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Author Notes:

Correspondence: dfallin@jhu.edu; claddac1@jhu.edu

MDF and CL-A conceived the study.

GCW, LAS, DES, LAC, MDF, and CJN led the participation and sample recruitment for SEED.

STW, RSA, and PC generated the methylation data and performed initial analysis on all the SSC samples.

CL-A and APF supervised methylation data collection.

SVA performed quality control and preprocessing for the SEED and SSC methylation data.

BS and CL-A performed quality control for the SEED genotype data.

SVA performed all analyses, supervised by MDF, and CL-A.

CL-A, MDF, and APF obtained funding for the DNA methylation measurements in SEED.

SVA, MDF, and CL-A wrote the manuscript.

All authors contributed to interpretation of results and edited and reviewed the manuscript.

All authors read and approved the final manuscript.

M. Daniele Fallin and Christine Ladd-Acosta contributed equally to this work.

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

The authors declare that they have no competing interests.

Subjects:

Research Funding:

This project was supported by Centers for Disease Control and Prevention (CDC) Cooperative Agreements announced under the following RFAs: 01086, 02199, DD11-002, DD06-003, DD04-001, and DD09-002.

The DNA methylation assays were supported by Autism Speaks Award #7659 and the genotype assays were supported by NIEHS (R01ES019001; R01ES017646).

S. Andrews was supported by the Burroughs-Wellcome Trust training grant: Maryland, Genetics, Epidemiology and Medicine (MD-GEM).

The SSC was supported by Simons Foundation (SFARI) award and NIH grant MH089606, both awarded to S.T. Warren.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Genetics & Heredity
  • Neurosciences
  • Neurosciences & Neurology
  • DNA methylation
  • Epigenome
  • Autism spectrum disorders
  • Peripheral blood
  • Study to Explore Early Development
  • Simons Simplex Collection
  • DIAGNOSTIC OBSERVATION SCHEDULE
  • EXPLORE EARLY DEVELOPMENT
  • GENOME-WIDE ASSOCIATION
  • FRAGILE-X-SYNDROME
  • RETT-SYNDROME
  • MUTATIONS
  • GENE
  • HETEROGENEITY
  • INDIVIDUALS
  • CONVERGENCE

Case-control meta-analysis of blood DNA methylation and autism spectrum disorder

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Journal Title:

Molecular Autism

Volume:

Volume 9, Number 1

Publisher:

, Pages 40-40

Type of Work:

Article | Final Publisher PDF

Abstract:

Background: Several reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies. Methods: DNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample. Findings: In this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12 × 10- 7. Seven CpGs showed differences at p < 1 × 10- 5and 48 at 1 × 10- 4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpG hits, which was consistent across EWAS and meQTL discovery p value thresholds. Conclusions: No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the seven sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD.

Copyright information:

© 2018 The Author(s).

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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