#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits


Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.


Vyšlo v časopise: Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits. PLoS Genet 9(6): e32767. doi:10.1371/journal.pgen.1003500
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1003500

Souhrn

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.


Zdroje

1. Legato M (2004) Principles of Gender-Specific Medicine, Vol. 1 & Vol. 2: New York: Elsevier Academic Press.

2. Wizemann TM, Pardue ML (2001) Exploring the biological contributions to human health: does sex matter? Washington, DC: National Academies Press.

3. Malina RM (2005) Variation in body composition associated with sex and ethnicity. In: Heymsfield S, editor. Human body composition. 2nd ed. Champaign, IL: Human Kinetics. pp. 271–298.

4. TaylorRW, GrantAM, WilliamsSM, GouldingA (2010) Sex differences in regional body fat distribution from pre- to postpuberty. Obesity 18: 1410–1416.

5. WellsJC (2007) Sexual dimorphism of body composition. Best practice & research Clinical endocrinology & metabolism 21: 415–430.

6. GreenHJ, FraserIG, RanneyDA (1984) Male and female differences in enzyme activities of energy metabolism in vastus lateralis muscle. Journal of the neurological sciences 65: 323–331.

7. KomiPV, KarlssonJ (1978) Skeletal muscle fibre types, enzyme activities and physical performance in young males and females. Acta physiologica Scandinavica 103: 210–218.

8. SimoneauJA, LortieG, BoulayMR, ThibaultMC, TheriaultG, et al. (1985) Skeletal muscle histochemical and biochemical characteristics in sedentary male and female subjects. Canadian journal of physiology and pharmacology 63: 30–35.

9. TrotterM, PetersonRR (1970) Weight of the skeleton during postnatal development. American journal of physical anthropology 33: 313–323.

10. GarnSM, NagyJM, SanduskyST (1972) Differential sexual dimorphism in bone diameters of subjects of European and African ancestry. American journal of physical anthropology 37: 127–129.

11. VazquezG, DuvalS, JacobsDRJr, SilventoinenK (2007) Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis. Epidemiol Rev 29: 115–128.

12. MokdadAH, FordES, BowmanBA, DietzWH, VinicorF, et al. (2003) Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA : the journal of the American Medical Association 289: 76–79.

13. MustA, SpadanoJ, CoakleyEH, FieldAE, ColditzG, et al. (1999) The disease burden associated with overweight and obesity. Jama-Journal of the American Medical Association 282: 1523–1529.

14. YusufS, HawkenS, OunpuuS, BautistaL, FranzosiMG, et al. (2005) Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet 366: 1640–1649.

15. CanoyD, BoekholdtSM, WarehamN, LubenR, WelchA, et al. (2007) Body fat distribution and risk of coronary heart disease in men and women in the European Prospective Investigation Into Cancer and Nutrition in Norfolk cohort: a population-based prospective study. Circulation 116: 2933–2943.

16. WelbornTA, DhaliwalSS, BennettSA (2003) Waist-hip ratio is the dominant risk factor predicting cardiovascular death in Australia. Medical Journal of Australia 179: 580–585.

17. BorugianMJ, ShepsSB, Kim-SingC, OlivottoIA, Van PattenC, et al. (2003) Waist-to-hip ratio and breast cancer mortality. American journal of epidemiology 158: 963–968.

18. RenehanAG, TysonM, EggerM, HellerRF, ZwahlenM (2008) Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet 371: 569–578.

19. PischonT, BoeingH, HoffmannK, BergmannM, SchulzeMB, et al. (2008) General and abdominal adiposity and risk of death in Europe. The New England journal of medicine 359: 2105–2120.

20. LangenbergC, SharpSJ, SchulzeMB, RolandssonO, OvervadK, et al. (2012) Long-term risk of incident type 2 diabetes and measures of overall and regional obesity: the EPIC-InterAct case-cohort study. PLoS medicine 9: e1001230.

21. WeedonMN, LangoH, LindgrenCM, WallaceC, EvansDM, et al. (2008) Genome-wide association analysis identifies 20 loci that influence adult height. Nature genetics 40: 575–583.

22. EstradaK, KrawczakM, SchreiberS, van DuijnK, StolkL, et al. (2009) A genome-wide association study of northwestern Europeans involves the C-type natriuretic peptide signaling pathway in the etiology of human height variation. Human molecular genetics 18: 3516–3524.

23. TonjesA, KoriathM, SchleinitzD, DietrichK, BottcherY, et al. (2009) Genetic variation in GPR133 is associated with height: genome wide association study in the self-contained population of Sorbs. Human molecular genetics 18: 4662–4668.

24. OkadaY, KamataniY, TakahashiA, MatsudaK, HosonoN, et al. (2010) A genome-wide association study in 19 633 Japanese subjects identified LHX3-QSOX2 and IGF1 as adult height loci. Human molecular genetics 19: 2303–2312.

25. Lango AllenH, EstradaK, LettreG, BerndtSI, WeedonMN, et al. (2010) Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467: 832–838.

26. FraylingTM, TimpsonNJ, WeedonMN, ZegginiE, FreathyRM, et al. (2007) A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316: 889–894.

