Diabetologia

, Volume 50, Issue 5, pp 980–984

Replication study for the association of TCF7L2 with susceptibility to type 2 diabetes in a Japanese population

  • T. Hayashi
  • Y. Iwamoto
  • K. Kaku
  • H. Hirose
  • S. Maeda
Article
  • 873 Downloads

Abstract

Aims/hypothesis

The transcription factor 7-like 2 gene (TCF7L2) has been shown to be strongly associated with an increased risk of type 2 diabetes in white populations. To further investigate the involvement of TCF7L2 in conferring susceptibility to type 2 diabetes, we examined the association of TCF7L2 polymorphisms with type 2 diabetes in a Japanese population.

Subjects and methods

We analysed four SNPs (rs12255372, rs7903146, rs7901695 and rs11196205) and one tetranucleotide repeat polymorphism (DG10S478) in 1,630 Japanese subjects with type 2 diabetes and 1,064 control subjects.

Results

All investigated polymorphisms were significantly associated with type 2 diabetes, and rs12255372 showed the strongest association (T vs G, χ2 = 9.20, p = 0.0024, odds ratio = 1.70, 95% CI = 1.20–2.41), although the frequency of the risk allele in our population was much lower than that in white populations. The microsatellite polymorphism showed an almost complete linkage disequilibrium to rs1255372 when the alleles with longer repeats (+8, +12) were considered as minor alleles and showed an association with type 2 diabetes (χ2 = 5.34, p = 0.021, odds ratio = 1.50, 95% CI = 1.06–2.12).

Conclusions/interpretation

These results indicate that TCF7L2 might be a strong candidate for conferring susceptibility to type 2 diabetes across different ethnicities.

Keywords

Association study Gene polymorphism Microsatellite marker TCF7L2 Transcription factor 7-like 2 Type 2 diabetes 

Abbreviations

GLP-1

glucagon-like peptide 1

LD

linkage disequilibrium

OR

odds ratio

SNP

single nucleotide polymorphism

Introduction

Type 2 diabetes affects more than 200 million individuals worldwide, and its prevalence continues to increase in many countries, including Japan. Although the precise mechanisms underlying the development and progression of type 2 diabetes have not been elucidated, a combination of multiple genetic and/or environmental factors is considered to contribute to the pathogenesis of the disease [1]. To date, several genes have been postulated as candidates for conferring susceptibility to type 2 diabetes [2, 3, 4, 5, 6, 7, 8]; however, studies have produced conflicting results, probably due to a combination of small effect sizes being sought in sample sizes too small, using levels of statistical confidence that were not strict enough, or due to differences between the study populations in terms of environmental circumstances or ethnicity [1, 9].

The transcription factor 7-like 2 gene (TCF7L2 [MIM 602228]) on chromosome 10q25 [10, 11], part of the Wnt signalling pathway [12], has been shown to be strongly associated with an increased risk of type 2 diabetes in Icelandic, Danish and US populations [13]. Five single nucleotide polymorphisms (SNPs) and one tetranucleotide repeat polymorphism (DG10S478) within TCF7L2 have shown strong evidence of an association with type 2 diabetes in these three cohorts, and two of the SNPs (rs12255372 and rs7903146) showed strong linkage disequilibrium (LD) with composite at-risk alleles of the microsatellite marker (DG10S478). The associations of the SNPs rs12255372 and rs7903146 with decreased insulin secretion were also reported in US subjects with impaired glucose tolerance [14]. Although replication studies [15, 16, 17, 18, 19, 20, 21] have confirmed the role of TCF7L2 in conferring susceptibility to type 2 diabetes in white populations, the pathophysiological mechanisms affected by the variations within TCF7L2 and the effect of the gene in other ethnic populations have yet to be fully established.

The aim of the present study was to determine whether the previously investigated variations within TCF7L2 are associated with susceptibility to type 2 diabetes in Japanese subjects.

