FLT4 causes developmental disorders of the cardiovascular and lymphovascular systems via pleiotropic molecular mechanisms.

AIMS: Rare, deleterious genetic variants in FLT4 are associated with Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease (CHD). Distinct genetic variants in FLT4 are also an established cause of Milroy disease, the most prevalent form of primary hereditary lymphoedema. Phenotypic features of these two conditions are non-overlapping, implying pleiotropic cellular mechanisms during development. METHODS AND RESULTS: Here, we show that FLT4 variants identified in TOF patients, when expressed in primary human endothelial cells, cause aggregation of FLT4 protein in the perinuclear endoplasmic reticulum, activating proteostatic and metabolic signalling, whereas lymphoedema-associated FLT4 variants and wildtype FLT4 do not. FLT4 TOF variants display characteristic gene expression profiles in key developmental signalling pathways, revealing a role for FLT4 in cardiogenesis distinct from its role in lymphatic development. Inhibition of proteostatic signalling abrogates these effects, identifying potential avenues for therapeutic intervention. Depletion of flt4 in zebrafish caused cardiac phenotypes of reduced heart size and altered heart looping. These phenotypes were rescued with coinjection of wildtype human FLT4 mRNA, but incompletely or not at all by mRNA harbouring FLT4 TOF variants. CONCLUSIONS: Taken together, we identify a pathogenic mechanism for FLT4 variants predisposing to TOF that is distinct from the known dominant negative mechanism of Milroy-causative variants. FLT4 variants give rise to conditions of the two circulatory subdivisions of the vascular system via distinct developmental pleiotropic molecular mechanisms. TRANSLATIONAL PERSPECTIVE: Proteostatic dysfunction, if confirmed as a mechanism of CHD pathogenesis for other predisposing genes, may identify pathways to therapeutic interventions. Distinguishing mechanistically how variants in FLT4 give rise to CHD may have potential to individualise genetic counselling in affected families.

Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets.

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology.

Recent genome-wide association studies have successfully identified associations between genetic variants and simple cardiac morphological parameters derived from cardiac magnetic resonance images. However, the emergence of large databases, including genetic data linked to cardiac magnetic resonance facilitates the investigation of more nuanced patterns of cardiac shape variability than those studied so far. Here we propose a framework for gene discovery coined unsupervised phenotype ensembles. The unsupervised phenotype ensemble builds a redundant yet highly expressive representation by pooling a set of phenotypes learnt in an unsupervised manner, using deep learning models trained with different hyperparameters. These phenotypes are then analysed via genome-wide association studies, retaining only highly confident and stable associations across the ensemble. We applied our approach to the UK Biobank database to extract geometric features of the left ventricle from image-derived three-dimensional meshes. We demonstrate that our approach greatly improves the discoverability of genes that influence left ventricle shape, identifying 49 loci with study-wide significance and 25 with suggestive significance. We argue that our approach would enable more extensive discovery of gene associations with image-derived phenotypes for other organs or image modalities.

Clinical risk associated with COVID-19 among 86000 patients with congenital heart disease.

OBJECTIVE: To determine the magnitude of any excess risk of mortality and hospitalisation due to COVID-19 infection in patients with congenital heart disease (CHD) in the UK healthcare system. METHODS: Matched case-control study within the Clinical Practice Research Datalink study of anonymised general practice records in the National Health Service in England. Patients with CHD were stratified for disease severity according to the European Society of Cardiology guidelines. Presence of a positive COVID-19 test, hospitalisation with a diagnosis of COVID-19 and COVID-19-related mortality were compared in case and control groups. RESULTS: 86 441 patients with CHD and 335 839 controls were studied. Of patients with a positive COVID-19 test, patients with CHD were more likely than controls to be hospitalised (22.4% vs 14.5%; OR=1.77 (95% CI 1.60 to 1.96); p=2.11e-28) and suffer COVID-19-related death (6.1% vs 3.8%; OR=1.60 (95% CI 1.35 to 1.89); p=7.00e-08). The excess risk of COVID-19 hospitalisation and death rose with increasing physiological severity of CHD (presence of pulmonary vascular disease and/or cyanosis), rather than anatomical complexity. CONCLUSIONS: In this study of the COVID-19 pandemic experience, using population health records in over 86000 patients with CHD in England, patients with CHD with COVID-19 were at around 50-75% higher risk of hospitalisation and mortality compared with matched controls with COVID-19. We provide the first primary care-derived estimates for COVID-19 hospitalisation and case-fatality rates in patients with CHD. Some factors predictive of worse COVID-19 outcome in general populations (such as non-white ethnic group), and other CHD-specific comorbidities (such as pulmonary hypertension), influenced outcomes among patients with CHD.

