Human Genetics

, Volume 131, Issue 11, pp 1795–1804 | Cite as

Genome-wide analysis of copy number variations reveals that aging processes influence body fat distribution in Korea Associated Resource (KARE) cohorts

  • Bo-Young Lee
  • Dong Hyun Shin
  • Seoae Cho
  • Kang-Seok Seo
  • Heebal Kim
Original Investigation

Abstract

Many anthropometric measures, including body mass index (BMI), waist-to-hip ratio (WHR), and subcutaneous fat thickness, are used as indicators of nutritional status, fertility and predictors of future health outcomes. While BMI is currently the best available estimate of body adiposity, WHR and skinfold thickness at various sites (biceps, triceps, suprailiac, and subscapular) are used as indices of body fat distribution. Copy number variation (CNV) is an attractive emerging approach to the study of associations with various diseases. In this study, we investigated the dosage effect of genes in the CNV genome widely associated with fat distribution phenotypes in large cohorts. We used the Affymetrix genome-wide human SNP Array 5.0 data of 8,842 healthy unrelated adults in KARE cohorts and identified CNVs associated with BMI and fat distribution-related traits including WHR and subcutaneous skinfold thickness at suprailiac (SUP) and subscapular (SUB) sites. CNV segmentation of each chromosome was performed using Golden Helix SVS 7.0, and single regression analysis was used to identify CNVs associated with each phenotype. We found one CNV for BMI, 287 for WHR, 2,157 for SUP, and 2,102 for SUB at the 5 % significance level after Holm–Bonferroni correction. Genes included in the CNV were used for the analysis of functional annotations using the Database for Annotation, Visualization and Integrated Discovery (DAVID v6.7b) tool. Functional gene classification analysis identified five significant gene clusters (metallothionein, ATP-binding proteins, ribosomal proteins, kinesin family members, and zinc finger proteins) for SUP, three (keratin-associated proteins, zinc finger proteins, keratins) for SUB, and one (protamines) for WHR. BMI was excluded from this analysis because the entire structure of no gene was identified in the CNV. Based on the analysis of genes enriched in the clusters, the fat distribution traits of KARE cohorts were related to the fat redistribution associated with the aging process. In addition to structural variation, dosage effect analysis of genes based on CNV is useful to gain an understanding of the comprehensive biological phenomena underlying particular phenotypes and/or diseases.

Notes

Acknowledgments

The large-scale genotyping data were supported by the Korea Association Resource (KARE) project, funded by the Korean National Institute of Health, Republic of Korea.

Supplementary material

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References

  1. Abdulrazzaq YM, Nagelkerke N, Moussa MA (2011) UAE population reference standard charts for body mass index and skinfold thickness, at ages 0–18 years. Int J Food Sci Nutr 62:692–702PubMedCrossRefGoogle Scholar
  2. Bell CG, Walley AJ, Froguel P (2005) The genetics of human obesity. Nat Rev Genet 6:221–234PubMedCrossRefGoogle Scholar
