Department of Pediatrics, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, 05403-900, Brazil.
Instituto Israelita de Ensino e Pesquisa Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, SP, 01310-200, Brazil.
Sci Rep. 2023 Jan 17;13(1):898. doi: 10.1038/s41598-023-28227-6.
Since the molecular mechanisms determining COVID-19 severity are not yet well understood, there is a demand for biomarkers derived from comparative transcriptome analyses of mild and severe cases, combined with patients' clinico-demographic and laboratory data. Here the transcriptomic response of human leukocytes to SARS-CoV-2 infection was investigated by focusing on the differences between mild and severe cases and between age subgroups (younger and older adults). Three transcriptional modules correlated with these traits were functionally characterized, as well as 23 differentially expressed genes (DEGs) associated to disease severity. One module, correlated with severe cases and older patients, had an overrepresentation of genes involved in innate immune response and in neutrophil activation, whereas two other modules, correlated with disease severity and younger patients, harbored genes involved in the innate immune response to viral infections, and in the regulation of this response. This transcriptomic mechanism could be related to the better outcome observed in younger COVID-19 patients. The DEGs, all hyper-expressed in the group of severe cases, were mostly involved in neutrophil activation and in the p53 pathway, therefore related to inflammation and lymphopenia. These biomarkers may be useful for getting a better stratification of risk factors in COVID-19.
由于确定 COVID-19 严重程度的分子机制尚不清楚,因此需要从轻度和重度病例的比较转录组分析中提取生物标志物,并结合患者的临床人口统计学和实验室数据。在这里,通过关注轻度和重度病例以及年龄亚组(年轻人和老年人)之间的差异,研究了人类白细胞对 SARS-CoV-2 感染的转录组反应。对与这些特征相关的三个转录模块以及与疾病严重程度相关的 23 个差异表达基因 (DEG) 进行了功能表征。与严重病例和老年患者相关的一个模块,其特征是参与固有免疫反应和中性粒细胞激活的基因表达上调,而另外两个与疾病严重程度和年轻患者相关的模块,包含了参与病毒感染固有免疫反应和调节该反应的基因。这种转录组机制可能与在年轻 COVID-19 患者中观察到的更好结果有关。在严重病例组中高表达的 DEG 主要涉及中性粒细胞激活和 p53 通路,因此与炎症和淋巴细胞减少有关。这些生物标志物可能有助于更好地分层 COVID-19 的危险因素。