Human Genetics

, Volume 132, Issue 11, pp 1275–1285

Common genetic variants associated with lipid profiles in a Chinese pediatric population

Original Investigation

Abstract

Genome-wide association (GWA) studies have identified many candidate genes that are associated with blood lipid and lipoprotein concentrations. In this study, we want to know whether the results from European for lipid-related single-nucleotide polymorphisms (SNPs) are generalizable to Chinese children. We genotyped seven SNPs in Chinese school-age children (n = 3,503) and assessed the associations of these SNPs with lipids profiles and dyslipidemia. After false discovery rate correction, of the seven SNPs, six (rs2144300, p ~ 9.30 × 10−3; rs1260333, p ~ 6.20 × 10−11; rs1260326, p ~ 8.73 × 10−11; rs10105606, p ~ 0.010; rs1748195, p ~ 0.016 and rs964184, p ~ 2.33 × 10−13) showed strong association with triglycerides. Three SNPs (rs1260333, p ~ 3.30 × 10−3; rs1260326, p ~ 4.39 × 10−3 and rs2954029, p ~ 6.36 × 10−4) showed strong association with total cholesterol. Two SNPs (rs10105606, p ~ 6.66 × 10−4 and rs1748195, p ~ 2.55 × 10−3) showed strong association with high density lipoprotein cholesterol. Four SNPs (rs1260333, p ~ 0.017; rs1260326, p ~ 0.013; rs2954029, p ~ 1.09 × 10−3 and rs964184, p ~ 5.51 × 10−3) showed strong association with low density lipoprotein cholesterol. There were significant associations between rs1260333 (OR is 0.82, 95 % CI 0.74–0.92, p ~ 3.96 × 10−4), rs1260326 (OR is 0.82, 95 % CI 0.74–0.92, p ~ 5.31 × 10−4), and rs964184 (OR is 1.36, 95 % CI 1.20–1.55, p ~ 1.89 × 10−6) and dyslipidemia. These SNPs generated strong combined effects on lipid profiles and dyslipidemia. Our study demonstrates that SNPs associated with lipids from European GWA studies also play roles in Chinese children, which broadened the understanding of lipids metabolism.

Abbreviations

GALNT2

Polypeptide N-acetyl galactosaminyl transferase 2

GCKR

Glucokinase (hexokinase 4) regulator

LPL

Lipoprotein lipase

TRIB1

Tribbles homolog 1 (Drosophila)

ANGPTL3

Angiopoietin-like 3

MAF

Minor allele frequency

BMI

Body mass index

OR

Odds ratio

CI

Confidence interval

Supplementary material

439_2013_1332_MOESM1_ESM.doc (502 kb)
Supplementary material 1 (DOC 501 kb)

