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The Effects of Genetic Variation in FTO rs9939609 on Obesity and Dietary Preferences in Chinese Han Children and Adolescents

  • Min Yang,

    Affiliation Department of Nutrition, Zhejiang University School of Public Health, Hangzhou, China

  • Yuyang Xu,

    Affiliations Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, China, Hangzhou Center for Disease Control and Prevention, Hangzhou, China

  • Li Liang,

    Affiliation Department of Pediatrics, the First Affiliated Hospital of College of Medicine, Zhejiang University, Hangzhou, China

  • Junfen Fu,

    Affiliation Department of Endocrinology, Children's Hospital of College of Medicine, Zhejiang University, Hangzhou, China

  • Feng Xiong,

    Affiliation Department of Endocrinology, Children's Hospital Affiliated to Chongqing Medical University, Chongqing, China

  • Geli Liu,

    Affiliation Department of Pediatrics, General Hospital of Tianjin Medical University, Tianjin, China

  • Chunxiu Gong,

    Affiliation Beijing Children's Hospital Affiliated to Capital Medical University, Beijing, China

  • Feihong Luo,

    Affiliation Department of Pediatric Endocrinology and Inborn Metabolic Diseases, Children's Hospital of Fudan University, Shanghai, China

  • Shaoke Chen,

    Affiliation Department of Pediatrics Endocrinology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China

  • Chunxiao Xu,

    Affiliation Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, China

  • Dandan Zhang,

    Affiliation Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, China

  • Zhengli Li,

    Affiliation Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, China

  • Shuai Zhang,

    Affiliation Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, China

  • Yan Zhang,

    Affiliation Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, China

  • Hao Wang,

    Affiliation Department of Pediatrics Endocrinology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China

  •  [ ... ],
  • Yimin Zhu

    zhuym@zju.edu.cn

    Affiliations Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, China, Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China

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  • [ view less ]

The Effects of Genetic Variation in FTO rs9939609 on Obesity and Dietary Preferences in Chinese Han Children and Adolescents

  • Min Yang, 
  • Yuyang Xu, 
  • Li Liang, 
  • Junfen Fu, 
  • Feng Xiong, 
  • Geli Liu, 
  • Chunxiu Gong, 
  • Feihong Luo, 
  • Shaoke Chen, 
  • Chunxiao Xu
PLOS
x

Abstract

The association of the rs9939609 single nucleotide polymorphism in FTO gene with obesity has been extensively investigated in studies of populations of European, African, and Asian ancestry. However, inconsistent results have been reported in Asian populations, and the relationship of FTO variation and dietary behaviors has only rarely been examined in Chinese children and adolescents. The aim of this study was to assess the association of rs9939609 with obesity and dietary preferences in childhood in a Chinese population. Epidemiological data including dietary preferences were collected in interviews using survey questionnaires, and rs9939609 genotype was determined by real-time PCR. The associations of rs9939609 genotypes with obesity and dietary preferences were analyzed by multivariate logistic regression using both additive and dominant models. The results showed that subjects with a TA or AA genotype had an increased risk of obesity compared with the TT participants; the odds ratios (ORs) were 1.47 (95% CI: 1.25–1.71, P = 1.73×10−6), and 3.32 (95% CI: 2.01–5.47, P = 2.68×10−6), respectively. After adjusting for age and gender, body mass index, waist circumference, hip circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose, triglycerides, and low-density lipoprotein cholesterol were higher, and high-density lipoprotein cholesterol was lower in TA and AA participants than in those with the TT genotype. After additionally controlling for body mass index, the association remained significant only for systolic blood pressure (P = 0.005). Compared with TT participants, those with the AA genotype were more likely to prefer a meat-based diet (OR = 2.81, 95% CI: 1.52–5.21). The combined OR for obesity in participants with TA/AA genotypes and preference for a meat-based diet was 4.04 (95% CI: 2.8–5.81) compared with the TT participants who preferred a plant-based diet. These findings indicate the genetic variation of rs9939609 is associated with obesity and dietary preferences in Chinese children and adolescents.

Introduction

Childhood and adolescent obesity is increasing rapidly in both developed and developing countries [1][3]. Over the past 25 years, obesity rates have increased approximately twofold in the US, threefold over 10 years in England, and 3.9-fold over 18 years in Egypt [4]. In China, the prevalence of overweight and obese children and adolescents increased from 5.2% in 1991 to 13.2% in 2006 [5]. Current estimates of obesity rates are higher in developed countries than in developing countries. However, the numbers of obese individuals are much larger in the developing countries [6], [7]. Childhood obesity poses a serious challenge to society because it is associated with the risk of adult obesity and developing obesity-related chronic diseases such as type 2 diabetes mellitus and cardiovascular disease [2], [7], [8]. Thus, more attention should be paid to preventing childhood obesity, especially in developing countries such as China.

