Identificación de polimorfismos en genes relevantes para la implantación y el desarrollo embrionario

Résumé

Background and objectives: The use of Assisted Reproduction Treatments in human fertility brings the challenge of combating early pregnancy loss. The embryo plays a key role in the efficiency of implantation which, together with the need to reduce the number of embryos to be transferred, leads, on the one hand, to the improvement of culture conditions and embryonic development, and, on the other, to the advancement of embryo selection techniques. Following the latter, the main object for this project was to identify embryo polymorphisms (SNPs) related to infertility, in order to use them as biomarkers. Secondary, the results obtained were integrated into an Artificial Intelligent (AI) system adding extra data from the reproductive cycle of the recruited patients, with the aim of creating a tool for embryo selection, able to predict the success of embryo implantation and early embryonic development. Methods: First, a panel composed of 27 genes, whose SNPs could be involved in human embryonic development, implantation failure and early embryonic loss was created. The genetic profile of those genes had previously been reported in mouse knock-out models. The selected panel was researched in 134 DNA samples from trophectoderm biopsies of euploid embryos. The embryos came from an ICSI treatment with PGT-A, and their destination was uterine transfer, while the gestational evolution was followed up until birth. To carry out the massive sequencing of the DNA samples and the bioinformatics analysis of the results, the Ion Torrent technology was used. The sequences, structural and functional characteristics of the proteins, as well as the associated phenotypes were studied using the available databases (Uniprot, GeneCards, Ensembl, MGI, ClinVar and OMIM). We proceeded to identify deleterious SNPs, considering the mutation, genotype, location of the gene, the possible harmful effect and its prevalence in the population. We compared these results with the clinical ones obtained from the embryo transfer and follow-up evolution. Finally, all the data was integrated into an AI system, together with other data which belongs to the reproductive cycle of the patients, age, origin of gametes, morphology and kinetics of the embryos. Results and Conclusions: After evaluating the SNPs, several genes that could be involved in human early embryonic development and/or the peri-implantation period were identified. These included RAE1, F2 and GDF3. From them, three SNPs with a possible deleterious effect have been detected in homozygotes on F2: chr11:46749646C>T, chr11:46750236A>T and chr11:46751102T>A; another two were heterozygous on RAE1: chr20:55941902C>*, and GDF3: chr20:55941902C>*. The panel design has been a key to identify them, and after verification, these polymorphisms could be used as biomarkers for embryonic post implantation failure. The novo mutation that was identified on PIKFYVE (chr2:209179025A>*) shows the necessity to verify the embryo genotype using conventional PCR and Sanger sequencing. Regarding the AI model, the algorithm based on the decision-making tree has been the best choice, and the genetic meta-variable PC1 being in second place amongst the most representative. Results using AI systems brings hope, although, as well as deleterious SNPS identification, the need of increasing the number of tested samples to obtain further representative conclusions is required.