OBJECTIVE—Genetic polymorphisms of the transcription factor 7-like 2 (TCF7L2) gene is one of the few validated genetic variants with large effects on the risk of type 2 diabetes in the populations of European ancestry. In this study, we aimed to explore the effect of the TCF7L2 polymorphisms in a Han Chinese population.

RESEARCH DESIGN AND METHODS—We genotyped 20 single nucleotide polymorphisms (SNPs) across the TCF7L2 gene in 1,520 unrelated subjects from a Han Chinese population in Taiwan. The associations of SNPs and haplotypes with type 2 diabetes and linkage disequilibrium (LD) structure of the TCF7L2 gene were analyzed.

RESULTS—The previously reported SNPs rs7903146 T- and rs12255372 T-alleles of the TCF7L2 gene were rare and were not associated with type 2 diabetes in a Chinese population, which may attribute to the low frequencies of these two SNPs. SNP rs290487 located in an LD block close to the 3′ end of the gene was associated with type 2 diabetes (allele-specific P = 0.0021; permuted P = 0.03). The odds ratio was 1.36 for the CT genotype (95% CI 1.08−1.71; P = 0.0063) and 1.51 for the CC genotype (1.10 −2.07; P = 0.0085) compared with the TT genotype, corresponding to a population attributable risk fraction of 18.7%. The haplotypes composed of rs290487 were also significantly associated with type 2 diabetes (global P = 0.012).

CONCLUSIONS—We identified a novel risk-conferring genetic variant of TCF7L2 for type 2 diabetes in a Chinese population. Our data suggested that the TCF7L2 genetic polymorphisms are major determinants for risk of type 2 diabetes in the Chinese population.

Type 2 diabetes is a highly inheritable metabolic disorder of polygenetic nature (1). Although theoretical analyses emphasized the power of genetic association study in common multifactorial diseases, the search for genes that increase the risk of type 2 diabetes has not been very successful so far. The genes implicated in type 2 diabetes confer only modest effects on the disease risk and in many cases have yielded inconsistent results in replication efforts (2). Only few associations, notably the Pro12Ala polymorphism in the peroxisome proliferator–activated receptor (PPARG) gene (3), the Glu23Lys polymorphism in the KCNJ11 gene (4), and the genetic variants of calpain-10 genes (5), have been convincingly replicated.

Recently, researchers seeking the cause of a previously identified linkage signal on chromosome 10q found a strong association of a common microsatellite (DG10S478) of the transcription factor 7-like 2 gene (TCF7L2) with type 2 diabetes in an Icelandic sample, and the result was replicated in the samples from the U.S. and Denmark (6). DG10S478 is located within a well-defined linkage disequilibrium (LD) block of 92.1 kb that encompassed exon 4 and parts of two large flanking introns. Five single nucleotide polymorphisms (SNPs) (rs12255372, rs7903146, rs7901695, rs11196205, and rs7895340) within the LD block also showed similarly robust associations with type 2 diabetes (6). Further studies in other European populations, African Americans, Mexican Americans, and Asian Indians confirmed the strong associations with an estimated population attributable risk of 17–28% (722). Several genome-wide association studies independently confirmed the strong associations of SNP rs7903146 in the TCF7L2 locus with type 2 diabetes (2326). Further phylogenetic reconstruction of the revolutionary relationship between the haplotypes within the exon 4 LD block identified the HapBT2D lineage, which contains all haplotypes carrying the ancestral T-allele of SNP rs7903146 as a type 2 diabetes risk variant (27). These data convincingly demonstrated that the genetic variants within the exon 4 LD block of the TCF7L2 gene, especially rs7903146 T, are major genetic risk factors for type 2 diabetes in populations of European ancestry.

However, unlike in populations of European origin, the frequency of the rs7903146 T-allele is relatively low (∼2%) in the HapMap Han Chinese Beijing (CHB) databank, raising the question of whether these variants are major contributors of type 2 diabetes in the Chinese population. Furthermore, the association study of the genetic polymorphism of TCF7L2 with type 2 diabetes in the Chinese population has been lacking. Therefore, we conducted an association study in 1,520 unrelated subjects from a Han Chinese population in Taiwan. SNPs tagging common variations across the TCF7L2 gene were selected according the HapMap CHB databank group (http://www.hapmap.org/), and additional SNPs with previously known strong associations with type 2 diabetes in populations of European ancestry were also genotyped. Their associations with type 2 diabetes and LD structure were analyzed.

The studied population comprised 760 normoglycemic control subjects and 760 type 2 diabetic patients from a Han Chinese population in Taiwan. The glucose-tolerant (determined by 75-g oral glucose tolerance tests) control subjects were recruited from routine health examinations, and type 2 diabetic patients were recruited from the metabolism clinics of the National Taiwan University Hospital. Type 2 diabetic patients were diagnosed based on the criteria of the American Diabetes Association (28) with fasting plasma glucose ≥126 mg/dl or 2-h plasma glucose ≥200 mg/dl during an oral glucose tolerance test. Patients with ages of onset <35 years were excluded. Total cholesterol and triglycerides were measured in fasting samples using an autoanalyzer (Hitachi 7250 special; Hitachi, Tokyo, Japan). A1C was measured by high-performance liquid chromatography (Primus, Wichita, KS). Written informed consent was obtained from every participating subject, and the study was approved by the institutional review board of the National Taiwan University Hospital.

Selection of tag SNPs and genotyping.