Individual susceptibility to obesity is determined by interactions between genetic and environmental factors [9], [10]. The fat mass and obesity associated (FTO) gene was the first obesity-related gene discovered by large-scale genome-wide association studies (GWAS), although its functional implications still need further validation [11][15]. Since the FTO gene was first identified in 2007, many subsequent studies have also demonstrated an association of FTO genetic variants with obesity and body mass index (BMI) in various ethnic populations in both children and adults [16][22]. The FTO rs9939609 single nucleotide polymorphism (SNP) variant is of particular interest because it has the strongest known effect on increased BMI [12], and its association with BMI and obesity-related phenotypes has been confirmed by independent studies in large Caucasian populations [16], [17].

However, studies of this association in Asian populations or child populations have yielded inconsistent results. Cha et al. reported a significant association of FTO genetic variants with BMI in a Korean population in 2008 [23]. Subsequently, a growing number of studies, including a few literature-based meta-analyses, have provided more evidence that the rs9939609 variant may be associated with BMI in east and south Asians, including Chinese, Japanese, Vietnamese, Malaysian, and Indians [9], [22][35]. However, the first study performed in Mainland China, in a population of 3,210 Chinese Han adults 50 to 70 years of age, found no association of FTO variants (rs9939609, rs8050136, and rs9930506) with BMI, waist circumference (WC), or other obesity-related traits [36]. Similarly, Horikoshi et al. found no association of FTO variants with BMI in a Japanese population [37]. Available, but limited evidence suggests that the association between rs9939609 and BMI in children changes with age [38][40]. A recent study conducted in a large sample of preschool children in Europe found no relationship between rs9939609 and BMI [41]. In another large meta-analysis, carriers of the FTO rs9939609 A allele were found to have a lower body weight before the age of 2.5 than carriers of the common allele [42]. Few studies have been conducted to examine the relationship of FTO variants with obesity in Asian children and adolescents, particularly in large childhood populations [18], [43], [44].

Evidence to date suggests that the association between rs9939609 variations and BMI may be predominantly driven by increased energy intake, particularly fat consumption and impaired satiety [45][49]. However, the relationships of rs9939609 with dietary intake and obesity found in recent studies have been inconsistent [46][53]. A population-based survey carried out in school-age children residing in Beijing showed that protein-rich foods, vegetables, and fruits may modify the effects of FTO rs9939609 variant on the risk of childhood obesity [54]. In addition, a recent study conducted in a selected cohort of obese children from a genetic isolate population in Sardinia found that the rs9939609 variant was associated with BMI but did not influence eating behavior, neither in the entire cohort nor when participants were stratified by age [55]. The findings from another study using a multi-ethnic population in Canada indicated that the rs9939609 variant was associated with intake of dietary macronutrients for Canadian aboriginals and Europeans only, but not in ethnic Chinese [56]. Traditional dietary patterns and preferences in China, especially among children and adolescents, are currently undergoing substantial changes. Therefore, further studies are needed to evaluate the interactions between rs9939609 variants and dietary preferences that influence obesity in China, especially in populations of children and adolescents.

The purpose of the present study was to examine the association of the FTO rs9939609 polymorphism with the risk of obesity and obesity-related traits in children and adolescents from different areas of China. The study also examined the relationship between rs9939609 and dietary preferences.

Materials and Methods

Subjects

A cross-sectional study on metabolic syndrome with cluster sampling was conducted in six cities in China (Beijing, Tianjin, Chongqing, Hangzhou, Shanghai and Nanning) in 2010. All students from 7 to 18 years of age in twelve selected schools were eligible to participate in this survey. Students with chronic heart, lung, liver and renal diseases, cancer, and other serious illnesses were excluded. After excluding survey questionnaires with incomplete or suspected incorrect answers, a final evaluable sample of 16,580 participants (8,477 boys and 8,103 girls) was obtained.

A total of 1400 obese students (950 boys and 450 girls) and 2600 non-obese control students (1700 boys and 900 girls) were randomly selected from the survey population. Obesity was defined as a BMI above the 95th percentile of the Chinese BMI reference data for Han children and adolescents in specific age- and gender- groups [57]. The control students had BMIs between the 15th and 85th percentile and were matched by age, gender and residence area to the obese students. Individuals with missing genotype data were excluded, leaving 1348 obese and 2576 control students who were enrolled in this study. The study protocols were approved by the research ethics committees of Zhejiang University and all collaborating hospitals. All the participants and their guardians provided written informed consent. A study flowchart, including information on missing data, is provided in Figure 1. The BMI thresholds of the 15th, 85th, 95th percentiles for Chinese Han children and adolescents in specific age- and gender- groups are shown in Table S1.

Anthropometric measurements and epidemiologic investigation

Anthropometric measurements, including height, weight, waist circumference (WC) and hip circumference (HC), systolic blood pressure (SBP) and diastolic blood pressure (DBP), were measured by trained physicians or investigators, following a standard protocol. Height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg) were measured with the participants wearing light clothing and without shoes. BMI was calculated as body weight in kilograms divided by the square of height in meters (kg/m2). WC (to the nearest 0.1 cm) was measured at the midpoint between the iliac crest and the lower costal margin while standing and at the end of an exhalation. HC (to the nearest 0.1 cm) was measured while standing at the maximum circumference around the buttocks. After at least a 5-minute rest period, blood pressure was measured in a sitting position with a mercury sphygmomanometer. The SBP and DBP were reported as the average of three repeat measurements with 30-second rest intervals between measurements.

