Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

DNA methylation and general psychopathology in childhood: an epigenome-wide meta-analysis from the PACE consortium

Molecular Psychiatry volume 28, pages 1128–1136 (2023)Cite this article

Subjects

Abstract

The general psychopathology factor (GPF) has been proposed as a way to capture variance shared between psychiatric symptoms. Despite a growing body of evidence showing both genetic and environmental influences on GPF, the biological mechanisms underlying these influences remain unclear. In the current study, we conducted epigenome-wide meta-analyses to identify both probe- and region-level associations of DNA methylation (DNAm) with school-age general psychopathology in six cohorts from the Pregnancy And Childhood Epigenetics (PACE) Consortium. DNAm was examined both at birth (cord blood; prospective analysis) and during school-age (peripheral whole blood; cross-sectional analysis) in total samples of N = 2178 and N = 2190, respectively. At school-age, we identified one probe (cg11945228) located in the Bromodomain-containing protein 2 gene (BRD2) that negatively associated with GPF (p = 8.58 × 10–8). We also identified a significant differentially methylated region (DMR) at school-age (p = 1.63 × 10–8), implicating the SHC Adaptor Protein 4 (SHC4) gene and the EP300-interacting inhibitor of differentiation 1 (EID1) gene that have been previously implicated in multiple types of psychiatric disorders in adulthood, including obsessive compulsive disorder, schizophrenia, and major depressive disorder. In contrast, no prospective associations were identified with DNAm at birth. Taken together, results of this study revealed some evidence of an association between DNAm at school-age and GPF. Future research with larger samples is needed to further assess DNAm variation associated with GPF.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Quantile-quantile plot of the meta-analytic associations of DNA methylation at birth and DNA methylation at school-age with general psychopathology.
Fig. 2: Manhattan plot of –log10 p-values versus CpG position (base pair and chromosome) showing meta-analytic associations of DNA methylation at birth and DNA methylation at school-age with general psychopathology.

Similar content being viewed by others

Data availability

Site-level meta-analytical results will be made publicly available (Supplementary data file) upon acceptance for publication. For access to cohort-level data, requests can be sent directly to individual studies.

Code availability

Analytical codes can be requested from authors.

References

  1. Angold A, Costello EJ, Erkanli A. Comorbidity. J Child Psychol Psychiatry. 1999;40:57–87.

    CAS  PubMed  Google Scholar 

  2. Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:617–27.

    PubMed  PubMed Central  Google Scholar 

  3. Cuffe SP, Visser SN, Holbrook JR, Danielson ML, Geryk LL, Wolraich ML, et al. ADHD and Psychiatric Comorbidity: Functional Outcomes in a School-Based Sample of Children. J Atten Disord. 2020;24:1345–54.

    PubMed  Google Scholar 

  4. Roy-Byrne PP, Stang P, Wittchen HU, Ustun B, Walters EE, Kessler RC. Lifetime panic-depression comorbidity in the National Comorbidity Survey. Association with symptoms, impairment, course and help-seeking. Br J Psychiatry. J Ment Sci. 2000;176:229–35.

    CAS  Google Scholar 

  5. Lahey BB, Rathouz PJ, Keenan K, Stepp SD, Loeber R, Hipwell AE. Criterion validity of the general factor of psychopathology in a prospective study of girls. J Child Psychol Psychiatry. 2015;56:415–22.

    PubMed  Google Scholar 

  6. Rijlaarsdam J, Cecil CAM, Buil JM, van Lier PAC, Barker ED. Exposure to Bullying and General Psychopathology: A Prospective, Longitudinal Study. Res Child Adolesc Psychopathol. 2021;49:727–36.

    PubMed  PubMed Central  Google Scholar 

  7. Neumann A, Pappa I, Lahey BB, Verhulst FC, Medina-Gomez C, Jaddoe VW, et al. Single Nucleotide Polymorphism Heritability of a General Psychopathology Factor in Children. J Am Acad Child Adolesc Psychiatry. 2016;55:1038–.e4.

    PubMed  Google Scholar 

  8. Caspi A, Moffitt TE. All for One and One for All: Mental Disorders in One Dimension. Am J Psychiatry. 2018;175:831–44.

