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      Male obesity effects on sperm and next-generation cord blood DNA methylation

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          Abstract

          The prevalence of metabolic disorders, in particular obesity has dramatically increased worldwide. Genetic variants explain only a minor part of the obesity epidemic induced by physical inactivity and over-nutrition. Epidemiological studies in humans and animal models indicate that epigenetic changes associated with adverse parental and/or intrauterine factors may contribute to the missing heritability of metabolic disorders. Possible adverse paternal effects are likely transmitted by sperm to the next-generation. To investigate this hypothesis, we have systematically analyzed the effects of male body mass index (BMI) on sperm epigenome and its association with next-generation fetal cord blood (FCB) DNA methylation. Methylation levels of maternally imprinted ( PEG1, PEG4, PEG5, and PEG10), paternally imprinted ( H19-IG DMR, IGF2-DMR0, and MEG3-IG DMR) regions, and obesity-related non-imprinted HIF3A gene were quantified by bisulphite pyrosequencing in sperm samples of 294 human donors undergoing in vitro fertilization or intracytoplasmic sperm injection, and in 113 FCBs of the resulting offspring. Multivariable regression analyses revealed that MEG3 intergenic differentially methylated region (IG DMR) showed positive correlation between sperm methylation and donor’s BMI. A gender-specific correlation between paternal BMI and FCB methylation was observed for MEG3-IG DMR, HIF3A, and IGF2-DMR0. The former two genes displayed same directional nominal association (as sperm) between paternal BMI and FCB methylation in male offspring. Hypomethylation of IGF2-DMR0 with increased paternal BMI was observed in FCBs from female offsprings. Our results suggest that male obesity is nominally associated with modification of sperm DNA methylome in humans, which may affect the epigenome of the next-generation. Nevertheless, it is important to note that none of the associated p-values survived multiple testing adjustments. Future work should test the effect of associated methylation aberrations in the offspring as DNA methylation was shown to control expression and/or imprint establishment across the studied genes.

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          Variability in the Heritability of Body Mass Index: A Systematic Review and Meta-Regression

          Cathy E Elks, Marcel den Hoed, Jing Hua Zhao … (2012)
          Evidence for a major role of genetic factors in the determination of body mass index (BMI) comes from studies of related individuals. Despite consistent evidence for a heritable component of BMI, estimates of BMI heritability vary widely between studies and the reasons for this remain unclear. While some variation is natural due to differences between populations and settings, study design factors may also explain some of the heterogeneity. We performed a systematic review that identified 88 independent estimates of BMI heritability from twin studies (total 140,525 twins) and 27 estimates from family studies (42,968 family members). BMI heritability estimates from twin studies ranged from 0.47 to 0.90 (5th/50th/95th centiles: 0.58/0.75/0.87) and were generally higher than those from family studies (range: 0.24–0.81; 5th/50th/95th centiles: 0.25/0.46/0.68). Meta-regression of the results from twin studies showed that BMI heritability estimates were 0.07 (P = 0.001) higher in children than in adults; estimates increased with mean age among childhood studies (+0.012/year, P = 0.002), but decreased with mean age in adult studies (−0.002/year, P = 0.002). Heritability estimates derived from AE twin models (which assume no contribution of shared environment) were 0.12 higher than those from ACE models (P < 0.001), whilst lower estimates were associated with self reported versus DNA-based determination of zygosity (−0.04, P = 0.02), and with self reported versus measured BMI (−0.05, P = 0.03). Although the observed differences in heritability according to aspects of study design are relatively small, together, the above factors explained 47% of the heterogeneity in estimates of BMI heritability from twin studies. In summary, while some variation in BMI heritability is expected due to population-level differences, study design factors explained nearly half the heterogeneity reported in twin studies. The genetic contribution to BMI appears to vary with age and may have a greater influence during childhood than adult life.
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            Timescales of genetic and epigenetic inheritance.

            Kevin Verstrepen, Oliver J. Rando (2007)
            According to classical evolutionary theory, phenotypic variation originates from random mutations that are independent of selective pressure. However, recent findings suggest that organisms have evolved mechanisms to influence the timing or genomic location of heritable variability. Hypervariable contingency loci and epigenetic switches increase the variability of specific phenotypes; error-prone DNA replicases produce bursts of variability in times of stress. Interestingly, these mechanisms seem to tune the variability of a given phenotype to match the variability of the acting selective pressure. Although these observations do not undermine Darwin's theory, they suggest that selection and variability are less independent than once thought.
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              Epigenetic regulation of the DLK1-MEG3 microRNA cluster in human type 2 diabetic islets.