After a 12-hour overnight fast, blood samples were drawn to determine the serum levels of total cholesterol (TC), total triglyceride (TG), low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC) and fasting blood glucose (FG) with a biochemical autoanalyzer (Hitachi 7060, Tokyo, Japan).

Demographic characteristics, health status, dietary preferences, physical activity, medical history and family history of obesity were collected using a standardized questionnaire during a face-to-face interview by a trained investigator. The dietary data included participants' preference for type of diet (meat-based, plant-based or balanced diet), preference for salty flavor (like, dislike or no strong preference), and preference for sweet flavor (like, dislike or no strong preference). The questionnaire was administered to 58 randomly selected participants from Hangzhou prior to the formal interview. Test-retest reliability was assessed by re-administering the questionnaire 4 weeks later, and validity was assessed by comparing 3-day food records. The reliability (Cronbach's α) and content validity of the questionnaire were 0.86 and 0.88, respectively.

Genotyping

Genomic DNA was extracted from peripheral blood, using the TOYOBO MagExtractor Genomic DNA Purification Kit (Toyobo, Osaka, Japan) following the protocol recommended by the vendor. The rs9939609 polymorphisms were genotyped using a TaqMan-based SNP allelic genotyping assay (Applied Biosystems, Foster City, USA). One-hundred-and-fifty replicate quality control samples were included in the genotyping plates with more than 99% concordance (149/150).

Statistical analysis

Summary statistics were performed to describe the characteristics of study participants, which were stratified by case/control status. The quantitative data were expressed as means ± standard deviations (SD) for approximately normal distributions, as medians (inter-quartile range) for non-normally distributed variables, and as frequencies (percentages) for categorical variables. Non-normally distributed variables were square-root transformed before analysis. The information on dietary preferences was analyzed as dichotomies of diet preference (+, meat-based diet; −, plant-based or balanced diet), salty flavor (+, like; −, dislike/no strong preference), and sweet flavor (+, like; −, dislike/no strong preference). Participants with missing genotype data were excluded from the analysis.

The Hardy–Weinberg equilibrium of rs9939609 was examined in control students with Pearson's chi-squared test. The t-test was used to compare the mean differences between obese and control students for normally distributed variables, and the Kruskal–Wallis test was used for non-normally distributed variables. The chi-square test was used to compare the frequency of differences in categorical variables. Associations of rs9939609 with obesity and dietary preferences were analyzed with multivariate logistic regression using both additive (TT/TA/AA) and dominant (TT/TA+AA) models. The interaction effects for obesity between rs9939609 and dietary preferences were calculated with a logistic regression model adding an additional interaction term. Comparisons of obesity-associated traits were carried out using multivariate linear regression that included covariates such as age, gender and BMI. All the analyses were performed using SPSS for Windows, version 16.0. A P-value <0.05 was considered to be statistically significant.

Results

Subject characteristics

The demographic and biochemical data for the total of 3924 evaluated participants (excluding 76 with missing genotype data) are shown in Table 1. The mean age ± SD was 11.0±2.6 years in the obese group and 11.6±2.4 years in the control group (P<0.0001). The percentage of males was 68.8% in the case group and 66.0% in the control group (P = 0.07). The obese participants had significantly higher levels of BMI, WC, HC, SBP, DBP, FG, TG, TC and LDLC, but a significantly lower level of HDLC than the controls (all P<0.0001).

FTO rs9939609 and obesity

The frequency of variant allele (A) was 11.1% in the control group and 16.3% in the obese group. This polymorphism was in Hardy–Weinberg equilibrium in the control group (P>0.05). Table 2 shows the association between rs9939609 polymorphism and obesity in the study subjects. The A allele of rs9939609 was significantly associated with an increased risk for obesity with an OR of 1.56 (95% CI: 1.36–1.78, P = 2.24×10−10), which means each additional copy of the A allele represented a 1.56-fold increase in the risk of obesity. Compared with the homozygous wild-type (TT) participants, heterozygous (TA) participants had a greater risk of obesity, with an OR of 1.47 (95% CI: 1.25–1.71, P = 1.73×10−6), and those who were homozygous for the variant allele (AA) had an OR of 3.32 (95% CI: 2.01–5.47, P = 2.68×10−6). Under the dominant model, the participants with the A allele had increased risk of obesity, with an OR of 1.56 (95% CI: 1.34–1.81, P = 1.19×10−8).

FTO rs9939609 and obesity-related metabolic traits

Linear regression models were used to estimate the associations between FTO rs9939609 and obesity-related metabolic traits in the additive model (Table 3). After adjusting for age and gender, BMI (P = 9.53×10−11), WC (P = 4.22×10−10), HC (P = 5.49×10−7), SBP (P = 2.12×10−7), DBP (P = 0.008), TG (P = 0.045), LDLC (P = 0.027), and FG (P = 0.012) were higher, and HDLC (P = 0.001) was lower, in the participants with TA or AA than in participants with the TT genotype. After further adjustment for BMI, the only association that remained significant was with SBP (P = 0.005).

