S100A12 as Biomarker of Disease Severity and Prognosis in Patients With Idiopathic Pulmonary Fibrosis

Mendelian randomization combined with single-cell sequencing data analysis of chemokines and chemokine receptors and key genes and molecular mechanisms associated with epilepsy

To explore the functions and potential regulatory mechanisms of chemokine and chemokine receptor (CCR)-related genes in epilepsy. CCRs were identified as candidate genes and their causal relationship with epilepsy was rigorously evaluated via Mendelian randomization analysis. Subsequently, single-cell RNA sequencing (scRNA-seq) data were analyzed to identify and classify cell clusters into distinct types based on cellular annotation. Differential expression analysis was conducted to pinpoint key genes by overlapping the candidate gene set with differentially expressed genes (DEGs). Furthermore, potential therapeutic drugs for epilepsy were predicted, offering novel avenues for disease management and treatment. In total, 6395 DEGs were identified across the six cell clusters. After their intersection,CCRL2, XCL2, CXCR5, CXCL1, and CX3CR1 were pinpointed as key genes. Microglia, T cells, B cells, and macrophages have been emerged as critical cells. Furthermore, CXCL1 was regulated by hsa-miR-570-3p and hsa-miR-532-5p. Notably, CXCR5, CXCL1, and CX3CR1 were associated with 27 drug compounds. This comprehensive study leveraged scRNA-seq and transcriptomic data to elucidate the roles of CCR-related genes in epilepsy. Notably, CCRL2, XCL2, CXCR5, CXCL1, and CX3CR1 were identified as key genes implicated in epilepsy, whereas microglia, T cells, B cells, and macrophages were recognized as critical contributors to the development of epilepsy. Regulating the expression of CCRL2, XCL2, CXCR5, CXCL1, and CX3CR1, along with the activity of these immune cells may offer therapeutic potential for the alleviation of epilepsy.

Analysis of baseline interstitial lung abnormality on the risk of checkpoint inhibitor-related pneumonitis and survival in advanced non-small cell lung cancer patients treated with first-line PD-1/PD-L1 inhibitors

Background

Chest computed tomography (CT) can be used to identify interstitial lung abnormality (ILA), which is known to lead to an increased risk of post-operative complications, and is related to a worse prognosis in early-stage lung cancer. However, research on the role of ILA in advanced non-small cell lung cancer (NSCLC) patients receiving immunotherapy is limited. This study sought to investigate the effect of pre-existing ILA and pulmonary function test (PFT) results on the occurrence of checkpoint inhibitor-related pneumonitis (CIP) and survival in advanced NSCLC patients after programmed cell death protein-1 (PD-1) or programmed cell death-ligand 1 (PD-L1) inhibitor therapy.

Methods

We retrospectively divided the patients with advanced NSCLC into two groups: the with ILA group, and the without ILA group. We also divided the patients into two groups based on whether they developed CIP during treatment. After first-line immunotherapy, we followed up with all patients and recorded their progression-free survival (PFS) and overall survival (OS). Two respiratory specialists recorded the cases of CIP and the existence of ILA on chest CT, and assessed the consistency of ILA. A logistic regression analysis was performed to explore the independent risk factors for CIP, and a Cox regression analysis was performed to investigate the factors influencing PFS and OS.

Results

Of the 269 patients with advanced NSCLC enrolled in the study, 93 (34.57%) had ILA, and 176 (65.43%) did not have ILA. Additionally, 39 (14.50%) of the patients developed CIP. The univariate analysis showed that pre-existing ILA [odds ratio (OR): 3.733; 95% confidence interval (CI): 1.846-7.549; P<0.001], body mass index (BMI) (≥24.12 kg/m2) (OR: 2.616; 95% CI: 1.312-5.214; P=0.006), and lactate dehydrogenase (LDH) (≥186.50 U/L) (OR: 2.231; 95% CI: 1.038-4.792; P=0.04) were highly correlated with CIP. In the multivariate analysis, ILA remained a robust independent predictor of CIP (OR: 4.128; 95% CI: 1.984-8.587; P<0.001). In terms of CIP, compared to the patients with mild CIP (grades 1/2), those with severe CIP (grades 3/4) had a worse OS (median for patients with grades 3/4: 12.4 months; median for patients with grades 1/2: 35.8 months) [hazard ratio (HR): 4.808; 95% CI: 1.671-13.830; P=0.004]. ILA was linked to a shorter OS time, such that the patients with ILA had a median OS of 21.1 months, while those without ILA had a median OS of 42.5 months (HR: 2.213; 95% CI: 1.404-3.488; P<0.001). The multivariable Cox regression analysis showed that ILA was also significantly associated with an increased risk of death (HR: 1.899; 95% CI: 1.253-2.878; P=0.002). However, no significant association was found between the PFTs before immunotherapy and CIP.

Conclusions

Pre-existing ILA is an independent risk factor that is strongly associated with CIP, and significantly correlated with worse PFS and OS in advanced NSCLC patients after first-line immunotherapy.

Uncovering Hippo pathway-related biomarkers in acute myocardial infarction via scRNA-seq binding transcriptomics

This study investigated Hippo signaling pathway-related biomarkers in acute myocardial infarction (AMI). First, differentially expressed genes (DEGs) between AMI patients and controls were identified. Consensus clustering then classified AMI subtypes, followed by subtype-specific DEG screening. Candidate genes were derived from intersecting initial DEGs with subtype-associated DEGs. Three machine-learning algorithms prioritized five biomarkers (NAMPT, CXCL1, CREM, GIMAP6, and GIMAP7), validated through multi-dataset analyses and cellular expression profiling. qRT-PCR and Western blot confirmed differential expression patterns between AMI and controls across experimental models. Notably, NAMPT, CXCL1, and GIMAP6 exhibited cell-type-specific expression in endothelial cells and macrophages. We further predicted 179 potential therapeutic agents targeting these biomarkers. Niclosamide and eugenol were observed to mitigate hypoxia-induced injury in neonatal mouse ventricular cardiomyocytes. In vivo experiments demonstrated upregulated NAMPT/CXCL1 and downregulated GIMAP6/GIMAP7 in AMI myocardial tissues, with significant NAMPT protein elevation. These biomarkers show clinical diagnostic potential and provide mechanistic insights into AMI pathogenesis.