  3. Benzinou M, Chevre JC, Ward KJ, Lecoeur C, Dina C, Lobbens S, Durand E, Delplanque J, Horber FF, Heude B, Balkau B, Borch-Johnsen K, Jorgensen T, Hansen T, Pedersen O, Meyre D, Froguel P (2008) Endocannabinoid receptor 1 gene variations increase risk for obesity and modulate body mass index in European populations. Hum Mol Genet 17:1916–1921PubMedCrossRefGoogle Scholar
  4. Bochukova EG, Huang N, Keogh J, Henning E, Purmann C, Blaszczyk K, Saeed S, Hamilton-Shield J, Clayton-Smith J, O’Rahilly S, Hurles ME, Farooqi IS (2010) Large, rare chromosomal deletions associated with severe early-onset obesity. Nature 463:666–670PubMedCrossRefGoogle Scholar
  5. Bouatia-Naji N, Meyre D, Lobbens S, Seron K, Fumeron F, Balkau B, Heude B, Jouret B, Scherer PE, Dina C, Weill J, Froguel P (2006) ACDC/adiponectin polymorphisms are associated with severe childhood and adult obesity. Diabetes 55:545–550PubMedCrossRefGoogle Scholar
  6. Bray GA, DeLany JP, Volaufova J, Harsha DW, Champagne C (2002) Prediction of body fat in 12-y-old African American and white children: evaluation of methods. Am J Clin Nutr 76:980–990PubMedGoogle Scholar
  7. Chambers JC, Elliott P, Zabaneh D, Zhang W, Li Y, Froguel P, Balding D, Scott J, Kooner JS (2008) Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat Genet 40:716–718PubMedCrossRefGoogle Scholar
  8. Cho YS, Go MJ, Kim YJ, Heo JY, Oh JH, Ban HJ, Yoon D, Lee MH, Kim DJ, Park M, Cha SH, Kim JW, Han BG, Min H, Ahn Y, Park MS, Han HR, Jang HY, Cho EY, Lee JE, Cho NH, Shin C, Park T, Park JW, Lee JK, Cardon L, Clarke G, McCarthy MI, Lee JY, Oh B, Kim HL (2009) A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. Nat Genet 41:527–534PubMedCrossRefGoogle Scholar
  9. Coyle P, Philcox JC, Carey LC, Rofe AM (2002) Metallothionein: the multipurpose protein. Cell Mol Life Sci 59:627–647PubMedCrossRefGoogle Scholar
  10. Cui X, Gao L, Jin Y, Zhang Y, Bai J, Feng G, Gao W, Liu P, He L, Fu S (2007) The E233del mutation in BFSP2 causes a progressive autosomal dominant congenital cataract in a Chinese family. Mol Vis 13:2023–2029PubMedGoogle Scholar
  11. Dina C, Meyre D, Gallina S, Durand E, Korner A, Jacobson P, Carlsson LMS, Kiess W, Vatin V, Lecoeur C, Delplanque J, Vaillant E, Pattou F, Ruiz J, Weill J, Levy-Marchal C, Horber F, Potoczna N, Hercberg S, Le Stunff C, Bougneres P, Kovacs P, Marre M, Balkau B, Cauchi S, Chevre J-C, Froguel P (2007) Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet 39:724–726PubMedCrossRefGoogle Scholar
  12. Foster M, Yang Q, Hwang S-J, Hoffmann U, Fox C (2011) Heritability and genome-wide association analysis of renal sinus fat accumulation in the Framingham Heart Study. BMC Med Genet 12:148PubMedCrossRefGoogle Scholar
  13. Freedman DS, Katzmarzyk PT, Dietz WH, Srinivasan SR, Berenson GS (2010) The relation of BMI and skinfold thicknesses to risk factors among young and middle-aged adults: the Bogalusa Heart Study. Ann Hum Biol 37:726–737PubMedCrossRefGoogle Scholar
  14. Friel A, Houghton JA, Glennon M, Lavery R, Smith T, Nolan A, Maher M (2002) A preliminary report on the implication of RT-PCR detection of DAZ, RBMY1, USP9Y and Protamine-2 mRNA in testicular biopsy samples from azoospermic men. Int J Androl 25:59–64PubMedCrossRefGoogle Scholar
