低2型生物标志物重度哮喘和哮喘控制中的血液转录组学特征
2023/07/21
摘要
背景：尽管皮质类固醇可以抑制T2炎症，但低2型（T2）细胞因子-重症哮喘患者通常仍有持续症状。
目的：我们试图分析738例严重哮喘T2生物标志物高/低患者的全血转录组，以将转录组特征与T2生物标志和哮喘症状评分联系起来。
方法：从301名参与者的血液样本（基线，第24周，第48周）中生成大量RNA-seq数据，这些参与者被招募到一项重症哮喘皮质类固醇优化的随机临床试验中。进行了无监督聚类、差异基因表达分析和通路分析。根据T2生物标志物状态和症状对患者进行分组。研究了临床特征与生物标志物和症状水平相关的差异表达基因（DEGs）之间的关系。
结果：无监督聚类识别出2个聚类；第2组患者的血液嗜酸性粒细胞水平较低/症状较高，更有可能接受口服皮质类固醇（OCSs）治疗。对这些聚类的差异基因表达分析，在有和没有OCSs分层的情况下，分别鉴定了2960个和4162个DEG。2960个基因中的627个在通过减去OCS特征基因对OCSs进行调整后仍然存在。途径分析表明，二磷酸低聚多糖生物合成和RNA聚合酶I复合物的组装是显著富集的途径。在T2生物标志物低的患者中，没有稳定的DEG与高症状相关，但许多DEG与T2生物标记物升高相关，包括15个在所有时间点上调的DEG，而与症状水平无关。
结论：OCSs对全血转录组有显著影响。差异基因表达分析显示了明确的T2生物标志物转录组学特征，但没有发现与低T2生物标志患者（包括症状负担高的患者）相关的特征。
Blood transcriptomic signature in type-2 biomarker-low severe asthma and asthma control
Xue Zeng, Jing Qing, Chi-Ming Li, Jiamiao Lu, Tracy Yamawaki, Yi-Hsiang Hsu, Bryan Vander Lugt, Hailing Hsu, John Busby, P J McDowell, David J Jackson, Ratko Djukanovic, John G Matthews, Joseph R Arron, Peter Bradding, Christopher E Brightling, Rekha Chaudhuri, David F Choy, D Cowan, S J Fowler, Timothy C Hardman, Tim Harrison, Peter Howarth, James Lordan, A H Mansur, Andrew Menzies-Gow, Ian D Pavord, Samantha Walker, Ashley Woodcock, Liam G Heaney; investigators for the UK MRC Refractory Asthma Stratification Program (RASP-UK)
Abstract
Background: Patients with type-2 (T2) cytokine-low severe asthma often have persistent symptoms despite suppression of T2 inflammation with corticosteroids.
Objectives: We sought to analyze whole blood transcriptome from 738 samples in T2-biomarker-high/-low patients with severe asthma to relate transcriptomic signatures to T2 biomarkers and asthma symptom scores.
Methods: Bulk RNA-seq data were generated for blood samples (baseline, week 24, week 48) from 301 participants recruited to a randomized clinical trial of corticosteroid optimization in severe asthma. Unsupervised clustering, differential gene expression analysis, and pathway analysis were performed. Patients were grouped by T2-biomarker status and symptoms. Associations between clinical characteristics and differentially expressed genes (DEGs) associated with biomarker and symptom levels were investigated.
Results: Unsupervised clustering identified 2 clusters; cluster 2 patients were blood eosinophil-low/symptom-high and more likely to be receiving oral corticosteroids (OCSs). Differential gene expression analysis of these clusters, with and without stratification for OCSs, identified 2960 and 4162 DEGs, respectively. Six hundred twenty-seven of 2960 genes remained after adjusting for OCSs by subtracting OCS signature genes. Pathway analysis identified dolichyl-diphosphooligosaccharide biosynthesis and assembly of RNA polymerase I complex as significantly enriched pathways. No stable DEGs were associated with high symptoms in T2-biomarker-low patients, but numerous associated with elevated T2 biomarkers, including 15 that were upregulated at all time points irrespective of symptom level.
Conclusions: OCSs have a considerable effect on whole blood transcriptome. Differential gene expression analysis demonstrates a clear T2-biomarker transcriptomic signature, but no signature was found in association with T2-biomarker-low patients, including those with a high symptom burden.
