Immune Dysregulation in Acute SARS-CoV-2 Infection.

Q1 Medicine Pathogens and Immunity Pub Date : 2022-01-01 DOI:10.20411/pai.v7i2.537
Lauren Grimm, Chinyere Onyeukwu, Grace Kenny, Danielle M Parent, Jia Fu, Shaurya Dhingra, Emily Yang, James Moy, P J Utz, Russell Tracy, Alan Landay
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Abstract

Introduction: Neutralizing antibodies have been shown to develop rapidly following SARS-CoV-2 infection, specifically against spike (S) protein, where cytokine release and production is understood to drive the humoral immune response during acute infection. Thus, we evaluated the quantity and function of antibodies across disease severities and analyzed the associated inflammatory and coagulation pathways to identify acute markers that correlate with antibody response following infection.

Methods: Blood samples were collected from patients at time of diagnostic SARS-CoV-2 PCR testing between March 2020-November 2020. Plasma samples were analyzed using the MesoScale Discovery (MSD) Platform using the COVID-19 Serology Kit and U-Plex 8 analyte multiplex plate to measure anti-alpha and beta coronavirus antibody concentration and ACE2 blocking function, as well as plasma cytokines.

Results: A total of 230 (181 unique patients) samples were analyzed across the 5 COVID-19 disease severities. We found that antibody quantity directly correlated with functional ability to block virus binding to membrane-bound ACE2, where a lower SARS-CoV-2 anti-spike/anti-RBD response corresponded with a lower antibody blocking potential compared to higher antibody response (anti-S1 r = 0.884, P < 0.001; anti-RBD r = 0.75, P < 0.001). Across all the soluble proinflammatory markers we examined, ICAM, IL-1β, IL-4, IL-6, TNFα, and Syndecan showed a statistically significant positive correlation between cytokine or epithelial marker and antibody quantity regardless of COVID-19 disease severity. Analysis of autoantibodies against type 1 interferon was not shown to be statistically significant between disease severity groups.

Conclusion: Previous studies have shown that proinflammatory markers, including IL-6, IL-8, IL-1β, and TNFα, are significant predictors of COVID-19 disease severity, regardless of demographics or comorbidities. Our study demonstrated that not only are these proinflammatory markers, as well as IL-4, ICAM, and Syndecan, correlative of disease severity, they are also correlative of antibody quantity and quality following SARS-CoV-2 exposure.

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急性SARS-CoV-2感染中的免疫失调
研究表明,中和抗体在SARS-CoV-2感染后迅速产生,特别是针对刺突蛋白,在急性感染期间,细胞因子的释放和产生被认为是驱动体液免疫反应的。因此,我们评估了不同疾病严重程度的抗体的数量和功能,并分析了相关的炎症和凝血途径,以确定感染后与抗体反应相关的急性标志物。方法:采集2020年3月- 2020年11月诊断性SARS-CoV-2 PCR检测时的患者血样。使用MesoScale Discovery (MSD)平台使用COVID-19血清学试剂盒和U-Plex 8分析物复合板分析血浆样品,测量抗α和β冠状病毒抗体浓度和ACE2阻断功能,以及血浆细胞因子。结果:共分析了5种COVID-19疾病严重程度的230例(181例独特患者)样本。我们发现抗体数量与阻断病毒与膜结合ACE2的功能能力直接相关,其中较低的SARS-CoV-2抗spike/抗rbd应答与较低的抗体阻断潜力相对应(抗s1 r = 0.884, P < 0.001;anti-RBD r = 0.75, P < 0.001)。在我们检测的所有可溶性促炎标志物中,无论COVID-19疾病严重程度如何,ICAM、IL-1β、IL-4、IL-6、TNFα和Syndecan均显示细胞因子或上皮标志物与抗体数量呈正相关,具有统计学意义。针对1型干扰素的自身抗体分析在疾病严重程度组之间没有统计学意义。结论:先前的研究表明,促炎标志物,包括IL-6、IL-8、IL-1β和TNFα,是COVID-19疾病严重程度的重要预测因子,与人口统计学或合并症无关。我们的研究表明,这些促炎标志物以及IL-4、ICAM和Syndecan不仅与疾病严重程度相关,而且与SARS-CoV-2暴露后的抗体数量和质量相关。
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来源期刊
Pathogens and Immunity
Pathogens and Immunity Medicine-Infectious Diseases
CiteScore
10.60
自引率
0.00%
发文量
16
审稿时长
10 weeks
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