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Abstract：
Human identical sequences of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) promoted the coronavirus disease 2019 (COVID-19) progression by upregulating hyaluronic acid (HA) via NamiRNA-enhancer network, based on previous experimental research. This study aimed to investigate the predictive value of HA for the severity of SARS-CoV-2 infection in the post-COVID-19 era.
A total of 217 consecutive patients with COVID-19 were enrolled at Beijing Ditan Hospital between July 2023 and October 2023. HA levels were analyzed using biochemical detector. Logistic regression analysis was used to screen independent factors for severe COVID-19. The predictive performance of HA for severe infection was assessed by ROC curve. Furthermore, the relationship between HA levels and COVID-19 severity was investigated using multivariate logistic regression models after adjustment for potential confounders.
According to the cut-off value of HA, COVID-19 patients were divided into HA < 90 ng/mL group (80 cases) and HA ≥ 90 ng/mL group (137 cases). High HA levels were positively associated with the severe SARS-CoV-2 infection, including elevated inflammatory indicators, severe lung involvement, prolonged clinical course, and higher incidence of respiratory failure and death (P < 0.05). Logistic regression analysis suggested that HA was an independent predictor of severe COVID-19 (OR = 4.540, 95% CI = 2.105-9.790, P < 0.001). ROC curve analysis showed that the AUC of HA for severe infection was 0.724. HA levels were significantly higher in COVID-19 cases compared to the healthy population (123.9 (82.6, 174.1) vs. 50.5 (37.8, 66.8), P < 0.001), but similar to those with non-SARS-CoV-2 lung infection (121.6 (78.5, 175.6) vs. 106.0 (66.5, 149.7), P = 0.244). We also found that the first COVID-19 infections had higher HA levels (118.8 (79.5, 174.3) vs. 85.0 (61.1, 128.8), P < 0.001) and a higher proportion of severe infection (37.1% vs. 21.3%, P = 0.043) than re-infections. However, HA expression failed to fully return to normal levels with infection recovery (204.7 (152.9, 242.2) vs. 97.0 (69.3, 137.3), P < 0.001).
HA was associated with severe SARS-CoV-2 infection and could be used as a novel serum biomarker to predict the risk of COVID-19 progression in the post-COVID-19 era.
A total of 217 consecutive patients with COVID-19 were enrolled at Beijing Ditan Hospital between July 2023 and October 2023. HA levels were analyzed using biochemical detector. Logistic regression analysis was used to screen independent factors for severe COVID-19. The predictive performance of HA for severe infection was assessed by ROC curve. Furthermore, the relationship between HA levels and COVID-19 severity was investigated using multivariate logistic regression models after adjustment for potential confounders.
According to the cut-off value of HA, COVID-19 patients were divided into HA < 90 ng/mL group (80 cases) and HA ≥ 90 ng/mL group (137 cases). High HA levels were positively associated with the severe SARS-CoV-2 infection, including elevated inflammatory indicators, severe lung involvement, prolonged clinical course, and higher incidence of respiratory failure and death (P < 0.05). Logistic regression analysis suggested that HA was an independent predictor of severe COVID-19 (OR = 4.540, 95% CI = 2.105-9.790, P < 0.001). ROC curve analysis showed that the AUC of HA for severe infection was 0.724. HA levels were significantly higher in COVID-19 cases compared to the healthy population (123.9 (82.6, 174.1) vs. 50.5 (37.8, 66.8), P < 0.001), but similar to those with non-SARS-CoV-2 lung infection (121.6 (78.5, 175.6) vs. 106.0 (66.5, 149.7), P = 0.244). We also found that the first COVID-19 infections had higher HA levels (118.8 (79.5, 174.3) vs. 85.0 (61.1, 128.8), P < 0.001) and a higher proportion of severe infection (37.1% vs. 21.3%, P = 0.043) than re-infections. However, HA expression failed to fully return to normal levels with infection recovery (204.7 (152.9, 242.2) vs. 97.0 (69.3, 137.3), P < 0.001).