Association between genetic prediction of 486 blood metabolites and the risk of idiopathic pulmonary fibrosis: A mendelian randomization study

Metabolic disorders are a significant feature of fibrotic diseases. Nevertheless, the lack of sufficient proof regarding the cause-and-effect association between circulating metabolites and the promotion or prevention of idiopathic pulmonary fibrosis (IPF) persists. To assess the causal association between IPF and genetic proxies of 486 blood metabolites, a dual sample Mendelian randomization (MR) analysis was performed. Therefore, the two-sample MR technique and genome-wide association study data were employed to assess the association between 486 serum metabolites and IPF. To produce the primary outcomes, the inverse variance weighted (IVW) technique was applied, while to assess the stability and dependability of the outcomes, sensitivity analysis using MR-Egger analysis was performed. Additionally, weighted median, Cochran's Q-test, Egger intercept test and the leave-one-out method were used. The results of the present study revealed a total of 21 metabolites in blood circulation that could affect the risk of IPF (PIVW<0.05). Among them, 10 compounds were already known, namely cotinine [odds ratio (OR)=1.206; 95% confidence interval (CI), 1.002-1.452; P=0.047], hypoxanthine (OR=0.225; 95% CI, 0.056-0.899; P=0.034), aspartyl phenylalanine (OR=4.309; 95% CI, 1.084-17.131; P=0.038), acetyl-carnitine (OR=5.767; 95% CI, 1.398-23.789; P=0.015), 2-aminobutyrate (OR=0.155; 95% CI, 0.033-0.713; P=0.016), Docosapentaenoic acid (PubChem ID: 5497182; OR=0.214; 95% CI, 0.055-0.833; P=0.026), octanoyl-carnitine (PubChem ID: 177508; OR=3.398; 95% CI, 1.179-9.794; P=0.023), alpha-hydroxy-isovalerate (PubChem ID: 857803-94-2; OR=0.324; 95% CI, 0.112-0.931; P=0.036), 1,7-dimethylurate (PubChem ID: 91611; OR=0.401; 95% CI, 0.172-0.931; P=0.033) and 1-linoleoyl-glycerophosphocholine (PubChem ID: 657272; OR=6.559; 95% CI, 1.060-40.557; P=0.043). Additionally, the study also identified 11 currently unknown chemical structures. The results of Cochran's Q-test indicated that there was no significant heterogeneity, while MR-Egger's intercept analysis verified the lack of horizontal pleiotropy. The retention of one method for plotting also supported the reliability of the MR analysis. Overall, the results of the current study supported the cause-and-effect association between IPF and 21 blood metabolites, including 10 with already known chemical composition and 11 which are still awaiting determination. These findings could provide novel insights for the further investigation of the mechanism underlying the development of IPF.

Identification and Analysis of Key Immune- and Inflammation-Related Genes in Idiopathic Pulmonary Fibrosis

Background

Studies suggest that immune and inflammation processes may be involved in the development of idiopathic pulmonary fibrosis (IPF); however, their roles remain unclear. This study aims to identify key genes associated with immune response and inflammation in IPF using bioinformatics.

Methods

We identified differentially expressed genes (DEGs) in the GSE93606 dataset and GSE28042 dataset, then obtained differentially expressed immune- and inflammation-related genes (DE-IFRGs) by overlapping DEGs. Two machine learning algorithms were used to further screen key genes. Genes with an area under curve (AUC) of > 0.7 in receiver operating characteristic (ROC) curves, significant expression and consistent trends across datasets were considered key genes. Based on these key genes, we carried out nomogram construction, enrichment and immune analyses, regulatory network mapping, drug prediction, and expression verification.

Results

27 DE-IFRGs were identified by intersecting 256 DEGs, 1793 immune-related genes, and 1019 inflammation-related genes. Three genes (RNASE3, S100A12, S100A8) were obtained by crossing two machine algorithms (Boruta and LASSO),which had good diagnostic performance with AUC values. These key genes were all enriched in the same pathways, such as GOCC_azurophil_granule, IL-12 signalling and production in macrophages is the pathway with the strongest role for key genes. Six distinct immune cells, including naive CD4 T cells, T cells CD4 memory resting, T cells regulatory (Tregs), Monocytes, Macrophages M2, Neutrophils were identified. Real-time quantitative polymerase chain reaction (RT-qPCR) results were consistent with the training and validation sets, and the expression of these key genes was significantly upregulated in the IPF samples.

Conclusion

This study identified three key genes (RNASE3, S100A12 and S100A8) associated with immune response and inflammation in IPF, providing valuable insights into the diagnosis and treatment of IPF.

Diagnostic Application of Bronchoalveolar Lavage Fluid Analysis in Cases of Idiopathic Pulmonary Fibrosis in which Diagnosis Cannot Be Confirmed by High-Resolution Computed Tomography

PURPOSE

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrotic lung disorder characterized by dry cough, fatigue, and exacerbated dyspnea. The prognosis of IPF is notably unfavorable, becoming extremely poor when the disease advances acutely. Effective therapeutic intervention is essential to mitigate disease progression; hence, early diagnosis and treatment are paramount. When high-resolution computed tomography (HRCT) reveals usual interstitial pneumonia (UIP), a diagnosis of IPF can be established. However, when HRCT fails to conclusively confirm IPF, the diagnostic pathway becomes intricate and necessitates a multidisciplinary approach involving clinicians, radiologists, and pathologists. Consequently, the objective of this study was to investigate new diagnostic approaches through bronchoalveolar lavage (BAL) analysis.

METHODS

BAL is a commonly utilized diagnostic tool for interstitial lung diseases. We review the application of bronchoalveolar lavage (BALF) in idiopathic pulmonary fibrotic disease, emphasizing that the cellular and solute composition of the lower respiratory tract offers valuable insights.

