A systematic review and evidence assessment of monogenic gene-disease relationships in human female infertility and differences in sex development.

Background: As in other domains of medicine, high-throughput sequencing methods have led to the identification of an ever-increasing number of gene variants in the fields of both male and female infertility. The increasing number of recently identified genes allows an accurate diagnosis for previously idiopathic cases of female infertility and more appropriate patient care. However, robust evidence of the gene-disease relationships (GDR) allowing the proper translation to clinical application is still missing in many cases.

Objective and rationale: An evidence-based curation of currently identified genes involved in female infertility and differences in sex development (DSD) would significantly improve both diagnostic performance and genetic research. We therefore performed a systematic review to summarize current knowledge and assess the available GDR.

Search methods: PRISMA guidelines were applied to curate all available information from PubMed and Web of Science on genetics of human female infertility and DSD leading to infertility, from 1 January 1988 to 1 November 2021. The reviewed pathologies include non-syndromic as well as syndromic female infertility, and endocrine and reproductive system disorders. The evidence that an identified phenotype is caused by pathogenic variants in a specific gene was assessed according to a standardized scoring system. A final score (no evidence, limited, moderate, strong, or definitive) was assigned to every GDR.

Outcomes: A total of 45 271 publications were identified and screened for inclusion of which 1078 were selected for gene and variant extraction. We have identified 395 genes and validated 466 GDRs covering all reported monogenic causes of female infertility and DSD. Furthermore, we present a genetic diagnostic flowchart including 105 genes with at least moderate evidence for female infertility and suggest recommendations for future research. The study did not take into account associated genetic risk factor(s) or oligogenic/polygenic causes of female infertility.

Wider implications: We have comprehensively reviewed the existing research on the genetics of female infertility and DSD, which will enable the development of diagnostic panels using validated genes. Whole genome analysis is shifting from predominantly research to clinical application, increasing its diagnostic potential. These new diagnostic possibilities will not only decrease the number of idiopathic cases but will also render genetic counselling more effective for infertile patients and their families.