From HapMap CHB databank (public data release 21 a/phase II, Jan. 2007), 112 SNPs that had minor allele frequencies exceeding 1% without violation of Hardy-Weinberg equilibrium were identified. To identify common haplotype tagging SNPs, these eligible SNPs were entered into the Tagger program implemented in Haploview version 3.32 (29) (http://www.broad.mit.edu/mpg/haploview/) with a minor allele frequency threshold of 20% and an r2 of 0.8. Thirteen tag SNPs (rs6585194, rs7919409, rs11196219, rs4918792, rs10749127, rs11196224, rs7085532, rs17130188, rs10787475, rs12775879, rs290489, rs290487, and rs290481) were selected, which captured 92.2% of the variance for haplotypes composed of all SNPs with minor allele frequencies ≥20% across the TCF7L2 gene. Because nearly all SNPs within the exon 4 LD block have minor allele frequencies <5% in the HapMap CHB databank, we additionally selected eight SNPs with known associations with type 2 diabetes (rs4506565, rs12243326, rs7895340, rs7904146, rs12255372, rs7079711, rs11196192, and rs11196213) within this region. Genotyping was performed using the GenomeLab SNPstream genotyping platform (Beckman Coulter) and its accompanying SNPstream software suite (30).

Statistical analyses.

A Hardy-Weinberg equilibrium test was performed for each sequence variant for the control group before marker-trait association analysis. Tests for the associations of each SNP and haplotype with type 2 diabetes were estimated by using the Haploview software (29). Nominal two-sided P values were reported and were corrected for multiple testings by permutation 10,000 times. For haplotype construction, genotype data of both case and control groups were used to estimate intermarker LD by measures pairwise D′ and r2 and define LD blocks. We used the solid spine of the LD method implemented in the Haploview software to define an LD block with an extended spine if D′ was >0.8 (29).

For the sliding window association analysis of the haplotypes composed of the adjacent 2–10 SNPs, we used the score test developed by Schaid et al. (31) and implemented in the Haplo.Stats package (http://www.mayo.edu/hsr/Sfunc.html). This method allows the adjustment for possible confounding variables and provides both global tests and haplotype-specific tests. The global P value for the associations of haplotypes composed of the adjacent 2–10 SNPs with type 2 diabetes were estimated with simulations 10,000 times. A P value <0.05 was considered statistically significant. We also performed multivariate analysis by considering age, sex, and BMI as covariates using the Haplo.Stats program. The population attributable risk fraction (PAF) was estimated with the data from the control group, calculated as follows: 1 − {1/[p2 ORhomo + 2p(1 − p)ORhetero + (1 − p)2]}, where p is the risk-allele frequency, ORhomo is the odds ratio (OR) for homozygotes, and ORhetero is the OR for heterozygotes.

Characteristics of subjects.

We genotyped a total of 1,520 unrelated subjects (including 760 type 2 diabetic case and 760 control subjects) from a Han Chinese population in Taiwan. The Han Chinese is the largest ethnic group in Taiwan, comprising ∼98% of the general population. The clinical and biochemical characteristics are summarized in Table 1.

Characteristics of the SNPs and LD structures of TCF7L2 gene.

On average, 99.08% of attempted genotypes were successful (success rates ranging from 98.1 to 99.9% for each SNP) except for rs6585194, in which genotyping failed in all samples. The concordance rate of genotyping duplication was 99.93%. Graphical representation of SNPs in relation to the exon-intron structure is shown in Fig. 1. All SNPs were in introns. The genomic position, nucleic acid composition, and minor allele frequencies of the 20 genotyped SNPs are summarized in Table 2.

To determine the extent of LD in the TCF7L2 gene, genotype data of both case and control groups were used to estimate intermarker LD. Standardized pairwise LD coefficients D′ and r2 between markers were estimated (Table 3). Six LD blocks were identified across the gene (Fig. 1). LD block 1 spanning over a part of intron 3, the whole exon 4, and a part of the intron 4 corresponds to the exon 4 LD block described previously by Grant et al. (6), which contains the variants of the strongest associations with type 2 diabetes in the populations of European ancestry.

Association analysis of genetic variants of TCF7L2 gene with type 2 diabetes.

The minor allele frequencies of SNPs located in LD block 1 were low (0.4–2.6%, Table 2) in this Chinese population compared with populations of European ancestry. The genetic variations within this region were rare, with one single haplotype (A-C-T-T-G-G) accounting for 95% of all chromosomes (Table 4). We did not detect any association of type 2 diabetes with any SNP within this LD block, including rs7903146 and rs12255372 (Table 2). There was no association of haplotypes in LD block 1 with type 2 diabetes (global P = 0.47, best haplotype-specific P = 0.39) (Table 4). Sliding window analysis for the haplotypes composed of adjacent SNPs (2–10 SNPs in length) also failed to reveal any association with type 2 diabetes within this region (Table 5).

However, we found that SNP rs290487 (minor allele frequency 39.03%), located 150 kb downstream of rs7903146, was significantly associated with type 2 diabetes (nominal P = 0.0021) (Table 2). The association remained significant after correction for multiple testing (permuted P = 0.03) (Table 2). The allelic OR of the rs290487 C-allele carriers was 1.26 (95% CI 1.08–1.46) (Table 2). The genotypic OR for the heterozygous genotype (CT) was 1.36 (1.08–1.71, P = 0.0063) and 1.51 (1.10–2.07, P = 0.0085) for homozygous genotype (CC), compatible with either dominant or additive genetic models (P = 0.0017 and 0.0059, respectively) and corresponding to a PAF of 18.7%. The SNP rs290487 was located in an LD block (LD block 6) spanning from intron 7 to intron 13 (14 kb in length) (Fig. 1). Another SNP rs290481 in this block was also associated with type 2 diabetes with marginal significance (nominal P = 0.021, permuted P = 0.27) (Table 2). The haplotypes within LD block 6 were significantly associated with type 2 diabetes (global P = 0.012) (Table 4). Among them, the haplotype T-A was associated with a reduced risk (OR 0.83 [95% CI 0.71–0.96], permuted P = 0.033) (Table 4), and the haplotype C-G was associated with an increased risk of type 2 diabetes (1.24 [1.06–1.44], permuted P = 0.014) (Table 4). These associations remained significant after adjustment for sex, age, and BMI (Tables 2 and 4), suggesting their effects on diabetes were not primarily mediated through adiposity. Sliding window analysis also revealed consistently significant associations of haplotypes containing rs290487 with type 2 diabetes (best global P = 0.002) (Table 5).

