MicroRNAs as novel biomarkers for prenatal fetal congenital heart disease – systematic literature review
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".