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Apoptotic qPCR gene expression array analysis demonstrates proof-of-concept for rapid blastocoel fluid-conditioned media molecular prediction

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Abstract

Purpose

Successful identification of transcriptomic biomarkers within human IVF embryos may enhance implantation prediction and provide insights not available through conventional embryo biopsy genomic analysis. We demonstrate proof-of-concept for a methodology to assess overall embryo gene expression using qPCR with blastocoel fluid-conditioned media by examining the comparative presence of apoptotic genes.

Methods

Blastocoel fluid-conditioned media were collected from 19 embryos (11 euploid) following trophectoderm biopsy of day-5 ICSI-IVF blastocysts. Media were assessed for apoptotic gene expression via qPCR. Statistical analysis of gene expression was conducted via Wilcoxon Signed-Ranks test (overall expression), multivariate ANOVA (functional gene groups), and chi-square test of independence (gene level).

Results

A significantly higher overall apoptotic gene expression within euploid versus aneuploid embryos (p = 0.001) was observed. There was significantly (p = 0.045) higher expression of pro-apoptotic genes between implanted and not implanted embryos. Pro- vs. anti-apoptotic gene expression from all euploid embryos approached significance (p = 0.053). The ploidy status-based claim is further substantiated at the gene level with significantly higher expression of BBC3 (p = 0.012) and BCL2L13 (p = 0.003) in euploid embryos compared to aneuploid embryos.

Conclusions

In this preliminary study, we demonstrate that (1) qualitative analysis of blastocoel fluid-conditioned media gene expression is possible, (2) global trends of expression are potentially related to clinical outcomes, and (3) gene-level expression trends exist and may be another viable metric for comparative expression between samples. The presence of statistical significance within analyses conducted with this sample size warrants a larger investigation of blastocoel fluid-conditioned media as an additional beneficial predictive tool for future IVF cases.

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Acknowledgements

We thank Alex Ewing for his statistical analysis recommendations for this dataset.

Funding

University of South Carolina Magellan Scholar funds supported JB and offset some costs for experiments. University of South Carolina School of Medicine Greenville development funds (to RJC and WER) offset experimental costs.

Author information

Authors and Affiliations

  1. Department of Biomedical Sciences, University of South Carolina School of Medicine Greenville, 701 Grove Road, Greenville, SC, 29605, USA

    Arnav Lal, Allison Kranyak, Jonathan Blalock, Deepti Athavale, Alyssa Barré, Addison Doran, Lauren A. Fowler, William E. Roudebush & Renee J. Chosed

  2. School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA

    Arnav Lal

  3. Department of Obstetrics and Gynecology, University of Texas Health Science Center, San Antonio, TX, 78229, USA

    T. Arthur Chang & Randal D. Robinson

  4. VIOS Fertility Institute, Swansea, IL, 62226, USA

    Shawn Zimmerman

  5. Department of Obstetrics and Gynecology-Reproductive Medicine, Wake Forest School of Medicine, Winston-Salem, NC, 27101, USA

    J. David Wininger

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  1. Arnav Lal
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  2. Allison Kranyak
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Contributions

R. J. C. and W. E. R. designed the experiments. S. Z., T. A. C., R. D. R., and J. D. W. carried out sample collection, pooled patient data records, and contributed to the revision of the manuscript. A. L., A. K., J. B., D. A., A. B, and A. B. carried out the cDNA synthesis and real-time experiments and aided in data analysis. A. L. led figure construction and played an integral role in manuscript writing. L. A. F. performed the statistical analysis on the dataset. A. L. and R. J. C. led the data analysis, interpretation of results, and manuscript writing. All authors contributed to the manuscript drafting process.

Corresponding author

Correspondence to Renee J. Chosed.

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Lal, A., Kranyak, A., Blalock, J. et al. Apoptotic qPCR gene expression array analysis demonstrates proof-of-concept for rapid blastocoel fluid-conditioned media molecular prediction. J Assist Reprod Genet 39, 1515–1522 (2022). https://doi.org/10.1007/s10815-022-02510-3

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