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Table 3. Association of the FTO rs9939609 genotypes with clinical and metabolic measurements.

https://doi.org/10.1371/journal.pone.0104574.t003

FTO rs9939609 and dietary preferences

The dietary preferences in different genotypes of rs9939609 are described in Table 4. 36.2% of the participants with the AA genotype preferred a meat-based diet, which was higher than participants with TA (15.4%) and TT (14.5%) genotypes. After adjusting for age, gender, and BMI in the logistic regression model, more AA than TT participants preferred a meat-based diet (OR = 2.81, 95% CI: 1.52–5.21; P = 0.001). No significant associations were found for preference of sweet or salty foods (all P>0.05).

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Table 4. Associations of the FTO rs9939609 genotypes with dietary preferences.

https://doi.org/10.1371/journal.pone.0104574.t004

FTO rs9939609, dietary preferences and obesity

No multiplicative interactions (all P>0.05) between FTO rs9939609 and dietary preferences on obesity were found, as described in Table 5. Compared with TT participants who did not prefer a meat-based diet, the OR for obesity in the participants with TA/AA genotypes and preferred a meat-based diet was 4.04 (95% CI: 2.80–5.81, P = 4.88×10−14). Similar results were observed for the effects of the rs9939609 TA and AA genotypes combined with salty flavor preference (OR = 3.31, 95% CI: 2.26–4.84, P = 1.33×10−10) and sweet flavor preference (OR = 1.42, 95% CI: 1.10–1.83, P = 0.006).

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Table 5. Joint effects between the FTO rs9939609 genotypes, obesity, and dietary preferences.

https://doi.org/10.1371/journal.pone.0104574.t005

Discussion

In the present study, FTO rs9939609 was found to be significantly associated with the risk of obesity and also with dietary preferences independently of BMI. In addition, rs9939609 was associated with multiple cardiovascular and metabolic risk factors, however after additional adjustment for BMI, only SBP still demonstrated a statistically significant association. This study confirms the association of FTO rs9939609 with obesity and dietary preferences in Chinese Han children and adolescents.

Childhood and adolescent obesity has become a serious public health problem. It predisposes individuals to a higher incidence of diseases related to cardiovascular, endocrine, respiratory, and immune function, and greatly increases the risk of chronic diseases in adulthood. Although the pathogenesis of obesity and its associated co-morbidities are multifactorial, increasing evidence has implied that the FTO gene, and in particular SNP rs9939609, play an important role in the occurrence and development of obesity in different ethnic populations in both children and adults [11], [12]. The association of the FTO rs9939609 variant with both increased BMI and obesity-related phenotypes has been examined by independent studies of large Caucasian populations. However, the data are less conclusive in non-Caucasian and childhood-age populations. A study by Li et al. found no significant association between rs9939609 and obesity in a Chinese Han population [36], but those findings were inconsistent with the results of a subsequent study performed in a Taiwanese population [58]. Hallman et al. found that the A/A genotype of rs9939609 was associated with higher BMI in non-Hispanic whites at all ages, but there were no significant associations in African Americans [19]. A study of 670 Chinese children and adolescents indicated that FTO rs9939609 was strongly associated with BMI and obesity-related metabolic traits [18]. However, a study of a relatively large sample size (n = 1718) of European preschool children (3–4 years of age) found no significant association [41]. These inconsistent results might be explained by ethnic differences in the allele frequencies of FTO, differences in population samples and age, and differences in the underlying distributions of key environmental exposures. Therefore, the current study was designed to examine the associations of FTO rs9939609 with the risk of obesity and obesity-related metabolic traits in 3924 Chinese Han children and adolescents (7–18 years of age) living in the northern, central and southern regions of China. In addition, the influence of rs9939609 on dietary preferences (preference for a meat-based diet, salty tastes, and sweet tastes) was evaluated to try to account for any observed physical and metabolic associations.

In the present study, the minor allele frequency (MAF) of rs9939609 in control participants was 11.1%, which is in line with that reported for Chinese populations in previous studies [18], [36], [58]. However, the risk allele A (mutant allele) of rs9939609 is more common in populations of European origin (MAF 0.45–0.48), which means 69.8% of the populations carry at least one risk allele and 20.3% carry two risk alleles. In this study, results showed that rs9939609 was associated with the risk of childhood obesity and were consistent with the results of two previously published independent studies conducted in Beijing, as mentioned above [18], [59]. However, the association was not statistically significant in a study that had been conducted in Chinese adults [36]. This inconsistency may be explained by the difference in age range of participants. A study by Loos et al. in a European population showed that the association between the FTO gene, obesity and BMI was more significant in children than in adults [60]. Qi et al. found that the strength of association between rs9939609 and BMI decreased with age in American male doctors [61]. The researchers speculated that environment-related influences accumulated with age and that this phenomenon may partly explain the reduction in association at an older age. Hence, more studies are needed to validate the age-related differences observed in the association between rs9939609 and obesity, and to clarify the underlying mechanism.

