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Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer
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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526572/ https://www.ncbi.nlm.nih.gov/pubmed/31198782 http://dx.doi.org/10.1155/2019/1905416 |
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author | Xie, Donghua Luo, Yingchun Xiong, Xiyue Lou, Mingxing Liu, Zhiyu Wang, Aihua Xiong, Lili Kong, Fanjuan Wang, Yichao Wang, Hua |
author_facet | Xie, Donghua Luo, Yingchun Xiong, Xiyue Lou, Mingxing Liu, Zhiyu Wang, Aihua Xiong, Lili Kong, Fanjuan Wang, Yichao Wang, Hua |
author_sort | Xie, Donghua |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6526572 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-65265722019-06-13 Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer Xie, Donghua Luo, Yingchun Xiong, Xiyue Lou, Mingxing Liu, Zhiyu Wang, Aihua Xiong, Lili Kong, Fanjuan Wang, Yichao Wang, Hua Biomed Res Int Research Article 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. Hindawi 2019-05-06 /pmc/articles/PMC6526572/ /pubmed/31198782 http://dx.doi.org/10.1155/2019/1905416 Text en Copyright © 2019 Donghua Xie et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xie, Donghua Luo, Yingchun Xiong, Xiyue Lou, Mingxing Liu, Zhiyu Wang, Aihua Xiong, Lili Kong, Fanjuan Wang, Yichao Wang, Hua Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer |
title | Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer |
title_full | Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer |
title_fullStr | Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer |
title_full_unstemmed | Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer |
title_short | Study on the Potential Biomarkers of Maternal Urine Metabolomics for Fetus with Congenital Heart Diseases Based on Modified Gas Chromatograph-Mass Spectrometer |
title_sort | study on the potential biomarkers of maternal urine metabolomics for fetus with congenital heart diseases based on modified gas chromatograph-mass spectrometer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526572/ https://www.ncbi.nlm.nih.gov/pubmed/31198782 http://dx.doi.org/10.1155/2019/1905416 |
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