Literature DB >> 23977173

The FTO gene rs9939609 polymorphism predicts risk of cardiovascular disease: a systematic review and meta-analysis.

Chibo Liu1, Sihua Mou, Chunqin Pan.   

Abstract

OBJECTIVE: Genome-wide association studies have shown that variance in the fat mass- and obesity- associated gene (FTO) is associated with risk of obesity in Europeans and Asians. Since obesity is associated with an increased risk of cardiovascular disease (CVD), several studies have investigated the association between variant in the FTO gene and CVD risk, with inconsistent results. In this study, we performed a meta-analysis to clarify the association of rs9939609 variant (or its proxies [r (2)>0.90]) in the FTO gene with CVD risk.
METHODS: Published literature from PubMed and Embase was retrieved. Pooled odds ratios with 95% confidence intervals were calculated using the fixed- or random- effects model.
RESULTS: A total of 10 studies (comprising 19,153 CVD cases and 103,720 controls) were included in the meta-analysis. The results indicated that the rs9939609 variant was significantly associated with CVD risk (odds ratio = 1.18, 95% confidence interval = 1.07-1.30, p = 0.001 [Z test], I (2) = 80.6%, p<0.001 [heterogeneity]), and there was an insignificant change after adjustment for body mass index (BMI) and other conventional CVD risk factors (odds ratio = 1.16, 95% confidence interval = 1.05-1.27, p = 0.003 [Z test], I (2) = 75.4%, p<0.001 [heterogeneity]).
CONCLUSIONS: The present meta-analysis confirmed the significant association of the rs9939609 variant in the FTO gene with CVD risk, which was independent of BMI and other conventional CVD risk factors.

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Year:  2013        PMID: 23977173      PMCID: PMC3747067          DOI: 10.1371/journal.pone.0071901

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

The prevalence of obesity has greatly increased globally [1], [2]. Obesity is one of the main risk factors for the development of hypertension, metabolic syndrome, type 2 diabetes (T2D), and cardiovascular disease (CVD) [3]. Recently, a genome-wide association study has identified the fat mass- and obesity- associated gene (FTO) associated with higher body mass index (BMI) and risk of obesity in the Europeans [4]. Since then, the association has been replicated in other ethnic populations [5], [6]. In addition, the original publication also indicated that the FTO gene variant affected T2D through an association with BMI/obesity [4]. However, the subsequent studies supported the conclusion that FTO gene variant was associated with risk of T2D independently of BMI [5], [7]. Since obesity is a well established risk factor for CVD, it is more likely that the FTO gene, as the BMI/obesity related locus, might confer the risk on CVD. To date, nine papers have investigated the association between variance in FTO gene and CVD risk [8]–[16]. However, the results have been inconsistent, which might be due to the differences in statistical power for each included study (the sample size in each study varied greatly), recruitment of study population, genetic and environmental background. Meta-analysis is a useful method to overcome the disadvantages of individual studies, thereby increasing the statistical power and the precision of effect estimates. In this study, we performed a meta-analysis to clarify the association between FTO gene rs9939609 variant (or its proxies [r 2>0.90]) [5] and the risk of CVD.

Methods

Literature and Search Strategy

We searched literature databases, including PubMed and Embase. The search strategy was to identify all possible studies involving the following key words: (fat-mass and obesity-associated gene or FTO) and (polymorphism or variant or variation or genotype) and (acute coronary syndromes or myocardial infarction or coronary artery disease or coronary heart disease or ischemic heart disease or cardiovascular disease or stroke). The publication language was restricted to English. The reference lists of retrieved articles were hand-searched. The literature search was updated on 31 December 2012.

Inclusion Criteria and Data Extraction

The studies were included in the meta-analysis only if they met all the following inclusion criteria: (1) evaluation of the association of FTO rs9939609 polymorphism (or its proxies [r 2>0.90]) with risk of CVD; (2) use of a case–control or cohort design; and (3) provision of an odds ratio (OR) with 95% confidence interval (CI) under an additive model with or without adjustment for BMI and other conventional CVD risk factors (e.g., age, sex, alcohol use, caloric intake, saturated fat and fiber intake, smoking, and obesity). The following information was extracted from each study: (1) name of the first author; (2) year of publication; (3) country of origin; (4) ethnicity of the studied population; (5) number of cases and controls; (6) endpoint; (7) frequency of men and the mean ages; (8) mean BMI; and (9) studied SNP. Two authors independently reviewed the articles for compliance with the inclusion/exclusion criteria, resolved disagreements and reached a consistent decision. All participants of the included studies provided informed consent and the studies were approved by the ethics committees of the participating institutions.

