Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Genetic variations in regulatory pathways of fatty acid and glucose metabolism are associated with obesity phenotypes: a population-based cohort study

International Journal of Obesity volume 33, pages 1143–1152 (2009)Cite this article

Abstract

Background:

As nuclear receptors and transcription factors have an important regulatory function in adipocyte differentiation and fat storage, genetic variation in these key regulators and downstream pathways may be involved in the onset of obesity.

Objective:

To explore associations between single nucleotide polymorphisms (SNPs) in candidate genes from regulatory pathways that control fatty acid and glucose metabolism, and repeated measurements of body mass index (BMI) and waist circumference in a large Dutch study population.

Methods:

Data of 327 SNPs across 239 genes were analyzed for 3575 participants of the Doetinchem cohort, who were examined three times during 11 years, using the Illumina Golden Gate assay. Adjusted random coefficient models were used to analyze the relationship between SNPS and obesity phenotypes. False discovery rate q-values were calculated to account for multiple testing. Significance of the associations was defined as a q-value ⩽0.20.

Results:

Two SNPs (in NR1H4 and SMARCA2 in women only) were significantly associated with both BMI and waist circumference. In addition, two SNPs (in SIRT1 and SCAP in women only) were associated with BMI alone. A functional SNP, in IL6, was strongly associated with waist.

Conclusion:

In this explorative study among participants of a large population-based cohort, five SNPs, mainly located in transcription mediator genes, were strongly associated with obesity phenotypes. The results from whole genome and candidate gene studies support the potential role of NR1H4, SIRT1, SMARCA2 and IL6 in obesity. Although replication of our findings and further research on the functionality of these SNPs and underlying mechanism is necessary, our data indirectly suggest a role of GATA transcription factors in weight control.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2

Similar content being viewed by others

References

  1. World Health Organization. Fact sheet N 311 Obesity and overweight. Http://Www.Who.Int/Mediacentre/Factsheets/Fs311/En/Index.Html 2006.

  2. Wang Y, Lobstein T . Worldwide trends in childhood overweight and obesity. Int J Pediatr Obes 2006; 1: 11–25.

    Article  PubMed  Google Scholar 

  3. Kopelman PG . Obesity as a medical problem. Nature 2000; 404: 635–643.

    Article  CAS  PubMed  Google Scholar 

  4. Anandacoomarasamy A, Caterson I, Sambrook P, Fransen M, March L . The impact of obesity on the musculoskeletal system. Int J Obes 2008; 32: 211–222.

    Article  CAS  Google Scholar 

  5. Mathers CD, Loncar D . Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006; 3: e442.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Yang W, Kelly T, He J . Genetic epidemiology of obesity. Epidemiol Rev 2007; 29: 49–61.

    Article  PubMed  Google Scholar 

  7. Lean ME, Han TS, Morrison CE . Waist circumference as a measure for indicating need for weight management. BMJ 1995; 311: 158–161.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Rankinen T, Zuberi A, Chagnon YC, Weisnagel SJ, Argyropoulos G, Walts B . et al. The human obesity gene map: the 2005 update. Obesity 2006; 14: 529–644.

    Article  PubMed  Google Scholar 

  9. Loos RJ, Bouchard C . Obesity—is it a genetic disorder? J Intern Med 2003; 254: 401–425.

    Article  CAS  PubMed  Google Scholar 

  10. Bell CG, Walley AJ, Froguel P . The genetics of human obesity. Nat Rev Genet 2005; 6: 221–234.

    Article  CAS  PubMed  Google Scholar 

  11. Hunt MS, Katzmarzyk PT, Perusse L, Rice T, Rao DC, Bouchard C . Familial resemblance of 7-year changes in body mass and adiposity. Obes Res 2002; 10: 507–517.

    Article  PubMed  Google Scholar 

  12. Tonjes A, Scholz M, Loeffler M, Stumvoll M . Association of Pro12Ala polymorphism in peroxisome proliferator-activated receptor gamma with pre-diabetic phenotypes: meta-analysis of 57 studies on nondiabetic individuals. Diabetes Care 2006; 29: 2489–2497.

    Article  PubMed  Google Scholar 

  13. Young EH, Wareham NJ, Farooqi S, Hinney A, Hebebrand J, Scherag A et al. The V103I polymorphism of the MC4R gene and obesity: population based studies and meta-analysis of 29 563 individuals. Int J Obes 2007; 31: 1437–1441.

