Defining human embryo phenotypes by cohort-specific prognostic factors

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Abstract

Background: Hundreds of thousands of human embryos are cultured yearly at in vitro fertilization (IVF) centers worldwide, yet the vast majority fail to develop in culture or following transfer to the uterus. However, human embryo phenotypes have not been formally defined, and current criteria for embryo transfer largely focus on characteristics of individual embryos. We hypothesized that embryo cohort-specific variables describing sibling embryos as a group may predict developmental competence as measured by IVF cycle outcomes and serve to define human embryo phenotypes. Methodology/Principal Findings: We retrieved data for all 1117 IVF cycles performed in 2005 at Stanford University Medical Center, and further analyzed clinical data from the 665 fresh IVF, non-donor cycles and their associated 4144 embryos. Thirty variables representing patient characteristics, clinical diagnoses, treatment protocol, and embryo parameters were analyzed in an unbiased manner by regression tree models, based on dichotomous pregnancy outcomes defined by positive serum β-human chorionic gonadotropin (β-hCG). IVF cycle outcomes were most accurately predicted at ∼70% by four non-redundant, embryo cohort-specific variables that, remarkably, were more informative than any measured of individual, transferred embryos: Total number of embryos, number of 8-cell embryos, rate (percentage) of cleavage arrest in the cohort and day 3 follicle stimulating hormone (FSH) level. While three of these variables captured the effects of other significant variables, only the rate of cleavage arrest was independent of any known variables. Conclusions/Significance: Our findings support defining human embryo phenotypes by non-redundant, prognostic variables that are specific to sibling embryos in a cohort. © 2008 Jun et al.

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Jun, S. H., Choi, B., Shahine, L., Westphal, L. M., Behr, B., Reijo Pera, R. A., … Yao, M. W. M. (2008). Defining human embryo phenotypes by cohort-specific prognostic factors. PLoS ONE, 3(7). https://doi.org/10.1371/journal.pone.0002562

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