Association of genetic variants for susceptibility to obesity with type 2 diabetes in Japanese individuals
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- Takeuchi, F., Yamamoto, K., Katsuya, T. et al. Diabetologia (2011) 54: 1350. doi:10.1007/s00125-011-2086-8
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In populations of East Asian descent, we performed a replication study of loci previously identified in populations of European descent as being associated with obesity measures such as BMI and type 2 diabetes.
We genotyped 14 single nucleotide polymorphisms (SNPs) from 13 candidate loci that had previously been identified by genome-wide association meta-analyses for obesity measures in Europeans. Genotyping was done in 18,264 participants from two general Japanese populations. For SNPs showing an obesity association in Japanese individuals, we further examined diabetes associations in up to 6,781 cases and 7,307 controls from a subset of the original, as well as from additional populations.
Significant obesity associations (p < 0.1 two-tailed, concordant direction with previous reports) were replicated for 11 SNPs from the following ten loci in Japanese participants: SEC16B, TMEM18, GNPDA2, BDNF, MTCH2, BCDIN3D–FAIM2, SH2B1–ATP2A1, FTO, MC4R and KCTD15. The strongest effect was observed at TMEM18 rs4854344 (p = 7.1 × 10−7 for BMI). Among the 11 SNPs showing significant obesity association, six were also associated with diabetes (OR 1.05−1.17; p = 0.04−2.4 × 10−7) after adjustment for BMI in the Japanese. When meta-analysed with data from the previous reports, the BMI-adjusted diabetes association was found to be highly significant for the FTO locus in East Asians (OR 1.13; 95% CI 1.09−1.18; p = 7.8 × 10−10) with substantial inter-ethnic heterogeneity (p = 0.003).
We confirmed that ten candidate loci are associated with obesity measures in the general Japanese populations. Six (of ten) loci exert diabetogenic effects in the Japanese, although relatively modest in size, and independently of increased adiposity.
KeywordsAsiansAssociation studyEthnicityObesityType 2 diabetes
Cardiovascular Genome Epidemiology
Single nucleotide polymorphism
Obesity is a major risk factor for type 2 diabetes, dyslipidaemia, hypertension and cardiovascular disease, and has a strong genetic component . Twin studies have generally found heritability estimates of 0.75 to 0.85 for BMI and approximately 0.70 for weight . Genome-wide association (GWA) studies have provided evidence that several loci are associated with common obesity mostly in populations of European descent [3–15]. The first such loci reported was the fat-mass and obesity-associated gene (FTO) [3, 16, 17]. A common variant in the FTO locus, rs9939609, was originally identified as part of a GWA study for type 2 diabetes ; people with homozygous risk alleles weighed approximately 3 kg more than those without a risk allele. It has been suggested that this variant can predispose individuals to type 2 diabetes and metabolic disorders through its primary effect on BMI in Europeans .
Ethnic differences have been assumed to exist between Europeans and Asians in terms of the components and impacts of genetic factors for obesity, and traits or disorders related to obesity (e.g. type 2 diabetes) [2, 19, 20]. For instance, the relationship between BMI and body fat per cent differs between these populations, with Asians in general having a higher body fat per cent at a lower BMI than Europeans . It has also been estimated that the absolute genetic variances for BMI and weight are greater in Europeans than in East Asians, according to an adolescent twin study . From an epidemiological viewpoint, moreover, it has been hypothesised that the overall impact of obesity on type 2 diabetes is greater in Asians than in Europeans . Accordingly, it is of interest to compare the genetic associations between populations of European descent and Japanese populations.
To date, several studies on non-European populations have replicated the associations for a number of novel obesity loci previously identified by GWA studies in Europeans [13, 22–25]; nevertheless, statistical power has not been sufficient to make strong conclusions. Therefore to test associations between obesity measures (BMI and weight) and type 2 diabetes for 14 single nucleotide polymorphisms (SNPs) from 13 candidate loci recently reported by two GWA meta-analyses [10, 11], we performed a replication study in the general Japanese populations.
