Faculty Bibliography

OBJECTIVE:To review the outcomes of patients who underwent autologous oocyte thaw after planned oocyte cryopreservation. DESIGN/METHODS:Retrospective cohort study. SETTING/METHODS:Large urban university-affiliated fertility center. PATIENT(S)/METHODS:All patients who underwent ≥1 autologous oocyte thaw before December 31, 2020. INTERVENTION(S)/METHODS:None. MAIN OUTCOME MEASURE(S)/METHODS:The primary outcome was the final live birth rate (FLBR) per patient, and only patients who had a live birth (LB) or consumed all remaining inventory (cryopreserved oocytes and resultant euploid/untested/no result embryos) were included. The secondary outcomes were laboratory outcomes and LB rates per transfer. RESULT(S)/RESULTS:A total of 543 patients underwent 800 oocyte cryopreservations, 605 thaws, and 436 transfers. The median age at the first cryopreservation was 38.3 years. The median time between the first cryopreservation and thaw was 4.2 years. The median numbers of oocytes and metaphase II oocytes (M2s) thawed per patient were 14 and 12, respectively. Overall survival of all thawed oocytes was 79%. Of all patients, 61% underwent ≥1 transfer. Among euploid (n = 262) and nonbiopsied (n = 158) transfers, the LB rates per transfer were 55% and 31%, respectively. The FLBR per patient was 39%. Age at cryopreservation and the number of M2s thawed were predictive of LB; the FLBR per patient was >50% for patients aged <38 years at cryopreservation or who thawed ≥20 M2s. A total of 173 patients (32%) have remaining inventory. CONCLUSION(S)/CONCLUSIONS:Autologous oocyte thaw resulted in a 39% FLBR per patient, which is comparable with age-matched in vitro fertilization outcomes. Studies with larger cohorts are necessary.

Embryos are diagnosed as mosaic if their chromosomal copy number falls between euploid and aneuploid. The purpose of this study was to investigate the impact of mosaicism on global gene expression. This study included 42 blastocysts that underwent preimplantation genetic testing for aneuploidy (PGT-A) and were donated for IRB approved research. Fourteen blastocysts were diagnosed as mosaic with Next-generation Sequencing (NGS). Three NGS diagnosed euploid embryos, and 25 aneuploid embryos (9 NGS, 14 array Comparative Genomic Hybridization, 2 Single Nucleotide Polymorphism array) were used as comparisons. RNA-sequencing was performed on all of the blastocysts. Differentially expressed genes (DEGs) were calculated using DESeq2/3.5 (R Bioconductor Package) with p < 0.05 considered significantly differentially expressed. Pathway analysis was performed on mosaic embryos using EnrichR with p < 0.05 considered significant. With euploid embryo gene expression used as a control, 12 of 14 mosaic embryos had fewer DEGs compared to aneuploid embryos involving the same chromosome. On principal component analysis (PCA), mosaic embryos mapped separately from aneuploid embryos. Pathways involving cell proliferation, differentiation, and apoptosis were the most disrupted within mosaic embryos. Mosaic embryos have decreased disruption of global gene expression compared to aneuploid embryos. This study was limited by the small sample size, lack of replicate samples for each mosaic abnormality, and use of multiple different PGT-A platforms for the diagnosis of aneuploid embryos.

In vitro fertilization is typically associated with high failure rates per transfer, leading to an acute need for the identification of embryos with high developmental potential. Current methods are tailored to specific times after fertilization, often require expert inspection, and have low predictive power. Automatic methods are challenged by ambiguous labels, clinical heterogeneity, and the inability to utilize multiple developmental points. In this work, we propose a novel method that trains a classifier conditioned on the time since fertilization. This classifier is then integrated over time and its output is used to assign soft labels to pairs of samples. The classifier obtained by training on these soft labels presents a significant improvement in accuracy, even as early as 30 h post-fertilization. By integrating the classification scores, the predictive power is further improved. Our results are superior to previously reported methods, including the commercial KIDScore-D3 system, and a group of eight senior professionals, in classifying multiple groups of favorable embryos into groups defined as less favorable based on implantation outcomes, expert decisions based on developmental trajectories, and/or genetic tests.