应用诱导痰转录组学研究重症哮喘内型、筛选预测/治疗生物标志物

The bottleneck problem that limits the big breakthrough of treatments for severe asthma, is attributed to heterogeneity and complicated pathogenic mechanisms, which differs from that in mild and moderate asthma. Until now, several clinical phenotypes of asthma have been defined which could improve our understanding of the heterogeneity of asthma, but these phenotypes, in isolation, do not identify the immunopathology that makes these clinical phenotypes distinct or makes it be difficult to search for a novel promising therapy. According to the recent hypothesis of asthma and "endotypes", we will use induced sputum-based transcriptomics, and hierarchical clustering analysis to define grouping of severe asthma endotypes, which are the integration of demographic, clinical, pathogenic, and transcriptome characteristics. Moreover, we will identify the differential components of the transcriptome between endotypes of severe asthma, explore the relationship between endotypes and the future risk of asthma outcomes, and screen for predictive and therapeutic biomarkers for severe asthma at translational level. Thus, we will establish a specimen bank of induced sputum and a database of severe asthma that could be the foundation for a severe asthma research program of China, provide evidence for elaborating pathogenic mechanisms, education and management of severe asthma, and screening novel therapies of severe asthma.

重症哮喘相关治疗一直无突破性进展的瓶颈，极大程度归结于重症哮喘的异质性和尚未完全明了且与轻、中度哮喘迥异的复杂病理机制。尽管应用临床表型（phenotype）对哮喘进行分类，可加深对哮喘异质性的认识，但这些临床表型，相对"孤立"，病理机制不明确，亦难以发现哮喘治疗新方法。本项目拟从重症哮喘异质性出发，从新近"哮喘内型（endotype）"假说入手，应用转录组学技术，诱导痰方法，从转化医学角度，采用分层聚类方法定义重症哮喘内型及其人口学、临床、病理和系统生物学特征，并分析重症哮喘内型间的转录组成分差异，及转录组信息与哮喘结局远期风险的关系，从转录组水平筛选具有预测和治疗前景的生物学标志物（biomarker）。若以上设想得以实施，（1）有望在西部建立重症哮喘诱导痰标本库/数据库，（2）为阐释重症哮喘病理新机制、规范重症哮喘教育和管理提供证据；（3）可望为发现重症哮喘治疗新方法提供科学证据。

支气管哮喘（简称哮喘）是一异质性疾病，通常采用不同的炎症表型来定义，但是尚没有研究观察基于诱导痰肥大细胞（mast cell, MC）的哮喘表型。应用痰诱导方法收集健康受试者（n=16）和慢性持续期哮喘患者（n=55）痰液，对痰液进行炎症细胞分类计数，并采用全基因组基因表达基因芯片分析诱导痰基因表达。诱导痰MC表型根据MC生物标志物（tryptase [TPSAB1], chymase [CMA1] and carboxypeptidase [CPA3]）进行分类。MC表型的差异基因表达应用qPCR方法进行验证。结果显示在哮喘患者中，我们成功确认了Non-MC（n=8）、MCTC（n=29）和MCT（n=18）三种临床表型。与其他MC表型比较，MCTC亚型的FENO、诱导痰嗜酸粒细胞比例和数量、支气管高反应明显增加，而哮喘控制水平明显较低。而且，MCTC亚型显示TPSAB1, CPA3, CD1A, CD1B, CD1C, CEBPE, CLC, CLEC4F, DNASE1L3, GPR56, HDC, FCER1A, CACNG6, CLEC10A和LTC4S基因表达明显增加。诱导痰嗜酸粒细胞比例和数量与TPSAB1（r=0.57, P<0.001和r=0.57, P<0.001）和CPA3 (r=0.68, P<0.001和 r=0.65, P<0.001)明显相关，但多因素Logistic回归模型显示，仅CPA3 (OR=1.21, 95% CI=[1.07, 1.37], P=0.004)而不是TPSAB1 (OR=0.92, 95%CI=[0.73, 1.17], P=0.502)与嗜酸粒细胞性哮喘 （eosinophilic asthma, EA）相关。我们的研究成功建立了诱导痰基于哮喘MC临床表型。MCTC亚型展示出较高的气道高反应性，并在EA发病机制中起着重要作用。靶向MCTC临床表型或许是针对EA的糖皮质激素的替代治疗方法。

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