痰液转录组分析与聚类揭示哮喘异质性新见解
2025/08/31
摘要
背景：哮喘是一种由不同炎症通路驱动的异质性疾病。本研究旨在分析哮喘患者的转录组特征，并将其与炎症反应、气道损伤及肺功能进行关联性研究。
方法：基于分支定界分析结果，我们选取了七种常见合并症（即鼻炎、胃食管反流病、呼吸模式障碍、肥胖、支气管扩张、非甾体抗炎药加重性呼吸疾病及阻塞性睡眠呼吸暂停）纳入MiDAS模型，并采用多元线性回归法将其整合，最终建立与WATCH研究中m-ASSESS评估指标相关联的MiDAS模型。
结果：MiDAS评分范围为9.6-16.2。在WATCH研究群体中，MiDAS平均值为11.97（标准差1.21），且与m-ASSESS中哮喘控制不佳（τ=0.31 [95% CI 0.24-0.38]）和急性发作（τ=0.16 [0.08-0.24]）两个组分呈名义相关性。MiDAS还与圣乔治呼吸问卷总分恶化（r=0.39 [95% 0.28-0.49], p<0.0001）及促炎性血浆细胞因子IL-4（r=0.19 [95% CI 0.06-0.31], p=0.0036）、IL-5（r=0.35 [0.24-0.46], p<0.0001）和瘦素（r=0.29 [0.17-0.40], p<0.0001）水平显著相关。四个国际队列的MiDAS值与英国WATCH队列结果相似：澳大利亚队列均值为12.33（标准差1.47）和12.31（1.37），美国队列为11.80（1.20），新加坡队列为11.55（1.23）。这些队列中MiDAS均与哮喘控制恶化、生活质量下降、焦虑抑郁及炎症加重相关。
结论：本研究通过跨越经典2型/非2型分类的框架，成功识别出三种不同的哮喘聚类亚型。
Sputum Transcriptomic Analysis and Clustering Reveals Insight Into Asthma Heterogeneity
Goossens, J., Jonckheere, A. C., De Boodt, S., Dilissen, E., Marain, N., Decaesteker, T., Cortes, A., Vanoirbeek, J. A., Seys, S. F., Dupont, L., & Bullens, D. M. A.
Abstract
BACKGROUND:Asthma is a heterogenous disease shaped by different inflammatory pathways. The aim is to investigate transcriptomic profiles in asthmatic patients and associate these with inflammation, airway damage and lung function.
METHODS:We selected seven common comorbidities (ie, rhinitis, gastro-oesophageal reflux disease, breathing pattern disorder, obesity, bronchiectasis, non-steroidal anti-inflammatory drug-exacerbated respiratory disease, and obstructive sleep apnoea) for inclusion in MiDAS on the basis of the branch-and-bound analysis and combined them using multivariate linear regression to derive a MiDAS model associated with m-ASSESS in WATCH.
RESULTS:The range of MiDAS scores was 9·6-16·2. In WATCH members, mean MiDAS value was 11·97 (SD 1·21) and MiDAS was nominally correlated with m-ASSESS components of poor asthma control (τ=0·31 [95% CI 0·24-0·38]) and exacerbations (τ=0·16 [0·08-0·24]). MiDAS was also correlated with worse total SGRQ score (r=0·39 [95% 0·28-0·49], p<0·0001) and with the proinflammatory plasma cytokines interleukin (IL)-4 (r=0·19 [95% CI 0·06-0·31], p=0·0036), IL-5 (r=0·35 [0·24-0·46], p<0·0001), and leptin (r=0·29 [0·17-0·40], p<0·0001) in WATCH. MiDAS values across the four international cohorts were similar to those of WATCH (UK cohort), with mean values of 12·33 (SD 1·47) and 12·31 (1·37) in the Australian cohorts, 11·80 (1·20) in the USA cohort, and 11·55 (1·23) in the Singapore cohort. In these cohorts, MiDAS correlated with worse asthma control, worse quality of life, anxiety, depression, and increased inflammation.
CONCLUSION:Three different asthma clusters could be identified bridging over the classical type 2/non-type 2 classification.