Clinical characteristics of study participants for BMI
Both sexes (n)
48.8 ± 12.6
62.6 ± 6.8
23.0 ± 3.2
23.1 ± 3.0
Body weight (kg)
61.8 ± 11.5
58.4 ± 10.2
Alcohol drinking (%)
Chance drinker a
Fasting plasma glucose (mmol/l)
5.22 ± 0.54
5.41 ± 0.84
5.23 ± 0.77
3.21 ± 0.81
1.24 ± 0.97
1.66 ± 1.12
1.63 ± 0.46
1.62 ± 0.44
Blood pressure (mmHg)
Systolic blood pressure
124.3 ± 18.1
138.8 ± 21.2
Diastolic blood pressure
75.9 ± 11.6
83.9 ± 11.7
Prevalence of metabolic diseases (%)d
Height and body weight were measured by trained personnel using standard anthropometric techniques for all participants other than Biobank Japan type 2 diabetes participants, for whom the relevant data were self-reported from questionnaire.
SNP genotyping and quality control
Samples (except for the CAGE–GWAS panel) were genotyped using the TaqMan assay (Applied Biosystems by Life Technologies, Carlsbad, CA, USA) for 14 SNPs from 13 unique obesity loci previously identified in populations of European descent [10, 11]. These SNPs included: rs2815752 (NEGR1), rs10913469 (SEC16B), rs4854344 (TMEM18), rs7647305 (ETV5), rs10938397 (GNPDA2), rs2844479 (NCR3–AIF1), rs6265 (BDNF), rs10838738 (MTCH2), rs7138803 (BCDIN3D–FAIM2), rs4788102 (SH2B1–ATP2A1), rs6499640 (FTO), rs9939609 (FTO), rs12970134 (MC4R) and rs29941 (KCTD15). The genotype distribution of all tested SNPs was in Hardy–Weinberg equilibrium (p > 10−4). We obtained successful genotyping call rates of >99.6% for all SNPs and >99.8% for all included samples (across 14 SNPs).
SNP association analysis
BMI and weight were inverse-normal transformed separately by sex in each panel before association analysis. In addition, in the Fukuoka study panel, we examined the WHR as a variable of fat distribution, which was also inverse-normal transformed. We tested SNPs for the trait association using linear regression analysis in an additive genotype model after adjustment for age classes separately by sex. Age classes were defined according to age distribution in the individual panels, and included ≤40, 41−50, 51−60 and >60 years for the Amagasaki panel, and ≤55, 56−60, 61−65, 66−70 and >70 years for the Fukuoka panel. A one tailed value of p < 0.05 (p < 0.1 two-tailed) was considered statistically significant. We combined association results for the two Japanese panels by using the inverse variance method. We used PLINK (version 1.06; http://pngu.mgh.harvard.edu/~purcell/plink/) , R software (version 2.8.1; www.r-project.org) and rmeta (version 2.16; http://cran.r-project.org) for association test and meta-analysis (websites accessed 6 February 2011).
Assessment of genetic effect of obesity variants
To assess the proportion of variance for BMI that was explained by each SNP, we calculated a coefficient of determination R2 as: 2f(1 − f)β2, where f is the minor allele frequency and β is the per-allele effect on the standardised values of BMI. We measured the cumulative effect of multiple SNPs by summing the R2 values for individual SNPs.
Test of ethnic diversity and sex specificity
We compared the per-allele effect size of each SNP on inverse-normal transformed BMI between the ethnic groups (Japanese vs Europeans) and between sexes. Taking into account the well-known male–female differences in body composition (e.g. fat distribution, deposition and accumulation) , we tested the potential sex specificity in the genetic associations with obesity. We examined the heterogeneity of the effect size with Cochran’s Q-test .
Association analysis of type 2 diabetes
While we tested the primary association with obesity measures, we tested type 2 diabetes association as a secondary analysis in the present study. Thus, we performed two-staged analysis for diabetes case–control study. That is, all SNPs were tested for association with type 2 diabetes in stage 1 samples and only SNPs with p < 0.1 for BMI or weight were then tested in stage 2 samples (ESM Table 1). Using logistic regression analysis, we tested association of candidate SNPs with type 2 diabetes, with and without adjustment for BMI. We adjusted the diabetes trait for sex and BMI, but not for age because age distribution differed between case and control groups; cases were younger than controls, who were defined as being ≥55 years of age.
