Elevated polygenic burden for autism is associated with differential DNA methylation at birth

iPSYCH-Broad ASD Group

Research output: Contribution to journalArticle

Abstract

Background: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors, interests, or activities. The etiology of ASD involves both inherited and environmental risk factors, with epigenetic processes hypothesized as one mechanism by which both genetic and non-genetic variation influence gene regulation and pathogenesis. The aim of this study was to identify DNA methylation biomarkers of ASD detectable at birth. Methods: We quantified neonatal methylomic variation in 1263 infants-of whom ~ 50% went on to subsequently develop ASD-using DNA isolated from archived blood spots taken shortly after birth. We used matched genotype data from the same individuals to examine the molecular consequences of ASD-associated genetic risk variants, identifying methylomic variation associated with elevated polygenic burden for ASD. In addition, we performed DNA methylation quantitative trait loci (mQTL) mapping to prioritize target genes from ASD GWAS findings. Results: We identified robust epigenetic signatures of gestational age and prenatal tobacco exposure, confirming the utility of DNA methylation data generated from neonatal blood spots. Although we did not identify specific loci showing robust differences in neonatal DNA methylation associated with later ASD, there was a significant association between increased polygenic burden for autism and methylomic variation at specific loci. Each unit of elevated ASD polygenic risk score was associated with a mean increase in DNA methylation of - 0.14% at two CpG sites located proximal to a robust GWAS signal for ASD on chromosome 8. Conclusions: This study is the largest analysis of DNA methylation in ASD undertaken and the first to integrate genetic and epigenetic variation at birth. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with disease, and of using mQTL to refine the functional and regulatory variation associated with ASD risk variants.

Original languageEnglish (US)
Article number19
JournalGenome Medicine
Volume10
Issue number1
DOIs
StatePublished - Mar 28 2018

Fingerprint

DNA Methylation
Autistic Disorder
Parturition
Quantitative Trait Loci
Genome-Wide Association Study
Epigenomics
Autism Spectrum Disorder
Genetic Epigenesis
Chromosomes, Human, Pair 8
Methylation
Genes
Gestational Age
Tobacco
Biomarkers
Communication
Genotype

Keywords

  • Autism
  • Birth
  • DNA methylation
  • DNA methylation quantitative trait loci (mQTL)
  • Epigenome-wide association study (EWAS)
  • Genetics
  • Genome-wide association study (GWAS)
  • Neonatal
  • Polygenic risk score
  • Prenatal smoking

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Genetics(clinical)

Cite this

Elevated polygenic burden for autism is associated with differential DNA methylation at birth. / iPSYCH-Broad ASD Group.

In: Genome Medicine, Vol. 10, No. 1, 19, 28.03.2018.

