Annika Wahl1, Silva Kasela2, Elena Carnero-Montoro3, Maarten van Iterson4, Jerko Štambuk5, Sapna Sharma1, Erik van den Akker6, Lucija Klaric7, Elisa Benedetti8, Genadij Razdorov5, Irena Trbojević-Akmačić5, Frano Vučković5, Ivo Ugrina9, Marian Beekman4, Joris Deelen10, Diana van Heemst11, Bastiaan T Heijmans4, Manfred Wuhrer12, Rosina Plomp12, Toma Keser13, Mirna Šimurina13, Tamara Pavić13, Ivan Gudelj5, Jasminka Krištić5, Harald Grallert14, Sonja Kunze1, Annette Peters15, Jordana T Bell3, Timothy D Spector3, Lili Milani2, P Eline Slagboom4, Gordan Lauc16, Christian Gieger17. 1. Research Unit Molecular Epidemiology, Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany. 2. Estonian Genome Center, University of Tartu, Tartu, Estonia. 3. Department of Twin Research and Genetic Epidemiology, King's College London, London, UK. 4. Department of Molecular Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands. 5. Genos Glycoscience Research Laboratory, Zagreb, Croatia. 6. Department of Molecular Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands; Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, The Netherlands. 7. Genos Glycoscience Research Laboratory, Zagreb, Croatia; Centre for Population Health Sciences, School of Molecular, Genetic and Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom. 8. Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany. 9. University of Zagreb, Faculty of Pharmacy and Biochemistry, Zagreb, Croatia; University of Split, Faculty of Science, Split, Croatia. 10. Department of Molecular Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands; Max Planck Institute for Biology of Ageing, Köln, Germany. 11. Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center (LUMC), Leiden, The Netherlands. 12. Center for Proteomics & Metabolomics, Leiden University Medical Center (LUMC), Leiden, The Netherlands. 13. University of Zagreb, Faculty of Pharmacy and Biochemistry, Zagreb, Croatia. 14. Research Unit Molecular Epidemiology, Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany. 15. Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany. 16. Genos Glycoscience Research Laboratory, Zagreb, Croatia; University of Zagreb, Faculty of Pharmacy and Biochemistry, Zagreb, Croatia. 17. Research Unit Molecular Epidemiology, Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology 2, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany. Electronic address: christian.gieger@helmholtz-muenchen.de.
Abstract
BACKGROUND: Glycosylation is one of the most common post-translation modifications with large influences on protein structure and function. The effector function of immunoglobulin G (IgG) alters between pro- and anti-inflammatory, based on its glycosylation. IgG glycan synthesis is highly complex and dynamic. METHODS: With the use of two different analytical methods for assessing IgG glycosylation, we aim to elucidate the link between DNA methylation and glycosylation of IgG by means of epigenome-wide association studies. In total, 3000 individuals from 4 cohorts were analyzed. RESULTS: The overlap of the results from the two glycan measurement panels yielded DNA methylation of 7 CpG-sites on 5 genomic locations to be associated with IgG glycosylation: cg25189904 (chr.1, GNG12); cg05951221, cg21566642 and cg01940273 (chr.2, ALPPL2); cg05575921 (chr.5, AHRR); cg06126421 (6p21.33); and cg03636183 (chr.19, F2RL3). Mediation analyses with respect to smoking revealed that the effect of smoking on IgG glycosylation may be at least partially mediated via DNA methylation levels at these 7 CpG-sites. CONCLUSION: Our results suggest the presence of an indirect link between DNA methylation and IgG glycosylation that may in part capture environmental exposures. GENERAL SIGNIFICANCE: An epigenome-wide analysis conducted in four population-based cohorts revealed an association between DNA methylation and IgG glycosylation patterns. Presumably, DNA methylation mediates the effect of smoking on IgG glycosylation.
BACKGROUND: Glycosylation is one of the most common post-translation modifications with large influences on protein structure and function. The effector function of immunoglobulin G (IgG) alters between pro- and anti-inflammatory, based on its glycosylation. IgG glycan synthesis is highly complex and dynamic. METHODS: With the use of two different analytical methods for assessing IgG glycosylation, we aim to elucidate the link between DNA methylation and glycosylation of IgG by means of epigenome-wide association studies. In total, 3000 individuals from 4 cohorts were analyzed. RESULTS: The overlap of the results from the two glycan measurement panels yielded DNA methylation of 7 CpG-sites on 5 genomic locations to be associated with IgG glycosylation: cg25189904 (chr.1, GNG12); cg05951221, cg21566642 and cg01940273 (chr.2, ALPPL2); cg05575921 (chr.5, AHRR); cg06126421 (6p21.33); and cg03636183 (chr.19, F2RL3). Mediation analyses with respect to smoking revealed that the effect of smoking on IgG glycosylation may be at least partially mediated via DNA methylation levels at these 7 CpG-sites. CONCLUSION: Our results suggest the presence of an indirect link between DNA methylation and IgG glycosylation that may in part capture environmental exposures. GENERAL SIGNIFICANCE: An epigenome-wide analysis conducted in four population-based cohorts revealed an association between DNA methylation and IgG glycosylation patterns. Presumably, DNA methylation mediates the effect of smoking on IgG glycosylation.
Authors: Cristina Menni; Ivan Gudelj; Erin Macdonald-Dunlop; Massimo Mangino; Jonas Zierer; Erim Bešić; Peter K Joshi; Irena Trbojević-Akmačić; Phil J Chowienczyk; Tim D Spector; James F Wilson; Gordan Lauc; Ana M Valdes Journal: Circ Res Date: 2018-03-13 Impact factor: 17.367