BMI and weight association at reported SNPs
Association of previously reported SNPs with BMI and type 2 diabetes in Japanese individuals
Type 2 diabetes (by BMI-adjusted status)
BMI (n = 18,264)
Weight (n = 18,264)
7.1 × 10−7b
6.3 × 10−6b
3.2 × 10−5b
2.9 × 10−4b
1.3 × 10−4b
1.3 × 10−3b
3.1 × 10−7b
6.3 × 10−5b
4.6 × 10−6b
2.5 × 10−4b
4.3 × 10−10b
2.4 × 10−7b
Ethnic heterogeneity in effect sizes
Association of obesity susceptibility SNPs with type 2 diabetes
For the case–control study of type 2 diabetes, we genotyped 11 obesity-associated SNPs in the stage 1 and stage 2 panels; the remaining three SNPs were genotyped only in the stage 1 panel (ESM Table 1). Some evidence of association with type 2 diabetes in a direction consistent with the BMI–SNP associations (p = 0.02−4.3 × 10−10 and OR 1.06–1.20 before adjustment for BMI; p = 0.04−2.4 × 10−7 and OR 1.05–1.17 after adjustment for BMI) was provided for six (of 11) SNPs in the Japanese population (Fig. 1b, Table 2). After adjusting for BMI, most of the observed associations between obesity-associated SNPs and diabetes were slightly attenuated, although nominal significance remained (Table 2, ESM Table 5). Considering the possibility of some selection bias in the case–control study design, we also tested the diabetes association by nested case–control comparison within the same population (i.e. Fukuoka panel) and verified a fair consistency in the OR for type 2 diabetes (ESM Table 6). Further, to examine the possibility that the BMI-independent diabetes associations derive from genetic susceptibility to fat distribution, we tested the association with WHR among the control participants in the Fukuoka panel (n = 4,889), where none of the six SNPs showed significant association with WHR in a direction consistent with the SNP–diabetes associations (ESM Table 7).
The present study investigated genetic susceptibility to common forms of obesity and its relevance to type 2 diabetes in Japanese populations. Replicating a study of candidate loci previously identified by GWA meta-analyses of Europeans [10, 11], we found some ethnic diversity in obesity variants (Fig. 1a). The top hit associations were consistently reported at FTO and MC4R in populations of European descent [5, 6, 10–12, 14, 15], whereas equivalent or more pronounced associations with obesity localised to TMEM18 and BDNF, together with modest association at SEC16B, GNPDA2, MTCH2, BCDIN3D–FAIM2, SH2B1–ATP2A1 and KCTD15, were found in the Japanese populations (Table 2, ESM Table 4). In addition, we found that the direction of BMI association was concordant between the ethnic groups at all tested loci, although the cumulative effect of the associated SNPs was smaller in Japanese than in Europeans. Of particular note is the fact that, in the present study, we highlighted the genetic impact of six loci on type 2 diabetes, this impact being independent of obesity susceptibility in all six loci.
Recently, two GWA meta-analyses were performed for examination of obesity in populations of European descent; the studies involved >32,000 and >25,000 individuals, with follow-up analysis using genotypes from large cohorts (>50,000 samples in total) and computer-generated association results [10, 11]. Collectively, these studies revealed 13 unique obesity-associated loci in Europeans. Four studies in total, including our present study, have attempted to replicate the obesity association in East Asians; of these, two studies involved Japanese individuals and two involved Chinese individuals [23–25]. While the design of these studies was not identical (two case–control studies, one quantitative trait analysis and one study with both-types of analytical approaches combined), all four studies consistently reported significant association with obesity at the GNPDA2 (rs10938397) and FTO (rs9939609 or its proxies) loci in East Asians. The present study, which is the largest of the four studies and the only one that involved quantitative trait analysis using the general population sample, has enabled us to validate nine other SNP loci. Eight of these SNP loci had previously shown obesity association in one or two studies [23–25], whereas replication at MTCH2 (rs10838738) has not been previously reported in East Asians.