背景：尽管皮质类固醇可以抑制T2炎症，但低2型（T2）细胞因子-重症哮喘患者通常仍有持续症状。
目的：我们试图分析738例严重哮喘T2生物标志物高/低患者的全血转录组，以将转录组特征与T2生物标志和哮喘症状评分联系起来。
方法：从301名参与者的血液样本（基线，第24周，第48周）中生成大量RNA-seq数据，这些参与者被招募到一项重症哮喘皮质类固醇优化的随机临床试验中。进行了无监督聚类、差异基因表达分析和通路分析。根据T2生物标志物状态和症状对患者进行分组。研究了临床特征与生物标志物和症状水平相关的差异表达基因（DEGs）之间的关系。
结果：无监督聚类识别出2个聚类；第2组患者的血液嗜酸性粒细胞水平较低/症状较高，更有可能接受口服皮质类固醇（OCSs）治疗。对这些聚类的差异基因表达分析，在有和没有OCSs分层的情况下，分别鉴定了2960个和4162个DEG。2960个基因中的627个在通过减去OCS特征基因对OCSs进行调整后仍然存在。途径分析表明，二磷酸低聚多糖生物合成和RNA聚合酶I复合物的组装是显著富集的途径。在T2生物标志物低的患者中，没有稳定的DEG与高症状相关，但许多DEG与T2生物标记物升高相关，包括15个在所有时间点上调的DEG，而与症状水平无关。
结论：OCSs对全血转录组有显著影响。差异基因表达分析显示了明确的T2生物标志物转录组学特征，但没有发现与低T2生物标志患者（包括症状负担高的患者）相关的特征。
(中日友好医院呼吸与危重症医学科 李红雯 摘译 林江涛 审校)
(J Allergy Clin Immunol. 2023 Jun 12;S0091-6749(23)00751-0. doi: 10.1016/j.jaci.2023.05.023.)
(J Allergy Clin Immunol. 2023 Jun 12;S0091-6749(23)00751-0. doi: 10.1016/j.jaci.2023.05.023.)
Blood transcriptomic signature in type-2 biomarker-low severe asthma and asthma control
Xue Zeng, Jing Qing, Chi-Ming Li, Jiamiao Lu, Tracy Yamawaki, Yi-Hsiang Hsu, Bryan Vander Lugt, Hailing Hsu, John Busby, P J McDowell, David J Jackson, Ratko Djukanovic, John G Matthews, Joseph R Arron, Peter Bradding, Christopher E Brightling, Rekha Chaudhuri, David F Choy, D Cowan, S J Fowler, Timothy C Hardman, Tim Harrison, Peter Howarth, James Lordan, A H Mansur, Andrew Menzies-Gow, Ian D Pavord, Samantha Walker, Ashley Woodcock, Liam G Heaney; investigators for the UK MRC Refractory Asthma Stratification Program (RASP-UK)
Abstract
Background: Patients with type-2 (T2) cytokine-low severe asthma often have persistent symptoms despite suppression of T2 inflammation with corticosteroids.
Objectives: We sought to analyze whole blood transcriptome from 738 samples in T2-biomarker-high/-low patients with severe asthma to relate transcriptomic signatures to T2 biomarkers and asthma symptom scores.
Methods: Bulk RNA-seq data were generated for blood samples (baseline, week 24, week 48) from 301 participants recruited to a randomized clinical trial of corticosteroid optimization in severe asthma. Unsupervised clustering, differential gene expression analysis, and pathway analysis were performed. Patients were grouped by T2-biomarker status and symptoms. Associations between clinical characteristics and differentially expressed genes (DEGs) associated with biomarker and symptom levels were investigated.
Results: Unsupervised clustering identified 2 clusters; cluster 2 patients were blood eosinophil-low/symptom-high and more likely to be receiving oral corticosteroids (OCSs). Differential gene expression analysis of these clusters, with and without stratification for OCSs, identified 2960 and 4162 DEGs, respectively. Six hundred twenty-seven of 2960 genes remained after adjusting for OCSs by subtracting OCS signature genes. Pathway analysis identified dolichyl-diphosphooligosaccharide biosynthesis and assembly of RNA polymerase I complex as significantly enriched pathways. No stable DEGs were associated with high symptoms in T2-biomarker-low patients, but numerous associated with elevated T2 biomarkers, including 15 that were upregulated at all time points irrespective of symptom level.
Conclusions: OCSs have a considerable effect on whole blood transcriptome. Differential gene expression analysis demonstrates a clear T2-biomarker transcriptomic signature, but no signature was found in association with T2-biomarker-low patients, including those with a high symptom burden.
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