Poorbaugh Josh, Sims Jonathan T, Zhang Lin, Chang Ching-Yun, Higgs Richard E, Nirula Ajay, Benschop Robert J
Eli Lilly and Company, Indianapolis, Indiana, United States of America.
PLoS One. 2025 May 27;20(5):e0324242. doi: 10.1371/journal.pone.0324242. eCollection 2025.
SARS-CoV-2 infections lead to a wide-range of outcomes from mild or asymptomatic illness to serious complications and death. While many studies have characterized hospitalized SARS-CoV-2 patient immune responses, we were interested in whether serious complications of SARS-CoV-2 infection could be predicted early in ambulatory subjects. To that end, we used samples from SARS-CoV-2-infected individuals from the placebo arm of the BLAZE-1 clinical trial who progressed to hospitalization or death compared to individuals in the same study who did not require medical intervention and investigated whether baseline serum cytokines and chemokines could predict severe outcome. High-risk demographic factors at baseline, including age, nasal pharyngeal viral load, duration from symptom onset, and BMI provide significant predictive capacity for a hospitalization or death with an AUC of ROC = 0.77. The predictive performance of our outcome modeling increased when baseline serum protein markers were included. In fact, the one-marker model indicated that there were 51 individual proteins (including known markers of inflammation like IL-6, MCP-3, CXCL10, IL-1Ra, and PTX3) that significantly increased the AUC of ROC beyond high-risk patient demographics alone to range between 0.78 to 0.88. Moreover, a two-marker model incorporating levels of both IL-6 and PTX3 further improved the prediction over the addition of a single protein marker to an AUC of ROC = 0.91. While the analytes identified in this study have been well-documented to be altered in SARS-CoV-2 infection, this analysis demonstrates the potential value of their use in predicting hospitalization or death in ambulatory participants infected with SARS-CoV-2 and could guide early treatment decisions.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染会导致从轻度或无症状疾病到严重并发症和死亡的广泛后果。虽然许多研究已经描述了住院的SARS-CoV-2患者的免疫反应,但我们感兴趣的是,SARS-CoV-2感染的严重并发症是否可以在门诊患者早期就被预测。为此,我们使用了BLAZE-1临床试验安慰剂组中进展为住院或死亡的SARS-CoV-2感染个体的样本,并与同一研究中不需要医疗干预的个体进行比较,研究基线血清细胞因子和趋化因子是否可以预测严重后果。基线时的高风险人口统计学因素,包括年龄、鼻咽病毒载量、症状出现后的持续时间和体重指数,对住院或死亡具有显著的预测能力,受试者工作特征曲线(ROC)下面积(AUC)为0.77。当纳入基线血清蛋白标志物时,我们的结局模型的预测性能有所提高。事实上,单标志物模型表明,有51种个体蛋白(包括白细胞介素-6、单核细胞趋化蛋白-3、CXC趋化因子配体10、白细胞介素-1受体拮抗剂和五聚素3等已知炎症标志物)显著提高了ROC的AUC,使其超出仅基于高风险患者人口统计学因素的范围,达到0.78至0.88。此外,结合白细胞介素-6和五聚素3水平的双标志物模型进一步改善了预测,使ROC的AUC达到0.91,超过了添加单个蛋白标志物的情况。虽然本研究中确定的分析物在SARS-CoV-2感染中已被充分证明会发生改变,但该分析证明了它们在预测感染SARS-CoV-2的门诊参与者住院或死亡方面的潜在价值,并可指导早期治疗决策。