methylation array Archives - Episona
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Aberrant sperm DNA methylation predicts male fertility status and embryo quality
Dec 2015 | Fertility Sterility
Kenneth I. Aston, Philip J. Uren, Timothy G. Jenkins, Alan Horsager, Bradley R. Cairns, Andrew D. Smith, Douglas T. Carrell
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. 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. <!--more-->Genomewide sperm DNA methylation analysis was performed to measure methylation at >485,000 sites across the genome. A comparison was made of DNA methylation patterns of IVF patients vs. normozoospermic, fertile men. 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. 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.
Decreased fecundity and sperm DNA methylation patterns
Oct 2015 | Fertility Sterility
Timothy G. Jenkins, Kenneth I. Aston, Tyson D. Meyer, James M. Hotaling, Monis B. Shamsi, Erica B. Johnstone, Kyley J. Cox, Joseph B. Stanford, Christina A. Porucznik, Douglas T. Carrell
To evaluate the relationship between epigenetic patterns in sperm and fecundity. Twenty-seven semen samples from couples who conceived within 2 months of attempting a pregnancy and 29 semen samples from couples unable to achieve a pregnancy within 12 months. Genomewide assessment of differential sperm DNA methylation and standard semen analysis. <!--more-->We analyzed DNA methylation alterations associated with fecundity in 124 semen samples, and identified regions of interest in 27 semen samples from couples who conceived within 2 months of attempting a pregnancy and a total of 29 semen samples from couples who were unable to achieve a pregnancy within 12 months. No differences in sperm count, sperm morphology, or semen volume were observed between the patients achieving a pregnancy within 2 months of study time and those not obtaining a pregnancy within 12 months. However, using data from the human methylation 450k array analysis we did identify two genomic regions with statistically significantly decreased (false discovery rate <0.01) methylation and three genomic regions with statistically significantly increased methylation in the failure-to-conceive group. The only two sites where decreased methylation was associated with reduced fecundity are at closely related genes known to be expressed in sperm, HSPA1L and HSPA1B. Our data suggest that there are genomic loci where DNA methylation alterations are associated with decreased fecundity. We have thus identified candidate loci for future study to verify these results and investigate the causative or contributory relationship between altered sperm methylation and decreased fecundity.
Genome-wide sperm DNA methylation changes after 3 months of exercise training in humans
Apr 2015 - Epigenomics
Joshua Denham, Brendan J. O’Brien, Jack T. Harvey, Fadi J. Charchar
DNA methylation programs gene expression and is involved in numerous biological processes. Accumulating evidence supports transgenerational inheritance of DNA methylation changes in mammals via germ cells. Our aim was to determine the effect of exercise on sperm DNA methylation. <!--more-->Twenty-four men were recruited and assigned to an exercise intervention or control group. Clinical parameters were measured and sperm samples were donated by subjects before and after the 3-month time-period. Mature sperm global and genome-wide DNA methylation was assessed using an ELISA assay and the 450K BeadChip (Illumina). Global and genome-wide sperm DNA methylation was altered after 3 months of exercise training. DNA methylation changes occurred in genes related to numerous diseases such as schizophrenia and Parkinson's disease. Our study provides the first evidence showing exercise training reprograms the sperm methylome. Whether these DNA methylation changes are inherited to future generations warrants attention.
Aberrant DNA methylation patterns of spermatozoa in men with unexplained infertility
May 2015 - Hum Reprod
Rocío G. Urdinguio, Gustavo F. Bayón, Marija Dmitrijeva, Estela G. Toraño, Cristina Bravo, Mario F. Fraga, Lluís Bassas, Sara Larriba, Agustín F. Fernández
Aberrant DNA methylation of sperm has been associated with human male infertility in patients demonstrating either deficiencies in the process of spermatogenesis or low semen quality. This study compares 46 sperm samples obtained from 17 normospermic fertile men and 29 normospermic infertile patients. Illumina Infinium HD Human Methylation 450K arrays were used to identify genomic regions showing differences in sperm DNA methylation patterns between five fertile and seven infertile individuals. <!--more-->Additionally, global DNA methylation of sperm was measured using the Methylamp Global DNA Methylation Quantification Ultra kit (Epigentek) in 14 samples, and DNA methylation at several repetitive sequences (LINE-1, Alu Yb8, NBL2, D4Z4) measured by bisulfite pyrosequencing in 44 sperm samples. A sperm-specific DNA methylation pattern was obtained by comparing the sperm methylomes with the DNA methylomes of differentiated somatic cells using data obtained from methylation arrays (Illumina 450 K) of blood, neural and glial cells deposited in public databases. In this study we conduct, for the first time, a genome-wide study to identify alterations of sperm DNA methylation in individuals with unexplained infertility that may account for the differences in their biological fertility compared with fertile individuals. We have identified 2752 CpGs showing aberrant DNA methylation patterns, and more importantly, these differentially methylated CpGs were significantly associated with CpG sites which are specifically methylated in sperm when compared with somatic cells. We also found statistically significant (P < 0.001) associations between DNA hypomethylation and regions corresponding to those which, in somatic cells, are enriched in the repressive histone mark H3K9me3, and between DNA hypermethylation and regions enriched in H3K4me1 and CTCF, suggesting that the relationship between chromatin context and aberrant DNA methylation of sperm in infertile men could be locus-dependent. Finally, we also show that DNA methylation patterns, not only at specific loci but also at several repetitive sequences (LINE-1, Alu Yb8, NBL2, D4Z4), were lower in sperm than in somatic cells. Interestingly, sperm samples at Alu Yb8 repetitive sequences of infertile patients showed significantly lower DNA methylation levels than controls. Our results are descriptive and further studies would be needed to elucidate the functional effects of aberrant DNA methylation on male fertility. Overall, our data suggest that aberrant sperm DNA methylation might contribute to fertility impairment in couples with unexplained infertility and they provide a promising basis for future research.