AI Article Synopsis
- CVOTMs, a significant subtype of congenital heart disease, have an unclear origin linked to lipid metabolism during embryonic cardiovascular development, prompting further investigation into the relationship between lipid metabolites and these conditions.
- A case-control study using data from the China Teratology Birth Cohort analyzed maternal serum and identified 70 lipid metabolites significantly differing between CVOTM cases and normal fetuses, utilizing advanced statistical methods for robust biomarker selection.
- The research indicates that specific lipid metabolites are associated with pathways related to glycerolipid metabolism, insulin resistance, and atherosclerosis, potentially paving the way for new insights into the mechanisms and detection of congenital heart diseases.
Article Abstract
Background: The congenital ventricular outflow tract malformations (CVOTMs) is a major congenital heart diseases (CHDs) subtype, and its pathogenesis is complex and unclear. Lipid metabolic plays a crucial role in embryonic cardiovascular development. However, due to the limited types of detectable metabolites in previous studies, findings on lipid metabolic and CHDs are still inconsistent, and the possible mechanism of CHDs remains unclear.
Methods: The nest case-control study obtained subjects from the multicenter China Teratology Birth Cohort (CTBC), and maternal serum from the pregnant women enrolled during the first trimester was utilized. The subjects were divided into a discovery set and a validation set. The metabolomics of CVOTMs and normal fetuses were analyzed by targeted lipid metabolomics. Differential comparison, random forest and lasso regression were used to screen metabolic biomarkers.
Results: The lipid metabolites were distributed differentially between the cases and controls. Setting the selection criteria of P value < 0.05, and fold change (FC) > 1.2 or < 0.833, we screened 70 differential metabolites. Within the prediction model by random forest and lasso regression, DG (14:0_18:0), DG (20:0_18:0), Cer (d18:2/20:0), Cer (d18:1/20:0) and LPC (0:0/18:1) showed good prediction effects in discovery and validation sets. Differential metabolites were mainly concentrated in glycerolipid and glycerophospholipids metabolism, insulin resistance and lipid & atherosclerosis pathways, which may be related to the occurrence and development of CVOTMs.
Conclusion: Findings in this study provide a new metabolite data source for the research on CHDs. The differential metabolites and involved metabolic pathways may suggest new ideas for further mechanistic exploration of CHDs, and the selected biomarkers may provide some new clues for detection of COVTMs.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11334326 | PMC |
| http://dx.doi.org/10.1186/s12884-024-06738-y | DOI Listing |
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