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Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex

Nature Neuroscience volume 19, pages 4047 (2016) | Download Citation

Abstract

DNA methylation (DNAm) is important in brain development and is potentially important in schizophrenia. We characterized DNAm in prefrontal cortex from 335 non-psychiatric controls across the lifespan and 191 patients with schizophrenia and identified widespread changes in the transition from prenatal to postnatal life. These DNAm changes manifest in the transcriptome, correlate strongly with a shifting cellular landscape and overlap regions of genetic risk for schizophrenia. A quarter of published genome-wide association studies (GWAS)-suggestive loci (4,208 of 15,930, P < 10−100) manifest as significant methylation quantitative trait loci (meQTLs), including 59.6% of GWAS-positive schizophrenia loci. We identified 2,104 CpGs that differ between schizophrenia patients and controls that were enriched for genes related to development and neurodifferentiation. The schizophrenia-associated CpGs strongly correlate with changes related to the prenatal-postnatal transition and show slight enrichment for GWAS risk loci while not corresponding to CpGs differentiating adolescence from later adult life. These data implicate an epigenetic component to the developmental origins of this disorder.

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Acknowledgements

We are grateful for the vision and generosity of the Lieber and Maltz Families who made this work possible. We thank the families who donated to this research and we thank A. Feinberg for helpful input on data analyses. This work was supported by the Lieber Institute for Brain Development. A.E.J. was partially supported by 1R21MH102791.

Author information

Author notes

    • Daniel R Weinberger
    •  & Joel E Kleinman

    These authors contributed equally to this work.

Affiliations

  1. Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland, USA.

    • Andrew E Jaffe
    • , Yuan Gao
    • , Amy Deep-Soboslay
    • , Ran Tao
    • , Thomas M Hyde
    • , Daniel R Weinberger
    •  & Joel E Kleinman
  2. Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

    • Andrew E Jaffe
  3. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

    • Andrew E Jaffe
  4. Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

    • Thomas M Hyde
    •  & Daniel R Weinberger
  5. Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

    • Thomas M Hyde
    •  & Daniel R Weinberger
  6. Department of Neuroscience and the Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

    • Daniel R Weinberger

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Contributions

A.E.J. designed the study, performed the data analysis and oversaw the writing of the manuscript. Y.G. oversaw the data generation. A.D.-S. collected phenotype data on all subjects. R.T. performed DNA extractions and contributed to the data generation. T.M.H. collected brain samples and performed tissue dissections to obtain biological materials. D.R.W. designed the study, contributed to the data analysis and interpretation of the results, and oversaw the writing of the manuscript. J.E.K. collected brain samples and provided clinical interpretation of the results. All authors contributed to the writing of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andrew E Jaffe.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–14 and Supplementary Analysis

  2. 2.

    Supplementary Methods Checklist

Excel files

  1. 1.

    Supplementary Table 1

    Demographic data for the samples analyzed, stratified by age group and diagnosis. P-values depict the differences between the demographic data by the cases and adult controls.

  2. 2.

    Supplementary Table 3

    Gene ontology (GO) enrichment statistics for those DMRs that increase/“up” or decrease/“down” across the transition from pre to postnatal life

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    Supplementary Table 6

    Overlap between DNAm changes and chromatin state data from the Epigenome Roadmap project for adult DLPFC Bolded cells indicated >2 fold enrichment or depletion compared to the relevant background CpGs/regions

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    Supplementary Table 8

    NHGRI GWAS catalog annotated by whether each SNP has an meQTL in the DLPFC dataset.

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    Supplementary Table 9

    meQTLs within the PGC2 SNPs and their proxies

CSV files

  1. 1.

    Supplementary Table 2

    Differentially methylated regions (DMRs) and corresponding annotation comparing prenatal and postnatal samples.

  2. 2.

    Supplementary Table 4

    Differentially methylated blocks comparing prenatal and postnatal samples

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    Supplementary Table 5

    Gene ontology (GO) analysis on the genes contained with the differentially methylated blocks.

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    Supplementary Table 7

    Overlap between PGC2 risk regions and DMRs associated with the transition from prenatal to postnatal life, n=31 regions. Rank: PGC Rank, P.value: p-value for the region, Position: range of LD block for region, numDMRs: the number of DMRs within the region.

  5. 5.

    Supplementary Table 10

    List of differentially methylated CpGs comparing patients with schizophrenia to adult controls.

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    Supplementary Table 11

    Gene ontology (GO) analysis for genes near differentially methylated CpGs for diagnosis.

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DOI

https://doi.org/10.1038/nn.4181

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