    PubMed  PubMed Central  Google Scholar 

  9. Pettersson E, Lahey BB, Larsson H, Lichtenstein P. Criterion Validity and Utility of the General Factor of Psychopathology in Childhood: Predictive Associations With Independently Measured Severe Adverse Mental Health Outcomes in Adolescence. J Am Acad Child Adolesc Psychiatry. 2018;57:372–83.

    PubMed  Google Scholar 

  10. Sallis H, Szekely E, Neumann A, Jolicoeur-Martineau A, van IJzendoorn M, Hillegers M, et al. General psychopathology, internalising and externalising in children and functional outcomes in late adolescence. J Child Psychol Psychiatry. 2019;60:1183–90.

    PubMed  PubMed Central  Google Scholar 

  11. Brikell I, Larsson H, Lu Y, Pettersson E, Chen Q, Kuja-Halkola R, et al. The contribution of common genetic risk variants for ADHD to a general factor of childhood psychopathology. Mol Psychiatry. 2020;25:1809–21.

    CAS  PubMed  Google Scholar 

  12. Riglin L, Thapar AK, Leppert B, Martin J, Richards A, Anney R, et al. Using Genetics to Examine a General Liability to Childhood Psychopathology. Behav Genet. 2020;50:213–20.

    PubMed  Google Scholar 

  13. Brodbeck J, Fassbinder E, Schweiger U, Fehr A, Späth C, Klein JP. Differential associations between patterns of child maltreatment and comorbidity in adult depressed patients. J Affect Disord. 2018;230:34–41.

    PubMed  Google Scholar 

  14. Caspi A, Houts RM, Belsky DW, Goldman-Mellor SJ, Harrington H, Israel S, et al. The p Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders? Clin Psychol Sci J Assoc. Psychol Sci. 2014;2:119–37.

    Google Scholar 

  15. Campbell M, Jahanshad N, Mufford M, Choi KW, Lee P, Ramesar R, et al. Overlap in genetic risk for cross-disorder vulnerability to mental disorders and genetic risk for altered subcortical brain volumes. J Affect Disord. 2021;282:740–56.

    CAS  PubMed  Google Scholar 

  16. Cross-Disorder Group of the Psychiatric Genomics Consortium. Electronic address: plee0@mgh.harvard.edu, Cross-Disorder Group of the Psychiatric Genomics Consortium. Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders. Cell. 2019;179:1469–.e11.

    PubMed Central  Google Scholar 

  17. Teschendorff AE, Relton CL. Statistical and integrative system-level analysis of DNA methylation data. Nat Rev Genet. 2018;19:129–47.

    CAS  PubMed  Google Scholar 

  18. Meaney MJ. Epigenetics and the biological definition of gene x environment interactions. Child Dev. 2010;81:41–79.

    PubMed  Google Scholar 

  19. Cecil CAM, Walton E, Jaffee SR, O’Connor T, Maughan B, Relton CL, et al. Neonatal DNA methylation and early-onset conduct problems: A genome-wide, prospective study. Dev Psychopathol. 2018;30:383–97.

    PubMed  Google Scholar 

  20. Neumann A, Walton E, Alemany S, Cecil C, González JR, Jima DD, et al. Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysis. Transl Psychiatry. 2020;10:398.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Hannon E, Dempster E, Viana J, Burrage J, Smith AR, Macdonald R, et al. An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation. Genome Biol. 2016;17:176.

    PubMed  PubMed Central  Google Scholar 

  22. Zhu Y, Strachan E, Fowler E, Bacus T, Roy-Byrne P, Zhao J. Genome-wide profiling of DNA methylome and transcriptome in peripheral blood monocytes for major depression: A Monozygotic Discordant Twin Study. Transl Psychiatry. 2019;9:215.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Rijlaarsdam J, Barker ED, Caserini C, Koopman-Verhoeff ME, Mulder RH, Felix JF, et al. Genome-wide DNA methylation patterns associated with general psychopathology in children. J Psychiatr Res. 2021;140:214–20.

    PubMed  PubMed Central  Google Scholar 

  24. Zhou W, Laird PW, Shen H. Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes. Nucl Acids Res. 2017;45:e22.

    PubMed  Google Scholar 

  25. Solomon O, MacIsaac J, Quach H, Tindula G, Kobor MS, Huen K, et al. Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children. Epigenetics. 2018;13:655–64.

