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Neuropsychiatric Disease and Treatment logoLink to Neuropsychiatric Disease and Treatment
. 2015 Jun 2;11:1381–1393. doi: 10.2147/NDT.S84736

Association analysis of the Cadherin13 gene with schizophrenia in the Japanese population

Ikuo Otsuka 1, Yuichiro Watanabe 2, Akitoyo Hishimoto 1,, Shuken Boku 1, Kentaro Mouri 1, Kyoichi Shiroiwa 1, Satoshi Okazaki 1, Ayako Nunokawa 2, Osamu Shirakawa 3, Toshiyuki Someya 2, Ichiro Sora 1
PMCID: PMC4461090  PMID: 26082635

Abstract

Background

Cadherin13 (CDH13) is a glycosylphosphatidylinositol-anchored cell adhesion molecule that plays a crucial role in morphogenesis and the maintenance of neuronal circuitry. CDH13 has been implicated in the susceptibility to a variety of psychiatric diseases. A recent genome-wide association study using Danish samples showed, for the first time, the involvement of a single nucleotide polymorphism (SNP) of CDH13 (intronic SNP rs8057927) in schizophrenia. Here, we investigated the association between other SNPs of CDH13 and schizophrenia and tried to replicate the association for the SNP of rs8057927, in the Japanese population.

Methods

Using TaqMan® SNP genotyping assays, five tag SNPs (rs12925602, rs7193788, rs736719, rs6565051, and rs7204454) in the promoter region of CDH13 were examined for their association with schizophrenia in two independent samples. The first sample comprised 665 patients and 760 controls, and the second sample comprised 677 patients and 667 controls. One tag SNP for rs8057927 was also examined for the association with schizophrenia in the first sample set.

Results

A GACAG haplotype of the five SNPs in the promoter region of CDH13 was significantly associated with schizophrenia in the first sample set (P=0.016 and corrected P=0.098). A combined analysis of the GACAG haplotype with the second sample set enhanced the significance (P=0.0026 and corrected P=0.021). We found no association between rs8057927 and schizophrenia in the first sample set.

Conclusion

Our results suggest that CDH13 may contribute to the genetic risk of schizophrenia. Further replication on the association of CDH13 with schizophrenia and functional studies are required to confirm the current findings.

Keywords: CDH13, promoter region, haplotype, SNP

Introduction

Schizophrenia is a severe mental disorder that ranks among the world’s top ten causes of long-term disability, with a worldwide prevalence of approximately 1%. Although the causes of schizophrenia are still largely unknown, previous studies have suggested that the inheritability of schizophrenia is high and that there is a small but significant environmental effect associated with the susceptibility to schizophrenia.1,2

Recent genome-wide association study (GWASs) has shown that common variants of single nucleotide polymorphisms (SNPs) with relatively weak effects may be associated with schizophrenia.3 Meanwhile, it is well established that macroscopic abnormalities, such as volume reductions of the prefrontal cortex, hippocampus, and generalized brain, are associated with schizophrenia.4,5 In addition, significant alterations in neuron size, morphology, and synaptic connectivity have been reported.68 These past studies suggest that neural development and mature brain function-related genes may also be schizophrenia- associated genes.

Cadherins (CDHs) belong to a superfamily of cell adhesion molecules that regulate morphogenesis by mediating cell adhesion. In the nervous system, CDHs play crucial roles in neural tube regionalization, neuronal migration, gray matter differentiation, neural circuit formation, spine morphology, and synapse formation and remodeling.9,10 The finding that the gene locus of the CDH superfamily overlaps with potential regions underlying schizophrenia susceptibility implicate an association between CDHs and schizophrenia.11,12 For example, protocadherin12 (PCDH12) and CDH18 are candidate genes that have been indicated to confer an increased risk for schizophrenia.7,12

CDH13, also known as H-cadherin or T-cadherin, belongs to the CDH superfamily. In humans, CDH13 is located on chromosome 16q23 and contains 1,169.8 kbp. Although the classical extracellular CDH structure is conserved, CDH13 lacks transmembrane and cytoplasmic domains and is anchored to the cellular membrane through glycosylphosphatidylinositol.13 CDH13 has been implicated in the susceptibility to a variety of psychiatric diseases. A GWAS of attention deficit hyperactivity disorder (ADHD) identified CDH13 as one of the genes that is most highly associated with ADHD,14 and a meta-analysis of ADHD linkage scans indicated the only genome-wide significant region overlapped with CDH13.15 GWASs have also indicated the involvement of CDH13 in depression,16 autism,17,18 alcohol dependence,19 nicotine dependence,20 and methamphetamine dependence.21 Recently, a GWAS of Danish samples indicated that rs8057927 in the intron of CDH13 is associated with schizophrenia.22 Although it was the first report to show an involvement of CDH13 in schizophrenia, rs8057927 in the intron of CDH13 is not a variant of coding region or promoter region. Therefore, the functional significance of rs8057927 in the intron of CDH13 remains unclear. In addition, there is a possibility that other SNPs in the coding region and/or promoter region of CDH13 are associated with schizophrenia.

Our present study was designed to investigate the association between coding or regulatory SNPs of CDH13 and schizophrenia, and to replicate the association for the SNP rs8057927, in the Japanese population. Here, we focused on five tag SNPs from the linkage disequilibrium (LD) block in the promoter region of CDH13 because we found neither cis-acting SNPs nor nonsynonymous SNPs after consulting the databases: mRNA by SNP Browser (http://www.sph.umich.edu/csg/liang/asthma/)23 and Japanese SNP (JSNP) DATABASE (http://snp.ims.u-tokyo.ac.jp).24

Materials and methods

Subjects

The present study was approved by the Ethical Committee for Genetic Studies of Kobe University Graduate School of Medicine and the Ethics Committee of Genetics at Niigata University School of Medicine. Informed consent was obtained from all of the participants. All of the participants were of Japanese descent and were recruited in the Kobe city area (the first set) or the Niigata area (the second set) of Japan.

The first set of participants consisted of 665 unrelated schizophrenia patients, including 344 males (with mean age ± standard deviation [SD] of 53.3±14.0 years) and 321 females (53.5±15.2 years), and 760 unrelated healthy volunteers (359 males [53.1±18.9 years]; 401 females [54.9±18.3 years]). There were no significant differences in the sex (χ2=1.277, P=0.258) and age (t=0.792, df=1381, P=0.429) distributions between the schizophrenia and the control groups. The second set consisted of 677 unrelated schizophrenia patients (363 males [39.5±13.3 years]; 314 females [39.7±14.3 years]) and 667 unrelated healthy volunteers (341 males [36.7±9.5 years]; 326 females [40.0±11.8 years]). There were no significant differences in the sex (χ2=0.838, P=0.360) and age (t=1.897, df=1,336, P=0.058) distributions between the schizophrenia and the control groups.

