• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of springeropenLink to Publisher's site
Journal of Human Genetics
J Hum Genet. Jun 2008; 53(6): 546–553.
Published online Apr 1, 2008. doi:  10.1007/s10038-008-0283-1
PMCID: PMC2413114

Variations in the FTO gene are associated with severe obesity in the Japanese

Abstract

Variations in the fat-mass and obesity-associated gene (FTO) are associated with the obesity phenotype in many Caucasian populations. This association with the obesity phenotype is not clear in the Japanese. To investigate the relationship between the FTO gene and obesity in the Japanese, we genotyped single nucleotide polymorphisms (SNPs) in the FTO genes from severely obese subjects [n = 927, body mass index (BMI) ≥ 30 kg/m2] and normal-weight control subjects (n = 1,527, BMI < 25 kg/m2). A case-control association analysis revealed that 15 SNPs, including rs9939609 and rs1121980, in a linkage disequilibrium (LD) block of approximately 50 kb demonstrated significant associations with obesity; rs1558902 was most significantly associated with obesity. P value in additive mode was 0.0000041, and odds ratio (OR) adjusted for age and gender was 1.41 [95% confidential interval (CI) = 1.22–1.62]. Obesity-associated phenotypes, which include the level of plasma glucose, hemoglobin A1c, total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and blood pressure were not associated with the rs1558902 genotype. Thus, the SNPs in the FTO gene were found to be associated with obesity, i.e., severe obesity, in the Japanese.

Electronic supplementary material

The online version of this article (doi:10.1007/s10038-008-0283-1) contains supplementary material, which is available to authorized users.

Keywords: Fat-mass and obesity-associated gene, Obesity, Japanese population, Association, SNP

Introduction

Obesity is the most common nutritional disorder in developed countries, and it is a major risk factor for hypertension, cardiovascular disease, and type 2 diabetes (Kopelman 2000; Wilson et al. 2003). Genetic and environmental factors contribute to obesity development (Maes et al. 1997; Barsh et al. 2000; Rankinen et al. 2006). Recent progress in single nucleotide polymorphism (SNP) genotyping techniques has enabled genome-wide association studies on common diseases (Herbert et al. 2006; Frayling et al. 2007; Scuteri et al. 2007; The Wellcome Trust Case Control Consortium 2007; Hinney et al. 2007). Using a large-scale case-control association study, we found that secretogranin III (SCG3) (Tanabe et al. 2007) and myotubularin-related protein 9 (MTMR9) (Yanagiya et al. 2007) are involved in susceptibility to the obesity phenotype. Genome-wide association studies have shown that the fat-mass and obesity-associated gene (FTO) is also associated with the obesity phenotype (Frayling et al. 2007; Scuteri et al. 2007; Hinney et al. 2007). This association was also found in many Caucasian and Hispanic American populations (Frayling et al. 2007; Scuteri et al. 2007; Dina et al. 2007; Field et al. 2007; Andreasen et al. 2008; Wåhlén et al. 2008; Peeters et al. 2008), whereas it was not found in the Chinese Han population (Li et al. 2008). Among Japanese, body mass index (BMI) was higher in subjects who had the A allele of rs9939609, similar to that observed in Caucasians; however, this finding was not significant (Horikoshi et al. 2007). Another group reported that rs9939609 was associated with BMI in the Japanese (Omori et al. 2008). Thus, the association of SNPs in the FTO gene with obesity in the Japanese remains controversial.

To investigate the relationship between the FTO gene and obesity in the Japanese, we performed a case-control association study using patients with severe adult obesity (BMI ≥ 30 kg/m2) and normal-weight controls (BMI < 25 kg/m2); we found that SNPs in intron 1 of the FTO gene were associated with severe adult obesity.

