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Nat Commun. 2018 Jun 11;9(1):2282. doi: 10.1038/s41467-018-04558-1.

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood.

Author information

1
Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
2
Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia.
3
The Eye Hospital, School of Ophthalmology & Optometry, Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China.
4
Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
5
Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
6
Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. jian.yang@uq.edu.au.
7
Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia. jian.yang@uq.edu.au.
8
The Eye Hospital, School of Ophthalmology & Optometry, Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China. jian.yang@uq.edu.au.

Abstract

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r b ). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples ([Formula: see text] for cis-eQTLs and [Formula: see text] for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes.

PMID:
29891976
PMCID:
PMC5995828
DOI:
10.1038/s41467-018-04558-1
[Indexed for MEDLINE]
Free PMC Article

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