Specific features of a metabolomic profile in preeclampsia

Objective. To search for markers for predicting preeclampsia on the basis of metabolomic analysis using mass spectrometry and bioinformatics. Subjects and methods. The investigation included two groups of pregnant women: a study group of 13 pregnant women with preeclampsia and a comparison group of 21 pregnant women with physiological pregnancy. Serum metabolite prof iles were obtained using liquid chromatography- mass spectrometry. Results. The investigators identified 22 amino acids with statistically significantly different concentrations: 3-methylhistidine, alanine, anserine, arginine, aspartate, carnosine, cystine, ethanolamine, glutamate, glutamine, glycine, histidine, homocitrulline, lysine, methionine, norvaline, O-phosphorylethanolamine, ornithine, phenylalanine, serine, threonine, and tyrosine. There was a moderate correlation with 3 amino acids: carnosine (KK = 0.526, p <0.001), arginine (KK = 0.437;p <0.001), ethanolamine (KK = 0.403;p = 0.003). In addition, there was a correlation of carnosine with hypertension (KK = 0.375; p = 0.038), proteinuria (KK = 0.543; p <0.001); arginine and ethanolamine also correlated with the level of high blood pressure (KK = 0.462; p = 0.009, and KK = 0.428; p = 0.002) and proteinuria (KK = 0.428; p = 0.002. and KK = 0.431, p = 0.002). Analysis of the ROC curves showed that carnosine, arginine, and ethanolamine were potentially sensitive and specific biomarkers for the diagnosis and prediction of preeclampsia (the area under the curve was 0.848, 0.789, and 0.767, respectively). Conclusion. The results of the investigation have shown that determination of the metabolic profile is of great clinical significance for predicting preeclampsia.

preeclampsia, metabolomics, prediction, biomarker