Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.
Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden.
J Immunol Methods. 2021 Feb;489:112908. doi: 10.1016/j.jim.2020.112908. Epub 2020 Nov 7.
The correct diagnosis of acute infections as to bacteria, mycoplasma or virus is a clinical challenge and has a great impact on the therapeutic decisions. Current diagnostic tests of mycoplasma pneumoniae infections of the respiratory tract such as PCR and serology are either somewhat unreliable or slow and do not entirely meet the clinical needs of accurate and fast diagnosis. The aim of this report was to examine a panel of candidate biomarkers and their capacity to distinguish mycoplasma pneumoniae respiratory infections from respiratory infections caused by either bacterial or virus.
Patients with confirmed etiology of their acute respiratory infections (n = 156) were included of which 28 patients were diagnosed with mycoplasma pneumoniae. Blood was taken before any antibiotics treatment and analysed for Azurocidin (HBP), Calprotectin, CRP, Human Neutrophil Lipocalin (HNL), Interferon γ-induced Protein 10 kDa (IP-10), Procalcitonin (PCT), Thymidine Kinase 1 (TK1), TNF-Related Apoptosis-Inducing Ligand (TRAIL).
Individually the concentrations of IP-10, TK1 and P-HNL distinguished mycoplasma pneumoniae from bacterial infections with AUCs of 0.79-0.85. However, in combination, TK1 with either IP-10 or P-HNL showed an AUC of 0.97-0.95. In the distinction between mycoplasma pneumoniae and viral respiratory infections CRP, Calprotectin and TRAIL showed individual AUCs of 0.94-0.84. Together with either P-HNL dimer or PCT, CRP showed AUCs of 0.97.
Our results indicate that it may be possible to design useful diagnostic algorithms of biomarkers that could help distinguish mycoplasma pneumoniae from respiratory infections caused by bacteria or virus. The development of rapid point-of-care assays based on such algorithms could be clinically useful tools in the therapeutic decision-making.
检查一组候选生物标志物及其区分肺炎支原体呼吸道感染与细菌或病毒引起的呼吸道感染的能力。
纳入了确诊病因的急性呼吸道感染患者(n=156),其中 28 例患者被诊断为肺炎支原体感染。在开始使用抗生素之前采集血液,并分析天青杀素(HBP)、钙卫蛋白、C 反应蛋白、人中性粒细胞明胶酶相关脂质运载蛋白(HNL)、干扰素 γ 诱导蛋白 10 kDa(IP-10)、降钙素原(PCT)、胸苷激酶 1(TK1)和肿瘤坏死因子相关凋亡诱导配体(TRAIL)的浓度。
IP-10、TK1 和 P-HNL 的浓度可单独区分肺炎支原体与细菌感染,AUC 为 0.79-0.85。然而,在组合中,TK1 与 IP-10 或 P-HNL 的 AUC 为 0.97-0.95。在区分肺炎支原体与病毒性呼吸道感染时,C 反应蛋白、钙卫蛋白和 TRAIL 的 AUC 分别为 0.94-0.84。与 P-HNL 二聚体或 PCT 联合使用时,C 反应蛋白的 AUC 为 0.97。
我们的结果表明,设计区分肺炎支原体与细菌或病毒引起的呼吸道感染的有用的生物标志物诊断算法是可能的。基于这些算法的快速床边检测方法的开发可能是治疗决策中的有用的临床工具。