Abstract
Despite advances in reproductive endocrinology, a significant fraction of infertile couples have no identifiable etiology for their reproductive problems. The Fertilome® test can aid reproductive endocrinologists in their evaluation of infertile couples by revealinggenetic factors associated with some of the most common female reproductive conditions. Natural language processing algorithms followed by manual curation were used to identify ∼4,758 studies reporting a statistical or functional association between 1,713 genetic regions and at least one female reproductive condition (RC). We then applied principles of the Clinical Genome Gene-Disease Clinical Validity Classification Framework to rank the evidence linking the genes with the RCs. The genetic variants related to 201 genes that were ranked as having strong evidence of association with at least one RC were statistically validated through meta-analyses of multiple case-control studies. These analyses identified 46 variants within 32 genes as having statistically significant odds ratios for increased risk of one or more of 6 RCs (endometriosis, polycystic ovary syndrome, primary ovarian insufficiency, recurrent pregnancy loss [RPL], idiopathic infertility, and recurrent implantation failure). These variants were included in the Fertilome test and categorized according to the effect size and allele frequency. The genes included in the Fertilome test function in just 10 biological processes: immune response regulation, hormone regulation, ovarian follicle development, blood circulation, cell proliferation/differentiation, DNA replication and repair, glucose homeostasis, tissue remodeling, steroidogenesis, and oxidative stress regulation.Understanding the biological pathways linked to these genetic markers may soon enable shifting clinical evaluations of infertility from descriptive diagnoses such as RPL to specific diagnoses based on molecular stratification. Having biological/molecular insight into a patient's RC should facilitate better clinical studies for assessing treatment options, bringing personalized medicine to the forefront of reproductive medicine.
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