Subjects and methods

Subjects and DNA preparation

DNA samples were obtained from peripheral blood samples from of 1,630 type 2 diabetes patients recruited from the outpatient clinic of Shiga University of Medical Science, Kawasaki Medical School (978 men, 652 women; age 61.5 ± 11.6 duration of diabetes 11.5 ± 13.9 HbA1c 7.4 ± 1.6%; fasting plasma glucose 9.1 ± 3.5 mmol/l; BMI 23.7 ± 3.9 kg/m2 [all values are expressed as means±SD]). Diabetes was diagnosed according to the WHO criteria [22]. Type 2 diabetes was clinically defined as a disease with gradual adult onset. Subjects who tested positive for anti-GAD antibodies and those with mitochondrial disease (mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episode [MELAS]) or MODY were excluded. We also examined 1,064 control subjects who were enrolled from an annual health check conducted either at Juntendo University or Keio University School of Medicine (Tokyo, Japan; 638 men, 426 women; age 45.5 ± 9.5 years; HbA1c 4.7 ± 0.4%; fasting plasma glucose 5.1 ± 0.5 mmol/l; and BMI 22.9 ± 3.0 kg/m2).

Written informed consent was obtained from all participants, and DNA extraction was performed using the standard phenol–chloroform procedure. The protocol was approved by the ethics committee of The Institute of Physical and Chemical Research.

Genotyping

A microsatellite marker (DG10S478) with a tetranucleotide repeat polymorphism was analysed with regard to fragment sizes for each allele using the ABI Prism 3700 Automatic DNA Sequencer and GeneScan and Genotyper software (Applied Biosystems, Foster City, CA, USA). The SNPs within TCF7L2 (rs12255372, rs7903146, rs7901695 and rs11196205) were analysed using the TaqMan assay (Applied Biosystems). The success rate of this assay was >95%, and there was almost 100% agreement between the results of genotyping and the results of direct sequencing.

Statistical analysis

Statistical analyses for the association study and calculation of linkage disequilibrium (LD) coefficients (r2) were performed as described previously [23]. The differences between the case and control groups in terms of genotype distribution or allele frequency were analysed using Pearson’s χ2 test.

Results

Association study

The clinical characteristics of the subjects are summarised in Table 1. We calculated the power of our sample size to identify associations between the SNPs and type 2 diabetes using a dominant model for the minor allele. In this case-control setting, the prevalence of type 2 diabetes was assumed to be 10%. Our study had >90% power (β) at the p = 0.05 significance level of detecting a genotypic relative risk (γ) of 1.5 for the SNPs with a minor allele frequency of 0.03 in our sample.
Table 1

Clinical characteristics of the subjects

 

Type 2 diabetic subjects

Control subjects

p value

(n = 1,064)

(n = 1,630)

Sex (male:female)

978:652

638:426

0.9845a

Age (years)b

61.5 ± 11.6

45.5 ± 9.5

<0.0001

BMI (kg/m2)b

23.7 ± 3.9

22.9 ± 3.0

<0.0001

FPG (mmol/l)b

9.1 ± 3.5

5.1 ± 0.5

<0.0001

HbA1c (%)b

7.4 ± 1.6

4.7 ± 0.4

<0.0001

Duration of diabetes (years)b

11.5 ± 13.9

aχ2 test

bValues are expressed as means ± SD

We genotyped four SNPs (rs12255372, rs7903146, rs7901695 and rs11196205) and the microsatellite (DG10S478) within TCF7L2 reported to be associated with type 2 diabetes [13], and found that the minor allele frequencies of these polymorphisms were much lower in our Japanese population than in the white populations previously studied (Table 2). All four SNPs and the microsatellite polymorphism were significantly associated with type 2 diabetes, and rs12255372 was more strongly associated than the other SNPs (T vs G, χ2 = 9.20, p = 0.0024, odds ratio [OR] = 1.7, 95% CI = 1.20–2.41; Table 3). The genotype distributions of all SNPs were in Hardy–Weinberg equilibrium (p = 0.48 for rs12255372, p = 0.91 for rs7903146, p = 0.99 for rs7901695, p = 0.58 for rs11196205)
Table 2

Genotype distribution and allele frequencies of SNPs and DG10S478 in TCF7L2

SNP

Genotype (n [%])

Allele (%)

MAF in white populationsa

rs12255372

GG

GT

TT

G

T

 

 Case

1,515 (92.9)

112 (6.9)

3 (0.2)

96.4

3.6

36.6

 Control

998 (95.7)

45 (4.3)

0 (0.0)

97.8

2.2

28.5

rs7903146

CC

CT

TT

C

T

 

 Case

1,450 (89.6)

165 (10.2)

4 (0.2)

94.7

5.3

39.7

 Control

980 (91.8)

85 (8.0)

2 (0.2)

95.8

4.2

30.1

rs7901695

TT

CT

CC

T

C

 

