We present the first large-scale methylome-wide association studies (MWAS) for major depressive disorder (MDD) to identify sites of potential importance for MDD etiology. Using a sequencing-based approach that provides near-complete coverage of all 28 million common CpGs in the human genome, we assay methylation in MDD cases and controls from both blood (N = 1132) and postmortem brain tissues (N = 61 samples from Brodmann Area 10, BA10). The MWAS for blood identified several loci with P ranging from 1.91 × 10−8 to 4.39 × 10−8 and a resampling approach showed that the cumulative association was significant (P = 4.03 × 10−10) with the signal coming from the top 25,000 MWAS markers. Furthermore, a permutation-based analysis showed significant overlap (P = 5.4 × 10−3) between the MWAS findings in blood and brain (BA10). This overlap was significantly enriched for a number of features including being in eQTLs in blood and the frontal cortex, CpG islands and shores, and exons. The overlapping sites were also enriched for active chromatin states in brain including genic enhancers and active transcription start sites. Furthermore, three loci located in GABBR2, RUFY3, and in an intergenic region on chromosome 2 replicated with the same direction of effect in the second brain tissue (BA25, N = 60) from the same individuals and in two independent brain collections (BA10, N = 81 and 64). GABBR2 inhibits neuronal activity through G protein-coupled second-messenger systems and RUFY3 is implicated in the establishment of neuronal polarity and axon elongation. In conclusion, we identified and replicated methylated loci associated with MDD that are involved in biological functions of likely importance to MDD etiology.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Scientific Reports Open Access 01 November 2022
Translational Psychiatry Open Access 01 June 2022
Clinical Epigenetics Open Access 29 October 2021
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
Judd LL. The clinical course of unipolar major depressive disorders. Arch Gen Psychiatry. 1997;54:989–91.
Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJ. Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. Lancet. 2006;367:1747–57.
Kessler RC, Berglund P, Demler O, Jin R, Koretz D, Merikangas KR, et al. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA. 2003;289:3095–105.
Avenevoli S, Swendsen J, He JP, Burstein M, Merikangas KR. Major depression in the national comorbidity survey-adolescent supplement: prevalence, correlates, and treatment. J Am Acad Child Adolesc Psychiatry. 2015;54:37–44.e32.
Mueller TI, Leon AC, Keller MB, Solomon DA, Endicott J, Coryell W, et al. Recurrence after recovery from major depressive disorder during 15 years of observational follow-up. Am J Psychiatry. 1999;156:1000–6.
Depression and other common mental disorders: global health estimates. Geneva: World Health Organization; 2017.
World Health Organization. The global burden of disease: 2004 update. Geneva: World Health Organization; 2008.
Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet. 2016;48:624–33.
Hyde CL, Nagle MW, Tian C, Chen X, Paciga SA, Wendland JR, et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet. 2016;48:1031–6.
PGC MDDWGot. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. http://www.biorxiv.org/content/early/2017/07/24/1675772017.
Miller CA, Sweatt JD. Covalent modification of DNA regulates memory formation. Neuron. 2007;53:857–69.
Kaffman A, Meaney MJ. Neurodevelopmental sequelae of postnatal maternal care in rodents: clinical and research implications of molecular insights. J Child Psychol Psychiatry. 2007;48:224–44.
Szyf M, Weaver IC, Champagne FA, Diorio J, Meaney MJ. Maternal programming of steroid receptor expression and phenotype through DNA methylation in the rat. Front Neuroendocrinol. 2005;26:139–62.
Davies MN, Volta M, Pidsley R, Lunnon K, Dixit A, Lovestone S, et al. Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol. 2012;13:R43.
Aberg KA, Xie LY, McClay JL, Nerella S, Vunck S, Snider S, et al. Testing two models describing how methylome-wide studies in blood are informative for psychiatric conditions. Epigenomics. 2013;5:367–77.
Efstratiadis A. Parental imprinting of autosomal mammalian genes. Curr Opin Genet Dev. 1994;4:265–80.
Sutherland JE, Costa M. Epigenetics and the environment. Ann NY Acad Sci. 2003;983:151–60.
Kerkel K, Spadola A, Yuan E, Kosek J, Jiang L, Hod E, et al. Genomic surveys by methylation-sensitive SNP analysis identify sequence-dependent allele-specific DNA methylation. Nat Genet. 2008;40:904–8.
