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Nat Genet. 2013 Oct;45(10):1238-1243. doi: 10.1038/ng.2756. Epub 2013 Sep 8.

Systematic identification of trans eQTLs as putative drivers of known disease associations.

Author information

1
Department of Genetics, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen, the Netherlands.
2
Department of Internal Medicine, Erasmus Medical Centre Rotterdam, the Netherlands.
3
The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, the Netherlands.
4
Estonian Genome Center, University of Tartu, Riia 23b, 51010, Tartu, Estonia.
5
Genetics of Complex Traits, University of Exeter Medical School, Exeter, EX1 2LU, UK.
6
Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, D-17487 Greifswald, Germany.
7
Institute for Molecular Medicine Finland FIMM, FI-00014 University of Helsinki, Helsinki, Finland.
8
Department of Chronic Disease Prevention, National Institute for Health and Welfare, FI-00271 Helsinki, Finland.
9
Cardiovascular Health Research Unit, University of Washington, Seattle, WA.
10
Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK.
11
Department of Oncology, Cancer and Haematology Centre, Churchill Hospital, Oxford, OX3 7LJ.
12
Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
13
Institute of Human Genetics, Technical University Munich, Munich, Germany.
14
University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland, Australia.
15
The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.
16
Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, Utrecht, the Netherlands.
17
Department of Epidemiology, Erasmus Medical Center Rotterdam, the Netherlands.
18
Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands.
19
Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Barrack Road, Exeter, EX2 5DW, UK.
20
Clinical Research Branch, National Institute on Aging NIA-ASTRA Unit, Harbor Hospital, MD, USA.
21
Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, 35 Lincoln Drive, Bethesda, MD, USA.
22
Department of Molecular Neuroscience and Reta Lila Laboratories, Institute of Neurology, UCL, Queen Square House, Queen Square, London WC1N 3BG, UK.
23
Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, D-17475 Greifswald, Germany.
24
Institute for Community Medicine, University Medicine Greifswald, D-17487 Greifswald, Germany.
25
Department of Epidemiology, University of Washington, Seattle, WA, USA.
26
Computational Medicine Core, Center for Lung Biology, Division of Pulmonary & Critical Care Medicine, Department of Medicine, University of Washington, Seattle, WA, USA.
27
Department of Statistics, University of Auckland, Auckland, New Zealand.
28
Queensland Institute of Medical Research, Herston, Brisbane, Australia.
29
Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, University Düsseldorf, Düsseldorf, Germany.
30
Departments of Endocrinology & Diabetology & Metabolic Diseases, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.
31
Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
32
German Center for Cardiovascular Research (DZHK), Germany; Munich Heart Allience, Munich, Germany.
33
Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Neuherberg, Germany.
34
Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
35
Groningen Bioinformatics Centre, University of Groningen, Groningen, the Netherlands.
36
Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA.
37
Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus,CB10 1SA, Hinxton, UK.
#
Contributed equally

Abstract

Identifying the downstream effects of disease-associated SNPs is challenging. To help overcome this problem, we performed expression quantitative trait locus (eQTL) meta-analysis in non-transformed peripheral blood samples from 5,311 individuals with replication in 2,775 individuals. We identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease: rs4917014, previously associated with systemic lupus erythematosus (SLE), altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE. DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3' UTR levels of IKZF1 in cis, and chromatin immunoprecipitation and sequencing analysis of the trans-regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.

PMID:
24013639
PMCID:
PMC3991562
DOI:
10.1038/ng.2756
[Indexed for MEDLINE]
Free PMC Article

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