Weighted gene co‑expression network analysis identifies key genes from extracellular vesicles as potential prognostic biomarkers for congenital pulmonary stenosis

Huang, Zirui; Li, Xiaohong; Qu, Min; Chen, Jing; Tian, Miao; Han, Fengzhen; Ou, Yanqiu; Liu, Xiaoqing; Zhou, Chunxiao; Yuan, Hongling; Zhuang, Jian; Chen, Jimei

doi:10.3892/mmr.2020.11332

Cited by 7 publications

(2 citation statements)

References 31 publications

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“…First, samples of synovium data set GSE55235 were clustered to detect and eliminate outliers using the flashClust function. 20 The independence and average connectivity degrees of the coexpression networks were mainly determined by a power value. 21 Then, suitable soft thresholding power value was selected using the pickSoftThreshold function of the WGCNA algorithm if the independence degree was >0.85.…”

Section: Methodsmentioning

confidence: 99%

Apolipoprotein D as a Potential Biomarker and Construction of a Transcriptional Regulatory-Immune Network Associated with Osteoarthritis by Weighted Gene Coexpression Network Analysis

Qin

Zhou

et al. 2021

CARTILAGE

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Objective Synovial inflammation influences the progression of osteoarthritis (OA). Herein, we aimed to identify potential biomarkers and analyze transcriptional regulatory-immune mechanism of synovitis in OA using weighted gene coexpression network analysis (WGCNA). Design A data set of OA synovium samples (GSE55235) was analyzed based on WGCNA. The most significant module with OA was identified and function annotation of the module was performed, following which the hub genes of the module were identified using Pearson correlation and a protein-protein interaction network was constructed. A transcriptional regulatory network of hub genes was constructed using the TRRUST database. The immune cell infiltration of OA samples was evaluated using the single-sample Gene Set Enrichment Analysis (ssGSEA) method. The hub genes coexpressed in multiple tissues were then screened out using data sets of synovium, cartilage, chondrocyte, subchondral bone, and synovial fluid samples. Finally, transcriptional factors and coexpressed hub genes were validated via experiments. Results The turquoise module of GSE55235 was identified via WGCNA. Functional annotation analysis showed that “mineral absorption” and “FoxO signaling pathway” were mostly enriched in the module. JUN, EGR1, FOSB, and KLF4 acted as central nodes in protein-protein interaction network and transcription factors to connect several target genes. “Activated B cell,” “activated CD4T cell,” “eosinophil,” “neutrophil,” and “type 17 T helper cell” showed high immune infiltration, while FOSB, KLF6, and MYBL2 showed significant negative correlation with type 17 T helper cell. Conclusions Our results suggest that the expression level of apolipoprotein D (APOD) was correlated with OA. Furthermore, transcriptional regulatory-immune network was constructed, which may contribute to OA therapy.

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Section: Methodsmentioning

confidence: 99%

Apolipoprotein D as a Potential Biomarker and Construction of a Transcriptional Regulatory-Immune Network Associated with Osteoarthritis by Weighted Gene Coexpression Network Analysis

Qin

Zhou

et al. 2021

CARTILAGE

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“…Both studies isolated EVs from maternal blood before profiling RNA expression. Jin et al [135] identified miRNAs that were differentially expressed in pregnant women carrying a child with ventricular septal defects compared to the control group, whilst Huang et al [136] identified differences in long non-coding RNA (lncRNA) expression in pregnant women carrying a child with pulmonary stenosis. In another study, Gu et al [137] identified differentially expressed lncRNA in maternal blood from a mixed cohort of CHD cases (including both ventricular and atrial septal defects as well as Tetralogy of Fallot) versus healthy controls.…”