The psychiatric assessment of each participant was conducted as previously described.25,26 In brief, the patients were diagnosed by at least two psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition DSM-IV27 criteria for schizophrenia, based on unstructured interviews and reviews of their medical records at each hospital. None of the patients had a history of substance abuse (excluding nicotine dependence) or organic mental disorders. All of the control subjects were interviewed and screened for psychiatric disorders, based on an unstructured interview by a psychiatrist. None of the control subjects had any present, past, or family (up to first-degree relatives) histories of psychiatric disorders or substance abuse (excluding nicotine dependence).

SNP selection and genotyping

We first identified one LD block in the promoter region of CDH13 from the HapMap database (release#27, www.hapmap.org) (population: Japanese Tokyo, minor allele frequencies [MAFs] of more than 0.05), using the Haploview software program version 4.2 (http://www.broad.mit.edu/mpg/haploview/).28 We then selected five tagging SNPs (rs12925602, rs7193788, rs736719, rs6565051, and rs7204454) from the LD block, with the criterion of an r2 threshold greater than 0.8 in “pair-wise tagging only” mode, using the “Tagger” program in the Haploview software, and we used these SNPs in the following association analysis.

For genotype determination, peripheral blood was drawn from all of the participants, and the leukocyte DNA was extracted. We used TaqMan® assays (Applied Biosystems®; Life Technologies Corp, Carlsbad, CA, USA) for genotyping all of the SNPs. We selected predesigned TaqMan SNP genotyping assays from the Life Technologies database for all five SNPs that were examined. The genotyping was performed according to the protocol recommended by the manufacturer.

Although we also tried to investigate the intronic SNP rs8057927 previously reported for its involvement in schizophrenia in the Danish population,22 TaqMan assays for genotyping rs8057927 were not available. Therefore, we chose rs8049308 as the substitute for rs8057927 because rs8049308 is a tag SNP for rs8057927 (these two SNPs have strong LD to each other [D’=1.0, r2=0.946]) (Figure S1).

Statistics

We used the Haploview software to determine the Hardy–Weinberg equilibrium (HWE), LD, allelic/haplotype frequencies, and genetic association, between the schizophrenia and control groups. The allele-based association was tested using the χ2 test. If necessary, permutation tests based on 10,000 replications were performed to calculate the corrected P-values of the allelic or haplotypic analyses for multiple testing by the Haploview software. The genotype-based association was evaluated using the Cochran–Armitage trend test. The haplotype-based association was examined using the χ2 test and the Fisher’s exact test, using R version 2.15.0 (The R Foundation for Statistical Computing, Vienna, Austria). The power analysis was performed using the Power and Sample Size Calculations Version3.1.2 program with an α of 0.05.29 Statistical significance was defined at P<0.05.

Results

rs12925602, rs7193788, rs736719, rs6565051, and rs7204454

The distributions of all of the SNPs did not deviate from the HWE in each set. Using the solid spine method, five selected SNPs (rs12925602, rs7193788, rs736719, rs6565051, and rs7204454) in LD with each other formed one haplotype block (D’=0.90–0.99) (Figure 1). The allelic frequencies of the tag SNPs in the promoter region of CDH13 are shown in Table 1. Neither the genotype distribution nor the allelic frequency of these five SNPs was significantly associated with schizophrenia in either set. Even when the data of the first and second set were combined, no significant difference was found.

Figure 1.

Figure 1

Cadherin13 (CDH13) tag single nucleotide polymorphisms (SNPs) and the genetic structure of CDH13. The genetic structure of CDH13 is shown at the top. The gene consists of fourteen exons spanning 1,169.8 kbp. Linkage disequilibrium (D’ values) of five SNPs studied here are shown.

Table 1.

Association between CDH13 SNPs with schizophrenia

Sample SNP ID positiona Phen Genotype distribution
Minor allele
P-value
Power OR (95% CI)
MM Mm mm MAF Allele HWE Genotypeb Allelec
rs12925602, rs7193788, rs736719, rs6565051, and rs7204454
First set
SCZ, n=665
CON, n=760
rs12925602 SCZ 418 198 29 0.198 A 0.428 0.708 0.696 0.059 0.97 (0.80–1.16)
81213402 CON 471 255 26 0.204 0.281 (0.991)
rs7193788 SCZ 203 304 139 0.449 G 0.269 0.327 0.369 0.099 1.08 (0.93–1.25)
81213661 CON 234 384 132 0.432 0.241 (0.815)
rs736719 SCZ 515 121 5 0.102 T 0.643 0.130 0.138 0.188 0.83 (0.66–1.06)
81214146 CON 575 161 9 0.12 0.698 (0.436)
rs6565051 SCZ 275 275 96 0.363 G 0.062 0.905 0.946 0.050 0.99 (0.85–1.16)
81216229 CON 310 337 105 0.364 0.479 (1.000)
rs7204454 SCZ 268 284 93 0.364 C 0.271 0.473 0.454 0.085 1.06 (0.91–1.24)
81216695 CON 315 342 92 0.350 0.982 (0.892)
Second set
SCZ, n=677
CON, n=667
rs12925602 SCZ 433 215 27 0.199 A 1.000 0.3505 0.3476 0.100 1.10 (0.91–1.33)
81213402 CON 444 196 25 0.185 0.629 (0.786)
rs7193788 SCZ 220 329 128 0.432 G 0.845 0.2825 0.6671 0.060 1.09 (0.94–1.27)
81213661 CON 244 316 123 0.424 0.575 (0.985)
rs736719 SCZ 522 140 15 0.126 T 0.180 0.1495 0.1455 0.176 1.19 (0.94–1.51)
81214146 CON 528 131 6 0.108 0.669 (0.445)
rs6565051 SCZ 265 308 101 0.378 G 0.497 0.3395 0.3389 0.104 0.93 (0.79–1.08)
81216229 CON 237 324 100 0.396 0.600 (0.774)
rs7204454 SCZ 289 296 83 0.346 C 0.639 0.7327 0.7267 0.056 0.97 (0.83–1.14)
81216695 CON 288 279 93 0.352 0.068 (0.993)
Combined
SCZ, n=1,342
CON, n=1,427
rs12925602 SCZ 851 413 56 0.199 A 0.555 0.729 0.738 0.058 1.02 (0.90–1.17)
81213402 CON 915 451 51 0.195 0.690 (0.994)
rs7193788 SCZ 423 633 267 0.440 G 0.334 0.161 0.366 0.098 1.08 (0.97–1.20)
81213661 CON 478 700 255 0.428 0.670 (0.811)
rs736719 SCZ 1,037 261 20 0.114 T 0.511 0.999 0.992 0.050 1.00 (0.85–1.18)
81214146 CON 1,103 292 15 0.114 0.462 (1.000)
rs6565051 SCZ 540 583 197 0.371 G 0.067 0.503 0.520 0.072 0.96 (0.86–1.07)
81216229 CON 547 661 205 0.379 0.909 (0.931)
rs7204454 SCZ 557 580 176 0.355 C 0.243 0.806 0.788 0.056 1.01 (0.91–1.13)
81216695 CON 603 621 185 0.351 0.245 (0.997)
rs8049308 (as the substitute for rs8057927)
First set
SCZ, n=665
CON, n=760
rs8049308 SCZ 309 267 69 0.314 C 0.357 0.634 0.630 0.066 1.04 (0.89–1.22)
81252503 CON 363 313 72 0.305 0.753 (0.658)

Notes:

a

SNP ID number and positions are available at http://hapmap.ncbi.nlm.nih.gov/.

b

Genotypic P-values were tested with the Cochran-Armitage test for trend.

c

Allelic P-values were tested with χ2; corrections for multiple comparisons are in parentheses (for 10,000 permutations).