RESULTS

This review delineates the advancements in diagnosing IPF cases that remain indeterminate via HRCT, leveraging BALF analysis. In contrast to surgical lung biopsy, BAL is minimally invasive and offers potential diagnostic utility through the identification of specific BALF biomarkers.

CONCLUSION

Augment the clinical diagnostic armamentarium for IPF, particularly in scenarios where HRCT findings are inconclusive.

Single-Cell RNA Sequencing of PBMCs Identified Junction Plakoglobin (JUP) as Stratification Biomarker for Endometriosis

This study aimed to identify unique characteristics in the peripheral blood mononuclear cells (PBMCs) of endometriosis patients and develop a non-invasive early diagnostic tool. Using single-cell RNA sequencing (scRNA-seq), we constructed the first single-cell atlas of PBMCs from endometriosis patients based on 107,964 cells and 25,847 genes. Within CD16+ monocytes, we discovered JUP as a dysregulated gene. To assess its diagnostic potential, we measured peritoneal fluid (PF) and serum JUP levels in a large cohort of 199 patients including 20 women with ovarian cancer (OC). JUP was barely detectable in PF but was significantly elevated in the serum of patients with endometriosis and OC, with levels 1.33 and 2.34 times higher than controls, respectively. Additionally, JUP was found in conditioned culture media of CD14+/CD16+ monocytes aligning with our scRNA-seq data. Serum JUP levels correlated with endometriosis severity and endometrioma presence but were unaffected by dysmenorrhea, menstrual cycle, or adenomyosis. When combined with CA125 (cancer antigen 125) JUP enhanced the specificity of endometriosis diagnosis from 89.13% (CA125 measured alone) to 100%. While sensitivity remains a challenge at 19%, our results suggest that JUP's potential to enhance diagnostic accuracy warrants additional investigation. Furthermore, employing serum JUP as a stratification marker unlocked the potential to identify additional endometriosis-related genes, offering novel insights into disease pathogenesis.

Single-Cell Analysis Reveals Novel Immune Perturbations in Fibrotic Hypersensitivity Pneumonitis

Rationale: Fibrotic hypersensitivity pneumonitis (FHP) is a debilitating interstitial lung disease driven by incompletely understood immune mechanisms. Objectives: To elucidate immune aberrations in FHP in single-cell resolution. Methods: Single-cell 5' RNA sequencing was conducted on peripheral blood mononuclear cells and BAL cells obtained from 45 patients with FHP, 63 patients with idiopathic pulmonary fibrosis (IPF), 4 patients with nonfibrotic hypersensitivity pneumonitis, and 36 healthy control subjects in the United States and Mexico. Analyses included differential gene expression (Seurat), TF (transcription factor) activity imputation (DoRothEA-VIPER), and trajectory analyses (Monocle3 and Velocyto-scVelo-CellRank). Measurements and Main Results: Overall, 501,534 peripheral blood mononuclear cells from 110 patients and control subjects and 88,336 BAL cells from 19 patients were profiled. Compared with control samples, FHP has elevated classical monocytes (adjusted-P = 2.5 × 10-3) and is enriched in CCL3hi/CCL4hi and S100Ahi classical monocytes (adjusted-P < 2.2 × 10-16). Trajectory analyses demonstrate that S100Ahi classical monocytes differentiate into SPP1hi lung macrophages associated with fibrosis. Compared with both control subjects and IPF, cells from patients with FHP are significantly enriched in GZMhi cytotoxic T cells. These cells exhibit TF activities indicative of TGFβ and TNFα and NFκB pathways. These results are publicly available at http://ildimmunecellatlas.com. Conclusions: Single-cell transcriptomics of patients with FHP uncovered novel immune perturbations, including previously undescribed increases in GZMhi cytotoxic CD4+ and CD8+ T cells-reflecting this disease's unique inflammatory T cell-driven nature-as well as increased S100Ahi and CCL3hi/CCL4hi classical monocytes also observed in IPF. Both cell populations may guide the development of new biomarkers and therapeutic interventions.

Unique transcriptomic profile of peripheral blood monocytes in rheumatoid arthritis-associated interstitial lung disease

OBJECTIVES

Though interstitial lung disease (ILD) contributes to excess morbidity and mortality in rheumatoid arthritis (RA), RA-ILD pathogenesis remains incompletely defined. As intermediate, non-classical and suppressed CD14+ monocytes are expanded in RA-ILD, this study sought to characterize gene expression profiles of circulating monocytes in RA-ILD.

METHODS

Peripheral blood mononuclear cells were collected from patients with RA without lung disease (N = 5), RA-ILD (N = 5), idiopathic pulmonary fibrosis (IPF; N = 5), and controls without lung and autoimmune disease (N = 4). RNA was extracted from CD14+ isolated monocytes and subjected to transcriptional analysis of 1365 genes. Gene enrichment and pathway analyses were performed.

RESULTS

Unsupervised clustering grouped patients with RA-ILD together with IPF for myeloid innate genes. For fibrosis genes, patients with RA-ILD clustered independent of comparator groups. There were 103, 66, and 64 upregulated and 66, 14, and 25 downregulated genes for RA-ILD, RA, and IPF, vs controls, respectively. For RA-ILD, there was increased expression of genes involved in regulating inflammation and fibrosis (SOCS3, CECAM1, LTB4R2, CLEC7A, IRF7, PHYKPL, GBP5, RAPGEF), epigenetic modification (KDM5D, KMT2D, OGT), and macrophage activation. Top canonical pathways included macrophage differentiation-activation, IL-12, neuroinflammatory, glucocorticoid receptor, and IL-27 signalling.

CONCLUSIONS

Circulating monocytes in RA-ILD patients demonstrate unique gene expression profiles with innate immune gene features more aligned with IPF as opposed to RA in the absence of clinical lung disease with fibrosis gene expression that was distinct from RA and IPF. These studies are important for understanding disease pathogenesis and may provide information for future therapeutic targets in RA-ILD.

