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

Ting Qi; eQTLGen Consortium

doi:10.1038/s41467-018-04558-1

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

Ting Qi
, eQTLGen Consortium

Research output: Contribution to journal › Article (Academic Journal) › peer-review

307 Citations (Scopus)

458 Downloads (Pure)

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 (r b = 0.70 for cis-eQTLs and r ^ 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.

Original language	English
Article number	2282
Number of pages	12
Journal	Nature Communications
Volume	9
DOIs	https://doi.org/10.1038/s41467-018-04558-1
Publication status	Published - 11 Jun 2018

Access to Document

10.1038/s41467-018-04558-1

Full-text PDF (final published version)Final published version, 1.11 MBLicence: CC BY

Handle.net

Persistent link

Cite this

@article{50f44eb9696e4793aa5d8003733e0f45,

title = "Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood",

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 (r b = 0.70 for cis-eQTLs and r \textasciicircum{} 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.",

author = "Ting Qi and \{eQTLGen Consortium\} and Yang Wu and Jian Zeng and Futao Zhang and Angli Xue and Longda Jiang and Zhihong Zhu and Kathryn Kemper and Loic Yengo and Zhili Zheng and Mawuss{\'e} Agbessi and Habibul Ahsan and Isabel Alves and Anand Andiappan and Philip Awadalla and Alexis Battle and Frank Beutner and \{Jan Bonder\}, Marc and Dorret Boomsma and Mark Christiansen and Annique Claringbould and Patrick Deelen and T{\~o}nu Esko and Fav{\'e}, \{Marie Julie\} and Lude Franke and Timothy Frayling and Sina Gharib and Gregory Gibson and Gibran Hemani and Rick Jansen and Mika K{\"a}h{\"o}nen and Anette Kalnapenkis and Silva Kasela and Johannes Kettunen and Yungil Kim and Holger Kirsten and Peter Kovacs and Knut Krohn and Jaanika Kronberg-Guzman and Viktorija Kukushkina and Zoltan Kutalik and Bernett Lee and Terho Lehtim{\"a}ki and Markus Loeffler and Marigorta, \{Urko M.\} and Andres Metspalu and Lili Milani and Martina M{\"u}ller-Nurasyid and Matthias Nauck and Susan Ring",

year = "2018",

month = jun,

day = "11",

doi = "10.1038/s41467-018-04558-1",

language = "English",

volume = "9",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Research",

}

TY - JOUR

T1 - Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

AU - Qi, Ting

AU - eQTLGen Consortium

AU - Wu, Yang

AU - Zeng, Jian

AU - Zhang, Futao

AU - Xue, Angli

AU - Jiang, Longda

AU - Zhu, Zhihong

AU - Kemper, Kathryn

AU - Yengo, Loic

AU - Zheng, Zhili

AU - Agbessi, Mawussé

AU - Ahsan, Habibul

AU - Alves, Isabel

AU - Andiappan, Anand

AU - Awadalla, Philip

AU - Battle, Alexis

AU - Beutner, Frank

AU - Jan Bonder, Marc

AU - Boomsma, Dorret

AU - Christiansen, Mark

AU - Claringbould, Annique

AU - Deelen, Patrick

AU - Esko, Tõnu

AU - Favé, Marie Julie

AU - Franke, Lude

AU - Frayling, Timothy

AU - Gharib, Sina

AU - Gibson, Gregory

AU - Hemani, Gibran

AU - Jansen, Rick

AU - Kähönen, Mika

AU - Kalnapenkis, Anette

AU - Kasela, Silva

AU - Kettunen, Johannes

AU - Kim, Yungil

AU - Kirsten, Holger

AU - Kovacs, Peter

AU - Krohn, Knut

AU - Kronberg-Guzman, Jaanika

AU - Kukushkina, Viktorija

AU - Kutalik, Zoltan

AU - Lee, Bernett

AU - Lehtimäki, Terho

AU - Loeffler, Markus

AU - Marigorta, Urko M.

AU - Metspalu, Andres

AU - Milani, Lili

AU - Müller-Nurasyid, Martina

AU - Nauck, Matthias

AU - Ring, Susan

PY - 2018/6/11

Y1 - 2018/6/11

N2 - 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 b = 0.70 for cis-eQTLs and r ^ 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.

AB - 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 b = 0.70 for cis-eQTLs and r ^ 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.

UR - https://www.scopus.com/pages/publications/85048415370

U2 - 10.1038/s41467-018-04558-1

DO - 10.1038/s41467-018-04558-1

M3 - Article (Academic Journal)

C2 - 29891976

AN - SCOPUS:85048415370

SN - 2041-1723

VL - 9

JO - Nature Communications

JF - Nature Communications

M1 - 2282

ER -

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

Abstract

Access to Document

Handle.net

Other files and links

Fingerprint

Professor Gibran Hemani

Cite this

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

Abstract

Access to Document

Handle.net

Other files and links

Fingerprint

Profiles

Professor Gibran Hemani

Cite this