The results of the current study also revealed significant association of rs9939609 with several metabolic risk factors, such as WC, HC, SBP, DBP, FG and HDLC, but not with TG, TC or LDLC, when adjusted for age and gender. However, after adding BMI in the model above, only SBP retained its significant association. These findings imply that the associations of the rs9939609 variation with the above obesity-related traits may be mediated through BMI. Similar results have been reported in Chinese and Japanese populations. However, the results were inconsistent in Europeans [18], [43], [58]. Nevertheless, our study found that rs9939609 was independently associated with SBP, and this finding was consistent with some recent studies [62], [63]. The variant allele (A) of rs9939609 might be an independent risk factor for increasing blood pressure/hypertension, the mechanism remains unknown. Further functional studies are required to clarify this association.

Increasing energy intake is a major contributor to the current obesity epidemic [46]. Evidence to date suggests that the association between rs9939609 and BMI may be predominantly driven by increased energy intake [53]. Cecil et al. reported that the A allele at rs9939609 predisposed to obesity but did not appear to be involved in the regulation of energy expenditure; instead, this allele may have a role in the control of food intake and food choice in European children, suggesting a link to a hyperphagic phenotype or a preference for energy-dense foods [46]. A study in Scottish children found that the rs9939609 obesity risk A allele was significantly associated with increased energy intake independent of body weight [50]. Timpson et al. also found that carriers of the minor variants of rs9939609 consumed more fat and total energy than those non-carriers [47]. Recently, further evidence has suggested that FTO interacts with energy intake patterns in children, as related to obesity risk [64][68]. The findings of this study showed that the genetic variation of rs9939609 was associated with a meat-based dietary preference, and children with the A allele were predisposed to prefer a meat-based diet, which is characterized by higher energy density, higher fat, and lower dietary fiber than either plant-based or balanced diets. Previous studies also found that FTO affected fat cell lipolysis [69], [70]. Therefore, FTO might be involved in the incidence of obesity by both direct and indirect mechanisms.

Although no significant multiplicative interactions were observed between rs9939609 and dietary preferences, their joint effects on obesity were observed in this study. As discussed earlier, the reason a meat-based diet predisposes to obesity may be its high energy density. As for strong tastes, the effect on obesity was consistent with a previous study [71]. However, preference for sweets was not significantly associated with obesity in the current study. On the contrary, another study showed a positive correlation between hedonic response (i.e., foods rich in sugar and fat) and weight gain in Pima Indians [72]. This inconsistency may be caused by the heterogeneity of cohorts and differences in the amounts of sweet foods consumed. These results indicate that dietary preferences play an important role in the development of obesity.

The current study has several strengths. First, the study population was a well-defined, homogenous group of children and adolescents, and standardized methods were used to measure the clinical parameters, such as height and weight. Second, the influence of rs9939609 on dietary preferences (preference for a meat-based diet, salty taste, or sweet taste) was examined to explain how variation of rs9939609 confers a predisposition to obesity. Third, the interaction of rs9939609 with three dietary factors was examined as well as their joint effect on obesity. Several limitations, however, are apparent. First, our findings may provide significant implications for Chinese and related ethnic groups, but they may not apply to other ethnicities. Therefore, further evaluations in other ethnic groups are needed. Second, information about dietary preferences was self-reported. The data would be more reliable if food intake were more accurately measured with diet diary records. However, recording a diet diary is difficult in epidemiological surveys with relatively large samples, such as in this study. Third, we adjusted for key covariates such as age, gender and BMI, but other related covariates (i.e., socioeconomic status, pubertal status, and physical activities) were not considered because of the high proportion of missing data. Fourth, the number of AA/AT individuals who had health-risk-related dietary preferences (i.e., meat-based diet, salty or sweet flavor) was very small because of the low frequency of the variant allele (A) in the Chinese population. Hence, further studies with larger populations are needed.

In brief, this study found that the FTO rs9939609 variation is significantly associated with the risk of obesity and a meat-based dietary preference in Chinese Han children and adolescents. Further studies are needed to understand the functional mechanisms underlying this association.

Supporting Information

Table S1.

BMI thresholds (Kg/m2) of the 15th, 85th, 95th percentile for the Chinese Han children and adolescents in specific age- and gender- groups.

https://doi.org/10.1371/journal.pone.0104574.s001

(DOC)

Author Contributions

Conceived and designed the experiments: YZ. Performed the experiments: LL JF FX GL CG FL SC CX DZ ZL SZ YZ HW. Analyzed the data: MY YX. Wrote the paper: MY. Revised the manuscript: MY YZ.