Chan RF, Shabalin AA, Xie LY, Adkins DE, Zhao M, Turecki G, et al. Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome. Nucleic Acids Res. 2017;45:e97.
Aberg KA, Chan RF, Shabalin AA, Zhao M, Turecki G, Staunstrup NH, et al. A MBD-seq protocol for large-scale methylome-wide studies with (very) low amounts of DNA. Epigenetics. 2017;12:743–50.
Wittchen HU. Reliability and validity studies of the WHO—Composite International Diagnostic Interview (CIDI): a critical review. J Psychiatr Res. 1994;28:57–84.
Rush AJ, Giles DE, Schlesser MA, Fulton CL, Weissenburger J, Burns C. The Inventory for Depressive Symptomatology (IDS): preliminary findings. Psychiatry Res. 1986;18:65–87.
Deep-Soboslay A, Iglesias B, Hyde TM, Bigelow LB, Imamovic V, Herman MM, et al. Evaluation of tissue collection for postmortem studies of bipolar disorder. Bipolar Disord. 2008;10:822–8.
Conner KR, Conwell Y, Duberstein PR. The validity of proxy-based data in suicide research: a study of patients 50 years of age and older who attempted suicide. II. Life events, social support and suicidal behavior. Acta Psychiatr Scand. 2001;104:452–7.
Kelly TM, Mann JJ. Validity of DSM-III-R diagnosis by psychological autopsy: a comparison with clinician ante-mortem diagnosis. Acta Psychiatr Scand. 1996;94:337–43.
Dumais A, Lesage AD, Alda M, Rouleau G, Dumont M, Chawky N, et al. Risk factors for suicide completion in major depression: a case-control study of impulsive and aggressive behaviors in men. Am J Psychiatry. 2005;162:2116–24.
Shabalin AA, Hattab MW, Clark SL, Chan RF, Kumar G, Aberg KA, et al. RaMWAS: fast methylome-wide association study pipeline for enrichment platforms. Bioinformatics. 2018;34:2283–5.
Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012;13:86.
Hattab MW, Shabalin AA, Clark SL, Zhao M, Kumar G, Chan RF, et al. Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies. Genome Biol. 2017;18:24.
Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33:1–22.
Simon N, Friedman J, Hastie T, Tibshirani R. Regularization paths for Cox’s proportional hazards model via coordinate descent. J Stat Softw. 2011;39:1–13.
Tibshirani R, Bien J, Friedman J, Hastie T, Simon N, Taylor J, et al. Strong rules for discarding predictors in lasso-type problems. J R Stat Soc Ser B Stat Methodol. 2012;74:245–66.
Hastie T, Tibshirani R, Friedman J. The elements of statistical learning: data mining, inference, and prediction.. New York: Springer Verlag; 2001.
Cabrera CP, Navarro P, Huffman JE, Wright AF, Hayward C, Campbell H, et al. Uncovering networks from genome-wide association studies via circular genomic permutation. G3 (Bethesda). 2012;2:1067–75.
Boomsma DI, Willemsen G, Sullivan PF, Heutnik P, Meijer P, Sondervan D, et al. Genome-wide association of major depression: description of samples for the GAIN major depressive disorder study: NTR and NESDA Biobank Projects. Eur J Hum Genet. 2008;16:335–42.
Penninx B, Beekman A, Smit J. The Netherlands Study of Depression and Anxiety (NESDA): rationales, objectives and methods. Int J Methods Psychiatr Res. 2008;17:121–40.
Sullivan P, de Geus E, Willemsen G, James MR, Smit JH, Zandbelt T, et al. Genomewide association for major depressive disorder: a possible role for the presynaptic protein piccolo. Mol Psychiatry. 2009;14:359–75.
van den Oord EJ, Bukszar J, Rudolf G, Nerella S, McClay JL, Xie LY, et al. Estimation of CpG coverage in whole methylome next-generation sequencing studies. BMC Bioinformatics. 2013;14:50.
Weissman MM, Klerman GL. Sex differences and the epidemiology of depression. Arch Gen Psychiatry. 1977;34:98–111.
Kessler RC, McGonagle KA, Swartz MS, Blazer DG, Nelson CB. Sex and depression in the National Comorbidity Survey: I. Lifetime prevalence, chronicity and recurrence. J Affect Disord. 1993;29:85–96.
Bebbington P. The origins of sex differences in depressive disorder: bridging the gap. Int Rev Psychiatry. 1996;8:295–332.