Single-cell transcriptome sequencing reveals altered peripheral blood immune cells in patients with severe tuberculosis

Tuberculosis is a serious global health burden, resulting in millions of deaths each year. Several circulating cell subsets in the peripheral blood are known to modulate the host immune response to Mycobacterium tuberculosis (Mtb) infection in different ways. However, the characteristics and functions of these subsets to varying stages of tuberculosis infection have not been well elucidated. Peripheral blood immune cells (PBICs) were isolated from healthy donors (HD group), individuals with mild tuberculosis (MI group), and individuals with severe tuberculosis (SE group). CD4+ naive T cells and CD8+ T cells were decreased in the SE and MI groups, while CD14+ monocytes were increased in the SE group. Further analysis revealed increased activated CD4+ T cells, transitional CD8+ T cells, memory-like NK cells, and IGHG3highTTNhighFCRL5high B cells were increased in all patients with tuberculosis (SE and MI group). In contrast, Th17 cells, cytotoxic NK cells, and cytotoxic CD4+ T cells were decreased. Moreover, the increase of CD14+CD16+ monocytes correlated with severe tuberculosis, and the GBP5highRSAD2high neutrophils were unique to patients with severe tuberculosis. Cellular communication analysis revealed that CD8+ T cells exhibited the highest incoming interaction strength in the SE group. The increased CD8+ T cell incoming interactions are associated with the MHC-I and LCK pathways, with HLA-(A-E)-CD8A, HLA-(A-E)-CD8B, and LCK-(CD8A+CD8B) being ligand-receptor pairs. Patients with tuberculosis, especially severe tuberculosis, have profound changes in peripheral blood immune cell profiles. CD8+ T cells showed the highest incoming interaction strength in patients with severe tuberculosis, with the main signals being MHC-I and LCK pathways.

Prognostic model of fibroblasts in idiopathic pulmonary fibrosis by combined bulk and single-cell RNA-sequencing

Background

Fibroblasts play an important role in the development of idiopathic pulmonary fibrosis (IPF).

Methods

We employed single-cell RNA-sequencing data obtained from the Gene Expression Omnibus database to perform cell clustering and annotation analyses. We then performed secondary clustering of fibroblasts and conducted functional enrichment and cell trajectory analyses of the two newly defined fibroblast subtypes. Bulk RNA-sequencing data were used to perform consensus clustering and weighted gene co-expression network analysis. We constructed a fibroblast-related prognostic model using least absolute shrinkage, selection operator regression, and Cox regression analysis. The prognostic model was validated using a validation dataset. Immune infiltration and functional enrichment analyses were conducted for patients in the high- and low-risk IPF groups.

Results

We characterized two fibroblast subtypes that are active in IPF (F3+ and ROBO2+). Using fibroblast-related genes, we identified five genes (CXCL14, TM4SF1, CYTL1, SOD3, and MMP10) for the prognostic model. The area under the curve values of our prognostic model were 0.852, 0.859, and 0.844 at one, two, and three years in the training set, and 0.837, 0.758, and 0.821 at one, two, and three years in the validation set, respectively.

Conclusion

This study annotates and characterizes different subtypes of fibroblasts in IPF.

Targeting S100A12 to Improve Angiogenesis and Accelerate Diabetic Wound Healing

Long-term inflammation and impaired angiogenesis are thought to be the causes of delayed healing or nonhealing of diabetic wounds. S100A12 is an essential pro-inflammatory factor involved in inflammatory reactions and serves as a biomarker for various inflammatory diseases. However, whether high level of S100A12 exists in and affects the healing of diabetic wounds, as well as the underlying molecular mechanisms, remain unclear. In this study, we found that the serum concentration of S100A12 is significantly elevated in patients with type 2 diabetes. Exposure of stratified epidermal cells to high glucose environment led to increased expression and secretion of S100A12, resulting in impaired endothelial function by binding to the advanced glycation endproducts (RAGE) or Toll-like receptor 4 (TLR4) on endothelial cell. The transcription factor Krüpple-like Factor 5 (KLF5) is highly expressed in the epidermis under high glucose conditions, activating the transcriptional activity of the S100A12 and boost its expression. By establishing diabetic wounds model in alloxan-induced diabetic rabbit, we found that local inhibition of S100A12 significantly accelerated diabetic wound healing by promoting angiogenesis. Our results illustrated the novel endothelial-specific injury function of S100A12 in diabetic wounds and suggest that S100A12 is a potential target for the treatment of diabetic wounds.

The role of fecal biomarkers in individuals with inflammatory bowel disease

INTRODUCTION

Inflammatory bowel disease (IBD), encompassing Crohn's disease (CD) and Ulcerative Colitis (UC), is a relapsing and remitting condition. Noninvasive biomarkers have an increasingly important role in the diagnosis of IBD and in the prediction of future disease course in individuals with IBD. Strategies for the management of IBD increasingly rely upon close monitoring of gastrointestinal inflammation.

AREAS COVERED

This review provides an update on the current understanding of established and novel stool-based biomarkers in the diagnosis and management of IBD. It also highlights key gaps, identifies limitations, and advantages of current markers, and examines aspects that require further study and analysis.

EXPERT OPINION

Current noninvasive inflammatory markers play an important role in the diagnosis and management of IBD; however, limitations exist. Future work is required to further characterize and validate current and novel markers of inflammation. In addition, it is essential to better understand the roles and characteristics of noninvasive markers to enable the appropriate selection to accurately determine the condition of the intestinal mucosa.

Identifying a survival-associated cell type based on multi-level transcriptome analysis in idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a progressive disease with a five-year survival rate of less than 40%. There is significant variability in survival time among IPF patients, but the underlying mechanisms for this are not clear yet.