    PubMed  PubMed Central  Google Scholar 

  26. Patalay P, Fonagy P, Deighton J, Belsky J, Vostanis P, Wolpert M. A general psychopathology factor in early adolescence. Br J Psychiatry J Ment Sci. 2015;207:15–22.

    Google Scholar 

  27. Gervin K, Salas LA, Bakulski KM, van Zelm MC, Koestler DC, Wiencke JK, et al. Systematic evaluation and validation of reference and library selection methods for deconvolution of cord blood DNA methylation data. Clin Epigenetics. 2019;11:125.

    PubMed  PubMed Central  Google Scholar 

  28. 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 Bioinforma. 2012;13:86.

    Google Scholar 

  29. Salas LA, Koestler DC, Butler RA, Hansen HM, Wiencke JK, Kelsey KT, et al. An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray. Genome Biol. 2018;19:64.

    PubMed  PubMed Central  Google Scholar 

  30. Rosseel Y. lavaan: An R Package for Structural Equation Modeling. J Stat Softw. 2012;48:1–36.

    Google Scholar 

  31. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinforma Oxf Engl. 2010;26:2190–1.

    CAS  Google Scholar 

  32. Min JL, Hemani G, Davey Smith G, Relton C, Suderman M. Meffil: efficient normalization and analysis of very large DNA methylation datasets. Bioinforma Oxf Engl. 2018;34:3983–9.

    CAS  Google Scholar 

  33. Suderman M, Staley JR, French R, Arathimos R, Simpkin A, Tilling K. dmrff: identifying differentially methylated regions efficiently with power and control. bioRxiv. 2018. https://www.biorxiv.org/content/biorxiv/early/2018/12/31/508556.full.pdf:508556.

  34. Battram T, Yousefi P, Crawford G, Prince C, Sheikhali Babaei M, Sharp G, et al. The EWAS Catalog: a database of epigenome-wide association studies. Wellcome Open Res. 2022;7:41.

    PubMed  PubMed Central  Google Scholar 

  35. Li M, Zou D, Li Z, Gao R, Sang J, Zhang Y, et al. EWAS Atlas: a curated knowledgebase of epigenome-wide association studies. Nucleic Acids Res. 2019;47:D983–D988.

    CAS  PubMed  Google Scholar 

  36. Hannon E, Knox O, Sugden K, Burrage J, Wong CCY, Belsky DW, et al. Characterizing genetic and environmental influences on variable DNA methylation using monozygotic and dizygotic twins. PLoS Genet. 2018;14:e1007544.

    PubMed  PubMed Central  Google Scholar 

  37. Hannon E, Lunnon K, Schalkwyk L, Mill J. Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes. Epigenetics 2015;10:1024–32.

    PubMed  PubMed Central  Google Scholar 

  38. Edgar RD, Jones MJ, Meaney MJ, Turecki G, Kobor MS. BECon: a tool for interpreting DNA methylation findings from blood in the context of brain. Transl Psychiatry. 2017;7:e1187.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Braun P, Han S, Nagahama Y, Gaul L, Heinzman J, Hing B, et al. 28 - IMAGE-CpG: DEVELOPMENT OF A WEB-BASED SEARCH TOOL FOR GENOME-WIDE DNA METHYLATION CORRELATION BETWEEN LIVE HUMAN BRAIN AND PERIPHERAL TISSUES WITHIN INDIVIDUALS. Eur Neuropsychopharmacol. 2019;29:S796.

    Google Scholar 

  40. Phipson B, Maksimovic J, Oshlack A. missMethyl: an R package for analyzing data from Illumina’s HumanMethylation450 platform. Bioinforma Oxf Engl. 2016;32:286–8.

    CAS  Google Scholar 

  41. isglobal-brge/EASIER: EwAS: quality control, meta-analysIs and EnRichment version 0.1.2.8 from GitHub. https://rdrr.io/github/isglobal-brge/EASIER/. Accessed May 2022.

  42. Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, Gentleman R, et al. Software for computing and annotating genomic ranges. PLoS Comput Biol. 2013;9:e1003118.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.

