title: Broad DNA methylation changes of spermatogenesis, inflammation and immune response-related genes in a subgroup of sperm samples for assisted reproduction.
abstract: Aberrant sperm DNA methylation patterns, mainly in imprinted genes, have been associated with male subfertility and oligospermia. Here, we performed a genome-wide methylation analysis in sperm samples representing a wide range of semen parameters. Sperm DNA samples of 38 males attending a fertility centre were analysed with Illumina HumanMethylation27 BeadChips, which quantify methylation of >27 000 CpG sites in cis-regulatory regions of almost 15 000 genes. In an unsupervised analysis of methylation of all analysed sites, the patient samples clustered into a major and a minor group. The major group clustered with samples from normozoospermic healthy volunteers and, thus, may more closely resemble the normal situation. When correlating the clusters with semen and clinical parameters, the sperm counts were significantly different between groups with the minor group exhibiting sperm counts in the low normal range. A linear model identified almost 3000 CpGs with significant methylation differences between groups. Functional analysis revealed a broad gain of methylation in spermatogenesis-related genes and a loss of methylation in inflammation- and immune response-related genes. Quantitative bisulfite pyrosequencing validated differential methylation in three of five significant candidate genes on the array. Collectively, we identified a subgroup of sperm samples for assisted reproduction with sperm counts in the low normal range and broad methylation changes (affecting approximately 10% of analysed CpG sites) in specific pathways, most importantly spermatogenesis-related genes. We propose that epigenetic analysis can supplement traditional semen parameters and has the potential to provide new insights into the aetiology of male subfertility.
authors.affiliation: Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany; Department of Bioinformatics, Julius Maximilians University, Würzburg, Germany.
authors.forename: B
authors.initials: B
authors.lastname: Schütte
authors.forename: N
authors.initials: N
authors.lastname: El Hajj
authors.forename: J
authors.initials: J
authors.lastname: Kuhtz
authors.forename: I
authors.initials: I
authors.lastname: Nanda
authors.forename: J
authors.initials: J
authors.lastname: Gromoll
authors.forename: T
authors.initials: T
authors.lastname: Hahn
authors.forename: M
authors.initials: M
authors.lastname: Dittrich
authors.forename: M
authors.initials: M
authors.lastname: Schorsch
authors.forename: T
authors.initials: T
authors.lastname: Müller
authors.forename: T
authors.initials: T
authors.lastname: Haaf
mesh_terms: D018899:CpG Islands / Q000502:physiology; D019175:DNA Methylation; D005298:Fertility / Q000235:genetics* / Q000276:immunology; D063990:Gene Ontology; D005802:Genes, MHC Class II; D006801:Humans; D007248:Infertility, Male / Q000235:genetics*; D007249:Inflammation / Q000235:genetics*; D008297:Male; D012098:Reproduction / Q000235:genetics; D013076:Sperm Count; D013091:Spermatogenesis / Q000235:genetics*
keywords: epigenetic markers; male infertility; methylation arrays; sperm DNA methylation