P-537 Linking genetic variation to infertility and embryonic genomic instability. Lessons from a database of whole genomes from targeted populations: challenges, and future directions
Authors: Mantzouratou A , Wieland J , Buchan S , Serhl P , Sioban S 
Published: July 2024

Abstract

Study question
Can novel genomic analysis methods be developed to identify genetic variants that predispose to specific types of infertility and genomic instability in embryos?

Summary answer
Whole genome analysis and the creation of a genomic variation database of highly targeted populations yielded several genomic links to human infertility and genomic instability.

What is known already
Infertility is a phenotypic manifestation that originates from highly variable causes, like repeated miscarriage (RM), repeated implantation failure (RIF) or various male and female factors. Specific genetic variations can predispose carriers to distinct types of infertility however quantifiable genetic risks are difficult to be established clinically due to the high amount of variables that exist in any relevant infertility studies. In addition, the combination of the maternal and paternal genetics further complicates the interpretation of genomics results especially when genetic instability in embryos are studied. Several studies have indicated multi[le risk variants however few have managed to establish causal relationships.

Study design, size, duration
The causes of infertility are extremely variable, which presents a challenge in the design and analysis of genome sequencing studies that involve large populations of participants with similar characteristics. In this study a targeted approach highly selected populations allows more detailed examination of the whole genome of the participants and the different subgroups that exist among them. The participants were recruited using specific selection criteria and samples were collected over a period of 5 years.

Participants/materials, setting, methods
Couples presenting with infertility and went through preimplantation genetic testing for aneuploidy (PGT- A) were invited to participate. Selection criteria were applied: i) referred for PGT-A after &gt;3 assisted reproduction failed cycles, ii) Normal karyotypes, iii) Female age less than 37, iv) Embryonic instability in their subsequent PGT-A cycles in more than 40% of the produced embryos. After whole genome sequencing (WGS) and variant calling, a bespoke genomic SQL database was constructed for genomic analysis.

Main results and the role of chance
From 118 individuals that consented to participate 28 individuals with repeated implantation failure (RIF) and 8 individuals RIF/RM passed the selection criteria and their DNA was processed with WGS using a short read platform. In addition, WGS Validation was performed using genomes with known mutations. After the WGS quality control and validation. In total 50 genomes were processed and produced variant results. A novel MySQL database was successfully constructed and validated. Variant z scores were calculated for each participant and the significantly flagged variants were pulled and analysed and comparison with other bespoke and publicly available databases was performed. Ethnicity bias in novel variations detected and corrected. Several smaller cohorts were identified with similar genomic characteristics and accumulation of specific sets of polymorphisms, that were associated with certain types of infertility and preimplantation embryo abnormalities. Of particular interest were variants in synaptonemal complex genes associated with gamete failure, meiotic errors and instability in embryos. Structural variations were significant for male factor infertility. The WGS approach also revealed novel intronic and extragenic variants that would not be usually picked up by other methods like exome sequencing but can play a vital role in gene expression.

Limitations, reasons for caution
As with all genomic studies relating to infertility, association does not mean causation. Further functional analysis would be required to establish definitive causal pathways based on significant risk variants. In addition, although our study is highly targeted more genomic data can enhance to validation of these results.

Wider implications of the findings
This highly targeted study using a personalised approach to genome analysis combined with WGS can lead to protocols that determine the cumulative clinical risk for infertility, by revelling the accumulation of specific sets of polymorphisms, intronic and exonic, can be associated with certain types of infertility and preimplantation embryo abnormalities.

Trial registration number
not applicable