Quantification of Cell-Free DNA in Normal and Complicated Pregnancies: Overcoming Biological and Technical Issues
Bibliographic record
Abstract
The characterization of cell-free DNA (cfDNA) originating from placental trophoblast in maternal plasma provides a powerful tool for non-invasive diagnosis of fetal and obstetrical complications. Due to its placental origin, the specific epigenetic features of this DNA (commonly known as cell-free fetal DNA) can be utilized in creating universal 'fetal' markers in maternal plasma, thus overcoming the limitations of gender- or rhesus-specific ones. The goal of this study was to compare the performance of relevant approaches and assays evaluating the amount of cfDNA in maternal plasma throughout gestation (7.2-39.5 weeks). Two fetal- or placental-specific duplex assays (RPP30/SRY and RASSF1A/β-Actin) were applied using two technologies, real-time quantitative PCR (qPCR) and droplet digital PCR (ddPCR). Both methods revealed similar performance parameters within the studied dynamic range. Data obtained using qPCR and ddPCR for these assays were positively correlated (total cfDNA (RPP30): R = 0.57, p = 0.001/placental cfDNA (SRY): R = 0.85, p<0.0001; placental cfDNA (RASSF1A): R = 0.75, p<0.0001). There was a significant correlation in SRY and RASSF1A results measured with qPCR (R = 0.68, p = 0.013) and ddPCR (R = 0.56, p = 0.039). Different approaches also gave comparable results with regard to the correlation of the placental cfDNA concentration with gestational age and pathological outcome. We conclude that ddPCR is a practical approach, adaptable to existing qPCR assays and well suited for analysis of cell-free DNA in plasma. However, it may need further optimization to surpass the performance of qPCR.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".