Algorithms to minimize the effect of maternal contamination in non-invasive chromosome screening

Area of Science:

• Reproductive Medicine
• Genetics
• Bioinformatics

Background:

• Maternal contamination in embryo spent culture medium can interfere with accurate copy number variation (CNV) analysis.
• Non-invasive prenatal testing (NIPT) and preimplantation genetic testing (PGT) rely on accurate chromosomal assessment.

Purpose of the Study:

• To develop and validate algorithms for detecting maternal contamination in embryo culture medium.
• To correct copy number variations (CNV) in embryos affected by maternal contamination without parental DNA.
• To enhance the accuracy of non-invasive chromosome screening.

Main Methods:

• Developed algorithms to assess maternal contamination using X and Y chromosome mosaic ratios.
• Developed an algorithm to correct CNV in embryos with maternal contamination.
• Tested algorithms on 317 embryo culture medium samples.
• Validated accuracy through a prospective clinical study, including donated embryos and prenatal testing cases.

Main Results:

• The CNV correction algorithm significantly improved consistency between corrected and whole embryo results (69.1% vs 10.9%).
• Maternal contamination was identified in 27.8% of 317 samples.
• Re-classification of samples using the CNV correction algorithm demonstrated improved accuracy in identifying euploid, aneuploid, and mosaic embryos.
• The clinical study achieved a live birth rate of 44.7% with an overall concordance rate of 95.8%.

Conclusions:

• Algorithms effectively detect maternal contamination in embryo culture medium.
• The CNV correction algorithm minimizes maternal contamination effects, enhancing non-invasive chromosome screening accuracy.
• This approach offers a promising tool for improving preimplantation genetic testing and reproductive outcomes.