Prediction And Approach Assessing The Incidence Of Preeclampsia Of Serum Markers And Metabonomics At The Second Trimester

Section 1 Prediction and approach assessing the incidence of preeclampsia of serum markers at the second trimesterOBJECTIVE:To investigate whether the serous concentrations of Down's syndrome markers, placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) in early pregnancy are altered in women who develope preeclampsia, and identify the factors associated with the increased risk of developing preeclampsia and to assess the predictive value on the preeclampsia of these factors.METHODS:A nested, case-control study was performed within a prospective cohort study of Down syndrome screening attending our hospitals in Shanghai for their prenatal care. We investigated 46 preeclamptic patients. The control group consisted of 46 healthy pregnant women. We reviewed the obstetric records of these women and measured serous levels ofα-fetoprotein (AFP), unconjugated estriol (uE3), total human chorionic gonadotrophin (HCG), sFlt-1 and PlGF of the serum sampled at 14-20 weeks of gestation.RESULTS:1. Changed levels of PlGF, BMI, AFP and diastolic blood pressure at first prenatal visit were associated with risk of preeclampsia.2. Between14-20 weeks, the ROC curve for the combining AFP,sFlt-1,BMI and diastolic blood pressure at first prenatal visit for the group with preeclampsia compared with unaffected subjects yielded a AUC of 0.874 (95%CI0.79-0.93). At 95.65% specificity, the cutoff value was-854.19, and sensitivity was 65.22%, Youden index and accuracy rate were 0.61 and 80.5%.CONCLUSION:During early second trimester, combined PlGF, BMI, AFP and diastolic blood pressure together may provide a helpful method for predicting preeclampsia. Section 2 Prediction and approach related to the incidence of pre-eclampsia of metabonomics at the second trimesterOBJECTIVE: High-performance liquid chromatography-time of flight mass spectrometry based metabolism was used to investigate the differences of serous metabolic patterns between patients with preeclampsia and healthy controls to find tentative diagnostic biomarkers. Based on the findings above, we tried to describe the metabolite changes related to the disease .It will provide a novel technological platform for the mechanism study of preeclampsia and assess the predictive value on the preeclampsia of these biomarkers.METHODS:A nested, case-control study was performed within a prospective cohort study of Down syndrome screening that our hospitals in Shanghai attended for their prenatal care. The serous samples were obtained when they came for Down syndrome screening. We investigated 46 preeclamptic patients. The control group consisted of 46 healthy pregnant women. We reviewed the obstetric records of these women. The serum samples were analyzed with High-performance liquid chromatography-time of flight mass spectrometry and the combination of the +ESI and -ESI scans were used to provide more useful information about the samples .The serum metabolic profiles were obtained. Principal components analysis (PCA) and Support Vector Machine (SVM) were used to compare such metabolic profiles.RESULTS:The metabolite differences in patients with preeclampsia: several tentative diagnostic biomarkers were found. From the support vector machines(SVM) method, ten unique m/z values were identified, the m/z values of markers selected from the +ESI scans were 123 Da,128Da,173 Da,191 Da,229Da,286Da,316Da,481 Da and 787 Da; marker selected from the -ESI scans was 187 Da. 10-fold cross-validation method was conducted by SVM to evaluate the prediction model, accuracy rate was 100%.CONCLUSION:The serous endogenous metabolites of preeclampsia have a high value in predicting preeclampsia.