Abbreviations: CDH13, cadherin13; CI, confidence interval; CON, control; HWE, Hardy–Weinberg equilibrium; M, major allele; m, minor allele; MAF, minor allele frequency; OR, odds ratio; Phen, phenotype; SCZ, schizophrenia; SNP, single nucleotide polymorphism; SNP ID, single nucleotide polymorphism identification.

Detailed haplotype frequencies between the schizophrenia and control groups are shown in Table 2. Each haplotype analysis of the LD block revealed a nominal significant distribution of the GACAG haplotype between the schizophrenia and control groups in the first set (P=0.016). Although no significant difference was found in the second set, the distributions of each haplotype between the schizophrenia and control groups were similar to those in the first sample. When the data of the first and second set were combined, the significance was enhanced for the GACAG haplotype (P=0.0026). The GACAG haplotype was also significantly associated with schizophrenia even after correction for multiple testing (corrected P=0.021). The frequency of the GACAG haplotype in the schizophrenia group (0.006) was lower than that in the control group (0.014).

Table 2.

Association between haplotypes in the promoter region of CDH13 and schizophrenia

Sample Haplotype Haplotype frequency
χ2 P-value* Global P-values OR (95% CI)
Schizophrenia Control
rs12925602–rs7204454
First set
SCZ, n=665
CON, n=760
GACGG 0.343 0.336 0.162 0.688 (0.999) χ2=9.87, df=6
P-value =0.130
(P-value =0.125 by Fisher’s exact test)
1.03 (0.88–1.21)
GGCAC 0.261 0.232 3.072 0.080 (0.492) 1.17 (0.98–1.39)
AACAG 0.191 0.201 0.441 0.507 (0.997) 0.94 (0.78–1.13)
GGTAC 0.097 0.107 0.863 0.353 (0.979) 0.89 (0.70–1.14)
GGCAG 0.071 0.066 0.262 0.609 (0.999) 1.08 (0.81–1.45)
GGCGG 0.011 0.011 0.019 0.890 (1.000) 0.95 (0.47–1.94)
GACAG 0.009 0.020 5.842 0.016 (0.098)** 0.44 (0.21–0.87)**
Second set
SCZ, n=677
CON, n=667
GACGG 0.362 0.384 1.389 0.239 (0.881) χ2=7.26, df=6
P-value =0.298
(P-value =0.303 by Fisher’s exact test)
0.91 (0.78–1.06)
GGCAC 0.224 0.242 1.208 0.272 (0.917) 0.90 (0.76–1.08)
AACAG 0.200 0.185 0.911 0.340 (0.967) 1.10 (0.91–1.33)
GGTAC 0.120 0.107 1.113 0.292 (0.938) 1.14 (0.90–1.44)
GGCAG 0.070 0.061 0.773 0.380 (0.975) 1.15 (0.85–1.56)
GGCGG 0.014 0.012 0.341 0.559 (0.996) 1.22 (0.62–2.40)
GACAG 0.003 0.008 2.612 0.106 (0.575) 0.40 (0.13–1.26)
Combined
SCZ, n=1,342
CON, n=1,427
GACGG 0.352 0.359 0.229 0.632 (1.000) χ2=9.90, df=6
P-value =0.129
(P-value =0.122 by Fisher’s exact test)
0.97 (0.87–1.09)
GGCAC 0.242 0.237 0.176 0.675 (1.000) 1.03 (0.91–1.16)
AACAG 0.196 0.194 0.033 0.855 (1.000) 1.01 (0.89–1.16)
GGTAC 0.109 0.107 0.033 0.8559 (1.000) 1.02 (0.86–1.21)
GGCAG 0.071 0.064 0.953 0.3289 (0.995) 1.11 (0.90–1.37)
GGCGG 0.012 0.012 0.040 0.8418 (1.000) 1.05 (0.65–1.71)
GACAG 0.006 0.014 9.100 0.0026 (0.021)** 0.41 (0.23–0.75)**

Notes:

*

This column shows the nominal P-values and the corrected P-values for multiple testing (for 10,000 permutations).

**

Significant differences between the schizophrenia and control groups.

Abbreviations: CDH13, cadherin13; CI, confidence interval; CON, control; OR, odds ratio; SCZ, schizophrenia.

rs8049308 (as the substitute for rs8057927)

The allelic frequency of rs8049308 in the first set is shown in Table 1. The distributions of this SNP did not differ from the HWE in the first set. Neither the genotype distribution nor the allelic frequency of rs8049308 was significantly associated with schizophrenia.

Discussion

Here we showed that SNPs in the promoter region of CDH13 are associated with schizophrenia in the Japanese population. Although CDH13 has been implicated in the susceptibility to a variety of psychiatric diseases,1421 there has been no report regarding the association between CDH13 and schizophrenia except for a recent GWAS of a Danish population sample.22 In addition, this recent GWAS found the association between schizophrenia and an intron of CDH13 but not the promoter region. Therefore, our present study was the first to investigate the association of the promoter region of CDH13 with schizophrenia in the Japanese population.

In the human adult brain, CDH13 expression is detected in the prefrontal cortex, hippocampus, hypothalamus, amygdala, and substantia nigra (http://www.gtexportal.org/),30 which overlap with regions linked to a variety of psychiatric diseases including schizophrenia.13,31 CDH13 might have a role as an axonal pathfinder during neurodevelopment and play a role in the maintenance of inhibitory and excitatory synapses after maturation of neuronal circuits.32 In addition, altered excitation/inhibition balance caused by the dysfunction or loss of inhibitory interneurons has been associated with the pathophysiology of schizophrenia.33,34 These past studies suggest the involvement of CDH13 in the pathophysiology of schizophrenia. Therefore, the attention to CDH13 in this manuscript may be reasonable, and further studies are needed to confirm the role of CDH13 in the pathophysiology of schizophrenia.

Our results showed significant differences in the distribution of the GACAG haplotype in the promoter region of CDH13 between schizophrenia patients and healthy controls. Based on the frequency of the haplotype, the GACAG haplotype may have a protective role. None of the SNPs in the promoter region of CDH13 evaluated in this study revealed a statistically significant association of the CDH13 locus with schizophrenia. One reason is that the sample size was too small to detect an association of CDH13 SNPs with schizophrenia. Based on the observed allele frequencies of rs12925602, rs7193788, rs736719, rs6565051, and rs7204454, the current combined samples provide powers of 0.058, 0.098, 0.050, 0.072, and 0.056, respectively, to detect nominally significant results. A recent mega analysis by the Psychiatric Genomics Consortium did not identify any association between CDH13 SNPs and schizophrenia.35 Although their analysis included 492 schizophrenia and 427 control Japanese samples, most of their samples were from European populations. Genetic association of CDH13 SNPs with schizophrenia may be variable in different ethnic populations. Therefore, further studies with larger samples in the Japanese and other Asian populations are needed.

