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  • Pediatric Original Article
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Study of eight GWAS-identified common variants for association with obesity-related indices in Chinese children at puberty

International Journal of Obesity volume 36, pages 542–547 (2012)Cite this article

Abstract

OBJECTIVE:

Genome-wide association studies (GWAS) have identified some common variants associated with obesity risk in European descents. However, their influences on obesity-related indices for the Chinese children at puberty are not widely clear yet. To address this question, we conducted a study that aims to examine effects of eight previously reported GWAS single-nucleotide polymorphisms (SNPs) on four obesity-related indices in a sample of Chinese children aged 10–12 years.

METHODS:

Anthropometric indices were measured in 1688 children (10.8±0.4 years, boys=877, girls=811) from Shanghai Children’s Sleep Project. Eight SNPs within the NEGR1, TMEM18, GNPDA2, MTCH2, SH2B1, FTO, MC4R and KCTD15 genes were genotyped using matrix-assisted laser desorption/ionization–time of flight mass spectrometry. Linear regression and genetic additive model were used to test for the association betweens SNPs and obesity-related indices (weight, body mass index (BMI), waist-to-height ratio and body fat).

RESULTS:

Only two SNPs, rs6548238 (TMEM18) and rs9939609 (FTO), were associated with all obesity-related indices with P<0.05. After adjusting for multiple tests, rs9939609 is the only one significantly associated with the indices. SNPs, rs6548238 and rs9939609 explained 0.28% (P=0.03) and 0.54% (P=0.002) variance of BMI, respectively, that are almost two-fold of the previously GWAS-reported effects. In addition, rs6548238 was associated with four indices in boys, but not in girls. In contrast, rs9939609 showed a strong association only in girls. Six other SNPs, rs2815752 (NEGR1), rs10938397 (GNPDA2), rs10838738 (MTCH2), rs7498665 (SH2B1), rs17782313 (MC4R) and rs11084753 (KCTD15), were not associated with obesity (P>0.05).

CONCLUSIONS:

Variants of TMEM18 and FTO are associated with obesity indices during puberty in Chinese children, but candidate SNPs of NEGR1, GNPDA2, MTCH2, SH2B1, MC4R and KCTD15 have no significant effects on obesity indices. The findings also suggest that obesity susceptibility genes may exert more obvious effects during children’s puberty. In addition, gender differences may exist in various obesity-related genes.

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References

  1. Haslam DW, James WP . Obesity. Lancet 2005; 366: 1197–1209.

    Article  Google Scholar 

  2. Bjørge T, Engeland A, Tverdal A, Smith GD . Body mass index in adolescence in relation to cause-specific mortality: a follow-up of 230,000 Norwegian adolescents. Am J Epidemiol 2008; 168: 30–37.

    Article  Google Scholar 

  3. Franks PW, Hanson RL, Knowler WC, Sievers ML, Bennett PH, Looker HC . Childhood obesity, other cardiovascular risk factors, and premature death. N Engl J Med 2010; 362: 485–493.

    Article  CAS  Google Scholar 

  4. de Onis M, Blössner M, Borghi E . Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr 2010; 92: 1257–1264.

    Article  CAS  Google Scholar 

  5. Han JC, Lawlor DA, Kimm SY . Childhood obesity. Lancet 2010; 375: 1737–1748.

    Article  Google Scholar 

  6. Walley AJ, Asher JE, Froguel P . The genetic contribution to non-syndromic human obesity. Nat Rev Genet 2009; 10: 431–442.

    Article  CAS  Google Scholar 

  7. Wardle J, Carnell S, Haworth CM, Plomin R . Evidence for a strong genetic influence on childhood adiposity despite the force of the obesogenic environment. Am J Clin Nutr 2008; 87: 398–404.

    Article  CAS  Google Scholar 

  8. 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  Google Scholar 

  9. Dina C, Meyre D, Gallina S, Durand E, Körner A, Jacobson P et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet 2007; 39: 724–726.

    Article  CAS  Google Scholar 

  10. Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 2009; 41: 25–34.

    Article  CAS  Google Scholar 

  11. Renström F, Payne F, Nordström A, Brito EC, Rolandsson O, Hallmans G et al. Replication and extension of genome-wide association study results for obesity in 4923 adults from northern Sweden. Hum Mol Genet 2009; 18: 1489–1496.

    Article  Google Scholar 

  12. Lasky-Su J, Lyon HN, Emilsson V, Heid IM, Molony C, Raby BA et al. On the replication of genetic associations: timing can be everything!. Am J Hum Genet 2008; 82: 849–858.

    Article  CAS  Google Scholar 

  13. de Onis M, Onyango AW, Van den Broeck J, Chumlea WC, Martorell R . Measurement and standardization protocols for anthropometry used in the construction of a new international growth reference. Food Nutr Bull 2004; 25: S27–S36.

    Article  Google Scholar 

  14. Yao XJ, Liu CL, Chen Z, Zhang GY, Wang JH, Wang GL et al. A study on body fat in children aged 7∼l2. Chin J Prev Med 1994; 28: 213–215.