Materials and methods

Study subjects

The sample size for severely obese Japanese subjects (BMI ≥ 30 kg/m2) was 927 (male:female ratio 419:508, age 48.7 ± 14.2 years, BMI 34.2 ± 5.4 kg/m2), whereas that for Japanese normal weight controls (BMI < 25 kg/m2) was 1,527 (male:female ratio 685:842, age 48.1 ± 16.5 years, BMI 21.7 ± 2.1 kg/m2). The severely obese subjects were recruited from among outpatients of medical institutes. Patients with secondary obesity and obesity-related hereditary disorders were not included, and neither were patients with medication-induced obesity. The normal-weight controls were recruited from among subjects who had undergone a medical examination for screening of common diseases. Clinical features of the subjects are illustrated in Table 1. Additionally, 1,604 subjects were recruited (male:female ratio 803:801, age 48.7 ± 16.9 years, BMI 22.66 ± 3.16 kg/m2) from the Japanese general population. Each subject provided written informed consent, and the protocol was approved by the ethics committee of each institution and that of RIKEN.

Table 1
Clinical characterization of obese and control subjects

DNA preparation and SNP genotyping

Genomic DNA was prepared from the blood sample of each subject by using the Genomix (Talent Srl, Trieste, Italy). We searched for dbSNPs with minor allele frequencies (MAF) > 0.10 in the FTO gene of Japanese people. We selected 90 SNPs and were able to construct Invader probes (Third Wave Technologies, Madison, WI) for them (Supplementary Table 1). SNPs were genotyped using Invader assays as described previously (Ohnishi et al. 2001; Takei et al. 2002). Nine SNPs (rs9937053, rs9939973, rs9940128, rs7193144, rs8043757, rs9923233, rs9926289, rs9939609, and rs9930506) reported in a previous genome-wide association study (Scuteri et al. 2007) were genotyped using TaqMan probes (C__29910458_10, C__11776771_10, C__29621384_10, C__29387650_10, C__29387665_10, C__29693738_10, C__30270568_10, C__30090620_10, and C__29819994_10; Applied Biosystems, Foster City, CA, USA).

Statistical analysis

Genotype or allele frequencies were compared between cases and controls in three different modes. In the first mode, i.e., the additive mode, χ2 test was performed according to Sladek et al. (Sladek et al. 2007). In the second mode, i.e., the minor allele recessive mode, frequencies of the homozygous genotype for the minor allele were compared using a 2 × 2 contingency table. In the third mode, i.e., the minor allele dominant mode, frequencies of the homozygous genotype for the major allele were compared using a 2 × 2 contingency table. A test of independence was performed using Pearson’s χ2 method. P values were corrected by Bonferroni adjustment and P < 0.00017 [0.05/99 (total SNP number)/3 (number of modes)] was considered significant. The odds ratio (OR) and 95% confidence interval (CI) were calculated by Woolf’s method. We coded genotypes as 0, 1, and 2, depending on the number of copies of the risk alleles. OR adjusted for age and gender was calculated using multiple logistic regression with genotypes, age, and gender as independent variables. Hardy–Weinberg equilibrium was assessed using the χ2 test (Nielsen et al. 1998). Haplotype blocks were determined using Haploview (Barrett et al. 2005). Simple comparison of the clinical data among the different genotypes was performed using one-way analysis of variance (ANOVA). Simple comparison of the clinical data between case and control groups was analyzed using Mann–Whitney U test. Difference in BMI between genotypes was analyzed using a multiple linear regression, with BMI as the dependent variable and genotype as the independent variable, and with gender and age as covariates for BMI. Statistical analyses were performed using StatView 5.0 (SAS Institute, Cary, NC, USA). Power was calculated by the Monte Carlo method.

Results

Case-control association studies

We searched for dbSNPs with MAF > 0.10 in the FTO gene. By using Invader and TaqMan assay, we successfully genotyped 99 SNPs spanning the FTO gene (Supplementary Table 1). Using these SNPs, we performed tests of independence between the phenotype and genotypes of obesity at each SNP by using severely obese subjects (BMI ≥ 30 kg/m2) and normal weight controls (BMI < 25 kg/m2). For each SNP, the lowest P value among the three different modes was selected as the minimum P value. All SNPs, including rs1421084, were in Hardy–Weinberg equilibrium (P > 0.01) (Supplementary Table 1).

