Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics

BackgroundResearch has demonstrated that the homeostasis of mitochondria and programmed cell death (PCD) are intimately linked to chronic obstructive pulmonary disease (COPD). Consequently, identifying biomarkers of COPD from mitochondria-related genes (MRGs) and programmed cell death-related genes...

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Main Authors: Xiaojuan Yang, Yutao Duan, Lei Qiu, Xia Huang, Fei Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Genetics
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Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2025.1567173/full
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author Xiaojuan Yang
Yutao Duan
Lei Qiu
Xia Huang
Fei Li
author_facet Xiaojuan Yang
Yutao Duan
Lei Qiu
Xia Huang
Fei Li
author_sort Xiaojuan Yang
collection DOAJ
description BackgroundResearch has demonstrated that the homeostasis of mitochondria and programmed cell death (PCD) are intimately linked to chronic obstructive pulmonary disease (COPD). Consequently, identifying biomarkers of COPD from mitochondria-related genes (MRGs) and programmed cell death-related genes (PCD-RGs) is of paramount importance.MethodsDifferentially expressed genes (DEGs) from the GSE42057 dataset and COPD-related genes (COPD-RGs) via weighted gene co-expression network analysis (WGCNA) were intersected with MRGs and PCD-RGs to select candidates. Machine learning identified biomarkers, validated across GSE42057 and GSE94916 datasets. Pathway enrichment, immune infiltration, and drug prediction analyses were performed.ResultsEight candidate genes were derived from intersecting DEGs, COPD-RGs, MRGs, and PCD-RGs. Five biomarkers (BCL2, CCR7, FAM162A, FOXO1, RPS3) were identified, showing consistent dysregulation in COPD. These biomarkers activated the “ribosome” pathway. CCR7 and FOXO1 correlated positively with naïve B cells, while BCL2 negatively correlated with M0 macrophages. BCL2 exhibited strong binding to dolastatin 10, beauvericin, and micellar paclitaxel. RT-qPCR confirmed biomarker expression.ConclusionBCL2, CCR7, FAM162A, FOXO1, and RPS3 are biomarkers for COPD, providing a new breakthrough point for the treatment of this disease.
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spelling doaj-art-408efe4e6bd4442db250c42d4f47473a2025-08-20T03:22:08ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-06-011610.3389/fgene.2025.15671731567173Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomicsXiaojuan Yang0Yutao Duan1Lei Qiu2Xia Huang3Fei Li4Department of Pulmonary and Critical Care Medicine, Shanxi Provincial People’s Hospital, Taiyuan, ChinaRadiology Department, The First People’s Hospital of Jinzhong, Jinzhong, Shanxi, ChinaDepartment of Pulmonary and Critical Care Medicine, Shanxi Provincial People’s Hospital, Taiyuan, ChinaThe Fifth Clinical Medical College of Shanxi Medical University, Taiyuan, ChinaDepartment of Pulmonary and Critical Care Medicine, Shanxi Provincial People’s Hospital, Taiyuan, ChinaBackgroundResearch has demonstrated that the homeostasis of mitochondria and programmed cell death (PCD) are intimately linked to chronic obstructive pulmonary disease (COPD). Consequently, identifying biomarkers of COPD from mitochondria-related genes (MRGs) and programmed cell death-related genes (PCD-RGs) is of paramount importance.MethodsDifferentially expressed genes (DEGs) from the GSE42057 dataset and COPD-related genes (COPD-RGs) via weighted gene co-expression network analysis (WGCNA) were intersected with MRGs and PCD-RGs to select candidates. Machine learning identified biomarkers, validated across GSE42057 and GSE94916 datasets. Pathway enrichment, immune infiltration, and drug prediction analyses were performed.ResultsEight candidate genes were derived from intersecting DEGs, COPD-RGs, MRGs, and PCD-RGs. Five biomarkers (BCL2, CCR7, FAM162A, FOXO1, RPS3) were identified, showing consistent dysregulation in COPD. These biomarkers activated the “ribosome” pathway. CCR7 and FOXO1 correlated positively with naïve B cells, while BCL2 negatively correlated with M0 macrophages. BCL2 exhibited strong binding to dolastatin 10, beauvericin, and micellar paclitaxel. RT-qPCR confirmed biomarker expression.ConclusionBCL2, CCR7, FAM162A, FOXO1, and RPS3 are biomarkers for COPD, providing a new breakthrough point for the treatment of this disease.https://www.frontiersin.org/articles/10.3389/fgene.2025.1567173/fullchronic obstructive pulmonary diseasemitochondriaprogrammed cell deathbiomarkersimmune infiltration
spellingShingle Xiaojuan Yang
Yutao Duan
Lei Qiu
Xia Huang
Fei Li
Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics
Frontiers in Genetics
chronic obstructive pulmonary disease
mitochondria
programmed cell death
biomarkers
immune infiltration
title Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics
title_full Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics
title_fullStr Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics
title_full_unstemmed Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics
title_short Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics
title_sort identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics
topic chronic obstructive pulmonary disease
mitochondria
programmed cell death
biomarkers
immune infiltration
url https://www.frontiersin.org/articles/10.3389/fgene.2025.1567173/full
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