Compared with the data for Europeans [10, 11], the variance for BMI explained by individual SNP loci appeared to be modest as a whole in the Japanese population, except for TMEM18 rs4854344 (R2 = 0.13%), BDNF rs6265 (R2 = 0.1%) and MTCH2 rs10838738 (R2 = 0.06%; Fig. 1b, ESM Table 4). It should be kept in mind that the larger cumulative effect on BMI in Europeans than in Japanese is partly due to the ‘winner’s curse effect’ , where the original meta-analysis tends to overestimate the true population effect, in addition to ethnic difference in at-risk alleles. We found that the effect size (β) was larger at TMEM18 rs4854344 than at FTO rs9939609 in the independent panels of Japanese samples (ESM Table 2). Nevertheless, there seems to be an overall consistency of genetic variants for susceptibility to obesity between the examined ethnic groups.
Sex specificity is another issue of interest in the genetics of obesity. Some epidemiological studies have suggested that different genes influence variation of BMI in men and women . However, little evidence has been provided to support this notion. In the present study, we found nominally significant sex-related differences in the effect sizes for two obesity variant loci, NEGR1 and GNPDA2 (ESM Table 3). Although heterogeneity was not statistically significant (p = 0.09), obesity association only in women appeared to be replicated for MC4R. Notably, a previous study has reported the equivalent type of sexual dimorphism for the association between a MC4R variant and obesity measures in the Swedish population . Despite no prior evidence of sex specificity at this locus in Europeans [4, 48], these findings warrant further investigation with reference to ethnic homogeneity and/or the specificity of target populations.
We acknowledge several limitations inherent in the present study. Specifically, the sample size used to screen obesity association was smaller for the Japanese group (n = 18,264) than that used for the European GWA meta-analyses (n > 25,000 in the discovery stage). Therefore, we assessed statistical power for each of the tested loci, assuming effect sizes equivalent to those reported in the original GWA studies for the allele frequencies in the Japanese (ESM Table 10). Apart from the replicated associations, sufficient power (i.e. >0.8) was not attainable for two (of 14) SNP loci in the Japanese samples. In addition to the issue of power, differences in linkage disequilibrium patterns between the ethnic groups could also have contributed to the lack of replicated association at a given locus. We found some cross-population differences in linkage disequilibrium relations at several SNP loci, which could also attenuate (or strengthen) the association signals accordingly. Regional examination of SNP–obesity association, which is ongoing in Asians, but not point-wise studies, will resolve this issue.
In summary, we confirmed that 11 SNPs from ten candidate loci were significantly associated with BMI in Japanese individuals, as was previously reported in Europeans. We also found some cross-population differences in the effect sizes of individual obesity variants. These studies, moreover, highlight the genetic influences on type 2 diabetes that appear to be independent of BMI, as well as the potential presence of sex specificity in the genetics of common obesity.
This work was supported by the Program for Promotion of Fundamental Studies in Health Sciences of the National Institute of Biomedical Innovation Organization (NIBIO), the Manpei Suzuki Diabetes Foundation, a grant from National Center for Global Health and Medicine (NCGM) and by the Ministry of Education, Cultures, Sports, Science and Technology, all of Japan. We acknowledge the outstanding contributions of the employees of NCGM, who provided technical and infrastructural support for this work. Above all, we thank the patients and study participants who made this work possible and who gave it value. We thank all the people who continuously support the Hospital-based Cohort Study at NCGM, the Amagasaki Study and the Kyushu University Fukuoka Cohort Study in Japan. We also thank S. Kono, M. Ogasawara, C. Makibayashi and the many physicians of the Amagasaki Medical Association for their contribution in collecting DNA samples and accompanying clinical information. Part of the DNA samples from type 2 diabetes cases used for this research were provided from the Leading Project for Personalized Medicine at the Ministry of Education, Culture, Sports, Science and Technology, Japan.
Duality of interest
The authors declare that there is no duality of interest associated with this manuscript.