Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, China.
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Rev Med Virol. 2021 Jul;31(4):e2195. doi: 10.1002/rmv.2195. Epub 2020 Nov 20.
Currently severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been on the rise worldwide. Predicting outcome in COVID-19 remains challenging, and the search for more robust predictors continues. We made a systematic meta-analysis on the current literature from 1 January 2020 to 15 August 2020 that independently evaluated 32 circulatory immunological signatures that were compared between patients with different disease severity was made. Their roles as predictors of disease severity were determined as well. A total of 149 distinct studies that evaluated ten cytokines, four antibodies, four T cells, B cells, NK cells, neutrophils, monocytes, eosinophils and basophils were included. Compared with the non-severe patients of COVID-19, serum levels of Interleukins (IL)-2, IL-2R, IL-4, IL-6, IL-8, IL-10 and tumor necrosis factor α were significantly up-regulated in severe patients, with the largest inter-group differences observed for IL-6 and IL-10. In contrast, IL-5, IL-1β and Interferon (IFN)-γ did not show significant inter-group difference. Four mediators of T cells count, including CD3 T, CD4 T, CD8 T, CD4 CD25 CD127 Treg, together with CD19 B cells count and CD16 CD56 NK cells were all consistently and significantly depressed in severe group than in non-severe group. SARS-CoV-2 specific IgA and IgG antibodies were significantly higher in severe group than in non-severe group, while IgM antibody in the severe patients was slightly lower than those in the non-severe patients, and IgE antibody showed no significant inter-group differences. The combination of cytokines, especially IL-6 and IL-10, and T cell related immune signatures can be used as robust biomarkers to predict disease severity following SARS-CoV-2 infection.
目前,全球范围内严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)的传播呈上升趋势。预测 COVID-19 的结局仍然具有挑战性,因此仍在寻找更强大的预测指标。我们对 2020 年 1 月 1 日至 2020 年 8 月 15 日的当前文献进行了系统的荟萃分析,该分析独立评估了 32 种循环免疫特征,这些特征在不同疾病严重程度的患者之间进行了比较。同时还确定了它们作为疾病严重程度预测因子的作用。共纳入了 149 项评估十种细胞因子、四种抗体、四种 T 细胞、B 细胞、NK 细胞、中性粒细胞、单核细胞、嗜酸性粒细胞和嗜碱性粒细胞的不同研究。与 COVID-19 的非重症患者相比,重症患者的血清白细胞介素(IL)-2、IL-2R、IL-4、IL-6、IL-8、IL-10 和肿瘤坏死因子-α水平明显升高,其中 IL-6 和 IL-10 的组间差异最大。相比之下,IL-5、IL-1β和干扰素(IFN)-γ 没有明显的组间差异。T 细胞计数的四个调节剂,包括 CD3 T、CD4 T、CD8 T、CD4 CD25 CD127 Treg,以及 CD19 B 细胞计数和 CD16 CD56 NK 细胞,在重症组均明显低于非重症组。SARS-CoV-2 特异性 IgA 和 IgG 抗体在重症组明显高于非重症组,而重症患者的 IgM 抗体略低于非重症患者,IgE 抗体无明显组间差异。细胞因子,尤其是 IL-6 和 IL-10,以及 T 细胞相关免疫特征的组合可作为预测 SARS-CoV-2 感染后疾病严重程度的强大生物标志物。