中国血液净化

中国血液净化 ›› 2024, Vol. 23 ›› Issue (05): 351-355.doi: 10.3969/j.issn.1671-4091.2024.05.007

• 临床研究 • 上一篇    下一篇

宏基因组二代测序和细胞因子在PD相关腹膜炎早期诊断中的应用

何萌萌     符 姣     姚 玲     邵小淇    李  楠     张  培   

  1. 230031 合肥，1安徽医科大学第一附属医院肾脏内科
  • 收稿日期:2023-10-24 修回日期:2024-02-07 出版日期:2024-05-12 发布日期:2024-05-12
  • 通讯作者: 张培 E-mail:zhangpei@ahmu.edu.cn
  • 基金资助:
    国家自然科学基金(81900697)

Application of metagenomic second-generation sequencing and cytokines in the early diagnosis of peritoneal dialysis-associated peritonitis

HE Meng-meng, FU Jiao, YAO Ling, SHAO Xiao-qi, LI Nan, ZHANG Pei   

  1. Department of Nephrology, The First Affiliated Hospital of  Anhui Medical   University, Hefei 230031, China
  • Received:2023-10-24 Revised:2024-02-07 Online:2024-05-12 Published:2024-05-12
  • Contact: 230031 合肥，1安徽医科大学第一附属医院 E-mail:zhangpei@ahmu.edu.cn

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摘要： 目的 探究宏基因组二代测序(metagenomic second-generation sequencing，mNGS)技术在早期检测腹膜透析相关腹膜炎(peritoneal dialysis-associated peritonitis，PDAP)患者细菌感染的病原学价值，了解不同细菌感染类型中细胞因子分布差异，构建相关风险预测模型。 方法 收集2020年4月─2023年4月就诊于安徽医科大学第一附属医院，符合国际腹膜透透协会(international society for peritoneal dialysis,ISPD)诊断标准的腹膜透析(peritoneal dialysis,PD)患者的临床资料，同时将其入院4小时内PD流出液送检mNGS检查及普通培养，并测定上清液中细胞因子水平，比较mNGS检测与实验室微生物培养病原学诊断结果,综合临床意义分为革兰氏阳性菌(G+菌)组、革兰氏阴性菌(G-菌)组和培养阴性(G0)组，比较2组细胞因子水平差异，确认危险因素并构建风险预测模型，同时进行效能检测。 结果 共50例PD相关腹膜炎患者纳入本研究，mNGS检测中41例患者检出病原体，检测阳性率高于微生物培养(χ2=0.059，P=0.440)，mNGS检测时间低于微生物培养(t=5.180，P＜0.001)。多因素Logistics回归分析提示PD液中高白细胞介素(IL)10(OR=1.010,95% CI:1.000～1.020,P=0.024)、低IL-6(OR=0.620,95% CI:0.360～0.890,P=0.038)及高血清降钙素原(OR=1.200,95% CI:1.050～1.530,P=0.016)、低C反应蛋白水平(OR=1.014,95% CI:1.010～1.050,P=0.035)为PDAP预测G-菌感染的独立危险因素。ROC曲线及列线图结果显示上述炎症因子联合较单一因子对预测G-菌感染价值更大。 结论 mNGS在早期快速检测PDAP病原体方面显示了极大的诊断潜力，PD流出液中细胞因子IL-6、IL-10及血清降钙素原、C反应蛋白水平的整合提高了mNGS结果解释的精确度，依据细胞因子构建的风险预测模型可以较好区分不同种类细菌相关PDAP腹膜炎的患者。

关键词: 腹膜透析, 腹膜炎, 宏基因组二代测序, 分子诊断标志物

Abstract: 【Abstract】Objective To assess the performance of metagenomic second-generation sequencing(mNGS) in early detection of bacterial infection in patients with peritoneal dialysis-related peritonitis and to investigate whether the integration of cytokines and mNGS assay could improve diagnostic accuracy. To construct and evaluate the etiological value of a risk prediction model to differentiate peritoneal dialysis-associated peritonitis (PDAP) caused by different types of bacteria. Methods PDAP patients admitted to the First Affiliated Hospital of Anhui Medical University from 2020 to 2023 were included in this study, and randomly divided into groups based on the results of mNGS and conventional microbiology testing (CMT). The clinical data were simultaneously collected. PD fluids were sent for conventional microbiological test (CMT), mNGS, and cytokine measurement in parallel. Independent predictors were selected by univariate and multivariate Logistics regression analysis, and prognostic nomogram was constructed for G- and G+ related . The accurate and discriminative abilities of the nomogram were evaluated by Objective  To assess metagenomic second-generation sequencing(mNGS) in the early detection of bacterial infection of peritoneal dialysis-related peritonitis(PDAP), to investigate whether mNGS combined with cytokines could improve the diagnostic accuracy, and to construct a risk prediction model to predict PDAP caused by different types of bacteria and its unfavorable outcome.  Methods   PDAP patients admitted to the First Affiliated Hospital of Anhui Medical University from 2020 to 2023 were included in this study. They were randomly divided into groups based on the results of mNGS and conventional microbiology testing (CMT). Their clinical data were collected, and peritoneal dialysis fluids were tested for CMT, mNGS, and cytokine measurement. Univariate and multivariate logistics regression analyses were used to find out the independent predictors, and a nomogram was constructed for the prediction of G- and G+ bacterial related prognosis. Efficacy of the nomogram was evaluated by receiver operating characteristic curve (ROC) and clinical impact curve (CIC).  Results  A total of 50 PDAP patients were included in this study. Peritoneal fluids were tested for pathogens by mNGS in 41 patients, showing higher positive detection rate (82% vs. 76%, P=0.440) and less detection time (23.0h vs. 29.4h, P＜0.001) than CMT. A model to predict the PDAP by different types of bacteria and a nomogram were constructed,  from which we found that IL-10 and IL-6 in peritoneal dialysis fluid, serum procalcitonin and serum C-reactive protein were the most important biomarkers to predict the prognosis of PDAP by different types of bacteria.  Conclusions   mNGS demonstrates its powerful potentials in the early and rapid detection of pathogens of PDAP. Comprehensive use of IL6 and IL10 in peritoneal dialysis fluid, serum procalcitonin, and serum C-reactive protein will increase the accuracy in the interpretation of mNGS results. A risk prediction model constructed based on cytokines can effectively distinguish G- and G+ bacterial PDAP. 

Key words: Peritoneal dialysis, Peritoneal dialysis related peritonitis, Metagenomic second-generation sequencing, Diagnostic biomarker, Clinical prediction model

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