Abstract

STUDY QUESTIONWhich genes are confidently linked to human monogenic male infertility?SUMMARY ANSWEROur systematic literature search and clinical validity assessment reveals that a total of 78 genes are currently confidently linked to 92 human male infertility phenotypes.WHAT IS KNOWN ALREADYThe discovery of novel male infertility genes is rapidly accelerating with the availability of next-generating sequencing methods, but the quality of evidence for gene–disease relationships varies greatly. In order to improve genetic research, diagnostics and counseling, there is a need for an evidence-based overview of the currently known genes.STUDY DESIGN, SIZE, DURATIONWe performed a systematic literature search and evidence assessment for all publications in Pubmed until December 2018 covering genetic causes of male infertility and/or defective male genitourinary development.PARTICIPANTS/MATERIALS, SETTING, METHODSTwo independent reviewers conducted the literature search and included papers on the monogenic causes of human male infertility and excluded papers on genetic association or risk factors, karyotype anomalies and/or copy number variations affecting multiple genes. Next, the quality and the extent of all evidence supporting selected genes was weighed by a standardized scoring method and used to determine the clinical validity of each gene–disease relationship as expressed by the following six categories: no evidence, limited, moderate, strong, definitive or unable to classify.MAIN RESULTS AND THE ROLE OF CHANCEFrom a total of 23 526 records, we included 1337 publications about monogenic causes of male infertility leading to a list of 521 gene–disease relationships. The clinical validity of these gene–disease relationships varied widely and ranged from definitive (n = 38) to strong (n = 22), moderate (n = 32), limited (n = 93) or no evidence (n = 160). A total of 176 gene–disease relationships could not be classified because our scoring method was not suitable.LARGE SCALE DATANot applicable.LIMITATIONS, REASONS FOR CAUTIONOur literature search was limited to Pubmed.WIDER IMPLICATIONS OF THE FINDINGSThe comprehensive overview will aid researchers and clinicians in the field to establish gene lists for diagnostic screening using validated gene–disease criteria and help to identify gaps in our knowledge of male infertility. For future studies, the authors discuss the relevant and important international guidelines regarding research related to gene discovery and provide specific recommendations for the field of male infertility.STUDY FUNDING/COMPETING INTEREST(S)This work was supported by a VICI grant from The Netherlands Organization for Scientific Research (918-15-667 to J.A.V.), the Royal Society, and Wolfson Foundation (WM160091 to J.A.V.) as well as an investigator award in science from the Wellcome Trust (209451 to J.A.V.).PROSPERO REGISTRATION NUMBERNone.

Highlights

  • Infertility is defined as the inability to conceive within 1 year of unprotected sexual intercourse (Zegers-Hochschild et al, 2009)

  • MAIN RESULTS AND THE ROLE OF CHANCE: From a total of 23 526 records, we included 1337 publications about monogenic causes of male infertility leading to a list of 521 gene–disease relationships

  • We aimed to identify all publications covering the genetics of male infertility, including those underlying syndromes affecting the endocrine system, disorders of sex development and genitourinary anomalies

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Summary

Introduction

Infertility is defined as the inability to conceive within 1 year of unprotected sexual intercourse (Zegers-Hochschild et al, 2009). High-impact mutations in any of these genes will always remain at very low frequency in the population because of their impact on fitness This means that in order to find recurrently mutated genes and novel genes confidently linked to infertility one has to screen large cohorts of patients for pathogenic variants in large numbers of genes. This has been laborious and expensive for a long time due to limitations of traditional genetic assays such as Sanger sequencing. This has expedited sequencing of large gene panels, all coding genes (the exome) and even whole genomes (Payne et al, 2018)

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