Abstract
Introduction
Congenital heart disease (CHD) is the most common congenital anomaly, representing a significant global disease burden. Limitations exist in our understanding of aetiology, diagnostic methodology and screening, with metabolomics offering promise in addressing these.
Objective
To evaluate maternal metabolomics and lipidomics in prediction and risk factor identification for childhood CHD.
Methods
We performed an observational study in mothers of children with CHD following pregnancy, using untargeted plasma metabolomics and lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). 190 cases (157 mothers of children with structural CHD (sCHD); 33 mothers of children with genetic CHD (gCHD)) from the children OMACp cohort and 162 controls from the ALSPAC cohort were analysed. CHD diagnoses were stratified by severity and clinical classifications. Univariate, exploratory and supervised chemometric methods were used to identify metabolites and lipids distinguishing cases and controls, alongside predictive modelling.
Results
499 metabolites and lipids were annotated and used to build PLS-DA and SO-CovSel-LDA predictive models to accurately distinguish sCHD and control groups. The best performing model had an sCHD test set mean accuracy of 94.74% (sCHD test group sensitivity 93.33%; specificity 96.00%) utilising only 11 analytes. Similar test performances were seen for gCHD. Across best performing models, 37 analytes contributed to performance including amino acids, lipids, and nucleotides.
Conclusions
Here, maternal metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models classifying mothers of children with CHD. Metabolites and lipids identified offer promise for maternal risk factor profiling, and understanding of CHD pathogenesis in the future.
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1 Introduction
Congenital heart disease (CHD) is defined as a ‘structural developmental anomaly of the heart or great vessels (Jacobs et al., 2021).’ It is the most common congenital anomaly, with a reported prevalence of 0.63–0.8% of total births in the UK and Europe (European Commission, 2019; Public Health England, 2019). CHD is a heterogeneous group of conditions often described using anatomical, clinical and severity classification systems (EUROCAT, 2013; Jacobs et al., 2021). Critical or severe CHD are defined as requiring intervention in the first year of life, representing 20–25% of cases (Bakker et al., 2019; Chamsi-Pasha & Chamsi-Pasha, 2016). Globally, data suggests reduced postoperative mortality and increased survival for complex CHD, representing a significant global disease burden from birth into adulthood. (Bouma & Mulder, 2017; Lytzen et al., 2019; Zimmerman et al., 2020).
Our understanding of CHD aetiology remains limited, with over 60% remaining unexplained (Botto & Correa, 2003; Yasuhara & Garg, 2021). Chromosomal aneuploidy including Down syndrome account for 10–15%, with monogenic single gene disorders such as DiGeorge syndrome present in up to 25% (Fahed et al., 2013; Kerstjens-Frederikse, 2014; Yasuhara & Garg, 2021). Research in maternal metabolic diseases including diabetes, obesity, and cardiovascular disease have identified metabolic risk factors and potential causative pathways validated in animal models (Botto & Correa, 2003; Chen et al., 2018; Cheng et al., 2012; Hedermann et al., 2021; Helle & Priest, 2020; Suhre et al., 2010; Wang et al., 2011). Non-genetic factors implicated in aetiology include parental smoking, alcohol and drug exposures (Lee et al., 2021). However, evidence strength, mechanistic understanding and causal inference is limited. Maternal folate and folate-containing multivitamin use reduce CHD risk (Cheng et al., 2022; Feng et al., 2015; Goh & Koren, 2008). However, there is not enough evidence to confidently conclude that maternal micronutrient deficiency is associated with fetal CHD (Mires et al., 2022). A greater understanding of potential maternal risk factors and mechanisms could revolutionise primary prevention of CHD.
The human metabolome is a global representation of physiology, representing individual phenotype influenced by genetics and the environment (Hollywood et al., 2006; Monni et al., 2021; Nalbantoglu, 2019). Metabolomics aims to identify and quantify all endogenous and exogenous small molecules and metabolites in a biological system (Letertre et al., 2021; Nalbantoglu, 2019). The metabolome is potentially influenced by several factors including diet, fasting, gender and pregnancy (Handelman et al., 2019; Heinzmann et al., 2012; Kochhar et al., 2006; Krug et al., 2012; Lenz et al., 2004; Monni et al., 2021). However, the variation in studies including sample size, population, biosamples and analytical methods limit the generalisability of findings.
