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Differential coexpression analysis of obesity-associated networks in human subcutaneous adipose tissue

International Journal of Obesity volume 36, pages 137–147 (2012)Cite this article

Abstract

Objective:

To use a unique obesity-discordant sib-pair study design to combine differential expression analysis, expression quantitative trait loci (eQTLs) mapping and a coexpression regulatory network approach in subcutaneous human adipose tissue to identify genes relevant to the obese state.

Study design:

Genome-wide transcript expression in subcutaneous human adipose tissue was measured using Affymetrix U133 Plus 2.0 microarrays (Affymetrix, Santa Clara, CA, USA), and genome-wide genotyping data was obtained using an Applied Biosystems (Applied Biosystems; Life Technologies, Carlsbad, CA, USA) SNPlex linkage panel.

Subjects:

A total of 154 Swedish families ascertained through an obese proband (body mass index (BMI) >30 kg m−2) with a discordant sibling (BMI>10 kg m−2 less than proband).

Results:

Approximately one-third of the transcripts were differentially expressed between lean and obese siblings. The cellular adhesion molecules (CAMs) KEGG grouping contained the largest number of differentially expressed genes under cis-acting genetic control. By using a novel approach to contrast CAMs coexpression networks between lean and obese siblings, a subset of differentially regulated genes was identified, with the previously GWAS obesity-associated neuronal growth regulator 1 (NEGR1) as a central hub. Independent analysis using mouse data demonstrated that this finding of NEGR1 is conserved across species.

Conclusion:

Our data suggest that in addition to its reported role in the brain, NEGR1 is also expressed in subcutaneous adipose tissue and acts as a central ‘hub’ in an obesity-related transcript network.

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Acknowledgements

We wish to acknowledge the participation of all the families and clinical staff involved in the SOS SibPair study. We thank Professor Eric Schadt for advice and the provision of the mouse data set and the staff of the Imperial College High-Performance Computing Service for their advice and support. This study was funded by Grant no. 079534/z/06/z from the Wellcome Trust, the Swedish Research Council (K2010-55X-11285-13), the Swedish foundation for Strategic Research to Sahlgrenska Center for Cardiovascular and Metabolic Research, the Swedish Diabetes foundation and the Swedish federal government under the LUA/ALF agreement. Sylvia Richardson acknowledges support from the MRC Grant G0600609.

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Author notes

  1. A J Walley, P Jacobson, M Falchi, L M S Carlsson and P Froguel: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK

    A J Walley, M Falchi, L Bottolo, J C Andersson, D Balding, M Petteni, Y S Park & P Froguel

  2. Department of Molecular and Clinical Medicine, The Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden

    P Jacobson, J C Andersson, M Jernas, L Sjostrom & L M S Carlsson

  3. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Marys Hospital, London, UK

    L Bottolo, E Petretto & S Richardson

  4. Division of Clinical Sciences, MRC Clinical Sciences Centre, Imperial College London, Commonwealth Building, Hammersmith Hospital, London, UK

    E Petretto & T Aitman

  5. CNRS 8090-Institute of Biology, Pasteur Institute, Lille, France

    A Bonnefond, E Vaillant, C Lecoeur, V Vatin & P Froguel

  6. Institute of Genetics, University College London, Kathleen Lonsdale Building, London, UK

    D Balding

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  1. A J Walley
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Correspondence to P Froguel.

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Walley, A., Jacobson, P., Falchi, M. et al. Differential coexpression analysis of obesity-associated networks in human subcutaneous adipose tissue. Int J Obes 36, 137–147 (2012). https://doi.org/10.1038/ijo.2011.22

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