The power of the test was calculated by Monte Carlo method with different MAFs and different effect sizes. Effect of the risk allele on penetrance was assumed to be multiplicative; i.e., the penetrances for three genotypes were assumed to be a, ar, and ar2, respectively, where a and r denote the lowest penetrance and genotype relative risk, respectively. Supplementary Table 2 shows the calculated values of the power of the test with different MAFs and different genotype relative risks (r). The lowest penetrance (a) was calculated for each gender by assuming the affection rates of 2.3% for men and 3.4% for women (Yoshiike et al. 2002). Genotype relative risk (r) was assumed to be the same for both genders. Supplementary Table 2 shows that the test has significant power at relative high risk allele frequency when genotype relative risk is >1.7.

As shown in Fig. 1 and Supplementary Table 1, 15 SNPs demonstrated significant associations with the obesity phenotype; the threshold of significance using Bonfferoni correction was P < 0.00017. These SNPs included rs9939609 (Frayling et al. 2007) and rs1121980 (Hinney et al. 2007) that were reported to be significantly associated with the obesity phenotype in the Caucasian population, as determined by genome-wide association studies; rs9930506 (Scuteri et al. 2007) showed marginal association with obesity in the Japanese. Linkage disequilibrium (LD) analysis revealed that these 15 SNPs were in almost complete LD (D' > 0.98, r> 0.80) and were located within the same LD block of approximately 50 kb (Fig. 1). The most significant association was observed for rs1558902 [additive mode, P = 0.0000041 and allele-specific OR (95% CI) adjusted for age and gender was 1.41 (1.22–1.62)]. The minor alleles of rs9939609 (MAF = 0.24) and rs1121980 (MAF = 0.26) were significantly more frequent in the obese group than in the normal-weight control group (additive mode, P = 0.000012 and P = 0.000051, respectively), and ORs were 1.38 (95% CI = 1.20–1.59) and 1.33 (95% CI = 1.16–1.52), respectively (Table 2, Supplementary Table 1). The MAF of both SNPs in the control group was 0.18; this was consistent with data obtained from the haplotype map of the human genome (HapMap) (Supplementary Table 1). Our data indicated that the SNPs in the FTO gene were associated with severe obesity in the Japanese.

Fig. 1
Linkage disequilibrium (LD) mapping, polymorphisms, and P values obtained in the test of independence between the phenotype and genotypes of obesity at various single nucleotide polymorphisms (SNPs) in the fat-mass and obesity-associated gene (FTO) gene. ...
Table 2
Associations of single nucleotide polymorphisms (SNPs) in the fat-mass and obesity-associated gene (FTO) gene with obesity existing in the 50-kb linkage disequilibrium (LD) block

Analysis of various quantitative phenotypes with rs1558902

To investigate whether the genotypes of SNP rs1558902 are associated with the phenotypes of metabolic disorders, we compared the following among the different genotypes in the cases, controls, and combined groups: ANOVA results, BMI, levels of fasting plasma glucose, hemoglobin A1c (HbA1c), total cholesterol, triglycerides, HDL cholesterol, and blood pressure. As rs1558902 showed the most significant association with obesity and its call rate was the highest, we analyzed various quantitative phenotypes by using this SNP. The quantitative phenotypes regarding BMI and the levels of fasting plasma glucose, HbA1c, total cholesterol, triglycerides, HDL cholesterol, and blood pressure were not found to be significantly associated with the genotypes at rs1558902 in either the case or control group (Table 3). Although there was no significant difference in BMI values among genotypes in either the control or case group, the direction of the difference (AA > AT > TT) was in accordance with the association between the qualitative obesity phenotype and the genotype shown.

Table 3
Comparison of various quantitative phenotypes among different genotypes at single nucleotide polymorphism (SNP) rs1558902 in obese and control subjects

Finally, we examined the BMI distribution of rs1558902 in the Japanese general population and found that rs1558902 genotype was significantly associated with BMI (Table 4). This result would confirm the association of rs1558902 with obesity.

