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

Abstract 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.

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Publication Details

Journal
Egyptian Journal of Medical Human Genetics
Published
2024-10-26
DOI
https://doi.org/10.1186/s43042-024-00598-z
Citations
1
Primary Topic
Ovarian function and disorders
Type
article
Field-Weighted Citation Impact
0.54

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article

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

Olga Lyangasova, Svetlana V. Lomteva, Elena V. Butenko, Karina Y. Sagamonova et al.
1 citations
Egyptian Journal of Medical Human Genetics
Ovarian function and disorders
0.54
article

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

Olga Lyangasova, Svetlana V. Lomteva, Elena V. Butenko, Karina Y. Sagamonova, Т. П. Шкурат
article en
1 citations

Abstract

Abstract 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.

Egyptian Journal of Medical Human GeneticsVol. 25(1)
Southern Federal University (RU), Rostov State Medical University (RU), Center for Human Reproduction (US)
Russian Science Foundation
Openalex Percentile: Top 26%
Ovarian function and disorders
0.54
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