 Case

1,440 (88.9)

173 (10.7)

4 (0.2)

94.4

5.6

38.4

 Control

966 (91.5)

88 (8.3)

2 (0.2)

95.6

4.4

29.3

rs11196205

GG

CG

CC

G

C

 

 Case

1,384 (86.8)

198 (12.4)

13 (0.8)

93.0

7.0

53.2

 Control

952 (89.7)

107 (10.1)

2 (0.2)

94.8

5.2

46.4

DG10S478b

AA

AB

BB

A

B

 

 Case

1497 (93.1)

111 (6.9)

0 (0)

96.5

3.5

36.0

 Control

962 (95.3)

47 (4.7)

0 (0)

97.7

2.3

26.3

aCombined data from [13, 14, 15, 16, 17, 18, 19, 20, 21]

bA: short allele (allele −8, 0, 4), B: long allele (allele 8, 12)

Table 3

Associations of SNPs in TCF7L2 with type 2 diabetes

SNP

 

χ2

p value

OR

95% CI

rs12255372

Genotype

9.51

0.0086

 (G>T)

G vs T

9.20

0.0024

1.70

1.20–2.41

 

GG vs GT+TT

8.49

0.0036

1.68

1.18–2.40

 

GG+GT vs TT

1.92

0.1656

rs7903146

Genotype

3.90

0.1426

 (C>T)

C vs T

3.81

0.0510

1.30

1.00–1.68

 

CC vs CT+TT

3.89

0.0485

1.31

1.00–1.72

 

CC+CT vs TT

0.10

0.7487

1.32

0.24–7.21

rs7901695

Genotype

4.17

0.1241

 (T>C)

T vs C

4.06

0.0439

1.30

1.01–1.68

 

TT vs CT+CC

4.17

0.0411

1.32

1.01–1.72

 

TT+CT vs CC

0.10

0.7568

1.31

0.24–7.15

rs11196205

Genotype

8.07

0.0177

 (G>C)

G vs C

6.91

0.0085

1.37

1.08–1.73

 

GG vs CG+CC

5.25

0.0219

1.33

1.04–1.70

 

GG+CG vs CC

4.45

0.0348

4.35

0.98–19.32

DG10S478

A vs B

5.51

0.019

1.52

1.07–2.15

 

AA vs AB

5.34

0.021

1.50

1.06–2.12

A short allele (allele −8, 0, 4), B long allele (allele 8, 12)

With regard to the microsatellite polymorphism (DG10S478), we identified five alleles in our study sample and, as observed in other populations, allele 0 was the most frequent (ESM Tables 1 and 2). We also found that DG10S478 was similar to rs12255372 in its association with type 2 diabetes (Table 3). Subsequent analysis for LD among these polymorphisms was performed; the microsatellite polymorphism showed complete LD to rs12255372 when the alleles with longer repeats (+8, +12) were considered as minor alleles (Table 4).
Table 4

Linkage disequilibrium coefficient (r2) among the four SNPs and the DG10S478 polymorphisms

 

rs12255372

rs7903146

rs7901695

rs11196205

DG10S478 (allele X)a

0.61

0.69

0.66

0.27

DG10S478 (allele 8 and allele 12)

0.99

0.53

0.52

0.48

rs12255372

 

0.53

0.52

0.48

rs7903146

  

0.96

0.27

rs7901695

   

0.28

aAllele X denotes all alleles except for allele 0

Logistic regression analysis revealed that carriers of the risk allele of rs12255372 were associated with susceptibility to the disease even after adjusting for age and BMI (OR = 2.06, 95% CI 1.20–3.52, p = 0.0083).

Discussion

In the present study the four SNPs and the microsatellite polymorphism analysed were found to be significantly associated with type 2 diabetes.

Growing evidence suggests that TCF7L2 is a strong susceptibility gene to type 2 diabetes in white populations [13, 14, 15, 16, 17, 18, 19, 20, 21]. To date, all studies in white populations have found the SNPs within the gene to be significantly associated with type 2 diabetes, and the estimated population-attributable risk was shown to be approximately 20% [13, 15, 16]. Although the contribution of TCF7L2 in conferring susceptibility to type 2 diabetes has been widely investigated in white populations, the effects of TCF7L2 should also be evaluated in different ethnic groups, because it is well known that there are significant differences in the frequencies of certain genetic variations among different ethnic groups [6, 9].