  15. Fuemmeler BF, Agurs-Collins TD, McClernon FJ, Kollins SH, Kail ME, Bergen AW, Ashley-Koch AE (2008) Genes implicated in serotonergic and dopaminergic functioning predict BMI categories. Obesity (Silver Spring) 16:348–355CrossRefGoogle Scholar
  16. Glessner JT, Wang K, Cai G, Korvatska O, Kim CE, Wood S, Zhang H, Estes A, Brune CW, Bradfield JP, Imielinski M, Frackelton EC, Reichert J, Crawford EL, Munson J, Sleiman PMA, Chiavacci R, Annaiah K, Thomas K, Hou C, Glaberson W, Flory J, Otieno F, Garris M, Soorya L, Klei L, Piven J, Meyer KJ, Anagnostou E, Sakurai T, Game RM, Rudd DS, Zurawiecki D, McDougle CJ, Davis LK, Miller J, Posey DJ, Michaels S, Kolevzon A, Silverman JM, Bernier R, Levy SE, Schultz RT, Dawson G, Owley T, McMahon WM, Wassink TH, Sweeney JA, Nurnberger JI, Coon H, Sutcliffe JS, Minshew NJ, Grant SFA, Bucan M, Cook EH, Buxbaum JD, Devlin B, Schellenberg GD, Hakonarson H (2009) Autism genome-wide copy number variation reveals ubiquitin and neuronal genes. Nature 459:569–573PubMedCrossRefGoogle Scholar
  17. Glessner JT, Bradfield JP, Wang K, Takahashi N, Zhang H, Sleiman PM, Mentch FD, Kim CE, Hou C, Thomas KA, Garris ML, Deliard S, Frackelton EC, Otieno FG, Zhao J, Chiavacci RM, Li M, Buxbaum JD, Berkowitz RI, Hakonarson H, Grant SFA (2010) A genome-wide study reveals copy number variants exclusive to childhood obesity cases. Am J Hum Genetics 87:661–666CrossRefGoogle Scholar
  18. Gylvin T, Ek J, Nolsoe R, Albrechtsen A, Andersen G, Bergholdt R, Brorsson C, Bang-Berthelsen CH, Hansen T, Karlsen AE, Billestrup N, Borch-Johnsen K, Jorgensen T, Pedersen O, Mandrup-Poulsen T, Nerup J, Pociot F (2009) Functional SOCS1 polymorphisms are associated with variation in obesity in whites. Diabetes Obes Metab 11:196–203PubMedCrossRefGoogle Scholar
  19. Hamer DH (1986) Metallothionein. Annu Rev Biochem 55:913–951PubMedCrossRefGoogle Scholar
  20. Heid IM, Jackson AU, Randall JC, Winkler TW, Qi L, Steinthorsdottir V, Thorleifsson G, Zillikens MC, Speliotes EK, Magi R, Workalemahu T, White CC, Bouatia-Naji N, Harris TB, Berndt SI, Ingelsson E, Willer CJ, Weedon MN, Luan J, Vedantam S, Esko T, Kilpelainen TO, Kutalik Z, Li S, Monda KL, Dixon AL, Holmes CC, Kaplan LM, Liang L, Min JL, Moffatt MF, Molony C, Nicholson G, Schadt EE, Zondervan KT, Feitosa MF, Ferreira T, Allen HL, Weyant RJ, Wheeler E, Wood AR, Estrada K, Goddard ME, Lettre G, Mangino M, Nyholt DR, Purcell S, Smith AV, Visscher PM, Yang J, McCarroll SA, Nemesh J, Voight BF, Absher D, Amin N, Aspelund T, Coin L, Glazer NL, Hayward C, Heard-Costa NL, Hottenga JJ, Johansson A, Johnson T, Kaakinen M, Kapur K, Ketkar S, Knowles JW, Kraft P, Kraja AT, Lamina C, Leitzmann MF, McKnight B, Morris AP, Ong KK, Perry JR, Peters MJ, Polasek O, Prokopenko I, Rayner NW, Ripatti S, Rivadeneira F, Robertson NR, Sanna S, Sovio U, Surakka I, Teumer A, van Wingerden S, Vitart V, Zhao JH, Cavalcanti-Proenca C, Chines PS, Fisher E, Kulzer JR, Lecoeur C, Narisu N, Sandholt C, Scott LJ, Silander K, Stark K, Tammesoo ML et al (2010) Meta-analysis identifies 13 new loci associated with waist–hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat Genet 42:949–960PubMedCrossRefGoogle Scholar