Table 4
Association of body mass index (BMI) with rs1558902 genotypes in the Japanese general population

Discussion

Recent genome-wide association studies have shown that the FTO gene is associated with obesity (Frayling et al. 2007; Scuteri et al. 2007; Hinney et al. 2007). The associations between variations in the FTO gene and the obesity phenotype have been observed in many Caucasian subjects (Frayling et al. 2007; Scuteri et al. 2007; Dina et al. 2007; Field et al. 2007; Andreasen et al. 2008; Wåhlén et al. 2008; Peeters et al. 2008). However, these associations were controversial with regard to Asian subjects (Horikoshi et al. 2007; Li et al. 2008; Omori et al. 2008). BMI values did not significantly differ among the genotypes in the general population of Chinese and Japanese (Horikoshi et al. 2007; Li et al. 2008). We performed a case-control association study with regard to severe obesity and found that the SNPs in the FTO gene were significantly associated with severe obesity. Although the SNPs demonstrated the most significant association in the Japanese, which was different from that in Caucasians, the significantly associated SNPs existed in a similar block as that in Caucasians. Therefore, the FTO gene could also contribute to the development of severe obesity in the Japanese.

BMI was modestly different among rs1558902 genotypes in the general population in this study; rs9939609 was not significantly associated with BMI in the general population (AA 23.22 ± 3.14 vs AT 22.79 ± 3.25 vs TT 22.58 ± 3.13, P = 0.063). In the Japanese population, rs1558902 may be more tightly associated with BMI than rs9939609. The National Nutrition Survey of Japan reported that the prevalence of subjects with a BMI of ≥30 kg/m2 is only 2.3% in men and 3.4% in women aged 20 years and older (Yoshiike et al. 2002), and the mean BMI was approximately 23 kg/m2 for ages 15–84 years (Yoshiike et al. 1998). Inconsistency in the results of effects of variations in the FTO gene on BMI between Japanese and Europians may be due to the relatively small mean and variance of BMI in the former than the latter.

The significant SNPs were located in intron 1 of the FTO gene. The rs1558902 and other significant SNPs, for example, rs9939609 and rs1121980, would affect transcriptional activity of the FTO gene, although further investigation is necessary. The precise mechanism by which the FTO gene leads to obesity development is unclear (Gerken et al. 2007; Sanchez-Pulido et al. 2007). However, the FTO gene is expressed in the hypothalamus and regulated by fasting and leptin (Frayling et al. 2007; Gerken et al. 2007). Using large-scale case-control association studies, we determined that the SCG3 (Tanabe et al. 2007) and MTMR9 (Yanagiya et al. 2007) genes are involved in susceptibility to the obesity phenotype. These two genes are expressed in the hypothalamus. Genetic studies in mice have suggested that mutations in several genes, such as those encoding leptin, proopiomelanocortin, and melanocortin-4 receptor, are implicated in a monogenic form of inherited obesity (Barsh et al. 2000; Rankinen et al. 2006). Such mutations have also been reported in obese humans. As most such genes are expressed in the hypothalamus and have been indicated to play important roles in the regulation of food intake, genes expressed in the hypothalamus are likely to be good candidates for susceptibility to obesity.

In summary, we have identified the genetic variations in the FTO gene that may influence the risk of severe obesity in the Japanese.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Acknowledgments

We thank Dr. Chisa Nakagawa (Otemae Hospital), Dr. Hideki Asakawa (Itami City Hospital), Ms. Yuko Ohta, Mr. Fumitaka Sakurai, Mr. Michihiro Nakamura, and Ms. Chiaki Ohkura for their contribution to our study. This work was supported by a grant from the Japanese Millennium Project and Takeda Science Foundation (KH).

Footnotes

Electronic supplementary material

The online version of this article (doi:10.1007/s10038-008-0283-1) contains supplementary material, which is available to authorized users.

