PANoptosis gene signatures identify candidate biomarkers and genetically associated genes in COPD.
- 1Huaian Clinical College of Xuzhou Medical University, Xuzhou, China
- 2The Affiliated Huai’an No.1 People’s Hospital of Nanjing Medical University, Huai’an, China
- 3The Affiliated Huai’an No.1 People’s Hospital of Nanjing Medical University, Huai’an Clinical College of Xuzhou Medical University, Huai’an, China
Abstract
Background
PANoptosis contributes to chronic obstructive pulmonary disease (COPD) pathogenesis. We aimed to identify PANoptosis-related gene signatures as candidate biomarkers and evaluate their genetic associations with COPD risk.Methods
Three transcriptomic data sets were integrated to identify differentially expressed PANoptosis-related genes in COPD, followed by enrichment analyses and immune infiltration profiling using CIBERSORT and single-sample gene set enrichment analysis. We selected feature genes using machine learning and evaluated their discriminative performance. We used Mendelian randomisation (MR) and multivariable MR (MVMR) to assess genetic associations with COPD risk, using the forced expiratory volume in one second/forced vital capacity (FEV1/FVC) ratio as a proxy for airflow limitation and adjusting for smoking. We validated candidate genes by quantitative real-time polymerase chain reaction (qRT-PCR) in human lung tissues from COPD patients and controls.Results
Seven PANoptosis-related genes (IL1B, IRF1, NTRK2, PIK3CG, SFN, TNFSF10, and UACA) were differentially expressed in COPD. Immune profiling suggested immune microenvironment remodelling, characterised by increased memory B cells, activated mast cells, and CD4⁺ T helper cell subsets, with decreased M2 macrophages, monocytes, and neutrophils. PIK3CG and IL1B were positively associated with adaptive immune-related signals, whereas UACA showed predominantly negative immune correlations. PIK3CG showed moderate and variable discriminative performance, with an area under the curve of 0.775 in the training data set and 0.614 and 0.743 in validation data sets. The MR and MVMR analyses suggested that IRF1- and UACA-mediated increases in FEV1/FVC were associated with lower COPD risk independently of smoking. Additionally, qRT-PCR confirmed PIK3CG up-regulation in COPD lung tissues, whereas IRF1 and UACA showed no remarkable expression changes.Conclusions
Our results suggest that PIK3CG is a computationally and experimentally supported biomarker for COPD, while IRF1 and UACA act as genetically implicated regulators of airflow limitation. Together, these findings show the potential importance of PANoptosis-driven immune microenvironmental remodelling as a therapeutic direction warranting further functional validation.
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BibTeX
@article{chen2026panoptosis,
title = {{PANoptosis gene signatures identify candidate biomarkers and genetically associated genes in COPD.}},
author = {Hongqing Chen and Jindao Wang and Dan Yang and Ting Ma and Liang Wang and Zongren Wan and Rong Zhu},
journal = {Journal of global health},
year = {2026},
month = oct,
doi = {10.7189/jogh.16.04302},
url = {https://europepmc.org/article/MED/42961086},
note = {CC BY},
}
RIS
TY - JOUR
TI - PANoptosis gene signatures identify candidate biomarkers and genetically associated genes in COPD.
AU - Hongqing Chen
AU - Jindao Wang
AU - Dan Yang
AU - Ting Ma
AU - Liang Wang
AU - Zongren Wan
AU - Rong Zhu
PY - 2026
DA - 2026/10/30
JO - Journal of global health
DO - 10.7189/jogh.16.04302
UR - https://europepmc.org/article/MED/42961086
AB - Background PANoptosis contributes to chronic obstructive pulmonary disease (COPD) pathogenesis. We aimed to identify PANoptosis-related gene signatures as candidate biomarkers and evaluate their genetic associations with COPD risk.Methods Three transcriptomic data sets were integrated to identify differentially expressed PANoptosis-related genes in COPD, followed by enrichment analyses and immune infiltration profiling using CIBERSORT and single-sample gene set enrichment analysis. We selected feature genes using machine learning and evaluated their discriminative performance. We used Mendelian randomisation (MR) and multivariable MR (MVMR) to assess genetic associations with COPD risk, using the forced expiratory volume in one second/forced vital capacity (FEV1/FVC) ratio as a proxy for airflow limitation and adjusting for smoking. We validated candidate genes by quantitative real-time polymerase chain reaction (qRT-PCR) in human lung tissues from COPD patients and controls.Results Seven PANoptosis-related genes (IL1B, IRF1, NTRK2, PIK3CG, SFN, TNFSF10, and UACA) were differentially expressed in COPD. Immune profiling suggested immune microenvironment remodelling, characterised by increased memory B cells, activated mast cells, and CD4⁺ T helper cell subsets, with decreased M2 macrophages, monocytes, and neutrophils. PIK3CG and IL1B were positively associated with adaptive immune-related signals, whereas UACA showed predominantly negative immune correlations. PIK3CG showed moderate and variable discriminative performance, with an area under the curve of 0.775 in the training data set and 0.614 and 0.743 in validation data sets. The MR and MVMR analyses suggested that IRF1- and UACA-mediated increases in FEV1/FVC were associated with lower COPD risk independently of smoking. Additionally, qRT-PCR confirmed PIK3CG up-regulation in COPD lung tissues, whereas IRF1 and UACA showed no remarkable expression changes.Conclusions Our results suggest that PIK3CG is a computationally and experimentally supported biomarker for COPD, while IRF1 and UACA act as genetically implicated regulators of airflow limitation. Together, these findings show the potential importance of PANoptosis-driven immune microenvironmental remodelling as a therapeutic direction warranting further functional validation.
SN - 2047-2978
SN - 2047-2986
ER -