Gabriel Oh1, Sun-Chong Wang2, Mrinal Pal3, Zheng Fei Chen4, Tarang Khare3, Mamoru Tochigi5, Catherine Ng3, Yeqing A Yang6, Andrew Kwan3, Zachary A Kaminsky7, Jonathan Mill8, Cerisse Gunasinghe9, Jennifer L Tackett10, Irving I Gottesman11, Gonneke Willemsen12, Eco J C de Geus12, Jacqueline M Vink12, P Eline Slagboom13, Naomi R Wray14, Andrew C Heath15, Grant W Montgomery16, Gustavo Turecki17, Nicholas G Martin16, Dorret I Boomsma12, Peter McGuffin9, Rafal Kustra4, Art Petronis18. 1. Krembil Family Epigenetics Laboratory, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan. 2. Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan; Department of Public Health Sciences, Dalla Lana School of Public Health, Toronto, Ontario, Canada. 3. Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan. 4. Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. 5. Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan; Driskill Graduate Program in Life Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois. 6. Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan; Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore Maryland. 7. Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan; Medical Research Council Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King׳s College, London, United Kingdom. 8. Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan; Department of Psychology, University of Houston, Houston, Texas. 9. Department of Psychology, University of Houston, Houston, Texas; University of Exeter Medical School, Exeter University, Exeter, United Kingdom. 10. Departments of Psychology and Psychiatry, University of Minnesota, Minneapolis, Minnesota. 11. Department of Biological Psychology, VU University Amsterdam, Netherlands Twin Register. 12. Molecular Epidemiology, Leiden University Medical Center, The Netherlands. 13. Queensland Institute of Medical Research, Herston. 14. The Queensland Brain Institute, University of Queensland, St Lucia, Australia; Department of Psychiatry, Washington University in St Louis, St Louis, Missouri. 15. McGill Group for Suicide Studies, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada. 16. The Queensland Brain Institute, University of Queensland, St Lucia, Australia. 17. Department of Psychiatry, McGill University, Montreal, Quebec, Canada; National Institute for Health Research Biomedical Research Centre for Mental Health at South London and Maudsley National Health Service Foundation Trust, London. 18. Institute of Systems Biology and Bioinformatics, National Central University, Chungli, Taiwan. Electronic address: art.petronis@camh.ca.
Abstract
BACKGROUND: Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. METHODS: We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. RESULTS: In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. CONCLUSIONS: Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations.
BACKGROUND:Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. METHODS: We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. RESULTS: In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. CONCLUSIONS: Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations.
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