Predicting congenital renal tract malformation genes using machine learning.

Congenital renal tract malformations (RTMs) are the major cause of severe kidney failure in children. Studies to date have identified defined genetic causes for only a minority of human RTMs. While some RTMs may be caused by poorly defined environmental perturbations affecting organogenesis, it is likely that numerous causative genetic variants have yet to be identified. Unfortunately, the speed of discovering further genetic causes for RTMs is limited by challenges in prioritising candidate genes harbouring sequence variants. Here, we exploited the computer-based artificial intelligence methodology of supervised machine learning to identify genes with a high probability of being involved in renal development. These genes, when mutated, are promising candidates for causing RTMs. With this methodology, the machine learning classifier determines which attributes are common to renal development genes and identifies genes possessing these attributes. Here we report the validation of an RTM gene classifier and provide predictions of the RTM association status for all protein-coding genes in the mouse genome. Overall, our predictions, whilst not definitive, can inform the prioritisation of genes when evaluating patient sequence data for genetic diagnosis. This knowledge of renal developmental genes will accelerate the processes of reaching a genetic diagnosis for patients born with RTMs.

Activation of telomerase by TA-65 enhances immunity and reduces inflammation post myocardial infarction.

Myocardial infarction (MI) accelerates immune ageing characterised by lymphopenia, expansion of terminally differentiated CD8+ T-lymphocytes (CD8+ TEMRA) and inflammation. Pre-clinical data showed that TA-65, an oral telomerase activator, reduced immune ageing and inflammation after MI. We conducted a double blinded randomised controlled pilot trial evaluating the use of TA-65 to reduce immune cell ageing in patients following MI. Ninety MI patients aged over 65 years were randomised to either TA-65 (16 mg daily) or placebo for 12 months. Peripheral blood leucocytes were analysed by flow cytometry. The pre-defined primary endpoint was the proportion of CD8+ T-lymphocytes which were CD8+ TEMRA after 12 months. Secondary outcomes included high-sensitivity C-reactive protein (hsCRP) levels. Median age of participants was 71 years. Proportions of CD8+ TEMRA did not differ after 12 months between treatment groups. There was a significant increase in mean total lymphocyte count in the TA-65 group after 12 months (estimated treatment effect: + 285 cells/µl (95% CI: 117-452 cells/ µ l, p < 0.004), driven by significant increases from baseline in CD3+, CD4+, and CD8+ T-lymphocytes, B-lymphocytes and natural killer cells. No increase in lymphocyte populations was seen in the placebo group. At 12 months, hsCRP was 62% lower in the TA-65 group compared to placebo (1.1 vs. 2.9 mg/L). Patients in the TA-65 arm experienced significantly fewer adverse events (130 vs. 185, p = 0.002). TA-65 did not alter CD8+ TEMRA but increased all major lymphocyte subsets and reduced hsCRP in elderly patients with MI after 12 months.

Rationale, Design, and the Baseline Characteristics of the RHDGen (The Genetics of Rheumatic Heart Disease) Network Study†.

