TY - JOUR
T1 - DNA modification study of major depressive disorder
T2 - Beyond locus-by-locus comparisons
AU - Oh, Gabriel
AU - Wang, Sun Chong
AU - Pal, Mrinal
AU - Chen, Zheng Fei
AU - Khare, Tarang
AU - Tochigi, Mamoru
AU - Ng, Catherine
AU - Yang, Yeqing A.
AU - Kwan, Andrew
AU - Kaminsky, Zachary A.
AU - Mill, Jonathan
AU - Gunasinghe, Cerisse
AU - Tackett, Jennifer L.
AU - Gottesman, Irving I.
AU - Willemsen, Gonneke
AU - De Geus, Eco J.C.
AU - Vink, Jacqueline M.
AU - Slagboom, P. Eline
AU - Wray, Naomi R.
AU - Heath, Andrew C.
AU - Montgomery, Grant W.
AU - Turecki, Gustavo
AU - Martin, Nicholas G.
AU - Boomsma, Dorret I.
AU - McGuffin, Peter
AU - Kustra, Rafal
AU - Petronis, Art
N1 - Funding Information:
This research has been supported by the Canadian Institutes of Health Research (CIHR) (Grant 77689 ) and the US National Institutes of Health (Grants MH074127 and MH088413 ) to AP. AP is Tapscott Chair in Schizophrenia Studies at the University of Toronto and a senior fellow of the Ontario Mental Health Foundation. GO was supported by the CIHR Vanier Canada Graduate Scholarship and the CIHR Collaborative Program – Molecular Medicine Research Award. Collection of Queensland Institute of Medical Research samples was funded by grants from the National Institutes of Health ( AA07535 and AA07728 ) and the Australian National Health and Medical Research Council ( 241944 , 339462 , 389927 , 389875 , 389891 , 389892 , 389938 , 442915 , 442981 , 496675 , 496739 , 552485 , 552498 ). Data collection for The Netherlands twin samples was funded by The Netherlands Organization for Scientific Research (MagW/ZonMW Grants 904-61-090 , 985-10-002 , 904-61-193 , 480-04-004 , 400-05-717 , Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI–NL, 184.021.007 ), the VU University Institute for Health and Care Research and Neuroscience Campus Amsterdam, and the European Science Council (ERC-230374).
Publisher Copyright:
© 2015 Society of Biological Psychiatry.
PY - 2015/2/1
Y1 - 2015/2/1
N2 - 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.
AB - 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.
KW - DNA modification
KW - Epigenetic outliers
KW - Epigenetics
KW - Heteroscedasticity
KW - Major depressive disorder
KW - Molecular networks
UR - http://www.scopus.com/inward/record.url?scp=84928210305&partnerID=8YFLogxK
U2 - 10.1016/j.biopsych.2014.06.016
DO - 10.1016/j.biopsych.2014.06.016
M3 - Article
C2 - 25108803
AN - SCOPUS:84928210305
SN - 0006-3223
VL - 77
SP - 246
EP - 255
JO - Biological Psychiatry
JF - Biological Psychiatry
IS - 3
ER -