Our results indicated that the frequencies of the minor allele of rs12255372, the SNP that showed the strongest association with the disease, were substantially lower in our Japanese population vs white populations (type 2 diabetic patients: 3.6 vs 36.6%, p = 1 × 10−299; control subjects: 2.2 vs 28.5%, p = 4 × 10−149) [13, 16, 18, 19], as were the frequencies of the other SNPs. In addition, the LD pattern for this locus in the Japanese population also appeared to be different from that in white individuals; the longer allele of the microsatellite polymorphism showed complete LD to rs12255372 in our sample, whereas the X allele (alleles other than allele 0) showed complete LD to the SNP in white populations [13]. There are therefore clear ethnic differences with regard to this locus between the populations. However, we did identify a consistent association of this gene with type 2 diabetes in our Japanese population, further validating the contribution of TCF7L2 to conferring susceptibility to the disease. Since the frequencies of the risk allele were much lower in our population, the estimated population-attributable risk was approximately 2.4%, suggesting that the genetic contribution of these polymorphisms to type 2 diabetes is relatively weak.

Previous studies have focused on the role of TCF7L2 in oncogenesis and cancer progression [24, 25, 26, 27]. Functional analyses are required to reveal the role of this gene in type 2 diabetes and to determine how variants of this gene confer susceptibility to the disease. Florez et al. recently reported the association between SNPs (rs12255372 and rs7903146) and decreased insulin secretion in US subjects with impaired glucose tolerance [14]. Damcott et al. also reported an association between SNPs (rs7901695 and rs7903146) and insulin resistance in white subjects [17]. Based on the fact that there is a putative TCF-binding motif within the promoter region of the gene encoding proglucagon [28], Yi et al. [12] suggested that TCF7L2 was capable of regulating the expression of this gene, whose protein product is enzymatically cleaved to produce glucagon-like peptide 1 (GLP-1), which is secreted from gut endocrine L cells and is involved in glucose homeostasis. We therefore examined whether the plasma total GLP-1 concentrations were correlated with the polymorphisms in our control subjects; however, we did not identify any significant correlations (H. Maegawa, H. Yamamoto, T. Tani, A. Kashiwagi [all affiliated with Shiga University of Medical Science, Otsu, Japan], and T. Hayashi and S. Maeda; unpublished observations). Since it was reported that adipose tissue TCF7L2 expression is decreased in subjects with type 2 diabetes [19], TCF7L2 might play some roles in the adipocytes, such as the regulation of adipogenesis by altering transcriptional regulation of the genes encoding CCAAT/enhancer-binding protein-α (CEBPA) and peroxisome proliferator-activated receptor-γ (PPARG). However, the precise mechanism by which TCF7L2 and its variants influence susceptibility to type 2 diabetes remains to be elucidated.

In summary, we have identified significant associations of TCF7L2 variants with type 2 diabetes in a Japanese population, and have shown that differences exist in the allele frequencies and the pattern of LD between different ethnic populations.

Notes

Acknowledgements

We would like to thank R. Kawamori (Department of Internal Medicine, Metabolism and Endocrinology, School of Medicine, Juntendo University, Tokyo, Japan), A. Kashiwagi (Department of Medicine, Shiga University of Medical Science, Otsu, Japan), T. Babazono (Diabetes Center, Tokyo Women’s Medical University, Tokyo, Japan) for helpful discussions. We also thank N. Osawa, S. Tsukada, K. Kamiyama and the technical staff of the Laboratory for Diabetic Nephropathy at the SNP Research Centre for their technical assistance. This work was partly supported by the Japanese Millennium Project.

Duality of interest

None of the authors has a conflict of interest to declare.

Supplementary material

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • T. Hayashi
    • 1
    • 2
  • Y. Iwamoto
    • 2
  • K. Kaku
    • 3
  • H. Hirose
    • 4
  • S. Maeda
    • 1
  1. 1.Laboratory for Diabetic Nephropathy, SNP Research CentreThe Institute of Physical and Chemical ResearchYokohamaJapan
  2. 2.Diabetes CentreTokyo Women’s Medical UniversityTokyoJapan
  3. 3.Division of Endocrinology and Metabolism, Department of Internal MedicineKawasaki Medical SchoolOkayamaJapan
  4. 4.Department of Internal MedicineKeio University School of MedicineTokyoJapan

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