METHODS AND RESULTS

We collected single-cell RNA sequence data of 13,223 epithelial cells taken from 32 IPF patients and bulk RNA sequence data from 456 IPF patients in GEO. Based on unsupervised clustering analysis at the single-cell level and deconvolution algorithm at bulk RNA sequence data, we discovered a special alveolar type 2 cell subtype characterized by high expression of CCL20 (referred to as ATII-CCL20), and found that IPF patients with a higher proportion of ATII-CCL20 had worse prognoses. Furthermore, we uncovered the upregulation of immune cell infiltration and metabolic functions in IPF patients with a higher proportion of ATII-CCL20. Finally, the comprehensive decision tree and nomogram were constructed to optimize the risk stratification of IPF patients and provide a reference for accurate prognosis evaluation.

CONCLUSIONS

Our study by integrating single-cell and bulk RNA sequence data from IPF patients identified a special subtype of ATII cells, ATII-CCL20, which was found to be a risk cell subtype associated with poor prognosis in IPF patients. More importantly, the ATII-CCL20 cell subtype was linked with metabolic functions and immune infiltration.

Identification of Neutrophil Extracellular Trap-Related Gene Expression Signatures in Ischemia Reperfusion Injury During Lung Transplantation: A Transcriptome Analysis and Clinical Validation

Purpose

Ischemia reperfusion injury (IRI) unavoidably occurs during lung transplantation, further contributing to primary graft dysfunction (PGD). Neutrophils are the end effectors of IRI and activated neutrophils release neutrophil extracellular traps (NETs) to further amplify damage. Nevertheless, potential contributions of NETs in IRI remain incompletely understood. This study aimed to explore NET-related gene biomarkers in IRI during lung transplantation.

Methods

Differential expression analysis was applied to identify differentially expressed genes (DEGs) for IRI during lung transplantation based on matrix data (GSE145989, 127003) downloaded from GEO database. The CIBERSORT and weighted gene co-expression network analysis (WGCNA) algorithms were utilized to identify key modules associated with neutrophil infiltration. Moreover, the least absolute shrinkage and selection operator regression and random forest were applied to identify potential NET-associated hub genes. Subsequently, the screened hub genes underwent further validation of an external dataset (GSE18995) and nomogram model. Based on clinical peripheral blood samples, immunofluorescence staining and dsDNA quantification were used to assess NET formation, and ELISA was applied to validate the expression of hub genes.

Results

Thirty-eight genes resulted from the intersection between 586 DEGs and 75 brown module genes, primarily enriched in leukocyte migration and NETs formation. Subsequently, four candidate hub genes (FCAR, MMP9, PADI4, and S100A12) were screened out via machine learning algorithms. Validation using an external dataset and nomogram model achieved better predictive value. Substantial NETs formation was demonstrated in IRI, with more pronounced NETs observed in patients with PGD ≥ 2. PADI4, S100A12, and MMP9 were all confirmed to be up-regulated after reperfusion through ELISA, with higher levels of S100A12 in PGD ≥ 2 patients compared with non-PGD patients.

Conclusion

We identified three potential NET-related biomarkers for IRI that provide new insights into early detection and potential therapeutic targets of IRI and PGD after lung transplantation.

Antifibrotic Drugs against Idiopathic Pulmonary Fibrosis and Pulmonary Fibrosis Induced by COVID-19: Therapeutic Approaches and Potential Diagnostic Biomarkers

The COVID-19 pandemic has had a significant impact on the health and economy of the global population. Even after recovery from the disease, post-COVID-19 symptoms, such as pulmonary fibrosis, continue to be a concern. This narrative review aims to address pulmonary fibrosis (PF) from various perspectives, including the fibrotic mechanisms involved in idiopathic and COVID-19-induced pulmonary fibrosis. On the other hand, we also discuss the current therapeutic drugs in use, as well as those undergoing clinical or preclinical evaluation. Additionally, this article will address various biomarkers with usefulness for PF prediction, diagnosis, treatment, prognosis, and severity assessment in order to provide better treatment strategies for patients with this disease.

The Association Between S100A12 Protein and C-Reactive Protein with Malignant Ventricular Arrhythmias Following Acute Myocardial Infarction in the Elderly

Objective

To investigate the association of S100A12 protein and C-reactive protein (CRP) with the onset of malignant ventricular arrhythmias (MVA) after acute myocardial infarction (AMI) in the elderly.

Methods

A total of 159 elderly AMI patients admitted to Chongming Hospital affiliated to Shanghai University of Medicine & Health Sciences from January 2018 to January 2023 were enrolled in the study. CRP levels were determined using an automatic biochemical analyzer, and S100A12 levels were measured using enzyme-linked immunosorbent assay (ELISA). Patients were categorized based on the Lown classification into groups without MVA and with MVA. Univariate analysis was initially performed to identify independent variables, followed by multivariate logistic regression to determine the risk factors for malignant ventricular arrhythmias post-AMI. The predictive value of S100A12 protein and CRP for malignant ventricular arrhythmias after acute myocardial infarction in the elderly was analyzed using the receiver operating characteristic (ROC) curve.

Results

Among the 159 patients with AMI, 27 (17%) had MVA. Multivariate logistic regression analysis indicated that both S100A12 protein and CRP could be independent risk factors for malignant ventricular arrhythmias following acute myocardial infarction in the elderly (p < 0.05). The area under the ROC curve showed the area under the curve (AUC) for S100A12 protein to be 0.7147, for CRP 0.7356, and for the combined diagnosis 0.8350 (p < 0.05).

Conclusion

S100A12 protein and CRP are independent risk factors for MVA after MI in the elderly. The combined application of S100A12 protein and CRP has higher diagnostic sensitivity and specificity.

Predictive biomarkers of disease progression in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial disease that cannot be cured, and treatment options for IPF are very limited. Early diagnosis, close monitoring of disease progression, and timely treatment are therefore the best options for patients due to the irreversibility of IPF. Effective markers help doctors judge the development and prognosis of disease. Recent research on traditional biomarkers (KL-6, SP-D, MMP-7, TIMPs, CCL18) has provided novel ideas for predicting disease progression and prognosis. Some emerging biomarkers (HE4, GDF15, PRDX4, inflammatory cells, G-CSF) also provide more possibilities for disease prediction. In addition to markers in serum and bronchoalveolar lavage fluid (BALF), some improvements related to the GAP model and chest HRCT also show good predictive ability for disease prognosis.

