Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer. (6th May 2019)

• Record Type: Journal Article
• Authors: Xie, Donghua; Luo, Yingchun; Xiong, Xiyue; Lou, Mingxing; Liu, Zhiyu; Wang, Aihua; Xiong, Lili; Kong, Fanjuan; Wang, Yichao; Wang, Hua
• Other Names: Bernardo David Academic Editor.
• Is Part Of: BioMed research international. Volume 2019(2019)
• Publication Date: 2019-05-06
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2019/1905416
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Background. There has been significant research on the genetic and environmental factors of congenital heart defects (CHDs), but few causes of teratogenicity, especially teratogenic mechanisms, can be clearly identified. Metabolomics has a potential advantage in researching the relationship between external factors and CHD. Objective. To find and identify the urinary potential biomarkers of pregnancy (including in the second and third trimesters) for fetuses with CHD based on modified gas chromatograph-mass spectrometer (GC-MS), which could reveal the possibility of high-risk factors for CHD and lay the foundation for early intervention, treatment, and prevention. Methods. Using a case-control design, we measured the urinary potential biomarkers of maternal urine metabolomics based on GC-MS in a population-based sample of women whose infants were diagnosed with CHD (70 case subjects) or were healthy (70 control subjects). SIMCA-P 13.0 software, principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), Wilcoxon-Mann-Whitney test, and logistics regression were used to find significant potential biomarkers. Result. The 3D score graph of the OPLS-DA showed that the CHD and control groups were fully separated. The fitting parameters were R 2 x=0.78 and R 2 y=0.69, and the forecast rate was Q 2 =0.61, indicating a high forecast ability. According to the ranking of VIPs from the OPLS-DA models, we found 34 potential metabolic markers with a VIP > 1, and after two pairwise rank sum tests, we found 20 significant potential biomarkers, which were further used in multifactor logistic regressions. Significant substances, including 4-hydroxybenzeneacetic acid ( OR =4.74, 95% CI: 1.06-21.06), 5-trimethylsilyloxy-n-valeric acid ( OR =15.78, 95% CI: 2.33-106.67), propanedioic acid ( OR =5.37, 95% CI: 1.87-15.45), hydracrylic acid ( OR =6.23, 95% CI: 1.07-36.21), and uric acid ( OR =5.23, 95% CI: 1.23-22.32), were associated with CHD. Conclusion. The major potential biomarkers in maternal urine associated with CHD were 4-hydroxybenzeneacetic acid, 5-trimethylsilyloxy-n-valeric acid, propanedioic acid, hydracrylic acid, and uric acid, respectively. These results indicated that the short chain fatty acids (SCFAs) and aromatic amino acid metabolism may be relevant with CHD.