Mathematical modeling of human oocyte aneuploidy.

Aneuploidy is the leading contributor to pregnancy loss, congenital anomalies, and in vitro fertilization (IVF) failure in humans. Although most aneuploid conceptions are thought to originate from meiotic division errors in the female germline, quantitative studies that link the observed phenotypes to underlying error mechanisms are lacking. In this study, we developed a mathematical modeling framework to quantify the contribution of different mechanisms of erroneous chromosome segregation to the production of aneuploid eggs. Our model considers the probabilities of all possible chromosome gain/loss outcomes that arise from meiotic errors, such as nondisjunction (NDJ) in meiosis I and meiosis II, and premature separation of sister chromatids (PSSC) and reverse segregation (RS) in meiosis I. To understand the contributions of different meiotic errors, we fit our model to aneuploidy data from 11,157 blastocyst-stage embryos. Our best-fitting model captures several known features of female meiosis, for instance, the maternal age effect on PSSC. More importantly, our model reveals previously undescribed patterns, including an increased frequency of meiosis II errors among eggs affected by errors in meiosis I. This observation suggests that the occurrence of NDJ in meiosis II is associated with the ploidy status of an egg. We further demonstrate that the model can be used to identify IVF patients who produce an extreme number of aneuploid embryos. The dynamic nature of our mathematical model makes it a powerful tool both for understanding the relative contributions of mechanisms of chromosome missegregation in human female meiosis and for predicting the outcomes of assisted reproduction.