The role of anti-Mullerian hormone in predicting the response to clomiphene citrate in unexplained infertility

Anti-Mullerian Hormone (AMH) as a Predictor of Ovarian Response to Clomiphene Citrate in Polycystic Ovarian Syndrome

Background: Serum Anti-Mullerian hormone (AMH) levels in women with polycystic ovary syndrome (PCOS) are two- to threefold higher than in ovulatory women with normal ovaries, corresponding to the two- to threefold increase in the number of small follicles in PCOS. The increased AMH has been hypothesized to reduce follicle sensitivity to follicle stimulating hormone (FSH) and estradiol production, thus preventing follicle selection, resulting in follicular arrest at the small antral phase with failure of dominance.

Objective: The study was undertaken to test the hypothesis that high AMH level is associated with poor response to ovulation induction in PCOS women.

Methods: This was a cross-sectional comparative study of 50 infertile women with PCOS, grouped into those with AMH level <8 ng/mL and those with AMH level [Formula: see text] 8 ng/mL. All participants received an initial dose of 100 mg/day of clomiphene citrate from 2nd to 6th day of menstrual cycle. Ovarian response (follicle size) was assessed by transvaginal monitoring on 12th day of cycle.

Results: A total of 50 women were recruited, of which 4 dropped out. Women with AMH [Formula: see text] 8 ng/mL comprised only 23.91% of the PCOS women. AMH and day 12 follicle size had a statistically significant association. Adjusting for other confounding variables in linear, logarithmic, and logistic analysis, serum AMH had significant negative relationship with follicle size (r = 0.511, p < 0.001). AMH was also positively correlated with serum LH, testosterone and negatively correlated with serum follicle stimulating hormone (FSH), serum TSH and BMI.

Conclusion: We observed that higher AMH level women had poor response to ovulation induction compared to women with low AMH level.

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

PURPOSE

To study the use of in silica model to better understand and propose new markers of ovarian response to controlled ovarian stimulation before IVF.

METHODS

A systematic review and in silica model using bioinformatics. After the selection of 103 papers from a systematic review process, we performed a GRADE qualification of all included papers for evidence-based quality evaluation. We included 57 genes in the silica model using a functional protein network interaction. Moreover, the construction of protein-protein interaction network was done importing these results to Cytoscape. Therefore, a cluster analysis using MCODE was done, which was exported to a plugin BINGO to determine Gene Ontology. A p value of < 0.05 was considered significant, using a Bonferroni correction test.

RESULTS

In silica model was robust, presenting an ovulation-related gene network with 87 nodes (genes) and 348 edges (interactions between the genes). Related to the network centralities, the network has a betweenness mean value = 102.54; closeness mean = 0.007; and degree mean = 8.0. Moreover, the gene with a higher betweenness was PTPN1. Genes with the higher closeness were SRD5A1 and HSD17B3, and the gene with the lowest closeness was GDF9. Finally, the gene with a higher degree value was UBB; this gene participates in the regulation of TP53 activity pathway.

CONCLUSIONS

This systematic review demonstrated that we cannot use any genetic marker before controlled ovarian stimulation for IVF. Moreover, in silica model is a useful tool for understanding and finding new markers for an IVF individualization.

PROSPERO

CRD42020197185.