Integrative genetic and metabolite profiling analysis suggests altered phosphatidylcholine metabolism in asthma

Authors

  • J. S. Ried,

    1. Institute of Genetic Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • H. Baurecht,

    1. Department of Dermatology, Allergology, and Venerology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
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  • F. Stückler,

    1. Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • J. Krumsiek,

    1. Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • C. Gieger,

    1. Institute of Genetic Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • J. Heinrich,

    1. Institute of Epidemiology I, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • M. Kabesch,

    1. University Children's Hospital Regensburg (KUNO), Department of Pediatric Pneumology and Allergy, Regensburg
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  • C. Prehn,

    1. Institute of Experimental Genetics, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • A. Peters,

    1. Institute of Epidemiology II, Helmholtz Zentrum München – German Research Center for Environmental Health, Genome Analysis Center, Neuherberg, Germany
    2. Research Unit of Molecular Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • E. Rodriguez,

    1. Department of Dermatology, Allergology, and Venerology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
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  • H. Schulz,

    1. Institute of Epidemiology I, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • K. Strauch,

    1. Institute of Genetic Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
    2. Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
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  • K. Suhre,

    1. Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
    2. Faculty of Biology, Ludwig-Maximilians-Universität, Munich, Germany
    3. Department of Physiology and Biophysics, Weill Cornell Medical College, Doha, Qatar
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  • R. Wang-Sattler,

    1. Research Unit of Molecular Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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  • H.-E. Wichmann,

    1. Institute of Epidemiology I, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
    2. Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
    3. Klinikum Grosshadern, Munich, Germany
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  • F. J. Theis,

    1. Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
    2. Department of Mathematics, Technische Universität München, Munich, Germany
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  • T. Illig,

    1. Research Unit of Molecular Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
    2. Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
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    • Contributed equally.
  • J. Adamski,

    1. Institute of Experimental Genetics, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
    2. Chair for Experimental Genetics, Technische Universität München, Freising-Weihenstephan, Germany
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    • Contributed equally.
  • S. Weidinger

    Corresponding author
    1. Department of Dermatology, Allergology, and Venerology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
    • Institute of Genetic Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
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    • Contributed equally.

  • Edited by: Hans-Uwe Simon

Correspondence

Prof. Dr. Stephan Weidinger, Department of Dermatology, Venereology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Schittenhelmstrasse 7, 24105 Kiel, Germany.

Tel.: 0049 431 597 2732

Fax: 0049 431 597 1815

E-mail: sweidinger@dermatology.uni-kiel.de

Abstract

Background

Genome-wide association studies (GWAS) have identified many risk loci for asthma, but effect sizes are small, and in most cases, the biological mechanisms are unclear. Targeted metabolite quantification that provides information about a whole range of pathways of intermediary metabolism can help to identify biomarkers and investigate disease mechanisms. Combining genetic and metabolic information can aid in characterizing genetic association signals with high resolution. This work aimed to investigate the interrelation of current asthma, candidate asthma risk alleles and a panel of metabolites.

Methods

We investigated 151 metabolites, quantified by targeted mass spectrometry, in fasting serum of asthmatic and nonasthmatic individuals from the population-based KORA F4 study (N = 2925). In addition, we analysed effects of single-nucleotide polymorphisms (SNPs) at 24 asthma risk loci on these metabolites.

Results

Increased levels of various phosphatidylcholines and decreased levels of various lyso-phosphatidylcholines were associated with asthma. Likewise, asthma risk alleles from the PDED3 and MED24 genes at the asthma susceptibility locus 17q21 were associated with increased concentrations of various phosphatidylcholines with consistent effect directions.

Conclusions

Our study demonstrated the potential of metabolomics to infer asthma-related biomarkers by the identification of potentially deregulated phospholipids that associate with asthma and asthma risk alleles.

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