Association of microRNAs With Embryo Development and Fertilization in Women Undergoing Subfertility Treatments: A Pilot Study

Abstract

Objective: Small non-coding RNAs, known as microRNAs (miRNAs), have emerging regulatory functions within the ovary that have been related to fertility. This study was undertaken to determine if circulating miRNAs reflect the changes associated with the parameters of embryo development and fertilization. Methods: In this cross-sectional pilot study. Plasma miRNAs were collected from 48 sequentially presenting women in the follicular phase prior to commencing in vitro fertilization (IVF). Circulating miRNAs were measured using locked nucleic acid (LNA)-based quantitative PCR (qPCR), while an updated miRNA data set was used to determine their level of expression. Results: Body mass index and weight were associated with the miRNAs let7b-3p and miR-375, respectively (p < 0.05), with the same relationship being found between endometrium thickness at oocyte retrieval and miR-885-5p and miR-34a-5p (p < 0.05). In contrast, miR-1260a was found to be inversely associated with anti-Mullerian hormone (AMH; p = 0.007), while miR-365a-3p, miR122-5p, and miR-34a-5p correlated with embryo fertilization rates (p < 0.05). However, when omitting cases of male infertility (n = 15), miR122-5p remained significant (p < 0.05), while miR-365a-3p and miR-34a-5p no longer differed; interestingly, however, miR1260a and mir93.3p became significant (p = 0.0087/0.02, respectively). Furthermore, age was negatively associated with miR-335-3p, miR-28-5p, miR-155-5p, miR-501-3p, and miR-497-5p (p < 0.05). Live birth rate was negatively associated with miR-335-3p, miR-100-5p, miR-497-5p, let-7d, and miR-574-3p (p < 0.05), but these were not significant when age was accounted for.However, with the exclusion of male factor infertility, all those miRNAs were no longer significant, though miR.150.5p emerged as significant (p = 0.042). A beta-regression model identified miR-1260a, miR-486-5p, and miR-132-3p (p < 0.03, p = 0.0003, p < 0.00001, respectively) as the most predictive for fertilization rate. Notably, changes in detectable miRNAs were not linked to cleavage rate, top quality embryos (G3D3), and blastocyst or antral follicle count. An ingenuity pathway analysis showed that miRNAs associated with age were also associated with the variables found in reproductive system diseases. Conclusion: Plasma miRNAs prior to the IVF cycle were associated with differing demographic and IVF parameters, including age, and may be predictive biomarkers of fertilization rate.

Keywords: IVF; embryo; fertilization rate; infertility; microRNA.

Figure 1

MicroRNA (miRNA) trained and prediction models for live birth rate. The miRNA trained and prediction models for live birth rate show the moderate training effect, but a weaker prediction effect, based on miR-1260a, miR-486.5p, and miR-132.3p (p < 0.03, p = 0.0003, p < 0.00001, respectively, was most predictive of fertilization rate.

Figure 2

Ingenuity pathway analysis (IPA). Pathway connections for the five miRNAs (miRNAs miR-335.3p, miR-28.5p, miR-155.5p, miR-501.3p, and miR-497.5p) that were significantly associated with age and reproductive abnormalities. The IPA demonstrates the most significantly affected pathways relating to the proteins in question. The miRNA in red showed a significant decrease.