Blastocyst Morphology Holds Clues Concerning The Chromosomal Status of The Embryo

Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements

BACKGROUND

The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy neonate. Some algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome, who subjected to preimplantation genetic testing for aneuploidy (PGT-A) treatment. However, it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal rearrangement.

METHODS

From February 2020 to May 2021, we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos, the clinical information of couples, and the comprehensive chromosome screening results of those blastocysts that had received PGT treatment. Initially, we developed a novel deep learning model called the Attentive Multi-Focus Selection Network (AMSNet) to analyze time-lapse videos in real time and predict blastocyst formation. Building upon AMSNet, we integrated additional clinically predictive variables and created a second deep learning model, the Attentive Multi-Focus Video and Clinical Information Fusion Network (AMCFNet), to assess the euploidy status of embryos. The efficacy of the AMCFNet was further tested in embryos with parental chromosomal rearrangements. The receiver operating characteristic curve (ROC) was used to evaluate the superiority of the model.

RESULTS

A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task, and 1422 qualified blastocysts received PGT-A ( n = 589) or PGT for chromosomal structural rearrangement (PGT-SR, n = 833) were enrolled for the euploidy assessment task in this study. The AMSNet model using seven focal raw time-lapse videos has the best real-time accuracy. The real-time accuracy for AMSNet to predict blastocyst formation reached above 70% on the day 2 of embryo culture, and then increased to 80% on the day 4 of embryo culture. Combing with 4 clinical features of couples, the AUC of AMCFNet with 7 focal points increased to 0.729 in blastocysts derived from couples with chromosomal rearrangement.

CONCLUSION

Integrating seven focal raw time-lapse images of embryos and parental clinical information, AMCFNet model have the capability of assessing euploidy status in blastocysts derived from couples with chromosomal rearrangement.

LC-MS Analysis Revealed the Significantly Different Metabolic Profiles in Spent Culture Media of Human Embryos with Distinct Morphology, Karyotype and Implantation Outcomes

In this study we evaluated possible differences in metabolomic profiles of spent embryo culture media (SECM) of human embryos with distinct morphology, karyotype, and implantation outcomes. A total of 153 samples from embryos of patients undergoing in vitro fertilization (IVF) programs were collected and analyzed by HPLC-MS. Metabolomic profiling and statistical analysis revealed clear clustering of day five SECM from embryos with different morphological classes and karyotype. Profiling of day five SECM from embryos with different implantation outcomes showed 241 significantly changed molecular ions in SECM of successfully implanted embryos. Separate analysis of paired SECM samples on days three and five revealed 46 and 29 molecular signatures respectively, significantly differing in culture media of embryos with a successful outcome. Pathway enrichment analysis suggests certain amino acids, vitamins, and lipid metabolic pathways to be crucial for embryo implantation. Differences between embryos with distinct implantation potential are detectable on the third and fifth day of cultivation that may allow the application of culture medium analysis in different transfer protocols for both fresh and cryopreserved embryos. A combination of traditional morphological criteria with metabolic profiling of SECM may increase implantation rates in assisted reproductive technology programs as well as improve our knowledge of the human embryo metabolism in the early stages of development.

The Relationship between Human Embryo Parameters and De Novo Chromosomal Abnormalities in Preimplantation Genetic Testing Cycles

DESIGN

In total, 456 PGT cycles, including 283 PGT-SR cycles and 173 PGT-A cycles, were assessed through comprehensive chromosome screening (CCS) from January 2017 to June 2020 at the Department of Reproductive Medicine of the Third Affiliated Hospital of Zhengzhou University. Trophectoderm (TE) biopsies were sequenced using next-generation sequencing (NGS). The incidence of de novo chromosome abnormalities was calculated, and the relationships between de novo chromosome abnormality rates and maternal age, number of oocytes retrieved, and parameters of cleavage-stage embryos and blastocyst-stage embryos were investigated.

RESULTS

The incidence of de novo chromosome abnormalities was 28.0% (318/1,135) in the PGT-SR cycles and 36.3% (214/590) in the PGT-A cycles, which increased with maternal age in both PGT-SR cycles (P = 0.018) and PGT-A cycles (P < 0.001). The incidence of de novo chromosome abnormalities was related to TE grade (P < 0.001), internal cell mass grade (P = 0.002), and development speed (day 5 vs. day 7: P < 0.001) of blastocyst-stage embryos. The incidence of de novo chromosomal abnormalities was irrelevant to the number of oocytes retrieved and the parameters of the embryo at the cleavage stage.