    PubMed Central  Google Scholar 

  44. Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, et al. Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. Nat Genet. 2018;50:920–7.

    CAS  PubMed  Google Scholar 

  45. Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat Genet. 2019;51:63–75.

    CAS  PubMed  Google Scholar 

  46. Levey DF, Gelernter J, Polimanti R, Zhou H, Cheng Z, Aslan M, et al. Reproducible Genetic Risk Loci for Anxiety: Results From ∼200,000 Participants in the Million Veteran Program. Am J Psychiatry. 2020;177:223–32.

    PubMed  PubMed Central  Google Scholar 

  47. Aragam N, Wang K-S, Pan Y. Genome-wide association analysis of gender differences in major depressive disorder in the Netherlands NESDA and NTR population-based samples. J Affect Disord. 2011;133:516–21.

    PubMed  Google Scholar 

  48. Howard DM, Hall LS, Hafferty JD, Zeng Y, Adams MJ, Clarke T-K, et al. Genome-wide haplotype-based association analysis of major depressive disorder in Generation Scotland and UK Biobank. Transl Psychiatry. 2017;7:1263.

    PubMed  PubMed Central  Google Scholar 

  49. Budde M, Friedrichs S, Alliey-Rodriguez N, Ament S, Badner JA, Berrettini WH, et al. Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder. Eur Neuropsychopharmacol J Eur Coll Neuropsychopharmacol. 2019;29:156–70.

    CAS  Google Scholar 

  50. Blokland GAM, Grove J, Chen C-Y, Cotsapas C, Tobet S, Handa R, et al. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders. Biol Psychiatry. 2022;91:102–17.

    CAS  PubMed  Google Scholar 

  51. Boraska V, Davis OSP, Cherkas LF, Helder SG, Harris J, Krug I, et al. Genome-wide association analysis of eating disorder-related symptoms, behaviors, and personality traits. Am J Med Genet Part B Neuropsychiatr Genet Publ Int Soc Psychiatr Genet. 2012;159B:803–11.

    Google Scholar 

  52. Goes FS, McGrath J, Avramopoulos D, Wolyniec P, Pirooznia M, Ruczinski I, et al. Genome-wide association study of schizophrenia in Ashkenazi Jews. Am J Med Genet Part B Neuropsychiatr Genet Publ Int Soc Psychiatr Genet. 2015;168:649–59.

    CAS  Google Scholar 

  53. Wang N, Wu R, Tang D, Kang R. The BET family in immunity and disease. Signal Transduct Target Ther. 2021;6:23.

    PubMed  PubMed Central  Google Scholar 

  54. Gyuris A, Donovan DJ, Seymour KA, Lovasco LA, Smilowitz NR, Halperin ALP, et al. The chromatin-targeting protein Brd2 is required for neural tube closure and embryogenesis. Biochim Biophys Acta. 2009;1789:413–21.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Garcia-Gutierrez P, Juarez-Vicente F, Wolgemuth DJ, Garcia-Dominguez M. Pleiotrophin antagonizes Brd2 during neuronal differentiation. J Cell Sci. 2014;127:2554–64.

    CAS  PubMed  PubMed Central  Google Scholar 

  56. DeMars KM, Yang C, Candelario-Jalil E. Neuroprotective effects of targeting BET proteins for degradation with dBET1 in aged mice subjected to ischemic stroke. Neurochem Int. 2019;127:94–102.

    CAS  PubMed  Google Scholar 

  57. Pathak S, Miller J, Morris EC, Stewart WCL, Greenberg DA. DNA methylation of the BRD2 promoter is associated with juvenile myoclonic epilepsy in Caucasians. Epilepsia. 2018;59:1011–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Wockner LF, Noble EP, Lawford BR, Young RM, Morris CP, Whitehall VLJ, et al. Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients. Transl Psychiatry. 2014;4:e339.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. McKinney B, Ding Y, Lewis DA, Sweet RA. DNA methylation as a putative mechanism for reduced dendritic spine density in the superior temporal gyrus of subjects with schizophrenia. Transl Psychiatry. 2017;7:e1032.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Skariah G, Seimetz J, Norsworthy M, Lannom MC, Kenny PJ, Elrakhawy M, et al. Mov10 suppresses retroelements and regulates neuronal development and function in the developing brain. BMC Biol. 2017;15:54.

