Aberrant sperm DNA methylation predicts male fertility status and embryo quality

Abstract

Objective: To evaluate whether male fertility status and/or embryo quality during in vitro fertilization (IVF) therapy can be predicted based on genomewide sperm deoxyribonucleic acid (DNA) methylation patterns.

Design: Retrospective cohort study.

Setting: University-based fertility center.

Patient(s): Participants were 127 men undergoing IVF treatment (where any major female factor cause of infertility had been ruled out), and 54 normozoospermic, fertile men. The IVF patients were stratified into 2 groups: patients who had generally good embryogenesis and a positive pregnancy (n = 55), and patients with generally poor embryogenesis (n = 72; 42 positive and 30 negative pregnancies) after IVF.

Intervention(s): Genomewide sperm DNA methylation analysis was performed to measure methylation at >485,000 sites across the genome.

Main outcome measure(s): A comparison was made of DNA methylation patterns of IVF patients vs. normozoospermic, fertile men.

Result(s): Predictive models proved to be highly accurate in classifying male fertility status (fertile or infertile), with 82% sensitivity, and 99% positive predictive value. Hierarchic clustering identified clusters enriched for IVF patient samples and for poor-quality-embryo samples. Models built to identify samples within these groups, from neat samples, achieved positive predictive value ≥ 94% while identifying >one fifth of all IVF patient and poor-quality-embryo samples in each case. Using density gradient prepared samples, the same approach recovered 46% of poor-quality-embryo samples with no false positives.

Conclusion(s): Sperm DNA methylation patterns differ significantly and consistently for infertile vs. fertile, normozoospermic men. In addition, DNA methylation patterns may be predictive of embryo quality during IVF.

Keywords: DNA methylation; IVF outcome; Sperm DNA; embryo; genomewide; male infertility; microarray.