References

  1. 1. Bradford NF (2009) Overweight and obesity in children and adolescents. Prim Care 36: 319–339.
  2. 2. Lanigan J, Barber S, Singhal A (2010) Prevention of obesity in preschool children. Proc Nutr Soc 69: 204–210.
  3. 3. Kuhne G (2011) [Aspects of prevention of obesity in children and adolescents - a European perspective]. Dtsch Med Wochenschr 136: 1613–1615.
  4. 4. Ebbeling CB, Pawlak DB, Ludwig DS (2002) Childhood obesity: public-health crisis, common sense cure. Lancet 360: 473–482.
  5. 5. Cui Z, Huxley R, Wu Y, Dibley MJ (2010) Temporal trends in overweight and obesity of children and adolescents from nine Provinces in China from 1991-2006. Int J Pediatr Obes 5: 365–374.
  6. 6. Prentice AM (2006) The emerging epidemic of obesity in developing countries. Int J Epidemiol 35: 93–99.
  7. 7. Low LC (2010) Childhood obesity in developing countries. World J Pediatr 6: 197–199.
  8. 8. Flynn MA, McNeil DA, Maloff B, Mutasingwa D, Wu M, et al. (2006) Reducing obesity and related chronic disease risk in children and youth: a synthesis of evidence with ‘best practice’ recommendations. Obes Rev 7 Suppl 1: 7–66.
  9. 9. Hotta K, Nakata Y, Matsuo T, Kamohara S, Kotani K, et al. (2008) Variations in the FTO gene are associated with severe obesity in the Japanese. J Hum Genet 53: 546–553.
  10. 10. Rutters F, Nieuwenhuizen AG, Bouwman F, Mariman E, Westerterp-Plantenga MS (2011) Associations between a single nucleotide polymorphism of the FTO Gene (rs9939609) and obesity-related characteristics over time during puberty in a Dutch children cohort. J Clin Endocrinol Metab 96: E939–942.
  11. 11. Dina C, Meyre D, Gallina S, Durand E, Korner A, et al. (2007) Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet 39: 724–726.
  12. 12. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, 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.
  13. 13. Scuteri A, Sanna S, Chen WM, Uda M, Albai G, et al. (2007) Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet 3: e115.
  14. 14. Tercjak M, Luczynski W, Wawrusiewicz-Kurylonek N, Bossowski A (2010) [The role of FTO gene polymorphism in the pathogenesis of obesity]. Pediatr Endocrinol Diabetes Metab 16: 109–113.
  15. 15. Cheung MK, Yeo GS (2011) FTO Biology and Obesity: Why Do a Billion of Us Weigh 3 kg More? Front Endocrinol (Lausanne) 2: 4.
  16. 16. Jonsson A, Renstrom F, Lyssenko V, Brito EC, Isomaa B, et al. (2009) Assessing the effect of interaction between an FTO variant (rs9939609) and physical activity on obesity in 15,925 Swedish and 2,511 Finnish adults. Diabetologia 52: 1334–1338.
  17. 17. Gonzalez-Sanchez JL, Zabena C, Martinez-Larrad MT, Martinez-Calatrava MJ, Perez-Barba M, et al. (2009) Variant rs9939609 in the FTO gene is associated with obesity in an adult population from Spain. Clin Endocrinol (Oxf) 70: 390–393.
  18. 18. Fang H, Li Y, Du S, Hu X, Zhang Q, et al. (2010) Variant rs9939609 in the FTO gene is associated with body mass index among Chinese children. BMC Med Genet 11: 136.
  19. 19. Hallman DM, Friedel VC, Eissa MA, Boerwinkle E, Huber JC Jr, et al. (2012) The association of variants in the FTO gene with longitudinal body mass index profiles in non-Hispanic white children and adolescents. Int J Obes (Lond) 36: 61–68.
  20. 20. Peters U, North KE, Sethupathy P, Buyske S, Haessler J, et al. (2013) A systematic mapping approach of 16q12.2/FTO and BMI in more than 20,000 African Americans narrows in on the underlying functional variation: results from the Population Architecture using Genomics and Epidemiology (PAGE) study. PLoS Genet 9: e1003171.
  21. 21. Yang J, Loos RJ, Powell JE, Medland SE, Speliotes EK, et al. (2012) FTO genotype is associated with phenotypic variability of body mass index. Nature 490: 267–272.
  22. 22. Li H, Kilpelainen TO, Liu C, Zhu J, Liu Y, et al. (2012) Association of genetic variation in FTO with risk of obesity and type 2 diabetes with data from 96,551 East and South Asians. Diabetologia 55: 981–995.
  23. 23. Cha SW, Choi SM, Kim KS, Park BL, Kim JR, et al. (2008) Replication of genetic effects of FTO polymorphisms on BMI in a Korean population. Obesity (Silver Spring) 16: 2187–2189.
  24. 24. Binh TQ, Phuong PT, Nhung BT, Thoang DD, Lien HT, et al. (2013) Association of the common FTO-rs9939609 polymorphism with type 2 diabetes, independent of obesity-related traits in a Vietnamese population. Gene 513: 31–35.
  25. 25. Vasan SK, Fall T, Neville MJ, Antonisamy B, Fall CH, et al. (2012) Associations of variants in FTO and near MC4R with obesity traits in South Asian Indians. Obesity (Silver Spring) 20: 2268–2277.
