DNA methylation across subcortical brain development in children and adolescents with ADHD
Poster No:
307
Submission Type:
Abstract Submission
Authors:
Jo Wrigglesworth1,2, Peter Fransquet1,2, Valentine Chirokoff1, Yen Ting Wong3,4, Jeffrey Craig3,4,5, Timothy Silk1,6
Institutions:
1Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Melbourne, Victoria, Australia, 2Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia, 3School of Medicine and the IMPACT, Deakin University, Geelong, Victoria, Australia, 4Murdoch Children’s Research Institute, Deakin University, Melbourne, Victoria, Australia, 5Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia, 6Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
First Author:
Jo Wrigglesworth
Centre for Social and Early Emotional Development and School of Psychology, Deakin University|Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University|Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Co-Author(s):
Peter Fransquet
Centre for Social and Early Emotional Development and School of Psychology, Deakin University|Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University|Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Valentine Chirokoff
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Victoria, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University
Melbourne, Victoria, Australia
Yen Ting Wong
School of Medicine and the IMPACT, Deakin University|Murdoch Children’s Research Institute, Deakin University
Geelong, Victoria, Australia|Melbourne, Victoria, Australia
School of Medicine and the IMPACT, Deakin University|Murdoch Children’s Research Institute, Deakin University
Geelong, Victoria, Australia|Melbourne, Victoria, Australia
Jeffrey Craig
School of Medicine and the IMPACT, Deakin University|Murdoch Children’s Research Institute, Deakin University|Department of Paediatrics, University of Melbourne
Geelong, Victoria, Australia|Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
School of Medicine and the IMPACT, Deakin University|Murdoch Children’s Research Institute, Deakin University|Department of Paediatrics, University of Melbourne
Geelong, Victoria, Australia|Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Timothy Silk
Centre for Social and Early Emotional Development and School of Psychology, Deakin University|Developmental Imaging, Murdoch Children’s Research Institute
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Centre for Social and Early Emotional Development and School of Psychology, Deakin University|Developmental Imaging, Murdoch Children’s Research Institute
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Introduction:
ADHD is a highly prevalent neurodevelopmental disorder in children and adolescents, which has been linked to both genetic and environmental factors. By mediating the effect of these factors on gene expression, epigenetic mechanisms, like DNA methylation, may be able to act as a potential biomarker of ADHD. Numerous epigenome wide studies have identified differential methylation in individuals with ADHD, relative to controls, though it remains unclear as to how they associate with brain development. We examined whether differential DNA methylation is associated with longitudinal change in brain development of children and adolescents with or without ADHD.
Methods:
Children and adolescents with or without ADHD who completed repeated T1-weighted MRI scans (3T Siemens scanner) across three waves of the Neuroimaging of the Children's Attention Project (NICAP) (Silk et al., 2016). Participants were 9-11 years of age at the first scan, and two additional visits were conducted at 18-month intervals. ADHD diagnoses were confirmed at the first and last wave of assessment using the NIMH Diagnostic Interview Schedule for Children-IV (DISC-IV).
Subcortical segmentations from the FreeSurfer (v6.0) were selected based on previous literature (Hoogman et al., 2017) including the right and left accumbens area, amygdala, caudate, hippocampus, and putamen.
DNA methylation from saliva samples was generated using the Illumina EPIC array (manufacturer). Using epigenetic data collected over repeated assessments, we previously identified three CpG sites with a significant main effect of diagnosis (remittent versus controls, cg11124426: log fold change(FC) = -0.631, adjusted p-value = 0.034) or interaction between diagnosis and time (persistent versus controls, cg26901352 [CCL17]: logFC = -0.13, adjusted p-value = 0.0021; cg17657037 [ITGB1BP]: logFC = 0.26, adjusted p-value = 0.013), which survived FDR correction. Here we address our aims by focusing on these three specific sites. Beta values of DNA methylation were converted to M-values (log2 [methylated/unmethylated]) for subsequent analyses (Du et al., 2010).
