BACKGROUND Lung quantitative computed tomography (qCT) severe asthma clusters have been reported, but their replication and underlying disease mechanisms are unknown. We identified and replicated qCT clusters of severe asthma in two independent asthma cohorts and determined their association with molecular pathways, using radiomultiomics, integrating qCT, multiomics and machine learning/artificial intelligence. METHODS We used consensus clustering on qCT measurements of airway and lung CT scans, performed in 105 severe asthmatic adults from the U-BIOPRED cohort. The same qCT measurements were used to replicate qCT clusters in a subsample of the ATLANTIS asthma cohort (n=97). We performed integrated enrichment analysis using blood, sputum, bronchial biopsies, bronchial brushings and nasal brushings transcriptomics and blood and sputum proteomics to characterise radiomultiomic-associated clusters (RACs). RESULTS qCT clusters and clinical features in U-BIOPRED were replicated in the matched ATLANTIS cohort. In the U-BIOPRED cohort, RAC1 (n=30) was predominantly female with elevated body mass index, mild airflow limitation, decreased CT lung volume and increased lung density and upregulation of the complement pathway. RAC2 (n=34) subjects had airway wall thickness and a mild degree of airflow limitation, with upregulation of proliferative pathways including neurotrophic receptor tyrosine kinase 2/tyrosine kinase receptor B, and downregulation of semaphorin pathways. RAC3 (n=41) showed increased lung attenuation area and air trapping, severe airflow limitation, hyperinflation, and upregulation of cytokine signalling and signalling by interleukin pathways, and matrix metallopeptidase 1, 2 and 9. CONCLUSIONS U-BIOPRED severe asthma qCT clusters were replicated in a matched independent asthmatic cohort and associated with specific molecular pathways. Radiomultiomics might represent a novel strategy to identify new molecular pathways in asthma pathobiology.

中文翻译：

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放射多组学：与多组学相关的严重哮喘的定量 CT 集群。


背景 肺定量计算机断层扫描 （qCT） 严重哮喘集群已有报道，但其复制和潜在疾病机制尚不清楚。我们在两个独立的哮喘队列中识别并复制了严重哮喘的 qCT 集群，并使用放射多组学、整合 qCT 、多组学和机器学习/人工智能确定了它们与分子途径的关联。方法 我们对来自 U-BIOPRED 队列的 105 名严重哮喘成人进行的气道和肺部 CT 扫描的 qCT 测量使用了共识聚类。相同的 qCT 测量值用于复制 ATLANTIS 哮喘队列 （n=97） 亚样本中的 qCT 集群。我们使用血液、痰液、支气管活检、支气管刷牙和刷鼻转录组学以及血液和痰液蛋白质组学进行了综合富集分析，以表征放射多组学相关集群 （RAC）。结果 U-BIOPRED 中的 qCT 集群和临床特征在匹配的 ATLANTIS 队列中复制。在 U-BIOPRED 队列中，RAC1 （n=30） 主要是女性，体重指数升高、轻度气流受限、CT 肺容量减少和肺密度增加以及补体途径上调。RAC2 （n=34） 受试者具有气道壁厚度和轻度气流受限，增殖途径上调，包括神经营养受体酪氨酸激酶 2/酪氨酸激酶受体 B，以及信号素通路下调。RAC3 （n=41） 显示肺衰减面积和空气潴留增加、严重的气流受限、过度充气以及细胞因子信号和白细胞介素途径以及基质金属肽酶 1、2 和 9 的信号传导上调。 结论 U-BIOPRED 严重哮喘 qCT 集群在匹配的独立哮喘队列中复制，并与特定分子通路相关。放射多组学可能代表了一种在哮喘病理生物学中识别新分子途径的新策略。