  21. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, Wichmann H-E, Meitinger T, Hunter D, Hu FB, Colditz G, Hinney A, Hebebrand J, Koberwitz K, Zhu X, Cooper R, Ardlie K, Lyon H, Hirschhorn JN, Laird NM, Lenburg ME, Lange C, Christman MF (2006) A common genetic variant is associated with adult and childhood obesity. Science 312:279–283PubMedCrossRefGoogle Scholar
  22. Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6:65–70Google Scholar
  23. Huang da W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57PubMedCrossRefGoogle Scholar
  24. Imken L, Rouba H, El Houate B, Louanjli N, Barakat A, Chafik A, McElreavey K (2009) Mutations in the protamine locus: association with spermatogenic failure? Mol Hum Reprod 15:733–738PubMedCrossRefGoogle Scholar
  25. Ionita-Laza I, Rogers AJ, Lange C, Raby BA, Lee C (2009) Genetic association analysis of copy-number variation (CNV) in human disease pathogenesis. Genomics 93:22–26PubMedCrossRefGoogle Scholar
  26. Jedrzejczak P, Kempisty B, Bryja A, Mostowska M, Depa-Martynow M, Pawelczyk L, Jagodzinski PP (2007) Quantitative assessment of transition proteins 1, 2 spermatid-specific linker histone H1-like protein transcripts in spermatozoa from normozoospermic and asthenozoospermic men. Arch Androl 53:199–205PubMedCrossRefGoogle Scholar
  27. Kato N, Takeuchi F, Tabara Y, Kelly TN, Go MJ, Sim X, Tay WT, Chen C-H, Zhang Y, Yamamoto K, Katsuya T, Yokota M, Kim YJ, Ong RTH, Nabika T, Gu D, Chang L, Kokubo Y, Huang W, Ohnaka K, Yamori Y, Nakashima E, Jaquish CE, Lee J-Y, Seielstad M, Isono M, Hixson JE, Chen Y-T, Miki T, Zhou X, Sugiyama T, Jeon J-P, Liu JJ, Takayanagi R, Kim SS, Aung T, Sung YJ, Zhang X, Wong TY, Han B-G, Kobayashi S, Ogihara T, Zhu D, Iwai N, Wu J-Y, Teo YY, Tai ES, Cho YS, He J (2011) Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in East Asians. Nat Genet 43:531–538PubMedCrossRefGoogle Scholar
  28. Kim HY, Cho S, Yu J, Sung S, Kim H (2010) Analysis of copy number variation in 8,842 Korean individuals reveals 39 genes associated with hepatic biomarkers AST and ALT. BMB Rep 43:547–553PubMedCrossRefGoogle Scholar
  29. Krude H, Biebermann H, Luck W, Horn R, Brabant G, Gruters A (1998) Severe early-onset obesity, adrenal insufficiency and red hair pigmentation caused by POMC mutations in humans. Nat Genet 19:155–157PubMedCrossRefGoogle Scholar
  30. Lee J, Park HS, Kim HH, Yun YJ, Lee DR, Lee S (2009) Functional polymorphism in H2BFWT-5′UTR is associated with susceptibility to male infertility. J Cell Mol Med 13:1942–1951PubMedCrossRefGoogle Scholar
  31. Lee B-Y, Cho S, Shin DH, Kim H (2011a) Genome-wide association study of copy number variations associated with pulmonary function measures in Korea Associated Resource (KARE) cohorts. Genomics 97:101–105PubMedCrossRefGoogle Scholar
  32. Lee K-T, Byun M-J, Kang K-S, Park E-W, Lee S-H, Cho S, Kim H, Kim K-W, Lee T, Park J-E, Park W, Shin D, Park H-S, Jeon J-T, Choi B-H, Jang G-W, Choi S-H, Kim D-W, Lim D, Park H-S, Park M-R, Ott J, Schook LB, Kim T-H, Kim H (2011b) Neuronal genes for subcutaneous fat thickness in human and pig are identified by local genomic sequencing and combined SNP association study. PLoS One 6:e16356PubMedCrossRefGoogle Scholar
