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

Journal name:
Nature Genetics
Volume:
45,
Pages:
1238–1243
Year published:
DOI:
doi:10.1038/ng.2756
Received
Accepted
Published online

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)1, altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE2, 3, 4. 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.

At a glance

Figures

  1. Trans-eQTL SNPs are enriched for functional elements.
    Figure 1: Trans-eQTL SNPs are enriched for functional elements.

    We investigated whether trans-eQTL SNPs are enriched for certain functional elements using the online tools SNPInfo, SNPNexus and HaploReg that rely on data from, among others, the ENCODE Project. (a) Trans-eQTL SNPs are enriched for mapping within miRNA binding sites. (b) Trans-eQTL SNPs show strong enrichment (as annotated using HaploReg) for enhancer regions that are present in K562 (myeloid) and GM12878 (lymphoid) cell lines (error bars, 1 s.d.).

  2. Independent trans-eQTL effects emanating from the IKZF1 locus.
    Figure 2: Independent trans-eQTL effects emanating from the IKZF1 locus.

    SNP rs4917014, associated with SLE, and unlinked SNP rs4917014, associated with MCV, both affect the expression of IKZF1 in cis. rs12718597 affects 50 genes in trans (mostly involved in hemoglobin metabolism), and rs4917014 affects 8 different genes in trans: the rs4917014[T] risk allele is associated with increased expression of genes involved in the type I interferon response. At a somewhat lower significance threshold (FDR = 0.28), rs4917014[T] is associated with decreased complement C1QB expression. Both processes are hallmark features of SLE.

  3. Two unlinked T1D risk alleles are associated with increased STAT1 and GBP4 expression.
    Figure 3: Two unlinked T1D risk alleles are associated with increased STAT1 and GBP4 expression.

    rs3184504[T], a risk allele for T1D (chromosome 12), affects the expression of SH2B3 in cis but also affects the expression of 14 unique genes in trans, including 2 interferon-γ response genes, GBP4 and STAT1. Another, unlinked T1D risk allele (rs4788084[C] on chromosome 16) also increases expression of these two interferon-γ response genes, suggesting that an elevated interferon-γ response is important in T1D.

Accession codes

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Author information

  1. These authors contributed equally to this work.

    • Harm-Jan Westra,
    • Marjolein J Peters,
    • Tõnu Esko,
    • Hanieh Yaghootkar,
    • Claudia Schurmann,
    • Johannes Kettunen &
    • Mark W Christiansen
  2. These authors jointly directed this work.

    • Bruce M Psaty,
    • Samuli Ripatti,
    • Alexander Teumer,
    • Timothy M Frayling,
    • Andres Metspalu,
    • Joyce B J van Meurs &
    • Lude Franke

Affiliations

  1. Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

    • Harm-Jan Westra,
    • Alexandra Zhernakova,
    • Daria V Zhernakova,
    • Juha Karjalainen,
    • Sebo Withoff &
    • Lude Franke
  2. Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam, The Netherlands.

    • Marjolein J Peters,
    • André G Uitterlinden,
    • Fernando Rivadeneira &
    • Joyce B J van Meurs
  3. Netherlands Genomics Initiative–sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden and Rotterdam, The Netherlands.

    • Marjolein J Peters,
    • André G Uitterlinden,
    • Albert Hofman,
    • Fernando Rivadeneira &
    • Joyce B J van Meurs
  4. Estonian Genome Center, University of Tartu, Tartu, Estonia.

    • Tõnu Esko,
    • Eva Reinmaa,
    • Krista Fischer,
    • Mari Nelis,
    • Lili Milani,
    • Markus Perola &
    • Andres Metspalu
  5. Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK.

    • Hanieh Yaghootkar &
    • Timothy M Frayling
  6. Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.

    • Claudia Schurmann,
    • Georg Homuth,
    • Uwe Völker &
    • Alexander Teumer
  7. Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.

    • Johannes Kettunen &
    • Samuli Ripatti
  8. Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.

    • Johannes Kettunen,
    • Markus Perola,
    • Veikko Salomaa &
    • Samuli Ripatti
  9. Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, USA.

    • Mark W Christiansen,
    • Jennifer Brody &
    • Bruce M Psaty
  10. Wellcome Trust Centre for Human Genetics, Oxford, UK.

    • Benjamin P Fairfax,
    • Seiko Makino &
    • Julian C Knight
  11. Department of Oncology, Cancer and Haematology Centre, Churchill Hospital, Oxford, UK.