The polymorphism of TCF7L2 (rs7903146) is the strongest single genetic variant associated with type 2 diabetes (6,2326) and has been convincingly replicated in multiple populations (7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26). In this study, we aimed to explore the effect of the TCF7L2 polymorphisms in a Han Chinese population. We found that the type 2 diabetes risk–conferring alleles in the exon 4 LD block described previously by Grant et al. (6), such as rs7903146 T and rs12255372 T, were rare in this Chinese population. We did not detect any association of genetic variants within this region with type 2 diabetes in this Chinese population. However, given their low allele frequencies of 2.3% and assuming the genotype relative risks of 1.45 and 2.41 in heterozygous and homozygous carriers, respectively (6), and the diabetes prevalence of 8% in the Chinese population in Taiwan, enrollment of ∼1,700 case subjects would be necessary for the case-control study to have 80% power (32). Thus, a sample size at least twice larger than our study would be needed to detect the effect of these genetic variants.

Florez et al. (22) recently reported the associations of these variants with increased risk of developing diabetes in a large prospective cohort of the Diabetes Prevention Program. In subgroup analysis, there were also no associations of these variants with type 2 diabetes in Asians, which could at least attribute to a small sample size (128 participants) (22). Horikoshi et al. (33) and Hayashi et al. (34) independently reported significant associations between rs7903146 and type 2 diabetes in the Japanese population. However, the minor allele frequency of rs7903146 was low (3–5%) in their study. The PAF for rs7903146 is only ∼3% in the Japanese population, a much lower value than that in the populations of European ancestry (6,33,34). These data indicated that the genetic variants within the exon 4 LD block were rare among the Japanese and Chinese population, so that large sample sizes would be needed to detect the effects.

Interestingly, we identified a novel association of SNP rs290487 C located in an LD bock spanning over intron 7 to intron 13 with type 2 diabetes. In contrast to rs7903146 T, rs290487 C was common (allele frequency 39.03%) in the Chinese population. The risk allele and genotypes were associated with a significantly increased risk of type 2 diabetes, and the corresponding PAF was also substantial (18.7%) in the Chinese population, comparable with that of rs7903146 T in the populations of European origin (6). These data suggested that genetic variants of the TCF7L2 gene were also major determinants of type 2 diabetes in the Chinese population. Moreover, our results along with the published reports from other ethnic groups demonstrate that different variations of the TCF7L2 gene confer the risk of type 2 diabetes in different populations. These findings provided novel evidence supporting a role of the TCF7L2 locus in the pathogenesis of type 2 diabetes in a Chinese population.

The underlying mechanisms by which a genetic variation within the intron of the TCF7L2 gene confers susceptibility of type 2 diabetes remain to be elucidated. The LD block harboring rs290487 lies very close (<2 kb) to the 3′ end of TCF7L2 gene. The human TCF7L2 gene displays a high degree of alternative splicing near the 3′ end of the gene (35,36). The 3′ end of the TCF7L2 gene encodes the binding domains for COOH-terminal binding protein, a protein implicated in the repression of the TCF7L2 transcriptional activity. The alternative splicing leads to the synthesis of a number of isoforms with different COOH-terminal ends and binding domain activities, which were associated with altered downstream signaling activities (35,36). Furthermore, many alternative splice sites were observed either experimentally or in silico in this region (35). It is intriguing to speculate that genetic variations in this region would affect the action of TCF7L2 through the regulation of alternative splicing. Based on multispecies sequence alignment analysis using a phylogenic hidden Markov model implemented in the PhastCons program (http://genome.ucsc.edu/cgi-bin/hgGateway) (37), there is a high degree of evolutional conservation in the 3′ end of human TCF7L2 gene, which we identified for association of diabetes. Functional studies will be required to determine the relationship between sequence variations, gene expression, protein product, and function in human tissues. LD block 6 contains two nonsynonymous exonic SNPs and 37 intronic SNPs. Therefore, further extensive search within this region may be needed to identify the true risk-conferring site as well as to confirm the association.

In summary, we identified a novel association of the genetic variant SNP rs290487 in the TCF7L2 gene with type 2 diabetes in a Chinese population, in contrast to the previous reports of the SNP rs7903146 in other ethnic groups. The variant was located in an LD block close to the 3′ end of the TCF7L2 gene, a region displaying a high degree of alternative splicing. The effect of this variant was significant, with a substantial PAF in the Chinese population. We did not detect any association of the previously established risk allele (rs7904136 T and rs12255372 T) with type 2 diabetes, probably owing to their low frequency in the Chinese population. These data suggested that genetic polymorphisms of the TCF7L2 gene were associated with type 2 diabetes and are major genetic contributors of the risk of type 2 diabetes a Chinese population.

FIG. 1.

