Mining the key genes for ventilator-induced lung injury using co-expression network analysis

Zhao, Li; Xiao, Yajun; Xu, Li; Wang, Qingxiu

doi:10.1042/bsr20203235

Cited by 3 publications

(3 citation statements)

References 55 publications

(51 reference statements)

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“…The results showed that the modules were worth our doing further analyses and research. [ 29 ]. Hierarchical clustering and heatmap analysis were performed on each module.…”

Section: Resultsmentioning

confidence: 99%

Changes Observed in Potential Key Candidate Genes of Peripheral Immunity Induced by Tai Chi among Patients with Parkinson’s Disease

Yang

Dong²,

Yang³

et al. 2022

Genes

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Parkinson’s disease (PD) is a common progressive neurodegenerative disease characterized by motor dysfunction. Although the inhibition of inflammation by Tai Chi has been demonstrated to involve a peripheral cytokine response and may play an important role in improving the motor function of PD patients, the related specific molecular mechanisms of the peripheral immune response to Tai Chi are not fully understood. The microarray dataset ‘GSE124676’ for the peripheral immune response to Tai Chi of PD patients was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened and analyzed using weighted gene co-expression network analysis (WGCNA). A total of 136 DEGs were found in the PD patients after Tai Chi, suggesting an effect of Tai Chi on the peripheral immunity of PD patients. The DEGs are mainly involved in neutrophil activation, T-cell activation, and NOD-like receptor and IL-17 signaling pathways. Furthermore, six key candidate genes (FOS, FOSB, JUNB, ZFP36, CAMP and LCN2) that are involved in peripheral inflammation and the inhibition of inflammation induced by Tai Chi were observed. The results in the present study could be conducive to comprehensively understanding the molecular mechanism involved in the effect of Tai Chi on peripheral inflammation in PD patients and providing novel targets for future advanced research.

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“…The results showed that the modules were worth our doing further analyses and research. [ 29 ]. Hierarchical clustering and heatmap analysis were performed on each module.…”

Section: Resultsmentioning

confidence: 99%

Changes Observed in Potential Key Candidate Genes of Peripheral Immunity Induced by Tai Chi among Patients with Parkinson’s Disease

Yang

Dong²,

Yang³

et al. 2022

Genes

View full text Add to dashboard Cite

show abstract

“…The threshold of the fitting index was set to 0.85 (R 2 >0.85) to fit with the scale-free network. When the fitting index reached 0.85, the β value (soft threshold) that maximized the average connectivity was selected to perform a power-law operation to convert the correlation matrix into an adjacency matrix (a i,j , a i,j =|S i,j | β ) [ 26 ].…”

Section: Methodsmentioning

confidence: 99%

Exploring autophagy related prognostic genes of Alzheimer's disease based on pathway crosstalk analysis

Qian

Kong

Wang

2022

Bosn J of Basic Med Sci

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Recent studies have shown that different signaling pathways are involved in the pathogenesis of Alzheimer's disease (AD), with complex molecular connections existing between these pathways. Autophagy is crucial for the degradation and production of pathogenic proteins in AD, and it shows link with other AD-related pathways. However, current methods for identifying potential therapeutic targets for AD are primarily based on single-gene analysis or a single signal pathway, both of which are somewhat limited. Finding other methods is necessary for providing novel underlying AD therapeutic targets. Therefore, given the central role of autophagy in AD and its interplay with its pathways, we aimed to identify prognostic genes related to autophagy within and between these pathways based on pathway crosstalk analysis. The method of pathway analysis based on global influence (PAGI) was applied to find the feature mRNAs involved in the crosstalk between autophagy and other AD-related pathways. Subsequently, the weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression module of feature mRNAs and differential lncRNAs. Finally, based on 2 autophagy-related crosstalk genes (CD40 and SMAD7), we constructed a prognosis model by multivariate Cox regression, which could predict the overall survival of AD patients with medium-to-high accuracy. In conclusion, we provided an effective method for extracting autophagy-related significant genes based on pathway crosstalk in AD. We found the biomarkers valuable to the AD prognosis, which may also play an essential role in the development and treatment of AD.

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“…To fit with the scale-free network, the threshold of the fitting index was set to 0.85 ( 2 >0.85). When the fitting index reached 0.85, the β value (soft threshold) that maximized the average connectivity was selected to perform a power-law operation to convert the correlation matrix into an adjacency matrix ( , , , = | , | β ) [23]. Then, the pickSoftThreshold function was used to calculate the corresponding 2 and average connectivity for different β values (the β values were set between 1 and 20).…”

Section: Construction Of Co-expression Gene Modules Based On Wgcna Analysismentioning

confidence: 99%

Exploring Biomarkers Related to Autophagy in Alzheimer's Disease Based on Pathway Crosstalk Analysis

Qian

Kong

Wang

2021

Preprint

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The pathological mechanism of Alzheimer's disease (AD) involves multiple pathways, and the crosstalk between autophagy and other pathways plays an increasingly prominent role in AD. However, current methods are primarily based on single-gene analysis or a single signal pathway to find therapeutic targets for AD, which are somewhat limited. The aim of our study is to identify autophagy-related biomarkers in AD based on the crosstalk between autophagy and other pathways. The pathway analysis method (PAGI) was applied to find the feature mRNAs involved in the crosstalk between autophagy and many other AD-related pathways. Then, the weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression module of feature mRNAs and differential lncRNAs. Finally, clinical information was used to screen the biomarkers related to the prognosis of AD in the co-expressed gene modules. The experiment finally identified 8 mRNAs and 2 lncRNAs (TLN1, ARRB1, FZD4, AKT1, JMJD7-PLA2G4B, STAT5A, SMAD7, ZNF274; AC113349.1, AC015878.2) as biomarkers of AD, and they all interact directly or indirectly with autophagy. In summary, we provide an effective method for extracting autophagy-related biomarkers based on pathway crosstalk in AD. This method enriches the therapeutic targets of AD and provides new insights into the molecular mechanism of autophagy in AD.

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Mining the key genes for ventilator-induced lung injury using co-expression network analysis

Cited by 3 publications

References 55 publications

Changes Observed in Potential Key Candidate Genes of Peripheral Immunity Induced by Tai Chi among Patients with Parkinson’s Disease

Changes Observed in Potential Key Candidate Genes of Peripheral Immunity Induced by Tai Chi among Patients with Parkinson’s Disease

Exploring autophagy related prognostic genes of Alzheimer's disease based on pathway crosstalk analysis

Exploring Biomarkers Related to Autophagy in Alzheimer's Disease Based on Pathway Crosstalk Analysis

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