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Targeting the association of calgranulin B (S100A9) with insulin resistance and type 2 diabetes

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An Erratum to this article was published on 08 March 2013

Abstract

Calgranulin B (S100A9) was recognized as a candidate type 2 diabetes (T2D) gene in the genomic profiling of muscle from a rodent model of T2D and identifying the human orthologs of genes localized in T2D susceptibility regions. Circulating and S100A9 expressions in muscle and adipose tissue, isolated fat cells, and mouse models were evaluated. A common 5′-upstream single-nucleotide polymorphism (SNP; rs3014866) for S100A9 was analyzed, as well as the effects of weight loss and treatments in vitro with recombinant S100A9. S100a9 expression was increased in muscle of diabetic mice (1.6-fold, p = 0.002), and in muscle from subjects with impaired glucose tolerance (∼4-fold, p = 0.028; n = 34). The rs3014866 SNP was associated with circulating S100A9 and the risk of T2D, having TT carriers at 28 % (p = 0.03) lower risk (n = 1,450). Indeed, increased circulating S100A9 (∼4-fold, p = 0.03; n = 206) and subcutaneous (2-fold, p = 0.01) and omental (1.4-fold, p = 0.04) S100A9 gene expressions (n = 83) in TT carriers run in parallel to decreased fasting glucose and glycated hemoglobin. Accordingly, metformin led to increased S100A9 mRNA in ex vivo-treated adipose tissue explants (n = 5/treatment). Otherwise, obese subjects showed a compensatory increase in circulating and S100A9 expressions in adipose (n = 126), as further demonstrated by decreased levels after diet- (−34 %, p = 0.002; n = 20) and surgery-induced (−58 %, p = 0.02; n = 8) weight loss. Lipopolysaccharide led to increased S100A9 in adipose from mice (n = 5/treatment) while recombinant S100A9 downregulated inflammation in adipocytes (n = 3/treatment). Current findings support the strategy of testing differentially expressed genes in mice and human orthologs associated with T2D. The increased S100A9 reported for obesity and insulin resistance may be envisioned as a compensatory mechanism for inflammation.

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Acknowledgments

We greatly appreciate the technical assistance of Gerard Pardo and Oscar Rovira (Unit of Diabetes, Endocrinology and Nutrition, Institut d’Investigació Biomèdica de Girona (IdIBGi) and Hospital Universitari Dr. Josep Trueta de Girona). The work of all the members of the Multidisciplinary Obesity Team of the Clínica Universitaria de Navarra is gratefully acknowledged. GenDiab Consortium was constituted with funds from the Ministerio de Educación y Ciencia (grant GEN2001-4758). This work was also supported by research grants from the Ministerio de Educación y Ciencia (SAF2005-02073 and SAF2008-02073), Generalitat de Catalunya 265, and the Instituto de Salud Carlos III (ISCIIIRETIC RD06, REDIMET, and CIBERDEM). JMM was supported by Sara Borrell fellowship from the Instituto de Salud Carlos III. RB is a recipient of a funding from the Agence Nationale de la Recherche (Florinflam and Floradip programs) as well as from L’Institute Nationale du Diabète. JMF-R is the guarantor of this work, had full access to all the data, and takes full responsibility for the integrity of data and the accuracy of data analysis.

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Authors and Affiliations

  1. Department of Diabetes, Endocrinology and Nutrition (UDEN), Institut d’Investigació Biomédica de Girona (IdIBGi), CIBER de la Fisiopatología de la Obesidad y la Nutrición (CIBERobn, CB06/03/0010) and Instituto de Salud Carlos III (ISCIII), Girona, Spain

    Francisco J. Ortega, José M. Moreno-Navarrete, Mónica Sabater, Neus Pueyo, Wifredo Ricart & José M. Fernández-Real

  2. Joint IRB-BSC Program on Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain

    Josep M. Mercader

  3. Service of Endocrinology and Nutrition, Hospital Universitario Carlos Haya, CIBER of Diabetes and Metabolism (CIBERdem, CB07/08) and Instituto de Salud Carlos III (ISCIII), Málaga, Spain

    Sergio Valdés

  4. Department of Surgery, Institut d’Investigació Biomédica de Girona (IdIBGi), Girona, Spain

    Bartomeu Ruiz

  5. INSERM Unité 858, Institut de Médecine Moléculaire de Rangueil, Université Paul Sabatier, IFR31, Toulouse, France

    Elodie Luche & Remy Burcelin

  6. Departament de Bioquímica i Biología Molecular, Facultat de Biología, Universitat de Barcelona, Institute for Research in Biomedicine (IRB Barcelona), CIBER of Diabetes and Metabolism (CIBERdem, CB07/08) and Instituto de Salud Carlos III (ISCIII), Barcelona, Spain

    Deborah Naon & Antonio Zorzano

  7. Hospital Central de Asturias, Oviedo, Spain

    Patricia Botas & Elias Delgado

  8. Clínica Universitaria de Navarra, CIBER de la Fisiopatología de la Obesidad y la Nutrición (CIBERobn, CB06/03/0010) and Instituto de Salud Carlos III (ISCIII), Pamplona, Spain

    Gema Frühbeck

  9. Center of Animal Biotechnology and Gene Therapy (CBATEG), Universitat Autònoma de Barcelona, Bellaterra, Spain

    Fatima Bosch

  10. Institute of Internal Medicine, Catholic University of Rome, Rome, Italy

    Gertrude Mingrone

  11. Section of Diabetes, Endocrinology and Nutrition, Hospital of Girona “Dr Josep Trueta” Carretera de França s/n, 17007, Girona, Spain

    José M. Fernández-Real

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  1. Francisco J. Ortega
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  11. Patricia Botas
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  18. José M. Fernández-Real
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Correspondence to José M. Fernández-Real.

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Ortega, F.J., Mercader, J.M., Moreno-Navarrete, J.M. et al. Targeting the association of calgranulin B (S100A9) with insulin resistance and type 2 diabetes. J Mol Med 91, 523–534 (2013). https://doi.org/10.1007/s00109-012-0979-8

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