Statistical Analysis

The association of FTO polymorphism with CVD was estimated by calculating the pooled OR and 95% CI. The significance of the OR was determined by the Z test (p<0.05 was considered statistically significant). Cochrane’s Q test was performed to test the between-study heterogeneity [17], [18]. I 2 represents the range for the existence or no of heterogeneity. Usually, I 2>50% represents the existence of heterogeneity. A random-effects (DerSimonian–Laird [17]) or fixed-effects (Mantel–Haenszel [18]) model was used to calculate the pooled OR in the presence (p≤0.10) or absence (p>0.10) of heterogeneity, respectively. To evaluate the stability of the results, we performed a sensitivity analysis by removing one study at a time. Publication bias was assessed by Begg’s test [19] (p<0.05 was considered statistically significant). Data were analysed using STATA version 11.0 (StataCorp LP, College Station, TX, USA).

Results

Characteristics of the Studies

A flow chart describing the process of inclusion/exclusion of studies is presented in Fig. 1. The literature search identified a total of 126 potentially relevant articles. Of these, 113 were excluded after reading the title or abstract because of obvious irrelevance. In addition, three articles were excluded as they investigated the association between the FTO polymorphism and risk factors for CVD, e.g., obesity, hypertension, diabetes and insulin resistance [20]–[22]. Therefore, 10 articles met the primary inclusion criteria, of which one article was excluded because it did not provide the sufficient data for calculation of an OR with 95% CI [23]. In addition, the two studies included in the paper by Lappalainen et al. [12] were considered as separate studies in the following data analysis. The variant rs9939609 is known to be in high linkage disequilibrium with proxies including rs8050136, rs17817449 and rs9937053 (All r 2>0.90). A total of 10 studies (comprising 19,153 CVD cases and 103,720 controls) for rs9939609 polymorphism (or its proxies) were included in the meta-analysis [8]–[16]. All studies were conducted in the European populations. The genotype frequency in controls was in Hardy–Weinberg equilibrium for all included studies (p>0.05). All studies (except for one study in the paper by Lappalainen et al. [12]) provided the crude and adjusted (adjusted for BMI and other conventional CVD risk factors calculated by multiple logistic regression model for each study) ORs with 95% CIs, and the majority provided OR with 95% CI under an additive genetic model, hence we calculated the summary estimate under this model only. All included studies were conducted in European population. The characteristics of the included studies are listed in Table 1.
Figure 1

Flow chart of meta-analysis for exclusion/inclusion of individual articles (or studies).

* One article (Lappalainen et al, 2011) contained two studies.

Table 1

Characteristics of individual studies included in the meta-analysis.

Authors (ref)CountryEthnicitySample sizeEndpointSex (% men)Age (Mean [SD], years)BMI (Mean [SD], kg/m2) FTO SNP (risk/non-risk allele)Genotyping methodStatisticalpower a
CasesControls
Doney, 2009 (8)UKEuropean3243777MIAll: 45.7All: 63.7 (11.7)All: 30.7 (5.9)rs9939609(A/T)TAQMAN, KASPAR0.886
Ahmad, 2010 (9)USAEuropean55518271CVDAll were womenAll: 52.0 (48.0–59.0)All: 24.9 (22.5–28.3)rs8050136(A/C)Illumina0.989
He, 2010 (10)USAEuropean425901CVDAll were womenCases: 60 (6)Controls: 57 (7)Cases: 30.1(6.0)Controls: 30.1(7.0)rs9939609(A/T)OpenArray™0.875
Hubacek, 2010 (11)CzechEuropean10921191ACSAll were menCases: 55.2 (7.5)Controls: 49.0 (10.8)Cases: 28.5 (4.3)Controls: 28.2 (4.0)rs17817449(G/T)PCR–RFLP0.992
Lappalainen, 2011 (12)FinlandEuropean250240CVDAll: 49.8All: 55.3 (7.0)All: 31.3 (4.6)rs9939609(A/T)TaqMan0.524
Lappalainen, 2011 (12)FinlandEuropean8515363CVDAll were menAll: 58.7 (6.4)All: 27.3 (4.2)rs9939609(A/T)TaqMan0.998
Winter, 2011 (13)GermanyEuropean379379StrokeCases: 62.8Controls: 62.8Cases: 67 (11)Controls: 65 (9)Cases: 28 (4)Controls: 27 (4)rs9937053(A/T)TaqMan0.710
Berzuini, 2012 (14)ItalyEuropean18381838MINANANArs9939609(A/T)MassARRAY0.999
Borglykke, 2012 (15)DenmarkEuropean23837189CVDMONICA 1: 50.9Inter99: 48.1MONICA 1: 45.0 (7.3)Inter99: 45.9 (7.9)MONICA 1: 24.6 (3.9)Inter99: 26.2 (4.6)rs9939609(A/T)KASPar0.999
Nordestgaard, 2012 (16)DenmarkEuropean1105664571IHDCGPS: 44.4CCHS: 44.4CIHDS: 57.0CGPS: 57 (47–67)CCHS: 60 (47–70)CIHDS: 60 (51–69)CGPS: 25.6 (23.2–28.5)CCHS: 23.9 (21.8–26.7)CIHDS:25.5 (23.3–28.1)rs9939609(A/T)ABI PRISM 7900HT0.999