Graphical representation of SNPs in relation to the exon-intron structure (upper line) and Haploview LD graph of TCF7L2 gene (lower panel). The exon regions are shown with filled rectangles and numbered in order. Pairwise LD coefficients D′ × 100 are shown in each cell (D′ values of 1.0 are not shown). Standard color scheme of Haploview was applied for LD color display (logarithm of odds [LOD] score ≥2 and D′ = 1, shown in bright red; LOD score ≥2 and D′ <1 shown in blue; LOD score <2 and D′ = 1 shown in pink; LOD score <2 and D′ <1 shown in white).

FIG. 1.

Graphical representation of SNPs in relation to the exon-intron structure (upper line) and Haploview LD graph of TCF7L2 gene (lower panel). The exon regions are shown with filled rectangles and numbered in order. Pairwise LD coefficients D′ × 100 are shown in each cell (D′ values of 1.0 are not shown). Standard color scheme of Haploview was applied for LD color display (logarithm of odds [LOD] score ≥2 and D′ = 1, shown in bright red; LOD score ≥2 and D′ <1 shown in blue; LOD score <2 and D′ = 1 shown in pink; LOD score <2 and D′ <1 shown in white).

TABLE 1

Clinical and biochemical characteristics of type 2 diabetic case subjects and normoglycemic control subjects

Control subjectsCase subjectsP value
n 760 760  
Age (years) 64.52 ± 13.64 60.03 ± 11.83 <0.001 
Male:female ratio 382:378 429:331 0.016 
BMI (kg/m223.61 ± 3.16 24.66 ± 3.40 <0.001 
Fasting glucose (mmol/l) 5.37 ± 0.73 8.65 ± 2.81 <0.001 
A1C (%) 5.44 ± 0.56 7.90 ± 1.66 <0.001 
Triglycerides (mmol/l) 1.27 ± 0.73 1.89 ± 1.89 <0.001 
Total cholesterol (mmol/l) 5.05 ± 0.97 5.25 ± 1.31 0.0012 
Control subjectsCase subjectsP value
n 760 760  
Age (years) 64.52 ± 13.64 60.03 ± 11.83 <0.001 
Male:female ratio 382:378 429:331 0.016 
BMI (kg/m223.61 ± 3.16 24.66 ± 3.40 <0.001 
Fasting glucose (mmol/l) 5.37 ± 0.73 8.65 ± 2.81 <0.001 
A1C (%) 5.44 ± 0.56 7.90 ± 1.66 <0.001 
Triglycerides (mmol/l) 1.27 ± 0.73 1.89 ± 1.89 <0.001 
Total cholesterol (mmol/l) 5.05 ± 0.97 5.25 ± 1.31 0.0012 

Data are means ± SD.

