| Objective Neonatal sepsis is a severe disease with high mortality and morbidity,early diagnosis and treatment can block the progression and improve the prognosis, butthe current relevant clinical signs and laboratory indicators about standard diagnosis ofneonatal sepsis are lag and nonspecific. Therefore, we are still lack of effective markersfor the clinical early warning on this disease. This study uses metabolomics as aplatform, based on gas chromatography-mass spectrometry technology (GC-MS), toestablish metabonomics detection method for neonatal serum samples by our instrumentand inquire into the serum metabolite differences between sepsis neonates and unsepsisneonates to find potential biomarkers group, to provide new diagnostic index for earlydiagnosis of neonatal sepsis and lay the foundation for follow-up studies.Methods Experiment1Through the study on influence of metabolite by differentsolvent, different sampling volume ratio, Internal standard solution concentration,different derivatization conditions，different injection mode and heating program,established suitable method about pretreatment of serum samples and data collectionbased on GC-MS. The repeatability of this method and the precision of the instrumentwere tested.Experiment230cases neotala of our hospital NICU who met the diagnostic criteria of neonatal sepsis from2012.01to2013.02as case group (Diagnostic criteria fromInternational pediatric sepsis consensus conference of2005).30cases neonatals whoexcept infection of the same period were selected as control group, the differences ofgender, gestational age, birth weight and age between the two groups had no statisticalsignificance. Total ion chromatogram(TIC) of metabolites acquired by GC-MStechnology, the spectral library of the instrument (NIST2008)was used for theidentification of metabolites. After data pretreatment of denoising, peak alignment,peak area calibration, using pattern recognition software, Principal componentanalysis(PCA) and Partial least square-discriminant analysis(PLS-DA) and t test wereused to analyze the data.Result Experiment11. The sample pretreatment methods include: the mixtureof400μl acetone and100μl chloroform as extraction agent,0.25mg/ml as internalstandard solution concentration and90℃(45min) as the derivatization conditions.2.The parameters of GC-MS were established through the study of the effect on the totalion chromatogram by different injection methods and different heating procedures,namely1μl（10:1）split injection mode, the initial oven temperature is60℃(1min),10℃/min rised to200℃(3min), and then10℃/min risesd to300C (5min) asheating procedure.3.The10main chromatographic peak area of a sample prepared for6injection samplesand a sample6times consecutive injection, shows relative standard deviation (RDS)within10%, which proves good repeatability of this method and the well precision ofthe instrument.Experiment2The differences in the serum metabolites distribution of sepsis neonates and non-sepsis neonates in PCA and PLS-DA model are visible combined with t test.Compared with non-sepsis neonatal group, the sepsis neonatal serum increased in thecontent of glucose, lactic acid, urea, pyruvic acid, phenylalanine, and decreased in thecontent of leucine, isoleucine, alanine, glutamine,palmitic acid,palmitoleic acid,linoleicacid, stearic acid. The sensitivity of the discriminat composited by the abovemetabolites was93.33%, specificity was100%, the Youden’s index was0.9333,compliance rate was96.66%.Conclusion1.the study established neonatal serum metabolome analysised methodbased on GC-MS technology,which demonstrates simple pre-treatment, goodreproducibility and precision, can be used for analysis of neonatal serum metabonomics.2.Gas chromatography-tandem mass spectrometry can indicate the neonatal sepsis.3.The discriminant composited by the above metabolites can be used for the diagnosisof neonatal sepsis. |
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