Bouma GJ, Hudson QJ, Washburn LL, Eicher EM. New candidate genes identified for controlling mouse gonadal sex determination and the early stages of granulosa and Sertoli cell differentiation. Biol Reprod. 2010;82:380–9.
Hammond GL. Plasma steroid-binding proteins: primary gatekeepers of steroid hormone action. J Endocrinol. 2016;230:R13–25.
Soares CN, Zitek B. Reproductive hormone sensitivity and risk for depression across the female life cycle: a continuum of vulnerability? J Psychiatry Neurosci. 2008;33:331–43.
Carrier N, Saland SK, Duclot F, He H, Mercer R, Kabbaj M. The anxiolytic and antidepressant-like effects of testosterone and estrogen in gonadectomized male rats. Biol Psychiatry. 2015;78:259–69.
McHenry J, Carrier N, Hull E, Kabbaj M. Sex differences in anxiety and depression: role of testosterone. Front Neuroendocrinol. 2014;35:42–57.
Gibbons AS, Brooks L, Scarr E, Dean B. AMPA receptor expression is increased post-mortem samples of the anterior cingulate from subjects with major depressive disorder. J Affect Disord. 2012;136:1232–7.
Kamburov A, Wierling C, Lehrach H, Herwig R. ConsensusPathDB—a database for integrating human functional interaction networks. Nucleic Acids Res. 2009;37(Database issue):D623–8.
Reynolds LM, Magid HS, Chi GC, Lohman K, Barr RG, Kaufman JD, et al. Secondhand tobacco smoke exposure associations with DNA methylation of the aryl hydrocarbon receptor repressor. Nicotine Tob Res. 2017;19:442–51.
Philibert R, Hollenbeck N, Andersen E, McElroy S, Wilson S, Vercande K, et al. Reversion of AHRR demethylation is a quantitative biomarker of smoking cessation. Front Psychiatry. 2016;7:55.
Edelmann E, Lessmann V, Brigadski T. Pre- and postsynaptic twists in BDNF secretion and action in synaptic plasticity. Neuropharmacology. 2014;76:610–27. Pt C
Park H, Poo MM. Neurotrophin regulation of neural circuit development and function. Nat Rev Neurosci. 2013;14:7–23.
Krishnan V, Nestler EJ. The molecular neurobiology of depression. Nature. 2008;455:894–902.
Vialou V, Feng J, Robison AJ, Nestler EJ. Epigenetic mechanisms of depression and antidepressant action. Annu Rev Pharmacol Toxicol. 2013;53:59–87.
Boulle F, van den Hove DL, Jakob SB, Rutten BP, Hamon M, van Os J, et al. Epigenetic regulation of the BDNF gene: implications for psychiatric disorders. Mol Psychiatry. 2012;17:584–96.
Ikegame T, Bundo M, Murata Y, Kasai K, Kato T, Iwamoto K. DNA methylation of the BDNF gene and its relevance to psychiatric disorders. J Hum Genet. 2013;58:434–8.
Converge Consortium. Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature. 2015;523:588–91.
Schizophrenia Psychiatric Genome-Wide Association Study Consortium, Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, et al. Genome-wide association study identifies five new schizophrenia loci. Nat Genet. 2011;43:969–76.
Pehrson AL, Sanchez C. Altered gamma-aminobutyric acid neurotransmission in major depressive disorder: a critical review of the supporting evidence and the influence of serotonergic antidepressants. Drug Des Dev Ther. 2015;9:603–24.
Fatemi SH, Folsom TD, Thuras PD. Deficits in GABA(B) receptor system in schizophrenia and mood disorders: a postmortem study. Schizophr Res. 2011;128:37–43.
Mori T, Wada T, Suzuki T, Kubota Y, Inagaki N. Singar1, a novel RUN domain-containing protein, suppresses formation of surplus axons for neuronal polarity. J Biol Chem. 2007;282:19884–93.
Honda A, Ito Y, Takahashi-Niki K, Matsushita N, Nozumi M, Tabata H, et al. Extracellular signals induce glycoprotein M6a clustering of lipid rafts and associated signaling molecules. J Neurosci. 2017;37:4046–64.
Wei Z, Sun M, Liu X, Zhang J, Jin Y. Rufy3, a protein specifically expressed in neurons, interacts with actin-bundling protein Fascin to control the growth of axons. J Neurochem. 2014;130:678–92.