    Article  CAS  Google Scholar 

  14. Sookoian SC, Gonzalez C, Pirola CJ . Meta-analysis on the G-308A tumor necrosis factor alpha gene variant and phenotypes associated with the metabolic syndrome. Obes Res 2005; 13: 2122–2131.

    Article  PubMed  Google Scholar 

  15. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007; 316: 889–894.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Benzinou M, Creemers JW, Choquet H, Lobbens S, Dina C, Durand E et al. Common nonsynonymous variants in PCSK1 confer risk of obesity. Nat Genet 2008; 40: 943–945.

    Article  CAS  PubMed  Google Scholar 

  17. Hattersley AT, McCarthy MI . What makes a good genetic association study? Lancet 2005; 366: 1315–1323.

    Article  PubMed  Google Scholar 

  18. Marvelle AF, Lange LA, Qin L, Adair LS, Mohlke KL . Association of FTO with obesity-related traits in the Cebu Longitudinal Health and Nutrition Survey (CLHNS) Cohort. Diabetes 2008; 57: 1987–1991.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Dolley G, Bertrais S, Frochot V, Bebel JF, Guerre-Millo M, Tores F et al. Promoter adiponectin polymorphisms and waist/hip ratio variation in a prospective French adults study. Int J Obes 2008; 32: 669–675.

    Article  CAS  Google Scholar 

  20. Snieder H, Wang X, Shiri-Sverdlov R, van Vliet-Ostaptchouk JV, Hofker MH, Perks U et al. TUB is a candidate gene for late-onset obesity in women. Diabetologia 2008; 51: 54–61.

    Article  CAS  PubMed  Google Scholar 

  21. 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 

  22. 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 

  23. Loos RJ, Lindgren CM, Li S, Wheeler E, Zhao JH, Prokopenko I et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet 2008; 40: 768–775.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Sorensen TI, Boutin P, Taylor MA, Larsen LH, Verdich C, Petersen L et al. Genetic polymorphisms and weight loss in obesity: a randomised trial of hypo-energetic high- versus low-fat diets. PLoS Clin Trials 2006; 1: e12.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Desvergne B, Michalik L, Wahli W . Transcriptional regulation of metabolism. Physiol Rev 2006; 86: 465–514.

    Article  CAS  PubMed  Google Scholar 

  26. Verschuren WMM, Blokstra A, Picavet HSJ, Smit HA . Cohort profile: the Doetinchem Cohort Study. Int J Epidemiol 2008; 37: 1236–1241.

    Article  CAS  PubMed  Google Scholar 

  27. World Health Organisation. Measuring Obesity—Classification and Description of Anthropometric Data. Regional Office for Europe. EUR/ICP/NUT 125, 1989.

  28. Hoebee B, Rietveld E, Bont L, Oosten M, Hodemaekers HM, Nagelkerke NJ et al. Association of severe respiratory syncytial virus bronchiolitis with interleukin-4 and interleukin-4 receptor alpha polymorphisms. J Infect Dis 2003; 187: 2–11.

    Article  CAS  PubMed  Google Scholar 

  29. Becker KG, Barnes KC, Bright TJ, Wang SA . The genetic association database. Nat Genet 2004; 36: 431–432.

    Article  CAS  PubMed  Google Scholar 

  30. Riva A, Kohane IS . A SNP-centric database for the investigation of the human genome. BMC Bioinformatics 2004; 5: 33.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Xu H, Gregory SG, Hauser ER, Stenger JE, Pericak-Vance MA, Vance JM et al. SNPselector: a web tool for selecting SNPs for genetic association studies. Bioinformatics 2005; 21: 4181–4186.

    Article  CAS  PubMed  Google Scholar 

  32. Fan JB, Chee MS, Gunderson KL . Highly parallel genomic assays. Nat Rev Genet 2006; 7: 632–644.

    Article  CAS  PubMed  Google Scholar 

  33. Twisk JWR . Applied Longitudinal Data Analysis for Epidemiology, A Practical Guide. Press Syndicate of the University of Cambridge: Cambridge, 2003.

