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The Relationship of Maternal Gestational Mass Spectrometry-Derived Metabolites with Offspring Congenital Heart Disease: Results from Multivariable and Mendelian Randomization Analyses

Authors :
Kurt Taylor
Nancy McBride
Jian Zhao
Sam Oddie
Rafaq Azad
John Wright
Ole A. Andreassen
Isobel D. Stewart
Claudia Langenberg
Maria Christine Magnus
Maria Carolina Borges
Massimo Caputo
Deborah A. Lawlor
Source :
Journal of Cardiovascular Development and Disease, Vol 9, Iss 8, p 237 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Background: It is plausible that maternal pregnancy metabolism influences the risk of offspring congenital heart disease (CHD). We sought to explore this through a systematic approach using different methods and data. Methods: We undertook multivariable logistic regression of the odds of CHD for 923 mass spectrometry (MS)-derived metabolites in a sub-sample of a UK birth cohort (Born in Bradford (BiB); N = 2605, 46 CHD cases). We considered metabolites reaching a p-value threshold Results: In the main multivariable analyses, we identified 44 metabolites suggestively associated with CHD, including those from the following super pathways: amino acids, lipids, co-factors and vitamins, xenobiotics, nucleotides, energy, and several unknown molecules. Of these 44, isoleucine and leucine were available in the larger BiB cohort (NMR), and for these the results were validated. The MR analyses were possible for 27/44 metabolites and for 11 there was consistency with the multivariable regression results. Conclusions: In summary, we have used complimentary data sources and statistical techniques to construct layers of evidence. We found that pregnancy amino acid metabolism, androgenic steroid lipids, and levels of succinylcarnitine could be important contributing factors for CHD.

Details

Language :
English
ISSN :
23083425
Volume :
9
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Journal of Cardiovascular Development and Disease
Publication Type :
Academic Journal
Accession number :
edsdoj.76ebb7b78ce64d719408e293433deeac
Document Type :
article
Full Text :
https://doi.org/10.3390/jcdd9080237