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Sepsis-induced acute respiratory distress syndrome (ARDS) poses a grave danger to life, resulting from sepsis-induced multi-organ failure. Although ferroptosis, a form of iron-dependent lipid peroxidative cell death, has been associated with sepsis-induced ARDS, the specific mechanisms are not fully understood. In this study, we utilized WGCNA, PPI, friends analysis, and six machine learning techniques (Lasso, SVM, RFB, XGBoost, AdaBoost, and LightGBM) to pinpoint STAT3 as a potential diagnostic marker. A significant increase in monocyte and neutrophil levels was observed in patients with sepsis-induced ARDS, as revealed by immune infiltration analyses, when compared to controls. Moreover, there was a positive correlation between STAT3 expression and the level of infiltration. Single-cell analysis uncovered a notable disparity in B-cell expression between sepsis and sepsis-induced ARDS. Furthermore, in vitro experiments using LPS-treated human bronchial epithelial cells (BEAS-2B) and THP1 cells demonstrated a significant increase in STAT3 phosphorylation expression. Additionally, the inhibition of STAT3 phosphorylation by Stattic effectively prevented LPS-induced ferroptosis in both BEAS-2B and THP1 cells. This indicates that the activation of STAT3 phosphorylation promotes ferroptosis in human bronchial epithelial cells in response to LPS. In summary, this research has discovered and confirmed STAT3 as a potential biomarker for the diagnosis and treatment of sepsis-induced ARDS. [ABSTRACT FROM AUTHOR]

Introduction: Acute respiratory distress syndrome (ARDS) remains a major clinical challenge for patients in intensive care units. Determining the differential mechanisms underlying ARDS with different etiologies is a key goal to improve the effectiveness of ARDS therapy. Despite growing evidence that different immune cell types are involved in ARDS, the role of altered immune cell subpopulations in disease progression is unelucidated.Methods: In this study, we combined scRNA-seq and bulk-level sequencing to analyze the transcriptomes of peripheral blood mononuclear cells from healthy volunteers and patients with septic ARDS (sep-ARDS) and pneumonic ARDS (PNE-ARDS).Results: Our data revealed differential alterations at the cellular and molecular levels and within biological signaling pathways in ARDS with different etiologies. The dynamics of neutrophils, macrophages (Macs), classical dendritic cells (cDCs), myeloid-derived suppressive cells (MDSCs), and CD8+ T cells varied significantly among groups of different samples, with neutrophils and cDCs at higher, and Macs at significantly lower, amounts in the patients with sep-ARDS. Furthermore, MDSCs were highly enriched only in the sep-ARDS patients, whereas a higher abundance of CD8+ T cells was observed in patients with PNE-ARDS. In addition, these cell subpopulations were found to be significantly involved in apoptosis, inflammatory, and immune-related pathways. In particular, a significant enhancement of the oxidative stress response was observed in the neutrophil subpopulation.Conclusion: Our study shows that the composition of cells involved in the main peripheral circulation differs in patients with ARDS with different etiologies. Studying the role and mechanism of action of these cells during ARDS will provide new opportunities for the treatment of this condition.

Mengfei Sun,1,* Qianqian Yang,2,* Chunling Hu,1 Hengchao Zhang,2 Lihua Xing1 1Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, People’s Republic of China; 2Department of Erythrocyte Biology Laboratory, School of Life Sciences, Zhengzhou University, Zhengzhou, 450052, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lihua Xing, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshedong Road, Zhengzhou, Henan, 450052, People’s Republic of China, Tel/Fax +8613838095088, Email xinglihua95088@163.comPurpose: Autophagy-related genes (ARGs) play an important role in the pathophysiology processes of sepsis-induced acute respiratory distress syndrome (ARDS). However, expression profiles of ARGs have rarely been used to explore the relationship between autophagy and sepsis-induced ARDS. Therefore, we aim to identify and validate the potential ARGs of sepsis-induced ARDS through bioinformatics analysis and experiment validation.Methods: We downloaded GSE32707 data from the Gene Expression Omnibus (GEO) database. The potential differentially expressed genes (DEGs) and differentially expressed ARGs (DEARGs) of sepsis-induced ARDS were screened by R software. Then, we performed functional enrichment analyses to explore the potential biological functions of DEARGs and constructed protein–protein interaction (PPI) networks. Subsequently, correlation analysis and receiver operating characteristic (ROC) curve were used for the DEARGs. In addition, we estimated the proportions of 22 immune cell subsets by using CIBERSORT algorithm. Finally, RNA expression of seven DEARGs were validated by qRT-PCR in blood samples from sepsis-induced ARDS and healthy controls.Results: We identified 28 DEARGs, including 11 up-regulated genes and 17 down-regulated genes, which were primarily involved in autophagy and apoptosis. Seven genes (BAG3, CTSD, ERBB2, MYC, PEA15, RAB24 and SIRT1) with AUC > 0.70 were considered possible to be sepsis-induced ARDS hub genes for ROC curve analysis. CIBERSORT results shown that sepsis-induced ARDS contained a higher proportion of naive CD4+ T cells, gamma delta T cells, monocytes, and neutrophils, and lower levels of CD8+ T cells, memory resting CD4+ T cells, follicular helper T cells were relatively lower. The results of qRT-PCR also demonstrated that the expression levels of BAG3, CTSD, ERBB2, MYC and SIRT1 in sepsis-induced ARDS patients and healthy controls had differences.Conclusion: We identified an association between DEGs and immune infiltration in sepsis-induced ARDS and validated BAG3, CTSD, ERBB2, MYC and SIRT1 that may be have excellent diagnostic performance.Keywords: autophagy, sepsis-induced ARDS, immune infiltration, bioinformatics analysis, Gene Expression Omnibus dataset

