2型生物标志物低的重度哮喘中的血液转录组特征和哮喘控制
2024/06/11
摘要
背景：尽管用糖皮质激素抑制了2型（T2）炎症，T2细胞因子低的重度哮喘患者仍有持续的哮喘症状。
目的：我们试图分析T2 high/low重度哮喘患者的 738 个样本的全血转录组特征，以将转录组特征与 T2 生物标志物和哮喘症状评分联系起来。
方法：从一项针对重度哮喘优化糖皮质激素治疗的随机对照临床试验的301名患者的血液样本（基线、第24周、第48周）中获得RNA-seq数据，进行无监督聚类分析、差异基因表达分析和通路分析。患者按 T2 生物标志物水平和哮喘症状进行分组。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）之间的关联。
结果：无监督聚类识别出 2 个类簇；类簇2的患者血液嗜酸性粒细胞水平低/症状高，且更有可能接受口服糖皮质激素（OCS）。对这些类簇进行差异基因表达分析，按照OCS分层鉴定出2960个DEGs，未分层鉴定出4162个DEGs。在减去 OCS 特征基因后，2960个基因中剩下627个基因仍然存在。通路分析发现多立基-二磷酸寡糖的生物合成和 RNA 聚合酶 I 复合物的组装是显著富集的通路。在 T2-low的患者中，没有发现稳定的 DEG 与症状控制不佳相关，但许多DEGs与 T2-high相关，包括 15 个DEG在所有时间点均上调，且独立于哮喘症状控制水平。
结论：OCSs对全血转录组有显著影响。差异基因表达分析发现了明确的 T2 生物标志物转录组特征，但未发现与 T2-low患者相关的特征，包括症状负担高的患者。
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)
J Allergy Clin Immunol. 2023 Oct;152(4):876-886.
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：尽管用糖皮质激素抑制了2型（T2）炎症，T2细胞因子低的重度哮喘患者仍有持续的哮喘症状。
目的：我们试图分析T2 high/low重度哮喘患者的 738 个样本的全血转录组特征，以将转录组特征与 T2 生物标志物和哮喘症状评分联系起来。
方法：从一项针对重度哮喘优化糖皮质激素治疗的随机对照临床试验的301名患者的血液样本（基线、第24周、第48周）中获得RNA-seq数据，进行无监督聚类分析、差异基因表达分析和通路分析。患者按 T2 生物标志物水平和哮喘症状进行分组。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）之间的关联。
结果：无监督聚类识别出 2 个类簇；类簇2的患者血液嗜酸性粒细胞水平低/症状高，且更有可能接受口服糖皮质激素（OCS）。对这些类簇进行差异基因表达分析，按照OCS分层鉴定出2960个DEGs，未分层鉴定出4162个DEGs。在减去 OCS 特征基因后，2960个基因中剩下627个基因仍然存在。通路分析发现多立基-二磷酸寡糖的生物合成和 RNA 聚合酶 I 复合物的组装是显著富集的通路。在 T2-low的患者中，没有发现稳定的 DEG 与症状控制不佳相关，但许多DEGs与 T2-high相关，包括 15 个DEG在所有时间点均上调，且独立于哮喘症状控制水平。
结论：OCSs对全血转录组有显著影响。差异基因表达分析发现了明确的 T2 生物标志物转录组特征，但未发现与 T2-low患者相关的特征，包括症状负担高的患者。
(四川大学华西医院呼吸与危重症医学科 金凡丁1 王霁1 王刚1译)
(J Allergy Clin Immunol. 2023 Oct;152(4):876-886.)
(J Allergy Clin Immunol. 2023 Oct;152(4):876-886.)
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)
J Allergy Clin Immunol. 2023 Oct;152(4):876-886.
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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新型降糖药物与二甲双胍与减少哮喘发作之间的关系
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