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。
【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.
[1]Yu J, Zhu L, Ni J, et al.Technique failure in peritoneal dialysis-related peritonitis: risk factors and patient survival[J].Renal Failure, 2023, 45(1):2205536-2205536
[2]Dzekova-Vidimliski P, Nikolov I G, Gjorgjievski N, et al.Peritoneal dialysis-related peritonitis: Rate,clinical outcomes and patient survival[J].prilozi, 2021, 42(3):47-55
[3]Gadola L, Poggi C, Dominguez P, et al.Risk factors and prevention of peritoneal dialysis-related peritonitis[J].Peritoneal Dialysis International, 2019, 39(2):119-125
[4]Zhang Q Y, Jin B, Feng Y, et al.Etiological diagnostic value of metagenomic next-generation sequencing in peritoneal dialysis-related peritonitis[J].Chinese Journal of Hepatology, 2023, 39(1):8-12
[5]Goodlad C, George S, Sandoval S, et al.Measurement of innate immune response biomarkers in peritoneal dialysis effluent using a rapid diagnostic point-of-care device as a diagnostic indicator of peritonitis[J].Kidney International, 2020, 97(6):1253-1259
[6]Peng Y, Zeng Y, Zheng T, et al.Effects of Tiaopi Xiezhuo decoction on constipation and gut dysbiosis in patients with peritoneal dialysis[J].Pharmaceutical Biology, 2023, 61(1):531-540
[7]Zhou J, Yang C, Lei W, et al.Exploration of the correlation between intestinal flora and Escherichia coli peritoneal dialysis-related peritonitis[J].BMC nephrology, 2022, 23(1):1-9
[8]Novljan G, Kri?an-Hergouth V, Battelino N.Peritonitis related to chronic peritoneal dialysis in Slovenian pediatric patients[J].Clinical Nephrology, 2021, 96(1):89-95
[9]Wang D, Lai M, Song H, et al.Integration of interleukin-6 improves the diagnostic precision of metagenomic next-generation sequencing for infection in immunocompromised children[J]. Frontiers in Microbiology, 2022, 13: 819467.[J]. Frontiers in Microbiology, 2022, 13:819467-819467
[10]Virzì G M, Mattiotti M, Milan Manani S, et al.Peritoneal NGAL: a reliable biomarker for PD-peritonitis monitoring[J]. Journal of Nephrology, 2023: 1-3.[J].Journal of Nephrology, 2023, :1-3
[11]庄乙君, 陈文, 云曼丽, 钟业腾, 林叶, 李军, 李飞, 汪水连, 韩淑苗.腹透液中中性粒细胞明胶酶相关载脂蛋白联合白细胞介素对腹透相关性腹膜炎预测价值[J].临床军医杂志, 2022, 50(08):862-864
[12]周飞燕, 吴凌慧, 汤素华等.和与检测早期诊断腹膜透析感染性腹膜炎及预后的临床价值[J].中华医院感染学杂志, 2020, 30(18):2772-2775
[13]Cao J, Xiao Y, Zhang M, et al.Deep Learning of Dual Plasma Fingerprints for High‐Performance Infection Classification[J].Small, 2023, 19(7):2206349-2206349
[14]FFung W W S, Li P K T.Recent advances in novel diagnostic testing for peritoneal dialysis-related peritonitis[J].Kidney Research and Clinical Practice, 2022, 41(2):156-156
[15]Zhang J, Friberg I M, Kift-Morgan A, et al.Machine-learning algorithms define pathogen-specific local immune fingerprints in peritoneal dialysis patients with bacterial infections[J].Kidney International, 2017, 92(1):179-191
[16]Salzer W L.Peritoneal dialysis-related peritonitis: challenges and solutions[J]. International journal of nephrology and renovascular disease, 2018: 173-186.[J].International journal of nephrology and renovascular disease, 2018, :173-186
[17]Llewelyn M J, Cohen J.Tracking the microbes in sepsis: advancements in treatment bring challenges for microbial epidemiology[J].Clinical infectious diseases, 2007, 44(10):1343-1348
[18]原慧芝, 朱学研, 杨立明, 张晓暄, 李忻阳, 谢彤, 翟婧竹, 庄小花, 崔文鹏.多中心肺炎克雷伯菌腹膜透析相关性腹膜炎的临床转归及治疗失败的危险因素[J].中国医学科学院学报, 2023, 45(02):227-234
[19]Dyck L, Mills K H G.Immune checkpoints and their inhibition in cancer and infectious diseases[J].European journal of immunology, 2017, 47(5):765-779
[20]de Lima J D, de Paula A G P, Yuasa B S, et al.Genetic and Epigenetic Regulation of the Innate Immune Response to Gout[J].Immunological Investigations, 2023, 52(3):364-397
[21]Ren J, Qiang Z, Li Y, et al.Biomarkers for a histological chorioamnionitis diagnosis in pregnant women with or without group B streptococcus infection: a case-control study[J].BMC Pregnancy and Childbirth, 2021, 21(1):1-11
[22]Santos J E, Rodríguez Magari?os C, García Gago L, et al.Long-term trends in the incidence of peritoneal dialysis-related peritonitis disclose an increasing relevance of streptococcal infections: a longitudinal study[J].PLoS One, 2020, 15(12):e0244283-e0244283
[23]Zeng Y, Jiang L, Lu Y, et al.Peritoneal dialysis-related peritonitis caused by gram-negative organisms: ten-years experience in a single center[J].Renal Failure, 2021, 43(1):993-1003
[24]Yang X W, Li H, Feng T, et al.Impairment of antigen-presenting function of peripheral Impairment of antigen-presenting function of peripheral γδT cells in patients with sepsis T cells in patients with sepsis[J].Clinical and Experimental Immunology, 2022, 207(1):104-112
[25]Finney S J, Leaver S K, Evans T W, et al.Differences in lipopolysaccharide-and lipoteichoic acid-induced cytokine/chemokine expression[J]. Intensive care medicine, 2012, 38: 324-332.[J].Intensive care medicine, 2012, 38:324-332
[26]Finney S J, Leaver S K, Evans T W, et al.Differences in lipopolysaccharide-and lipoteichoic acid-induced cytokine/chemokine expression[J]. Intensive care medicine, 2012, 38: 324-332.[J].Intensive care medicine, 2012, 38:324-332
[27]Lin C Y, Roberts G W, Kift-Morgan A, et al.Pathogen-specific local immune fingerprints diagnose bacterial infection in peritoneal dialysis patients[J].Journal of the American Society of Nephrology: JASN, 2013, 24(12):2002-2002
