Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, India.
Department of Pharmacology, All India Institute of Medical Sciences, Jodhpur, India.
J Trace Elem Med Biol. 2022 Dec;74:127075. doi: 10.1016/j.jtemb.2022.127075. Epub 2022 Sep 13.
Nutritional deficiency is associated with weaken immune system and increased susceptibility to infection. Among other nutrients, several trace elements have been shown to regulate immune responses. Iron is one of the most abundant trace elements present in our body, which is required in various biological processes. Iron has an immunomodulatory function and thus influence the susceptibility to the course and outcome of a variety of viral infections. So, this present study was aimed to study relations of different iron-related biomarkers in association to severity and mortality in SARS-CoV-2 patients.
A total of 150 individuals infected with COVID-19 and 50 healthy individuals were recruited. Cases were divided based on severity (mild, moderate, and severe) and outcome (discharged or deceased). Serum iron, TIBC, ferritin, transferrin, transferrin saturation levels were analyzed by the direct colourimetric method.
In cases the median levels of serum iron, TIBC, transferrin, transferrin saturation and ferritin are 29 µg/dL, 132.53 µg/dL, 106.3 mg/dL, 17.74 % and 702.9 ng/dL respectively. Similarly, in controls the median levels of serum iron, TIBC, transferrin, transferrin saturation and ferritin are 53 µg/dL, 391.88 µg/dL, 313.51 mg/dL, 12.81 % and 13.52 ng/dL respectively. On comparing the cases with the controls, a significant lower level of iron, TIBC, and transferrin were found in the cases along with the significant higher levels of ferritin and transferrin saturation. On comparing the Receiver operating characteristic (ROC) curves of Iron, Ferritin, Transferrin, Transferrin sat % and TIBC in relation to survival in COVID-19 patients it was found that iron, followed by transferrin and ferritin has the highest area under the curve (AUC) with 74 %, 63 % and 61 % respectively. Further, in pairwise analysis of ROC curve, a significant difference was found between the Iron-transferrin (p < 0.01), iron-TIBC (p < 0.001) and transferrin-ferritin (P < 0.01). The multiple regression model based on Iron and transferrin outperformed any other combination of variables via stepwise AIC selection with an AUC of 98.2 %. The cutoff point according to Youden's J index is characterized with a sensitivity of 98 % and a specificity of 96.8 %, indicating that iron along with transferrin can be a useful marker that may contribute to a better assessment of survival chances in COVID-19.
Our study demonstrated a significantly decreased levels of iron, TIBC, & transferrin and a significantly increased levels of ferritin and transferrin saturation in COVID-19 patients when compared with controls. Further, Iron and transferrin were observed to be a good predictor of mortality in patients with COVID-19. From the above analysis we confirm that iron-related biomarkers play an important role in the development of oxidative stress and further lead to activation of the cytokine storm. So, continuous monitoring of these parameters could be helpful in the early detection of individuals developing the severe disease and can be used to decrease mortality in upcoming new waves of COVID-19.
营养缺乏与免疫系统减弱和易感染增加有关。在其他营养素中，一些微量元素已被证明可以调节免疫反应。铁是我们体内最丰富的微量元素之一，它在各种生物过程中都需要。铁具有免疫调节功能，因此会影响各种病毒感染的病程和结果。因此，本研究旨在研究 SARS-CoV-2 患者中不同铁相关生物标志物与严重程度和死亡率的关系。
共招募了 150 名感染 COVID-19 的个体和 50 名健康个体。病例根据严重程度（轻度、中度和重度）和结局（出院或死亡）进行分组。采用直接比色法分析血清铁、总铁结合力、铁蛋白、转铁蛋白和转铁蛋白饱和度水平。
在病例中，血清铁、总铁结合力、转铁蛋白、转铁蛋白饱和度和铁蛋白的中位数水平分别为 29μg/dL、132.53μg/dL、106.3mg/dL、17.74%和 702.9ng/dL。同样，在对照组中，血清铁、总铁结合力、转铁蛋白、转铁蛋白饱和度和铁蛋白的中位数水平分别为 53μg/dL、391.88μg/dL、313.51mg/dL、12.81%和 13.52ng/dL。在将病例与对照组进行比较时，发现病例组的铁、总铁结合力和转铁蛋白水平显著降低，而铁蛋白和转铁蛋白饱和度水平显著升高。在比较 COVID-19 患者生存的铁、铁蛋白、转铁蛋白、转铁蛋白饱和度和总铁结合力的 ROC 曲线的Receiver operating characteristic（ROC）曲线时，发现铁、转铁蛋白和铁蛋白具有最高的曲线下面积（AUC），分别为 74%、63%和 61%。此外，在 ROC 曲线的两两分析中，铁-转铁蛋白（p<0.01）、铁-总铁结合力（p<0.001）和转铁蛋白-铁蛋白（P<0.01）之间存在显著差异。基于铁和转铁蛋白的多元回归模型通过逐步 AIC 选择优于任何其他变量组合，AUC 为 98.2%。根据 Youden's J 指数的截断点具有 98%的敏感性和 96.8%的特异性，表明铁和转铁蛋白可以作为有用的标志物，有助于更好地评估 COVID-19 患者的生存机会。
与对照组相比，COVID-19 患者的铁、总铁结合力和转铁蛋白水平显著降低，而铁蛋白和转铁蛋白饱和度水平显著升高。进一步观察到铁和转铁蛋白是 COVID-19 患者死亡率的良好预测指标。从上述分析中我们可以确认，铁相关生物标志物在氧化应激的发展中起着重要作用，并进一步导致细胞因子风暴的激活。因此，连续监测这些参数有助于早期发现病情加重的个体，并有助于降低即将到来的 COVID-19 新一波疫情中的死亡率。