MI, myocardial infarction; CVD, cardiovascular disease; ACS, acute coronary syndrome; IHD, ischemic heart disease; NA, not available; MONICA, the study focus on multinational monitoring of trends and determinants in cardiovascular disease; Inter99, the study focus on effect on IHD incidence of individually tailored non-pharmacological intervention on lifestyle using a newly developed computer-based health educational tool; CGPS, Copenhagen General Population Study; CCHS, Copenhagen City Heart Study; CIHDS, Copenhagen Ischemic Heart Disease Study.

The power calculation was performed using Quanto software http://hydra.usc.edu/gxe/.

Flow chart of meta-analysis for exclusion/inclusion of individual articles (or studies).

* One article (Lappalainen et al, 2011) contained two studies. MI, myocardial infarction; CVD, cardiovascular disease; ACS, acute coronary syndrome; IHD, ischemic heart disease; NA, not available; MONICA, the study focus on multinational monitoring of trends and determinants in cardiovascular disease; Inter99, the study focus on effect on IHD incidence of individually tailored non-pharmacological intervention on lifestyle using a newly developed computer-based health educational tool; CGPS, Copenhagen General Population Study; CCHS, Copenhagen City Heart Study; CIHDS, Copenhagen Ischemic Heart Disease Study. The power calculation was performed using Quanto software http://hydra.usc.edu/gxe/.

Meta-analysis Results

The results indicated a significant association of the rs9939609 polymorphism in the FTO gene with the risk of CVD (OR = 1.18, 95% CI = 1.07–1.30, p = 0.001 [Z test], I 2 = 80.6%, p<0.001 [heterogeneity], Fig. 2), which did not substantially change after adjustment for BMI and other conventional CVD risk factors (OR = 1.16, 95% CI = 1.05–1.27, p = 0.003 [Z test], I 2 = 75.4%, p<0.001 [heterogeneity], Fig. 3).
Figure 2

Meta-analysis of the association between rs9939609 (or its proxies) polymorphism in the FTO gene and cardiovascular disease risk.

OR is reported to increased CVD risk; weights are calculated from the inverse of their variance.

Figure 3

Meta-analysis of the association between rs9939609 (or its proxies) polymorphism in the FTO gene and cardiovascular disease risk after adjustment for BMI and other conventional CVD risk factors.

OR is reported to increased CVD risk; weights are calculated from the inverse of their variance.

Meta-analysis of the association between rs9939609 (or its proxies) polymorphism in the FTO gene and cardiovascular disease risk.

OR is reported to increased CVD risk; weights are calculated from the inverse of their variance.

Meta-analysis of the association between rs9939609 (or its proxies) polymorphism in the FTO gene and cardiovascular disease risk after adjustment for BMI and other conventional CVD risk factors.

OR is reported to increased CVD risk; weights are calculated from the inverse of their variance.