27. LoosRJ, LindgrenCM, LiS, WheelerE, ZhaoJH, et al. (2008) Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nature genetics 40: 768–775.

28. WillerCJ, SpeliotesEK, LoosRJ, LiS, LindgrenCM, et al. (2009) Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nature genetics 41: 25–34.

29. SpeliotesEK, WillerCJ, BerndtSI, MondaKL, ThorleifssonG, et al. (2010) Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nature genetics 42: 937–948.

30. LindgrenCM, HeidIM, RandallJC, LaminaC, SteinthorsdottirV, et al. (2009) Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution. PLoS genetics 5: e1000508.

31. HeidIM, JacksonAU, RandallJC, WinklerTW, QiL, 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. Nature genetics 42: 949–960.

32. BenjaminiYaH, Y (1995) Controlling The False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J Roy Statist Soc Ser B 57: 289–300.

33. LehrkeM, LazarMA (2005) The many faces of PPARgamma. Cell 123: 993–999.

34. TeslovichTM, MusunuruK, SmithAV, EdmondsonAC, StylianouIM, et al. (2010) Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466: 707–713.

35. DupuisJ, LangenbergC, ProkopenkoI, SaxenaR, SoranzoN, et al. (2010) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nature genetics 42: 105–116.

36. ZegginiE, ScottLJ, SaxenaR, VoightBF, MarchiniJL, et al. (2008) Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature genetics 40: 638–645.

37. BarteltA, BrunsOT, ReimerR, HohenbergH, IttrichH, et al. (2011) Brown adipose tissue activity controls triglyceride clearance. Nature Medicine 17: 200–205.

38. JacksonAS, StanforthPR, GagnonJ, RankinenT, LeonAS, et al. (2002) The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study. Int J Obes Relat Metab Disord 26: 789–796.

39. McQuaidSE, ManolopoulosKN, DennisAL, CheesemanJ, KarpeF, et al. (2010) Development of an arterio-venous difference method to study the metabolic physiology of the femoral adipose tissue depot. Obesity 18: 1055–1058.

40. Pi-SunyerFX (2004) The epidemiology of central fat distribution in relation to disease. Nutr Rev 62: S120–126.

41. MaynardLM, WisemandleW, RocheAF, ChumleaWC, GuoSS, et al. (2001) Childhood body composition in relation to body mass index. Pediatrics 107: 344–350.

42. HattoriK, TaharaY, MojiK, AoyagiK, FurusawaT (2004) Chart analysis of body composition change among pre- and postadolescent Japanese subjects assessed by underwater weighing method. Int J Obes Relat Metab Disord 28: 520–524.

43. LovejoyJC, ChampagneCM, de JongeL, XieH, SmithSR (2008) Increased visceral fat and decreased energy expenditure during the menopausal transition. International journal of obesity 32: 949–958.

44. CintiS (2001) The adipose organ: morphological perspectives of adipose tissues. Proc Nutr Soc 60: 319–328.

45. DempfleA, HinneyA, Heinzel-GutenbrunnerM, RaabM, GellerF, et al. (2004) Large quantitative effect of melanocortin-4 receptor gene mutations on body mass index. J Med Genet 41: 795–800.

46. van NasA, GuhathakurtaD, WangSS, YehyaN, HorvathS, et al. (2009) Elucidating the role of gonadal hormones in sexually dimorphic gene coexpression networks. Endocrinology 150: 1235–1249.

47. RantalainenM, HerreraBM, NicholsonG, BowdenR, WillsQF, et al. (2011) MicroRNA expression in abdominal and gluteal adipose tissue is associated with mRNA expression levels and partly genetically driven. PloS one 6: e27338.

48. MinJL, NicholsonG, HalgrimsdottirI, AlmstrupK, PetriA, et al. (2012) Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes. PLoS genetics 8: e1002505.

49. AlexandersonC, ErikssonE, Stener-VictorinE, LystigT, GabrielssonB, et al. (2007) Postnatal testosterone exposure results in insulin resistance, enlarged mesenteric adipocytes, and an atherogenic lipid profile in adult female rats: comparisons with estradiol and dihydrotestosterone. Endocrinology 148: 5369–5376.

50. ZhangFF, CardarelliR, CarrollJ, FuldaKG, KaurM, et al. (2011) Significant differences in global genomic DNA methylation by gender and race/ethnicity in peripheral blood. Epigenetics 6: 623–629.

51. ZillikensMC, YazdanpanahM, PardoLM, RivadeneiraF, AulchenkoYS, et al. (2008) Sex-specific genetic effects influence variation in body composition. Diabetologia 51: 2233–2241.

52. RobitailleJ, DespresJP, PerusseL, VohlMC (2003) The PPAR-gamma P12A polymorphism modulates the relationship between dietary fat intake and components of the metabolic syndrome: results from the Quebec Family Study. Clinical genetics 63: 109–116.

53. MoriniE, TassiV, CapponiD, LudovicoO, DallapiccolaB, et al. (2008) Interaction between PPARgamma2 variants and gender on the modulation of body weight. Obesity 16: 1467–1470.