As shown in Table S1, the genotype and allele frequencies of the SNPs (rs12925602, rs7193788, rs736719, rs6565051, and rs7204454) are different among populations. The distributions of haplotypes of the five SNPs (rs12925602–rs7204454) are also different (Table S2). The frequency of the GACAG haplotype is rare among Asian and Caucasian populations, while the frequency of this haplotype in Africans is 0.024–0.126.28 Therefore, replication studies, especially in other Asian populations and African populations, are required to confirm the findings of our present study.

Although we also conducted a case-control study for the intronic SNP rs8049308 as the substitute for rs8057927, which previously indicated an association with schizophrenia in the Danish samples,22 neither the genotype distribution nor the allelic frequency of rs8049308 was significantly associated with schizophrenia in the first set. As shown in Table S1, the genotype and allele frequencies of rs8057927 and rs8049308 in the Caucasian populations are significantly lower compared with the Asian populations. These differences may explain why the result identified in the Danish samples was not replicated in our Japanese samples.

A limitation in the present study should be considered. The number of subjects in the association study was small and may not have been large enough to detect a significant difference because the genetic impact of CDH13 on schizophrenia may be mild. Therefore, further investigations with larger sample sizes are needed to confirm the present results.

The results reported here raise the question: do nucleotide substitutions in the CDH13 promoter actually affect the transcriptional activity of the CDH13 promoter? Our computational analysis using the TFBIND (http://tfbind.hgc.jp/)36 revealed that most of the SNPs we studied here were located in the putative transcription factor binding sites (Table S3). This suggests that nucleotide substitution in the CDH13 promoter region may affect the transcriptional activity of this promoter region by affecting the ability of this promoter region to bind to transcription factors. To test this hypothesis, transcriptional assays, such as a luciferase assay, are required in future studies.

Conclusion

The present study suggests that haplotype variants in the promoter region of CDH13 may affect the susceptibility to schizophrenia. To confirm this result, further replication studies using larger sample sizes and different populations and functional studies are required.

Supplementary materials

Figure S1

The intronic SNPs (rs8057927 and rs8049308) have strong LD to each other (D’=1.0, r2=0.946). rs8049308 is a tag SNP for rs8057927 with the criteria of r2 threshold greater than 0.8 in ‘pair-wise tagging only’ mode using the ‘Tagger’ program in the Haploview software.

Abbreviations: CDH13, cadherin13; SNPs, single nucleotide polymorphisms; LD, linkage disequilibrium.

ndt-11-1381s1.tif (268.9KB, tif)

Table S1.

Genotype frequencies and allele frequencies of CDH13 SNPs in different ethnic populations