Identification of cuproptosis-related diagnostic biomarkers in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with clinical and pathological heterogeneity. Recent studies have identified cuproptosis as a novel cell death mechanism. However, the role of cuproptosis-related genes in the pathogenesis of IPF is still unclear. Two IPF datasets of the Gene Expression Omnibus database were studied. Mann-Whitney U test, correlation analysis, functional enrichment analyses, single-sample gene set enrichment analysis, CIBERSORT, unsupervised clustering, weighted gene co-expression network analysis, and receiver operating characteristic curve analysis were used to conduct our research. The dysregulated cuproptosis-related genes and immune responses were identified between IPF patients and controls. Two cuproptosis-related molecular clusters were established in IPF, the high immune score group (C1) and the low immune score group (C2). Significant heterogeneity in immunity between clusters was revealed by functional analyses results. The module genes with the strongest correlation to the 2 clusters were identified by weighted gene co-expression network analysis results. Seven hub genes were found using the Cytoscape software. Ultimately, 2 validated diagnostic biomarkers of IPF, CDKN2A and NEDD4, were obtained. Subsequently, the results were validated in GSE47460. Our investigation illustrates that CDKN2A and NEDD4 may be valid biomarkers that were useful for IPF diagnosis and copper-related clustering.

Prognostic significance of peripheral blood S100A12, S100A8, and S100A9 concentrations in idiopathic pulmonary fibrosis

BACKGROUND

S100A12, S100A8, and S100A9 are inflammatory disease biomarkers whose functional significance in idiopathic pulmonary fibrosis (IPF) remains unclear. We evaluated the significance of S100A12, S100A8, and S100A9 levels in IPF development and prognosis.

METHODS

The dataset was collected from the Gene Expression Omnibus (GEO) database and differentially expressed genes were screened using GEO2R. We conducted a retrospective study of 106 patients with IPF to explore the relationships between different biomarkers and poor outcomes. Pearson's correlation coefficient, Kaplan-Meier, Cox regression, and functional enrichment analyses were used to evaluate relationships between these biomarkers' levels and clinical parameters or prognosis.

RESULTS

Serum levels of S100A12, S100A8, and S100A9 were significantly elevated in patients with IPF. The two most significant co-expression genes of S100A12 were S100A8 and S100A9. Patients with levels of S100A12 (median 231.21 ng/mL), S100A9 (median 57.09 ng/mL) or S100A8 (median 52.20 ng/mL), as well as combined elevated S100A12, S100A9, and S100A8 levels, exhibited shorter progression-free survival and overall survival. Serum S100A12 and S100A8, S100A12 and S100A9, S100A9 and S100A8 concentrations also displayed a strong positive correlation (rs2 = 0.4558, rs2 = 0.4558, rs2 = 0.6373; P < 0.001). S100A12 and S100A8/9 concentrations were independent of FVC%, DLCO%, and other clinical parameters (age, laboratory test data, and smoking habit). Finally, in multivariate analysis, the serum levels of S100A12, S100A8, and S100A9 were significant prognostic factors (hazard ratio 1.002, P = 0.032, hazard ratio 1.039, P = 0.001, and hazard ratio 1.048, P = 0.003).

CONCLUSIONS

S100A12, S100A8, and S100A9 are promising circulating biomarkers that may aid in determining IPF patient prognosis. Multicenter clinical trials are needed to confirm their clinical value.

Circulating markers of extracellular matrix remodelling in severe COVID-19 patients

BACKGROUND

Abnormal remodelling of the extracellular matrix (ECM) has generally been linked to pulmonary inflammation and fibrosis and may also play a role in the pathogenesis of severe COVID-19. To further elucidate the role of ECM remodelling and excessive fibrogenesis in severe COVID-19, we examined circulating levels of mediators involved in various aspects of these processes in COVID-19 patients.

METHODS

Serial blood samples were obtained from two cohorts of hospitalised COVID-19 patients (n = 414). Circulating levels of ECM remodelling mediators were quantified by enzyme immunoassays in samples collected during hospitalisation and at 3-month follow-up. Samples were related to disease severity (respiratory failure and/or treatment at the intensive care unit), 60-day total mortality and pulmonary pathology after 3-months. We also evaluated the direct effect of inactivated SARS-CoV-2 on the release of the different ECM mediators in relevant cell lines.

RESULTS

Several of the measured markers were associated with adverse outcomes, notably osteopontin (OPN), S100 calcium-binding protein A12 and YKL-40 were associated with disease severity and mortality. High levels of ECM mediators during hospitalisation were associated with computed tomography thorax pathology after 3-months. Some markers (i.e. growth differential factor 15, galectin 3 and matrix metalloproteinase 9) were released from various relevant cell lines (i.e. macrophages and lung cell lines) in vitro after exposure to inactivated SARS-CoV-2 suggesting a direct link between these mediators and the causal agent of COVID-19.

CONCLUSION

Our findings highlight changes to ECM remodelling and particularly a possible role of OPN, S100A12 and YKL-40 in the pathogenesis of severe COVID-19.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

A comprehensive cuproptosis score and associated gene signatures reveal prognostic and immunological features of idiopathic pulmonary fibrosis

Background

Cuproptosis, the most recently identified and regulated cell death, depends on copper ions in vivo. Copper regulates the pathogenesis of Idiopathic pulmonary fibrosis (IPF), but the mechanism of action underlying cuproptosis in IPF remains unclear.

Methods

We identified three cuproptosis patterns based on ten cuproptosis-related genes using unsupervised consensus clustering. We quantified these patterns using a PCA algorithm to construct a cuproptosis score. ssGSEA and the Cibersort algorithm assessed the immune profile of IPF patients. GSEA and GSVA were used to analyze the functional differences in different molecular patterns. Drug susceptibility prediction based on cuproptosis scores and meaningful gene markers was eventually screened in combination with external public data sets,in vitro experiments and our cases.