Source of Heterogeneity

Meta-regress was conducted to examine the source of heterogeneity. Publication year, country, design, number of cases and controls were considered as independent variables. However, these variables can’t explain the source of heterogeneity (all p>0.05). Galbraith figure was drawn to identify outliers of the source of heterogeneity. In the model unadjusted for BMI, four studies [8], [10], [14], [15] were the outliers (Figure S1). In the model adjusted for BMI, five studies [8], [10], [11], [12], [14] were the outliers (Figure S2).

Sensitivity Analysis

Sensitivity analysis was performed by excluding one study at a time. The results confirmed the significant association between the rs9939609 polymorphism in the FTO gene and the risk of CVD, with ORs and 95% CIs ranging from 1.13 (1.04, 1.24) to 1.23 (1.09, 1.39) (Table S1), and from 1.12 (1.02, 1.23) to 1.22 (1.07, 1.39) after adjustment for BMI and other conventional CVD risk factors (Table S2).

Publication Bias

No publication bias was observed for the association between rs9939609 polymorphism and CVD risk without (p = 0.118, Figure S3) or with (p = 0.152, Figure S4) adjustment for BMI other conventional CVD risk factors.

Discussion

To our knowledge, this is the first meta-analysis investigating the association between the FTO gene variant and CVD risk. Our meta-analysis with 19,383 CVD cases and 103,490 controls indicated that the FTO gene rs9939609 variant was significantly associated with an increased risk of CVD and the association did not substantially alter even after adjustment for BMI and other conventional CVD risk factors. In 2007, Frayling et al. [4] initially reported that the FTO gene rs9939609 variant was significantly associated with T2D in Europeans, which was completely explained by the effect of the FTO gene variant on BMI. However, the recent two meta-analyses suggested that the FTO gene variant influenced the risk of T2D independently of BMI in both Europeans and East Asians [5], [7]. Regarding for the association between FTO gene and CVD risk, Doney et al. [8] firstly demonstrated that the A allele of rs9939609 in the FTO gene increased the risk of myocardial infarction in 4,897 patients with T2D in the prospective study, which was independently of BMI, glycohemoglobin, mean arterial pressure, HDL-C, triglycerides, and total cholesterol. However, the subsequent eight papers revealed conflicting conclusions [9]–[16]. Pooling all the studies together, we found the significant association between the FTO gene variant and CVD risk independent of BMI and other conventional CVD risk factors. The mechanism underlying the association of the FTO variant with CVD risk remains unclear. As is known, FTO protein is highly expressed in the central nervous system, which regulates energy metabolism [24]. Indeed, the FTO gene variant is found to influence energy-dense food intake instead of regulation of energy expenditure [25]. In addition, the FTO variant is associated with diabetes-related metabolic traits (including higher fasting insulin, glucose and triglycerides, and lower HDL cholesterol), although the association disappeared after adjustment for BMI [26]. Other studies have indicated that FTO variant is associated with increased risk for hypertension through the regulation of sympathetic modulation of vasomotor tone [27]. Notably, Hubacek et al. [11] believed that the FTO variant could increase the risk of CVD through another mechanism, namely through its possible effect on DNA methylation. In other words, the FTO gene variant could interact with an unhealthy lifestyle (such as high fat diet and lack of physical activity), and affect the epigenetic status [11] and ultimately contribute to the development of CVD. Our study is subject to several limitations. First, the individual studies are not homogeneous in the subject cases that might have an effect in the meta-analysis (Table 1). Only five studies provided the specific endpoint (two were on myocardial infarction, one was on acute coronary syndrome, one was on stroke and one was on ischemic heart disease) and the remaining five studies indicated CVD only. Thus, we were unable to perform the subgroup analysis to observe the effect of different endpoints on the association. Second, we only calculated the pooled OR under an additive model since most studies provided OR with 95%CI under this model only. In other word, the insufficient data under dominant and recessive models impeded us for further analysis. Third, the genotyping methods are different among the included studies, which may influence the association between FTO gene variant and CVD risk. In conclusion, our meta-analysis confirmed that the FTO gene rs9939609 variant is significantly associated with an increased risk of CVD in the Europeans and the genetic effect is not mediated by the changes in BMI and other conventional CVD risk factors. The observed association remains to be replicated in the non-European populations. Further studies should be conducted to investigate the mechanism underlying the link between FTO gene and CVD risk. Galbraith figure for identification outliers of the source of heterogeneity in the model unadjusted for BMI. (TIF) Click here for additional data file. Galbraith figure for identification outliers of the source of heterogeneity in the model adjusted for BMI. (TIF) Click here for additional data file. Funnel plot for the association between rs9939609 polymorphism and CVD risk without adjustment for BMI. (TIF) Click here for additional data file. Funnel plot for the association between rs9939609 polymorphism and CVD risk with adjustment for BMI. (TIF) Click here for additional data file. (DOC) Click here for additional data file. (DOC) Click here for additional data file.
  27 in total