背景：哮喘是一种由不同炎症通路驱动的异质性疾病。本研究旨在分析哮喘患者的转录组特征，并将其与炎症反应、气道损伤及肺功能进行关联性研究。
方法：基于分支定界分析结果，我们选取了七种常见合并症（即鼻炎、胃食管反流病、呼吸模式障碍、肥胖、支气管扩张、非甾体抗炎药加重性呼吸疾病及阻塞性睡眠呼吸暂停）纳入MiDAS模型，并采用多元线性回归法将其整合，最终建立与WATCH研究中m-ASSESS评估指标相关联的MiDAS模型。
结果：MiDAS评分范围为9.6-16.2。在WATCH研究群体中，MiDAS平均值为11.97（标准差1.21），且与m-ASSESS中哮喘控制不佳（τ=0.31 [95% CI 0.24-0.38]）和急性发作（τ=0.16 [0.08-0.24]）两个组分呈名义相关性。MiDAS还与圣乔治呼吸问卷总分恶化（r=0.39 [95% 0.28-0.49], p<0.0001）及促炎性血浆细胞因子IL-4（r=0.19 [95% CI 0.06-0.31], p=0.0036）、IL-5（r=0.35 [0.24-0.46], p<0.0001）和瘦素（r=0.29 [0.17-0.40], p<0.0001）水平显著相关。四个国际队列的MiDAS值与英国WATCH队列结果相似：澳大利亚队列均值为12.33（标准差1.47）和12.31（1.37），美国队列为11.80（1.20），新加坡队列为11.55（1.23）。这些队列中MiDAS均与哮喘控制恶化、生活质量下降、焦虑抑郁及炎症加重相关。
结论：本研究通过跨越经典2型/非2型分类的框架，成功识别出三种不同的哮喘聚类亚型。
（中日友好医院呼吸与危重症医学科 沈焜路 摘译 林江涛 审校）
（Lung. 2025 Aug 20;203(1):89; DOI: 10.1007/s00408-025-00843-1）
Sputum Transcriptomic Analysis and Clustering Reveals Insight Into Asthma Heterogeneity
Goossens, J., Jonckheere, A. C., De Boodt, S., Dilissen, E., Marain, N., Decaesteker, T., Cortes, A., Vanoirbeek, J. A., Seys, S. F., Dupont, L., & Bullens, D. M. A.
Abstract
BACKGROUND:Asthma is a heterogenous disease shaped by different inflammatory pathways. The aim is to investigate transcriptomic profiles in asthmatic patients and associate these with inflammation, airway damage and lung function.
METHODS:We selected seven common comorbidities (ie, rhinitis, gastro-oesophageal reflux disease, breathing pattern disorder, obesity, bronchiectasis, non-steroidal anti-inflammatory drug-exacerbated respiratory disease, and obstructive sleep apnoea) for inclusion in MiDAS on the basis of the branch-and-bound analysis and combined them using multivariate linear regression to derive a MiDAS model associated with m-ASSESS in WATCH.
RESULTS:The range of MiDAS scores was 9·6-16·2. In WATCH members, mean MiDAS value was 11·97 (SD 1·21) and MiDAS was nominally correlated with m-ASSESS components of poor asthma control (τ=0·31 [95% CI 0·24-0·38]) and exacerbations (τ=0·16 [0·08-0·24]). MiDAS was also correlated with worse total SGRQ score (r=0·39 [95% 0·28-0·49], p<0·0001) and with the proinflammatory plasma cytokines interleukin (IL)-4 (r=0·19 [95% CI 0·06-0·31], p=0·0036), IL-5 (r=0·35 [0·24-0·46], p<0·0001), and leptin (r=0·29 [0·17-0·40], p<0·0001) in WATCH. MiDAS values across the four international cohorts were similar to those of WATCH (UK cohort), with mean values of 12·33 (SD 1·47) and 12·31 (1·37) in the Australian cohorts, 11·80 (1·20) in the USA cohort, and 11·55 (1·23) in the Singapore cohort. In these cohorts, MiDAS correlated with worse asthma control, worse quality of life, anxiety, depression, and increased inflammation.
CONCLUSION:Three different asthma clusters could be identified bridging over the classical type 2/non-type 2 classification.
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