Serum microRNA profiling for the identification of predictive molecular markers of the response to controlled ovarian stimulation

JBRA Assist Reprod. 2020 May 1;24(2):97-103. doi: 10.5935/1518-0557.20190070.


Objective: To identify potential microRNA (miRNA) biomarkers of poor, normal and hyperresponse to controlled ovarian stimulation (COS).

Methods: In the present study, we assessed 40 serum samples from patients undergoing COS. We used ten samples to standardize miRNAs detection in the serum. The remaining 30 samples were split into three groups depending on the patient's response to COS: poor response (PR group, n=10), normal response (NR group, n=10), and hyperresponse (HR group, n=10). Aberrantly expressed miRNAs were identified using a large-scale expression analysis platform. Gene set enrichment analysis was performed to assess the biological processes potentially modulated by the identified miRNAs.

Results: Twenty-two miRNAs were detected only in the PR or HR groups when compared with the NR group. From those, 11 presented poor dissociation curves and were excluded from further analysis. A bioinformatics analysis revealed that the selected 11 miRNAs target several genes involved in GnRH, estrogen and prolactin signaling, oocyte maturation, female pregnancy, and meiosis.

Conclusion: The large-scale analysis of miRNA expression identified distinct miRNA profiles for poor and hyperresponse to COS, which potentially modulate key processes for human assisted reproduction. All evidence suggests that the serum microRNA profiling may discriminate patients who will respond in an exacerbated manner from those who will respond insufficiently to COS. Further studies may validate these miRNAs, enabling the individualization of treatment and more successful outcomes.

Keywords: COS; biomarker; hyper responder; microRNA; poor responder; stimulation.

MeSH terms

  • Adult
  • Biomarkers / blood
  • Female
  • Humans
  • MicroRNAs / blood*
  • Ovulation / blood*
  • Ovulation Detection
  • Ovulation Induction*


  • Biomarkers
  • MicroRNAs