Minimally Invasive Cell-Free Human Embryo Aneuploidy Testing (miPGT-A) Utilizing Combined Spent Embryo Culture Medium and Blastocoel Fluid –Towards Development of a Clinical Assay
Bibliographic record
Abstract
Preimplantation genetic testing for aneuploidies (PGT-A) using trophectoderm (TE) biopsy samples is labour intensive, invasive, and subject to sampling bias. In this study, we report on the efficacy and factors affecting accuracy of a technique we pioneered for minimally invasive preimplantation genetic testing for aneuploidy (miPGT-A). Our technique uses cell-free embryonic DNA (cfeDNA) in spent embryo culture medium (SEM) combined with blastocoel fluid (BF) to increase the amount of assayable cfeDNA. We compared miPGT-A results (n = 145 embryos) with standard PGT-A analysis of the corresponding trophectoderm biopsy. We found that accuracy of miPGT was not related to blastocyst morphological grade. The overall concordance rate per sample for euploidy/aneuploidy status between miPGT-A and TE biopsy samples was 88/90 (97.8%), and was not different between good 47/48 (97.9%) and moderate/low quality blastocysts 41/42 (97.9%) (p > 0.05). Importantly, we also discovered that for cfeDNA analysis, the SurePlex whole genome amplification (WGA) kit can be utilized without an additional cell lysis/extraction DNA step; this efficiency likely reduces the risk of maternal contamination. Regarding origin of embryonic cfeDNA, the average amount of miPGT-A WGA-DNA we obtained from blastocysts with different morphological grades, as well as the size miPGT-A WGA-DNA fragments, suggest that it is unlikely that apoptosis and necrosis are only mechanisms of DNA release from the inner cell mass (ICM) and TE into BF and SEM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".