Metabolites measured in an individual represent their metabolic phenotype or metabotype. This reflects the interaction of their genetics and environmental factors (Yousri et al., 2014). Longitudinal studies in individuals have aimed to describe conservation of metabotype over time, with large scale analyses in blood and urine over periods of 3 months to 10 years suggesting conservation of over 70% of metabotype in the majority of participants (Assfalg et al., 2008; Bernini et al., 2009; Carayol et al., 2015; Ghini et al., 2015; Nicholson et al., 2011; Townsend et al., 2013; Yousri et al., 2014). This data suggests that whilst metabolic profiles are under the influence of multiple factors, a large component of individual metabotype is stable over time. Therefore, metabolomic profiles of mothers measured following pregnancy are likely to share significant similarities with those during the periconceptual period. This reproducibility is essential for applications in epidemiological studies of human disease.
In perinatal metabolomics, it is hypothesised that congenital anomalies such as CHD may alter fetal organ function and perfusion, with changes reflected in maternal blood (Monni et al., 2021). Therefore, maternal metabolomic profiling could facilitate biomarker screening in pregnancy, representing a potential fetal effect. Furthermore, metabolic changes could represent maternal aetiological factors for fetal CHD. Studies have assessed metabolomic profiles in mothers of children with CHD during and following the index pregnancy with the identification of several potential metabolites differentiating case and control groups, and development of risk prediction models (Bahado-Singh et al., 2014; Fang et al., 2023; Friedman et al., 2021; Hobbs et al., 2005a, b; Hsu et al., 2022; Taylor et al., 2022; Troisi et al., 2021; Wang et al., 2021; ** fetus with mice knocked out for the taurine transporter showing defects in multiple systems including markers of cardiomyopathy and heart failure (Ito et al., 2008). Excessive taurine in rats led to accelerated growth, obesity and insulin resistance (Hultman et al., 2007). Taurine has been shown to be increased in the blood of children with CHD compared to controls (Yu et al., 2018; Yuan et al., 2020). Maternal metabolomic assessment during pregnancy showed decreased taurine in mothers of children with CHD compared to controls, however, this was limited by a small sample size (n = 17 cases) (Fang et al., 2023). The human fetus and placenta lack the enzymes necessary for taurine synthesis, with taurine transport from maternal plasma to the umbilical circulation (Lambert et al., 2015). Therefore, changes in the maternal circulation are unlikely to be fetally derived.
4.1.2 Lipids, lipid-like molecules, and lipid messengers
Phosphatidylserine is a phospholipid involved in cell and mitochondrial membrane structure and function, derivation of phosphatidylethanolamine and formation and stability of lipoproteins for lipid transport and lipogenesis (van der Veen et al., 2017; Vance, 2018). Several studies have identified differences in maternal phospholipid profiles between mothers of children with CHD and controls during and following pregnancy, with similar findings in children and adults with CHD (Bahado-Singh et al., 2014; Guvenc et al., 2023; Hsu et al., 2022; Michel et al., 2020; Taylor et al., 2022).
Palmitoleoyl ethanolamide (PEA) is a fatty amide part of the N-acetylethanolamine (NAE) lipid messenger family, generated from phospholipid metabolism (Mock et al., 2023). Mothers of children with CHD had reduced PEA compared to controls in this study. NAEs have known anti-inflammatory effects. Administration of PEA in rat myocardial ischaemia reduces markers of inflammation and apoptosis in reperfusion, showing potential myocardial protective effects (Di Paola et al., 2016).
Oleamide is an endogenous lipid mediator discovered within the central nervous system in sleep deprivation (Hiley & Hoi, 2007). Epoxyoctadecenoic acid is a medium-chain fatty acid, produced as a perixodation product of linoleic acid from low density lipoprotein. It has been shown to accumulate in cardiovascular disease processes such as atherosclerosis (Jira & Spiteller, 1999). Administration in animal models may lead to heart failure and cardiovascular death (Fukushima et al., 1988). Methylmaleate is a methyl-fatty acid with immunomodulatory and antioxidant roles (Chen et al., 2022). There is little current evidence on the roles of these metabolites in the embryology or structure of the heart.
4.1.3 Nucleoside and nucleotide analogues
Hypoxanthine is a purine derivative, formed in the breakdown of adenosine triphosphate (ATP). Increased levels have been identified in tissue and plasma during hypoxic events including myocardial infarction (Farthing et al., 2015; Saugstad, 1988). Hypoxanthine can cross the placenta (Barros, 1994). Previous studies in and following pregnancy have suggested increased hypoxanthine in mothers of children without CHD (Fang et al., 2023; Wang et al., 2021). Hypoxanthine was increased in mothers of children with CHD within this study.
Uridine is a pyrimidine nucleotide for RNA, glycogen synthesis and lipid deposition (Zhang et al., 2020). Plasma metabolomic analysis of mothers of children with CHD following pregnancy has previously suggested increased uridine compared to controls (Wang et al., 2021). Lower uridine in cases was seen in this study. Pseudouridine, an isomer of uridine, a component and regulatory controller of RNA was also lower in cases (Charette & Gray, 2000).
