Our colleague Mireia Boluda, project coordinator of our R+D team, has taken part in a paper published in the journal Human Reproduction in collaboration with IVI RMA.
Madrid, February 11, 2025.
In assisted reproductive treatments, embryos are tested before implantation to minimize the risk of miscarriage and transmission of certain genetic conditions.
For this purpose, various techniques are used, generally morphology- or kinetics-based, which are not always optimal for reflecting molecular viability. Genetic testing is also used, mainly based on DNA analysis (known as pre-implantation genetic diagnosis, or PGD).
However, to date, even taking only chromosomally normal embryos into account, only 50-60% of them are able to implant, and 10% of those still end in miscarriage.
New approaches to pre-implantation genetic diagnosis
A new study published in the journal Human Reproduction with the participation of our colleague Mireia Boluda Navarro, project coordinator of our R+D team, has experimentally explored the use of RNA sequencing to advance pre-implantation genetic diagnosis, thanks to a collaboration between Health in Code and IVI RMA, the leading company in reproductive medicine.
This study proposes a more comprehensive study approach, using transcriptomics data to understand how genes are expressed and to identify molecular markers that can better predict implantation capacity.
Highlights of the study results
- RNA sequencing achieved significant agreement with the results from PGT-A (a genetic diagnosis technique used to identify chromosomal abnormalities).
- The study identified 76 genes with differing expression between embryos that could adhere to the uterus and those that could not, pointing at essential molecular pathways for a successful development.
- Some of the genes that stood out were EMP2, AURKB, NOTCH3, and FZD5, linked with implantation and development.
This groundbreaking experimental method could complement traditional pre-implantation genetic diagnosis in order to select those embryos with an optimal reproductive prognosis.
Read the full article here: https://lc.cx/3CwMBn