Uddin M, Koenen KC, Aiello AE, Wildman DE, de los Santos R, Galea S. Epigenetic and inflammatory marker profiles associated with depression in a community-based epidemiologic sample. Psychol Med. 2011;41:997–1007.
Davies MN, Krause L, Bell JT, Gao F, Ward KJ, Wu H, et al. Hypermethylation in the ZBTB20 gene is associated with major depressive disorder. Genome Biol. 2014;15:R56.
Dempster EL, Wong CC, Lester KJ, Burrage J, Gregory AM, Mill J, et al. Genome-wide methylomic analysis of monozygotic twins discordant for adolescent depression. Biol Psychiatry. 2014;76:977–83.
Nagy C, Suderman M, Yang J, Szyf M, Mechawar N, Ernst C, et al. Astrocytic abnormalities and global DNA methylation patterns in depression and suicide. Mol Psychiatry. 2015;20:320–8.
Sabunciyan S, Aryee MJ, Irizarry RA, Rongione M, Webster MJ, Kaufman WE, et al. Genome-wide DNA methylation scan in major depressive disorder. PLoS ONE. 2012;7:e34451.
Murphy TM, Crawford B, Dempster EL, Hannon E, Burrage J, Turecki G, et al. Methylomic profiling of cortex samples from completed suicide cases implicates a role for PSORS1C3 in major depression and suicide. Transl Psychiatry. 2017;7:e989.
Haghighi F, Xin Y, Chanrion B, O’Donnell AH, Ge Y, Dwork AJ, et al. Increased DNA methylation in the suicide brain. Dialog Clin Neurosci. 2014;16:430–8.
Oh G, Wang SC, Pal M, Chen ZF, Khare T, Tochigi M, et al. DNA modification study of major depressive disorder: beyond locus-by-locus comparisons. Biol Psychiatry. 2015;77:246–55.
Philibert R, Hollenbeck N, Andersen E, Osborn T, Gerrard M, Gibbons FX, et al. A quantitative epigenetic approach for the assessment of cigarette consumption. Front Psychol. 2015;6:656.
Andersen AM, Dogan MV, Beach SR, Philibert RA. Current and future prospects for epigenetic biomarkers of substance use disorders. Genes (Basel). 2015;6:991–1022.
Zhang Y, Elgizouli M, Schottker B, Holleczek B, Nieters A, Brenner H. Smoking-associated DNA methylation markers predict lung cancer incidence. Clin Epigenet. 2016;8:127.
Baglietto L, Ponzi E, Haycock P, Hodge A, Bianca Assumma M, Jung CH, et al. DNA methylation changes measured in pre-diagnostic peripheral blood samples are associated with smoking and lung cancer risk. Int J Cancer. 2017;140:50–61.
The current methylation study was supported by grant R01MH099110 from the National Institute of Mental Health. Tissues were received from five brain banks, including the Victorian Brain Bank, supported by The Florey Institute of Neuroscience and Mental Health, The Alfred and Victorian Forensic Institute of Medicine and funded by Australia’s National Health & Medical Research Council and Parkinson’s Victoria; the Stanley Medical Research Institute; The Netherlands Brain Bank, Netherlands Institute of Neuroscience, Amsterdam; the Harvard Brain Tissue Resource Center; and The Douglas – Bell Canada Brain Bank, Douglas Institute Research Center, Canada. Funding for NESDA was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10-000-1002); the Center for Medical Systems Biology (CSMB, NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University’s Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, R01D0042157-01A, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO.
Conflict of interest
B.W.J.H.P. has received research funding (non-related) from Jansen Research and Boehringer Ingelheim. The remaining authors declare that they have no conflict of interest.
About this article
Cite this article
Aberg, K.A., Dean, B., Shabalin, A.A. et al. Methylome-wide association findings for major depressive disorder overlap in blood and brain and replicate in independent brain samples. Mol Psychiatry 25, 1344–1354 (2020). https://doi.org/10.1038/s41380-018-0247-6
This article is cited by
Translational Psychiatry (2022)
Scientific Reports (2022)
Clinical Epigenetics (2021)
Modulation of DNA Methylation and Gene Expression in Rodent Cortical Neuroplasticity Pathways Exerts Rapid Antidepressant-Like Effects
Molecular Neurobiology (2021)
Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
Molecular Psychiatry (2021)