  26. 26. Kotani K, Fujiwara S, Tsuzaki K, Sakane N (2012) FTO gene polymorphisms and platelet counts in a general Japanese population. J Investig Med 60: 514–516.
  27. 27. Tan JT, Dorajoo R, Seielstad M, Sim XL, Ong RT, et al. (2008) FTO variants are associated with obesity in the Chinese and Malay populations in Singapore. Diabetes 57: 2851–2857.
  28. 28. Ng MC, Park KS, Oh B, Tam CH, Cho YM, et al. (2008) Implication of genetic variants near TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, and FTO in type 2 diabetes and obesity in 6,719 Asians. Diabetes 57: 2226–2233.
  29. 29. Vasan SK, Karpe F, Gu HF, Brismar K, Fall CH, et al. (2013) FTO genetic variants and risk of obesity and type 2 diabetes: A meta-analysis of 28,394 Indians. Obesity (Silver Spring).
  30. 30. Xi B, Wang C, Wang R, Huang Y (2011) FTO gene polymorphisms are associated with obesity and type 2 diabetes in East Asian populations: an update. Obesity (Silver Spring) 19: 236–237; author reply 238.
  31. 31. Peng S, Zhu Y, Xu F, Ren X, Li X, et al. (2011) FTO gene polymorphisms and obesity risk: a meta-analysis. BMC Med 9: 71.
  32. 32. Liu Y, Liu Z, Song Y, Zhou D, Zhang D, et al. (2010) Meta-analysis added power to identify variants in FTO associated with type 2 diabetes and obesity in the Asian population. Obesity (Silver Spring) 18: 1619–1624.
  33. 33. Xi B, Mi J (2009) FTO polymorphisms are associated with obesity but not with diabetes in East Asian populations: a meta-analysis. Biomed Environ Sci 22: 449–457.
  34. 34. Wang H, Dong S, Xu H, Qian J, Yang J (2012) Genetic variants in FTO associated with metabolic syndrome: a meta- and gene-based analysis. Mol Biol Rep 39: 5691–5698.
  35. 35. Zhou D, Liu H, Zhou M, Wang S, Zhang J, et al. (2012) Common variant (rs9939609) in the FTO gene is associated with metabolic syndrome. Mol Biol Rep 39: 6555–6561.
  36. 36. Li H, Wu Y, Loos RJ, Hu FB, Liu Y, et al. (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.
  37. 37. Horikoshi M, Hara K, Ito C, Shojima N, Nagai R, et al. (2007) Variations in the HHEX gene are associated with increased risk of type 2 diabetes in the Japanese population. Diabetologia 50: 2461–2466.
  38. 38. Hardy R, Wills AK, Wong A, Elks CE, Wareham NJ, et al. (2010) Life course variations in the associations between FTO and MC4R gene variants and body size. Hum Mol Genet 19: 545–552.
  39. 39. Haworth CM, Carnell S, Meaburn EL, Davis OS, Plomin R, et al. (2008) Increasing heritability of BMI and stronger associations with the FTO gene over childhood. Obesity (Silver Spring) 16: 2663–2668.
  40. 40. Jess T, Zimmermann E, Kring SI, Berentzen T, Holst C, et al. (2008) Impact on weight dynamics and general growth of the common FTO rs9939609: a longitudinal Danish cohort study. Int J Obes (Lond) 32: 1388–1394.
  41. 41. Velders FP, De Wit JE, Jansen PW, Jaddoe VW, Hofman A, et al. (2012) FTO at rs9939609, food responsiveness, emotional control and symptoms of ADHD in preschool children. PLoS One 7: e49131.
  42. 42. Sovio U, Mook-Kanamori DO, Warrington NM, Lawrence R, Briollais L, et al. (2011) Association between common variation at the FTO locus and changes in body mass index from infancy to late childhood: the complex nature of genetic association through growth and development. PLoS Genet 7: e1001307.
  43. 43. Okuda M, Hinoda Y, Okayama N, Suehiro Y, Shirabe K, et al. (2011) Association between the FTO gene and overweight in Japanese children and adolescents. Pediatr Diabetes 12: 494–500.
  44. 44. Dwivedi OP, Tabassum R, Chauhan G, Ghosh S, Marwaha RK, et al. (2012) Common variants of FTO are associated with childhood obesity in a cross-sectional study of 3,126 urban Indian children. PLoS One 7: e47772.
  45. 45. Speakman JR (2010) FTO effect on energy demand versus food intake. Nature 464: E1 discussion E2.
  46. 46. Cecil JE, Tavendale R, Watt P, Hetherington MM, Palmer CN (2008) An obesity-associated FTO gene variant and increased energy intake in children. N Engl J Med 359: 2558–2566.
  47. 47. Timpson NJ, Emmett PM, Frayling TM, Rogers I, Hattersley AT, et al. (2008) The fat mass- and obesity-associated locus and dietary intake in children. Am J Clin Nutr 88: 971–978.
  48. 48. den Hoed M, Westerterp-Plantenga MS, Bouwman FG, Mariman EC, Westerterp KR (2009) Postprandial responses in hunger and satiety are associated with the rs9939609 single nucleotide polymorphism in FTO. Am J Clin Nutr 90: 1426–1432.
  49. 49. Wardle J, Llewellyn C, Sanderson S, Plomin R (2009) The FTO gene and measured food intake in children. Int J Obes (Lond) 33: 42–45.