HA was associated with severe SARS-CoV-2 infection and could be used as a novel serum biomarker to predict the risk of COVID-19 progression in the post-COVID-19 era.
摘要：
■人类相同序列的严重急性呼吸道综合症冠状病毒-2（SARS-CoV-2）通过NamiRNA增强子网络上调透明质酸（HA），促进了2019年冠状病毒病（COVID-19）的进展，基于以往的实验研究。本研究旨在探讨后COVID-19时代HA对SARS-CoV-2感染严重程度的预测价值。
■在2023年7月至2023年10月期间，北京地坛医院共招募了217例COVID-19连续患者。使用生化检测器分析HA水平。采用Logistic回归分析筛选重症COVID-19的独立因素。通过ROC曲线评估HA对严重感染的预测性能。此外，在校正了潜在的混杂因素后,使用多变量逻辑回归模型研究了HA水平与COVID-19严重程度之间的关系.
■根据HA的截止值，将COVID-19患者分为HA<90ng/mL组(80例)和HA≥90ng/mL组(137例)。高HA水平与严重的SARS-CoV-2感染呈正相关。包括炎症指标升高，严重的肺部受累,延长临床病程，呼吸衰竭和死亡的发生率较高(P<0.05)。Logistic回归分析提示HA是重症COVID-19的独立预测因子(OR=4.540,95%CI=2.105~9.790,P<0.001)。ROC曲线分析显示严重感染的HA的AUC为0.724。与健康人群相比，COVID-19病例的HA水平明显更高（123.9（82.6，174.1）与50.5(37.8,66.8),P<0.001)，但与非SARS-CoV-2肺部感染患者相似（121.6（78.5，175.6）与106.0(66.5,149.7),P=0.244）。我们还发现，首次COVID-19感染的HA水平较高（118.8（79.5，174.3）与85.0(61.1,128.8),P<0.001），严重感染的比例更高（37.1%vs.21.3%,P=0.043）比再感染。然而,随着感染恢复，HA表达未能完全恢复到正常水平（204.7（152.9，242.2）与97.0(69.3,137.3),P<0.001)。
■HA与严重的SARS-CoV-2感染有关，可作为一种新的血清生物标志物来预测COVID-19后时代COVID-19进展的风险。
■在2023年7月至2023年10月期间，北京地坛医院共招募了217例COVID-19连续患者。使用生化检测器分析HA水平。采用Logistic回归分析筛选重症COVID-19的独立因素。通过ROC曲线评估HA对严重感染的预测性能。此外，在校正了潜在的混杂因素后,使用多变量逻辑回归模型研究了HA水平与COVID-19严重程度之间的关系.
■根据HA的截止值，将COVID-19患者分为HA<90ng/mL组(80例)和HA≥90ng/mL组(137例)。高HA水平与严重的SARS-CoV-2感染呈正相关。包括炎症指标升高，严重的肺部受累,延长临床病程，呼吸衰竭和死亡的发生率较高(P<0.05)。Logistic回归分析提示HA是重症COVID-19的独立预测因子(OR=4.540,95%CI=2.105~9.790,P<0.001)。ROC曲线分析显示严重感染的HA的AUC为0.724。与健康人群相比，COVID-19病例的HA水平明显更高（123.9（82.6，174.1）与50.5(37.8,66.8),P<0.001)，但与非SARS-CoV-2肺部感染患者相似（121.6（78.5，175.6）与106.0(66.5,149.7),P=0.244）。我们还发现，首次COVID-19感染的HA水平较高（118.8（79.5，174.3）与85.0(61.1,128.8),P<0.001），严重感染的比例更高（37.1%vs.21.3%,P=0.043）比再感染。然而,随着感染恢复，HA表达未能完全恢复到正常水平（204.7（152.9，242.2）与97.0(69.3,137.3),P<0.001)。
■HA与严重的SARS-CoV-2感染有关，可作为一种新的血清生物标志物来预测COVID-19后时代COVID-19进展的风险。