SNP Population Genotype frequencies
Allele frequencies
Genotype Freq Count Genotype Freq Count Genotype Freq Count Total Allele Freq Count Allele Freq Count Total
rs12925602 JPT G/G 0.708 80 A/G 0.265 30 A/A 0.027 3 113 G 0.841 190 A 0.159 36 226
CHB G/G 0.708 97 A/G 0.255 35 A/A 0.036 5 137 G 0.836 229 A 0.164 45 274
CHD G/G 0.642 70 A/G 0.339 37 A/A 0.018 2 109 G 0.812 177 A 0.188 41 218
GIH G/G 0.802 81 A/G 0.149 15 A/A 0.050 5 101 G 0.876 177 A 0.124 25 202
CEU G/G 0.850 96 A/G 0.142 16 A/A 0.009 1 113 G 0.920 208 A 0.080 18 226
TSI G/G 0.745 76 A/G 0.255 26 A/A 0.000 0 102 G 0.873 178 A 0.127 26 204
ASW G/G 0.750 42 A/G 0.250 14 A/A 0.000 0 56 G 0.875 98 A 0.125 14 112
LWK G/G 0.782 86 A/G 0.191 21 A/A 0.027 3 110 G 0.877 193 A 0.123 27 220
MKK G/G 0.833 130 A/G 0.160 25 A/A 0.006 1 156 G 0.913 285 A 0.087 27 312
YRI G/G 0.789 116 A/G 0.204 30 A/A 0.007 1 147 G 0.891 262 A 0.109 32 294
MEX G/G 0.741 43 A/G 0.224 13 A/A 0.034 2 58 G 0.853 99 A 0.147 17 116
rs7193788 JPT A/A 0.265 30 A/G 0.504 57 G/G 0.230 26 113 A 0.518 117 G 0.482 109 226
CHB A/A 0.285 39 A/G 0.445 61 G/G 0.270 37 137 A 0.507 139 G 0.493 135 274
CHD A/A 0.275 30 A/G 0.560 61 G/G 0.165 18 109 A 0.555 121 G 0.445 97 218
GIH A/A 0.584 59 A/G 0.366 37 G/G 0.050 5 101 A 0.767 155 G 0.233 47 202
CEU A/A 0.690 78 A/G 0.274 31 G/G 0.035 4 113 A 0.827 187 G 0.173 39 226
TSI A/A 0.784 80 A/G 0.186 19 G/G 0.029 3 102 A 0.877 179 G 0.123 25 204
ASW A/A 0.719 41 A/G 0.246 14 G/G 0.035 2 57 A 0.842 96 G 0.158 18 114
LWK A/A 0.691 76 A/G 0.273 30 G/G 0.036 4 110 A 0.827 182 G 0.173 38 220
MKK A/A 0.679 106 A/G 0.282 44 G/G 0.038 6 156 A 0.821 256 G 0.179 56 312
YRI A/A 0.796 117 A/G 0.190 28 G/G 0.014 2 147 A 0.891 262 G 0.109 32 294
MEX A/A 0.741 43 A/G 0.241 14 G/G 0.017 1 58 A 0.862 100 G 0.138 16 116
rs736719 JPT C/C 0.779 88 C/T 0.186 21 T/T 0.035 4 113 C 0.872 197 T 0.128 37 226
CHB C/C 0.679 93 C/T 0.277 38 T/T 0.044 6 133 C 0.818 224 T 0.182 50 274
CHD C/C 0.688 75 C/T 0.303 33 T/T 0.009 1 109 C 0.839 183 T 0.161 35 218
GIH C/C 0.762 77 C/T 0.228 23 T/T 0.010 1 101 C 0.876 177 T 0.124 25 202
CEU C/C 0.699 79 C/T 0.265 30 T/T 0.035 4 113 C 0.832 188 T 0.168 38 226
TSI C/C 0.784 80 C/T 0.186 19 T/T 0.029 3 102 C 0.877 179 T 0.123 25 204
ASW C/C 0.737 42 C/T 0.228 13 T/T 0.035 2 57 C 0.851 97 T 0.149 17 114
LWK C/C 0.700 77 C/T 0.264 29 T/T 0.036 4 110 C 0.832 183 T 0.168 37 220
MKK C/C 0.679 106 C/T 0.288 45 T/T 0.032 5 156 C 0.824 257 T 0.176 55 312
YRI C/C 0.796 117 C/T 0.190 28 T/T 0.014 2 147 C 0.891 262 T 0.109 32 294
MEX C/C 0.776 45 C/T 0.207 12 T/T 0.017 1 58 C 0.879 102 T 0.121 14 116
rs6565051 JPT G/G 0.133 15 A/G 0.469 53 A/A 0.398 45 113 G 0.367 83 A 0.633 143 226
CHB G/G 0.146 20 A/G 0.416 57 A/A 0.438 60 137 G 0.354 97 A 0.646 177 274
CHD G/G 0.148 16 A/G 0.463 50 A/A 0.389 42 108 G 0.380 82 A 0.620 134 216
GIH G/G 0.079 8 A/G 0.356 36 A/A 0.564 57 101 G 0.257 83 A 0.743 150 202
CEU G/G 0.071 8 A/G 0.354 40 A/A 0.575 65 113 G 0.248 56 A 0.752 170 226
TSI G/G 0.108 11 A/G 0.461 47 A/A 0.431 44 102 G 0.338 69 A 0.662 135 204
ASW G/G 0.088 5 A/G 0.421 24 A/A 0.491 28 57 G 0.298 34 A 0.702 80 114
LWK G/G 0.073 8 A/G 0.355 39 A/A 0.573 63 110 G 0.250 55 A 0.750 165 220
MKK G/G 0.052 8 A/G 0.426 66 A/A 0.523 81 155 G 0.265 82 A 0.735 228 310
YRI G/G 0.095 14 A/G 0.442 65 A/A 0.463 68 147 G 0.316 93 A 0.684 201 294
MEX G/G 0.140 8 A/G 0.509 29 A/A 0.351 20 57 G 0.395 45 A 0.605 69 114
rs7204454 JPT G/G 0.319 36 C/G 0.540 61 C/C 0.142 16 113 G 0.588 133 C 0.412 93 226
CHB G/G 0.382 52 C/G 0.441 60 C/C 0.176 24 136 G 0.603 164 C 0.397 108 272
CHD G/G 0.394 43 C/G 0.486 53 C/C 0.119 13 109 G 0.638 139 C 0.362 79 218
GIH G/G 0.158 16 C/G 0.406 41 C/C 0.436 44 101 G 0.361 73 C 0.639 129 202
CEU G/G 0.100 11 C/G 0.436 48 C/C 0.464 51 110 G 0.318 70 C 0.682 150 220
TSI G/G 0.147 15 C/G 0.598 61 C/C 0.255 26 102 G 0.446 91 C 0.554 113 204
ASW G/G 0.263 15 C/G 0.439 25 C/C 0.298 17 57 G 0.482 55 C 0.518 59 114
LWK G/G 0.164 18 C/G 0.536 59 C/C 0.300 33 110 G 0.432 95 C 0.568 125 220
MKK G/G 0.141 22 C/G 0.449 70 C/C 0.410 64 156 G 0.365 114 C 0.635 198 312
YRI G/G 0.284 40 C/G 0.504 71 C/C 0.213 30 141 G 0.535 151 C 0.465 131 282
MEX G/G 0.310 18 C/G 0.500 29 C/C 0.190 11 58 G 0.560 65 C 0.440 51 116
rs8057927 JPT T/T 0.478 54 C/T 0.425 48 C/C 0.097 11 113 T 0.690 156 C 0.310 70 226
CHB T/T 0.478 65 C/T 0.412 56 C/C 0.110 15 136 T 0.684 186 C 0.316 86 272
CHD T/T 0.514 56 C/T 0.394 43 C/C 0.092 10 109 T 0.711 155 C 0.289 63 218
GIH T/T 0.901 91 C/T 0.089 9 C/C 0.010 1 101 T 0.946 191 C 0.054 11 202
CEU T/T 0.876 99 C/T 0.124 14 C/C 0 0 113 T 0.938 212 C 0.062 14 226
TSI T/T 0.853 87 C/T 0.147 15 C/C 0 0 102 T 0.926 189 C 0.074 15 204
ASW T/T 0.632 36 C/T 0.351 20 C/C 0.018 1 57 T 0.807 92 C 0.193 22 114
LWK T/T 0.620 67 C/T 0.324 35 C/C 0.056 6 108 T 0.782 169 C 0.218 47 216
MKK T/T 0.692 108 C/T 0.250 39 C/C 0.058 9 156 T 0.817 255 C 0.183 57 312
YRI T/T 0.623 91 C/T 0.336 49 C/C 0.041 6 146 T 0.791 231 C 0.209 61 292
MEX T/T 0.807 46 C/T 0.175 10 C/C 0.018 1 57 T 0.895 102 C 0.105 12 114
rs8049308 JPT T/T 0.455 20 C/T 0.500 22 C/C 0.045 2 44 T 0.705 62 C 0.295 26 88
CHB T/T 0.364 16 C/T 0.477 21 C/C 0.159 7 44 T 0.602 53 C 0.398 35 88
CEU T/T 0.650 39 C/T 0.333 20 C/C 0.017 1 60 T 0.817 98 C 0.183 22 120
YRI T/T 0.583 35 C/T 0.383 23 C/C 0.033 2 60 T 0.775 93 C 0.225 27 120

Note: Genotype frequencies and allele frequencies data were determined by the HapMap database (HapMap data release 28, Phase 2+3, August 10), on NCBI B36 assembly, dbSNP b126 (http://hapmap.ncbi.nlm.nih.gov/).

Abbreviations: ASW, African ancestry in southwest USA; CDH13, cadherin13; CEU, residents of UT, USA with Northern and Western European ancestry, from the Centre d’Etude du Polymorphisme Humain collection; CHB, Han Chinese in Beijing, People’s Republic of China; CHD, Chinese in metropolitan Denver, CO, USA; freq, frequency; GIH, Gujarati Indians in Houston, TX, USA; JPT, Japanese in Tokyo, Japan; LWK, Luhya in Webuye, Kenya; MEX, Mexican ancestry in Los Angeles, CA, USA; MKK, Maasai in Kinyawa, Kenya; SNP, single nucleotide polymorphism; TSI, Tuscan in Italy; YRI, Yoruba in Ibadan, Nigeria.

Table S2.