54. ZegginiE, WeedonMN, LindgrenCM, FraylingTM, ElliottKS, et al. (2007) Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316: 1336–1341.

55. ScottLJ, MohlkeKL, BonnycastleLL, WillerCJ, LiY, et al. (2007) A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316: 1341–1345.

56. SaxenaR, VoightBF, LyssenkoV, BurttNP, de BakkerPI, et al. (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316: 1331–1336.

57. SheaMK, NicklasBJ, MarshAP, HoustonDK, MillerGD, et al. (2011) The effect of pioglitazone and resistance training on body composition in older men and women undergoing hypocaloric weight loss. Obesity 19: 1636–1646.

58. GoenagaD, HampeC, CarreN, CailliauK, Browaeys-PolyE, et al. (2009) Molecular determinants of Grb14-mediated inhibition of insulin signaling. Molecular endocrinology 23: 1043–1051.

59. WaterworthDM, RickettsSL, SongK, ChenL, ZhaoJH, et al. (2010) Genetic variants influencing circulating lipid levels and risk of coronary artery disease. Arteriosclerosis, thrombosis, and vascular biology 30: 2264–2276.

60. PruittKD, TatusovaT, MaglottDR (2007) NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic acids research 35: D61–65.

61. PearlmanA, LokeJ, Le CaignecC, WhiteS, ChinL, et al. (2010) Mutations in MAP3K1 cause 46,XY disorders of sex development and implicate a common signal transduction pathway in human testis determination. American journal of human genetics 87: 898–904.

62. LeendersF, TesdorpfJG, MarkusM, EngelT, SeedorfU, et al. (1996) Porcine 80-kDa protein reveals intrinsic 17 beta-hydroxysteroid dehydrogenase, fatty acyl-CoA-hydratase/dehydrogenase, and sterol transfer activities. J Biol Chem 271: 5438–5442.

63. PeltoketoH, IsomaaV, PoutanenM, VihkoR (1996) Expression and regulation of 17 beta-hydroxysteroid dehydrogenase type 1. J Endocrinol 150 Suppl: S21–30.

64. ThompsonJB, DzuburE, WadeJ, TomaszyckiM (2011) The effects of estradiol on 17beta-hydroxysteroid dehydrogenase type IV and androgen receptor expression in the developing zebra finch song system. Brain research 1401: 66–73.

65. LiY, WillerC, SannaS, AbecasisG (2009) Genotype imputation. Annual review of genomics and human genetics 10: 387–406.

66. MarchiniJ, HowieB, MyersS, McVeanG, DonnellyP (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nature genetics 39: 906–913.

67. GuanY, StephensM (2008) Practical issues in imputation-based association mapping. PLoS genetics 4: e1000279.

68. LiY, WillerCJ, DingJ, ScheetP, AbecasisGR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genetic epidemiology 34: 816–834.

69. AulchenkoYS, StruchalinMV, van DuijnCM (2010) ProbABEL package for genome-wide association analysis of imputed data. BMC bioinformatics 11: 134.

70. AulchenkoYS, RipkeS, IsaacsA, van DuijnCM (2007) GenABEL: an R library for genome-wide association analysis. Bioinformatics 23: 1294–1296.

71. AbecasisGR, WiggintonJE (2005) Handling marker-marker linkage disequilibrium: pedigree analysis with clustered markers. American journal of human genetics 77: 754–767.

72. PurcellS, NealeB, Todd-BrownK, ThomasL, FerreiraMA, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. American journal of human genetics 81: 559–575.

73. ServinB, StephensM (2007) Imputation-based analysis of association studies: candidate regions and quantitative traits. PLoS genetics 3: e114.

74. DevlinB, RoederK (1999) Genomic control for association studies. Biometrics 55: 997–1004.

75. WillerCJ, LiY, AbecasisGR (2010) METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26: 2190–2191.

76. ProkopenkoI, LangenbergC, FlorezJC, SaxenaR, SoranzoN, et al. (2009) Variants in MTNR1B influence fasting glucose levels. Nature genetics 41: 77–81.

77. SegreAV, GroopL, MoothaVK, DalyMJ, AltshulerD (2010) Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS genetics 6: e1001058 doi:10.1371/journal.pgen.1001058

78. HindorffLA, SethupathyP, JunkinsHA, RamosEM, MehtaJP, et al. (2009) Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proceedings of the National Academy of Sciences of the United States of America 106: 9362–9367.

79. Hindorff LA, MacArthur JEBI, Wise A, Junkins HA, Hall PN, et al.. (2010) A Catalog of Published Genome-Wide Association Studies.

80. JohnsonAD, HandsakerRE, PulitSL, NizzariMM, O'DonnellCJ, et al. (2008) SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24: 2938–2939.

81. KumarP, HenikoffS, NgPC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4: 1073–1081.

82. XuZ, TaylorJA (2009) SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic acids research 37: W600–605.

Štítky
Genetika Reprodukčná medicína

Článok vyšiel v časopise

PLOS Genetics


2013 Číslo 6
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autori: MUDr. Tomáš Ürge, PhD.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#