Evidence map›Paper›PMID 39164614›Full record

ArticleBMC pregnancy and childbirth2024

Biomarkers for congenital ventricular outflow tract malformations based on maternal serum lipid metabolomics analysis.

Xuelian Yuan, Hong Kang, Yuqin Qin, Haibo Li, Lu Li, Yuting Li, Meixian Wang, Nana Li, Ying Deng, Xiaohong Li and 3 more

Abstract readMulticenter Study
In one paragraph

Article in BMC pregnancy and childbirth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Xuelian Yuan *National Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Hong Kang *National Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Yuqin QinDepartment of Obstetrics and Gynecology, Maternal and Child Healthcare Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Haibo LiDepartment of Obstetrics and Gynecology, Fujian provincial Maternal and Child Healthcare Hospital, Fuzhou, Fujian, China.
Lu LiKey Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China.
Yuting LiKey Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China.
Meixian WangNational Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Nana LiNational Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Ying DengNational Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiaohong LiNational Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Ping YuNational Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Yanping WangNational Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China. wyxyanping@163.com.
Zhen LiuNational Center for Birth Defects Monitoring of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China. Jenny_liu@scu.edu.cn.

Funding

Applied Basic Research Program of Sichuan Province 2021YJ0212National Key Research and Development Program of China 2016YFC1000102National Natural Science Foundation of China 82103858Popularization Application Project 21PJ057
6 · The paper itself

Abstract

backgroundThe 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.

methodsThe 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.

resultsThe 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.

conclusionFindings 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.

Indexed as

BiomarkersLipidsMetabolomicsVentricular Outflow ObstructionAdultCase-Control StudiesChinaFemaleHeart Defects, CongenitalHumansInfant, NewbornLipid MetabolismPregnancyPregnancy Trimester, FirstBiomarkersLipidsBiomarkerCongenital heart defectsLipid metabolomicsMachine learning

Identifiers

PMID39164614
PMCPMC11334326

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