Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder

Shan V. Andrews, Shannon E. Ellis, Kelly M. Bakulski, Brooke Sheppard, Lisa A. Croen, Irva Hertz-Picciotto, Craig J. Newschaffer, Andrew P. Feinberg, Dan E. Arking, Christine Ladd-Acosta () and M. Daniele Fallin ()
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Shan V. Andrews: Johns Hopkins Bloomberg School of Public Health
Shannon E. Ellis: Johns Hopkins School of Medicine
Kelly M. Bakulski: University of Michigan School of Public Health
Brooke Sheppard: Johns Hopkins Bloomberg School of Public Health
Lisa A. Croen: Kaiser Permanente Northern California
Irva Hertz-Picciotto: University of California Davis
Craig J. Newschaffer: Drexel University
Andrew P. Feinberg: Johns Hopkins School of Medicine
Dan E. Arking: Johns Hopkins Bloomberg School of Public Health
Christine Ladd-Acosta: Johns Hopkins Bloomberg School of Public Health
M. Daniele Fallin: Johns Hopkins Bloomberg School of Public Health

Nature Communications, 2017, vol. 8, issue 1, 1-10

Abstract: Abstract Integration of emerging epigenetic information with autism spectrum disorder (ASD) genetic results may elucidate functional insights not possible via either type of information in isolation. Here we use the genotype and DNA methylation (DNAm) data from cord blood and peripheral blood to identify SNPs associated with DNA methylation (meQTL lists). Additionally, we use publicly available fetal brain and lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs. ASD-associated SNPs are enriched for fetal brain (OR = 3.55; P

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-00868-y

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DOI: 10.1038/s41467-017-00868-y

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