RESUMO
Objective:To investigate the changes and to establish a reference interval of bile acid profile of healthy pregnant women in the second and third trimesters of pregnancy in our hospital.Methods:A total of 298 healthy singleton pregnant women who underwent prenatal examination in the Department of Obstetrics of Zhejiang Provincial People′s Hospital from July 2019 to August 2020 were enrolled in this study. The overnight fasting serum samples were collected from all subjects during their second and third trimesters of pregnancy. The concentrations of 15 bile acids(cholic acid, chenodeoxycholic acid, deoxycholic acid, ursodeoxycholic acid, lithocholic acid and their glycine-and taurine-conjugated types)were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS). The characteristics of changes were analyzed and the reference intervals were determined for the second and third trimesters. The concentrations of 15 bile acids and total bile acids were skewed-distributed, and 99 percentiles (P 99) were used to represent the unilateral upper limit of the reference interval. Results:There was significant difference in the serum levels of glycine cholic acid (GCA), taurocholic acid (TCA), glycine ursodeoxycholic acid (GUDCA) and lithocholic acid (LCA) between the second and third trimesters healthy pregnant females ( P<0.05). For other 11 bile acids, there was no significant difference. The levels of total bile acids, primary or secondary bile acids, free or conjugated bile acids (glycine-bound and taurine-bound bile acids) were stable with gestation. Conclusion:Primary, secondary or free, and conjugated bile acids in healthy pregnant women remained stable at T 2 and T 3, with significant differences in only a few subtypes of bile acids. While the correlation between glycine-bound and taurine-bound bile acids showed a weakening trend at T 3 ( P<0.05). It is necessary to establish reference intervals of bile acids for healthy pregnant women in this area. This study provided data support for future research on related diseases during pregnancy.
RESUMO
Severe COVID-19 patients account for most of the mortality of this disease. Early detection and effective treatment of severe patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model correctly classified severe patients with an accuracy of 93.5%, and was further validated using ten independent patients, seven of which were correctly classified. We identified molecular changes in the sera of COVID-19 patients implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study shows that it is possible to predict progression to severe COVID-19 disease using serum protein and metabolite biomarkers. Our data also uncovered molecular pathophysiology of COVID-19 with potential for developing anti-viral therapies.
