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 in | Scientific reports Vol. 15; no. 1; pp. 14347 - 16 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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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 |
Author_xml | – sequence: 1 givenname: Meijuan surname: Peng fullname: Peng, Meijuan organization: Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University – sequence: 2 givenname: Chen surname: Jiang fullname: Jiang, Chen organization: Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University – sequence: 3 givenname: Ziyu surname: Dai fullname: Dai, Ziyu organization: Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University – sequence: 4 givenname: Bin surname: Xie fullname: Xie, Bin organization: Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University – sequence: 5 givenname: Qiong surname: Chen fullname: Chen, Qiong organization: Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University – sequence: 6 givenname: Jianing surname: Lin fullname: Lin, Jianing email: 13187097907@163.com organization: Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University |
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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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