BACKGROUND: The genetics of rheumatic heart disease (RHDGen) Network was developed to assist the discovery and validation of genetic variations and biomarkers of risk for rheumatic heart disease (RHD) in continental Africans, as a part of the global fight to control and eradicate rheumatic fever/RHD. Thus, we describe the rationale and design of the RHDGen study, comprising participants from 8 African countries. METHODS: RHDGen screened potential participants using echocardiography, thereafter enrolling RHD cases and ethnically-matched controls for whom case characteristics were documented. Biological samples were collected for conducting genetic analyses, including a discovery case-control genome-wide association study (GWAS) and a replication trio family study. Additional biological samples were also collected, and processed, for the measurement of biomarker analytes and the biomarker analyses are underway. RESULTS: Participants were enrolled into RHDGen between December 2012 and March 2018. For GWAS, 2548 RHD cases and 2261 controls (3301 women [69%]; mean age [SD], 37 [16.3] years) were available. RHD cases were predominantly Black (66%), Admixed (24%), and other ethnicities (10%). Among RHD cases, 34% were asymptomatic, 26% had prior valve surgery, and 23% had atrial fibrillation. The trio family replication arm included 116 RHD trio probands and 232 parents. CONCLUSIONS: RHDGen presents a rare opportunity to identify relevant patterns of genetic factors and biomarkers in Africans that may be associated with differential RHD risk. Furthermore, the RHDGen Network provides a platform for further work on fully elucidating the causes and mechanisms associated with RHD susceptibility and development.

Data on cardiac lncRNA STX18-AS1 expression in developing human hearts and function during in vitro hESC-cardiomyocyte differentiation.

This article presents data concerning STX18-AS1, a long noncoding RNA gene identified from a Genome-wide association study of Atrial Septal Defect (ASD). The data describes its expression patterns in human tissues and functions in regulating cardiomyocyte differentiation in vitro. STX18-AS1 is a lncRNA with a higher abundance in developing tissues, including hearts. Its transcription distribution within the embryonic hearts during key heart septation stages supports STX18-AS1's association with risk SNPs for ASD. The CRISPR stem cell pool in which STX18-AS1 was knocked down, showed reduced CM differentiation efficiency and lower expression of key cardiac transcriptional factors. This indicated its regulative role in supporting the lineage specification from cardiac mesoderm into cardiac progenitors and cardiomyocytes. These data can benefit the understanding of human embryonic heart developmental biology, and the time-course changes of cardiac transcriptional factors during in vitro cardiomyocyte differentiation from human embryonic stem cells.

Significantly increased risk of chronic obstructive pulmonary disease amongst adults with predominantly mild congenital heart disease.

Adults with congenital heart disease (CHD) face increased risk of various comorbid diseases. Previous work on lung dysfunction in this population has mainly focused on restrictive lung disease, in patients with severe CHD phenotypes. We examined the association of mild CHD with chronic obstructive pulmonary disease (COPD) in the UK Biobank (UKB). Electronic health records (EHR) were used to identify 3385 CHD cases and 479,765 healthy controls in UKB, before performing a case-control analysis over a 20-year study period for a total of > 9.5 M person-years of follow-up. Our analysis showed that UKB participants with CHD are at substantially greater risk of developing COPD than healthy controls (8.7% vs 3.1% prevalence, unadjusted OR 2.98, 95% CI 2.63, 3.36, P = 1.40e-53). Slightly increased rates of smoking were observed amongst CHD cases, however the association with COPD was shown to be robust to adjustment for smoking and other factors known to modulate COPD risk within a multivariable-adjusted Cox regression framework (fully adjusted HR 2.21, 95% CI 1.97, 2.48, P = 5.5e-41). Care for adults with CHD should aim to mitigate their increased risk of COPD, possibly via increased smoking cessation support.

Investigation of Copy Number Variation in South African Patients With Congenital Heart Defects.