4.1.4 Metabolomic and lipidomic profiles stratified by diagnosis
In previous studies considering maternal metabolic profiles in mothers of children with CHD, inclusion criteria are generally limited to isolated CHD without a known underlying genetic syndrome. In this study, the gCHD group allowed for assessment in a presumed genetic or chromosomal aetiology. Interestingly, model performance was similar in the sCHD and gCHD subgroups, suggesting potential commonalities between maternal risk profiles in the presence of genetic conditions. Further investigation with a larger sample size of specific genetic conditions would be beneficial.
We developed models to assess whether mothers of children with different classifications of CHD could be accurately classified on metabolomic and lipidomic markers. Models performed less accurately for the EUROCAT classification, potentially related to its lack of biological basis. Model performance was better for clinical classifications based on cyanosis; however, sensitivity and specificity were not optimal. Further investigation is warranted as greater understanding could aid in understanding maternal risk or prognostic markers, as well as potentially improving clinical classification systems of CHD.
4.2 Strengths and limitations
This study performs comprehensive untargeted and lipidomic analysis in a well characterized cohort of CHD patients. Here, we utilise maternal sampling following pregnancy to infer risk factor profiles for fetal CHD. Whilst studies suggest a large component of an individual’s metabotype is stable over time, samples taken may not be reflective of the periconceptual state (Assfalg et al., 2008; Bernini et al., 2009; Carayol et al., 2015; Ghini et al., 2015; Nicholson et al., 2011; Townsend et al., 2013; Yousri et al., 2014). However, prospective pre-conception sampling is infeasible in this setting. Several metabolites potentially implicated as maternal risk factors have been identified, but the observational nature of the study limits the ability to currently establish causative links.
Samples were taken following pregnancy. Participants known to be pregnant were excluded, however, pregnancy status was not routinely recorded for cOMACp participants and some ALSPAC data was missing. Efforts were made to identify potential differences between case and control groups; however, there remains the potential for unmeasured confounders. It was not possible to accurately compare further maternal characteristics between cohorts. Reassuringly, we did not observe any separation or subclassifications in classes within unsupervised and supervised models; suggesting potential known and unknown confounders are unlikely to have had a substantial effect. Future work will further explore the interactions of maternal characteristics with important metabolites identified as well as considering potential additional unexplored confounders.
5 Conclusions
Here, untargeted plasma metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models identifying mothers of children with CHD. Implicated metabolites and lipids offer promise for maternal risk factor profiling, and greater understanding of biological mechanisms of CHD pathogenesis. Validation of findings in greater sample sizes, with development of targeted platforms will aid greater understanding going forward.
Data availability
Data is provided within the manuscript or supplementary information files.
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Acknowledgements
The authors would like to thank the families who took part in cOMACp, the research nurses and laboratory staff who are invaluable in the running and management of the cOMACp cohort. We are extremely grateful to all the families who took part in ALSPAC, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computers and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses.
Funding
Children OMACp is funded by NIHR Bristol Biomedical Research Centre (BRC) and the British Heart Foundation (BHF; CH/17/32804). The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. Additional grants have supported ALSPAC data and sample collection utilised in this study (Wellcome Trust (WT092830/Z/10/Z; WT092830/Z/10/Z), Wellcome Trust and MRC (102215/2/13/2O); MRC (MR/M009351/1); John Templeton Foundation (61356; 61917); BHF (SP/07/008/24066); Lifelong Health and Wellbeing via MRC (G1001357). This project received funding from the Bristol and Weston Hospitals Charity/UHBW NIHR Research Capability Funding (2022-23-03). CDH-UK supported clinical research fellow time on this project. This work was supported by Ministero dell’Università e della Ricerca (MUR) project PIR01_00032 BIO OPEN LAB BOL “CUP” J37E19000050007, project CIR01_00032 – BOL “BIO Open Lab – Rafforzamento del capitale umano” granted to P.Campiglia. The publication is the work of the authors, who will serve as guarantors for the contents of this work.
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SM conceptualised the project and instigated study design and planning. SM, ESo, VC, PC, KAE, CS and MC contributed to study and experimental design. ESo, FMe, ESa and MGB performed metabolomics and lipidomics analyses. SM, ESo, VC, FMe, FMa and TD performed statistical and chemometric analyses and interpreted the results. MB provided support with children OMACp cohort. SM wrote the first version of the paper. All authors revised the paper and approved the submission.
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Mires, S., Sommella, E., Merciai, F. et al. Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study. Metabolomics 20, 70 (2024). https://doi.org/10.1007/s11306-024-02129-8
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DOI: https://doi.org/10.1007/s11306-024-02129-8