OBJECTIVE: 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.
目的:本研究旨在根据患者的血液转录组对患者进行聚类,并揭示其疾病的潜在途径。
方法:收集了来自P4O2COVID-19研究的77例长COVID患者的血液。对全血转录组进行无监督分层聚类。分析了这些聚类的临床特征差异,肺功能检查和基因本体论(GO)术语富集。
结果:聚类在转录组水平上显示了两个不同的簇。与集群2(n=65)相比,第1组患者(n=12)表现出较高的预先存在的心血管疾病的比率(58%vs22%),胃肠道症状的患病率较高(58%对29%),SARS-CoV-2感染期间住院时间较短(中位数:3天vs8天),较低的Tiffeneau指数(72%vs81%)和较低的肺对一氧化碳(DLCO)的扩散能力(68%vs85%预测)。GO-term富集分析显示在簇1中参与抗病毒先天性免疫应答的基因上调,而与适应性免疫应答相关的基因在簇2中上调。
结论:这项研究为揭示长期COVID的病理生理机制提供了一个起点。需要进一步的研究来解释为什么这些集群中的免疫反应不同,并确定潜在的治疗靶点,为个体长期COVID患者创建优化的治疗或监测策略。