BACKGROUND: Congenital heart disease (CHD) is a leading non-infectious cause of pediatric morbidity and mortality worldwide. Although the etiology of CHD is poorly understood, genetic factors including copy number variants (CNVs) contribute to the risk of CHD in individuals of European ancestry. The presence of rare CNVs in African CHD populations is unknown. This study aimed to identify pathogenic and likely pathogenic CNVs in South African patients with CHD. METHODS: Genotyping was performed on 90 patients with nonsyndromic CHD using the Affymetrix CytoScan HD platform. These data were used to identify large, rare CNVs in known CHD-associated genes and candidate genes. RESULTS: We identified eight CNVs overlapping known CHD-associated genes (GATA4, CRKL, TBX1, FLT4, B3GAT3, NSD1) in six patients. The analysis also revealed CNVs encompassing five candidate genes likely to play a role in the development of CHD (DGCR8, KDM2A, JARID2, FSTL1, CYFIP1) in five patients. One patient was found to have 47, XXY karyotype. We report a total discovery yield of 6.7%, with 5.6% of the cohort carrying pathogenic or likely pathogenic CNVs expected to cause the observed phenotypes. CONCLUSIONS: In this study, we show that chromosomal microarray is an effective technique for identifying CNVs in African patients diagnosed with CHD and have demonstrated results similar to previous CHD genetic studies in Europeans. Novel potential CHD genes were also identified, indicating the value of genetic studies of CHD in ancestrally diverse populations.

A review of causal discovery methods for molecular network analysis.

BACKGROUND: With the increasing availability and size of multi-omics datasets, investigating the casual relationships between molecular phenotypes has become an important aspect of exploring underlying biology andgenetics. There are an increasing number of methodlogies that have been developed and applied to moleular networks to investigate these causal interactions. METHODS: We have introduced and reviewed the available methods for building large-scale causal molecular networks that have been developed and applied in the past decade. RESULTS: In this review we have identified and summarized the existing methods for infering causality in large-scale causal molecular networks, and discussed important factors that will need to be considered in future research in this area. CONCLUSION: Existing methods to infering causal molecular networks have their own strengths and limitations so there is no one best approach, and it is instead down to the discretion of the researcher. This review also to discusses some of the current limitations to biological interpretation of these networks, and important factors to consider for future studies on molecular networks.

Joint analysis of functionally related genes yields further candidates associated with Tetralogy of Fallot.

Although several genes involved in the development of Tetralogy of Fallot have been identified, no genetic diagnosis is available for the majority of patients. Low statistical power may have prevented the identification of further causative genes in gene-by-gene survey analyses. Thus, bigger samples and/or novel analytic approaches may be necessary. We studied if a joint analysis of groups of functionally related genes might be a useful alternative approach. Our reanalysis of whole-exome sequencing data identified 12 groups of genes that exceedingly contribute to the burden of Tetralogy of Fallot. Further analysis of those groups showed that genes with high-impact variants tend to interact with each other. Thus, our results strongly suggest that additional candidate genes may be found by studying the protein interaction network of known causative genes. Moreover, our results show that the joint analysis of functionally related genes can be a useful complementary approach to classical single-gene analyses.

Genetic analyses of circulating PUFA-derived mediators identifies heritable dihydroxyeicosatrienoic acid species.

Estimates of heritability are the first step in identifying a trait with substantial variation due to genetic factors. Large-scale genetic analyses can identify the DNA variants that influence the levels of circulating lipid species and the statistical technique Mendelian randomisation can use these DNA variants to address potential causality of these lipids in disease. We estimated the heritability of plasma eicosanoids, octadecanoids and docosanoids to identify those lipid species with substantial heritability. We analysed plasma lipid mediators in 31 White British families (196 participants) ascertained for high blood pressure and deeply clinically and biochemically phenotyped over a 25-year period. We found that the dihydroxyeicosatrienoic acid (DHET) species, 11,12-DHET and 14,15-DHET, products of arachidonic acid metabolism by cytochrome P450 (CYP) monooxygenase and soluble epoxide hydrolase (sEH), exhibited substantial heritability (h2 = 33%-37%; Padj<0.05). Identification of these two heritable bioactive lipid species allows for future large-scale, targeted, lipidomics-genomics analyses to address causality in cardiovascular and other diseases.

Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.

BACKGROUND: Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics. METHODS: We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case-control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses. RESULTS: Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls. CONCLUSIONS: These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity.

Genetic resiliency associated with dominant lethal TPM1 mutation causing atrial septal defect with high heritability.

Analysis of large-scale human genomic data has yielded unexplained mutations known to cause severe disease in healthy individuals. Here, we report the unexpected recovery of a rare dominant lethal mutation in TPM1, a sarcomeric actin-binding protein, in eight individuals with large atrial septal defect (ASD) in a five-generation pedigree. Mice with Tpm1 mutation exhibit early embryonic lethality with disrupted myofibril assembly and no heartbeat. However, patient-induced pluripotent-stem-cell-derived cardiomyocytes show normal beating with mild myofilament defect, indicating disease suppression. A variant in TLN2, another myofilament actin-binding protein, is identified as a candidate suppressor. Mouse CRISPR knock-in (KI) of both the TLN2 and TPM1 variants rescues heart beating, with near-term fetuses exhibiting large ASD. Thus, the role of TPM1 in ASD pathogenesis unfolds with suppression of its embryonic lethality by protective TLN2 variant. These findings provide evidence that genetic resiliency can arise with genetic suppression of a deleterious mutation.

Modern genomic techniques in the identification of genetic causes of cardiomyopathy.

Over the past three decades numerous disease-causing genes have been linked to the pathogenesis of heritable cardiomyopathies, but many causal genes are yet to be identified. Next-generation sequencing (NGS) platforms have revolutionised clinical testing capacity in familial cardiomyopathy. In this review, we summarise how NGS technologies have advanced our understanding of genetic non-syndromic cardiomyopathy over the last decade. First, 26 putative new disease-causing genes have been identified to date, mostly from whole-exome sequencing, and some of which (FLNC, MTO1, HCN4) have had a considerable clinical impact and are now included in routine diagnostic gene panels. Second, we consider challenges in variant interpretation and the importance of large-scale NGS population control cohorts for this purpose. Third, an emerging role of common variation in some forms of genetic cardiomyopathy is being elucidated through recent studies which have illustrated an additive effect of numerous polymorphic loci on cardiac parameters; this may explain phenotypic variability and low rates of genetic diagnosis from sequencing studies. Finally, we discuss the clinical utility of genetic testing in cardiomyopathy in Western settings, where NGS panel testing of core disease genes is currently recommended with possible implications for patient management. Given the findings of recent studies, whole-exome or whole-genome sequencing should be considered in patients of non-European ancestry with clearly familial disease, or severe paediatric disease, when no result is obtained on panel sequencing. The clinical utility of polygenic risk assessment needs to be investigated further in patients with unexplained dilated cardiomyopathy and hypertrophic cardiomyopathy in whom a pathogenic variant is not identified.

Rare GATA6 variants associated with risk of congenital heart disease phenotypes in 200,000 UK Biobank exomes.

Congenital heart disease (CHD) has a complex and largely uncharacterised genetic etiology. Using 200,000 UK Biobank (UKB) exomes, we assess the burden of ultra-rare, potentially pathogenic variants in the largest case/control cohort of predominantly mild CHD to date. We find an association with GATA6, a member of the GATA family of transcription factors that play an important role during heart development and has been linked with several CHD phenotypes previously. Several identified GATA6 variants are previously unreported and their roles in conferring risk to CHD warrants further study. We demonstrate that despite limitations regarding detailed familial phenotype information in large-scale biobank projects, through careful consideration of case and control cohorts it is possible to derive important associations.

A novel RNA-mediated mechanism causing down-regulation of insulating promoter interactions in human embryonic stem cells.