    Google Scholar 

  34. Benjamini Y, Yekutieli D . Quantitative trait Loci analysis using the false discovery rate. Genetics 2005; 171: 783–790.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Allison DB, Cui X, Page GP, Sabripour M . Microarray data analysis: from disarray to consolidation and consensus. Nat Rev Genet 2006; 7: 55–65.

    Article  CAS  PubMed  Google Scholar 

  36. Smith NL, Hindorff LA, Heckbert SR, Lemaitre RN, Marciante KD, Rice K et al. Association of genetic variations with nonfatal venous thrombosis in postmenopausal women. JAMA 2007; 297: 489–498.

    Article  CAS  PubMed  Google Scholar 

  37. Wang B, Zhao H, Zhou L, Dai X, Wang D, Cao J et al. Association of genetic variation in apolipoprotein E and low density lipoprotein receptor with ischemic stroke in Northern Han Chinese. J Neurol Sci 2009; 276: 118–122.

    Article  CAS  PubMed  Google Scholar 

  38. Ferrari SL, Ahn-Luong L, Garnero P, Humphries SE, Greenspan SL . Two promoter polymorphisms regulating interleukin-6 gene expression are associated with circulating levels of C-reactive protein and markers of bone resorption in postmenopausal women. J Clin Endocrinol Metab 2003; 88: 255–259.

    Article  CAS  PubMed  Google Scholar 

  39. Cancello R, Tounian A, Poitou Ch, Clement K . Adiposity signals, genetic and body weight regulation in humans. Diabetes Metab 2004; 30: 215–227.

    Article  CAS  PubMed  Google Scholar 

  40. Slattery ML, Curtin K, Sweeney C, Wolff RK, Baumgartner RN, Baumgartner KB et al. Modifying effects of IL-6 polymorphisms on body size-associated breast cancer risk. Obesity 2008; 16: 339–347.

    Article  CAS  PubMed  Google Scholar 

  41. Hamid YH, Rose CS, Urhammer SA, Glumer C, Nolsoe R, Kristiansen OP et al. Variations of the interleukin-6 promoter are associated with features of the metabolic syndrome in Caucasian Danes. Diabetologia 2005; 48: 251–260.

    Article  CAS  PubMed  Google Scholar 

  42. Qi L, Zhang C, van Dam RM, Hu FB . Interleukin-6 genetic variability and adiposity: associations in two prospective cohorts and systematic review in 26,944 individuals. J Clin Endocrinol Metab 2007; 92: 3618–3625.

    Article  CAS  PubMed  Google Scholar 

  43. Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 2007; 316: 1331–1336.

    Article  CAS  PubMed  Google Scholar 

  44. Rodgers JT, Lerin C, Haas W, Gygi SP, Spiegelman BM, Puigserver P . Nutrient control of glucose homeostasis through a complex of PGC-1alpha and SIRT1. Nature 2005; 434: 113–118.

    Article  CAS  PubMed  Google Scholar 

  45. Fox CS, Heard-Costa N, Cupples LA, Dupuis J, Vasan RS, Atwood LD . Genome-wide association to body mass index and waist circumference: the Framingham Heart Study 100 K project. BMC Med Genet 2007; 8 (Suppl 1): S18.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Watanabe M, Houten SM, Mataki C, Christoffolete MA, Kim BW, Sato H et al. Bile acids induce energy expenditure by promoting intracellular thyroid hormone activation. Nature 2006; 439: 484–489.

    Article  CAS  PubMed  Google Scholar 

  47. Horton JD, Goldstein JL, Brown MS . SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver. J Clin Invest 2002; 109: 1125–1131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Le Hellard S, Theisen FM, Haberhausen M, Raeder MB, Ferno J, Gebhardt S et al. Association between the insulin-induced gene 2 (INSIG2) and weight gain in a German sample of antipsychotic-treated schizophrenic patients: perturbation of SREBP-controlled lipogenesis in drug-related metabolic adverse effects? Mol Psychiatry 2008; 14: 308–317.

    Article  PubMed  Google Scholar 

  49. Nieminen T, Matinheikki J, Nenonen A, Kukkonen-Harjula K, Lindi V, Hamelahti P et al. The relationship of sterol regulatory element-binding protein cleavage-activation protein and apolipoprotein E gene polymorphisms with metabolic changes during weight reduction. Metabolism 2007; 56: 876–880.