              Vasumathi Kameswaran, Nuria C Bramswig, Lindsay McKenna … (2014)
              Type 2 diabetes mellitus (T2DM) is a complex disease characterized by the inability of the insulin-producing β cells in the endocrine pancreas to overcome insulin resistance in peripheral tissues. To determine if microRNAs are involved in the pathogenesis of human T2DM, we sequenced the small RNAs of human islets from diabetic and nondiabetic organ donors. We identified a cluster of microRNAs in an imprinted locus on human chromosome 14q32 that is highly and specifically expressed in human β cells and dramatically downregulated in islets from T2DM organ donors. The downregulation of this locus strongly correlates with hypermethylation of its promoter. Using HITS-CLIP for the essential RISC-component Argonaute, we identified disease-relevant targets of the chromosome 14q32 microRNAs, such as IAPP and TP53INP1, that cause increased β cell apoptosis upon overexpression in human islets. Our results support a role for microRNAs and their epigenetic control by DNA methylation in the pathogenesis of T2DM. Copyright © 2014 Elsevier Inc. All rights reserved.
              Article 0 comments Cited 133 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Ramya Potabattula: Role: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Marcus Dittrich: Role: Formal analysis
                Martin Schorsch: Role: Resources
                Thomas Hahn: Role: Resources
                Thomas Haaf: Role: ConceptualizationRole: Funding acquisitionRole: Writing – original draftRole: Writing – review & editing
                Nady El Hajj:
                ORCID: http://orcid.org/0000-0003-3420-8531
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Yvonne Böttcher: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 27 June 2019
                Publication date Collection: 2019
                Volume: 14
                Issue: 6
                Electronic Location Identifier: e0218615
                Affiliations
                [1 ] Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
                [2 ] Fertility Center; Wiesbaden, Germany
                [3 ] College of Health and Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
                University of Oslo, NORWAY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-3420-8531
                Article
                Publisher ID: PONE-D-19-00505
                DOI: 10.1371/journal.pone.0218615
                PMC ID: 6597061
                PubMed ID: 31246962
                SO-VID: d3f8b2b0-aae4-4d3e-8550-d0293f2926ff
                Copyright © © 2019 Potabattula et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 7 January 2019
                Date accepted : 5 June 2019
                Page count
                Figures: 1, Tables: 4, Pages: 13
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: EL 742/1-1
                Award Recipient :
                ORCID: http://orcid.org/0000-0003-3420-8531
                Funded by: funder-id http://dx.doi.org/10.13039/501100007601, Horizon 2020;
                Award ID: Eraofart
                Award Recipient :
                R.P. was supported by a fellowship of the German Excellence Initiative to the Graduate School of Life Sciences, University of Würzburg. This study was supported by the German Research Foundation (grant EL 742/1-1 to N.E.H.) and the European Union (ERAofART to T.Hf.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Biology and life sciences
                Subject: Cell biology
                Subject: Chromosome biology
                Subject: Chromatin
                Subject: Chromatin modification
                Subject: DNA methylation
                Subject: Biology and life sciences
                Subject: Genetics
                Subject: Epigenetics
                Subject: Chromatin
                Subject: Chromatin modification
                Subject: DNA methylation
                Subject: Biology and life sciences
                Subject: Genetics
                Subject: Gene expression
                Subject: Chromatin
                Subject: Chromatin modification
                Subject: DNA methylation
                Subject: Biology and life sciences
                Subject: Genetics
                Subject: DNA
                Subject: DNA modification
                Subject: DNA methylation
                Subject: Biology and life sciences
                Subject: Biochemistry
                Subject: Nucleic acids
                Subject: DNA
                Subject: DNA modification
                Subject: DNA methylation
                Subject: Biology and life sciences
                Subject: Genetics
                Subject: Epigenetics
                Subject: DNA modification
                Subject: DNA methylation
                Subject: Biology and life sciences
                Subject: Genetics
                Subject: Gene expression
                Subject: DNA modification
                Subject: DNA methylation
                Subject: Biology and Life Sciences
                Subject: Cell Biology
                Subject: Cellular Types
                Subject: Animal Cells
                Subject: Germ Cells
                Subject: Sperm
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Physiological Parameters
                Subject: Body Weight
                Subject: Body Mass Index
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Physiological Parameters
                Subject: Body Weight
                Subject: Body Mass Index
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Body Fluids
                Subject: Blood
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Body Fluids
                Subject: Blood
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Body Fluids
                Subject: Blood
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Body Fluids
                Subject: Blood
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Physiological Parameters
                Subject: Body Weight
                Subject: Obesity
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Physiological Parameters
                Subject: Body Weight
                Subject: Obesity
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Epigenetics
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Physiological Parameters
                Subject: Body Weight
                Subject: Obesity
                Subject: Childhood Obesity
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Physiological Parameters
                Subject: Body Weight
                Subject: Obesity
                Subject: Childhood Obesity
                Subject: Research and Analysis Methods
                Subject: Mathematical and Statistical Techniques
                Subject: Statistical Methods
                Subject: Regression Analysis
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Statistics
                Subject: Statistical Methods
                Subject: Regression Analysis
                Custom metadata
                Data Availability All relevant data are within the manuscript and its Supporting Information files.

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