The genome-wide promoter interactome is primarily maintained and regulated by architectural proteins such as CTCF and cohesin. However, some studies suggest a role for non-coding RNAs (ncRNAs) in this process. We aimed to characterise the regulatory role of RNA-mediated promoter interactions in the control of gene expression. We integrated genome-wide datasets of RNA-chromatin and promoter-genome interactions in human embryonic stem cells (hESCs) to identify putative RNA-mediated promoter interactions. We discovered that CTCF sites were enriched in RNA-PIRs (promoter interacting regions co-localising with RNA-chromatin interaction sites) and genes interacting with RNA-PIRs containing CTCF sites showed higher expression levels. One of the long noncoding RNAs (lncRNAs) expressed in hESCs, Syntaxin 18-Antisense 1 (STX18-AS1), appeared to be involved in an insulating promoter interaction with the neighbouring gene, MSX1. By knocking down STX18-AS1, the MSX1 promoter-PIR interaction was intensified and the target gene (MSX1) expression was down-regulated. Conversely, reduced MSX1 promoter-PIR interactions, resulting from CRISPR-Cas9 deletion of the PIR, increased the expression of MSX1. We conclude that STX18-AS1 RNA antagonised local CTCF-mediated insulating promoter interactions to augment gene expression. Such down-regulation of the insulating promoter interactions by this novel mechanism may explain the higher expression of genes interacting with RNA-PIRs linked to CTCF sites.

PROTEA, A Southern African Multicenter Congenital Heart Disease Registry and Biorepository: Rationale, Design, and Initial Results.

Objectives: The PartneRships in cOngeniTal hEart disease (PROTEA) project aims to establish a densely phenotyped and genotyped Congenital Heart Disease (CHD) cohort for southern Africa. This will facilitate research into the epidemiology and genetic determinants of CHD in the region. This paper introduces the PROTEA project, characterizes its initial cohort, from the Western Cape Province of South Africa, and compares the proportion or "cohort-prevalences" of CHD-subtypes with international findings. Methods: PROTEA is a prospective multicenter CHD registry and biorepository. The initial cohort was recruited from seven hospitals in the Western Cape Province of South Africa from 1 April 2017 to 31 March 2019. All patients with structural CHD were eligible for inclusion. Descriptive data for the preliminary cohort are presented. In addition, cohort-prevalences (i.e., the proportion of patients within the cohort with a specific CHD-subtype) of 26 CHD-subtypes in PROTEA's pediatric cohort were compared with the cohort-prevalences of CHD-subtypes in two global birth-prevalence studies. Results: The study enrolled 1,473 participants over 2 years, median age was 1.9 (IQR 0.4-7.1) years. Predominant subtypes included ventricular septal defect (VSD) (339, 20%), atrial septal defect (ASD) (174, 11%), patent ductus arteriosus (185, 11%), atrioventricular septal defect (AVSD) (124, 7%), and tetralogy of Fallot (121, 7%). VSDs were 1.8 (95% CI, 1.6-2.0) times and ASDs 1.4 (95% CI, 1.2-1.6) times more common in global prevalence estimates than in PROTEA's pediatric cohort. AVSDs were 2.1 (95% CI, 1.7-2.5) times more common in PROTEA and pulmonary stenosis and double outlet right ventricle were also significantly more common compared to global estimates. Median maternal age at delivery was 28 (IQR 23-34) years. Eighty-two percent (347/425) of mothers used no pre-conception supplementation and 42% (105/250) used no first trimester supplements. Conclusions: The cohort-prevalence of certain mild CHD subtypes is lower than for international estimates and the cohort-prevalence of certain severe subtypes is higher. PROTEA is not a prevalence study, and these inconsistencies are unlikely the result of true differences in prevalence. However, these findings may indicate under-diagnosis of mild to moderate CHD and differences in CHD management and outcomes. This reemphasizes the need for robust CHD epidemiological research in the region.