    CAS  Google Scholar 

  15. Emigh TH . A comparison of tests for Hardy-Weinberg equilibrium. Biometrics 1980; 36: 627–642.

    Article  CAS  Google Scholar 

  16. International HapMap Consortium, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007; 449: 851–861.

    Article  Google Scholar 

  17. Romero-Corral A, Somers VK, Sierra-Johnson J, Thomas RJ, Collazo-Clavell ML, Korinek J et al. Accuracy of body mass index in diagnosing obesity in the adult general population. Int J Obes (Lond) 2008; 32: 959–966.

    Article  CAS  Google Scholar 

  18. Stevens J, Nowicki EM . Body mass index and mortality in asian populations: implications for obesity cut-points. Nutr Rev 2003; 61: 104–107.

    Article  Google Scholar 

  19. Demerath EW, Schubert CM, Maynard LM, Sun SS, Chumlea WC, Pickoff A et al. Do changes in body mass index percentile reflect changes in body composition in children? Data from the Fels longitudinal study. Pediatrics 2006; 117: e487–e495.

    Article  Google Scholar 

  20. Bray GA, DeLany JP, Volaufova J, Harsha DW, Champagne C . Prediction of body fat in 12-y-old African American and white children: evaluation of methods. Am J Clin Nutr 2002; 76: 980–990.

    Article  CAS  Google Scholar 

  21. Freedman DS, Wang J, Ogden CL, Thornton JC, Mei Z, Pierson RN et al. The prediction of body fatness by BMI and skinfold thicknesses among children and adolescents. Ann Hum Biol 2007; 34: 183–194.

    Article  Google Scholar 

  22. Ashwell M, Hsieh SD . Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity. Int J Food Sci Nutr 2005; 56: 303–307.

    Article  Google Scholar 

  23. Gauderman WJ . Sample size requirements for association studies of gene-gene interaction. Am J Epidemiol 2002; 155: 478–484.

    Article  Google Scholar 

  24. Loos RJ, Bouchard C . FTO: the first gene contributing to common forms of human obesity. Obes Rev 2008; 9: 246–250.

    Article  CAS  Google Scholar 

  25. McCarthy MI . Genomics, type 2 diabetes, and obesity. N Engl J Med 2010; 363: 2339–2350.

    Article  CAS  Google Scholar 

  26. Scuteri A, Sanna S, Chen WM, Uda M, Albai G, Strait J et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet 2007; 3: e115.

    Article  Google Scholar 

  27. Church C, Moir L, McMurray F, Girard C, Banks GT, Teboul L et al. Overexpression of FTO leads to increased food intake and results in obesity. Nat Genet 2010; 42: 1086–1092.

    Article  CAS  Google Scholar 

  28. Li H, Wu Y, Loos RJ, Hu FB, Liu Y, Wang J et al. Variants in the fat mass- and obesity-associated (FTO) gene are not associated with obesity in a Chinese Han population. Diabetes 2008; 57: 264–268.

    Article  CAS  Google Scholar 

  29. Chang YC, Liu PH, Lee WJ, Chang TJ, Jiang YD, Li HY et al. Common variation in the fat mass and obesity-associated (FTO) gene confers risk of obesity and modulates BMI in the Chinese population. Diabetes 2008; 57: 2245–2252.

    Article  CAS  Google Scholar 

  30. Liu Y, Liu Z, Song Y, Zhou D, Zhang D, Zhao T et al. Meta-analysis added power to identify variants in FTO associated with type 2 diabetes and obesity in the Asian population. Obesity (Silver Spring) 2010; 18: 1619–1624.

    Article  CAS  Google Scholar 

  31. Xi B, Shen Y, Zhang M, Liu X, Zhao X, Wu L et al. The common rs9939609 variant of the fat mass and obesity-associated gene is associated with obesity risk in children and adolescents of Beijing, China. BMC Med Genet 2010; 11: 107.

    Article  Google Scholar 

  32. Fang H, Li Y, Du S, Hu X, Zhang Q, Liu A et al. Variant rs9939609 in the FTO gene is associated with body mass index among Chinese children. BMC Med Genet 2010; 11: 136.

    Article  Google Scholar 

  33. Farooqi IS, Keogh JM, Yeo GS, Lank EJ, Cheetham T, O’Rahilly S . Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med 2003; 348: 1085–1095.

    Article  CAS  Google Scholar 

  34. 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  Google Scholar 

  35. Cheung CY, Tso AW, Cheung BM, Xu A, Ong KL, Fong CH et al. Obesity susceptibility genetic variants identified from recent genome-wide association studies: implications in a chinese population. J Clin Endocrinol Metab 2010; 95: 1395–1403.

    Article  CAS  Google Scholar 

  36. Wu L, Xi B, Zhang M, Shen Y, Zhao X, Cheng H et al. Associations of six single nucleotide polymorphisms in obesity-related genes with BMI and risk of obesity in Chinese children. Diabetes 2010; 59: 3085–3089.

    Article  CAS  Google Scholar 

  37. Grant SF, Bradfield JP, Zhang H, Wang K, Kim CE, Annaiah K et al. Investigation of the locus near MC4R with childhood obesity in Americans of European and African ancestry. Obesity (Silver Spring) 2009; 17: 1461–1465.

