Transcriptomic profiling in Mycobacterium avium complex pulmonary disease identifies clusters linked to disease severity and neutrophil activation

医学 肺病 基因表达谱 疾病 转录组 仿形(计算机编程) 免疫学 呼吸道疾病 发病机制 复杂疾病 星团(航天器) 生物信息学 疾病严重程度 基因表达调控 慢性阻塞性肺病 基因 基因表达
作者
Chio Sakai,Mizu Nonaka,Masashi Matsuyama,Sosuke Matsumura,Masayuki Nakajima,Kodai Ueda,Naoki Arai,Yuko Morishima,Masafumi Muratani,Yukio Ishii,Takefumi Saito,Nobuyuki Hizawa
出处
期刊:American Journal of Respiratory and Critical Care Medicine [American Thoracic Society]
卷期号:212 (3): 625-641 被引量:2
标识
DOI:10.1164/rccm.202503-0665oc
摘要

RATIONALE: Mycobacterium avium complex (MAC) pulmonary disease presents with heterogeneous clinical phenotypes. OBJECTIVES: This study aimed to elucidate the heterogeneity of MAC pulmonary disease by analyzing gene expression profiles in whole blood cells and identifying factors contributing to its pathogenesis, treatment response, and disease severity. METHODS: A total of 100 patients with MAC pulmonary disease newly treated with guideline-based therapy (GBT) were analyzed prospectively, and RNA-sequencing was performed on whole blood cells. Unsupervised cluster analysis, differentially -expressed gene (DEG) analysis, and logistic least absolute shrinkage and selection operator regression were performed to identify key genes of the severe cluster. The expressions of these genes were validated in mice infected with M. avium bacteria. MEASUREMENTS AND MAIN RESULTS: The cluster analysis identified 3 distinct patient clusters, each with unique clinical characteristic and treatment responses. Notably, Cluster 3 (C3) showed high neutrophil counts, older age, severe disease manifestations, and poor survival, despite sputum culture conversion. DEG analysis identified 6 neutrophil-related genes, FTH1, C19orf59 (MCEMP1), S100A9, SELL, ISG15, and IFITM1, as characteristic of C3. Furthermore, high expression of these genes correlated significantly with poor survival in both the present cohort and a previously reported cohort of pulmonary nontuberculous mycobacterial disease patients. M. avium infection increased S100A9 expression, particularly in old, but not young, mouse lungs, suggesting that increased S100A9 expression is associated with aging and infection. CONCLUSIONS: Gene expression profiling in MAC pulmonary disease patients identified 3 distinct clusters, with the most severe cluster characterized by neutrophil activation. Six genes were associated with disease severity and prognosis, though their causal roles require further investigation.
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