TABLE 2

TCF7L2 sequence variants and association with type 2 diabetes

No.SNP nameGene position (kb)Gene regionMinor/major alleleMAF
OR (95% CI)Allelic P (adjusted P*)Permuted P
CaseControl
rs7079711 35.57 Intron 3 A/G 0.0266 0.0276 0.96 (0.60–1.54) 0.86 (0.92) 1.00 
rs4506565 45.82 Intron 3 T/A 0.0227 0.0273 0.83 (0.51–1.35) 0.42 (0.70) 0.99 
rs7903146 48.13 Intron 3 T/C 0.0234 0.0287 0.81 (0.50–1.31) 0.36 (0.70) 0.99 
rs11196192 72.07 Intron 3 G/T 0.0040 0.0020 2.00 (0.43–12.4) 0.31 (0.41) 0.99 
rs12243326 78.59 Intron 3 C/T 0.0050 0.0040 1.34 (0.41–4.71) 0.58 (0.76) 1.00 
rs7895340 91.31 Intron 4 A/G 0.0260 0.0208 1.25 (0.76–2.10) 0.35 (0.27) 0.99 
rs12255372 98.68 Intron 4 T/G 0.0060 0.0040 1.51 (0.48–5.16) 0.43 (0.53) 0.99 
rs11196213 111.34 Intron 4 T/C 0.0246 0.0174 1.43 (0.84–2.47) 0.16 (0.17) 0.89 
rs7919409 114.76 Intron 4 C/T 0.2540 0.2427 1.06 (0.90–1.26) 0.47 (0.71) 0.99 
10 rs11196219 130.42 Intron 4 A/G 0.2750 0.2444 1.17 (0.99–1.39) 0.055 (0.16) 0.51 
11 rs4918792 133.73 Intron 4 G/A 0.4926 0.4854 1.03 (0.89–1.19) 0.69 (0.72) 1.00 
12 rs10749127 139.13 Intron 4 T/C 0.2977 0.2779 1.10 (0.94–1.15) 0.22 (0.59) 0.96 
13 rs11196224 145.18 Intron 4 T/C 0.3081 0.3123 0.98 (0.84–1.15) 0.80 (0.32) 1.00 
14 rs7085532 149.24 Intron 4 A/G 0.4321 0.4234 1.04 (0.90–1.20) 0.63 (0.98) 1.00 
15 rs17130188 157.94 Intron 4 C/T 0.4721 0.4474 1.11 (0.96–1.28) 0.15 (0.10) 0.87 
16 rs10787475 182.25 Intron 4 C/T 0.2895 0.2633 1.14 (0.99–1.34) 0.10 (0.08) 0.78 
17 rs12775879 193.98 Intron 6 G/T 0.2430 0.2063 1.23 (1.04–1.49) 0.016 (0.023) 0.19 
18 rs290489 196.86 Intron 7 A/G 0.3243 0.3114 1.06 (0.91–1.24) 0.44 (0.46) 0.99 
19 rs290487 199.51 Intron 7 C/T 0.4178 0.3632 1.26 (1.09–1.47) 0.0021 (0.0035) 0.030 
20 rs290481 213.61 Intron 13 G/A 0.4178 0.3773 1.19 (1.02–1.38) 0.021 (0.024) 0.27 
No.SNP nameGene position (kb)Gene regionMinor/major alleleMAF
OR (95% CI)Allelic P (adjusted P*)Permuted P
CaseControl
rs7079711 35.57 Intron 3 A/G 0.0266 0.0276 0.96 (0.60–1.54) 0.86 (0.92) 1.00 
rs4506565 45.82 Intron 3 T/A 0.0227 0.0273 0.83 (0.51–1.35) 0.42 (0.70) 0.99 
rs7903146 48.13 Intron 3 T/C 0.0234 0.0287 0.81 (0.50–1.31) 0.36 (0.70) 0.99 
rs11196192 72.07 Intron 3 G/T 0.0040 0.0020 2.00 (0.43–12.4) 0.31 (0.41) 0.99 
rs12243326 78.59 Intron 3 C/T 0.0050 0.0040 1.34 (0.41–4.71) 0.58 (0.76) 1.00 
rs7895340 91.31 Intron 4 A/G 0.0260 0.0208 1.25 (0.76–2.10) 0.35 (0.27) 0.99 
rs12255372 98.68 Intron 4 T/G 0.0060 0.0040 1.51 (0.48–5.16) 0.43 (0.53) 0.99 
rs11196213 111.34 Intron 4 T/C 0.0246 0.0174 1.43 (0.84–2.47) 0.16 (0.17) 0.89 
rs7919409 114.76 Intron 4 C/T 0.2540 0.2427 1.06 (0.90–1.26) 0.47 (0.71) 0.99 
10 rs11196219 130.42 Intron 4 A/G 0.2750 0.2444 1.17 (0.99–1.39) 0.055 (0.16) 0.51 
11 rs4918792 133.73 Intron 4 G/A 0.4926 0.4854 1.03 (0.89–1.19) 0.69 (0.72) 1.00 
12 rs10749127 139.13 Intron 4 T/C 0.2977 0.2779 1.10 (0.94–1.15) 0.22 (0.59) 0.96 
13 rs11196224 145.18 Intron 4 T/C 0.3081 0.3123 0.98 (0.84–1.15) 0.80 (0.32) 1.00 
14 rs7085532 149.24 Intron 4 A/G 0.4321 0.4234 1.04 (0.90–1.20) 0.63 (0.98) 1.00 
15 rs17130188 157.94 Intron 4 C/T 0.4721 0.4474 1.11 (0.96–1.28) 0.15 (0.10) 0.87 
16 rs10787475 182.25 Intron 4 C/T 0.2895 0.2633 1.14 (0.99–1.34) 0.10 (0.08) 0.78 
17 rs12775879 193.98 Intron 6 G/T 0.2430 0.2063 1.23 (1.04–1.49) 0.016 (0.023) 0.19 
18 rs290489 196.86 Intron 7 A/G 0.3243 0.3114 1.06 (0.91–1.24) 0.44 (0.46) 0.99 
19 rs290487 199.51 Intron 7 C/T 0.4178 0.3632 1.26 (1.09–1.47) 0.0021 (0.0035) 0.030 
20 rs290481 213.61 Intron 13 G/A 0.4178 0.3773 1.19 (1.02–1.38) 0.021 (0.024) 0.27 
*

Adjusted for age, sex, and BMI.

Permutation 10,000 times. MAF, minor allele frequency.

TABLE 3

Standardized pairwise LD coefficients D′ (below diagonal of empty cells) and r2 (above diagonal) of polymorphic sites at the TCF7L2 gene locus