Research output: Contribution to journalArticle

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title = "Elevated polygenic burden for autism is associated with differential DNA methylation at birth",
abstract = "Background: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors, interests, or activities. The etiology of ASD involves both inherited and environmental risk factors, with epigenetic processes hypothesized as one mechanism by which both genetic and non-genetic variation influence gene regulation and pathogenesis. The aim of this study was to identify DNA methylation biomarkers of ASD detectable at birth. Methods: We quantified neonatal methylomic variation in 1263 infants-of whom ~ 50{\%} went on to subsequently develop ASD-using DNA isolated from archived blood spots taken shortly after birth. We used matched genotype data from the same individuals to examine the molecular consequences of ASD-associated genetic risk variants, identifying methylomic variation associated with elevated polygenic burden for ASD. In addition, we performed DNA methylation quantitative trait loci (mQTL) mapping to prioritize target genes from ASD GWAS findings. Results: We identified robust epigenetic signatures of gestational age and prenatal tobacco exposure, confirming the utility of DNA methylation data generated from neonatal blood spots. Although we did not identify specific loci showing robust differences in neonatal DNA methylation associated with later ASD, there was a significant association between increased polygenic burden for autism and methylomic variation at specific loci. Each unit of elevated ASD polygenic risk score was associated with a mean increase in DNA methylation of - 0.14{\%} at two CpG sites located proximal to a robust GWAS signal for ASD on chromosome 8. Conclusions: This study is the largest analysis of DNA methylation in ASD undertaken and the first to integrate genetic and epigenetic variation at birth. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with disease, and of using mQTL to refine the functional and regulatory variation associated with ASD risk variants.",
keywords = "Autism, Birth, DNA methylation, DNA methylation quantitative trait loci (mQTL), Epigenome-wide association study (EWAS), Genetics, Genome-wide association study (GWAS), Neonatal, Polygenic risk score, Prenatal smoking",
author = "{iPSYCH-Broad ASD Group} and Eilis Hannon and Diana Schendel and Ladd-Acosta, {Christine Marie} and Jakob Grove and Hansen, {Christine S{\o}holm} and Andrews, {Shan V.} and Hougaard, {David Michael} and Michaeline Bresnahan and Ole Mors and Hollegaard, {Mads Vilhelm} and Marie B{\ae}kvad-Hansen and Mady Hornig and Mortensen, {Preben Bo} and B{\o}rglum, {Anders D.} and Thomas Werge and Pedersen, {Marianne Gi{\o}rtz} and Merete Nordentoft and Joseph Buxbaum and Fallin, {Daniele Daniele} and Jonas Bybjerg-Grauholm and Abraham Reichenberg and Jonathan Mill and Esben Agerbo and Als, {Thomas D.} and Rich Belliveau and Marie B{\ae}kved-Hansen and Anders B{\o}rglum and Felecia Cerrato and Jane Christensen and Kimberly Chambert and Claire Churchhouse and Mark Daly and Ditte Demontis and Ashley Dumont and Jacqueline Goldstein and Christine Hansen and Mads Hauberg and David Hougaard and Daniel Howrigan and Hailiang Huang and Julian Maller and Alicia Martin and Joanna Martin and Manuel Mattheisen and Jennifer Moran and Preben Mortensen and Benjamin Neale and Mette Nyegaard and Jonatan Pallsen and Duncan Palmer",
year = "2018",
month = "3",
day = "28",
doi = "10.1186/s13073-018-0527-4",
language = "English (US)",
volume = "10",
journal = "Genome Medicine",
issn = "1756-994X",
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T1 - Elevated polygenic burden for autism is associated with differential DNA methylation at birth

AU - iPSYCH-Broad ASD Group

AU - Hannon, Eilis

AU - Schendel, Diana

AU - Ladd-Acosta, Christine Marie

AU - Grove, Jakob

AU - Hansen, Christine Søholm

AU - Andrews, Shan V.

AU - Hougaard, David Michael

AU - Bresnahan, Michaeline

AU - Mors, Ole

AU - Hollegaard, Mads Vilhelm

AU - Bækvad-Hansen, Marie

AU - Hornig, Mady

AU - Mortensen, Preben Bo

AU - Børglum, Anders D.

AU - Werge, Thomas

AU - Pedersen, Marianne Giørtz

AU - Nordentoft, Merete

AU - Buxbaum, Joseph

AU - Fallin, Daniele Daniele

AU - Bybjerg-Grauholm, Jonas

AU - Reichenberg, Abraham

AU - Mill, Jonathan

AU - Agerbo, Esben

AU - Als, Thomas D.

