Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis
Abstract Introduction Congenital heart disease (CHD) is one of the most prevalent birth defects in the world. The pathogenesis of CHD is complex and unclear. With the development of metabolomics technology, variations in metabolites may provide new clues about the causes of CHD and may serve as a bi...
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| Format: | Article |
| Language: | English |
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BMC
2022-11-01
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| Series: | BMC Cardiovascular Disorders |
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| Online Access: | https://doi.org/10.1186/s12872-022-02912-2 |
| _version_ | 1811211881670508544 |
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| author | Xuelian Yuan Lu Li Hong Kang Meixian Wang Jing Zeng Yanfang Lei Nana Li Ping Yu Xiaohong Li Zhen Liu |
| author_facet | Xuelian Yuan Lu Li Hong Kang Meixian Wang Jing Zeng Yanfang Lei Nana Li Ping Yu Xiaohong Li Zhen Liu |
| author_sort | Xuelian Yuan |
| collection | DOAJ |
| description | Abstract Introduction Congenital heart disease (CHD) is one of the most prevalent birth defects in the world. The pathogenesis of CHD is complex and unclear. With the development of metabolomics technology, variations in metabolites may provide new clues about the causes of CHD and may serve as a biomarker during pregnancy. Methods Sixty-five amniotic fluid samples (28 cases and 37 controls) during the second and third trimesters were utilized in this study. The metabolomics of CHD and normal fetuses were analyzed by untargeted metabolomics technology. Differential comparison and randomForest were used to screen metabolic biomarkers. Results A total of 2472 metabolites were detected, and they were distributed differentially between the cases and controls. Setting the selection criteria of fold change (FC) ≥ 2, P value < 0.01 and variable importance for the projection (VIP) ≥ 1.5, we screened 118 differential metabolites. Within the prediction model by random forest, PE(MonoMe(11,5)/MonoMe(13,5)), N-feruloylserotonin and 2,6-di-tert-butylbenzoquinone showed good prediction effects. Differential metabolites were mainly concentrated in aldosterone synthesis and secretion, drug metabolism, nicotinate and nicotinamide metabolism pathways, which may be related to the occurrence and development of CHD. Conclusion This study provides a new database of CHD metabolic biomarkers and mechanistic research. These results need to be further verified in larger samples. |
| first_indexed | 2024-04-12T05:20:54Z |
| format | Article |
| id | doaj.art-07ba2dba2c294df1a9a65cebd69b3f67 |
| institution | Directory Open Access Journal |
| issn | 1471-2261 |
| language | English |
| last_indexed | 2024-04-12T05:20:54Z |
| publishDate | 2022-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cardiovascular Disorders |
| spelling | doaj.art-07ba2dba2c294df1a9a65cebd69b3f672022-12-22T03:46:28ZengBMCBMC Cardiovascular Disorders1471-22612022-11-0122111110.1186/s12872-022-02912-2Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysisXuelian Yuan0Lu Li1Hong Kang2Meixian Wang3Jing Zeng4Yanfang Lei5Nana Li6Ping Yu7Xiaohong Li8Zhen Liu9National Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityNational Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityNational Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityNational Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityDepartment of Obstetrics & Gynecology, Longchang Maternal and Child Healthcare HospitalDepartment of Obstetrics, Zhaotong Second People’s HospitalNational Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityNational Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityNational Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityNational Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan UniversityAbstract Introduction Congenital heart disease (CHD) is one of the most prevalent birth defects in the world. The pathogenesis of CHD is complex and unclear. With the development of metabolomics technology, variations in metabolites may provide new clues about the causes of CHD and may serve as a biomarker during pregnancy. Methods Sixty-five amniotic fluid samples (28 cases and 37 controls) during the second and third trimesters were utilized in this study. The metabolomics of CHD and normal fetuses were analyzed by untargeted metabolomics technology. Differential comparison and randomForest were used to screen metabolic biomarkers. Results A total of 2472 metabolites were detected, and they were distributed differentially between the cases and controls. Setting the selection criteria of fold change (FC) ≥ 2, P value < 0.01 and variable importance for the projection (VIP) ≥ 1.5, we screened 118 differential metabolites. Within the prediction model by random forest, PE(MonoMe(11,5)/MonoMe(13,5)), N-feruloylserotonin and 2,6-di-tert-butylbenzoquinone showed good prediction effects. Differential metabolites were mainly concentrated in aldosterone synthesis and secretion, drug metabolism, nicotinate and nicotinamide metabolism pathways, which may be related to the occurrence and development of CHD. Conclusion This study provides a new database of CHD metabolic biomarkers and mechanistic research. These results need to be further verified in larger samples.https://doi.org/10.1186/s12872-022-02912-2Congenital heart diseaseMetabolomicsReproductionBiomarkerDiagnosis |
| spellingShingle | Xuelian Yuan Lu Li Hong Kang Meixian Wang Jing Zeng Yanfang Lei Nana Li Ping Yu Xiaohong Li Zhen Liu Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis BMC Cardiovascular Disorders Congenital heart disease Metabolomics Reproduction Biomarker Diagnosis |
| title | Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis |
| title_full | Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis |
| title_fullStr | Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis |
| title_full_unstemmed | Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis |
| title_short | Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis |
| title_sort | biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis |
| topic | Congenital heart disease Metabolomics Reproduction Biomarker Diagnosis |
| url | https://doi.org/10.1186/s12872-022-02912-2 |
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