    Article  CAS  PubMed  Google Scholar 

  50. Mangelsdorf DJ, Evans RM . The RXR heterodimers and orphan receptors. Cell 1995; 83: 841–850.

    Article  CAS  PubMed  Google Scholar 

  51. Xu L, Glass CK, Rosenfeld MG . Coactivator and corepressor complexes in nuclear receptor function. Curr Opin Genet Dev 1999; 9: 140–147.

    Article  CAS  PubMed  Google Scholar 

  52. Muchardt C, Yaniv M . ATP-dependent chromatin remodelling: SWI/SNF and Co. are on the job. J Mol Biol 1999; 293: 187–198.

    Article  CAS  PubMed  Google Scholar 

  53. Fischle W, Dequiedt F, Hendzel MJ, Guenther MG, Lazar MA, Voelter W et al. Enzymatic activity associated with class II HDACs is dependent on a multiprotein complex containing HDAC3 and SMRT/N-CoR. Mol Cell 2002; 9: 45–57.

    Article  CAS  PubMed  Google Scholar 

  54. Xu J, Li Q . Review of the in vivo functions of the p160 steroid receptor coactivator family. Mol Endocrinol 2003; 17: 1681–1692.

    Article  CAS  PubMed  Google Scholar 

  55. Misra P, Qi C, Yu S, Shah SH, Cao WQ, Rao MS et al. Interaction of PIMT with transcriptional coactivators CBP, p300, and PBP differential role in transcriptional regulation. J Biol Chem 2002; 277: 20011–20019.

    Article  CAS  PubMed  Google Scholar 

  56. Puigserver P, Spiegelman BM . Peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PGC-1 alpha): transcriptional coactivator and metabolic regulator. Endocr Rev 2003; 24: 78–90.

    Article  CAS  PubMed  Google Scholar 

  57. Oishi Y, Manabe I, Tobe K, Ohsugi M, Kubota T, Fujiu K et al. SUMOylation of Kruppel-like transcription factor 5 acts as a molecular switch in transcriptional programs of lipid metabolism involving PPAR-delta. Nat Med 2008; 14: 656–666.

    Article  CAS  PubMed  Google Scholar 

  58. Tong Q, Tsai J, Tan G, Dalgin G, Hotamisligil GS . Interaction between GATA and the C/EBP family of transcription factors is critical in GATA-mediated suppression of adipocyte differentiation. Mol Cell Biol 2005; 25: 706–715.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank the epidemiologists and fieldworkers of the Municipal Health Service in Doetinchem for their contribution to the data collection for this study. Logistic management was provided by J Steenbrink and P Vissink, and administrative support by EP van der Wolf. Data management was provided by A Blokstra, AWD van Kessel and PE Steinberger. Genotyping assistance was provided by HM Hodemaekers. This study was financially supported by the National Institute for Public Health and the Environment and the Ministry of Health, Welfare and Sport of The Netherlands.

Author information

Author notes

  1. S W van den Berg and M E T Dollé: These authors contributed equally to this work.

Authors and Affiliations

  1. National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands

    S W van den Berg, M E T Dollé, S Imholz, D L van der A, W M M Verschuren, C Strien, C L E Siezen, B Hoebee & J M A Boer

  2. Department of Biomedical Genetics, Complex Genetics Section, University Medical Center Utrecht, Utrecht, The Netherlands

    R van ‘t Slot & C Wijmenga

  3. Department of genetics, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands

    C Wijmenga

  4. Division of Human Nutrition, Wageningen University and Research Centre, Wageningen, The Netherlands

    E J M Feskens

Authors
  1. S W van den Berg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M E T Dollé
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S Imholz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D L van der A
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. R van ‘t Slot
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C Wijmenga
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. W M M Verschuren
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. C Strien
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. C L E Siezen
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. B Hoebee
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. E J M Feskens
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. J M A Boer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S W van den Berg.

Additional information

Supplementary Information accompanies the paper on International Journal of Obesity website (http://www.nature.com/ijo)

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Cite this article

van den Berg, S., Dollé, M., Imholz, S. et al. Genetic variations in regulatory pathways of fatty acid and glucose metabolism are associated with obesity phenotypes: a population-based cohort study. Int J Obes 33, 1143–1152 (2009). https://doi.org/10.1038/ijo.2009.152

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijo.2009.152

Keywords

This article is cited by

Search

Advanced search

Quick links