  33. Lindgren CM, Heid IM, Randall JC, Lamina C, Steinthorsdottir V, Qi L, Speliotes EK, Thorleifsson G, Willer CJ, Herrera BM, Jackson AU, Lim N, Scheet P, Soranzo N, Amin N, Aulchenko YS, Chambers JC, Drong A, Luan J, Lyon HN, Rivadeneira F, Sanna S, Timpson NJ, Zillikens MC, Zhao JH, Almgren P, Bandinelli S, Bennett AJ, Bergman RN, Bonnycastle LL, Bumpstead SJ, Chanock SJ, Cherkas L, Chines P, Coin L, Cooper C, Crawford G, Doering A, Dominiczak A, Doney AS, Ebrahim S, Elliott P, Erdos MR, Estrada K, Ferrucci L, Fischer G, Forouhi NG, Gieger C, Grallert H, Groves CJ, Grundy S, Guiducci C, Hadley D, Hamsten A, Havulinna AS, Hofman A, Holle R, Holloway JW, Illig T, Isomaa B, Jacobs LC, Jameson K, Jousilahti P, Karpe F, Kuusisto J, Laitinen J, Lathrop GM, Lawlor DA, Mangino M, McArdle WL, Meitinger T, Morken MA, Morris AP, Munroe P, Narisu N, Nordstrom A, Nordstrom P, Oostra BA, Palmer CN, Payne F, Peden JF, Prokopenko I, Renstrom F, Ruokonen A, Salomaa V, Sandhu MS, Scott LJ, Scuteri A, Silander K, Song K, Yuan X, Stringham HM, Swift AJ, Tuomi T, Uda M, Vollenweider P, Waeber G, Wallace C, Walters GB, Weedon MN et al (2009) Genome-wide association scan meta-analysis identifies three loci influencing adiposity and fat distribution. PLoS Genet 5:e1000508PubMedCrossRefGoogle Scholar
  34. Mocchegiani E, Muzzioli M, Giacconi R (2000) Zinc and immunoresistance to infection in aging: new biological tools. Trends Pharmacol Sci 21:205–208PubMedCrossRefGoogle Scholar
  35. Nath R, Kumar D, Li T, Singal PK (2000) Metallothioneins, oxidative stress and the cardiovascular system. Toxicology 155:17–26PubMedCrossRefGoogle Scholar
  36. Qi L, Kraft P, Hunter DJ, Hu FB (2008) The common obesity variant near MC4R gene is associated with higher intakes of total energy and dietary fat, weight change and diabetes risk in women. Hum Mol Genet 17:3502–3508PubMedCrossRefGoogle Scholar
  37. Rybar R, Kopecka V, Prinosilova P, Markova P, Rubes J (2011) Male obesity and age in relationship to semen parameters and sperm chromatin integrity. Andrologia 43:286–291PubMedCrossRefGoogle Scholar
  38. Ryoo H, Woo J, Kim Y, Lee C (2011) Heterogeneity of genetic associations of CDKAL1 and HHEX with susceptibility of type 2 diabetes mellitus by gender. Eur J Hum Genet 19:672–675PubMedCrossRefGoogle Scholar
  39. Seve M, Chimienti F, Favier A (2002) Role of intracellular zinc in programmed cell death. Pathol Biol (Paris) 50:212–221CrossRefGoogle Scholar
  40. Sha B-Y, Yang T-L, Zhao L-J, Chen X-D, Guo Y, Chen Y, Pan F, Zhang Z-X, Dong S–S, Xu X-H, Deng H-W (2009) Genome-wide association study suggested copy number variation may be associated with body mass index in the Chinese population. J Hum Genet 54:199–202PubMedCrossRefGoogle Scholar