AU - Belliveau, Rich

AU - Bækved-Hansen, Marie

AU - Børglum, Anders

AU - Cerrato, Felecia

AU - Christensen, Jane

AU - Chambert, Kimberly

AU - Churchhouse, Claire

AU - Daly, Mark

AU - Demontis, Ditte

AU - Dumont, Ashley

AU - Goldstein, Jacqueline

AU - Hansen, Christine

AU - Hauberg, Mads

AU - Hougaard, David

AU - Howrigan, Daniel

AU - Huang, Hailiang

AU - Maller, Julian

AU - Martin, Alicia

AU - Martin, Joanna

AU - Mattheisen, Manuel

AU - Moran, Jennifer

AU - Mortensen, Preben

AU - Neale, Benjamin

AU - Nyegaard, Mette

AU - Pallsen, Jonatan

AU - Palmer, Duncan

PY - 2018/3/28

Y1 - 2018/3/28

N2 - Background: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors, interests, or activities. The etiology of ASD involves both inherited and environmental risk factors, with epigenetic processes hypothesized as one mechanism by which both genetic and non-genetic variation influence gene regulation and pathogenesis. The aim of this study was to identify DNA methylation biomarkers of ASD detectable at birth. Methods: We quantified neonatal methylomic variation in 1263 infants-of whom ~ 50% went on to subsequently develop ASD-using DNA isolated from archived blood spots taken shortly after birth. We used matched genotype data from the same individuals to examine the molecular consequences of ASD-associated genetic risk variants, identifying methylomic variation associated with elevated polygenic burden for ASD. In addition, we performed DNA methylation quantitative trait loci (mQTL) mapping to prioritize target genes from ASD GWAS findings. Results: We identified robust epigenetic signatures of gestational age and prenatal tobacco exposure, confirming the utility of DNA methylation data generated from neonatal blood spots. Although we did not identify specific loci showing robust differences in neonatal DNA methylation associated with later ASD, there was a significant association between increased polygenic burden for autism and methylomic variation at specific loci. Each unit of elevated ASD polygenic risk score was associated with a mean increase in DNA methylation of - 0.14% at two CpG sites located proximal to a robust GWAS signal for ASD on chromosome 8. Conclusions: This study is the largest analysis of DNA methylation in ASD undertaken and the first to integrate genetic and epigenetic variation at birth. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with disease, and of using mQTL to refine the functional and regulatory variation associated with ASD risk variants.

AB - Background: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors, interests, or activities. The etiology of ASD involves both inherited and environmental risk factors, with epigenetic processes hypothesized as one mechanism by which both genetic and non-genetic variation influence gene regulation and pathogenesis. The aim of this study was to identify DNA methylation biomarkers of ASD detectable at birth. Methods: We quantified neonatal methylomic variation in 1263 infants-of whom ~ 50% went on to subsequently develop ASD-using DNA isolated from archived blood spots taken shortly after birth. We used matched genotype data from the same individuals to examine the molecular consequences of ASD-associated genetic risk variants, identifying methylomic variation associated with elevated polygenic burden for ASD. In addition, we performed DNA methylation quantitative trait loci (mQTL) mapping to prioritize target genes from ASD GWAS findings. Results: We identified robust epigenetic signatures of gestational age and prenatal tobacco exposure, confirming the utility of DNA methylation data generated from neonatal blood spots. Although we did not identify specific loci showing robust differences in neonatal DNA methylation associated with later ASD, there was a significant association between increased polygenic burden for autism and methylomic variation at specific loci. Each unit of elevated ASD polygenic risk score was associated with a mean increase in DNA methylation of - 0.14% at two CpG sites located proximal to a robust GWAS signal for ASD on chromosome 8. Conclusions: This study is the largest analysis of DNA methylation in ASD undertaken and the first to integrate genetic and epigenetic variation at birth. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with disease, and of using mQTL to refine the functional and regulatory variation associated with ASD risk variants.

KW - Autism

KW - Birth

KW - DNA methylation

KW - DNA methylation quantitative trait loci (mQTL)

KW - Epigenome-wide association study (EWAS)

KW - Genetics

KW - Genome-wide association study (GWAS)

KW - Neonatal

KW - Polygenic risk score

KW - Prenatal smoking

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U2 - 10.1186/s13073-018-0527-4

DO - 10.1186/s13073-018-0527-4

M3 - Article

C2 - 29587883

AN - SCOPUS:85044353251

VL - 10

JO - Genome Medicine

JF - Genome Medicine

SN - 1756-994X

IS - 1

M1 - 19

ER -