SNP no.r2
SNP1SNP2SNP3SNP4SNP5SNP6SNP7SNP8SNP9SNP10SNP11SNP12SNP13SNP14SNP15SNP16SNP17SNP18SNP19SNP20
D′↓ SNP1 — 0.55 0.53 0.061 0.017 0.004 0.005 0.005 0.007 0.002 0.001 0.011 0.002 0.001 0.001 0.002 
 SNP2 0.78 — 0.97 0.12 0.17 0.10 0.16 0.047 0.002 0.004 0.007 0.003 0.008 0.004 0.005 0.013 0.004 
 SNP3 0.74 1 — 0.11 0.18 0.11 0.19 0.05 0.001 0.004 0.005 0.003 0.008 0.004 0.006 0.012 0.004 0.001 
 SNP4 1 1 1 — 0.64 0.13 0.60 0.14 0.001 0.001 0.001 0.001 0.002 0.001 0.002 0.001 0.003 0.002 
 SNP5 1 1 1 1 — 0.18 0.93 0.22 0.002 0.002 0.001 0.001 0.003 0.002 
 SNP6 0.27 0.34 0.34 1 1 — 0.17 0.69 0.001 0.001 0.006 0.001 0.001 0.003 0.001 0.002 0.001 0.002 
 SNP7 1 0.93 1 1 1 0.93 — 0.20 0.002 0.001 0.001 0.001 0.001 0.002 0.001 
 SNP8 0.15 0.24 0.25 1 1 0.90 0.93 — 0.007 0.007 0.012 0.002 0.003 0.006 0.003 0.002 0.002 
 SNP9 0.21 0.44 0.40 0.99 1 0.39 0.99 1 — 0.001 0.002 0.003 0.015 0.003 0.014 0.001 0.001 0.017 0.009 
 SNP10 0.22 0.24 0.22 1 0.077 0.37 0.19 0.17  — 0.36 0.45 0.21 0.37 0.12 0.001 0.007 0.002 0.003 
 SNP11 0.40 0.51 0.43 0.68 0.61 0.49 0.47 0.54 0.068 1 — 0.20 0.23 0.47 0.18 0.018 0.002 0.03 0.001 
 SNP12 0.27 0.20 0.20 1 0.25 0.36 0.15 0.15 0.079 0.73 0.72 — 0.46 0.41 0.15 0.003 0.006 0.01 0.007 
 SNP13 0.34 0.38 0.37 0.39 0.054 0.29 0.12 0.30 0.15 0.52 0.70 0.71 — 0.57 0.29 0.029 0.015 0.004 0.036 0.037 
 SNP14 0.25 0.35 0.33 1 0.11 0.025 0.24 0.32 0.89 0.78 0.88 0.97 — 0.38 0.001 0.002 0.011 0.005 0.004 
 SNP15 0.15 0.48 0.49 0.61 0.48 0.12 0.47 0.13 0.12 0.62 0.47 0.66 0.87 0.77 — 0.009 0.055 0.026 0.016 
 SNP16 0.39 0.44 0.41 0.45 0.16 0.20 0.20 0.25 0.19 0.1 0.21 0.008 0.41 0.039 0.14 — 0.52 0.41 0.13 0.12 
 SNP17 0.44 0.73 0.73 0.03 1 0.40 0.74 0.95 0.03 0.009 0.074 0.066 0.34 0.11 0.40 0.82 — 0.38 0.11 0.11 
 SNP18 0.22 0.16 0.11 0.39 0.18 0.20 0.21 0.24 0.099 0.094 0.25 0.085 0.14 0.13 0.004 0.70 0.78 — 0.09 0.10 
 SNP19 0.26 0.14 0.14 0.79 0.67 0.18 0.54 0.21 0.026 0.099 0.033 0.19 0.35 0.098 0.19 0.46 0.50 0.35 — 0.78 
 SNP20 0.311 0.17 0.17 0.60 0.52 0.23 0.41 0.27 0.18 0.11 0.016 0.16 0.35 0.092 0.14 0.46 0.49 0.38 0.90 — 
SNP no.r2
SNP1SNP2SNP3SNP4SNP5SNP6SNP7SNP8SNP9SNP10SNP11SNP12SNP13SNP14SNP15SNP16SNP17SNP18SNP19SNP20
D′↓ SNP1 — 0.55 0.53 0.061 0.017 0.004 0.005 0.005 0.007 0.002 0.001 0.011 0.002 0.001 0.001 0.002 
 SNP2 0.78 — 0.97 0.12 0.17 0.10 0.16 0.047 0.002 0.004 0.007 0.003 0.008 0.004 0.005 0.013 0.004 
 SNP3 0.74 1 — 0.11 0.18 0.11 0.19 0.05 0.001 0.004 0.005 0.003 0.008 0.004 0.006 0.012 0.004 0.001 
 SNP4 1 1 1 — 0.64 0.13 0.60 0.14 0.001 0.001 0.001 0.001 0.002 0.001 0.002 0.001 0.003 0.002 
 SNP5 1 1 1 1 — 0.18 0.93 0.22 0.002 0.002 0.001 0.001 0.003 0.002 
 SNP6 0.27 0.34 0.34 1 1 — 0.17 0.69 0.001 0.001 0.006 0.001 0.001 0.003 0.001 0.002 0.001 0.002 
 SNP7 1 0.93 1 1 1 0.93 — 0.20 0.002 0.001 0.001 0.001 0.001 0.002 0.001 
 SNP8 0.15 0.24 0.25 1 1 0.90 0.93 — 0.007 0.007 0.012 0.002 0.003 0.006 0.003 0.002 0.002 
 SNP9 0.21 0.44 0.40 0.99 1 0.39 0.99 1 — 0.001 0.002 0.003 0.015 0.003 0.014 0.001 0.001 0.017 0.009 
 SNP10 0.22 0.24 0.22 1 0.077 0.37 0.19 0.17  — 0.36 0.45 0.21 0.37 0.12 0.001 0.007 0.002 0.003 
 SNP11 0.40 0.51 0.43 0.68 0.61 0.49 0.47 0.54 0.068 1 — 0.20 0.23 0.47 0.18 0.018 0.002 0.03 0.001 
 SNP12 0.27 0.20 0.20 1 0.25 0.36 0.15 0.15 0.079 0.73 0.72 — 0.46 0.41 0.15 0.003 0.006 0.01 0.007 
 SNP13 0.34 0.38 0.37 0.39 0.054 0.29 0.12 0.30 0.15 0.52 0.70 0.71 — 0.57 0.29 0.029 0.015 0.004 0.036 0.037 
 SNP14 0.25 0.35 0.33 1 0.11 0.025 0.24 0.32 0.89 0.78 0.88 0.97 — 0.38 0.001 0.002 0.011 0.005 0.004 
 SNP15 0.15 0.48 0.49 0.61 0.48 0.12 0.47 0.13 0.12 0.62 0.47 0.66 0.87 0.77 — 0.009 0.055 0.026 0.016 
 SNP16 0.39 0.44 0.41 0.45 0.16 0.20 0.20 0.25 0.19 0.1 0.21 0.008 0.41 0.039 0.14 — 0.52 0.41 0.13 0.12 
 SNP17 0.44 0.73 0.73 0.03 1 0.40 0.74 0.95 0.03 0.009 0.074 0.066 0.34 0.11 0.40 0.82 — 0.38 0.11 0.11 
 SNP18 0.22 0.16 0.11 0.39 0.18 0.20 0.21 0.24 0.099 0.094 0.25 0.085 0.14 0.13 0.004 0.70 0.78 — 0.09 0.10 
 SNP19 0.26 0.14 0.14 0.79 0.67 0.18 0.54 0.21 0.026 0.099 0.033 0.19 0.35 0.098 0.19 0.46 0.50 0.35 — 0.78 
 SNP20 0.311 0.17 0.17 0.60 0.52 0.23 0.41 0.27 0.18 0.11 0.016 0.16 0.35 0.092 0.14 0.46 0.49 0.38 0.90 — 

