Metabolomics Signatures and Subsequent Maternal Health among Mothers with a Congenital Heart Defect-Affected Pregnancy

Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study

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.

Integrative metabolomics dictate distinctive signature profiles in patients with Tetralogy of Fallot

BACKGROUND

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease (CCHD) with multifactorial etiology. We aimed to investigate the metabolic profiles of CCHD and their independent contributions to TOF.

METHODS

A cohort comprising 42 individuals with TOF and atrial septal defect (ASD) was enrolled. Targeted ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was employed to systematically analyze metabolite levels and identify TOF-associated metabolic profiles.

RESULTS

Of 370 identified metabolites in tissue and 284 in plasma, over one-third of metabolites showed an association with microbiome. Differential metabolic pathways including amino acids biosynthesis, ABC (ATP-binding cassette) transporters, carbon metabolism, and fatty acid biosynthesis, shed light on TOF biological phenotypes. Additionally, ROC curves identified potential biomarkers, such as erythronic acid with an AUC of 0.868 in plasma, and 3-β-hydroxy-bisnor-5-cholenic acid, isocitric acid, glutaric acid, ortho-Hydroxyphenylacetic acid, picolinic acid with AUC close to 1 in tissue, whereas the discriminative performance of those substances significantly improved when combined with clinical phenotypes.

CONCLUSIONS

Distinct metabolic profiles exhibited robust discriminatory capabilities, effectively distinguishing TOF from ASD patients. These metabolites may serve as biomarkers or key molecular players in the intricate metabolic pathways involved in CCHD development.

IMPACT

Distinct metabolic profiles exhibited robust discriminatory capabilities, effectively distinguishing Tetralogy of Fallot from atrial septal defect patients. Similar profiling but inconsistent differential pathways between plasma and tissue. More than one-third metabolites in plasma and tissue are associated with the microbiome. The discovery of biomarkers is instrumental in facilitating early detection and diagnosis of Tetralogy of Fallot. Disturbed metabolism offers insights into interpretation of pathogenesis of Tetralogy of Fallot.

Plasma metabolic profiling of patients with tetralogy of fallot

BACKGROUND

Tetralogy of Fallot (TOF) is a common congenital heart disease with high mortality. However, the medical imageology and liquidbiopsy techniques present certain limitations. Thus, this study investigated the plasma metabolic profiles to distinguish key metabolites for early diagnosis of TOF.

METHODS

In total, 69 patients with TOF and 43 normal controls were enrolled for targeted metabolomics based on liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Absolute quantification of metabolites was performed using our standard database. The differentially expressed metabolites (DEMs) were screened by fold change (FC), VIP value and pearson correlation coefficient of OPLS-DA model. Receiver operating characteristic curve (ROC) was used to evaluate predictive ability of DEMs.

RESULTS

Different metabolic profiles were presented between TOF and Normal.The pathway analysis showed that significantly changed metabolites were enriched in nicotinamide and purine metabolism. Many intermediatesproductof purine and amido acid were higher in TOF than in Normal group, while energy substrates and electron carriers were lower in TOF than in Normal group. ROC analysis revealed a high diagnostic value of plasma FAD for differentiating TOF from Normal (AUC = 1).

CONCLUSION

Our study quantitatively characterized plasma metabolites in patients with TOF and may help to develop reliable biomarkers that contribute to the early TOF screening.

Maternal metabolomic profiling and congenital heart disease risk in offspring: A systematic review of observational studies

Aetiological understanding and screening methods for congenital heart disease (CHD) are limited. Maternal metabolomic assessment offers the potential to identify risk factors and biomarkers. We performed a systematic review (PROSPERO CRD42022308452) investigating the association between fetal/childhood CHD and endogenous maternal metabolites. Ovid-MEDLINE, Ovid-EMBASE and Cochrane Library were searched between inception and 06/09/2022. Case control studies included analysing maternal blood or urine metabolites in pregnancy or postpartum where there was foetal/childhood CHD. Risk of bias assessment utilised the Scottish Intercollegiate Guidelines Network methodology checklist and narrative synthesis was performed. A total of 134 records were screened with eight eligible studies (n = 3242 pregnancies, n = 842 CHD-affected offspring). Five studies performed metabolomic analysis in pregnancy. Metabolites distinguishing case and control groups spanned lipid, glucose and amino-acid pathways, with the development of sensitive risk prediction models. No single metabolite consistently distinguished cases and controls across studies. Three studies performed targeted analysis postnatally with altered lipid and amino acid metabolites and raised homocysteine and markers of oxidative stress identified in cases. Included studies reported small sample sizes, analysing different biosamples at variable time points using differing techniques. At present, there is not enough evidence to confidently associate maternal metabolomic profiles with offspring CHD risk. However, several identified pathways warrant further investigation.

Metabolomics: A New Tool in Our Understanding of Congenital Heart Disease

Although the genetic origins underpinning congenital heart disease (CHD) have been extensively studied, genes, by themselves, do not entirely predict phenotypes, which result from the complex interplay between genes and the environment. Consequently, genes merely suggest the potential occurrence of a specific phenotype, but they cannot predict what will happen in reality. This task can be revealed by metabolomics, the most promising of the "omics sciences". Though metabolomics applied to CHD is still in its infant phase, it has already been applied to CHD prenatal diagnosis, as well as to predict outcomes after cardiac surgery. Particular metabolomic fingerprints have been identified for some of the specific CHD subtypes. The hallmarks of CHD-related pulmonary arterial hypertension have also been discovered. This review, which is presented in a narrative format, due to the heterogeneity of the selected papers, aims to provide the readers with a synopsis of the literature on metabolomics in the CHD setting.

Lysophosphatidylcholine: Potential Target for the Treatment of Chronic Pain

The bioactive lipid lysophosphatidylcholine (LPC), a major phospholipid component of oxidized low-density lipoprotein (Ox-LDL), originates from the cleavage of phosphatidylcholine by phospholipase A2 (PLA2) and is catabolized to other substances by different enzymatic pathways. LPC exerts pleiotropic effects mediated by its receptors, G protein-coupled signaling receptors, Toll-like receptors, and ion channels to activate several second messengers. Lysophosphatidylcholine (LPC) is increasingly considered a key marker/factor positively in pathological states, especially inflammation and atherosclerosis development. Current studies have indicated that the injury of nervous tissues promotes oxidative stress and lipid peroxidation, as well as excessive accumulation of LPC, enhancing the membrane hyperexcitability to induce chronic pain, which may be recognized as one of the hallmarks of chronic pain. However, findings from lipidomic studies of LPC have been lacking in the context of chronic pain. In this review, we focus in some detail on LPC sources, biochemical pathways, and the signal-transduction system. Moreover, we outline the detection methods of LPC for accurate analysis of each individual LPC species and reveal the pathophysiological implication of LPC in chronic pain, which makes it an interesting target for biomarkers and the development of medicine regarding chronic pain.