Longitudinal gene expression analysis in COVID-19 sepsis highlights dynamic immune, cellular, and metabolic dysfunction in high severity patients

COVID-19 脓毒症的纵向基因表达分析突显了重症患者动态的免疫、细胞和代谢功能障碍

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Abstract

COVID-19 patients experience dynamic changes in immune and cellular function over time, similar to that in sepsis. However, there is insufficient research investigating, at the gene expression level, the mechanisms that become activated or suppressed over time as patients deteriorate or recover. This has potential prognostic and therapeutic implications. In this longitudinal study, 300 whole blood samples were analyzed from 128 adult patients throughout their COVID-19 hospitalization. Transcriptome sequencing (RNA-Seq), differential gene expression analysis, pathway enrichment, and drug-gene set enrichment analysis were performed to elucidate key mechanisms for therapeutic targeting during six distinct disease phases through the COVID-19 trajectory. Adaptive immune dysfunction, inflammation, and metabolic dysregulation were most pronounced during phases with higher disease severity. Hemostatic dysregulation was present early and persisted throughout the disease course, in contrast to an early antiviral response and late heme metabolism activity. Drug-gene set enrichment analysis predicted repurposed medications for potential use, including platelet inhibitors, antidiabetic medications, and dasatinib. Disease phases had distinct transcriptional signatures and were highly correlated to previously developed sepsis endotypes, indicating that severity and disease timing were significant contributors to heterogeneity observed in COVID-19 sepsis. These findings provide an opportunity for better prognostication of patients and potential time-dependent personalized treatments.

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