ArticleJournal of cardiovascular development and disease2022
The Relationship of Maternal Gestational Mass Spectrometry-Derived Metabolites with Offspring Congenital Heart Disease: Results from Multivariable and Mendelian Randomization Analyses.
Article in Journal of cardiovascular development and disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 8 citations in OpenAlex.
- Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review.European journal of epidemiology · 2024Pooled it
- Maternal metabolomic profiling and congenital heart disease risk in offspring: A systematic review of observational studies.Prenatal diagnosis · 2023Pooled it
- Article
- Prenatal Metabolomics Analysis and Fetal Congenital Anomalies and Genetic Conditions: A Review of Current Literature.Prenatal diagnosis · 2025Review
- Causal associations between blood metabolites and breast cancer.Archives of medical science : AMS · 2025Article
- The causal relationship between CSF metabolites and GBM: a two-sample mendelian randomization analysis.BMC cancer · 2024Article
- Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study.Metabolomics : Official journal of the Metabolomic Society · 2024Observational
Corrections and comments
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Authors and funding
13 authors at 8 institutions in 4 countries.
Funding
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 <0.05 to be suggestively associated with CHD. We sought validation of our findings, by repeating the multivariable regression analysis within the BiB cohort for any suggestively associated metabolite that was measured by nuclear magnetic resonance (NMR) or clinical chemistry (N = 7296, 87 CHD cases), and by using genetic risk scores (GRS: weighted genetic risk scores of single nucleotide polymorphisms (SNPs) that were associated with any suggestive metabolite) in Mendelian randomization (MR) analyses. The MR analyses were performed in BiB and two additional European birth cohorts (N = 38,662, 319 CHD cases). 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.
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