Sepsis-induced acute respiratory distress syndrome (ARDS) can be mediated by an imbalance in macrophage polarization; however, the underlying mechanisms remain poorly understood. This study aimed to investigate the modulatory role of sirtuin 6 (SIRT6) in macrophage polarization during sepsis-induced ARDS. A mouse ARDS model was established using cecal ligation and puncture. Isolated alveolar macrophages (AMs) and lipopolysaccharide (LPS)-stimulated bone marrow-derived macrophages (BMDMs) were adopted as in vitro models. Macrophage polarization was evaluated by measuring M1 and M2 macrophage percentages via flow cytometry and expression of specific markers. The expression of microtubule-associated light chain protein 3I/II and beclin-1 was detected for assessing macrophage autophagy. Binding between specificity protein 1 (SP1) and the target gene promoter was evaluated using a chromatin immunoprecipitation assay. RNA expression was analyzed by quantitative reverse transcription polymerase chain reaction and western blotting. Treatment with the SIRT6 activator UBCS039 significantly alleviated lung injury in the mouse ARDS model and enhanced autophagy and M2 polarization in isolated AMs. M2 polarization and autophagy in LPS-challenged BMDMs were also effectively promoted by UBCS039 treatment or SIRT6 overexpression. An adenosine monophosphate-activated protein kinase inhibitor (Compound C) or autophagy inhibitor (3-methyladenine) partially abrogated M2 polarization mediated by SIRT6 overexpression upon LPS exposure. SIRT6 induced autophagy and M2 polarization of BMDMs partially via its deacetylase activity. SIRT6 inhibited mammalian target of rapamycin transcription by modulating SP1 to promote BMDM M2 polarization, which was independent of autophagy. SIRT6 promotes M2 polarization of macrophages to alleviate sepsis-induced ARDS in an autophagy-dependent and -independent manner. [ABSTRACT FROM AUTHOR]

Jihua Feng,* Jielong Pang,* Dan He,* Zimeng Wu, Qian Li, Pan Ji, Cuiying He, Zhimei Zhong, Hongyuan Li, Jianfeng Zhang Department of Emergency Medicine, The Second Affiliated Hospital of Guangxi Medical University, Nanning 530007, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jianfeng ZhangDepartment of Emergency Medicine, The Second Affiliated Hospital of Guangxi Medical University, Nanning 530007, People’s Republic of ChinaEmail drzhangjf@163.comPurpose: Early diagnosis of sepsis-induced acute respiratory distress syndrome (ARDS) is critical for effective treatment. We aimed to identify early stage biomarkers.Materials and Methods: Differentially expressed genes were identified in whole blood samples from patients with sepsis or ARDS based on the Gene Expression Omnibus (GEO) datasets GSE32707, GSE54514 and GSE10361. Functional enrichment analysis explored the biological characteristics of differentially expressed genes. Genes with high functional connectivity based on a protein-protein interaction network were marked as hub genes, which were validated using the GEO dataset GSE76293, and a gene set variation analysis index (GSVA) was assigned. Diagnostic and predictive ability of the hub genes were assessed by receiver operating characteristic (ROC) curve analysis. DNA methylation levels of hub genes were quantified using the GEO dataset GSE67530.Results: Forty-one differentially expressed genes were shared between sepsis-specific and ARDS-specific datasets. MAP2K2 and IRF7 functional activity was highly connected in sepsis-induced ARDS. Hub genes included RETN, MVP, DEFA4, CTSG, AZU1, FMNL1, RBBP7, POLD4, RIN3, IRF7. ROC curve analysis of the hub gene GSVA index showed good diagnostic ability in sepsis or ARDS. Among genes related to sepsis-induced ARDS, 17 were differentially methylated. Principal component analysis and heatmaps indicated that gene methylation patterns differed significantly between ARDS patients and controls.Conclusion: We identified a genetic profile specific to early-stage sepsis-induced ARDS. The abnormal expression of these genes may be caused by hypomethylation, which may serve as a biomarker for early diagnosis of ARDS.Keywords: acute respiratory distress syndrome, ARDS, sepsis-induced ARDS, hub genes, methylation, gene set variation analysis