1.  A FTO variant and risk of acute coronary syndrome.

Authors:  Jaroslav A Hubacek; Vladimír Stanek; Marie Gebauerová; Alexandra Pilipcincová; Dana Dlouhá; Rudolf Poledne; Michal Aschermann; Hana Skalická; Jana Matousková; Andreas Kruger; Martin Penicka; Hana Hrabáková; Josef Veselka; Petr Hájek; Vera Lánská; Vera Adámková; Jan Pitha
Journal:  Clin Chim Acta       Date:  2010-04-01       Impact factor: 3.786

2.  A common variant of the FTO gene is associated with not only increased adiposity but also elevated blood pressure in French Canadians.

Authors:  Zdenka Pausova; Catriona Syme; Michal Abrahamowicz; Yongling Xiao; Gabriel T Leonard; Michel Perron; Louis Richer; Suzanne Veillette; George Davey Smith; Ondrej Seda; Johanne Tremblay; Pavel Hamet; Daniel Gaudet; Tomas Paus
Journal:  Circ Cardiovasc Genet       Date:  2009-03-31

3.  Meta-analysis in clinical trials.

Authors:  R DerSimonian; N Laird
Journal:  Control Clin Trials       Date:  1986-09

4.  Operating characteristics of a rank correlation test for publication bias.

Authors:  C B Begg; M Mazumdar
Journal:  Biometrics       Date:  1994-12       Impact factor: 2.571

5.  The fat-mass and obesity-associated (FTO) gene, physical activity, and risk of incident cardiovascular events in white women.

Authors:  Tariq Ahmad; Daniel I Chasman; Samia Mora; Guillaume Paré; Nancy R Cook; Julie E Buring; Paul M Ridker; I-Min Lee
Journal:  Am Heart J       Date:  2010-12       Impact factor: 4.749

6.  Association of the FTO gene variant (rs9939609) with cardiovascular disease in men with abnormal glucose metabolism--the Finnish Diabetes Prevention Study.

Authors:  T Lappalainen; M Kolehmainen; U S Schwab; A M Tolppanen; A Stančáková; J Lindström; J G Eriksson; S Keinänen-Kiukaanniemi; S Aunola; P Ilanne-Parikka; C Herder; W Koenig; H Gylling; H Kolb; J Tuomilehto; J Kuusisto; M Uusitupa
Journal:  Nutr Metab Cardiovasc Dis       Date:  2010-04-18       Impact factor: 4.222

7.  The association of the FTO rs9939609 polymorphism with obesity and metabolic risk factors for cardiovascular diseases in Polish children.

Authors:  W Luczynski; G Zalewski; A Bossowski
Journal:  J Physiol Pharmacol       Date:  2012-06       Impact factor: 3.011

8.  A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity.

Authors:  Timothy M Frayling; Nicholas J Timpson; Michael N Weedon; Eleftheria Zeggini; Rachel M Freathy; Cecilia M Lindgren; John R B Perry; Katherine S Elliott; Hana Lango; Nigel W Rayner; Beverley Shields; Lorna W Harries; Jeffrey C Barrett; Sian Ellard; Christopher J Groves; Bridget Knight; Ann-Marie Patch; Andrew R Ness; Shah Ebrahim; Debbie A Lawlor; Susan M Ring; Yoav Ben-Shlomo; Marjo-Riitta Jarvelin; Ulla Sovio; Amanda J Bennett; David Melzer; Luigi Ferrucci; Ruth J F Loos; Inês Barroso; Nicholas J Wareham; Fredrik Karpe; Katharine R Owen; Lon R Cardon; Mark Walker; Graham A Hitman; Colin N A Palmer; Alex S F Doney; Andrew D Morris; George Davey Smith; Andrew T Hattersley; Mark I McCarthy
Journal:  Science       Date:  2007-04-12       Impact factor: 47.728