*Pairwise LD coefficients D′ >0.8 are shown in bold.

TABLE 4

Association analysis of TCF7L2 haplotypes with type 2 diabetes

HaplotypesFrequencies
OR (95% CI)Nominal P (adjusted P*)Permuted PGlobal P (adjusted P*)
CaseControl
Block 1      0.47 (0.58) 
    A-C-T-T-G-G 0.947 0.959 1.03 (0.71–1.51) 0.85 (0.55) 0.99  
    T-T-T-T-G-G 0.014 0.019 0.68 (0.37–1.26) 0.20 (0.62) 0.39  
    A-C-T-T-A-G 0.017 0.012 1.26 (0.67–2.40) 0.39 (0.20) 0.70  
Block 2      0.26 (0.36) 
    C-T 0.726 0.745 0.91 (0 0.77–1.07) 0.25 (0.43) 0.46  
    C-C 0.256 0.244 1.07 (0.90–1.26) 0.47 (0.70) 0.73  
    T-T 0.024 0.017 1.44 (0.84–2.49) 0.17 (0.17) 0.35  
Block 3      0.23 (0.32) 
    G-A 0.506 0518 0.97 (0 0.84–1.12) 0.66 (0.73) 0.90  
    A-G 0.274 0246 1.17 (0 0.99–1.38) 0.061 (0.17) 0.14  
    G-G 0.219 0.242 0.88 (0 0.74–1.05) 0.15 (0.31) 0.33  
Block 4      0.12 (0.11) 
    C-C-G 0.543 0.554 0.97 (0 0.84–1.12) 0.68 (0.87) 0.99  
    T-T-A 0.230 0.233 0.99 (0 0.84–1.18) 0.93 (0.44) 1.00  
    C-C-A 0.082 0.089 0.92 (0.71–1.20) 0.52 (0.62) 0.98  
    C-T-A 0.075 0.077 0.98 (0.74–1.29) 0.88 (0.82) 1.00  
    T-C-A 0.047 0.029 1.62 (1.09–2.44) 0.011 (0.011) 0.04  
    T-C-G 0.021 0.019 1.11 (0.64–1.93) 0.70 (0.51) 0.99  
Block 5      0.16 (0.20) 
    T-T 0.679 0.714 0.87 (0.74–1.01) 0.072 (0.05) 0.20  
    C-G 0.212 0.181 1.22 (1.01–1.46) 0.034 (0.06) 0.10  
    C-T 0078 0.083 0.94 (0 0.72–1.24) 0.65 (0.97) 0.95  
    T-G 0.031 0.027 1.18 (0.75–1.86) 0.50 (0.39) 0.87  
Block 6      0.012 (0.025) 
    T-A 0.555 0.601 0.83 (0 0.71–0.96) 0.011 (0.0092) 0.033  
    C-G 0.390 0.340 1.24 (1.06–1.44) 0.0046 (0.012) 0.014  
    T-G 0.027 0.036 0.74 (0.48–1.14) 0.15 (0.42) 0.42  
    C-A 0.027 0.022 1.25 (0.77–2.06) 0.34 (0.21) 0.72  
HaplotypesFrequencies
OR (95% CI)Nominal P (adjusted P*)Permuted PGlobal P (adjusted P*)
CaseControl
Block 1      0.47 (0.58) 
    A-C-T-T-G-G 0.947 0.959 1.03 (0.71–1.51) 0.85 (0.55) 0.99  
    T-T-T-T-G-G 0.014 0.019 0.68 (0.37–1.26) 0.20 (0.62) 0.39  
    A-C-T-T-A-G 0.017 0.012 1.26 (0.67–2.40) 0.39 (0.20) 0.70  
Block 2      0.26 (0.36) 
    C-T 0.726 0.745 0.91 (0 0.77–1.07) 0.25 (0.43) 0.46  
    C-C 0.256 0.244 1.07 (0.90–1.26) 0.47 (0.70) 0.73  
    T-T 0.024 0.017 1.44 (0.84–2.49) 0.17 (0.17) 0.35  
Block 3      0.23 (0.32) 
    G-A 0.506 0518 0.97 (0 0.84–1.12) 0.66 (0.73) 0.90  
    A-G 0.274 0246 1.17 (0 0.99–1.38) 0.061 (0.17) 0.14  
    G-G 0.219 0.242 0.88 (0 0.74–1.05) 0.15 (0.31) 0.33  
Block 4      0.12 (0.11) 
    C-C-G 0.543 0.554 0.97 (0 0.84–1.12) 0.68 (0.87) 0.99  
    T-T-A 0.230 0.233 0.99 (0 0.84–1.18) 0.93 (0.44) 1.00  
    C-C-A 0.082 0.089 0.92 (0.71–1.20) 0.52 (0.62) 0.98  
    C-T-A 0.075 0.077 0.98 (0.74–1.29) 0.88 (0.82) 1.00  
    T-C-A 0.047 0.029 1.62 (1.09–2.44) 0.011 (0.011) 0.04  
    T-C-G 0.021 0.019 1.11 (0.64–1.93) 0.70 (0.51) 0.99  
Block 5      0.16 (0.20) 
    T-T 0.679 0.714 0.87 (0.74–1.01) 0.072 (0.05) 0.20  
    C-G 0.212 0.181 1.22 (1.01–1.46) 0.034 (0.06) 0.10  
    C-T 0078 0.083 0.94 (0 0.72–1.24) 0.65 (0.97) 0.95  
    T-G 0.031 0.027 1.18 (0.75–1.86) 0.50 (0.39) 0.87  
Block 6      0.012 (0.025) 
    T-A 0.555 0.601 0.83 (0 0.71–0.96) 0.011 (0.0092) 0.033  
    C-G 0.390 0.340 1.24 (1.06–1.44) 0.0046 (0.012) 0.014  
    T-G 0.027 0.036 0.74 (0.48–1.14) 0.15 (0.42) 0.42  
    C-A 0.027 0.022 1.25 (0.77–2.06) 0.34 (0.21) 0.72  
*