Results

Of the three types of cuproptosis-related clusters identified in the study, patients in the clusterA, geneclusterB, and score-high groups showed improved prognoses. Moreover, each cluster exhibited differential immune characteristics, with the subtype showing a poorer prognosis associated with an immune overreaction. Cuproptosis score can be an independent risk factor for predicting the prognosis of IPF patients. GSEA showed a significant functional correlation between the score and cuproptosis. The genes AKAP9, ANK3, C6orf106, LYRM7, and MBNL1, were identified as prognostic-related signatures in IPF patients. The functional role of immune regulation in IPF was further explored by correlating essential genes with immune factors. Also, the nomogram constructed by cumulative information from gene markers and cuproptosis score showed reliable clinical application.

Conclusions

Cuproptosis patterns differ significantly in the prognosis and immune characteristics of IPF patients. The cuproptosis score and five gene signatures can provide a reliable reference in the prognosis and diagnosis of IPF.

IL18R1-Related Molecules as Biomarkers for Asthma Severity and Prognostic Markers for Idiopathic Pulmonary Fibrosis

To determine the role of inflammation-related proteins in predicting asthma severity and outcome, 92 inflammation-related proteins were measured in the asthmatic serum using Olink analysis. Different bioinformatics algorithms were developed to cross analyze with the single-cell or transcriptome data sets from the Gene Expression Omnibus database to explore the role of IL18R1 and related genes in asthma and idiopathic pulmonary fibrosis (IPF). Olink identified 52 differentially expressed proteins in asthma. They were strongly linked to the cytokine-cytokine receptor interaction, TNF, and NF-κB signaling pathway. Seven proteins were found in both single-cell RNA and Olink analyses. Among them, IL18R1 was predominantly expressed in mast cells, and the results suggested enhanced communication between mast cells and CD 8+ T cells. IL18R1 was upregulated in serum and induced sputum and bronchoalveolar lavage fluid of patients with uncontrolled or severe asthma. IL18R1 was positively correlated with TNFSF1 and OSM and S100A12. The diagnostic efficacy of these serum IL18R1-related molecules for asthma ranged from 0.839 to 0.921. Moreover, high levels of IL18R1, TNFSF1, OSM, and S100A12 were significantly associated with shorter survival times and worse lung function. IL18R1-related molecules may serve as biomarkers for monitoring uncontrolled or severe asthma and as prognostic markers for IPF.

Peripheral Blood Single-Cell Sequencing Uncovers Common and Specific Immune Aberrations in Fibrotic Lung Diseases

Rationale and Objectives

The extent and commonality of peripheral blood immune aberrations in fibrotic interstitial lung diseases are not well characterized. In this study, we aimed to identify common and distinct immune aberrations in patients with idiopathic pulmonary fibrosis (IPF) and fibrotic hypersensitivity pneumonitis (FHP) using cutting-edge single-cell profiling technologies.

Methods

Single-cell RNA sequencing was performed on patients and healthy controls' peripheral blood and bronchoalveolar lavage samples using 10X Genomics 5' gene expression and V(D)J profiling. Cell type composition, transcriptional profiles, cellular trajectories and signaling, and T and B cell receptor repertoires were studied. The standard Seurat R pipeline was followed for cell type composition and differential gene expression analyses. Transcription factor activity was imputed using the DoRothEA-VIPER algorithm. Pseudotime analyses were conducted using Monocle3, while RNA velocity analyses were performed with Velocyto, scVelo, and CellRank. Cell-cell connectomics were assessed using the Connectome R package. V(D)J analyses were conducted using CellRanger and Immcantation frameworks. Across all analyses, disease group differences were assessed using the Wilcoxon rank-sum test.

Measurements and Main Results

327,990 cells from 83 samples were profiled. Overall, changes in monocytes were common to IPF and FHP, whereas lymphocytes exhibited disease-specific aberrations. Both diseases displayed enrichment of CCL3 hi /CCL4 hi CD14+ monocytes (p<2.2e-16) and S100A hi CD14+ monocytes (p<2.2e-16) versus controls. Trajectory and RNA velocity analysis suggested that pro-fibrotic macrophages observed in BAL originated from peripheral blood monocytes. Lymphocytes exhibited disease-specific aberrations, with CD8+ GZMK hi T cells and activated B cells primarily enriched in FHP patients. V(D)J analyses revealed unique T and B cell receptor complementarity-determining region 3 (CDR3) amino acid compositions (p<0.05) in FHP and significant IgA enrichment in IPF (p<5.2e-7).

Conclusions

We identified common and disease-specific immune mechanisms in IPF and FHP; S100A hi monocytes and SPP1 hi macrophages are common to IPF and FHP, whereas GMZK hi T lymphocytes and T and B cell receptor repertoires were unique in FHP. Our findings open novel strategies for the diagnosis and treatment of IPF and FHP.

Identification of potential hub genes linked to immune and metabolic alterations in postoperative systemic inflammatory dysregulation

Background

Postoperative systemic inflammatory dysregulation (PSID) is characterised by strongly interlinked immune and metabolic abnormalities. However, the hub genes responsible for the interconnections between these two systemic alterations remain to be identified.

Methods

We analysed differentially expressed genes (DEGs) of individual peripheral blood nucleated cells in patients with PSID (n = 21, CRP > 250 mg/L) and control patients (n = 25, CRP < 75 mg/L) following major abdominal surgery, along with their biological functions. Correlation analyses were conducted to explore the interconnections of immune-related DEGs (irDEGs) and metabolism-related DEGs (mrDEGs). Two methods were used to screen hub genes for irDEGs and mrDEGs: we screened for hub genes among DEGs via 12 algorithms using CytoHubba in Cytoscape, and also screened for hub immune-related and metabolic-related genes using weighted gene co-expression network analysis. The hub genes selected were involved in the interaction between changes in immunity and metabolism in PSID. Finally, we validated our results in mice with PSID to confirm the findings.

