A1 Refereed original research article in a scientific journal
Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood
Authors: Qi T, Wu Y, Zeng J, Zhang FT, Xue AL, Jiang LD, Zhu ZH, Kemper K, Yengo L, Zheng ZL; eQTLGen Consortium, Marioni RE, Montgomery GW, Deary IJ, Wray NR, Visscher PM, McRae AF, Yang J
Publisher: NATURE PUBLISHING GROUP
Publication year: 2018
Journal: Nature Communications
Journal name in source: NATURE COMMUNICATIONS
Journal acronym: NAT COMMUN
Article number: ARTN 2282
Volume: 9
Number of pages: 12
ISSN: 2041-1723
eISSN: 2041-1723
DOI: https://doi.org/10.1038/s41467-018-04558-1
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/32113458
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 ((r) over cap (b) = 0.70 for ciseQTLs and (r) over cap (b) = 0.78 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.
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