Introduction: Herein we introduce the discovery of an epigenetic (DNA Methylation) biomarker that is predictive of sperm quality. Currently, the standard semen evaluation is the primary tool for the assessment of fertility potential. However, the semen analysis only provides a very superficial analysis of a man’s fertility potential. The optimization of the biomarker described here has potential to improve the current standard of care.
Methods: In phase 1 of this study, sperm DNA methylation patterns were analyzed from 122 men who were undergoing IVF treatment and 54 fertile controls samples. For the 122 men, we collected semen analysis data, embryo quality, and pregnancy outcomes. Outcomes were divided up into four categories: 1) fertile, 2) good embryos with pregnancy, 3) poor embryos with pregnancy, and 4) poor embryos with no pregnancy. 10,000 promoters were analyzed for differential methylation compared to a training set of fertile controls. A cutoff of normal vs. unhealthy differential methylation was determined using a testing set of fertile donors, with the unhealthy men having an aberrant methylation pattern. Men with “unhealthy” methylation were designated to be at High-Risk for poor sperm quality. Utilizing the cut-offs defined in the phase 1 study, a phase 2 study was conducted analyzing the sperm DNA methylation of 74 new men seeking infertility care compared with a new set of 60 fertile controls.
Results: For the phase 1 study there was a significant difference in the presence of the high-risk biomarker in fertile controls versus the men undergoing IVF (p=0.004). Prevalence of the high-risk biomarker increased with poorer outcomes as the high-risk biomarker was present in: 4% of the fertile donors, 38% of the good embryos with pregnancy, 38% of the poor embryos with pregnancy, and 44% of the poor embryos with no pregnancy. Of the men with a high-risk biomarker 94% of them had normal semen parameters. In the phase 2 study, 5% of the fertile donor sperm sample had a high-risk biomarker while 38% of the men seeking fertility care had the high-risk biomarker (p=3.80 E -0.6).
Conclusions: In this study of 310 total men with varying fertility outcomes, we have identified a sperm DNA methylation pattern that can classify a subset of infertile men that would be missed by the standard semen analysis. Here we observe this biomarker to be associated with poor fertility outcomes and we found that it has very low prevalence in known fertile population. These findings introduce a new method for detection of male infertility.
Source of Funding: This material is based upon work supported by the NSF under Grant 2034014
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