Results

We identified 512 upregulated and 254 downregulated DEGs in patients with PSID compared with controls. Gene enrichment analysis revealed that DEGs were significantly associated with immune- and metabolism-related biological processes and pathways. Correlation analyses revealed a close association between irDEGs and mrDEGs. Fourteen unique hub genes were identified via 12 screening algorithms using CytoHubba in Cytoscape and via weighted gene co-expression network analysis. Among these, CD28, CD40LG, MAPK14, and S100A12 were identified as hub genes among both immune- and metabolism-related genes; these genes play a critical role in the interaction between alterations in immunity and metabolism in PSID. The experimental results also showed that the expression of these genes was significantly altered in PSID mice.

Conclusion

This study identified hub genes associated with immune and metabolic alterations in patients with PSID and hub genes that link these alterations. These findings provide novel insights into the mechanisms underlying immune and metabolic interactions and new targets for clinical treatment can be proposed on this basis.

Prognostic Value of Serum Biomarkers in Patients with Idiopathic Pulmonary Fibrosis in Relation to Disease Progression

BACKGROUND

The aim of this present study was to determine serum biomarker levels and their correlation with respiratory function and the clinical course of patients with idiopathic pulmonary fibrosis (IPF).

MATERIALS AND METHODS

This study included 72 IPF patients, according to the ATS/ERS criteria, in whom antifibrotic treatment was initiated. Blood samples were taken, and serum biomarkers, such as KL-6, SP-D, CCL18, CXCL13, VEGF-A, IL-8, IGFBP-1, IGFBP-2, IGFBP-7 and ICAM-1 were measured using ELISA methodology. Pulmonary function tests (FVC, TLC, DLCO-% pred) were determined at baseline and after 12 and 24 months and analyzed in correlation with the biomarkers.

RESULTS

The majority of patients (mean age 72 ± 6 years) were men (83%). The FVC and DLCO values at the 12-month follow-up were found to be statistically decreased in deceased patients (p < 0.05). The SP-D (p < 0.001) and the IGFBP-1 (p = 0.021) levels were found to be increased at the 1-year follow-up in deceased patients, and similarly, the SP-D (p = 0.005) and ICAM-1 (p = 0.043) levels at the 2-year follow-up. A chi-square test revealed that 70% of the category IV GAP index was found with cut-off elevated levels of a biomarker combination (KL-6, SP-D, VEGF-A) from the ROC curve analysis (p < 0.05).

CONCLUSION

This study provides evidence, for the first time in a Greek population, of the possibility of using a combination of KL-6, SP-D, and VEGF-A serum levels along with the GAP index.

A potential three-gene-based diagnostic signature for idiopathic pulmonary fibrosis

Background: Idiopathic pulmonary fibrosis (IPF) is a life-threatening disease whose etiology remains unknown. This study aims to explore diagnostic biomarkers and pathways involved in IPF using bioinformatics analysis. Methods: IPF-related gene expression datasets were retrieved and downloaded from the NCBI Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened, and weighted correlation network analysis (WGCNA) was performed to identify key module and genes. Functional enrichment analysis was performed on genes in the clinically significant module. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were run to screen candidate biomarkers. The expression and diagnostic value of the biomarkers in IPF were further validated in external test datasets (GSE110147). Results: 292 samples and 1,163 DEGs were screened to construct WGCNA. In WGCNA, the blue module was identified as the key module, and 59 genes in this module correlated highly with IPF. Functional enrichment analysis of blue module genes revealed the importance of extracellular matrix-associated pathways in IPF. IL13RA2, CDH3, and COMP were identified as diagnostic markers of IPF via LASSO and SVM-RFE. These genes showed good diagnostic value for IPF and were significantly upregulated in IPF. Conclusion: This study indicates that IL13RA2, CDH3, and COMP could serve as diagnostic signature for IPF and might offer new insights in the underlying diagnosis of IPF.

Deciphering the Function of New Therapeutic Targets and Prospective Biomarkers in the Management of Psoriasis

Psoriasis is an immune-mediated skin condition affecting people worldwide, presenting at any age, and leading to a substantial burden physically and mentally. The innate and adaptive immune systems interact intricately with the pathomechanisms that underlie disease. T cells can interact with keratinocytes, macrophages, and dendritic cells through the cytokines they secrete. According to recent research, psoriasis flare-ups can cause systemic inflammation and various other co-morbidities, including depression, psoriatic arthritis, and cardio-metabolic syndrome. Additionally, several auto-inflammatory and auto-immune illnesses may be linked to psoriasis. Although psoriasis has no proven treatment, care must strive by treating patients as soon as the disease surfaces, finding and preventing concurrent multimorbidity, recognising and reducing bodily and psychological distress, requiring behavioural modifications, and treating each patient individually. Biomarkers are traits that are assessed at any time along the clinical continuum, from the early stages of a disease through the beginning of treatment (the foundation of precision medicine) to the late stages of treatment (outcomes and endpoints). Systemic therapies that are frequently used to treat psoriasis provide a variety of outcomes. Targeted therapy selection, better patient outcomes, and more cost-effective healthcare would be made possible by biomarkers that reliably predict effectiveness and safety. This review is an attempt to understand the role of Antimicrobial peptides (AMP), Interleukin-38 (IL-38), autophagy 5 (ATG5) protein and squamous cell carcinoma antigen (SCCA) as biomarkers of psoriasis.

Review: The Development of Risk Factors and Cytokines in Retinal Vein Occlusion

Retinal vein occlusion (RVO) is the second most prevalent retinal disease. Despite this, the pathogenic mechanisms and risk factors are not entirely clear. In this article, we review recent publications on the classification, pathogenesis, risk factors, ischemic changes, cytokines, and vital complications of RVO. Risk factors and cytokines are important for exploring the mechanisms and new treatment targets. Furthermore, risk factors are interrelated, making RVO mechanisms more complex. Cytokines act as powerful mediators of pathological conditions, such as inflammation, neovascularization, and macular edema. This review aims to summarize the updated knowledge on risk factors, cytokines of RVO and signaling in order to provide valuable insight on managing the disease.