    Google Scholar 

  38. Berthoud HR, Morrison C . The brain, appetite, and obesity. Annu Rev Psychol 2008; 59: 55–92.

    Article  Google Scholar 

  39. Holzapfel C, Grallert H, Huth C, Wahl S, Fischer B, Döring A et al. Genes and lifestyle factors in obesity: results from 12,462 subjects from MONICA/KORA. Int J Obes (Lond) 2010; 34: 1538–1545.

    Article  CAS  Google Scholar 

  40. Hotta K, Nakamura M, Nakamura T, Matsuo T, Nakata Y, Kamohara S et al. Association between obesity and polymorphisms in SEC16B, TMEM18, GNPDA2, BDNF, FAIM2 and MC4R in a Japanese population. J Hum Genet 2009; 54: 727–731.

    Article  CAS  Google Scholar 

  41. Dorajoo R, Blakemore AI, Sim X, Ong RT, Ng DP, Seielstad M et al. Replication of 13 obesity loci among Singaporean Chinese, Malay and Asian-Indian populations. Int J Obes (Lond) 2011; e-pub ahead of print 19 April 2011; doi:10.1038/ijo.2011.86.

    Article  Google Scholar 

  42. Almén MS, Jacobsson JA, Shaik JH, Olszewski PK, Cedernaes J, Alsiö J et al. The obesity gene, TMEM18, is of ancient origin, found in majority of neuronal cells in all major brain regions and associated with obesity in severely obese children. BMC Med Genet 2010; 11: 58.

    Article  Google Scholar 

  43. Jurvansuu J, Zhao Y, Leung DS, Boulaire J, Yu YH, Ahmed S et al. Transmembrane protein 18 enhances the tropism of neural stem cells for glioma cells. Cancer Res 2008; 68: 4614–4622.

    Article  CAS  Google Scholar 

  44. Myers AJ, Gibbs JR, Webster JA, Rohrer K, Zhao A, Marlowe L et al. A survey of genetic human cortical gene expression. Nat Genet 2007; 39: 1494–1499.

    Article  CAS  Google Scholar 

  45. Jacobsson JA, Danielsson P, Svensson V, Klovins J, Gyllensten U, Marcus C et al. Major gender difference in association of FTO gene variant among severely obese children with obesity and obesity related phenotypes. Biochem Biophys Res Commun 2008; 368: 476–482.

    Article  CAS  Google Scholar 

  46. Hennig BJ, Fulford AJ, Sirugo G, Rayco-Solon P, Hattersley AT, Frayling TM et al. FTO gene variation and measures of body mass in an African population. BMC Med Genet 2009; 10: 21.

    Article  Google Scholar 

  47. Wisniewski AB, Chernausek SD . Gender in childhood obesity: family environment, hormones, and genes. Gend Med 2009; 6 (Suppl 1): 76–85.

    Article  Google Scholar 

  48. Tanyolaç S, Mahley RW, Hodoglugil U, Goldfine ID . Gender differences in the relationship of ENPP1/PC-1 variants to obesity in a Turkish population. Obesity (Silver Spring) 2008; 16: 2468–2471.

    Article  Google Scholar 

  49. Ben Ali S, Ben Yahia F, Sediri Y, Kallel A, Ftouhi B, Feki M et al. Gender-specific effect of Pro12Ala polymorphism in peroxisome proliferator-activated receptor gamma-2 gene on obesity risk and leptin levels in a Tunisian population. Clin Biochem 2009; 42: 1642–1647.

    Article  CAS  Google Scholar 

  50. Wacker MJ, Godard MP, McCabe EH, Donnelly JE, Kelly JK . Sex difference in the association of the angiotensin converting enzyme I/D polymorphism and body mass index. Med Sci Monit 2008; 14: 353–357.

    Google Scholar 

  51. Fu J, Festen EA, Wijmenga C . Multi-ethnic studies in complex traits. Hum Mol Genet 2011; 20 (R2): R206–R213.

    Article  CAS  Google Scholar 

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Acknowledgements

The study was supported by Ministry of Science and Technology of China (2010CB535000); Chinese National Natural Science Foundation (81172685); Shanghai Science and Technology Commission (10QA1404800); AFINS research project; Shengyuan Research Project and MOE-Shanghai Key Laboratory of Children's Environmental Health (04DZ05904, 06DZ22024).

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Author notes

  1. J Wang and H Mei: These authors contributed equally to this work, and should be considered as co-first author.

Authors and Affiliations

  1. Department of Laboratory Medicine, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, PR China

    J Wang & Q Fu

  2. Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA

    H Mei

  3. Department of Developmental and Behavioral Pediatrics, Pediatric Translational Research Institution, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, PR China

    W Chen, Y Jiang, W Sun & F Jiang

  4. Department of Pediatrics, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China

    F Li

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Wang, J., Mei, H., Chen, W. et al. Study of eight GWAS-identified common variants for association with obesity-related indices in Chinese children at puberty. Int J Obes 36, 542–547 (2012). https://doi.org/10.1038/ijo.2011.218

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