Adjusted for age, sex, and BMI.

Permutation 10,000 times.

TABLE 5

Sliding window association analysis of global P value* for haplotypes composed of adjacent 2–10 SNPs

No.SNP2 SNPs3 SNPs4 SNPs5 SNPs6 SNPs7 SNPs8 SNPs9 SNPs10 SNPs
rs7079711 0.20 0.26 0.25 0.33 0.48 0.47 0.40 0.47 0.11 
rs4506565 0.69 0.28 0.40 0.46 0.47 0.33 0.40 0.078 0.16 
rs7903146 0.28 0.39 0.47 0.38 0.25 0.33 0.087 0.16 0.22 
rs11196192 0.50 0.66 0.54 0.44 0.55 0.099 0.10 0.18 0.098 
rs12243326 0.67 0.54 0.44 0.54 0.12 0.11 0.18 0.088 0.049 
rs7895340 0.53 0.45 0.54 0.12 0.068 0.17 0.087 0.050 0.027 
rs12255372 0.31 0.39 0.076 0.068 0.16 0083 0.049 0.027 0.11 
rs11196213 0.26 0.083 0.11 0.16 0.070 0.034 0.026 0.089 0.023 
rs7919409 0.057 0.10 0.20 0.07 0.30 0.038 0.15 0.028 0.057 
10 rs11196219 0.12 0.48 0.33 0.30 0.096 0.11 0.062 0.075 0.003 
11 rs4918792 0.78 0.44 0.35 0.096 0.46 0.13 0.098 0.017 0.017 
12 rs10749127 0.14 0.12 0.25 0.46 0.22 0.15 0.026 0.030  
13 rs11196224 0.40 0.31 0.51 0.23 0.086 0.017 0.034   
14 rs7085532 0.13 0.12 0.20 0.086 0.004 0.015    
15 rs17130188 0.077 0.15 0.10 0.004 0.045     
16 rs10787475 0.16 0.18 0.017 0.045      
17 rs12775879 0.085 0.002 0.024       
18 rs290489 0.022 0.15        
19 rs290487 0.012         
20 rs290481          
No.SNP2 SNPs3 SNPs4 SNPs5 SNPs6 SNPs7 SNPs8 SNPs9 SNPs10 SNPs
rs7079711 0.20 0.26 0.25 0.33 0.48 0.47 0.40 0.47 0.11 
rs4506565 0.69 0.28 0.40 0.46 0.47 0.33 0.40 0.078 0.16 
rs7903146 0.28 0.39 0.47 0.38 0.25 0.33 0.087 0.16 0.22 
rs11196192 0.50 0.66 0.54 0.44 0.55 0.099 0.10 0.18 0.098 
rs12243326 0.67 0.54 0.44 0.54 0.12 0.11 0.18 0.088 0.049 
rs7895340 0.53 0.45 0.54 0.12 0.068 0.17 0.087 0.050 0.027 
rs12255372 0.31 0.39 0.076 0.068 0.16 0083 0.049 0.027 0.11 
rs11196213 0.26 0.083 0.11 0.16 0.070 0.034 0.026 0.089 0.023 
rs7919409 0.057 0.10 0.20 0.07 0.30 0.038 0.15 0.028 0.057 
10 rs11196219 0.12 0.48 0.33 0.30 0.096 0.11 0.062 0.075 0.003 
11 rs4918792 0.78 0.44 0.35 0.096 0.46 0.13 0.098 0.017 0.017 
12 rs10749127 0.14 0.12 0.25 0.46 0.22 0.15 0.026 0.030  
13 rs11196224 0.40 0.31 0.51 0.23 0.086 0.017 0.034   
14 rs7085532 0.13 0.12 0.20 0.086 0.004 0.015    
15 rs17130188 0.077 0.15 0.10 0.004 0.045     
16 rs10787475 0.16 0.18 0.017 0.045      
17 rs12775879 0.085 0.002 0.024       
18 rs290489 0.022 0.15        
19 rs290487 0.012         
20 rs290481          
*

Permutation 10,000 times.

Published ahead of print at http://diabetes.diabetesjournals.org on 19 June 2007. DOI: 10.2337/db07-0421.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

This research project was supported by grants from the National Science Council (NSC-93-B-002-005 and NSC-94-3112-B-002-019) of Taiwan.

We thank all of the patients for their participation in this study.

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