Toll-Like Receptor Characterization Correlates with Asthma and Is Predictive of Diagnosis

Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation

BACKGROUND

Asthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood. This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease.

METHODS

The gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between asthma and healthy control groups. Finally, the expression level of TLR7 was validated in induced sputum samples of patients with asthma.

RESULTS

A total of 320 differential expression genes between the asthma and healthy control groups were screened, including 184 upregulated genes and 136 downregulated genes. TLR7 was identified as the core gene after combining the results of LASSO regression, SVM-RFE algorithm, and top 10 hub genes. Significant differences were observed in the distribution of 13 out of 22 infiltrating immune cells in asthma. TLR7 was found to be closely related to the level of several infiltrating immune cells. TLR7 mRNA levels were downregulated in asthmatic patients compared with healthy controls (p = 0.0049). The area under the curve of TLR7 for the diagnosis of asthma was 0.7674 (95% CI 0.631-0.904, p = 0.006). Moreover, TLR7 mRNA levels were negatively correlated with exhaled nitric oxide fraction (r = - 0.3268, p = 0.0347) and the percentage of peripheral blood eosinophils (%) (r = - 0.3472, p = 0.041), and positively correlated with forced expiratory volume in the first second (FEV1) (% predicted) (r = 0.3960, p = 0.0071) and FEV1/forced vital capacity (r = 0.3213, p = 0.0314) in asthmatic patients.

CONCLUSIONS

Decreased TLR7 in the induced sputum of eosinophilic asthmatic patients was involved in immune cell infiltration and airway inflammation, which may serve as a new biomarker for the diagnosis of eosinophilic asthma.

TREM1 is involved in the mechanism between asthma and lung cancer by regulating the Toll‑like receptor signaling pathway

Lung cancer and asthma are both global health problems with significant economic consequences. Recent studies have demonstrated that asthma may be a risk factor for lung cancer. The present study aimed to explore the pathogenesis between these two diseases through a comprehensive analysis. Differentially expressed genes (DEGs) screened in the asthma-related GSE165934 dataset were analyzed to find relevant inflammatory pathways. Overlapping genes regulated by inflammatory pathways and lung cancer-DEGs from The Cancer Genome Atlas (TCGA) were obtained and subjected to survival and gene-wide mutation analyses, and nomogram construction to determine the hub gene. The hub gene was further analyzed through expression validation, immunoassays and functional experiments to investigate its role and mechanism in lung cancer. Functional enrichment analysis showed that 1,275 DEGs from GSE165934 were closely associated with the Toll-like receptor signaling pathway, and 8 overlapping genes were identified from 12 genes regulated by the Toll-like receptor signaling pathway and 3,134 TCGA-DEGs. After a series of bioinformatics analyses, it was found that triggering receptor expressed on myeloid cells 1 (TREM1) was the hub gene involved in the mechanism of asthma and lung cancer. TREM1 was also found to be a suppressor gene in lung cancer correlated with immune cells, immune checkpoint-related genes and tumor mutational burden score. Additionally, the results of Cell Counting Kit-8 and Transwell experiments demonstrated that overexpression of TREM1 could significantly inhibit the invasion, proliferation and migration of lung cancer cells. Reverse transcription-quantitative PCR and western blotting demonstrated that the overexpression of TREM1 could also significantly reduce the level of Toll-like receptor signaling pathway proteins. The present findings suggest that TREM1 is associated with the mechanism of asthma and lung cancer through its regulation of the Toll-like receptor signaling pathway. Furthermore, TREM1 may serve as a potential treatment target and prognostic indicator for patients with lung cancer.

Identification of cuproptosis-related asthma diagnostic genes by WGCNA analysis and machine learning

OBJECTIVE

Cuproptosis is the latest novel form of cell death. However, the relationship between asthma and cuproptosis is not fully understood.

METHODS

In this study, we screened differentially expressed cuproptosis-related genes from the Gene Expression Omnibus (GEO) database and performed immune infiltration analysis. Subsequently, patients with asthma were typed and analyzed by Kyoto Encyclopedia of Genes and Genomes (KEGG). Weighted gene co-expression network analysis (WGCNA) was performed to calculate the module-trait correlations, and the hub genes of the intersection were taken to construct machine learning (XGB, SVM, RF, GLM). Finally, we used TGF-β to establish a BEAS-2B asthma model to observe the expression levels of hub genes.

RESULTS

Six cuproptosis-related genes were obtained. Immune-infiltration analysis shows that cuproptosis-related genes are associated with a variety of biological functions. We classified asthma patients into two subtypes based on the expression of cuproptosis-related genes and found significant Gene Ontology (GO) and immune function differences between the different subtypes. WGCNA selected 2 significant modules associated with disease features and typing. Finally, we identified TRIM25, DYSF, NCF4, ABTB1, CXCR1 as asthma biomarkers by taking the intersection of the hub genes of the 2 modules and constructing a 5-genes signature, which nomograph, decision curve analysis (DCA) and calibration curves, receiver operating characteristic curve (ROC) showed high efficiency in diagnosing the probability of survival of asthma patients. Finally, in vitro experiments have shown that DYSF and CXCR1 expression is up expressed in asthma.

CONCLUSIONS

Our study provides further directions for studying the molecular mechanism of asthma.