    • Benjamin P Fairfax
  12. Institute of Human Genetics, Helmholz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany.

    • Katharina Schramm,
    • Holger Prokisch &
    • Thomas Meitinger
  13. Institute of Human Genetics, Technical University Munich, Munich, Germany.

    • Katharina Schramm,
    • Holger Prokisch &
    • Thomas Meitinger
  14. University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland, Australia.

    • Joseph E Powell &
    • Peter M Visscher
  15. Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia.

    • Joseph E Powell &
    • Peter M Visscher
  16. Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, Utrecht, The Netherlands.

    • Jan H Veldink &
    • Leonard H Van den Berg
  17. Department of Epidemiology, Erasmus Medical Centre Rotterdam, Rotterdam, The Netherlands.

    • André G Uitterlinden,
    • Albert Hofman &
    • Fernando Rivadeneira
  18. Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands.

    • Peter A C 't Hoen
  19. Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, Exeter, UK.

    • David Melzer
  20. Clinical Research Branch, National Institute on Aging–Advanced Studies in Translational Research on Aging (ASTRA) Unit, Harbor Hospital, Baltimore, Maryland, USA.

    • Luigi Ferrucci
  21. Laboratory of Neurogenetics, National Institute on Aging, US National Institutes of Health, Bethesda, Maryland, USA.

    • Andrew B Singleton,
    • Dena G Hernandez &
    • Michael A Nalls
  22. Department of Molecular Neuroscience, Reta Lila Laboratories, Institute of Neurology, University College London, London, UK.

    • Dena G Hernandez
  23. Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.

    • Matthias Nauck
  24. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.

    • Dörte Radke
  25. Department of Epidemiology, University of Washington, Seattle, Washington, USA.

    • Astrid Suchy-Dicey &
    • Daniel A Enquobahrie
  26. Computational Medicine Core, Center for Lung Biology, Division of Pulmonary & Critical Care Medicine, Department of Medicine, University of Washington, Seattle, Washington, USA.

    • Sina A Gharib
  27. Department of Statistics, University of Auckland, Auckland, New Zealand.

    • Thomas Lumley
  28. Queensland Institute of Medical Research, Herston, Queensland, Australia.

    • Grant W Montgomery
  29. Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.

    • Christian Herder &
    • Michael Roden
  30. Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.

    • Michael Roden
  31. Department of Metabolic Diseases, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.

    • Michael Roden
  32. Research Unit of Molecular Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany.

    • Harald Grallert
  33. German Center for Cardiovascular Research (DZHK), Göttingen, Germany.

    • Thomas Meitinger
  34. Munich Heart Alliance, Munich, Germany.

    • Thomas Meitinger
  35. Institute of Medical Informatics, Biometry and Epidemiology, Ludwig Maximilians Universität, Neuherberg, Germany.

    • Konstantin Strauch
  36. Institute of Genetic Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany.

    • Konstantin Strauch
  37. Groningen Bioinformatics Center, University of Groningen, Groningen, The Netherlands.

    • Yang Li &
    • Ritsert C Jansen
  38. Group Health Research Institute, Group Health Cooperative, Seattle, Washington, USA.

    • Bruce M Psaty
  39. Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.

    • Samuli Ripatti

Contributions

Experiment design and method development: H.-J.W., M.J.P., T.E., H.Y., C.S., J. Kettunen, M.W.C., B.P.F., K. Schramm, J. Karjalainen, T.L., Y.L., R.C.J., B.M.P., S.R., A.T., T.M.F., A.M., J.B.J.M. and L. Franke. Reviewing and editing of the manuscript: H.-J.W., M.J.P., T.E., H.Y., C.S., J. Kettunen, M.W.C., B.P.F., A.Z., A.G.U., A.H., F.R., V.S., J.B., T.L., Y.L., R.C.J., P.M.V., J.C.K., B.M.P., S.R., A.T., T.M.F., A.M., J.B.J.M. and L. Franke. Data collection: D.V.Z., J.H.V., J. Karjalainen, S.W., F.R., P.A.C.t.H., E.R., K.F., M. Nelis, L.M., D.M., L. Ferrucci, A.B.S., D.G.H., M.A.N., G.H., M. Nauck, D.R., U.V., M.P., A.S.-D., S.A.G., D.A.E., G.W.M., S.M., H.P., C.H., M.R., H.G., T.M., K. Strauch and L.H.V.d.B. Replication of trans-eQTL results: B.P.F., K. Schramm, J.E.P., P.M.V. and J.C.K.

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The authors declare no competing financial interests.

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