{"title":"Whole blood transcriptome in long-COVID patients reveals association with lung function and immune response","authors":"","doi":"10.1016/j.jaci.2024.04.032","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Months after infection with severe acute respiratory syndrome coronavirus 2, at least 10% of patients still experience complaints. Long-COVID (coronavirus disease 2019) is a heterogeneous disease, and clustering efforts revealed multiple phenotypes on a clinical level. However, the molecular pathways underlying long-COVID phenotypes are still poorly understood.</p></div><div><h3>Objectives</h3><p>We sought to cluster patients according to their blood transcriptomes and uncover the pathways underlying their disease.</p></div><div><h3>Methods</h3><p>Blood was collected from 77 patients with long-COVID from the Precision Medicine for more Oxygen (P4O2) COVID-19 study. Unsupervised hierarchical clustering was performed on the whole blood transcriptome. These clusters were analyzed for differences in clinical features, pulmonary function tests, and gene ontology term enrichment.</p></div><div><h3>Results</h3><p>Clustering revealed 2 distinct clusters on a transcriptome level. Compared with cluster 2 (n = 65), patients in cluster 1 (n = 12) showed a higher rate of preexisting cardiovascular disease (58% vs 22%), higher prevalence of gastrointestinal symptoms (58% vs 29%), shorter hospital duration during severe acute respiratory syndrome coronavirus 2 infection (median, 3 vs 8 days), lower FEV<sub>1</sub>/forced vital capacity (72% vs 81%), and lower diffusion capacity of the lung for carbon monoxide (68% vs 85% predicted). Gene ontology term enrichment analysis revealed upregulation of genes involved in the antiviral innate immune response in cluster 1, whereas genes involved with the adaptive immune response were upregulated in cluster 2.</p></div><div><h3>Conclusions</h3><p>This study provides a start in uncovering the pathophysiological mechanisms underlying long-COVID. Further research is required to unravel why the immune response is different in these clusters, and to identify potential therapeutic targets to create an optimized treatment or monitoring strategy for the individual long-COVID patient.</p></div>","PeriodicalId":14936,"journal":{"name":"Journal of Allergy and Clinical Immunology","volume":null,"pages":null},"PeriodicalIF":11.4000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0091674924005669/pdfft?md5=f62b92f847558969da05210d4b002b95&pid=1-s2.0-S0091674924005669-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Allergy and Clinical Immunology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0091674924005669","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ALLERGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Months after infection with severe acute respiratory syndrome coronavirus 2, at least 10% of patients still experience complaints. Long-COVID (coronavirus disease 2019) is a heterogeneous disease, and clustering efforts revealed multiple phenotypes on a clinical level. However, the molecular pathways underlying long-COVID phenotypes are still poorly understood.
Objectives
We sought to cluster patients according to their blood transcriptomes and uncover the pathways underlying their disease.
Methods
Blood was collected from 77 patients with long-COVID from the Precision Medicine for more Oxygen (P4O2) COVID-19 study. Unsupervised hierarchical clustering was performed on the whole blood transcriptome. These clusters were analyzed for differences in clinical features, pulmonary function tests, and gene ontology term enrichment.
Results
Clustering revealed 2 distinct clusters on a transcriptome level. Compared with cluster 2 (n = 65), patients in cluster 1 (n = 12) showed a higher rate of preexisting cardiovascular disease (58% vs 22%), higher prevalence of gastrointestinal symptoms (58% vs 29%), shorter hospital duration during severe acute respiratory syndrome coronavirus 2 infection (median, 3 vs 8 days), lower FEV1/forced vital capacity (72% vs 81%), and lower diffusion capacity of the lung for carbon monoxide (68% vs 85% predicted). Gene ontology term enrichment analysis revealed upregulation of genes involved in the antiviral innate immune response in cluster 1, whereas genes involved with the adaptive immune response were upregulated in cluster 2.
Conclusions
This study provides a start in uncovering the pathophysiological mechanisms underlying long-COVID. Further research is required to unravel why the immune response is different in these clusters, and to identify potential therapeutic targets to create an optimized treatment or monitoring strategy for the individual long-COVID patient.
背景在感染严重急性呼吸系统综合征冠状病毒2数月后,至少有10%的患者仍有不适症状。长COVID(冠状病毒病2019)是一种异质性疾病,聚类工作揭示了临床上的多种表型。目标我们试图根据患者的血液转录组对其进行聚类,并揭示其疾病的基础通路。方法我们从更多氧气的精准医学(P4O2)COVID-19研究中收集了77名长COVID患者的血液。对全血转录组进行了无监督分层聚类。结果聚类在转录组水平上发现了两个不同的群组。与第2群组(n = 65)相比,第1群组(n = 12)的患者患有心血管疾病的比例更高(58% vs 22%),胃肠道症状发生率更高(58% vs 29%),感染严重急性呼吸系统综合征冠状病毒2的住院时间更短(中位数为3天 vs 8天),FEV1/肺活量更低(72% vs 81%),肺对一氧化碳的弥散能力更低(68% vs 85%预测值)。基因本体术语富集分析显示,群组 1 中参与抗病毒先天免疫反应的基因上调,而群组 2 中参与适应性免疫反应的基因上调。还需要进一步的研究来揭示这些群组中免疫反应不同的原因,并确定潜在的治疗靶点,从而为长程COVID患者制定优化的治疗或监测策略。
期刊介绍:
The Journal of Allergy and Clinical Immunology is a prestigious publication that features groundbreaking research in the fields of Allergy, Asthma, and Immunology. This influential journal publishes high-impact research papers that explore various topics, including asthma, food allergy, allergic rhinitis, atopic dermatitis, primary immune deficiencies, occupational and environmental allergy, and other allergic and immunologic diseases. The articles not only report on clinical trials and mechanistic studies but also provide insights into novel therapies, underlying mechanisms, and important discoveries that contribute to our understanding of these diseases. By sharing this valuable information, the journal aims to enhance the diagnosis and management of patients in the future.