age and ancestry); RNA sequencing of peripheral blood from a discovery set of eight CAC cases and eight matched controls was used to identify dysregulated genes, which were validated using the NanoString® and Affymetrix GeneChip® Human Exon ST Array platforms. The median CAC scores for cases in the screening and validation sets were 1531.5 and 668.5, respectively, while all controls had a score of zero.

2014-06-10 | E-GEOD-58150 | biostudies-arrayexpress

Characterization of IL-6R-expressing monocytes in the lung of patients with chronic obstructive pulmonary disease [THP1]

Project description:Background: Monocytes play a crucial role in innate immune responses for host defense, yet their involvement in chronic obstructive pulmonary disease (COPD) remains poorly understood. We previously identified a subset of monocytes in COPD lung tissues characterized by high interleukin-6 receptor (IL-6R) expression. This study aimed to characterize the phenotypes of IL-6Rhi monocytes in the lung of COPD patients. Methods: Using flow cytometry, we assessed the abundance of pulmonary CD14+IL-6Rhi cells in never smokers (CNS), control ex-smokers (CES) and COPD patients. IL-6 expression in CD14+ monocytes from peripheral blood of patients with COPD was also examined. CD45+CD206–CD14+IL-6Rhi and CD45+CD206–CD14+IL-6R– cells were isolated from COPD lung tissues for transcriptome analysis. A monocyte line THP1 cell with constitutive IL-6R expression was stimulated with recombinant IL-6, followed by RNA sequencing to evaluate IL-6 responsiveness of IL-6R+ monocytes. Results: The number of pulmonary CD14+IL-6Rhi monocytes was elevated in COPD patients compared to CNS, while CD14+ monocytes in the peripheral blood of COPD patients did not express IL-6R. Upregulated mRNA expression in CD14+IL-6Rhi monocytes was associated with chemotaxis, monocyte differentiation, fatty acid metabolism and integrin-mediated signaling pathway. Stimulation of THP1 cells with recombinant IL-6 induced gene expression changes linked to chemotaxis and organism development. Conclusion: In patients with COPD, CD14+IL-6Rhi monocytes increase in lung tissues compared to CNS and exhibit a different transcriptome profile from CD14+IL-6R– monocytes.

2024-08-21 | GSE265855 | GEO

Single cell transcriptomics in blood of patients with chronic obstructive pulmonary disease

Project description:Background Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Single-cell RNA sequencing (scRNA-seq) provides gene expression profiles at the single-cell level. Hence, we evaluated gene expression in the peripheral blood of patients with COPD. Methods Peripheral blood samples from seven healthy controls and eight patients with COPD were obtained in this study. The 10X Genomics Chromium Instrument and cDNA synthesis kit was utilized to generate a barcoded cDNA library for single cell RNA-sequencing. We compared the scRNA-seq data between the COPD and control groups using computational analysis. Functional analyses were performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Results scRNA-seq was used to analyze the transcriptome of peripheral blood mononuclear cells from seven normal controls and eight patients with COPD. We found increased numbers of monocyte macrophages in the COPD group compared to those in the normal control group. Among the differentially expressed genes (DEGs) in monocyte-macrophages, we identified five upregulated genes (HLA-DRB5, ITGB2, EGR1, CXCL8, and CCL4) and seven downregulated genes (FOLR3, RPS4Yq, CD52, LY6E, HLA-DQB1, G0S2, and CCL3L1) in the COPD group compared to the normal control group. Conclusions Using scRNA-seq, we found differences in cell type distribution, especially in monocyte macrophages. Several upregulated and downregulated genes were found in the monocyte-macrophages of the COPD groups.

2024-10-01 | GSE249584 | GEO

Plasma proteomics enable differentiation of lung adenocarcinoma from chronic obstructive pulmonary disease (COPD)

Project description:Background: Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD, thus the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Methods: Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Results: Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, Random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. Conclusion: We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.

2022-10-17 | PXD035120 | Pride

Pulmonary microRNA changes alter angiogenesis in chronic obstructive pulmonary disease and lung cancer

Project description:This experiment was carried out to see if there were any miRNA expression differences in pulmonary endothelial cells between patients with and without COPD. COPD is an inflammatory condition and although much work has previously been performed to investigate the inflammatory cells in COPD there has not been as much research looking at the endothelium through which inflammatory cells must pass through to reach the lung tissue. In this experiment pulmonary endothelial cells were extracted from whole lung tissue removed at the time of cardiothoracic surgery. This was performed for patients with and without COPD. RNA was extracted using the Qiagen microRNeasy kits prior to transferring to the University of Birmingham Biosciences department who performed RNA labelling and ran the microarrays. Once the microarrays were performed quality was checked using ArrayQualityMetrics and the COPD group was compared to the non-COPD group using SAM. The experiment was then repeated using another patient group. MiRNAs of interest were validated with qPCR initially before moving on to functional work.

2021-08-01 | E-MTAB-10311 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data