血清Ninj1作为预测COVID-19患者严重程度的潜在生物标志物的评估

IF 2.9 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
Hua Sun , Ling Yan , Hong Chen, Ding Wang, Chenfan Niu, Siyang Wen, Qin Hu
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引用次数: 0

摘要

感染SARS-CoV-2会提高细胞因子的表达,导致细胞因子风暴,这是导致严重疾病和死亡的主要因素;然而,缺乏预测疾病严重程度和预防的有效标志物。因此,我们研究了血清神经损伤诱导蛋白1 (Ninj1)水平(质膜破裂介质)与COVID-19患者肺损伤程度之间的关系,以预测SARS-CoV-2感染的严重程度。这项研究包括62名健康参与者和264名COVID-19患者。采用Pearson相关检验检测血清中nin1、细胞因子(白细胞介素(IL)- 1β、IL-2、IL-6、IL-8、IL-10、干扰素-γ (IFN-γ)、肿瘤坏死因子-α (TNF-α))和炎症标志物(c反应蛋白(CRP)、降钙素原(PCT)、铁蛋白、乳酸脱氢酶(LDH))的水平,并将其与疾病严重程度进行相关性分析。我们的测试显示,在COVID-19患者中观察到Ninj1、IL-6、PCT和LDH水平升高,这些浓度与疾病的严重程度有关。相关分析表明,nin1水平与这些生物标志物的浓度有关。此外,Ninj1的表达与SARS-CoV-2的病毒载量相关。循环Ninj1水平具有良好的预测呼吸衰竭和预后的潜力。最后,我们发现SARS-CoV-2感染增加了血清Ninj1水平,这与疾病严重程度相关。nin1可作为预测COVID-19严重程度的血清生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of serum Ninj1 as a potential biomarker for predicting severity in patients with COVID-19
Infection with SARS-CoV-2 elevates the expression of cytokines, resulting in a cytokine storm that serves as the primary factor for severe illness and mortality; however, effective markers for predicting disease severity and preventing are lacking. Thus, we investigated the association between serum levels of nerve injury-induced protein 1 (Ninj1), a mediator of plasma membrane rupture, and the extent of lung damage in COVID-19 patients was examined to anticipate the severity of SARS-CoV-2 infection. This study included 62 healthy participants and 264 patients with COVID-19. The serum levels of Ninj1, cytokines (interleukin (IL)- 1β, IL-2, IL-6, IL-8, IL-10, interferon-γ (IFN-γ), and tumor necrosis factor-alpha (TNF-α)), and inflammatory markers (C-reactive protein (CRP), procalcitonin (PCT), ferritin, and lactate dehydrogenase (LDH)) were measured and correlated with disease severity using Pearson’s correlation test. Our tests revealed that elevated levels of Ninj1, IL-6, PCT, and LDH were observed in individuals suffering from COVID-19, and these concentrations were linked to the severity of the illness. Analysis of correlation indicated that Ninj1 levels were related to the concentrations of these biomarkers. Additionally, Ninj1 expression exhibited a correlation with the viral load of SARS-CoV-2. Circulating Ninj1 levels showed good predictive potential for respiratory failure and prognosis. Finally, we found that SARS-CoV-2 infection increases serum Ninj1 levels, which are correlated with disease severity. Ninj1 could serve as a serum biomarker for forecasting the severity of COVID-19.
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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