  50. 50. Speakman JR, Rance KA, Johnstone AM (2008) Polymorphisms of the FTO gene are associated with variation in energy intake, but not energy expenditure. Obesity (Silver Spring) 16: 1961–1965.
  51. 51. Tanofsky-Kraff M, Han JC, Anandalingam K, Shomaker LB, Columbo KM, et al. (2009) The FTO gene rs9939609 obesity-risk allele and loss of control over eating. Am J Clin Nutr 90: 1483–1488.
  52. 52. Wardle J, Carnell S, Haworth CM, Farooqi IS, O'Rahilly S, et al. (2008) Obesity associated genetic variation in FTO is associated with diminished satiety. J Clin Endocrinol Metab 93: 3640–3643.
  53. 53. Karra E, O'Daly OG, Choudhury AI, Yousseif A, Millership S, et al. (2013) A link between FTO, ghrelin, and impaired brain food-cue responsivity. J Clin Invest 123: 3539–3551.
  54. 54. Xi B, Zhang MX, Shen Y, Zhao XY, Wang XY, et al. (2010) [Impact on the risk of obesity due to interactions between fat mass- and obesity-associated gene rs9939609 variants and behavioral factors, in the Chinese school-aged children]. Zhonghua Liu Xing Bing Xue Za Zhi 31: 737–741.
  55. 55. Ibba A, Pilia S, Zavattari P, Loche A, Guzzetti C, et al. (2013) The role of FTO genotype on eating behavior in obese Sardinian children and adolescents. J Pediatr Endocrinol Metab 26: 539–544.
  56. 56. Lear SA, Deng WQ, Pare G, Sulistyoningrum DC, Loos RJ, et al. (2011) Associations of the FTO rs9939609 variant with discrete body fat depots and dietary intake in a multi-ethnic cohort. Genet Res (Camb) 93: 419–426.
  57. 57. Group of China Obesity Task F (2004) Body mass index reference norm for screening overweight and obesity in Chinese children and adolescents. Zhonghua Liu Xing Bing Xue Za Zhi 25: 97–102.
  58. 58. Chang YC, Liu PH, Lee WJ, Chang TJ, Jiang YD, et al. (2008) Common variation in the fat mass and obesity-associated (FTO) gene confers risk of obesity and modulates BMI in the Chinese population. Diabetes 57: 2245–2252.
  59. 59. Li M, Liu Y, Xu P, Ye M, Liu Y (2010) [Association of the rs9939609 polymorphism of FTO gene with overweight or obesity in Hazakh children]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 27: 678–681.
  60. 60. Loos RJ, Bouchard C (2008) FTO: the first gene contributing to common forms of human obesity. Obes Rev 9: 246–250.
  61. 61. Qi L, Kang K, Zhang C, van Dam RM, Kraft P, et al. (2008) Fat mass-and obesity-associated (FTO) gene variant is associated with obesity: longitudinal analyses in two cohort studies and functional test. Diabetes 57: 3145–3151.
  62. 62. Xi B, Zhang M, Wang C, Shen Y, Zhao X, et al. (2013) The common SNP (rs9939609) in the FTO gene modifies the association between obesity and high blood pressure in Chinese children. Mol Biol Rep 40: 773–778.
  63. 63. Baik I, Shin C (2012) Interactions between the FTO rs9939609 polymorphism, body mass index, and lifestyle-related factors on metabolic syndrome risk. Nutr Res Pract 6: 78–85.
  64. 64. Johnson L, van Jaarsveld CH, Emmett PM, Rogers IS, Ness AR, et al. (2009) Dietary energy density affects fat mass in early adolescence and is not modified by FTO variants. PLoS One 4: e4594.
  65. 65. Jonsson A, Franks PW (2009) Obesity, FTO gene variant, and energy intake in children. N Engl J Med 360: 1571–1572; author reply 1572.
  66. 66. Sonestedt E, Roos C, Gullberg B, Ericson U, Wirfalt E, et al. (2009) Fat and carbohydrate intake modify the association between genetic variation in the FTO genotype and obesity. Am J Clin Nutr 90: 1418–1425.
  67. 67. Moleres A, Ochoa MC, Rendo-Urteaga T, Martinez-Gonzalez MA, Azcona San Julian MC, et al. (2012) Dietary fatty acid distribution modifies obesity risk linked to the rs9939609 polymorphism of the fat mass and obesity-associated gene in a Spanish case-control study of children. Br J Nutr 107: 533–538.
  68. 68. Steemburgo T, Azevedo MJ, Gross JL, Milagro FI, Campion J, et al. (2013) The rs9939609 polymorphism in the FTO gene is associated with fat and fiber intakes in patients with type 2 diabetes. J Nutrigenet Nutrigenomics 6: 97–106.
  69. 69. Wahlen K, Sjolin 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.
  70. 70. Zabena C, Gonzalez-Sanchez JL, Martinez-Larrad MT, Torres-Garcia A, Alvarez-Fernandez-Represa J, et al. (2009) The FTO obesity gene. Genotyping and gene expression analysis in morbidly obese patients. Obes Surg 19: 87–95.
  71. 71. Matsushita Y, Mizoue T, Takahashi Y, Isogawa A, Kato M, et al. (2009) Taste preferences and body weight change in Japanese adults: the JPHC Study. Int J Obes (Lond) 33: 1191–1197.
  72. 72. Salbe AD, DelParigi A, Pratley RE, Drewnowski A, Tataranni PA (2004) Taste preferences and body weight changes in an obesity-prone population. Am J Clin Nutr 79: 372–378.