Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysis

Abstract While dysregulated autophagy has been linked to acute respiratory distress syndrome (ARDS) development in sepsis, the exact regulatory mechanisms driving this process remain unclear. This study systematically investigated autophagy-related genes in sepsis-induced ARDS using integrative bioi...

Full description

Saved in:
Bibliographic Details
Main Authors: Wei Wang, Jianfeng Zhao, Hui Li, Dabing Huang, Shuiqiao Fu, Zhitao Li
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-92409-7
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849761482132160512
author Wei Wang
Jianfeng Zhao
Hui Li
Dabing Huang
Shuiqiao Fu
Zhitao Li
author_facet Wei Wang
Jianfeng Zhao
Hui Li
Dabing Huang
Shuiqiao Fu
Zhitao Li
author_sort Wei Wang
collection DOAJ
description Abstract While dysregulated autophagy has been linked to acute respiratory distress syndrome (ARDS) development in sepsis, the exact regulatory mechanisms driving this process remain unclear. This study systematically investigated autophagy-related genes in sepsis-induced ARDS using integrative bioinformatics, including weighted gene coexpression network analysis (WGCNA), differential gene expression analysis (DEGs), receiver operating characteristic (ROC) curve analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein‒protein interaction (PPI) network analysis, and immune infiltration analysis. Hub genes were further validated by qPCR in Beas-2B cells receiving lipopolysaccharide (LPS) stimulation. We identified 18 autophagy-related DEGs with diagnostic potential for sepsis-induced ARDS. These DEGs were linked to endocytosis, protein kinase inhibition, and enigmatic Ficolin-1-rich granules. The downregulated hallmark signaling pathways involved apoptosis, complement, IL-2/STAT5, and KRAS signaling. Immune infiltration analysis revealed alterations in 7 immune cell subsets, including CD8 + T-cell exhaustion, natural killer cell reduction, and the type 1 helper T-cell response. When Beas-2B cells were treated with LPS, we discovered that 6 out of the 18 hub genes were significantly downregulated. Our findings provide novel insights into autophagy-mediated ARDS pathogenesis in sepsis. The hub genes represent promising candidates for clinical biomarker development and therapeutic targeting, which necessitates further validation.
format Article
id doaj-art-9f858e0ebea34cb99f417e40adc65157
institution DOAJ
issn 2045-2322
language English
publishDate 2025-03-01
publisher Nature Portfolio
record_format Article
series Scientific Reports
spelling doaj-art-9f858e0ebea34cb99f417e40adc651572025-08-20T03:06:01ZengNature PortfolioScientific Reports2045-23222025-03-0115111210.1038/s41598-025-92409-7Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysisWei Wang0Jianfeng Zhao1Hui Li2Dabing Huang3Shuiqiao Fu4Zhitao Li5Department of Surgical Intensive Care Unit, First Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Surgical Intensive Care Unit, First Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Surgical Intensive Care Unit, First Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Surgical Intensive Care Unit, First Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Surgical Intensive Care Unit, First Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Surgical Intensive Care Unit, First Affiliated Hospital, School of Medicine, Zhejiang UniversityAbstract While dysregulated autophagy has been linked to acute respiratory distress syndrome (ARDS) development in sepsis, the exact regulatory mechanisms driving this process remain unclear. This study systematically investigated autophagy-related genes in sepsis-induced ARDS using integrative bioinformatics, including weighted gene coexpression network analysis (WGCNA), differential gene expression analysis (DEGs), receiver operating characteristic (ROC) curve analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein‒protein interaction (PPI) network analysis, and immune infiltration analysis. Hub genes were further validated by qPCR in Beas-2B cells receiving lipopolysaccharide (LPS) stimulation. We identified 18 autophagy-related DEGs with diagnostic potential for sepsis-induced ARDS. These DEGs were linked to endocytosis, protein kinase inhibition, and enigmatic Ficolin-1-rich granules. The downregulated hallmark signaling pathways involved apoptosis, complement, IL-2/STAT5, and KRAS signaling. Immune infiltration analysis revealed alterations in 7 immune cell subsets, including CD8 + T-cell exhaustion, natural killer cell reduction, and the type 1 helper T-cell response. When Beas-2B cells were treated with LPS, we discovered that 6 out of the 18 hub genes were significantly downregulated. Our findings provide novel insights into autophagy-mediated ARDS pathogenesis in sepsis. The hub genes represent promising candidates for clinical biomarker development and therapeutic targeting, which necessitates further validation.https://doi.org/10.1038/s41598-025-92409-7AutophagyAcute respiratory distress syndromeSepsisBioinformatics
spellingShingle Wei Wang
Jianfeng Zhao
Hui Li
Dabing Huang
Shuiqiao Fu
Zhitao Li
Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysis
Scientific Reports
Autophagy
Acute respiratory distress syndrome
Sepsis
Bioinformatics
title Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysis
title_full Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysis
title_fullStr Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysis
title_full_unstemmed Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysis
title_short Autophagy-related biomarkers identified in sepsis-induced ARDS through bioinformatics analysis
title_sort autophagy related biomarkers identified in sepsis induced ards through bioinformatics analysis
topic Autophagy
Acute respiratory distress syndrome
Sepsis
Bioinformatics
url https://doi.org/10.1038/s41598-025-92409-7
work_keys_str_mv AT weiwang autophagyrelatedbiomarkersidentifiedinsepsisinducedardsthroughbioinformaticsanalysis
AT jianfengzhao autophagyrelatedbiomarkersidentifiedinsepsisinducedardsthroughbioinformaticsanalysis
AT huili autophagyrelatedbiomarkersidentifiedinsepsisinducedardsthroughbioinformaticsanalysis
AT dabinghuang autophagyrelatedbiomarkersidentifiedinsepsisinducedardsthroughbioinformaticsanalysis
AT shuiqiaofu autophagyrelatedbiomarkersidentifiedinsepsisinducedardsthroughbioinformaticsanalysis
AT zhitaoli autophagyrelatedbiomarkersidentifiedinsepsisinducedardsthroughbioinformaticsanalysis