Longitudinal change in brain volume was investigated using mixed models, adjusted for sex, and includes a random intercept for each participant. All regions were modelled with a linear change, the exception being the non-linear change in the accumbens area, which includes the polynomial of time. Multiple comparisons were corrected at a false discovery rate of 5%.
Subcortical segmentations from the FreeSurfer (v6.0) were selected based on previous literature (Hoogman et al., 2017) including the right and left accumbens area, amygdala, caudate, hippocampus, and putamen.
DNA methylation from saliva samples was generated using the Illumina EPIC array (manufacturer). Using epigenetic data collected over repeated assessments, we previously identified three CpG sites with a significant main effect of diagnosis (remittent versus controls, cg11124426: log fold change(FC) = -0.631, adjusted p-value = 0.034) or interaction between diagnosis and time (persistent versus controls, cg26901352 [CCL17]: logFC = -0.13, adjusted p-value = 0.0021; cg17657037 [ITGB1BP]: logFC = 0.26, adjusted p-value = 0.013), which survived FDR correction. Here we address our aims by focusing on these three specific sites. Beta values of DNA methylation were converted to M-values (log2 [methylated/unmethylated]) for subsequent analyses (Du et al., 2010).
Longitudinal change in brain volume was investigated using mixed models, adjusted for sex, and includes a random intercept for each participant. All regions were modelled with a linear change, the exception being the non-linear change in the accumbens area, which includes the polynomial of time. Multiple comparisons were corrected at a false discovery rate of 5%.
Results:
A total of 86 participants had epigenetic and MRI data at baseline (aged between 9.5-12.9 years; 39 had ADHD, and 70% were male), and had completed two (n = 62) or three (n = 24) MRI scans. We identified a positive three-way interaction between cg26901352 methylation, time and diagnosis on the right putamen (p = 0.025), which suggests higher levels of methylation at baseline are associated with increased rate of change in brain volume in ADHD compared to controls. A similar positive interaction was observed between cg17657037 and the left caudate (p = 0.039). However, these findings did not survive FDR correction. We found no evidence of an association between cg11124426 and any of the regions investigated here (refer to Figure 1).
·Figure 1. Forest plots of linear mixed model results: interaction between methylation, time and diagnosis
Conclusions:
We investigated the potential role of differential DNA methylation in longitudinal brain development in ADHD. Whilst findings were not strong, we identified some associations between DNA methylation and subcortical brain volume, which require further investigation. Future study is warranted into diagnostic subgroups, including remittance and persistence, along with how differences in DNA methylation may associate with differential brain development trajectories in ADHD.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Genetics:
Genetic Association Studies 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures
Novel Imaging Acquisition Methods:
Anatomical MRI
Keywords:
Attention Deficit Disorder
Development
MRI
STRUCTURAL MRI
Sub-Cortical
Other - Epigenetics, DNA methylation
1|2Indicates the priority used for review
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Provide references using APA citation style.
Du, P., Zhang, X., Huang, C. C., Jafari, N., Kibbe, W. A., Hou, L., & Lin, S. M. (2010). Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics, 11, 587. https://doi.org/10.1186/1471-2105-11-587
Hoogman, M., Bralten, J., Hibar, D. P., Mennes, M., Zwiers, M. P., Schweren, L., van Hulzen, K. J., Medland, S. E., Shumskaya, E., & Jahanshad, N. (2017). Subcortical brain volume differences of participants with ADHD across the lifespan: an ENIGMA collaboration. The Lancet. Psychiatry, 4(4), 310.
Silk, T. J., Genc, S., Anderson, V., Efron, D., Hazell, P., Nicholson, J. M., Kean, M., Malpas, C. B., & Sciberras, E. (2016). Developmental brain trajectories in children with ADHD and controls: a longitudinal neuroimaging study. BMC Psychiatry, 16, 59. https://doi.org/10.1186/s12888-016-0770-4