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      DNA methylation in human sperm: a systematic review

      1 , 2 , 3 , 4
      Human Reproduction Update
      Oxford University Press (OUP)

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          Abstract

          BACKGROUND

          Studies in non-human mammals suggest that environmental factors can influence spermatozoal DNA methylation, and some research suggests that spermatozoal DNA methylation is also implicated in conditions such as subfertility and imprinting disorders in the offspring. Together with an increased availability of cost-effective methods of interrogating DNA methylation, this premise has led to an increasing number of studies investigating the DNA methylation landscape of human spermatozoa. However, how the human spermatozoal DNA methylome is influenced by environmental factors is still unclear, as is the role of human spermatozoal DNA methylation in subfertility and in influencing offspring health.

          OBJECTIVE AND RATIONALE

          The aim of this systematic review was to critically appraise the quality of the current body of literature on DNA methylation in human spermatozoa, summarize current knowledge and generate recommendations for future research.

          SEARCH METHODS

          A comprehensive literature search of the PubMed, Web of Science and Cochrane Library databases was conducted using the search terms ‘semen’ OR ‘sperm’ AND ‘DNA methylation’. Publications from 1 January 2003 to 2 March 2020 that studied human sperm and were written in English were included. Studies that used sperm DNA methylation to develop methodologies or forensically identify semen were excluded, as were reviews, commentaries, meta-analyses or editorial texts. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) criteria were used to objectively evaluate quality of evidence in each included publication.

          OUTCOMES

          The search identified 446 records, of which 135 were included in the systematic review. These 135 studies were divided into three groups according to area of research; 56 studies investigated the influence of spermatozoal DNA methylation on male fertility and abnormal semen parameters, 20 studies investigated spermatozoal DNA methylation in pregnancy outcomes including offspring health and 59 studies assessed the influence of environmental factors on spermatozoal DNA methylation. Findings from studies that scored as ‘high’ and ‘moderate’ quality of evidence according to GRADE criteria were summarized. We found that male subfertility and abnormal semen parameters, in particular oligozoospermia, appear to be associated with abnormal spermatozoal DNA methylation of imprinted regions. However, no specific DNA methylation signature of either subfertility or abnormal semen parameters has been convincingly replicated in genome-scale, unbiased analyses. Furthermore, although findings require independent replication, current evidence suggests that the spermatozoal DNA methylome is influenced by cigarette smoking, advanced age and environmental pollutants. Importantly however, from a clinical point of view, there is no convincing evidence that changes in spermatozoal DNA methylation influence pregnancy outcomes or offspring health.

          WIDER IMPLICATIONS

          Although it appears that the human sperm DNA methylome can be influenced by certain environmental and physiological traits, no findings have been robustly replicated between studies. We have generated a set of recommendations that would enhance the reliability and robustness of findings of future analyses of the human sperm methylome. Such studies will likely require multicentre collaborations to reach appropriate sample sizes, and should incorporate phenotype data in more complex statistical models.

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          Most cited references180

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          The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration

          Systematic reviews and meta-analyses are essential to summarise evidence relating to efficacy and safety of healthcare interventions accurately and reliably. The clarity and transparency of these reports, however, are not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (quality of reporting of meta-analysis) statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realising these issues, an international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and meta-analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this explanation and elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA statement, this document, and the associated website (www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.
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            DNA methylation age of human tissues and cell types

            Background It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. Conclusions I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.
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              Is Open Access

              Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling

              Background In recent years the Illumina HumanMethylation450 (HM450) BeadChip has provided a user-friendly platform to profile DNA methylation in human samples. However, HM450 lacked coverage of distal regulatory elements. Illumina have now released the MethylationEPIC (EPIC) BeadChip, with new content specifically designed to target these regions. We have used HM450 and whole-genome bisulphite sequencing (WGBS) to perform a critical evaluation of the new EPIC array platform. Results EPIC covers over 850,000 CpG sites, including >90 % of the CpGs from the HM450 and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58 % of FANTOM5 enhancers, only 7 % distal and 27 % proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and WGBS show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform. Finally, we provide an annotated list of probes whose signal could be affected by cross-hybridisation or underlying genetic variation. Conclusion The EPIC array is a significant improvement over the HM450 array, with increased genome coverage of regulatory regions and high reproducibility and reliability, providing a valuable tool for high-throughput human methylome analyses from diverse clinical samples. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1066-1) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                (View ORCID Profile)
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                Journal
                Human Reproduction Update
                Oxford University Press (OUP)
                1355-4786
                1460-2369
                November 2020
                November 01 2020
                August 13 2020
                November 2020
                November 01 2020
                August 13 2020
                : 26
                : 6
                : 841-873
                Affiliations
                [1 ]UCL EGA Institute for Women’s Health, London WC1E 6AU, UK
                [2 ]German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
                [3 ]UK Dementia Research Institute, Imperial College London, London W12 0NN, UK
                [4 ]Department of Brain Sciences, Imperial College London, London, UK
                Article
                10.1093/humupd/dmaa025
                32790874
                f52ae466-503f-4744-9895-67370ae95031
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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