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  • Original Article
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Genetic variation in SH3-domain GRB2-like (endophilin)-interacting protein 1 has a major impact on fat mass

International Journal of Obesity volume 36, pages 201–206 (2012)Cite this article

Abstract

Objective:

The SH3-domain GRB2-like (endophilin)-interacting protein 1 (SGIP1) gene has been shown to be differentially expressed in the hypothalamus of lean versus obese Israeli sand rats (Psammomys obesus), and is suspected of having a role in regulating food intake. The purpose of this study was to assess the role of genetic variation in SGIP1 in human disease.

Subjects:

We performed single-nucleotide polymorphism (SNP) genotyping in a large family pedigree cohort from the island of Mauritius. The Mauritius Family Study (MFS) consists of 400 individuals from 24 Indo-Mauritian families recruited from the genetically homogeneous population of Mauritius. We measured markers of the metabolic syndrome, including diabetes and obesity-related phenotypes such as fasting plasma glucose, waist:hip ratio, body mass index and fat mass.

Results:

Statistical genetic analysis revealed associations between SGIP1 polymorphisms and fat mass (in kilograms) as measured by bioimpedance. SNP genotyping identified associations between several genetic variants and fat mass, with the strongest association for rs2146905 (P=4.7 × 10−5). A strong allelic effect was noted for several SNPs where fat mass was reduced by up to 9.4% for individuals homozygous for the minor allele.

Conclusions:

Our results show association between genetic variants in SGIP1 and fat mass. We provide evidence that variation in SGIP1 is a potentially important determinant of obesity-related traits in humans.

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References

  1. WHO. World Health Organisation Factsheet No.311. WHO: Geneva, 2005.

  2. Shaw JE, Sicree RA, Zimmet PZ . Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010; 87: 4–14.

    Article  CAS  PubMed  Google Scholar 

  3. Barsh GS, Schwartz MW . Genetic approaches to studying energy balance: perception and integration. Nat Rev Genet 2002; 3: 589–600.

    Article  CAS  PubMed  Google Scholar 

  4. Schwartz MW, Woods SC, Porte Jr D, Seeley RJ, Baskin DG . Central nervous system control of food intake. Nature 2000; 404: 661–671.

    Article  CAS  PubMed  Google Scholar 

  5. Benzinou M, Chevre JC, Ward KJ, Lecoeur C, Dina C, Lobbens S et al. Endocannabinoid receptor 1 gene variations increase risk for obesity and modulate body mass index in European populations. Hum Mol Genet 2008; 17: 1916–1921.

    Article  CAS  PubMed  Google Scholar 

  6. Jackson RS, Creemers JW, Ohagi S, Raffin-Sanson ML, Sanders L, Montague CT et al. Obesity and impaired prohormone processing associated with mutations in the human prohormone convertase 1 gene. Nat Genet 1997; 16: 303–306.

    Article  CAS  PubMed  Google Scholar 

  7. Lange LA, Norris JM, Langefeld CD, Nicklas BJ, Wagenknecht LE, Saad MF et al. Association of adipose tissue deposition and beta-2 adrenergic receptor variants: the IRAS family study. Int J Obes (Lond) 2005; 29: 449–457.

    Article  CAS  Google Scholar 

  8. Loos RJ, Rankinen T, Tremblay A, Perusse L, Chagnon Y, Bouchard C . Melanocortin-4 receptor gene and physical activity in the Quebec Family Study. Int J Obes (Lond) 2005; 29: 420–428.

    Article  CAS  Google Scholar 

  9. Ribases M, Gratacos M, Fernandez-Aranda F, Bellodi L, Boni C, Anderluh M et al. Association of BDNF with restricting anorexia nervosa and minimum body mass index: a family-based association study of eight European populations. Eur J Hum Genet 2005; 13: 428–434.

    Article  CAS  PubMed  Google Scholar 

  10. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T et al. A common genetic variant is associated with adult and childhood obesity. Science 2006; 312: 279–283.

    Article  CAS  PubMed  Google Scholar 

  11. Liu YJ, Liu XG, Wang L, Dina C, Yan H, Liu JF et al. Genome-wide association scans identified CTNNBL1 as a novel gene for obesity. Hum Mol Genet 2008; 17: 1803–1813.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Meyre D, Delplanque J, Chevre JC, Lecoeur C, Lobbens S, Gallina S et al. Genome-wide association study for early-onset and morbid adult obesity identifies three new risk loci in European populations. Nat Genet 2009; 41: 157–159.

    Article  CAS  PubMed  Google Scholar 

  13. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci USA 2009; 106: 9362–9367.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Barnett M, Collier GR, Collier FM, Zimmet P, O’Dea K . A cross-sectional and short-term longitudinal characterisation of NIDDM in Psammomys obesus. Diabetologia 1994; 37: 671–676.

    Article  CAS  PubMed  Google Scholar 

  15. Collier GR, Walder K, Lewandowski P, Sanigorski A, Zimmet P . Leptin and the development of obesity and diabetes in Psammomys obesus. Obes Res 1997; 5: 455–458.