Section: Evidence For Evs From the Foetal Nervous And Cardiovascular ...mentioning

confidence: 99%

Are there foetal extracellular vesicles in maternal blood? Prospects for diagnostic biomarker discovery

et al. 2022

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Prenatal diagnosis of congenital disease improves clinical outcomes; however, as many as 50% of congenital heart disease cases are missed by current ultrasound screening methods. This indicates a need for improved screening technology. Extracellular vesicles (EVs) have attracted enormous interest in recent years for their potential in diagnostics. EVs mediate endocrine signalling in health and disease and are known to regulate aspects of embryonic development. Here, we critically evaluate recent evidence suggesting that EVs released from the foetus are able to cross the placenta and enter the maternal circulation. Furthermore, EVs from the mother appear to be transported in the reverse direction, whilst the placenta itself acts as a source of EVs. Experimental work utilising rodent models employing either transgenically encoded reporters or application of fluorescent tracking dyes provide convincing evidence of foetal-maternal crosstalk. This is supported by clinical data demonstrating expression of placental-origin EVs in maternal blood, as well as limited evidence for the presence of foetal-origin EVs. Together, this work raises the possibility that foetal EVs present in maternal blood could be used for the diagnosis of congenital disease. We discuss the challenges faced by researchers in translating these basic science findings into a clinical non-invasive prenatal test.

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Extracellular vesicles, RNA sequencing, and bioinformatic analyses: Challenges, solutions, and recommendations

Miceli,

Chen,

Nose

et al. 2024

J of Extracellular Vesicle

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Extracellular vesicles (EVs) are heterogeneous entities secreted by cells into their microenvironment and systemic circulation. Circulating EVs carry functional small RNAs and other molecular footprints from their cell of origin, and thus have evident applications in liquid biopsy, therapeutics, and intercellular communication. Yet, the complete transcriptomic landscape of EVs is poorly characterized due to critical limitations including variable protocols used for EV‐RNA extraction, quality control, cDNA library preparation, sequencing technologies, and bioinformatic analyses. Consequently, there is a gap in knowledge and the need for a standardized approach in delineating EV‐RNAs. Here, we address these gaps by describing the following points by (1) focusing on the large canopy of the EVs and particles (EVPs), which includes, but not limited to – exosomes and other large and small EVs, lipoproteins, exomeres/supermeres, mitochondrial‐derived vesicles, RNA binding proteins, and cell‐free DNA/RNA/proteins; (2) examining the potential functional roles and biogenesis of EVPs; (3) discussing various transcriptomic methods and technologies used in uncovering the cargoes of EVPs; (4) presenting a comprehensive list of RNA subtypes reported in EVPs; (5) describing different EV‐RNA databases and resources specific to EV‐RNA species; (6) reviewing established bioinformatics pipelines and novel strategies for reproducible EV transcriptomics analyses; (7) emphasizing the significant need for a gold standard approach in identifying EV‐RNAs across studies; (8) and finally, we highlight current challenges, discuss possible solutions, and present recommendations for robust and reproducible analyses of EVP‐associated small RNAs. Overall, we seek to provide clarity on the transcriptomics landscape, sequencing technologies, and bioinformatic analyses of EVP‐RNAs. Detailed portrayal of the current state of EVP transcriptomics will lead to a better understanding of how the RNA cargo of EVPs can be used in modern and targeted diagnostics and therapeutics. For the inclusion of different particles discussed in this article, we use the terms large/small EVs, non‐vesicular extracellular particles (NVEPs), EPs and EVPs as defined in MISEV guidelines by the International Society of Extracellular Vesicles (ISEV).

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Weighted gene co‑expression network analysis identifies key genes from extracellular vesicles as potential prognostic biomarkers for congenital pulmonary stenosis

Cited by 7 publications

References 31 publications

Apolipoprotein D as a Potential Biomarker and Construction of a Transcriptional Regulatory-Immune Network Associated with Osteoarthritis by Weighted Gene Coexpression Network Analysis

Apolipoprotein D as a Potential Biomarker and Construction of a Transcriptional Regulatory-Immune Network Associated with Osteoarthritis by Weighted Gene Coexpression Network Analysis

Are there foetal extracellular vesicles in maternal blood? Prospects for diagnostic biomarker discovery

Extracellular vesicles, RNA sequencing, and bioinformatic analyses: Challenges, solutions, and recommendations

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