9.  FTO gene polymorphisms and obesity risk: a meta-analysis.

Authors:  Sihua Peng; Yimin Zhu; Fangying Xu; Xiaobin Ren; Xiaobo Li; Maode Lai
Journal:  BMC Med       Date:  2011-06-08       Impact factor: 8.775

10.  Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

Authors:  Cristen J Willer; Elizabeth K Speliotes; Ruth J F Loos; Shengxu Li; Cecilia M Lindgren; Iris M Heid; Sonja I Berndt; Amanda L Elliott; Anne U Jackson; Claudia Lamina; Guillaume Lettre; Noha Lim; Helen N Lyon; Steven A McCarroll; Konstantinos Papadakis; Lu Qi; Joshua C Randall; Rosa Maria Roccasecca; Serena Sanna; Paul Scheet; Michael N Weedon; Eleanor Wheeler; Jing Hua Zhao; Leonie C Jacobs; Inga Prokopenko; Nicole Soranzo; Toshiko Tanaka; Nicholas J Timpson; Peter Almgren; Amanda Bennett; Richard N Bergman; Sheila A Bingham; Lori L Bonnycastle; Morris Brown; Noël P Burtt; Peter Chines; Lachlan Coin; Francis S Collins; John M Connell; Cyrus Cooper; George Davey Smith; Elaine M Dennison; Parimal Deodhar; Paul Elliott; Michael R Erdos; Karol Estrada; David M Evans; Lauren Gianniny; Christian Gieger; Christopher J Gillson; Candace Guiducci; Rachel Hackett; David Hadley; Alistair S Hall; Aki S Havulinna; Johannes Hebebrand; Albert Hofman; Bo Isomaa; Kevin B Jacobs; Toby Johnson; Pekka Jousilahti; Zorica Jovanovic; Kay-Tee Khaw; Peter Kraft; Mikko Kuokkanen; Johanna Kuusisto; Jaana Laitinen; Edward G Lakatta; Jian'an Luan; Robert N Luben; Massimo Mangino; Wendy L McArdle; Thomas Meitinger; Antonella Mulas; Patricia B Munroe; Narisu Narisu; Andrew R Ness; Kate Northstone; Stephen O'Rahilly; Carolin Purmann; Matthew G Rees; Martin Ridderstråle; Susan M Ring; Fernando Rivadeneira; Aimo Ruokonen; Manjinder S Sandhu; Jouko Saramies; Laura J Scott; Angelo Scuteri; Kaisa Silander; Matthew A Sims; Kijoung Song; Jonathan Stephens; Suzanne Stevens; Heather M Stringham; Y C Loraine Tung; Timo T Valle; Cornelia M Van Duijn; Karani S Vimaleswaran; Peter Vollenweider; Gerard Waeber; Chris Wallace; Richard M Watanabe; Dawn M Waterworth; Nicholas Watkins; Jacqueline C M Witteman; Eleftheria Zeggini; Guangju Zhai; M Carola Zillikens; David Altshuler; Mark J Caulfield; Stephen J Chanock; I Sadaf Farooqi; Luigi Ferrucci; Jack M Guralnik; Andrew T Hattersley; Frank B Hu; Marjo-Riitta Jarvelin; Markku Laakso; Vincent Mooser; Ken K Ong; Willem H Ouwehand; Veikko Salomaa; Nilesh J Samani; Timothy D Spector; Tiinamaija Tuomi; Jaakko Tuomilehto; Manuela Uda; André G Uitterlinden; Nicholas J Wareham; Panagiotis Deloukas; Timothy M Frayling; Leif C Groop; Richard B Hayes; David J Hunter; Karen L Mohlke; Leena Peltonen; David Schlessinger; David P Strachan; H-Erich Wichmann; Mark I McCarthy; Michael Boehnke; Inês Barroso; Gonçalo R Abecasis; Joel N Hirschhorn
Journal:  Nat Genet       Date:  2008-12-14       Impact factor: 38.330

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  17 in total

1.  Maternal and neonatal FTO rs9939609 polymorphism affect insulin sensitivity markers and lipoprotein profile at birth in appropriate-for-gestational-age term neonates.

Authors:  Eva Gesteiro; Francisco J Sánchez-Muniz; Carolina Ortega-Azorín; Marisa Guillén; Dolores Corella; Sara Bastida
Journal:  J Physiol Biochem       Date:  2016-02-06       Impact factor: 4.158

Review 2.  Clinical applications of epigenetics in cardiovascular disease: the long road ahead.

