The role of cellular senescence-related genes in Asthma: Insights from bioinformatics and animal experiments.

BACKGROUND: Asthma is a heterogeneous chronic respiratory disease, affecting about 10% of the global population. Cellular senescence is a multifaceted phenomenon defined as the irreversible halt of the cell cycle, commonly referred to as the senescence-associated secretory phenotype. Recent studies suggest that cellular senescence may play a role in asthma. This study aims to dissect the role and biological mechanisms of CSRGs in asthma, enhancing our understanding of the progression of asthma. METHODS: The study utilized the GSE147878 dataset, employing methods like WGCNA, Differential analysis, Cibersort, GO, KEGG, unsupervised clustering, and GSVA to explore CSRGs functions and immune cell patterns in asthma. Machine learning identified key diagnostic genes, validated externally with the GSE165934 dataset and through qRT-PCR and WB experiments in animal models. RESULT: From the GSE147878 dataset, 24 CSRGs were identified, highlighting their role in immune and inflammatory processes in asthma. Differences in CD4 naive T cells and activated dendritic cells between asthma and control groups underscored CSRGs' role in immune regulation. Cluster analysis revealed two distinct asthma patient groups with unique immune microenvironments. Machine learning identified five genes, leading to a TF-miRNA-mRNA network and singling out RHOA and RBM39 as key diagnostic genes, which were experimentally validated. Finally, a nomogram was created based on these genes. CONCLUSION: This study, utilizing bioinformatics and animal experiments, identified RHOA and RBM39 as key diagnostic genes for asthma, providing new insights into the potential role and biological mechanisms of CSRGs in asthma.

Metagenomic Next-Generation Sequencing Can Clinch Diagnosis of Non-Tuberculous Mycobacterial Infections: A Case Report.

Non-tuberculou Mycobacteria (NTM) is ubiquitous in the environment and is conditional pathogen. Due to NTM and Mycobacterium tuberculosis belong to the genus Mycobacterium, their pathogenic mechanisms and clinical manifestations are similar. Therefore, NTM can cause tuberculosis-like lesions and lead to misdiagnosis. Early diagnosis and treatment greatly improve prognosis. However, traditional pathogenic microorganism detection has limitations, and it is difficult to accurately identify strains in clinical practice. Here, we report a 65-year-old man with NTM who presented with recurrent fever and cough. Computed tomography of the chest revealed a lung infection. The previous improper diagnosis and treatment did not improve his condition. With the aid of metagenomic next-generation sequencing, the pathogen was identified as Mycobacterium avium complex. Subsequently, he received accurate treatment and made significant improvements in clinical and radiology.