Downregulation of spermatogenesis-associated transcripts in the spermatozoa of idiopathic infertile men

Xinran Qi; Han Ji; Enrica Bianchi; Susan J Hall; Gabriella Avellino; William Berg; Priyanka Bearelly; Mark Sigman; Zhijin Wu; Daniel J Spade

doi:10.1111/andr.70060

Downregulation of spermatogenesis-associated transcripts in the spermatozoa of idiopathic infertile men

Andrology. 2025 May 10. doi: 10.1111/andr.70060. Online ahead of print.

Authors

Affiliations

¹ Department of Pathology and Laboratory Medicine, Brown University, Providence, Rhode Island, USA.
² Department of Biostatistics, Brown University, Providence, Rhode Island, USA.
³ Department of Surgery, Division of Urology, Brown University, Providence, Rhode Island, USA.

PMID: 40346865
DOI: 10.1111/andr.70060

Abstract

Background: Approximately half of male factor infertility cases are idiopathic, indicating a need for new methods to supplement male fertility assessment.

Objectives: The objective of this study was to identify differences in the sperm transcriptomes of men with different clinical fertility status. We hypothesized that sperm mRNA profiling could distinguish men presenting for fertility assessment from proven fertile men.

Materials and methods: We compared two groups of study participants: men who presented for infertility assessment (n = 53, "infertility"), and men without a history of infertility who had fathered a child and were presenting for vasectomy (n = 14, "proven fertile" control). Study participants provided a semen sample for semen analysis and sperm mRNA sequencing. Differentially abundant genes were identified, and a gene expression summary score was constructed to test the ability of RNA-seq data to differentiate between study populations.

Results: The semen parameter that best differentiated between study populations was motility (area under the ROC curve = 0.746). In RNA-seq analysis, 1885 total differentially abundant transcripts were identified (q < 0.05, fold difference ≥ 2), 1004 (53.3%) of which were downregulated in infertility study participants. The Gene Ontology term, spermatogenesis, was enriched, with 40 out of 44 differentially abundant genes downregulated in infertility study participants. A gene expression summary score consisting of 100 upregulated and 100 downregulated genes was able to differentiate between the two groups of study participants.

Discussion: Sperm mRNAs differed between proven fertile and infertility study men. Known fertility-associated genes, including PRM1 and PRM2, and potentially novel fertility markers, including HOOK1 and SPATA6, were downregulated in infertility study samples. Future studies should test these results for reproducibility and test whether novel biomarker candidates can provide mechanistic information about etiologies of idiopathic male infertility.

Conclusion: Our results support the hypothesis that sperm mRNA abundance differs by clinical fertility status.

Keywords: biomarkers; infertility; spermatozoa; transcriptomics.

Abstract

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