Authors:  Stella Aslibekyan; Steven A Claas; Donna K Arnett
Journal:  Transl Res       Date:  2014-04-08       Impact factor: 7.012

3.  FTO gene variation, macronutrient intake and coronary heart disease risk: a gene-diet interaction analysis.

Authors:  Jaana Gustavsson; Kirsten Mehlig; Karin Leander; Christina Berg; Gianluca Tognon; Elisabeth Strandhagen; Lena Björck; Annika Rosengren; Lauren Lissner; Fredrik Nyberg
Journal:  Eur J Nutr       Date:  2015-02-03       Impact factor: 5.614

4.  'The obesity paradox': a reconsideration of obesity and the risk of preterm birth.

Authors:  A Tsur; J A Mayo; R J Wong; G M Shaw; D K Stevenson; J B Gould
Journal:  J Perinatol       Date:  2017-07-27       Impact factor: 2.521

5.  Is the adiposity-associated FTO gene variant related to all-cause mortality independent of adiposity? Meta-analysis of data from 169,551 Caucasian adults.

Authors:  E Zimmermann; L H Ängquist; S S Mirza; J H Zhao; D I Chasman; K Fischer; Q Qi; A V Smith; M Thinggaard; M N Jarczok; M A Nalls; S Trompet; N J Timpson; B Schmidt; A U Jackson; L P Lyytikäinen; N Verweij; M Mueller-Nurasyid; M Vikström; P Marques-Vidal; A Wong; K Meidtner; R P Middelberg; R J Strawbridge; L Christiansen; K O Kyvik; A Hamsten; T Jääskeläinen; A Tjønneland; J G Eriksson; J B Whitfield; H Boeing; R Hardy; P Vollenweider; K Leander; A Peters; P van der Harst; M Kumari; T Lehtimäki; A Meirhaeghe; J Tuomilehto; K-H Jöckel; Y Ben-Shlomo; N Sattar; S E Baumeister; G Davey Smith; J P Casas; D K Houston; W März; K Christensen; V Gudnason; F B Hu; A Metspalu; P M Ridker; N J Wareham; R J F Loos; H Tiemeier; E Sonestedt; T I A Sørensen
Journal:  Obes Rev       Date:  2015-03-05       Impact factor: 9.213

6.  The obesity-risk variant of FTO is inversely related with the So-Eum constitutional type: genome-wide association and replication analyses.

Authors:  Seongwon Cha; Hyunjoo Yu; Ah Yeon Park; Soo A Oh; Jong Yeol Kim
Journal:  BMC Complement Altern Med       Date:  2015-04-15       Impact factor: 3.659

7.  FTO rs9939609 polymorphism is associated with metabolic disturbances and response to HCV therapy in HIV/HCV-coinfected patients.

Authors:  Daniel Pineda-Tenor; Juan Berenguer; María A Jiménez-Sousa; Mónica García-Alvarez; Teresa Aldámiz-Echevarria; Ana Carrero; Sonia Vázquez-Morón; Pilar García-Broncano; Cristina Diez; Francisco Tejerina; María Guzmán-Fulgencio; Salvador Resino
Journal:  BMC Med       Date:  2014-11-03       Impact factor: 8.775

8.  Role of a common variant of Fat Mass and Obesity associated (FTO) gene in obesity and coronary artery disease in subjects from Punjab, Pakistan: a case control study.

Authors:  Saleem Ullah Shahid; Abdul Rehman; Shahida Hasnain
Journal:  Lipids Health Dis       Date:  2016-02-16       Impact factor: 3.876

Review 9.  Type 2 Diabetes Mellitus and Cardiovascular Disease: Genetic and Epigenetic Links.

Authors:  Salvatore De Rosa; Biagio Arcidiacono; Eusebio Chiefari; Antonio Brunetti; Ciro Indolfi; Daniela P Foti
Journal:  Front Endocrinol (Lausanne)       Date:  2018-01-17       Impact factor: 5.555

10.  Is FTO gene variant related to cancer risk independently of adiposity? An updated meta-analysis of 129,467 cases and 290,633 controls.

Authors:  Yu Kang; Fang Liu; Yao Liu
Journal:  Oncotarget       Date:  2017-03-22
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