  41. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, Allen HL, Lindgren CM, Luan J, Magi R, Randall JC, Vedantam S, Winkler TW, Qi L, Workalemahu T, Heid IM, Steinthorsdottir V, Stringham HM, Weedon MN, Wheeler E, Wood AR, Ferreira T, Weyant RJ, Segre AV, Estrada K, Liang L, Nemesh J, Park JH, Gustafsson S, Kilpelainen TO, Yang J, Bouatia-Naji N, Esko T, Feitosa MF, Kutalik Z, Mangino M, Raychaudhuri S, Scherag A, Smith AV, Welch R, Zhao JH, Aben KK, Absher DM, Amin N, Dixon AL, Fisher E, Glazer NL, Goddard ME, Heard-Costa NL, Hoesel V, Hottenga JJ, Johansson A, Johnson T, Ketkar S, Lamina C, Li S, Moffatt MF, Myers RH, Narisu N, Perry JR, Peters MJ, Preuss M, Ripatti S, Rivadeneira F, Sandholt C, Scott LJ, Timpson NJ, Tyrer JP, van Wingerden S, Watanabe RM, White CC, Wiklund F, Barlassina C, Chasman DI, Cooper MN, Jansson JO, Lawrence RW, Pellikka N, Prokopenko I, Shi J, Thiering E, Alavere H, Alibrandi MT, Almgren P, Arnold AM, Aspelund T, Atwood LD, Balkau B, Balmforth AJ, Bennett AJ, Ben-Shlomo Y, Bergman RN, Bergmann S, Biebermann H, Blakemore AI, Boes T, Bonnycastle LL, Bornstein SR, Brown MJ, Buchanan TA et al (2010) Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 42:937–948PubMedCrossRefGoogle Scholar
  42. Stefanidou M, Maravelias C, Dona A, Spiliopoulou C (2006) Zinc: a multipurpose trace element. Arch Toxicol 80:1–9PubMedCrossRefGoogle Scholar
  43. Stone S, Abkevich V, Russell DL, Riley R, Timms K, Tran T, Trem D, Frank D, Jammulapati S, Neff CD, Iliev D, Gress R, He G, Frech GC, Adams TD, Skolnick MH, Lanchbury JS, Gutin A, Hunt SC, Shattuck D (2006) TBC1D1 is a candidate for a severe obesity gene and evidence for a gene/gene interaction in obesity predisposition. Hum Mol Genet 15:2709–2720PubMedCrossRefGoogle Scholar
  44. Suviolahti E, Oksanen LJ, Ohman M, Cantor RM, Ridderstrale M, Tuomi T, Kaprio J, Rissanen A, Mustajoki P, Jousilahti P, Vartiainen E, Silander K, Kilpikari R, Salomaa V, Groop L, Kontula K, Peltonen L, Pajukanta P (2003) The SLC6A14 gene shows evidence of association with obesity. J Clin Invest 112:1762–1772PubMedGoogle Scholar
  45. Tanaka S, Isoda F, Ishihara Y, Kimura M, Yamakawa T (2001) T lymphopaenia in relation to body mass index and TNF-alpha in human obesity: adequate weight reduction can be corrective. Clin Endocrinol (Oxf) 54:347–354Google Scholar
  46. Tanaka H, Miyagawa Y, Tsujimura A, Matsumiya K, Okuyama A, Nishimune Y (2003) Single nucleotide polymorphisms in the protamine-1 and -2 genes of fertile and infertile human male populations. Mol Hum Reprod 9:69–73PubMedCrossRefGoogle Scholar
  47. Tchkonia T, Morbeck DE, Von Zglinicki T, Van Deursen J, Lustgarten J, Scrable H, Khosla S, Jensen MD, Kirkland JL (2010) Fat tissue, aging, and cellular senescence. Aging Cell 9:667–684PubMedCrossRefGoogle Scholar
  48. Thorleifsson G, Walters GB, Gudbjartsson DF, Steinthorsdottir V, Sulem P, Helgadottir A, Styrkarsdottir U, Gretarsdottir S, Thorlacius S, Jonsdottir I, Jonsdottir T, Olafsdottir EJ, Olafsdottir GH, Jonsson T, Jonsson F, Borch-Johnsen K, Hansen T, Andersen G, Jorgensen T, Lauritzen T, Aben KK, Verbeek AL, Roeleveld N, Kampman E, Yanek LR, Becker LC, Tryggvadottir L, Rafnar T, Becker DM, Gulcher J, Kiemeney LA, Pedersen O, Kong A, Thorsteinsdottir U, Stefansson K (2009) Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat Genet 41:18–24PubMedCrossRefGoogle Scholar
