Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms

Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. We utiliz...

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Published inScientific reports Vol. 15; no. 1; pp. 14347 - 16
Main Authors Peng, Meijuan, Jiang, Chen, Dai, Ziyu, Xie, Bin, Chen, Qiong, Lin, Jianing
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 24.04.2025
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Abstract Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. We utilized the limma package and Weighted Gene Co-expression Network Analysis (WGCNA) to analyze datasets from the Gene Expression Omnibus (GEO) database (GSE57148), identifying 12 key differentially expressed mitochondrial genes (MitoDEGs). Using 12 distinct machine learning algorithms (comprising 143 predictive models), we identified the optimal diagnostic model, which includes five pivotal MitoDEGs: ERN1 , FASTK , HIGD1B , NDUFA7 and NDUFB7 . The diagnostic specificity and sensitivity of each gene, as well as the diagnostic model itself, were evaluated using Receiver operating characteristic (ROC) curves. This model demonstrated high specificity in the validation cohorts (GSE76925, GSE151052, GSE239897). Expression analysis revealed upregulation of ERN1 and downregulation of FASTK , HIGD1B , NDUFA7 and NDUFB7 in COPD patients. Spearman’s correlation analysis indicated a significant association between MitoDEGs and immune cell infiltration, with ERN1 expression positively correlated with neutrophil infiltration and the other genes negatively correlated. The GABA receptor modulator androstenol was identified as a potential therapeutic candidate. In vivo studies confirmed reduced mRNA expression of HIGD1B and NDUFB7 in COPD mice. These findings elucidate mitochondrial-immune interactions in COPD and highlight novel diagnostic and therapeutic targets.
AbstractList Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. We utilized the limma package and Weighted Gene Co-expression Network Analysis (WGCNA) to analyze datasets from the Gene Expression Omnibus (GEO) database (GSE57148), identifying 12 key differentially expressed mitochondrial genes (MitoDEGs). Using 12 distinct machine learning algorithms (comprising 143 predictive models), we identified the optimal diagnostic model, which includes five pivotal MitoDEGs: ERN1 , FASTK , HIGD1B , NDUFA7 and NDUFB7 . The diagnostic specificity and sensitivity of each gene, as well as the diagnostic model itself, were evaluated using Receiver operating characteristic (ROC) curves. This model demonstrated high specificity in the validation cohorts (GSE76925, GSE151052, GSE239897). Expression analysis revealed upregulation of ERN1 and downregulation of FASTK , HIGD1B , NDUFA7 and NDUFB7 in COPD patients. Spearman’s correlation analysis indicated a significant association between MitoDEGs and immune cell infiltration, with ERN1 expression positively correlated with neutrophil infiltration and the other genes negatively correlated. The GABA receptor modulator androstenol was identified as a potential therapeutic candidate. In vivo studies confirmed reduced mRNA expression of HIGD1B and NDUFB7 in COPD mice. These findings elucidate mitochondrial-immune interactions in COPD and highlight novel diagnostic and therapeutic targets.
Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. We utilized the limma package and Weighted Gene Co-expression Network Analysis (WGCNA) to analyze datasets from the Gene Expression Omnibus (GEO) database (GSE57148), identifying 12 key differentially expressed mitochondrial genes (MitoDEGs). Using 12 distinct machine learning algorithms (comprising 143 predictive models), we identified the optimal diagnostic model, which includes five pivotal MitoDEGs: ERN1, FASTK, HIGD1B, NDUFA7 and NDUFB7. The diagnostic specificity and sensitivity of each gene, as well as the diagnostic model itself, were evaluated using Receiver operating characteristic (ROC) curves. This model demonstrated high specificity in the validation cohorts (GSE76925, GSE151052, GSE239897). Expression analysis revealed upregulation of ERN1 and downregulation of FASTK, HIGD1B, NDUFA7 and NDUFB7 in COPD patients. Spearman's correlation analysis indicated a significant association between MitoDEGs and immune cell infiltration, with ERN1 expression positively correlated with neutrophil infiltration and the other genes negatively correlated. The GABA receptor modulator androstenol was identified as a potential therapeutic candidate. In vivo studies confirmed reduced mRNA expression of HIGD1B and NDUFB7 in COPD mice. These findings elucidate mitochondrial-immune interactions in COPD and highlight novel diagnostic and therapeutic targets.Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. We utilized the limma package and Weighted Gene Co-expression Network Analysis (WGCNA) to analyze datasets from the Gene Expression Omnibus (GEO) database (GSE57148), identifying 12 key differentially expressed mitochondrial genes (MitoDEGs). Using 12 distinct machine learning algorithms (comprising 143 predictive models), we identified the optimal diagnostic model, which includes five pivotal MitoDEGs: ERN1, FASTK, HIGD1B, NDUFA7 and NDUFB7. The diagnostic specificity and sensitivity of each gene, as well as the diagnostic model itself, were evaluated using Receiver operating characteristic (ROC) curves. This model demonstrated high specificity in the validation cohorts (GSE76925, GSE151052, GSE239897). Expression analysis revealed upregulation of ERN1 and downregulation of FASTK, HIGD1B, NDUFA7 and NDUFB7 in COPD patients. Spearman's correlation analysis indicated a significant association between MitoDEGs and immune cell infiltration, with ERN1 expression positively correlated with neutrophil infiltration and the other genes negatively correlated. The GABA receptor modulator androstenol was identified as a potential therapeutic candidate. In vivo studies confirmed reduced mRNA expression of HIGD1B and NDUFB7 in COPD mice. These findings elucidate mitochondrial-immune interactions in COPD and highlight novel diagnostic and therapeutic targets.
Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. We utilized the limma package and Weighted Gene Co-expression Network Analysis (WGCNA) to analyze datasets from the Gene Expression Omnibus (GEO) database (GSE57148), identifying 12 key differentially expressed mitochondrial genes (MitoDEGs). Using 12 distinct machine learning algorithms (comprising 143 predictive models), we identified the optimal diagnostic model, which includes five pivotal MitoDEGs: ERN1, FASTK, HIGD1B, NDUFA7 and NDUFB7. The diagnostic specificity and sensitivity of each gene, as well as the diagnostic model itself, were evaluated using Receiver operating characteristic (ROC) curves. This model demonstrated high specificity in the validation cohorts (GSE76925, GSE151052, GSE239897). Expression analysis revealed upregulation of ERN1 and downregulation of FASTK, HIGD1B, NDUFA7 and NDUFB7 in COPD patients. Spearman's correlation analysis indicated a significant association between MitoDEGs and immune cell infiltration, with ERN1 expression positively correlated with neutrophil infiltration and the other genes negatively correlated. The GABA receptor modulator androstenol was identified as a potential therapeutic candidate. In vivo studies confirmed reduced mRNA expression of HIGD1B and NDUFB7 in COPD mice. These findings elucidate mitochondrial-immune interactions in COPD and highlight novel diagnostic and therapeutic targets.
Abstract Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. We utilized the limma package and Weighted Gene Co-expression Network Analysis (WGCNA) to analyze datasets from the Gene Expression Omnibus (GEO) database (GSE57148), identifying 12 key differentially expressed mitochondrial genes (MitoDEGs). Using 12 distinct machine learning algorithms (comprising 143 predictive models), we identified the optimal diagnostic model, which includes five pivotal MitoDEGs: ERN1, FASTK, HIGD1B, NDUFA7 and NDUFB7. The diagnostic specificity and sensitivity of each gene, as well as the diagnostic model itself, were evaluated using Receiver operating characteristic (ROC) curves. This model demonstrated high specificity in the validation cohorts (GSE76925, GSE151052, GSE239897). Expression analysis revealed upregulation of ERN1 and downregulation of FASTK, HIGD1B, NDUFA7 and NDUFB7 in COPD patients. Spearman’s correlation analysis indicated a significant association between MitoDEGs and immune cell infiltration, with ERN1 expression positively correlated with neutrophil infiltration and the other genes negatively correlated. The GABA receptor modulator androstenol was identified as a potential therapeutic candidate. In vivo studies confirmed reduced mRNA expression of HIGD1B and NDUFB7 in COPD mice. These findings elucidate mitochondrial-immune interactions in COPD and highlight novel diagnostic and therapeutic targets.
ArticleNumber 14347
Author Jiang, Chen
Peng, Meijuan
Dai, Ziyu
Chen, Qiong
Xie, Bin
Lin, Jianing
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Keywords Machine learning
Immune infiltration
COPD
Mitochondria-related genes
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Snippet Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis...
Abstract Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics...
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SubjectTerms 631/114
692/308
692/699
692/699/1785
Algorithms
Animals
Biomarkers - metabolism
Computational Biology - methods
COPD
Gene Expression Profiling
Gene Regulatory Networks
Genes, Mitochondrial
Humanities and Social Sciences
Humans
Immune infiltration
Machine Learning
Mice
Mitochondria - genetics
Mitochondria - metabolism
Mitochondria-related genes
multidisciplinary
Pulmonary Disease, Chronic Obstructive - diagnosis
Pulmonary Disease, Chronic Obstructive - genetics
Pulmonary Disease, Chronic Obstructive - immunology
Pulmonary Disease, Chronic Obstructive - pathology
Science
Science (multidisciplinary)
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Title Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms
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