Haplotype frequencies of CDH13 SNPs (rs12925602–rs7204454) in different ethnic populations1

JPT CHB CHD GIH CEU TSI ASW LWK MKK YRI MEX
GACGG 0.355 0.351 0.347 0.233 0.244 0.335 0.286 0.289 0.231 0.287 0.394
CGCAC 0.285 0.220 0.206 0.085
AACAG 0.151 0.161 0.194 0.119 0.081 0.114 0.127 0.106 0.091 0.130 0.154
GGTAC 0.128 0.179 0.135 0.142 0.162 0.114 0.103 0.167 0.154 0.087 0.106
GGCAG 0.070 0.077 0.076
GGCGG 0.012 0.006 0.018 0.006
GACAG 0.006 0.071 0.067 0.024 0.126 0.010
AACGG 0.006 0.017
GGCGC 0.012
AGCAG 0.006
AACAC 0.004
GACGC 0.017 0.006 0.008 0.004
GGCAC 0.009 0.008 0.003 0.019
AGTAC 0.008
GGTGG 0.014
GGTGC 0.006 0.014 0.022 0.010
GACAC 0.006 0.392 0.500 0.415 0.389 0.367 0.469 0.343 0.308

Note: Haplotype frequencies data were determined by the Haploview software program (version 4.2; Broad Institute, Cambridge, MA, USA) (http://www.broad.mit.edu/mpg/haploview/).

Abbreviations: ASW, African ancestry in southwest USA; CDH13, cadherin13; CEU, residents of UT, USA with Northern and Western European ancestry, from the Centre d’Etude du Polymorphisme Humain collection; CHB, Han Chinese in Beijing, People’s Republic of China; CHD, Chinese in metropolitan Denver, CO, USA; GIH, Gujarati Indians in Houston, TX, USA; JPT, Japanese in Tokyo, Japan; LWK, Luhya in Webuye, Kenya; MEX, Mexican ancestry in Los Angeles, CA, USA; MKK, Maasai in Kinyawa, Kenya; SNPs, single nucleotide polymorphisms; TSI, Tuscan in Italy; YRI, Yoruba in Ibadan, Nigeria.

Table S3.

Putative transcription factor binding site in each SNP on the promoter region of CDH13

SNP ID Allele Sequence Predicted TF Binding site Function
rs12925602 A TCTGCCTACATC[A]
AGGAAATTCAGA
c-Ets- ATCAAGGAAATT Regulates numerous genes and involved in stem cell development, cell senescence and death, and tumorigenesis
GATA-1 CATCAAGGA Regulates the switch of fetal hemoglobin to adult hemoglobin for erythroid development
CdxA CA TCAAG A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes
G TCTGCCTACATC[G]
AGGAAATTCAGA
c-Ets- ATCGAGGAAATT Regulates numerous genes and involved in stem cell development, cell senescence and death, and tumorigenesis
GATA-1 CATCGAGGA Regulates the switch of fetal hemoglobin to adult hemoglobin for erythroid development
rs7193788 A GCACGCAGCAGT[A]
AAAATACAGAAA
CdxA TAAAAATAAAAATA A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes
AhR/Ar GAGCACGCAGCAGTAA A ligand-activated transcription factor involved in the regulation of biological responses to planar aromatic hydrocarbons
Sox5 GTAAAAATAC A transcription factor involved in the regulation of embryonic development and in the determination of cell fate
G GCACGCAGCAGT[G]
AAAATACAGAAA
AhR/Ar ACGCAGCAGTGAAAA A ligand-activated transcription factor involved in the regulation of biological responses to planar aromatic hydrocarbons
rs736719 C CAGGAAGAAACA[C]
GAAGCAGTGTTT
SRY AAACACG A transcription factor and a member of the HMG-box family of DNA binding proteins, which may directly generate some male-specific properties of the brain
T CAGGAAGAAACA[T]
GAAGCAGTGTTT
SRY AAACATG A transcription factor and a member of the HMG-box family of DNA binding proteins, which may directly generate some male specific properties of the brain
HNF-3b GAAGAAACA TGA A transcription factor and a member of the forkhead class of DNA-binding proteins
rs6565051 A ACCTTCCCTGGA[A]
TGGAGAAAAGTC
C/EBPb GAATG GAGAAAAGT A transcription factor that can bind as a homodimer to certain DNA regulatory regions and can also form heterodimers with other C/EBP
G ACCTTCCCTGGA[G]
TGGAGAAAAGTC
C/EBPb GAGTG GAGAAAAGT A transcription factor that can bind as a homodimer to certain DNA regulatory regions and can also form heterodimers with other C/EBP
MZF1 AGTG GAGA A member of the SCAN domain family transcription factors that form dimers through their highly conserved SCAN motifs
rs7204454 C GTGAGTTCAGTA[C]
AATTTGTGTTTT
CdxA TACAATT A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes
G GTGAGTTCAGTA[G]
AATTTGTGTTTT
CdxA TAGAATT A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes

Abbreviations: CDH13, cadherin13; SNP, single nucleotide polymorphism; SNP ID, single nucleotide polymorphism identification; TF, transcription factor.

Reference

  • 1.Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–265. doi: 10.1093/bioinformatics/bth457. [DOI] [PubMed] [Google Scholar]

Acknowledgments

This work was supported in part by research grants from the Ministry of Education, Culture, Sports, Science, and Technology of Japan and the Smoking Research Foundation. We thank Y Nagashima and N Yamazaki for technical assistance.

Footnotes

Disclosure

The authors report no conflicts of interest in this work.

