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. 2017 Feb;22(2):250-256.
doi: 10.1038/mp.2016.85. Epub 2016 May 24.

Epigenetic Profiling of ADHD Symptoms Trajectories: A Prospective, Methylome-Wide Study

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Free PMC article

Epigenetic Profiling of ADHD Symptoms Trajectories: A Prospective, Methylome-Wide Study

E Walton et al. Mol Psychiatry. .
Free PMC article

Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent developmental disorder, associated with a range of long-term impairments. Variation in DNA methylation, an epigenetic mechanism, is implicated in both neurobiological functioning and psychiatric health. However, the potential role of DNA methylation in ADHD symptoms is currently unclear. In this study, we examined data from the Avon Longitudinal Study of Parents and Children (ALSPAC)-specifically the subsample forming the Accessible Resource for Integrated Epigenomics Studies (ARIES)-that includes (1) peripheral measures of DNA methylation (Illumina 450k) at birth (n=817, 49% male) and age 7 (n=892, 50% male) and (2) trajectories of ADHD symptoms (7-15 years). We first employed a genome-wide analysis to test whether DNA methylation at birth associates with later ADHD trajectories; and then followed up at age 7 to investigate the stability of associations across early childhood. We found that DNA methylation at birth differentiated ADHD trajectories across multiple genomic locations, including probes annotated to SKI (involved in neural tube development), ZNF544 (previously implicated in ADHD), ST3GAL3 (linked to intellectual disability) and PEX2 (related to perixosomal processes). None of these probes maintained an association with ADHD trajectories at age 7. Findings lend novel insights into the epigenetic landscape of ADHD symptoms, highlighting the potential importance of DNA methylation variation in genes related to neurodevelopmental and peroxisomal processes that play a key role in the maturation and stability of cortical circuits.

Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
Trajectory analyses of the DAWBA ADHD scores yielded a 3 trajectory solution. Trajectories were estimated using k-means for longitudinal data, a non-parametric procedure, which classifies participants into homogenous subgroups following similar developmental patterns (trajectories). See method and results section as well as Supplementary sections 1.4 and 1.5 for statistical details.
Figure 2
Figure 2
Manhattan plot and bar graphs of methylome-wide results at birth. A) CpG chromosome positions are plotted against -log10 p-values. The red line indicates FDR-corrected significance threshold. Results were derived using a general linear model between DNA methylation (407,462 probes at birth, cell type and batch-corrected) and ADHD trajectories, adjusting for sex. See method section for further statistical details. B-D) Bar graphs (mean ± s.e.m.) of three DMPs associated with ADHD trajectories.
Figure 3
Figure 3
Gene network analysis using GeneMANIA. Darker circles represent genes associated with the 13 probes found to be related to ADHD trajectories in the methylome-wide analysis at birth. Lighted circles represent additional genes predicted by GeneMANIA based on genetic and physical interactions, shared pathways and protein domains as well as protein co-expression data. The gene network analysis demonstrates that, rather than being isolated (e.g. FBXW5), these genes clustered into a complex interconnected network. For more information on GeneMANIA methods, see Supplementary section 2.2.

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