References


  • Andreasen CH, Stender-Petersen KL, Mogensen MS, Torekov SS, Wegner L, Andersen G, Nielsen AL, Albrechtsen A, Borch-Johnsen K, Rasmussen SS, Clausen JO, Sandbaek A, Lauritzen T, Hansen L, Jørgensen T, Pedersen O, Hansen T (2008) Low physical activity accentuates the effect of the FTO rs9939609 polymorphism on body fat accumulation. Diabetes 57:95–101 [PubMed]

  • Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263–265 [PubMed]

  • Barsh GS, Farooqi IS, O’Rahilly S (2000) Genetics of body-weight regulation. Nature 404:644–651 [PubMed]

  • Dina C, Meyre D, Gallina S, Durand E, Körner 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, Stunff CL, Bougnères P, Kovacs P, Marre M, Balkau B, Cauchi S, Chèvre JC, Froguel P (2007) Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet 39:724–726 [PubMed]

  • Field SF, Howson JM, Walker NM, Dunger DB, Todd JA (2007) Analysis of the obesity gene FTO in 14,803 type 1 diabetes cases and controls. Diabetologia 50:2218–2220 [PMC free article] [PubMed]
  • Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, Perry JRB, Elliott KS, Lango H, Rayner NW, Shields B, Harries LW, Barrett JC, Ellard S, Groves CJ, Knight B, Patch AM, Ness AR, Ebrahim S, Lawlor DA, Ring SM, Ben-Shlomo Y, Jarvelin MR, Sovio U, Bennett AJ, Melzer D, Ferrucci L, Loos RJF, Barroso I, Wareham NJ, Karpe F, Owen KR, Cardon LR, Walker M, Hitman GA, Palmer CNA, Doney ASF, Morris AD, Smith GD, The Welcome Trust Case Control Consortium, Hattersley AT, McCarthy MI (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 [PMC free article] [PubMed]

  • Gerken T, Girard CA, Tung YC, Webby CJ, Saudek V, Hewitson KS, Yeo GSH, McDonough MA, Cunliffe S, McNeill LA, Galvanovskis J, Rorsman P, Robins P, Prieur X, Coll AP, Ma M, Jovanovic Z, Farooqi IS, Sedgwick B, Barroso I, Lindahl T, Ponting CP, Ashcroft FM, O’Rahilly S, Schofield CJ (2007) The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science 318:1469–1472 [PMC free article] [PubMed]

  • Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, Wichmann HE, 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 312:279–283 [PubMed]

  • Hinney A, Nguyen TT, Scherag A, Friedel S, Brönner G, Müller TD, Grallert H, Illig T, Wichmann HE, Rief W, Schäfer H, Hebebrand J (2007) Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants. PLoS ONE 2:e1361–e1365 [PMC free article] [PubMed]

  • Horikoshi M, Hara K, Ito C, Shojima N, Nagai R, Ueki K, Froguel P, Kadowaki T (2007) Variations in the HHEX gene are associated with increased risk of type 2 diabetes in the Japanese population. Diabetologia 50:2461–2466 [PubMed]

  • Kopelman PG (2000) Obesity as a medical problem. Nature 404:635–643 [PubMed]

  • Li H, Wu Y, Loos RJ, Hu FB, Liu Y, Wang J, Yu Z, Lin X (2008) Variants in the fat mass- and obesity-associated (FTO) gene are not associated with obesity in a Chinese Han population. Diabetes 57:264–268 [PubMed]

  • Maes HHM, Neale MC, Eaves LJ (1997) Genetic and environmental factors in relative body weight and human adiposity. Behav Genet 27:325–351 [PubMed]

  • Ohnishi Y, Tanaka T, Ozaki K, Yamada R, Suzuki H, Nakamura Y (2001) A high-throughput SNP typing system for genome-wide association studies. J Hum Genet 46:471–477 [PubMed]

  • Omori S, Tanaka Y, Takahashi A, Hirose H, Kashiwagi A, Kaku K, Kawamori R, Nakamura Y, Maeda S (2008) Association of CDKAL1, IGF2BP2, CDKN2A/B, HHEX, SLC30A8 and KCNJ11 with susceptibility to type 2 diabetes in a Japanese population. Diabetes 57:791–795 [PubMed]

