An in silico model using prognostic genetic factors for ovarian response in controlled ovarian stimulation: A systematic review

Background Predicting the number of follicles obtained after controlled ovarian stimulation (COS) is challenging, especially considering individual variability. Since FSH is a fundamental hormone that controls growing follicle activity, genetic variants are predicted to affect ovarian response to stimulation. The aim of the study The purpose of this study was to analyze whether FSHB rs10835638 and FSHR rs6166 genetic variants in combination with clinical parameters might be considered as potential precise predictors of ovarian response during COS. Materials and methods The present study included 144 women from infertile couples who underwent assisted reproductive technologies. Women with reduced FSH and/or AMH serum levels were excluded from the study. Genotyping was carried out applying restriction fragment length polymorphism analysis. Results Genotypes frequencies for FSHB rs10835638 and FSHR rs6166 were GG (73%), GT (24%), TT (3%) and AA (42%), AG (39%), GG (19%), respectively. FSHR rs6166 GG genotype was shown as associated with higher early follicular phase serum FSH, LH and progesterone levels, compared to AA and AG genotypes. Logistic regressive models that simultaneously use the patient’s genetic and clinical characteristics to calculate the probability of low or high ovarian response have been developed. Conclusion The present study suggests that rs10835638 and rs6166 genetic variants affect hypothalamic-pituitary–gonadal hormones serum levels, and together may provide an improved model for predicting an ovarian response during COS.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

An in silico model using prognostic genetic factors for ovarian response in controlled ovarian stimulation: A systematic review

Cited by 2 publications

References 122 publications

Effects of HRG and TP73 gene variations on ovarian response

Effects of HRG and TP73 gene variations on ovarian response

FSHB and FSHR genes variants in combination with hormones levels predict low and high ovarian response to controlled ovarian stimulation: a logistic regressive model

Contact Info

Product

Resources

About