HMGB1 is a promising therapeutic target for asthma

High-mobility group box protein 1 (HMGB1) is a non-histone deoxyribonucleic acid-binding nuclear protein. In physiological state it is involved in gene transctioripn regulation and cell replication, differentiation and maturation. HMGB1 is actively secreted into the extracellular space in the form of intracellular vesicles, upon stimulation of inflammation and infection, by monocytes, macrophages, dendritic cells (DCs), and other immune cells, and can also be passively released by necrotic or injured cells. After binding with the corresponding receptors, HMGB1 can activate the downstream substrate and trigger a series of biological effects. HMGB1 was mainly dependent on toll-like re ceptors (TLR) 2 and 4, and receptors for advanced glycation end products (RAGE) to trigger intracellular signal transduction, and mediate innate and adoptive immune responses. Besides these, studies have reported the participation of TLR3, TLR9, T-cell immunoglobulin mucin (TIM) 3, CD24, anti-N-methyl-D-aspartate receptor (NMDAR) in Th2 inflammatory response, eosinophilic airway inflammation, and airway hyperresponsiveness, mediated by HMGB1 in asthma. Both clinical and experimental studies suggested that HMGB1 was involved in the pathogenesis of asthma probably by regulating the downstream signaling pathways via corresponding receptors. This article reviews the role of HMGB1 in pathogenesis of asthma, and provides a new theoretical basis for the diagnosis and treatment of asthma.

Association of Toll-like receptors 4 (TLR-4) gene expression and polymorphisms in patients with severe asthma

Innate immunity plays a central role in the pathogenesis of severe asthma, and it is closely linked to elevated IgE and Toll-like receptor 4 (TLR-4) levels. However, there is a scarcity of information about the association of the TLR-4 receptor polymorphism in the pathogenesis of severe asthma. This study highlights the level of gene expression of different alleles in asthmatic patients compared to healthy control individuals. This was a randomized control trial, which included 150 patients with asthma (with high serum levels of IgE) with a matching 150 healthy control individuals. Participants had a series of blood tests to measure various immune parameters: interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor (TNF), intercellular adhesion molecule-1 (ICAM1) and detect allele type and gene expression of the TLR-4 gene. Patients with asthma had significantly higher levels of IL-8 when compared to the healthy control participants. In addition, in the rs91 genotyping, there were significant differences in the levels of IL-8 and TNF between CC and TT genotyping. While in rs90 TLR-4, TNF levels were significantly higher in AA vs. AG and GG genotypes among the asthmatic patients when compared to the control group. The results showed that in TLR-4, rs4986791 were significantly associated with asthma risk. Polymorphisms in TLRs play essential roles in asthma.

Molecular mechanisms of An-Chuan Granule for the treatment of asthma based on a network pharmacology approach and experimental validation

An-Chuan Granule (ACG), a traditional Chinese medicine (TCM) formula, is an effective treatment for asthma but its pharmacological mechanism remains poorly understood. In the present study, network pharmacology was applied to explore the potential mechanism of ACG in the treatment of asthma. The tumor necrosis factor (TNF), Toll-like receptor (TLR), and Th17 cell differentiation-related, nucleotide-binding oligomerization domain (NOD)-like receptor, and NF-kappaB pathways were identified as the most significant signaling pathways involved in the therapeutic effect of ACG on asthma. A mouse asthma model was established using ovalbumin (OVA) to verify the effect of ACG and the underlying mechanism. The results showed that ACG treatment not only attenuated the clinical symptoms, but also reduced inflammatory cell infiltration, mucus secretion and MUC5AC production in lung tissue of asthmatic mice. In addition, ACG treatment notably decreased the inflammatory cell numbers in bronchoalveolar lavage fluid (BALF) and the levels of pro-inflammatory cytokines (including IL-6, IL-17, IL-23, TNF-alpha, IL-1beta and TGF-beta) in lung tissue of asthmatic mice. In addition, ACG treatment remarkably down-regulated the expression of TLR4, p-P65, NLRP3, Caspase-1 and adenosquamous carcinoma (ASC) in lung tissue. Further, ACG treatment decreased the expression of receptor-related orphan receptor (RORγt) in lung tissue but increased that of Forkhead box (Foxp3). In conclusion, the above results demonstrate that ACG alleviates the severity of asthma in a ´multi-compound and multi-target’ manner, which provides a basis for better understanding of the application of ACG in the treatment of asthma.

Interferon characterization associates with asthma and is a potential biomarker of predictive diagnosis

Interferon (IFN) plays a role in immune and inflammation responses. However, the effect of IFN in asthma is still not fully clear. The present study was conducted to better understand the role of IFN signatures in asthma. Blood samples from case–control studies (study 1: 348 asthmas and 39 normal controls and validation study 2: 411 asthmas and 87 normal controls) were enrolled. The single-sample gene set enrichment analysis (ssGSEA) method was used to quantify the levels of 74 IFN signatures. Gene Ontology analysis and pathway function analysis were performed for functional analysis and a protein–protein interaction (PPI) network was constructed. The area under the curve (AUC) value was used to evaluate the diagnostic ability. In our work, IFN-γ response-DN, negative regulation of IFN-γ secretion, IFNG pathway, negative regulation of response to IFN-γ, and type 1 IFN biosynthetic process showed higher levels in asthma. Functional analysis demonstrated that pathway and biological process involved in IFN signaling pathway, regulation of type 1 IFN production and response to IFN-γ. Hub IFN-related genes were identified, and their combination as biomarker exhibited a good diagnostic capacity for asthma (AUC = 0.832). These findings offered more insight into the underlying mechanism of how IFN signatures affected asthma. The use of the easy-to-apply IFN-related genes might serve as a promising blood-based biomarker for early diagnosis of asthma.