References

  1. Aulchenko YS, Ripatti S, Lindqvist I, Boomsma D, Heid IM, Pramstaller PP, Penninx BW, Janssens AC, Wilson JF, Spector T, Martin NG, Pedersen NL, Kyvik KO, Kaprio J, Hofman A, Freimer NB, Jarvelin MR, Gyllensten U, Campbell H, Rudan I, Johansson A, Marroni F, Hayward C, Vitart V, Jonasson I, Pattaro C, Wright A, Hastie N, Pichler I, Hicks AA, Falchi M, Willemsen G, Hottenga JJ, de Geus EJ, Montgomery GW, Whitfield J, Magnusson P, Saharinen J, Perola M, Silander K, Isaacs A, Sijbrands EJ, Uitterlinden AG, Witteman JC, Oostra BA, Elliott P, Ruokonen A, Sabatti C, Gieger C, Meitinger T, Kronenberg F, Doring A, Wichmann HE, Smit JH, McCarthy MI, van Duijn CM, Peltonen L (2009) Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet 41:47–55PubMedCrossRefGoogle Scholar
  2. Benjamini Yoav, Hochberg Yosef (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Statistical Soc B 57:289–300Google Scholar
  3. Berenson GS (2002) Childhood risk factors predict adult risk associated with subclinical cardiovascular disease. The Bogalusa Heart Study. Am J Cardiol 90:3L–7LPubMedCrossRefGoogle Scholar
  4. Brautbar A, Covarrubias D, Belmont J, Lara-Garduno F, Virani SS, Jones PH, Leal SM, Ballantyne CM (2011) Variants in the APOA5 gene region and the response to combination therapy with statins and fenofibric acid in a randomized clinical trial of individuals with mixed dyslipidemia. Atherosclerosis 219:737–742PubMedCrossRefGoogle Scholar
  5. Castelli WP (1996) Lipids, risk factors and ischaemic heart disease. Atherosclerosis 124(Suppl):S1–S9PubMedCrossRefGoogle Scholar
  6. Daniels SR, Greer FR (2008) Lipid screening and cardiovascular health in childhood. Pediatrics 122:198–208PubMedCrossRefGoogle Scholar
  7. Editorial Board of Chinese Journal of Pediatrics, Subspecialty Group of Child Health Care, The Society of Pediatrics, Chinese Medical Association, Subspecialty Group of Cardiovascular Disease, The Society of Pediatrics, Chinese Medical Association, Subspecialty Group of Atherosclerosis, The Society of Cardiovascular Disease, Chinese Medical Association (2009) Experts consensus for prevention and treatment of dyslipidemia in children and adolescents. Zhonghua Er Ke Za Zhi 47:426–428Google Scholar
  8. Friedlander Y, Kark JD, Stein Y (1986) Biological and environmental sources of variation in plasma lipids and lipoproteins: the Jerusalem Lipid Research Clinic. Hum Hered 36:143–153PubMedCrossRefGoogle Scholar
  9. Garces C, de Oya I, Lasuncion MA, Lopez-Simon L, Cano B, de Oya M (2010) Sex hormone-binding globulin and lipid profile in pubertal children. Metabolism 59:166–171Google Scholar
  10. Horvatovich K, Bokor S, Barath A, Maasz A, Kisfali P, Jaromi L, Polgar N, Toth D, Repasy J, Endreffy E, Molnar D, Melegh B (2011a) Haplotype analysis of the apolipoprotein A5 gene in obese pediatric patients. Int J Pediatr Obes 6:e318–e325PubMedCrossRefGoogle Scholar
  11. Horvatovich K, Bokor S, Polgar N, Kisfali P, Hadarits F, Jaromi L, Csongei V, Repasy J, Molnar D, Melegh B (2011b) Functional glucokinase regulator gene variants have inverse effects on triglyceride and glucose levels, and decrease the risk of obesity in children. Diabetes Metab 37:432–439PubMedCrossRefGoogle Scholar
  12. Ji CY (2005) Report on childhood obesity in China (1)—body mass index reference for screening overweight and obesity in Chinese school-age children. Biomed Environ Sci 18:390–400PubMedGoogle Scholar
  13. Johansen CT, Wang J, Lanktree MB, Cao H, McIntyre AD, Ban MR, Martins RA, Kennedy BA, Hassell RG, Visser ME, Schwartz SM, Voight BF, Elosua R, Salomaa V, O’Donnell CJ, Linga-Thie GM, Anand SS, Yusuf S, Huff MW, Kathiresan S, Hegele RA (2010) Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia. Nat Genet 42:684–687PubMedCrossRefGoogle Scholar