References

  • 1.Sullivan PF, Kendler KS, Neale MC. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry. 2003;60(12):1187–1192. doi: 10.1001/archpsyc.60.12.1187. [DOI] [PubMed] [Google Scholar]
  • 2.Mueser KT, McGurk SR. Schizophrenia. Lancet. 2004;363(9426):2063–2072. doi: 10.1016/S0140-6736(04)16458-1. [DOI] [PubMed] [Google Scholar]
  • 3.Sullivan PF, Daly MJ, O’Donovan M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet. 2012;13(8):537–551. doi: 10.1038/nrg3240. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.McCarley RW, Wible CG, Frumin M, et al. MRI anatomy of schizophrenia. Biol Psychiatry. 1999;45(9):1099–1119. doi: 10.1016/s0006-3223(99)00018-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Shenton ME, Dickey CC, Frumin M, McCarley RW. A review of MRI findings in schizophrenia. Schizophr Res. 2001;49(1–2):1–52. doi: 10.1016/s0920-9964(01)00163-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Harrison PJ. The neuropathology of schizophrenia. A critical review of the data and their interpretation. Brain. 1999;122(Pt4):593–624. doi: 10.1093/brain/122.4.593. [DOI] [PubMed] [Google Scholar]
  • 7.Gregório SP, Sallet PC, Do KA, Lin E, Gattaz WF, Dias-Neto E. Polymorphisms in genes involved in neurodevelopment may be associated with altered brain morphology in schizophrenia: preliminary evidence. Psychiatry Res. 2009;165(1–2):1–9. doi: 10.1016/j.psychres.2007.08.011. [DOI] [PubMed] [Google Scholar]
  • 8.Stephan KE, Friston KJ, Frith CD. Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring. Schizophr Bull. 2009;35(3):509–527. doi: 10.1093/schbul/sbn176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Takeichi M. The cadherin superfamily in neuronal connections and interactions. Nat Rev Neurosci. 2007;8(1):11–20. doi: 10.1038/nrn2043. [DOI] [PubMed] [Google Scholar]
  • 10.Hirano S, Takeichi M. Cadherins in brain morphogenesis and wiring. Physiol Rev. 2012;92(2):597–634. doi: 10.1152/physrev.00014.2011. [DOI] [PubMed] [Google Scholar]
  • 11.Pedrosa E, Stefanescu R, Margolis B, et al. Analysis of protocadherin alpha gene enhancer polymorphism in bipolar disorder and schizophrenia. Schizophr Res. 2008;102(1–3):210–219. doi: 10.1016/j.schres.2008.04.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Redies C, Hertel N, Hübner CA. Cadherins and neuropsychiatric disorders. Brain Res. 2012;1470:130–144. doi: 10.1016/j.brainres.2012.06.020. [DOI] [PubMed] [Google Scholar]
  • 13.Rivero O, Sich S, Popp S, Schmitt A, Franke B, Lesch KP. Impact of the ADHD-susceptibility gene CDH13 on development and function of brain networks. Eur Neuropsychopharmacol. 2013;23(6):492–507. doi: 10.1016/j.euroneuro.2012.06.009. [DOI] [PubMed] [Google Scholar]
  • 14.Neale BM, Lasky-Su J, Anney R, et al. Genome-wide association scan of attention deficit hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet. 2008;147B(8):1337–1344. doi: 10.1002/ajmg.b.30866. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Zhou K, Dempfle A, Arcos-Burgos M, et al. Meta-analysis of genome-wide linkage scans of attention deficit hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet. 2008;147B(8):1392–1398. doi: 10.1002/ajmg.b.30878. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Terracciano A, Tanaka T, Sutin AR, et al. Genome-wide association scan of trait depression. Biol Psychiatry. 2010;68(9):811–817. doi: 10.1016/j.biopsych.2010.06.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Wang K, Zhang H, Ma D, et al. Common genetic variants on 5p14.1 associate with autism spectrum disorders. Nature. 2009;459:528–533. doi: 10.1038/nature07999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Sanders SJ, Ercan-Sencicek AG, Hus V, et al. Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism. Neuron. 2011;70(5):863–885. doi: 10.1016/j.neuron.2011.05.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Treutlein J, Cichon S, Ridinger M, et al. Genome-wide association study of alcohol dependence. Arch Gen Psychiatry. 2009;66(77):773–784. doi: 10.1001/archgenpsychiatry.2009.83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Uhl GR, Drgon T, Johnson C, et al. Genome-wide association for smoking cessation success: participants in the Patch in Practice trial of nicotine replacement. Pharmacogenomics. 2010;11(3):357–367. doi: 10.2217/pgs.09.156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Uhl GR, Drgon T, Liu QR, et al. Genome-wide association for methamphetamine dependence: convergent results from 2 samples. Arch Gen Psychiatry. 2008;65(3):345–355. doi: 10.1001/archpsyc.65.3.345. [DOI] [PubMed] [Google Scholar]
  • 22.Børglum AD, Demontis D, Grove J, et al. GROUP investigators 10 Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci. Mol Psychiatry. 2014;19(3):325–333. doi: 10.1038/mp.2013.2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Dixon AL, Liang L, Moffatt MF, et al. A genome-wide association study of global gene expression. Nat Genet. 2007;39:1202–1207. doi: 10.1038/ng2109. [DOI] [PubMed] [Google Scholar]
  • 24.Hirakawa M, Tanaka T, Hashimoto, et al. JSNP: a database of common gene variations in the Japanese population. Nucleic Acids Res. 2002;30:158–162. doi: 10.1093/nar/30.1.158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Watanabe Y, Muratake T, Kaneko N, Nunokawa A, Someya T. No association between the brain-derived neurotrophic factor gene and schizophrenia in a Japanese population. Schizophr Res. 2006;84(1):29–35. doi: 10.1016/j.schres.2006.03.011. [DOI] [PubMed] [Google Scholar]
  • 26.Okazaki S, Watanabe Y, Hishimoto A, et al. Association analysis of putative cis-acting polymorphisms of interleukin-19 gene with schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry. 2014;50:151–156. doi: 10.1016/j.pnpbp.2013.12.006. [DOI] [PubMed] [Google Scholar]
  • 27.American Psychiatric Association . The Diagnostic and Statistical Manual of Mental Disorders, Fourth edition, text revision (DSM-IV TR) American Psychiatric Association Press; 2000. [Google Scholar]
  • 28.Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2):263–265. doi: 10.1093/bioinformatics/bth457. [DOI] [PubMed] [Google Scholar]
  • 29.Dupont WD, Plummer WD. Power and sample size calculations for studies involving linear regression. Control Clin Trials. 1998;19(6):589–601. doi: 10.1016/s0197-2456(98)00037-3. [DOI] [PubMed] [Google Scholar]
  • 30.GTEx Consortium The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45(6):580–585. doi: 10.1038/ng.2653. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Benes FM. Amygdalocortical circuitry in schizophrenia: from circuits to molecules. Neuropsychopharmacology. 2010;35(1):239–257. doi: 10.1038/npp.2009.116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Paradis S, Harrar DB, Lin Y, et al. An RNAi-based approach identifies molecules required for glutamatergic and GABAergic synapse development. Neuron. 2007;53(2):217–232. doi: 10.1016/j.neuron.2006.12.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Yizhar O, Fenno LE, Prigge M, et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature. 2011;477(7363):171–178. doi: 10.1038/nature10360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Mao W, Watanabe T, Cho S, et al. Shank1 regulates excitatory synaptic transmission in mouse hippocampal parvalbumin-expressing inhibitory interneurons. Eur J Neurosci. 2015;41(8):1025–1035. doi: 10.1111/ejn.12877. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Schizophrenia Working Group of the Psychiatric Genomics Consortium Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511(7510):421–427. doi: 10.1038/nature13595. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Tsunoda T, Takagi T. Estimating transcription factor bindability on DNA. Bioinformatics. 1999;15(7–8):622–630. doi: 10.1093/bioinformatics/15.7.622. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1

The intronic SNPs (rs8057927 and rs8049308) have strong LD to each other (D’=1.0, r2=0.946). rs8049308 is a tag SNP for rs8057927 with the criteria of r2 threshold greater than 0.8 in ‘pair-wise tagging only’ mode using the ‘Tagger’ program in the Haploview software.

Abbreviations: CDH13, cadherin13; SNPs, single nucleotide polymorphisms; LD, linkage disequilibrium.

ndt-11-1381s1.tif (268.9KB, tif)

Table S1.

