Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile : Nature Genetics : Nature Publishing Group

Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile : Nature Genetics : Nature Publishing Group: "Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile

* Tuomas O Kilpeläinen,1
* M Carola Zillikens,2, 3
* Alena Stančákova,4
* Francis M Finucane,1
* Janina S Ried,5
* Claudia Langenberg,1
* Weihua Zhang,6
* Jacques S Beckmann,7
* Jian'an Luan,1
* Liesbeth Vandenput,8
* Unnur Styrkarsdottir,9
* Yanhua Zhou,10
* Albert Vernon Smith,11
* Jing-Hua Zhao,1
* Najaf Amin,12
* Sailaja Vedantam,13, 14
* So-Youn Shin,15
* Talin Haritunians,16
* Mao Fu,17
* Mary F Feitosa,18
* Meena Kumari,19
* Bjarni V Halldorsson,9, 20
* Emmi Tikkanen,21, 22
* Massimo Mangino,23
* Caroline Hayward,24
* Ci Song,25
* Alice M Arnold,26
* Yurii S Aulchenko,12
* Ben A Oostra,12
* Harry Campbell,27
* L Adrienne Cupples,10, 28
* Kathryn E Davis,29
* Angela Döring,5
* Gudny Eiriksdottir,11
* Karol Estrada,2, 3, 12
* José Manuel Fernández-Real,30
* Melissa Garcia,31
* Christian Gieger,5
* Nicole L Glazer,32, 33
* Candace Guiducci,13
* Albert Hofman,3, 12
* Steve E Humphries,34
* Bo Isomaa,35, 36
* Leonie C Jacobs,2
* Antti Jula,37
* David Karasik,38
* Magnus K Karlsson,39, 40
* Kay-Tee Khaw,41
* Lauren J Kim,31
* Mika Kivimäki,42
* Norman Klopp,5
* Brigitte Kühnel,5
* Johanna Kuusisto,4
* Yongmei Liu,43
* Östen Ljunggren,44
* Mattias Lorentzon,8
* Robert N Luben,41
* Barbara McKnight,26, 32
* Dan Mellström,8
* Braxton D Mitchell,17
* Vincent Mooser,45
* José Maria Moreno,30
* Satu Männistö,46
* Jeffery R O'Connell,17
* Laura Pascoe,47
* Leena Peltonen,15, 21, 22, 75
* Belén Peral,48
* Markus Perola,21, 22
* Bruce M Psaty,32, 49, 50, 51, 52
* Veikko Salomaa,46
* David B Savage,53
* Robert K Semple,53
* Tatjana Skaric-Juric,54
* Gunnar Sigurdsson,55, 56
* Kijoung S Song,45
* Timothy D Spector,23
* Ann-Christine Syvänen,57
* Philippa J Talmud,34
* Gudmar Thorleifsson,9
* Unnur Thorsteinsdottir,9, 56
* André G Uitterlinden,2, 3, 12
* Cornelia M van Duijn,3, 12, 58
* Antonio Vidal-Puig,53
* Sarah H Wild,27
* Alan F Wright,24
* Deborah J Clegg,29
* Eric Schadt,59, 60
* James F Wilson,27
* Igor Rudan,27, 61, 62
* Samuli Ripatti,21, 22
* Ingrid B Borecki,18
* Alan R Shuldiner,17, 63
* Erik Ingelsson,25, 64
* John-Olov Jansson,65
* Robert C Kaplan,66
* Vilmundur Gudnason,11, 67
* Tamara B Harris,31
* Leif Groop,68
* Douglas P Kiel,38
* Fernando Rivadeneira,2, 3, 12
* Mark Walker,47
* Inês Barroso,15, 53
* Peter Vollenweider,69
* Gérard Waeber,69
* John C Chambers,6
* Jaspal S Kooner,70
* Nicole Soranzo,15
* Joel N Hirschhorn,13, 14, 71
* Kari Stefansson,9, 56
* H-Erich Wichmann,5, 72
* Claes Ohlsson,8
* Stephen O'Rahilly,53
* Nicholas J Wareham,1
* Elizabeth K Speliotes,13, 73
* Caroline S Fox,74
* Markku Laakso4
* & Ruth J F Loos1
* et al.

* Affiliations
* Contributions
* Corresponding author

Journal name: Nature Genetics
Year published: (2011)
DOI: doi:10.1038/ng.866

Received 18 January 2011
Accepted 25 May 2011
Published online 26 June 2011

Abstract
Genome-wide association studies have identified 32 loci influencing body mass index, but this measure does not distinguish lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ~2.5 million SNPs and body fat percentage from 36,626 individuals and followed up the 14 most significant (P < 10−6) independent loci in 39,576 individuals. We confirmed a previously established adiposity locus in FTO (P = 3 × 10−26) and identified two new loci associated with body fat percentage, one near IRS1 (P = 4 × 10−11) and one near SPRY2 (P = 3 × 10−8). Both loci contain genes with potential links to adipocyte physiology. Notably, the body-fat–decreasing allele near IRS1 is associated with decreased IRS1 expression and with an impaired metabolic profile, including an increased visceral to subcutaneous fat ratio, insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.

Figures at a glance
left

1. Figure 1: Manhattan plot showing the significance of association with body fat percentage for SNPs in the stage 1 meta-analysis of all individuals (n = 36,626).

SNPs are plotted on the x axis according to their position on each chromosome against association with body fat percentage on the y axis (shown as −log10 P). The loci highlighted in blue are the 11 loci that reached an association P < 10−6 in the stage 1 meta-analysis of all individuals, Europeans, men or women and were taken forward for follow-up analyses but did not achieve genome-wide significance (P < 5 × 10−8) in the meta-analyses combining GWAS and follow-up data. The three loci colored in red are those that reached genome-wide significant association (P < 5 × 10−8) in the meta-analyses combining GWAS and follow-up data.

2. Figure 2: Regional plot of the loci near IRS1, near SPRY2 and in FTO that reached genome-wide significant evidence for association with body fat percentage.

The plotted data for the locus near SPRY2 are from the meta-analysis of individuals of European descent only, and the data for the loci near IRS1 and in FTO are from the meta-analysis of all individuals. The rs2943650 (near IRS1), rs534870 (near SPRY2) and rs8050136 (FTO) SNPs that showed the strongest association with body fat percentage are indicated. For the locus near IRS1, rs2972146, rs2943641 and rs2943634, which have been associated with blood levels of HDL cholesterol and triglycerides9, risk of type 2 diabetes10 and risk of coronary artery disease11, respectively, in GWAS meta-analyses, are also indicated. The plot was generated using LocusZoom44 (see URLs).

3. Figure 3: Association of the body-fat-percentage–decreasing (T) allele of rs2943650 near IRS1 with blood lipids, insulin sensitivity traits, leptin and adiponectin.

The error bars indicate 95% confidence intervals. All traits were inverse normally transformed to approximate normality (mean = 0, s.d. = 1) in men and women separately. All models were adjusted for age and age squared. The numeric values for the associations are presented in Supplementary Table 6. We found a significant difference between men and women for the levels of HDL cholesterol (P = 0.027), triglycerides (P = 0.025) and adiponectin (P = 0.040). InsAUC/GluAUC, insulin area under the curve (AUC) to glucose AUC ratio.


- Enviado mediante la barra Google"