Kenneth I Aston1, Philip J Uren2, Timothy G Jenkins1, Alan Horsager3, Bradley R Cairns4, Andrew D Smith2, Douglas T Carrell5. 1. Department of Surgery, University of Utah Andrology and IVF Laboratories, University of Utah School of Medicine, Salt Lake City, Utah. 2. Molecular and Computational Biology, University of Southern California, Los Angeles, California. 3. Episona, Inc, Glendale, California. 4. Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah; Howard Hughes Medical Institute, Chevy Chase, Maryland. 5. Department of Surgery, University of Utah Andrology and IVF Laboratories, University of Utah School of Medicine, Salt Lake City, Utah; Department of Obstetrics and Gynecology and Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah. Electronic address: douglas.carrell@hsc.utah.edu.
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.
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 IVFpatients 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 IVFpatients 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 IVFpatient 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 IVFpatient 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.
Authors: Sanaa Choufani; Andrei L Turinsky; Nir Melamed; Ellen Greenblatt; Michael Brudno; Anick Bérard; William D Fraser; Rosanna Weksberg; Jacquetta Trasler; Patricia Monnier Journal: Hum Mol Genet Date: 2019-02-01 Impact factor: 6.150
Authors: Jacob Netherton; Rachel A Ogle; Louise Hetherington; Ana Izabel Silva Balbin Villaverde; Hubert Hondermarck; Mark A Baker Journal: Mol Cell Proteomics Date: 2019-12-17 Impact factor: 5.911
Authors: Louise Hetherington; Elena K Schneider; Caroline Scott; David DeKretser; Charles H Muller; Hubert Hondermarck; Tony Velkov; Mark A Baker Journal: Mol Cell Proteomics Date: 2016-10-21 Impact factor: 5.911
Authors: D Chan; S McGraw; K Klein; L M Wallock; C Konermann; C Plass; P Chan; B Robaire; R A Jacob; C M T Greenwood; J M Trasler Journal: Hum Reprod Date: 2016-12-18 Impact factor: 6.918
Authors: Darshan P Patel; Tim G Jenkins; Kenneth I Aston; Jingtao Guo; Alexander W Pastuszak; Heidi A Hanson; James M Hotaling Journal: Fertil Steril Date: 2020-02-20 Impact factor: 7.329