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Panminerva Medica 2019 March;61(1):76-81

DOI: 10.23736/S0031-0808.18.03496-1


language: English

Pharmacogenetic algorithm for individualized controlled ovarian stimulation in assisted reproductive technology cycles

Matheus ROQUE 1, 2 , Bianca BIANCO 3, Denise M. CHRISTOFOLINI 3, Emerson BARCHI CORDTS 3, Fabia VILARINO 3, Waldemar CARVALHO 3, Marcello VALLE 1, Marcos SAMPAIO 1, Selmo GEBER 1, 2, Sandro C. ESTEVES 4, Caio PARENTE BARBOSA 3

1 Center for Reproductive Medicine ORIGEN, Rio de Janeiro, Brazil; 2 Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; 3 Department of Collective Health, Faculty of Medicine of ABC, Human Reproduction and Genetic Center, Santo André, Brazil; 4 Division of Urology, Department of Surgery, Andrology and Human Reproduction Clinic ANDROFERT, University of Campinas (UNICAMP), Campinas, Brazil

Controlled ovarian stimulation (COS) is crucial for optimizing in-vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) success. Multiple factors influence the ovarian response to COS, making predictions about oocyte yields not so straightforward. As a result, the ovarian response may be poor or suboptimal, or even excessive, all of which have negative consequences for the affected patient. There is a group of patients that present with a suboptimal response to COS despite normal biomarkers of ovarian reserve, such as AFC and AMH. These patients have a lower number of retrieved oocytes than what was expected based on their ovarian reserve, thus showing the inadequacy of using only the traditional ovarian reserve biomarkers to predict the ovarian response. Suboptimal response to COS might be related to ovarian sensitivity to exogenous gonadotropins modulated by genetic factors. The understanding of the gene polymorphisms related to reproductive function can help to improve the clinical management of this patient population and to explain some of the individual patient variability in response to COS. The development of a pharmacogenetic approach concerning COS in the context of assisted reproduction seems attractive as it might help to understand the relationship between genetic variants and ovarian response to exogenous gonadotropins. The patient’s genetic profile could be used to select the most appropriate gonadotropin type, predict the optimal dosage for each drug, develop a cost-effective treatment plan, maximize the success rates, and lastly, decrease the time-to-pregnancy.

KEY WORDS: Pharmacogenetics - Algorithms - Ovulation induction - Polymorphism, genetic - Fertilization in vitro - Reproductive techniques

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