    PubMed  PubMed Central  Google Scholar 

  61. Vissers LELM, Gilissen C, Veltman JA. Genetic studies in intellectual disability and related disorders. Nat Rev Genet. 2016;17:9–18.

    CAS  PubMed  Google Scholar 

  62. Hanson E, Bernier R, Porche K, Jackson FI, Goin-Kochel RP, Snyder LG, et al. The cognitive and behavioral phenotype of the 16p11.2 deletion in a clinically ascertained population. Biol Psychiatry. 2015;77:785–93.

    CAS  PubMed  Google Scholar 

  63. Zufferey F, Sherr EH, Beckmann ND, Hanson E, Maillard AM, Hippolyte L, et al. A 600 kb deletion syndrome at 16p11.2 leads to energy imbalance and neuropsychiatric disorders. J Med Genet. 2012;49:660–8.

    CAS  PubMed  Google Scholar 

  64. Weiss LA, Shen Y, Korn JM, Arking DE, Miller DT, Fossdal R, et al. Association between microdeletion and microduplication at 16p11.2 and autism. N. Engl J Med. 2008;358:667–75.

    CAS  PubMed  Google Scholar 

  65. Chang H, Li L, Li M, Xiao X. Rare and common variants at 16p11.2 are associated with schizophrenia. Schizophr Res. 2017;184:105–8.

    PubMed  Google Scholar 

  66. You Y, Li W, Gong Y, Yin B, Qiang B, Yuan J, et al. ShcD interacts with TrkB via its PTB and SH2 domains and regulates BDNF-induced MAPK activation. BMB Rep. 2010;43:485–90.

    CAS  PubMed  Google Scholar 

  67. Liu R, Lei JX, Luo C, Lan X, Chi L, Deng P, et al. Increased EID1 nuclear translocation impairs synaptic plasticity and memory function associated with pathogenesis of Alzheimer’s disease. Neurobiol Dis. 2012;45:902–12.

    CAS  PubMed  Google Scholar 

  68. Sullivan PF, de Geus EJC, Willemsen G, James MR, Smit JH, Zandbelt T, et al. Genome-wide association for major depressive disorder: a possible role for the presynaptic protein piccolo. Mol Psychiatry. 2009;14:359–75.

    CAS  PubMed  Google Scholar 

  69. Mulder RH, Neumann A, Cecil CAM, Walton E, Houtepen LC, Simpkin AJ, et al. Epigenome-wide change and variation in DNA methylation in childhood: trajectories from birth to late adolescence. Hum Mol Genet. 2021;30:119–34.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Singham T, Viding E, Schoeler T, Arseneault L, Ronald A, Cecil CM, et al. Concurrent and Longitudinal Contribution of Exposure to Bullying in Childhood to Mental Health: The Role of Vulnerability and Resilience. JAMA Psychiatry. 2017;74:1112–9.

    PubMed  PubMed Central  Google Scholar 

  71. Bale TL, Epperson CN. Sex as a Biological Variable: Who, What, When, Why, and How. Neuropsychopharmacol Publ Am Coll Neuropsychopharmacol. 2017;42:386–96.

    CAS  Google Scholar 

Download references

Author information

Author notes

  1. These authors contributed equally: Jolien Rijlaarsdam, Marta Cosin-Tomas, Laura Schellhas.

  2. These authors jointly supervised this work: Doretta Caramaschi, Silvia Alemany, Charlotte A. M. Cecil.

Authors and Affiliations

  1. Department of Child and Adolescent Psychiatry/ Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands

    Jolien Rijlaarsdam & Charlotte A. M. Cecil

  2. ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain

    Marta Cosin-Tomas, Jordi Sunyer & Silvia Alemany

  3. Universitat Pompeu Fabra, Barcelona, Spain

    Marta Cosin-Tomas & Jordi Sunyer

  4. Centro de investigación biomédica en red en epidemiología y salud pública (ciberesp), Madrid, Spain

    Marta Cosin-Tomas & Jordi Sunyer

  5. School of Psychological Science, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK

    Laura Schellhas

  6. Institute for Sex Research, Sexual Medicine and Forensic Psychiatry, University Medical Center Hamburg, Eppendorf, Germany

