Stratification of COVID-19 patients based on quantitative immune-related gene expression in whole blood

根据全血中免疫相关基因的定量表达对 COVID-19 患者进行分层

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作者:Josefine Persson, Björn Andersson, Suzanne van Veen, Mariëlle C Haks, Ogonna Obudulu, Sara Torkzadeh, Tom H M Ottenhoff, Nelly Kanberg, Magnus Gisslén, Lars-Magnus Andersson, Ali M Harandi

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes mild symptoms in the majority of infected individuals, yet in some cases it leads to a life-threatening condition. Determination of early predictive biomarkers enabling risk stratification for coronavirus disease 2019 (COVID-19) patients can inform treatment and intervention strategies. Herein, we analyzed whole blood samples obtained from individuals infected with SARS-CoV-2, varying from mild to critical symptoms, approximately one week after symptom onset. In order to identify blood-specific markers of disease severity status, a targeted expression analysis of 143 immune-related genes was carried out by dual-color reverse transcriptase multiplex ligation-dependent probe amplification (dcRT-MLPA). The clinically well-defined subgroups of COVID-19 patients were compared with healthy controls. The transcriptional profile of the critically ill patients clearly separated from that of healthy individuals. Moreover, the number of differentially expressed genes increased by severity of COVID-19. It was also found that critically ill patients can be distinguished by reduced peripheral blood expression of several genes, which most likely reflects the lower lymphocyte counts. There was a notable predominance of IFN-associated gene expression in all subgroups of COVID-19, which was most profound in critically ill patients. Interestingly, the gene encoding one of the main TNF-receptors, TNFRS1A, had selectively lower expression in mild COVID-19 cases. This report provides added value in understanding COVID-19 disease, and shows potential of determining early immune transcript signatures in the blood of patients with different disease severity. These results can guide further explorations to uncover mechanisms underlying immunity and immunopathology in COVID-19.

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