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Enregistrement W4319063653 · doi:10.1093/eurheartj/ehad033

Unravelling associations between maternal health and congenital heart defect risk in the offspring—the FINNPEDHEART study

2023· article· en· W4319063653 sur OpenAlexaff
Anu Kaskinen, Emmi Helle

Notice bibliographique

RevueEuropean Heart Journal · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueCongenital Heart Disease Studies
Établissements canadiensSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineOffspringCardiovascular healthMaternal healthEnvironmental healthPregnancyInternal medicineGeneticsDiseasePopulation

Résumé

récupéré en direct d'OpenAlex

Congenital heart defects (CHDs) are structural malformations of the heart and intrathoracic vessels. CHDs are the most common congenital malformations in children, affecting roughly one in a hundred new-borns. The care of CHD patients is resource intensive. CHDs accounted for 3.7% of all paediatric hospitalizations in the US in 2009, and the costs of these were estimated at $5.6 billion, representing 15.1% of costs for all paediatric hospitalizations.1 Given that even less complex CHD are associated with significant mortality and morbidity, and a shorter life-expectancy,2,3 primary prevention of CHD with significant benefit to public health should be the essential goal. The FINNPEDHEART project utilizes Finnish nationwide registers, biobank, and genomic data to identify modifiable maternal factors predisposing for offspring’s CHD, ultimately aiming to reduce the incidence of CHD. Both genes and environmental factors, such as maternal diabetes and obesity,4 contribute to the pathogenesis of CHD (Figure 1). Offspring’s risk for CHD is 5%–10% if a parent has a CHD, and for unknown reasons, CHD is inherited more often from the mother than the father.5 Due to the complex inheritance pattern, reduced penetrance, and variable expressivity, identifying gene variants associated with CHD has been challenging. Indeed, relatively few causal genes have been identified. It seems likely that single gene disorders cause the minority of isolated CHD and most isolated CHD are multifactorial, ie. oligogenic or caused by environmental factors in genetically susceptible individuals. The genetic susceptibility has been demonstrated in a number of genome-wide association studies (GWAS), where genome-wide significant loci for certain CHD subgroups and for CHD in general have been identified .6 The complex aetiology of congenital heart defects (CHDs). Both genetic and environmental factors can alter cardiac development during the first pregnancy trimester and cause CHD. The figure has been created with BioRender.com. Little is known about the molecular and cellular-level events that lead to abnormal cardiac development in CHD pregnancies. In addition, the pathophysiological mechanisms caused by maternal chronic conditions leading to CHD are poorly known. Interestingly, CHD and adult cardiovascular disease share common risk factors, such as obesity, diabetes mellitus, and pre-eclampsia.7,8 However, this link has received relatively little attention in CHD research. Recent studies suggest early cardiovascular morbidity in mothers of infants with CHD 7 and adults with lower complexity CHD2 and raise the question: Could cardiac development and adulthood cardiovascular morbidity share similar genetic mechanisms? Deeper understanding of the risk factors for CHD and cardiovascular disease early in life, as well as association between these has the potential to reduce the burden of both diseases. The FINNPEDHEART study approaches the knowledge gap in CHD aetiology from the maternal side and hypotheses the existence of an aetiologically distinct ‘environmental CHD’ subgroup, where in addition to the child’s genes, maternal genetics and gene expression plays a major role in disease development. Finland provides exceptional conditions for epidemiologic and genetic research due to its universal tax-funded health care system, large-scale biobanks, and population-based nationwide registers. First, several Finnish registers record phenotypes and health events over the entire lifespan, including the Medical Birth Register, Register of Congenital Malformations, Care Register for Health Care, Causes of Death Register, the National Infectious Diseases Register, Cancer Register, Primary Health Care Register, and Medication Reimbursement Register. Importantly, all citizens have personal identity numbers, enabling individual-level linkage of these registries. Second, Finnish municipalities organize, provide and finance primary, secondary and tertiary care, and as a part of this system free maternity care, which 99.5% of expectant mothers utilize.9 As a part of the maternity follow-up, certain viral antibodies have been screened from a blood sample between 10 and 14 weeks of gestation since 1983. The leftover samples from 1983–2016 have been deposited in the biobanks for research purposes. Sera exists from ∼98% of pregnancies, comprising more than 2 million samples. Finally, the FinnGen Project is a large-scale biobank study that aims to genotype 500 000 Finnish participants recruited from hospitals as well as from prospective and retrospective epidemiological and disease-based cohorts. The FinnGen genotype data are combined with longitudinal register data and then provided for research for multiple purposes, for example to identify genetic determinants of disease. The FINNPEDHEART project will utilize these unique data collections to study the maternal origins of offspring’s CHD. Three different approaches (Figure 2) will be used: (i) Finnish national registers gathering health related information of all Finns from birth to death will be used in a cohort of ∼1.5 million children, and their 1 million unique mothers and fathers to determine and compare cardiovascular illness, such as metabolic conditions, atherosclerosis and related traits, between parents who have offspring with CHD and unaffected control parents. (ii) Genotype data from the FinnGen project will be utilized to identify maternal genetic risk loci for offspring’s CHD, and (iii) Maternal first trimester serum samples from pregnancies with and without CHD will be analysed to identify CHD associated biomarkers. The FINNPEDHEART study will unravel pathophysiological mechanisms of the genetic and environmental aetiology of congenital heart defects by utilizing (i) Finnish national registers gathering health related information of all Finns from birth to death in a study cohort of 1.5 million children and 1 million unique mothers and fathers, (ii) the FinnGen study collecting genomic and health care data from 500 000 Finns and (iii) the Finnish Maternity Cohort 1st trimester serum samples from expectant mothers. The figure has been created with BioRender.com. The FINNPEDHEART approach of observing environmental CHD with a maternal genetic risk profile as its own subtype will provide novel information on how the combination of maternal genetic and environmental risk factors can contribute to CHD development during early pregnancy. The study questions are timely, since maternal obesity has been increasing at an alarming rate during recent years and cardiovascular morbidity is the leading cause of death in women worldwide accounting for 9% of deaths in 20–44-year-old women in the United States in 2018. In European countries, 7–25% of expectant mothers are overweight, and in the United States only 45% of mothers have a normal weight when entering pregnancy.4 Recognising modifiable risk factors for offspring’s CHD and understanding the risk transmission from the mother to the foetus can aid in developing guidelines and treatments to reduce the incidence of these defects. Lifestyle factors such as dietary habits, body composition, and physical activity, as well as certain dietary supplements and optimal treatment of chronic conditions represent targets for preconception and prenatal interventions. For example, maternal early pregnancy serum lipid profile could be optimized.10 Moreover, by identifying risk factors for offspring’s CHD, more intense monitoring of pregnancy could be targeted to those with the highest risk. Finally, identifying maternal early pregnancy biomarkers and maternal genetic loci associated with offspring’s CHD will provide new, critically needed insights for future research on the cellular and molecular mechanisms of cardiac development. The FINNPEDHEART project is funded by the European Union (ERC, StG, project number 101076986). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. The study will be conducted at the University of Helsinki during 2023–2028.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,061

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,004
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,072
Tête enseignante GPT0,348
Écart entre enseignants0,276 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2023
Routes d'admission1
Résumé présentnon

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