Mapping the genetic architecture of gene regulation in whole blood

Katharina Schramm; Carola Marzi; Claudia Schurmann; Maren Carstensen; Eva Reinmaa; Reiner Biffar; Gertrud Eckstein; Christian Gieger; Hans-Jörgen Grabe; Georg Homuth; Gabriele Kastenmüller; Reedik Mägi; Andres Metspalu; Evelin Mihailov; Annette Peters; Astrid Petersmann; Michael Roden; Konstantin Strauch; Karsten Suhre; Alexander Teumer; Uwe Völker; Henry Völzke; Rui Wang-Sattler; Melanie Waldenberger; Thomas Meitinger; Thomas Illig; Christian Herder; Harald Grallert; Holger Prokisch

doi:10.1371/journal.pone.0093844

Mapping the genetic architecture of gene regulation in whole blood

PLoS One. 2014 Apr 16;9(4):e93844. doi: 10.1371/journal.pone.0093844. eCollection 2014.

Authors

Katharina Schramm¹, Carola Marzi², Claudia Schurmann³, Maren Carstensen⁴, Eva Reinmaa⁵, Reiner Biffar⁶, Gertrud Eckstein⁷, Christian Gieger⁸, Hans-Jörgen Grabe⁹, Georg Homuth³, Gabriele Kastenmüller¹⁰, Reedik Mägi¹¹, Andres Metspalu⁵, Evelin Mihailov¹², Annette Peters¹³, Astrid Petersmann¹⁴, Michael Roden¹⁵, Konstantin Strauch¹⁶, Karsten Suhre¹⁷, Alexander Teumer³, Uwe Völker³, Henry Völzke¹⁸, Rui Wang-Sattler¹⁹, Melanie Waldenberger¹⁹, Thomas Meitinger²⁰, Thomas Illig²¹, Christian Herder⁴, Harald Grallert², Holger Prokisch¹

Affiliations

¹ Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany; Institute of Human Genetics, Technical University Munich, München, Germany.
² Research Unit of Molecular Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology II, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany.
³ Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany.
⁴ Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; German Center for Diabetes Research (DZD e.V.), partner site Düsseldorf, Germany.
⁵ Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia; Estonian Genome Center, University of Tartu, Tartu, Estonia.
⁶ Department of Prosthetic Dentistry, Gerostomatology and Dental Materials, University Medicine Greifswald, Greifswald, Germany.
⁷ Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.
⁸ Institute of Genetic Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.
⁹ Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, University Medicine of Greifswald, Greifswald, Germany.
¹⁰ Institute of Bioinformatics and Systems Biology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.
¹¹ Estonian Genome Center, University of Tartu, Tartu, Estonia.
¹² Estonian Genome Center, University of Tartu, Tartu, Estonia; Estonian Biocentre, Tartu, Estonia.
¹³ Institute of Human Genetics, Technical University Munich, München, Germany.
¹⁴ Institute of Clinical Chemistry and Laboratory Medicine, Greifswald, Germany.
¹⁵ Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; German Center for Diabetes Research (DZD e.V.), partner site Düsseldorf, Germany; Division of Endocrinology and Diabetology, University Hospital Düsseldorf, Düsseldorf, Germany.
¹⁶ Institute of Genetic Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany; Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität Munich, Neuherberg, Germany.
¹⁷ Institute of Bioinformatics and Systems Biology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany; Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City, Qatar Foundation, Doha, Qatar.
¹⁸ Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
¹⁹ Research Unit of Molecular Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology II, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.
²⁰ Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany; Institute of Human Genetics, Technical University Munich, München, Germany; Munich Heart Alliance, München, Germany.
²¹ Hannover Unified Biobank, Hannover Medical School, Hannover, Germany.

Abstract

Background: We aimed to assess whether whole blood expression quantitative trait loci (eQTLs) with effects in cis and trans are robust and can be used to identify regulatory pathways affecting disease susceptibility.

Materials and methods: We performed whole-genome eQTL analyses in 890 participants of the KORA F4 study and in two independent replication samples (SHIP-TREND, N = 976 and EGCUT, N = 842) using linear regression models and Bonferroni correction.

Results: In the KORA F4 study, 4,116 cis-eQTLs (defined as SNP-probe pairs where the SNP is located within a 500 kb window around the transcription unit) and 94 trans-eQTLs reached genome-wide significance and overall 91% (92% of cis-, 84% of trans-eQTLs) were confirmed in at least one of the two replication studies. Different study designs including distinct laboratory reagents (PAXgene™ vs. Tempus™ tubes) did not affect reproducibility (separate overall replication overlap: 78% and 82%). Immune response pathways were enriched in cis- and trans-eQTLs and significant cis-eQTLs were partly coexistent in other tissues (cross-tissue similarity 40-70%). Furthermore, four chromosomal regions displayed simultaneous impact on multiple gene expression levels in trans, and 746 eQTL-SNPs have been previously reported to have clinical relevance. We demonstrated cross-associations between eQTL-SNPs, gene expression levels in trans, and clinical phenotypes as well as a link between eQTLs and human metabolic traits via modification of gene regulation in cis.

Conclusions: Our data suggest that whole blood is a robust tissue for eQTL analysis and may be used both for biomarker studies and to enhance our understanding of molecular mechanisms underlying gene-disease associations.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Blood / metabolism*
Chromosome Mapping
Gene Expression Regulation*
Gene Regulatory Networks
Genetic Association Studies
Genetic Markers
Humans
Linear Models
Polymorphism, Single Nucleotide
Quantitative Trait Loci

Substances

Genetic Markers

Grants and funding

The KORA research platform and the KORA Augsburg studies are financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, which is funded by the BMBF and by the State of Bavaria. Furthermore, KORA research was supported within the Munich Center of Health Sciences (MC Health), Ludwig Maximilians-Universität, as part of the LMUinnovative and in part by a grant from the BMBF to the German Center for Diabetes Research (DZD). The German Diabetes Center is funded by the German Federal Ministry of Health and the Ministry of School, Science and Research of the State of North-Rhine-Westphalia. This study was supported by the BMBF funded Systems Biology of Metabotypes grant (SysMBo#0315494A). Additional support was obtained from the BMBF (National Genome Research Network NGFNplus Atherogenomics, 01GS0834) and from the European Commission's Seventh Framework Programme (FP7/2007-2013, HEALTH-F2-2011, grant agreement No. 277984, TIRCON). K. Suhre is supported by ‘Biomedical Research Program’ funds at Weill Cornell Medical College in Qatar, a program funded by the Qatar Foundation. SHIP-TREND is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the BMBF (German Ministry of Education and Research), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Analyses were supported by the ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ consortium funded by the BMBF (grant 03IS2061A). Genome-wide genotyping and expression data have been supported by the BMBF (grant no. 03ZIK012) and the Federal State of Mecklenburg, West Pomerania. The University of Greifswald is a member of the ‘Center of Knowledge Interchange’ program of the Siemens AG and the Caché Campus program of the InterSystems GmbH. EGCUT studies were financed by University of Tartu (grant “Center of Translational Genomics”), by Estonian Goverment (grant #SF0180142s08) and by European Commission through the European Regional Development Fund in the frame of grant “Centre of Excellence in Genomics” and Estonian Research Infrastructure's Roadmap and through FP7 grant #313010. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.