  14. Kathiresan S, Melander O, Anevski D, Guiducci C, Burtt NP, Roos C, Hirschhorn JN, Berglund G, Hedblad B, Groop L, Altshuler DM, Newton-Cheh C, Orho-Melander M (2008a) Polymorphisms associated with cholesterol and risk of cardiovascular events. N Engl J Med 358:1240–1249PubMedCrossRefGoogle Scholar
  15. Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, Cooper GM, Roos C, Voight BF, Havulinna AS, Wahlstrand B, Hedner T, Corella D, Tai ES, Ordovas JM, Berglund G, Vartiainen E, Jousilahti P, Hedblad B, Taskinen MR, Newton-Cheh C, Salomaa V, Peltonen L, Groop L, Altshuler DM, Orho-Melander M (2008b) Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat Genet 40:189–197PubMedCrossRefGoogle Scholar
  16. Kathiresan S, Willer CJ, Peloso GM, Demissie S, Musunuru K, Schadt EE, Kaplan L, Bennett D, Li Y, Tanaka T, Voight BF, Bonnycastle LL, Jackson AU, Crawford G, Surti A, Guiducci C, Burtt NP, Parish S, Clarke R, Zelenika D, Kubalanza KA, Morken MA, Scott LJ, Stringham HM, Galan P, Swift AJ, Kuusisto J, Bergman RN, Sundvall J, Laakso M, Ferrucci L, Scheet P, Sanna S, Uda M, Yang Q, Lunetta KL, Dupuis J, de Bakker PI, O’Donnell CJ, Chambers JC, Kooner JS, Hercberg S, Meneton P, Lakatta EG, Scuteri A, Schlessinger D, Tuomilehto J, Collins FS, Groop L, Altshuler D, Collins R, Lathrop GM, Melander O, Salomaa V, Peltonen L, Orho-Melander M, Ordovas JM, Boehnke M, Abecasis GR, Mohlke KL, Cupples LA (2009) Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet 41:56–65PubMedCrossRefGoogle Scholar
  17. Kouda K, Nakamura H, Tokunaga R, Takeuchi H (2004) Trends in levels of cholesterol in Japanese children from 1993 through 2001. J Epidemiol 14:78–82PubMedCrossRefGoogle Scholar
  18. Lettre G, Palmer CD, Young T, Ejebe KG, Allayee H, Benjamin EJ, Bennett F, Bowden DW, Chakravarti A, Dreisbach A, Farlow DN, Folsom AR, Fornage M, Forrester T, Fox E, Haiman CA, Hartiala J, Harris TB, Hazen SL, Heckbert SR, Henderson BE, Hirschhorn JN, Keating BJ, Kritchevsky SB, Larkin E, Li M, Rudock ME, McKenzie CA, Meigs JB, Meng YA, Mosley TH, Newman AB, Newton-Cheh CH, Paltoo DN, Papanicolaou GJ, Patterson N, Post WS, Psaty BM, Qasim AN, Qu L, Rader DJ, Redline S, Reilly MP, Reiner AP, Rich SS, Rotter JI, Liu Y, Shrader P, Siscovick DS, Tang WH, Taylor HA, Tracy RP, Vasan RS, Waters KM, Wilks R, Wilson JG, Fabsitz RR, Gabriel SB, Kathiresan S, Boerwinkle E (2011) Genome-wide association study of coronary heart disease and its risk factors in 8,090 African Americans: the NHLBI CARe Project. PLoS Genet 7:e1001300PubMedCrossRefGoogle Scholar
  19. Li JZ, Li PY, Niu QT, Wang S, Jiang L, Zhao SH, Guo HB, Gao H, Zhang ZM, Fang XZ (1988) Serum-lipid and lipoprotein patterns of Beijing populations from birth to senescence. Chin Med J (Engl) 101:659–664Google Scholar
  20. Li Q, Yin RX, Yan TT, Miao L, Cao XL, Hu XJ, Aung LH, Wu DF, Wu JZ, Lin WX (2011) Association of the GALNT2 gene polymorphisms and several environmental factors with serum lipid levels in the Mulao and Han populations. Lipids Health Dis 10:160PubMedCrossRefGoogle Scholar
  21. Liao Y, Liu Y, Mi J, Tang C, Du J (2008) Risk factors for dyslipidemia in Chinese children. Acta Paediatr 97:1449–1453PubMedCrossRefGoogle Scholar
  22. Malloy MJ, Kane JP (2001) A risk factor for atherosclerosis: triglyceride-rich lipoproteins. Adv Intern Med 47:111–136PubMedGoogle Scholar
  23. Manios Y, Magkos F, Christakis G, Kafatos AG (2005) Changing relationships of obesity and dyslipidemia in Greek children: 1982–2002. Prev Med 41:846–851PubMedCrossRefGoogle Scholar
  24. Marshall WA, Tanner JM (1986) Puberty. In: Falkner F, Tanner JM (eds) Human growth. II. Postnatal growth. Plenum Press, New YorkGoogle Scholar
