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pmid:32382555

Bioinformatics Analysis of the Molecular Mechanism of Late-Stage Heterotopic Ossification.

Qiang Zhang · Yan Zhang · Meijun Yan · Kai Zhu · Dong Zhou · Jun Tan

BioMed research international · 2020 doi:10.1155/2020/5097823

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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title
Bioinformatics Analysis of the Molecular Mechanism of Late-Stage Heterotopic Ossification.
doi
10.1155/2020/5097823
pmid
32382555
authors array · 6 items
[0]
Qiang Zhang
[1]
Yan Zhang
[2]
Meijun Yan
[3]
Kai Zhu
[4]
Dong Zhou
[5]
Jun Tan
journal
BioMed research international
year
2020
abstract
BACKGROUND: Heterotopic ossification (HO) is a common disease happened in soft tissues after injury. The present study utilized the bioinformatics method to analyze the HO samples in a mouse burn/tenotomy-induced HO model to identify the possible key points and treatment targets. METHODS: The transcriptome profiles of GSE126118 were obtained from the Gene Expression Omnibus (GEO) database. The study was based on a mouse burn/tenotomy-induced HO model, and 2 tenotomy samples and 3 uninjured contralateral hindlimb tendon samples were collected at 3 weeks after injury for further analysis. The transcripts per million approach was performed for background correction and normalization; then, the differentially expressed genes (DEGs) were detected using the limma R package with the settings p < 0.01 and ∣log2FC∣ > 2.0. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and the protein-protein interaction (PPI) network analysis were performed with the detected DEGs. RESULTS: A total of 74 DEGs were upregulated, and 159 DEGs were downregulated between the tenotomy and uninjured tendon group. Pathway and process enrichment analyses demonstrated that the upregulated DEGs were mainly associated with terms related to ECM remodeling, ossification, angiogenesis, inflammation, etc., and the downregulated DEGs were mainly associated with oxidative phosphorylation, metabolic process, etc. CONCLUSION: The results of GO, KEGG, and PPI network analyses suggested that the ECM remodeling, ossification, angiogenesis, and inflammation processes were markedly upregulated in the tenotomy site. And the oxidative phosphorylation and metabolic processes were markedly downregulated. These findings provide valuable clues for highlighting the characteristics of late-stage HO and investigating possible treatments.
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The transcripts per million (TPM) approach was performed for background correction and normalization of the raw data of the dataset; then, the differentially expressed genes (DEGs) were detected using the limma R package. The DGEs were defined with the settings p < 0.01 and ∣log2FC∣ > 2.0 based on Benjamini and Hochberg (BH) procedure.
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sections[4] "2.2. Data Preprocessing and Differential Expression Analysis" paragraph 2
quote
The transcripts per million (TPM) approach was performed for background correction and normalization of the raw data of the dataset; then, the differentially expressed genes (DEGs) were detected using the limma R package. The DGEs were defined with the settings p < 0.01 and ∣log2FC∣ > 2.0 based on Benjamini and Hochberg (BH) procedure.
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The transcripts per million (TPM) approach was performed for background correction and normalization of the raw data of the dataset; then, the differentially expressed genes (DEGs) were detected using the limma R package. The DGEs were defined with the settings p < 0.01 and ∣log2FC∣ > 2.0 based on Benjamini and Hochberg (BH) procedure.
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Complete file
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The present study utilized the bioinformatics method to analyze the HO samples in a mouse burn/tenotomy-induced HO model to identify the possible key points and treatment targets.\nMETHODS: The transcriptome profiles of GSE126118 were obtained from the Gene Expression Omnibus (GEO) database. The study was based on a mouse burn/tenotomy-induced HO model, and 2 tenotomy samples and 3 uninjured contralateral hindlimb tendon samples were collected at 3 weeks after injury for further analysis. The transcripts per million approach was performed for background correction and normalization; then, the differentially expressed genes (DEGs) were detected using the limma R package with the settings p < 0.01 and ∣log2FC∣ > 2.0. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and the protein-protein interaction (PPI) network analysis were performed with the detected DEGs.\nRESULTS: A total of 74 DEGs were upregulated, and 159 DEGs were downregulated between the tenotomy and uninjured tendon group. Pathway and process enrichment analyses demonstrated that the upregulated DEGs were mainly associated with terms related to ECM remodeling, ossification, angiogenesis, inflammation, etc., and the downregulated DEGs were mainly associated with oxidative phosphorylation, metabolic process, etc.\nCONCLUSION: The results of GO, KEGG, and PPI network analyses suggested that the ECM remodeling, ossification, angiogenesis, and inflammation processes were markedly upregulated in the tenotomy site. And the oxidative phosphorylation and metabolic processes were markedly downregulated. 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