Multidisciplinary Research Units (MRU), Pt. J.N.M. Medical College, Raipur, Chhattisgarh, 492001, India.
Department of Microbiology, Pt. J.N.M. Medical College, Raipur, C.G., India.
Sci Rep. 2024 Aug 22;14(1):19510. doi: 10.1038/s41598-024-70161-8.
Unpredictable fatal outcome of COVID-19 is attributed to dysregulated inflammation. Impaired early adaptive immune response leads to late-stage inflammatory outcome. The purpose of this study was to develop biomarkers for early detection of host immune impairment at first diagnosis from leftover RNA samples, which may in turn identify high risk patients. Leftover RNA samples of COVID-19 patients at first diagnosis were stored. Following prospective follow-up, the samples were shorted and categorized into outcome groups. Impaired adaptive T cell response (severity score) and Impaired IL-10 response (undetectable IL-10 in the presence of high expression of a representative interferon response gene) were determined by RT-PCR based assay. We demonstrate that a T cell response based 'severity score' comprising rational combination of Ct values of a target genes' signature can predict high risk noncomorbid potentially critical COVID-19 patients with a sensitivity of 91% (95% CI 58.7-99.8) and specificity of 92.6% (95% CI 75.7-99) (AUC:0.88). Although inclusion of comorbid patients reduced sensitivity to 77% (95% CI 54.6-92.2), the specificity was still 94% (95% CI 79.8-99.3) (AUC:0.82). The same for 'impaired IL-10 response' were little lower to predict high risk noncomorbid patients 64.2% (95% CI 35.1-87.2) and 82% (95% CI 65.5-93.2) respectively. Inclusion of comorbid patients drastically reduce sensitivity and specificity51.6% (95% CI 33.1-69.8) and 80.5% (95% CI 64.0-91.8) respectively. As best of our knowledge this is the first demonstration of a metric-based approach showing the 'severity score' as an indicator of early adoptive immune response, could be used as predictor of severe COVID-19 outcome at the time of first diagnosis using the same leftover swab RNA. The work flow could reduce expenditure and reporting time of the prognostic test for an earliest clinical decision ensuring possibility of early rational management.
COVID-19 无法预测的致命后果归因于失调的炎症反应。早期适应性免疫应答受损导致晚期炎症结果。本研究旨在从遗留的 RNA 样本中开发出用于早期检测宿主免疫受损的生物标志物,从而识别高危患者。COVID-19 患者在初次诊断时的遗留 RNA 样本被储存。经过前瞻性随访,这些样本被缩短并分类为结局组。通过基于 RT-PCR 的检测,确定适应性 T 细胞反应受损(严重程度评分)和 IL-10 反应受损(在高表达代表性干扰素反应基因的情况下无法检测到 IL-10)。我们证明,基于 T 细胞反应的“严重程度评分”,由目标基因特征的 Ct 值的合理组合组成,可以预测高风险非合并潜在严重 COVID-19 患者,其敏感性为 91%(95%CI 58.7-99.8),特异性为 92.6%(95%CI 75.7-99)(AUC:0.88)。尽管纳入合并症患者将敏感性降低至 77%(95%CI 54.6-92.2),但特异性仍为 94%(95%CI 79.8-99.3)(AUC:0.82)。对于预测高风险非合并症患者,“IL-10 反应受损”的预测结果略低,分别为 64.2%(95%CI 35.1-87.2)和 82%(95%CI 65.5-93.2)。纳入合并症患者会大大降低敏感性和特异性,分别为 51.6%(95%CI 33.1-69.8)和 80.5%(95%CI 64.0-91.8)。据我们所知,这是首次证明基于指标的方法可以显示“严重程度评分”作为早期适应性免疫反应的指标,可用于使用相同的遗留拭子 RNA 在初次诊断时预测 COVID-19 严重结局。该工作流程可以减少预后测试的支出和报告时间,为最早的临床决策提供保证,并有可能进行早期合理的管理。