  25. Mi J, Cheng H, Hou DQ, Duan JL, Teng HH, Wang YF (2006) Prevalence of overweight and obesity among children and adolescents in Beijing in 2004. Zhonghua Liu Xing Bing Xue Za Zhi 27:469–474PubMedGoogle Scholar
  26. Sabatti C, Service SK, Hartikainen AL, Pouta A, Ripatti S, Brodsky J, Jones CG, Zaitlen NA, Varilo T, Kaakinen M, Sovio U, Ruokonen A, Laitinen J, Jakkula E, Coin L, Hoggart C, Collins A, Turunen H, Gabriel S, Elliot P, McCarthy MI, Daly MJ, Jarvelin MR, Freimer NB, Peltonen L (2009) Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nat Genet 41:35–46PubMedCrossRefGoogle Scholar
  27. Sandhu MS, Waterworth DM, Debenham SL, Wheeler E, Papadakis K, Zhao JH, Song K, Yuan X, Johnson T, Ashford S, Inouye M, Luben R, Sims M, Hadley D, McArdle W, Barter P, Kesaniemi YA, Mahley RW, McPherson R, Grundy SM, Bingham SA, Khaw KT, Loos RJ, Waeber G, Barroso I, Strachan DP, Deloukas P, Vollenweider P, Wareham NJ, Mooser V (2008) LDL-cholesterol concentrations: a genome-wide association study. Lancet 371:483–491PubMedCrossRefGoogle Scholar
  28. Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, Roix JJ, Kathiresan S, Hirschhorn JN, Daly MJ, Hughes TE, Groop L, Altshuler D, Almgren P, Florez JC, Meyer J, Ardlie K, Bengtsson BK, Isomaa B, Lettre G, Lindblad U, Lyon HN, Melander O, Newton-Cheh C, Nilsson P, Orho-Melander M, Rastam L, Speliotes EK, Taskinen MR, Tuomi T, Guiducci C, Berglund A, Carlson J, Gianniny L, Hackett R, Hall L, Holmkvist J, Laurila E, Sjogren M, Sterner M, Surti A, Svensson M, Svensson M, Tewhey R, Blumenstiel B, Parkin M, Defelice M, Barry R, Brodeur W, Camarata J, Chia N, Fava M, Gibbons J, Handsaker B, Healy C, Nguyen K, Gates C, Sougnez C, Gage D, Nizzari M, Gabriel SB, Chirn GW, Ma Q, Parikh H, Richardson D, Ricke D, Purcell S (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316:1331–1336PubMedCrossRefGoogle Scholar
  29. Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin CY, Jin GM, Jin KY, Lee JY, Park T, Kim K, Sim X, Twee-Hee OR, Croteau-Chonka DC, Lange LA, Smith JD, Song K, Hua ZJ, Yuan X, Luan J, Lamina C, Ziegler A, Zhang W, Zee RY, Wright AF, Witteman JC, Wilson JF, Willemsen G, Wichmann HE, Whitfield JB, Waterworth DM, Wareham NJ, Waeber G, Vollenweider P, Voight BF, Vitart V, Uitterlinden AG, Uda M, Tuomilehto J, Thompson JR, Tanaka T, Surakka I, Stringham HM, Spector TD, Soranzo N, Smit JH, Sinisalo J, Silander K, Sijbrands EJ, Scuteri A, Scott J, Schlessinger D, Sanna S, Salomaa V, Saharinen J, Sabatti C, Ruokonen A, Rudan I, Rose LM, Roberts R, Rieder M, Psaty BM, Pramstaller PP, Pichler I, Perola M, Penninx BW, Pedersen NL, Pattaro C, Parker AN, Pare G, Oostra BA, O’Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, Meitinger T, McPherson R, McCarthy MI, McArdle W, Masson D, Martin NG, Marroni F, Mangino M, Magnusson PK, Lucas G, Luben R, Loos RJ, Lokki ML, Lettre G, Langenberg C, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, Kronenberg F, Konig IR, Khaw KT, Kaprio J, Kaplan LM, Johansson A, Jarvelin MR, Janssens AC, Ingelsson E, Igl W, Kees HG, Hottenga JJ, Hofman A, Hicks AA, Hengstenberg C, Heid IM, Hayward C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Gyllensten U, Guiducci C, Groop LC, Gonzalez E, Gieger C, Freimer NB, Ferrucci L, Erdmann J, Elliott P, Ejebe KG, Doring A, Dominiczak AF, Demissie S, Deloukas P, de Geus EJ, de Faire U, Crawford G, Collins FS, Chen YD, Caulfield MJ, Campbell H, Burtt NP, Bonnycastle LL, Boomsma DI, Boekholdt SM, Bergman RN, Barroso I, Bandinelli S, Ballantyne CM, Assimes TL, Quertermous T, Altshuler D, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Adair LS, Taylor HA Jr, Borecki IB, Gabriel SB, Wilson JG, Holm H, Thorsteinsdottir U, Gudnason V, Krauss RM, Mohlke KL, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJ, Schadt EE, Rotter JI, Boerwinkle E, Strachan DP, Mooser V, Stefansson K, Reilly MP, Samani NJ, Schunkert H, Cupples LA, Sandhu MS, Ridker PM, Rader DJ, van Duijn CM, Peltonen L, Abecasis GR, Boehnke M, Kathiresan S (2010) Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466:707–713PubMedCrossRefGoogle Scholar
