Personalized reproductive medicine will ultimately be realized with patient-tailored infertility treatments and fertility preservation planning. However the development of predictive genetic tests for women is hampered by the complex etiology of important fertility factors, such as the ovarian reserve. The ovarian reserve constitutes the capacity of ovaries to produce viable, fertilizable oocytes. Deficiencies in the ovarian reserve can lead to infertility, and an increased incidence of miscarriages, birth defects and premature ovarian failure. Thousands of genes are involved in mammalian reproduction, and infertility likely arises from deleterious combinations of multiple alleles, rather than single gene defects, making the identification of causative polymorphisms that much more challenging in large-scale human genetic studies. Thus, appropriate genetic models must be developed to identify genetic factors and their profiles that reflect reproductive traits and risks inherent to diverse populations. Our overarching hypothesis is that multiple genetic factors regulating oocyte development determine differences in the ovarian reserve among genetically diverse individuals and that defined genetic profiles can be used to predict the risk of ovarian reserve deficiencies and subsequent fertility issues in women. We propose two complimentary studies using ovarian phenotyping and quantitative trait loci mapping in genetically heterogeneous mice from the Collaborative Cross (CC) and Diversity Outbred (DO) programs. The CC, comprised of diverse inbred lines, is optimal for longitudinal studies of oocyte development; while the DO, comprised of many single genetically unique individuals, is ideal for high precision mapping of genetic variants regulating ovarian reserve.
Aim 1 will determine how genetic variation affects early oocyte development and contributes to differences in oocyte numbers and quality in mice with different genetic backgrounds. We will phenotype CC mice for reproductive traits including meiotic recombination, fetal and perinatal oocyte loss, primordial follicle formation and the size of the ovarian reserve. These experiments will define genetic profiles linked to specific deficiencies in oocyte development and generate a phenotyped collection of models for the development of new diagnostic tools and treatment methods. We will refine the list of potential genes and gene networks linked to ovarian deficiencies in Aim 2, where we will identify genetic variants underlying variation in ovarian reserve size using DO mice. We will perform quantitative trait loci mapping and analyze identified regions for candidate genes and non-coding elements regulating oocyte development.
This aim will deliver a list of potential genes, variants and pathways underlying low ovarian reserve as candidates for similar conditions in women. For women with idiopathic infertility, those postponing child bearing and pediatric cancer patients undergoing ovario-toxic treatments, genetic tests that can predict the capacity of the ovarian reserve may provide avenues to diagnosis and novel treatment discovery, and unprecedented insight and control over their lifelong fertility.

Public Health Relevance

Nearly 50% of infertility cases are due to genetic factors, yet genetic tests to predict the risk of infertility are lacking. Infertility is a complex genetic trait requiring the coordinated expression of thousands of genes, and is most likely caused by deleterious combinations of polymorphic alleles, rather than single gene defects. For the first time, we will use genetically diverse mouse populations to establish a model system reflecting the genetic heterogeneity of human population in order to identify genetic causes of female infertility and propel female reproductive health into the era of personalized medicine.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Research Project (R01)
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Cellular, Molecular and Integrative Reproduction Study Section (CMIR)
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Taymans, Susan
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Jackson Laboratory
Bar Harbor
United States
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