Addressing the pharmacogenomic variance associated with infertility outcomes in south Asians and recommendations for customization of assisted reproductive technology techniques.

Abstract

Female subfertility impacts approximately 15% of the world population. Those experiencing infertility rely on Assisted Reproductive Technologies (ART), which constitutes a variety of procedures including In Vitro Fertilization (IVF). The CDC estimates national ART success rates at 23.4% with numbers swiftly declining with age. IVF is financially and emotionally cumbersome on the patient, with prohibitive barriers for lower socio-economic groups. Despite scientific advances in the field, there are several unknowns that give rise to poor outcomes as standard fertility protocols are not customized based on genomic ethnic variation. This thesis aims to address the pharmacogenomic variance in infertility outcomes in the South Asian population and attempts to provide a blueprint for a customized approach to infertility treatment. Additionally, the merits of multifactorial customization and its potential to improve fertility outcomes have been explored to provide a holistic depiction of the south Asian health landscape, socio economic factors and their impact to the presence and treatment of infertility in this unique population. Literature searches were performed to identify 5 key genes involved in ovulatory dysfunction, recurrent pregnancy loss, unexplained factors and implantation (CDC infertility diagnosis categories). Analysis was conducted on genomic variation categorized by ancestry groups in the genomic aggregator database gnomAD, and cross referenced with other databases. Allele frequencies of pathogenic, predicted loss of function, and previously identified infertility associated gene variants were calculated and compared against the backdrop of general allele frequencies. Clinical trial representation, disease burdens and future projections, lifestyle factors, reported genomic variations, cultural and socio-economic factors were analyzed for South Asians. IVF protocols were assessed from three leading fertility clinics and assessed for gaps and risks in the South Asian context and recommendations for customization have been postulated. The 5 genes of interested assessed were LIF, IGF-1, HOXA10, HOXA11, and ESR1. Pathogenic, predicted loss of function, and previously identified infertility associated previously identified variants showed variation in allele frequencies in South Asian populations when compared to other ancestry groups. Additionally, disease prevalence statistics and key genomic variations associated with PCOS, diabetes, drug metabolism and their potential links to infertility were identified. Potential recommendations for custom IVF protocol enhancements for South Asian infertility patients have been put forth with the goal to improve ART outcomes and additional commentary has been provided to address population differentiators and factors of influence. This thesis sheds light on the existing “one size fits all” approach towards infertility and provides avenues for multifactorial customization of infertility treatment based on genomic ethnic variation. Additionally, it illuminates the need of ethnic inclusion in clinical trials and genomic databases to be able to remove health disparities globally. It also highlights the need for deep research in the identification of key genes, rare variants, proteins, and enzymes as therapeutic targets to improve fertility outcomes. Ultimately, a pharmacogenomic approach that couples emerging technologies such as artificial intelligence and machine learning with genomic research can result in predictive algorithms to solving infertility with precision for inter and intra population groups. This coupled with a holistic understanding of socio-economic, cultural constraints, developing and global healthcare challenges will lead to reduced costs of infertility treatments, improved success outcomes, mitigation of ART associated risks and demonstrate benefits to policy makers, clinicians, insurance companies, and patients.