  30. Tikkanen E, Tuovinen T, Widen E, Lehtimaki T, Viikari J, Kahonen M, Peltonen L, Raitakari OT, Ripatti S (2011) Association of known loci with lipid levels among children and prediction of dyslipidemia in adults. Circ Cardiovasc Genet 4:673–680PubMedCrossRefGoogle Scholar
  31. Wallace C, Newhouse SJ, Braund P, Zhang F, Tobin M, Falchi M, Ahmadi K, Dobson RJ, Marcano AC, Hajat C, Burton P, Deloukas P, Brown M, Connell JM, Dominiczak A, Lathrop GM, Webster J, Farrall M, Spector T, Samani NJ, Caulfield MJ, Munroe PB (2008) Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia. Am J Hum Genet 82:139–149PubMedCrossRefGoogle Scholar
  32. Waterworth DM, Ricketts SL, Song K, Chen L, Zhao JH, Ripatti S, Aulchenko YS, Zhang W, Yuan X, Lim N, Luan J, Ashford S, Wheeler E, Young EH, Hadley D, Thompson JR, Braund PS, Johnson T, Struchalin M, Surakka I, Luben R, Khaw KT, Rodwell SA, Loos RJ, Boekholdt SM, Inouye M, Deloukas P, Elliott P, Schlessinger D, Sanna S, Scuteri A, Jackson A, Mohlke KL, Tuomilehto J, Roberts R, Stewart A, Kesaniemi YA, Mahley RW, Grundy SM, McArdle W, Cardon L, Waeber G, Vollenweider P, Chambers JC, Boehnke M, Abecasis GR, Salomaa V, Jarvelin MR, Ruokonen A, Barroso I, Epstein SE, Hakonarson HH, Rader DJ, Reilly MP, Witteman JC, Hall AS, Samani NJ, Strachan DP, Barter P, van Duijn CM, Kooner JS, Peltonen L, Wareham NJ, McPherson R, Mooser V, Sandhu MS (2010) Genetic variants influencing circulating lipid levels and risk of coronary artery disease. Arterioscler Thromb Vasc Biol 30:2264–2276PubMedCrossRefGoogle Scholar
  33. Weissglas-Volkov D, Guilar-Salinas CA, Sinsheimer JS, Riba L, Huertas-Vazquez A, Ordonez-Sanchez ML, Rodriguez-Guillen R, Cantor RM, Tusie-Luna T, Pajukanta P (2010) Investigation of variants identified in caucasian genome-wide association studies for plasma high-density lipoprotein cholesterol and triglycerides levels in Mexican dyslipidemic study samples. Circ Cardiovasc Genet 3:31–38PubMedCrossRefGoogle Scholar
  34. Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, Heath SC, Timpson NJ, Najjar SS, Stringham HM, Strait J, Duren WL, Maschio A, Busonero F, Mulas A, Albai G, Swift AJ, Morken MA, Narisu N, Bennett D, Parish S, Shen H, Galan P, Meneton P, Hercberg S, Zelenika D, Chen WM, Li Y, Scott LJ, Scheet PA, Sundvall J, Watanabe RM, Nagaraja R, Ebrahim S, Lawlor DA, Ben-Shlomo Y, Vey-Smith G, Shuldiner AR, Collins R, Bergman RN, Uda M, Tuomilehto J, Cao A, Collins FS, Lakatta E, Lathrop GM, Boehnke M, Schlessinger D, Mohlke KL, Abecasis GR (2008) Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet 40:161–169PubMedCrossRefGoogle Scholar
  35. Wu L, Xi B, Zhang M, Shen Y, Zhao X, Cheng H, Hou D, Sun D, Ott J, Wang X, Mi J (2010) Associations of six single nucleotide polymorphisms in obesity-related genes with BMI and risk of obesity in Chinese children. Diabetes 59:3085–3089PubMedCrossRefGoogle Scholar
  36. Xi B, Shen Y, Zhang M, Liu X, Zhao X, Wu L, Cheng H, Hou D, Lindpaintner K, Liu L, Mi J, Wang X (2010) 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 11:107PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Graduate School of Peking Union Medicine CollegeBeijingChina
  2. 2.Institute of Maternal and Child Health Care, School of Public HealthShandong UniversityJinanChina
  3. 3.Department of EpidemiologyCapital Institute of PediatricsBeijingChina
  4. 4.Laboratory of Human GeneticsBeijing Hypertension League InstituteBeijingChina

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