血清代谢组学与细胞因子谱在儿童慢性活动性EB病毒感染中的预测价值  

Predictive value of serum metabolomics and cytokine profiles in children with chronic active Epstein-Barr virus infection

作　　者：施金金 张方园 陈颖青 严秋丽 SHI Jinjin;ZHANG Fangyuan;CHEN Yingqing;YAN Qiuli(Department of Digestive and Infection,Suzhou Wujiang District Children’s Hospital,Jiangsu Province,Suzhou 215200,China)

机构地区：[1]江苏省苏州市吴江区儿童医院消化感染科,江苏苏州215200

出　　处：《妇儿健康导刊》2025年第3期189-193,共5页JOURNAL OF WOMEN AND CHILDREN'S HEALTH GUIDE

基　　金：江苏省苏州市吴江区“科教兴卫”项目(WWK202111);江苏省苏州市吴江区儿童医院青年基金项目(2021QN02)。

摘　　要：目的探讨血清代谢组学与细胞因子谱在儿童慢性活动性EB病毒感染(CAEBV)中的预测价值。方法选取2021年1月至2023年12月苏州市吴江区儿童医院收治的50例CAEBV患儿作为CAEBV组,另选取50例健康儿童为对照组。采集血清样本,应用代谢组学和细胞因子谱技术,分析两组代谢产物和细胞因子水平。构建logistic预测模型分析血清代谢组学与细胞因子谱对儿童CAEBV的预测价值。结果两组脂肪酸、氨基酸及代谢产物存在统计学意义(P<0.05)。与对照组相比,CAEBV组白细胞介素-1β(IL-1β)、白细胞介素-6(IL-6)、白细胞介素-10(IL-10)、肿瘤坏死因子-α(TNF-α)、γ干扰素(IFN-γ)水平均较高,差异有统计学意义(P<0.05)。采用logistic回归模型,通过逐步回归法选择显著的自变量[代谢物(亚油酸、二十碳五烯酸、亮氨酸、苯丙氨酸、乳酸、尿素)和细胞因子(IL-1β、IL-6、IL-10、TNF-α、IFN-γ)],构建预测模型log(p/1-p)=0.615×亚油酸+0.475×二十碳五烯酸+0.420×亮氨酸+0.480×苯丙氨酸+0.540×乳酸+0.462×尿素+0.700×IL-1β+0.850×IL-6+0.610×IL-10+0.790×TNF-α+0.870×IFN-γ。结果显示,该模型能够预测CAEBV(P<0.05)。结论血清代谢组学与细胞因子谱在儿童CAEBV的早期预测中具有重要价值,可成为预测儿童CAEBV的生物标志物。Objective To investigate the predictive value of serum metabolomics and cytokine profiles in children with chronic active Epstein-Barr virus infection(CAEBV).Methods A total of 50 children with CAEBV who were admitted to Suzhou Wujiang District Children’s Hospital from January 2021 to December 2023 were selected as the CAEBV group,and another 50 healthy children were selected as the control group.Serum samples were collected and analyzed using metabolomics and cytokine profiles techniques to analyze the levels of metabolites and cytokines in the two groups.The logistic prediction model was constructed to analyze the predictive value of serum metabolomics and cytokine profiles in children with CAEBV.Results There were significant differences in fatty acids,amino acids,and metabolites between the two groups(P<0.05).The levels of interleukin-1β(IL-1β),interleukin-6(IL-6),interleukin-10(IL-10),tumor necrosis factor-α(TNF-α),and interferon-γ(IFN-γ)in the CAEBV group were higher than those in the control group(P<0.05).The logistic regression model of log(p/1-p)=0.615×linoleic acid+0.475×eicosapentaenoic acid+0.420×leucine+0.480×phenylalanine+0.540×lactic acid+0.462×urea+0.700×IL-1β+0.850×IL-6+0.610×IL-10+0.790×TNF-α+0.870×IFN-γwas constructed using stepwise regression to select significant independent variables(metabolites[linoleic acid,eicosapentaenoic acid,leucine,phenylalanine,lactic acid,and urea]and cytokines[IL-1β,IL-6,IL-10,TNF-α,IFN-γ]).The results showed that the model could predict CAEBV(P<0.05).Conclusion Serum metabolomics and cytokine profiles have important value in the early prediction of children with CAEBV and can become a biomarker for predicting children with CAEBV.

关 键 词：血清代谢组学 细胞因子谱 慢性活动性EB病毒感染 预测价值 

分 类 号：R446.1[医药卫生—诊断学]