    Article  CAS  PubMed  Google Scholar 

  16. Trevaskis J, Walder K, Foletta V, Kerr-Bayles L, McMillan J, Cooper A et al. Src homology 3-domain growth factor receptor-bound 2-like (endophilin) interacting protein 1, a novel neuronal protein that regulates energy balance. Endocrinology 2005; 146: 3757–3764.

    Article  CAS  PubMed  Google Scholar 

  17. Walder KR, Fahey RP, Morton GJ, Zimmet PZ, Collier GR . Characterization of obesity phenotypes in Psammomys obesus (Israeli sand rats). Int J Exp Diabetes Res 2000; 1: 177–184.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Jowett JB, Elliott KS, Curran JE, Hunt N, Walder KR, Collier GR et al. Genetic variation in BEACON influences quantitative variation in metabolic syndrome-related phenotypes. Diabetes 2004; 53: 2467–2472.

    Article  CAS  PubMed  Google Scholar 

  19. Collier GR, McMillan JS, Windmill K, Walder K, Tenne-Brown J, de Silva A et al. Beacon: a novel gene involved in the regulation of energy balance. Diabetes 2000; 49: 1766–1771.

    Article  CAS  PubMed  Google Scholar 

  20. Curran JE, Jowett JB, Elliott KS, Gao Y, Gluschenko K, Wang J et al. Genetic variation in selenoprotein S influences inflammatory response. Nat Genet 2005; 37: 1234–1241.

    Article  CAS  PubMed  Google Scholar 

  21. Uezu A, Horiuchi A, Kanda K, Kikuchi N, Umeda K, Tsujita K et al. SGIP1alpha is an endocytic protein that directly interacts with phospholipids and Eps15. J Biol Chem 2007; 282: 26481–26489.

    Article  CAS  PubMed  Google Scholar 

  22. Shmulewitz D, Heath SC, Blundell ML, Han Z, Sharma R, Salit J et al. Linkage analysis of quantitative traits for obesity, diabetes, hypertension, and dyslipidemia on the island of Kosrae, Federated States of Micronesia. Proc Natl Acad Sci USA 2006; 103: 3502–3509.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Jowett JB, Diego VP, Kotea N, Kowlessur S, Chitson P, Dyer TD et al. Genetic influences on type 2 diabetes and metabolic syndrome related quantitative traits in Mauritius. Twin Res Hum Genet 2009; 12: 44–52.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Boehnke M . Allele frequency estimation from data on relatives. Am J Hum Genet 1991; 48: 22–25.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Almasy L, Blangero J . Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 1998; 62: 1198–1211.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Blangero J, Goring HH, Kent Jr JW, Williams JT, Peterson CP, Almasy L et al. Quantitative trait nucleotide analysis using Bayesian model selection. Hum Biol 2005; 77: 541–559.

    Article  PubMed  Google Scholar 

  27. Boerwinkle E, Chakraborty R, Sing CF . The use of measured genotype information in the analysis of quantitative phenotypes in man. I. Models and analytical methods. Ann Hum Genet 1986; 50: 181–194.

    Article  CAS  PubMed  Google Scholar 

  28. Abecasis GR, Cookson WO, Cardon LR . Pedigree tests of transmission disequilibrium. Eur J Hum Genet 2000; 8: 545–551.

    Article  CAS  PubMed  Google Scholar 

  29. Havill LM, Dyer TD, Richardson DK, Mahaney MC, Blangero J . The quantitative trait linkage disequilibrium test: a more powerful alternative to the quantitative transmission disequilibrium test for use in the absence of population stratification. BMC Genet 2005; 6 (Suppl 1): S91.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Li J, Ji L . Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 2005; 95: 221–227.

    Article  CAS  PubMed  Google Scholar 

  31. Nyholt DR . A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet 2004; 74: 765–769.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Cummings N, Dyer TD, Kotea N, Kowlessur S, Chitson P, Zimmet P et al. Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate. Eur J Hum Genet 2010; 18: 1243–1247.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Cheverud JM . A simple correction for multiple comparisons in interval mapping genome scans. Heredity 2001; 87: 52–58.

    Article  CAS  PubMed  Google Scholar 

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Author information

Author notes

  1. N Cummings and K A Shields: These authors contributed equally to this work.

Authors and Affiliations

  1. Genomics and Systems Biology, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia

    N Cummings, K A Shields, K Bozaoglu, K Gluschenko, P Zimmet & J B M Jowett

  2. Southwest Foundation for Biomedical Research, San Antonio, TX, USA

    J E Curran, G Cai, A G Comuzzie, T D Dyer & J Blangero

  3. Metabolic Research Unit, Faculty of Health, Medicine, Nursing and Behavioural Sciences, Deakin University, Waurn Ponds, Victoria, Australia

    J Trevaskis & K R Walder

  4. Chemgenex Pharmaceuticals, Geelong, Victoria, Australia

    G R Collier

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  1. N Cummings
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Correspondence to J B M Jowett.

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Cummings, N., Shields, K., Curran, J. et al. Genetic variation in SH3-domain GRB2-like (endophilin)-interacting protein 1 has a major impact on fat mass. Int J Obes 36, 201–206 (2012). https://doi.org/10.1038/ijo.2011.67

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  • DOI: https://doi.org/10.1038/ijo.2011.67

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