| Sepsis, the systemic inflammatory response syndrome to severe infection, is the leading cause of death in intensive care units (ICU). This syndrome is associated with a complex network of biological mediators, and its pathogenesis is not yet clear. It involves patients complicated primary diseases, complex pathogens, complex toxic factors, complex gene polymorphisms and host responses, complex multiple system interaction network, etc. The complexity and nonlinearity lead to serious difficulties in diagnosis and prognosis prediction of sepsis, which is also the main reason of high mortality in sepsis. In recent years, many groups devoted to sepsis biomarker research to try to find some biomarker which could demonstrate the presence or absence or severity of sepsis, and could distinguish bacterial from viral and fungal infection, and systemic sepsis from local infection, in order to promote the development of the methods in diagnosis, prediction and new treatment of sepsis. So far, more than200biomarkers have been assessed for diagnosis or prognosis in sepsis. However, none has been routinely employed in clinical practice due to sensitivity or specificity issues, the effect of a single biomarker for the diagnosis and prognosis of sepsis is not ideal. Therefore, it is important for us to find some new and reliable biomarkers to improve diagnosis and prognosis prediction in sepsis using modern science and technology.We adopted the method of the cecal ligature and puncture (CLP) to prepare a rat model of sepsis. All the rats were divided into four groups according to their outcomes:the group of24h non-survivor, the group of48h non-survivor, the group of survivor, and the group of sham.2or2.5millilitres of blood were obtained by direct cardiac puncture under deep anesthesia at12hour after sepsis induction. Serum samples were depleted of high-abundance proteins, labeled with isobaric tags (iTRAQTM), and the proteomic changes were analyzed using two-dimensional liquid chromatography and tandem mass spectrometry in tne24h non-survivor, the48h non-survivor, the survivor, and the sham groups. ELISAs were used to further confirm the protein identification and differential expression. A logistic regression was then used to screen the index set for diagnosis and prognosis of sepsis in rats. We established5logistic regression models for diagnosis and a model for prognosis prediction of sepsis and further to evaluated the reliabilities of these models. Moreover, to investigate whether PTX3could be used as a reliable markers for diagnosis and prognosis prediction of patients with sepsis, we evaluated the PTX3in patients with sepsis and compared the potential significance of C-reactive protein (CRP), procalcitonin (PCT) and PTX3in the diagnosis and prognosis prediction of sepsis. All the results are as follows:1. By quantitative LC-MS/MS analysis with iTRAQ,162proteins were detected in serum of rats. A total of47differentially expressed proteins were identified in serum samples in septic rats compared with shams, of which31proteins were up-regulated and16proteins were down-regulated in the septic rats. In addition,28serum proteins were differentially expressed in non-survivor rats compared with survivor ones, of which14proteins were up-regulated and14proteins were down-regulated in the non-survivors.2. Based on the iTRAQ findings above, the protein markers potentially associated with sepsis were further confirmed by ELISA. Twenty-five differential expression proteins were tested by ELISA using commercially available ELISA kits.21of25proteins measured by ELISA and iTRAQ analysis gave similar results in term of changes in protein expression. To evaluate the proteins with significantly altered serum levels as potential biomarkers in the diagnosis of sepsis, ELISA results of25differential expression proteins from septic rats and sham rats were analyzed. It was found that several biomarkers such as pentraxin3(PTX3), multimerin1(MMRN1), ficolin1(FCN1), carboxypeptidase N (CPN2), serine protease1(PRSS1) and platelet factor4(PF4) were tightly associated with the diagnosis of sepsis and six logistic regression analysis models were established for diagnosis of sepsis by these biomarkers. Six logistic regression analysis models were as follows:Logit P=1.473PTX3-37.054, Logit P=4.118MMNR139.249, Logit P=0.053FCN1-52.381, Logit P=0.074CPN221.569, Logit P=9.967PF4-6.520, Logit P=0.039PRSS1-4.227. All the six models for the diagnosis of sepsis in the validation set show a sensitivity of100percent and specificity of100percent. To evaluate the proteins with significantly altered serum levels as potential biomarkers in the prognosis prediction of sepsis, ELISA results of25differential expression proteins from non-survivor and survivor rats were analyzed. A logistic regression model for the prognosis prediction of sepsis including a set of4biomarkers, multimerin1(MMRN1), pro-platelet basic protein (PPBP), fibrinogen alpha (FGa), and fibrinogen beta (FGβ) was established which could be used to estimate prognosis of sepsis in rats. The logistic regression model predicted the outcome of sepsis in a validation set with a sensitivity of100percent and specificity of91.7percent. The study reveals a number of potential new sepsis biomarkers, and provides new thoughts and experimental clues for the clinical diagnosis and prognosis prediction of sepsis.3. To investigate whether PTX3could be used as a reliable markers for diagnosis and prognosis prediction of patients with sepsis, we selected a batch of patients with sepsis from intensive care unit(ICU) for clinical research, and evaluated the PTX3in patients with sepsis and compared the results of PTX3with C-reactive protein (CRP) and procalcitonin (PCT) in the diagnosis and prognosis of sepsis. PTX3, CRP and PCT were measured in serum by the enzyme-linked immunosorbent assay kit. The levels of three indicators were higher among patients with sepsis than patients with SIRS (P<0.05). In addition, serum PCT in non-survivors with sepsis were higher than in survivors (4.05±0.63vs3.03±0.09, p<0.05), whereas PCT and CRP levels did not differ between survivors and non-survivors sepsis patients. ROC analysis of PTX3, CRP, PCT and APACHE Ⅱ score shown that the ROC curve area of PTX3are the biggest in the diagnosis and prognosis. The cut-off of2.43ng/ml for PTX3was defined as early diagnosis of patients with sepsis and3.16ng/ml for PTX3was defined as early predictors of unfavorable outcome. In contrast to CRP, PCT and APACHE Ⅱ, PTX3appears to be a more useful early biomarker for diagnose and prognosis prediction in patients with sepsis.In this study, we combined iTRAQ labelled peptides and LC/MS/MS system for serum proteomic study and found that several biomarkers (PTX3, MMRN1, FCN1, CPN2, PRSS1and PF4) were closely correlated with sepsis and established six logistic regression analysis models for the diagnosis of sepsis and established a logistic regression model with a set of4biomarkers (MMRN1, PPBP, FGa and FGP) which could be used for the prognosis prediction of sepsis in rats. Moreover, PTX3level was correlated with diagnosis or mortality in patients with sepsis, its effectiveness was better than that of traditional biological markers (PCT and CRP). This study revealed several potential new sepsis biomarkers by using proteomics strategies, and provided new experimental evidences and research methods for the early diagnosis, efficacy evaluation and prognosis prediction of sepsis. |
PDF Full Text Request