CONCLUSION

Blastocysts with higher morphology scores and faster progression had a lower incidence of de novo chromosome abnormalities, especially complex chromosome abnormalities. De novo chromosome abnormalities may negatively affect the morphological grading of blastocysts. Our findings will provide valuable information to the fertility doctor for embryo selection in non-PGT cycles.

End-to-end deep learning for recognition of ploidy status using time-lapse videos

PURPOSE

Our retrospective study is to investigate an end-to-end deep learning model in identifying ploidy status through raw time-lapse video.

METHODS

By randomly dividing the dataset of time-lapse videos with known outcome of preimplantation genetic testing for aneuploidy (PGT-A), a deep learning model on raw videos was trained by the 80% dataset, and used to test the remaining 20%, by feeding time-lapse videos as input and the PGT-A prediction as output. The performance was measured by an average area under the curve (AUC) of the receiver operating characteristic curve.

RESULT(S)

With 690 sets of time-lapse video image, combined with PGT-A results, our deep learning model has achieved an AUC of 0.74 from the test dataset (138 videos), in discriminating between aneuploid embryos (group 1) and others (group 2, including euploid and mosaic embryos).

CONCLUSION

Our model demonstrated a proof of concept and potential in recognizing the ploidy status of tested embryos. A larger scale and further optimization on the exclusion criteria would be included in our future investigation, as well as prospective approach.

SV40 Large T Antigen Disrupts Embryogenesis of Canine and Porcine Somatic Cell Nuclear Transfer Embryo

Background

Somatic cell nuclear transfer (SCNT) is a useful biotechnological tool for transgenic animal production using genetically modified somatic cells (GMSCs). However, there are several limitations preventing successful transgenic animal generation by SCNT, such as obtaining proper somatic donor cells with a sufficiently long life span and proliferative capacity for generating GMSCs. Here, we established simian virus 40 large T antigen (SV40LT)-mediated lifespan-extended canine fibroblast cells (SV40LT-K9 cells) and evaluated their potential as nuclei donors for SCNT, based on cellular integrity and SCNT embryo development.

Results

SV40LT did not cause canine cell transformation, based on cell morphology and proliferation rate. No anchorage-independent growth in vitro and tumorigenicity in vivo were observed. After SCNT with SV40LT-K9 cells, embryos were transferred into surrogate dogs. All dogs failed to become pregnant. Most embryos did not proceed past the 8-cell stage and only one surrogate showed an implantation trace in its oviduct, indicating that the cells rarely developed into blastocysts. Because of the absence of an in vitro maturation method for canine embryos, we performed identical experiments using porcine fibroblast cells. Similarly, SV40LT did not transform porcine fibroblast cells (SV40LT-Pig cells). During in vitro development of SV40LT-Pig cell-driven SCNT embryos, their blastocyst formation rate was clearly lower than those of normal cells. Karyotyping analysis revealed that both SV40LT-K9 and SV40LT-Pig cells had aberrant chromosomal statuses.

Conclusions

Although lifespan-extended canine and porcine cells via SV40LT exhibit no apparent transforming changes, they are inappropriate for use as nuclei donors for SCNT because of their aneuploidy.

Could time-lapse embryo imaging reduce the need for biopsy and PGS?

PURPOSE

To review relevant studies examining the relationship between embryo morpho-kinetics and aneuploidy.

METHODS

Search of Pubmed and Medline using relevant keywords pertaining to morphology, morphokinetics and embryonic aneuploidy, as well as examination of various reference lists and conference proceedings.

RESULTS

An abundance of publications, both preliminary and peer-reviewed, have emerged regarding the usefulness of time-lapse imaging in tracking embryo development and improving embryo selection. Recently, these publications have explored ability to not only predict blastocyst formation and implantation, but also the ability to detect embryonic chromosomal aneuploidy. Of the two peer-reviewed retrospective studies on morpho-kinetics and embryonic aneuploidy, one demonstrates that early cleavage timings can indicate chromosomal complement, while the other demonstrates that key events following the maternal-zygotic transition can be markers of aneuploidy. A recent paper also demonstrates improved outcomes following IVF using a selection algorithm to identify embryos at "low risk" of chromosomal abnormalities. However, the predictive nature of these events and timings is far from ideal. Additionally, results may be dependent upon the day of biopsy and method utilized for chromosomal assessment.

CONCLUSION

With continued effort, the combination of multiple morphologic endpoint assessments and developmental timings and refinement of modeling systems may improve the predictive ability to determine embryonic aneuploidy. This may help select a subset of embryos that are less likely to carry chromosomal abnormalities and improve assisted reproductive outcomes. However, embryo biopsy, followed by preimplantation genetic screening/comprehensive chromosomal screening still remains the most reliable method to assess chromosomal complement of preimplantation embryos.