  49. Walley AJ, Asher JE, Froguel P (2009) The genetic contribution to non-syndromic human obesity. Nat Rev Genet 10:431–442PubMedCrossRefGoogle Scholar
  50. Wermter AK, Scherag A, Meyre D, Reichwald K, Durand E, Nguyen TT, Koberwitz K, Lichtner P, Meitinger T, Schafer H, Hinney A, Froguel P, Hebebrand J, Bronner G (2008) Preferential reciprocal transfer of paternal/maternal DLK1 alleles to obese children: first evidence of polar overdominance in humans. Eur J Hum Genet 16:1126–1134PubMedCrossRefGoogle Scholar
  51. Willer CJ, Speliotes EK, Loos RJ, Li S, Lindgren CM, Heid IM, Berndt SI, Elliott AL, Jackson AU, Lamina C, Lettre G, Lim N, Lyon HN, McCarroll SA, Papadakis K, Qi L, Randall JC, Roccasecca RM, Sanna S, Scheet P, Weedon MN, Wheeler E, Zhao JH, Jacobs LC, Prokopenko I, Soranzo N, Tanaka T, Timpson NJ, Almgren P, Bennett A, Bergman RN, Bingham SA, Bonnycastle LL, Brown M, Burtt NP, Chines P, Coin L, Collins FS, Connell JM, Cooper C, Smith GD, Dennison EM, Deodhar P, Elliott P, Erdos MR, Estrada K, Evans DM, Gianniny L, Gieger C, Gillson CJ, Guiducci C, Hackett R, Hadley D, Hall AS, Havulinna AS, Hebebrand J, Hofman A, Isomaa B, Jacobs KB, Johnson T, Jousilahti P, Jovanovic Z, Khaw KT, Kraft P, Kuokkanen M, Kuusisto J, Laitinen J, Lakatta EG, Luan J, Luben RN, Mangino M, McArdle WL, Meitinger T, Mulas A, Munroe PB, Narisu N, Ness AR, Northstone K, O’Rahilly S, Purmann C, Rees MG, Ridderstrale M, Ring SM, Rivadeneira F, Ruokonen A, Sandhu MS, Saramies J, Scott LJ, Scuteri A, Silander K, Sims MA, Song K, Stephens J, Stevens S, Stringham HM, Tung YC, Valle TT, Van Duijn CM, Vimaleswaran KS, Vollenweider P et al (2009) Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 41:25–34PubMedCrossRefGoogle Scholar
  52. Yanagiya T, Tanabe A, Iida A, Saito S, Sekine A, Takahashi A, Tsunoda T, Kamohara S, Nakata Y, Kotani K, Komatsu R, Itoh N, Mineo I, Wada J, Masuzaki H, Yoneda M, Nakajima A, Miyazaki S, Tokunaga K, Kawamoto M, Funahashi T, Hamaguchi K, Tanaka K, Yamada K, Hanafusa T, Oikawa S, Yoshimatsu H, Nakao K, Sakata T, Matsuzawa Y, Kamatani N, Nakamura Y, Hotta K (2007) Association of single-nucleotide polymorphisms in MTMR9 gene with obesity. Hum Mol Genet 16:3017–3026PubMedCrossRefGoogle Scholar
  53. Zobel DP, Andreasen CH, Burgdorf KS, Andersson EA, Sandbaek A, Lauritzen T, Borch-Johnsen K, Jorgensen T, Maeda S, Nakamura Y, Eiberg H, Pedersen O, Hansen T (2009) Variation in the gene encoding Kruppel-like factor 7 influences body fat: studies of 14818 Danes. Eur J Endocrinol 160:603–609PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Bo-Young Lee
    • 1
  • Dong Hyun Shin
    • 1
  • Seoae Cho
    • 2
    • 4
  • Kang-Seok Seo
    • 3
  • Heebal Kim
    • 1
  1. 1.Laboratory of Bioinformatics and Population Genetics, Department of Agricultural BiotechnologySeoul National UniversitySeoulRepublic of Korea
  2. 2.Department of StatisticsUniversity of California, BerkeleyBerkeleyUSA
  3. 3.Department of Animal Science and TechnologySunchon National UniversitySuncheonRepublic of Korea
  4. 4. C&K genomicsSeoulRepublic of Korea

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