Background: In recent years, sepsis-induced acute respiratory distress syndrome (ARDS) has remained a major clinical challenge for patients in intensive care units. While some progress has been reported over the years, the pathogenesis of ARDS still needs to be further expounded. Methods: In the present study, gene set enrichment analysis, differentially expressed genes analysis, short time-series expression miner, protein–protein interaction (PPI) networks, module analysis, hypergeometric test, and functional enrichment analysis were performed in whole blood gene expression profiles of sepsis and induced-sepsis ARDS to explore the molecular mechanism of sepsis-induced ARDS. Results: Further dysregulated genes in the process evolving from healthy control through sepsis to sepsis-induced ARDS were identified and organized into 10 functional modules based on their PPI networks. These functional modules were significantly involved in cell cycle, ubiquitin mediated proteolysis, spliceosome, and other pathways. MYC, STAT3, LEF1, and BRCA1 were potential transcription factors (TFs) regulating these modules. A TF-module-pathway global regulation network was constructed. In particular, our findings suggest that MYC and STAT3 may be the key regulatory genes in the underlying dysfunction of sepsis-induced ARDS. Receiver operating characteristic curve analysis showed the core genes in the global regulation network may be biomarkers for sepsis or sepsis-induced ARDS. Conclusions: We found that MYC and STAT3 may be the key regulatory genes in the underlying dysfunction of sepsis-induced ARDS. The reviews of this paper are available via the supplementary material section. [ABSTRACT FROM AUTHOR]

Introduction: Acute respiratory distress syndrome (ARDS) remains a major clinical challenge for patients in intensive care units. Determining the differential mechanisms underlying ARDS with different etiologies is a key goal to improve the effectiveness of ARDS therapy. Despite growing evidence that different immune cell types are involved in ARDS, the role of altered immune cell subpopulations in disease progression is unelucidated. Methods: In this study, we combined scRNA-seq and bulk-level sequencing to analyze the transcriptomes of peripheral blood mononuclear cells from healthy volunteers and patients with septic ARDS (sep-ARDS) and pneumonic ARDS (PNE-ARDS). Results: Our data revealed differential alterations at the cellular and molecular levels and within biological signaling pathways in ARDS with different etiologies. The dynamics of neutrophils, macrophages (Macs), classical dendritic cells (cDCs), myeloid-derived suppressive cells (MDSCs), and CD8 + T cells varied significantly among groups of different samples, with neutrophils and cDCs at higher, and Macs at significantly lower, amounts in the patients with sep-ARDS. Furthermore, MDSCs were highly enriched only in the sep-ARDS patients, whereas a higher abundance of CD8 + T cells was observed in patients with PNE-ARDS. In addition, these cell subpopulations were found to be significantly involved in apoptosis, inflammatory, and immune-related pathways. In particular, a significant enhancement of the oxidative stress response was observed in the neutrophil subpopulation. Conclusion: Our study shows that the composition of cells involved in the main peripheral circulation differs in patients with ARDS with different etiologies. Studying the role and mechanism of action of these cells during ARDS will provide new opportunities for the treatment of this condition., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Mo, Yang, Feng, Lei, Huang, Cen, Wei, Huang, Lu and Zhang.)

Sepsis-induced acute respiratory distress syndrome (ARDS) remains a major threat to human health without effective therapeutic drugs. Previous studies demonstrated the power of gene expression profiling to reveal pathological changes associated with sepsis-induced ARDS. However, there is still a lack of systematic data mining framework for identifying potential targets for treatment. In this study, we demonstrated the feasibility of druggable targets prediction based on gene expression data. Through the functional enrichment analysis of microarray-based expression profiles between sepsis-induced ARDS and non-sepsis ARDS samples, we revealed genes involved in anti-microbial infection immunity were significantly altered in sepsis-induced ARDS. Protein-protein interaction (PPI) network analysis highlighted TOP2A gene as the key regulator in the dysregulated gene network of sepsis-induced ARDS. We were also able to predict several therapeutic drug candidates for sepsis-induced ARDS using Connectivity Map (Cmap) database, among which doxorubicin was identified to interact with TOP2A with a high affinity similar to its endogenous ligand. Overall, our findings suggest that doxorubicin could be a potential therapeutic for sepsis-induced ARDS by targeting TOP2A, which requires further investigation and validation. The whole study relies on publicly available dataset and publicly accessible database or bioinformatic tools for data mining. Therefore, our study benchmarks a workflow for druggable target prediction which can be widely applicable in the search of targets in other pathological conditions.