  • Rankinen T, Zuberi A, Chagnon YC, Weisnagel SJ, Argyropoulos G, Walts B, Pérusse L, Bouchard C (2006) The human obesity gene map: the 2005 update. Obesity 14:529–644 [PubMed]

  • Nielsen DM, Ehm MG, Weir BS (1998) Detecting marker-disease association by testing for Hardy–Weinberg disequilibrium at a marker locus. Am J Hum Genet 63:1531–1540 [PMC free article] [PubMed]
  • Peeters A, Beckers S, Verrijken A, Roevens P, Peeters P, Van Gaal L, Van Hul W (2008) Variants in the FTO gene are associated with common obesity in the Belgian population. Mol Genet Metab (in press) [PubMed]

  • Sanchez-Pulido L, Andrade-Navarro MA (2007) The FTO (fat mass and obesity associated) gene codes for a novel member of the non-heme dioxygenase superfamily. BMC Biochem 8:23–28 [PMC free article] [PubMed]

  • Scuteri A, Sanna S, Chen WM, Uda M, Albai G, Strait J, Najjar S, Nagaraja R, Orrú M, Usala G, Dei M, Lai S, Maschio A, Busonero F, Mulas A, Ehret GB, Fink AA, Weder AB, Cooper RS, Galan P, Chakravarti A, Schlessinger D, Cao A, Lakatta E, Abecasis GR (2007) Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet 3:1200–1210 [PMC free article] [PubMed]

  • Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, Boutin P, Vincent D, Belisle A, Hadjadj S, Balkau B, Heude B, Charpentier G, Hudson TJ, Montpetit A, Pshezhetsky AV, Prentki M, Posner BI, Balding DJ, Meyre D, Polychronakos C, Froguel P (2007) A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445:881–885 [PubMed]

  • Takei T, Iida A, Nitta K, Tanaka T, Ohnishi Y, Yamada R, Maeda S, Tsunoda T, Takeoka S, Ito K, Honda K, Uchida K, Tsuchiya K, Suzuki Y, Fujioka T, Ujiie T, Nagane Y, Miyano S, Narita I, Gejyo F, Nihei H, Nakamaura Y (2002) Association between single-nucleotide polymorphisms in selectin genes and immunoglobulin A nephropathy. Am J Hum Genet 70:781–786 [PMC free article] [PubMed]

  • Tanabe A, Yanagiya T, Iida A, Saito S, Sekine A, Takahashi A, Nakamura T, Tsunoda T, Kamohara S, Nakata Y, Kotani K, Komatsu R, Itoh N, Mineo I, Wada J, Funahashi T, Miyazaki S, Tokunaga K, Hamaguchi K, Shimada T, Tanaka K, Yamada K, Hanafusa T, Oikawa S, Yoshimatsu H, Sakata T, Matsuzawa Y, Kamatani N, Nakamura Y, Hotta K (2007) Functional single-nucleotide polymorphisms in the secretogranin III (SCG3) gene that form secretory granules with appetite-related neuropeptides are associated with obesity. J Clin Endocrinol Metab 92:1145–1154 [PubMed]

  • The Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447:661–683 [PMC free article] [PubMed]

  • Wåhlén K, Sjölin E, Hoffstedt J (2008) The common rs9939609 gene variant of the fat mass and obesity associated gene (FTO) is related to fat cell lipolysis. J Lipid Res 49:607–611 [PubMed]

  • Wilson PWF, Grundy SM (2003) The metabolic syndrome: practical guide to origins and treatment: Part I. Circulation 108:1422–1425 [PubMed]

  • 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 16:3017–3026 [PubMed]

  • Yoshiike N, Matsumura Y, Zaman MM, Yamaguchi M (1998) Descriptive epidemiology of body mass index in the Japanese adults in a representative sample from the National Nutrition Survey 1990–1994. Int J Obes 22:684–687 [PubMed]

  • Yoshiike N, Kaneda F, Takimoto H (2002) Epidemiology of obesity and public health strategies for its control in Japan. Asia Pac J Clin Nutr 11:S727–S731 [PubMed]

Articles from Springer Open Choice are provided here courtesy of Springer
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...