MicroRNAs as novel biomarkers for prenatal fetal congenital heart disease – systematic literature review
Notice bibliographique
Résumé
Introduction: CHD accounts for about one-third of all congenital malformations and is the leading cause of infant mortality. Currently, the primary method for diagnosing CHD during pregnancy is fetal echocardiography. Several studies have observed significant differences in the expression levels of specific miRNAs between CHD fetuses and normal fetuses. This systematic review explores the potential of miRNAs as non-invasive biomarkers for the prenatal detection of CHD in fetuses. Material and methods: The systematic review followed PRISMA guidelines, conducting a detailed search across PubMed, Scopus, and Web of Science using predefined terms related to microRNAs and congenital heart defects. Inclusion was limited to original, full-text articles in English, while non-English studies, reviews, and inaccessible full texts were excluded. Data extraction and quality assessment using the Newcastle Ottawa Scale ensured comprehensive evaluation and minimized bias. Results: Studies explored the potential of miRNAs as biomarkers for detecting congenital heart defects (CHD) in fetuses, employing diverse sample types such as maternal serum, umbilical cord blood, and amniotic fluid. Diagnostic methods primarily included fetal echocardiography, complemented by postnatal confirmation through surgery or autopsy. Gestational ages at sample collection ranged predominantly from the second trimester (16-27 weeks) to narrower windows, reflecting methodological variability across studies. The included studies utilized advanced technologies, such as next-generation sequencing (e.g., Illumina HiSeq, NovaSeq) and microarrays, for discovery-phase experiments, while validation predominantly employed qRT-PCR techniques. Identified miRNAs showed heterogeneity in expression patterns and diagnostic potential, with several studies reporting high sensitivity, specificity, and AUC values for specific miRNAs like miR-146a-5p and miR-142-5p. While some miRNAs demonstrated exceptional diagnostic accuracy, others were only described in terms of differential expression, highlighting the variability and complexity of miRNA biomarker discovery for CHD. Conslusion: The findings of this systematic literature review provide evidence that some miRNAs could serve as non-invasive biomarkers for the early detection of CHD in fetuses. However, each of the reviewed studies identified different miRNAs as potential biomarkers. This variability may stem from differences in experimental methodologies, including approaches to miRNA isolation, quantification techniques, and the types of biological materials analyzed. Such methodological heterogeneity, combined with small sample sizes and the diverse spectrum of CHDs, underscores the need for caution in interpreting these findings. At this stage, it is not feasible to translate these results into clinical practice or establish standardized miRNA-based prenatal screening protocols.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».