Journal of Proteomics & Bioinformatics
Open Access

Abstract

Predictive Roles of Proteomic Profiles in Assisted Reproduction-An Update

Sajal Gupta, Rakesh Sharma, Jasmine Eliwa and Ashok Agarwal

The prevalence of infertility is 12-15% in sexually active couples. When, a subgroup analysis is done, 50% of infertility can be ascribed to male factor or a combination of male and female factor. With the growing trend of male factor infertility and the desire for infertile couples to reproduce, assisted reproductive technology provides a means to overcome these challenges. Several techniques exist depending on the extent of the infertility. For cases of severe oligospermia or even azoospermia, a combination of in vitro fertilization (IVF) and intracytoplasmic injection is used. There has been birth of more than 4 million babies worldwide using the assisted reproductive techniques. In the United States alone 1% of the total babies born each year are conceived through ART However, there are very low rates of successful implantation and pregnancy per transferred embryo in in vitro fertilization. According to literature reports 70% of transferred embryos fail to implant. Also, several ART clinics perform multiple embryo transfer, rather than a single embryo transfer, which exposes patients to several complications. Proteomics has the potential to aid in selection of the best embryo. In this review, we present an appraisal; of existing scientific literature regarding the proteomic profiles of the key players impacting ART outcomes. We elaborate on the potential proteomic biomarkers that are a key to establishing a non-invasive, reliable, reproducible, and specific means of assessing endometrial receptivity, embryonic viability, aneuploidy, and fertilizing potential of the sperm. These biomarkers include a variety of both structural and functional proteins. The application of these potential biomarkers in the future will help in enhancing the ART outcomes by offering a personalized treatment for patients based upon their individualized signature proteomics profiles.