    Laura Schellhas

  7. Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    Sarina Abrishamcar & Anke Hüls

  8. Department of Psychology & Logopedics, University of Helsinki, Helsinki, Finland

    Anni Malmberg, Kati Heinonen, Katri Räikkönen & Jari Lahti

  9. VIB Center for Molecular Neurology, Antwerp, Belgium

    Alexander Neumann

  10. The Generation R Study Group, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands

    Janine F. Felix

  11. Department of Pediatrics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands

    Janine F. Felix

  12. Division of Climate and Environmental Health, Norwegian Institute of Public Health (NIPH), Oslo, Norway

    Kristine B. Gutzkow

  13. Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania

    Regina Grazuleviciene

  14. Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK

    John Wright

  15. Department of Social Medicine, University of Crete, Crete, Greece

    Mariza Kampouri

  16. Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, University of Cape Town, Cape Town, South Africa

    Heather J. Zar

  17. South African Medical Research Council (SAMRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa

    Heather J. Zar

  18. Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa

    Dan J. Stein

  19. South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Neuroscience Institute, University of Cape Town, Cape Town, South Africa

    Dan J. Stein

  20. Psychology/ Welfare Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland

    Kati Heinonen

  21. Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    Anke Hüls

  22. Medical Research Council Integrative Epidemiology Unit, Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK

    Doretta Caramaschi

  23. Department of Psychology, , University of Exeter, Exeter, UK

    Doretta Caramaschi

  24. Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain

    Silvia Alemany

  25. Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain

    Silvia Alemany

  26. Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands

    Charlotte A. M. Cecil

  27. Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands

    Charlotte A. M. Cecil

Authors
  1. Jolien Rijlaarsdam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marta Cosin-Tomas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Laura Schellhas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sarina Abrishamcar
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Anni Malmberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alexander Neumann
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Janine F. Felix
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jordi Sunyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Kristine B. Gutzkow
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Regina Grazuleviciene
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. John Wright
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Mariza Kampouri
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Heather J. Zar
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Dan J. Stein
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Kati Heinonen
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Katri Räikkönen
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Jari Lahti
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Anke Hüls
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Doretta Caramaschi
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Silvia Alemany
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Charlotte A. M. Cecil
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JR: analysis plan and study design, Generation R analysis, quality control of data and meta-analyses, interpretation of results, manuscript drafting; MCT: Helix and INMA analyses, quality control of data, shadow meta-analysis, functional and genomic enrichment analyses, results interpretation, manuscript drafting, revision; LS: contributed to analysis plan and study design, ALSPAC analysis, interpretation of results, and manuscript review; SaA: DCHS analysis, and manuscript review; AM: GLAKU analysis and manuscript review; AN: Generation R coordination, manuscript review; JF: study design, Generation R coordination, critical revision of the manuscript; JS: INMA coordination, provided funding, manuscript review; KBG: MoBa Helix funding, MoBa coordination; RG: KANC-Helix funding, KANC coordination; JW: BiB-Helix funding, BiB coordination; MK: Rhea-Helix data acquisition; HJZ: DCHS coordination, and manuscript review; DJS: DCHS coordination, and manuscript review; KH: GLAKU coordination, manuscript review; KR: GLAKU coordination, manuscript review; JL: GLAKU coordination, manuscript review; AH: DCHS analysis, and manuscript review; DC: contributed to analysis plan and review of drafts and manuscript; SiA: analysis plan and study design, INMA analysis, manuscript review; CC: analysis plan and study design, Generation R coordination, funding, manuscript drafting and review.

Corresponding authors

Correspondence to Marta Cosin-Tomas or Charlotte A. M. Cecil.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

All studies acquired approval from local ethics committees and informed consent was obtained for all participants. Full details are listed in the methods supplement.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rijlaarsdam, J., Cosin-Tomas, M., Schellhas, L. et al. DNA methylation and general psychopathology in childhood: an epigenome-wide meta-analysis from the PACE consortium. Mol Psychiatry 28, 1128–1136 (2023). https://doi.org/10.1038/s41380-022-01871-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-022-01871-6

Search

Advanced search

Quick links