Genotype frequencies and allele frequencies of CDH13 SNPs in different ethnic populations

SNP Population Genotype frequencies
Allele frequencies
Genotype Freq Count Genotype Freq Count Genotype Freq Count Total Allele Freq Count Allele Freq Count Total
rs12925602 JPT G/G 0.708 80 A/G 0.265 30 A/A 0.027 3 113 G 0.841 190 A 0.159 36 226
CHB G/G 0.708 97 A/G 0.255 35 A/A 0.036 5 137 G 0.836 229 A 0.164 45 274
CHD G/G 0.642 70 A/G 0.339 37 A/A 0.018 2 109 G 0.812 177 A 0.188 41 218
GIH G/G 0.802 81 A/G 0.149 15 A/A 0.050 5 101 G 0.876 177 A 0.124 25 202
CEU G/G 0.850 96 A/G 0.142 16 A/A 0.009 1 113 G 0.920 208 A 0.080 18 226
TSI G/G 0.745 76 A/G 0.255 26 A/A 0.000 0 102 G 0.873 178 A 0.127 26 204
ASW G/G 0.750 42 A/G 0.250 14 A/A 0.000 0 56 G 0.875 98 A 0.125 14 112
LWK G/G 0.782 86 A/G 0.191 21 A/A 0.027 3 110 G 0.877 193 A 0.123 27 220
MKK G/G 0.833 130 A/G 0.160 25 A/A 0.006 1 156 G 0.913 285 A 0.087 27 312
YRI G/G 0.789 116 A/G 0.204 30 A/A 0.007 1 147 G 0.891 262 A 0.109 32 294
MEX G/G 0.741 43 A/G 0.224 13 A/A 0.034 2 58 G 0.853 99 A 0.147 17 116
rs7193788 JPT A/A 0.265 30 A/G 0.504 57 G/G 0.230 26 113 A 0.518 117 G 0.482 109 226
CHB A/A 0.285 39 A/G 0.445 61 G/G 0.270 37 137 A 0.507 139 G 0.493 135 274
CHD A/A 0.275 30 A/G 0.560 61 G/G 0.165 18 109 A 0.555 121 G 0.445 97 218
GIH A/A 0.584 59 A/G 0.366 37 G/G 0.050 5 101 A 0.767 155 G 0.233 47 202
CEU A/A 0.690 78 A/G 0.274 31 G/G 0.035 4 113 A 0.827 187 G 0.173 39 226
TSI A/A 0.784 80 A/G 0.186 19 G/G 0.029 3 102 A 0.877 179 G 0.123 25 204
ASW A/A 0.719 41 A/G 0.246 14 G/G 0.035 2 57 A 0.842 96 G 0.158 18 114
LWK A/A 0.691 76 A/G 0.273 30 G/G 0.036 4 110 A 0.827 182 G 0.173 38 220
MKK A/A 0.679 106 A/G 0.282 44 G/G 0.038 6 156 A 0.821 256 G 0.179 56 312
YRI A/A 0.796 117 A/G 0.190 28 G/G 0.014 2 147 A 0.891 262 G 0.109 32 294
MEX A/A 0.741 43 A/G 0.241 14 G/G 0.017 1 58 A 0.862 100 G 0.138 16 116
rs736719 JPT C/C 0.779 88 C/T 0.186 21 T/T 0.035 4 113 C 0.872 197 T 0.128 37 226
CHB C/C 0.679 93 C/T 0.277 38 T/T 0.044 6 133 C 0.818 224 T 0.182 50 274
CHD C/C 0.688 75 C/T 0.303 33 T/T 0.009 1 109 C 0.839 183 T 0.161 35 218
GIH C/C 0.762 77 C/T 0.228 23 T/T 0.010 1 101 C 0.876 177 T 0.124 25 202
CEU C/C 0.699 79 C/T 0.265 30 T/T 0.035 4 113 C 0.832 188 T 0.168 38 226
TSI C/C 0.784 80 C/T 0.186 19 T/T 0.029 3 102 C 0.877 179 T 0.123 25 204
ASW C/C 0.737 42 C/T 0.228 13 T/T 0.035 2 57 C 0.851 97 T 0.149 17 114
LWK C/C 0.700 77 C/T 0.264 29 T/T 0.036 4 110 C 0.832 183 T 0.168 37 220
MKK C/C 0.679 106 C/T 0.288 45 T/T 0.032 5 156 C 0.824 257 T 0.176 55 312
YRI C/C 0.796 117 C/T 0.190 28 T/T 0.014 2 147 C 0.891 262 T 0.109 32 294
MEX C/C 0.776 45 C/T 0.207 12 T/T 0.017 1 58 C 0.879 102 T 0.121 14 116
rs6565051 JPT G/G 0.133 15 A/G 0.469 53 A/A 0.398 45 113 G 0.367 83 A 0.633 143 226
CHB G/G 0.146 20 A/G 0.416 57 A/A 0.438 60 137 G 0.354 97 A 0.646 177 274
CHD G/G 0.148 16 A/G 0.463 50 A/A 0.389 42 108 G 0.380 82 A 0.620 134 216
GIH G/G 0.079 8 A/G 0.356 36 A/A 0.564 57 101 G 0.257 83 A 0.743 150 202
CEU G/G 0.071 8 A/G 0.354 40 A/A 0.575 65 113 G 0.248 56 A 0.752 170 226
TSI G/G 0.108 11 A/G 0.461 47 A/A 0.431 44 102 G 0.338 69 A 0.662 135 204
ASW G/G 0.088 5 A/G 0.421 24 A/A 0.491 28 57 G 0.298 34 A 0.702 80 114
LWK G/G 0.073 8 A/G 0.355 39 A/A 0.573 63 110 G 0.250 55 A 0.750 165 220
MKK G/G 0.052 8 A/G 0.426 66 A/A 0.523 81 155 G 0.265 82 A 0.735 228 310
YRI G/G 0.095 14 A/G 0.442 65 A/A 0.463 68 147 G 0.316 93 A 0.684 201 294
MEX G/G 0.140 8 A/G 0.509 29 A/A 0.351 20 57 G 0.395 45 A 0.605 69 114
rs7204454 JPT G/G 0.319 36 C/G 0.540 61 C/C 0.142 16 113 G 0.588 133 C 0.412 93 226
CHB G/G 0.382 52 C/G 0.441 60 C/C 0.176 24 136 G 0.603 164 C 0.397 108 272
CHD G/G 0.394 43 C/G 0.486 53 C/C 0.119 13 109 G 0.638 139 C 0.362 79 218
GIH G/G 0.158 16 C/G 0.406 41 C/C 0.436 44 101 G 0.361 73 C 0.639 129 202
CEU G/G 0.100 11 C/G 0.436 48 C/C 0.464 51 110 G 0.318 70 C 0.682 150 220
TSI G/G 0.147 15 C/G 0.598 61 C/C 0.255 26 102 G 0.446 91 C 0.554 113 204
ASW G/G 0.263 15 C/G 0.439 25 C/C 0.298 17 57 G 0.482 55 C 0.518 59 114
LWK G/G 0.164 18 C/G 0.536 59 C/C 0.300 33 110 G 0.432 95 C 0.568 125 220
MKK G/G 0.141 22 C/G 0.449 70 C/C 0.410 64 156 G 0.365 114 C 0.635 198 312
YRI G/G 0.284 40 C/G 0.504 71 C/C 0.213 30 141 G 0.535 151 C 0.465 131 282
MEX G/G 0.310 18 C/G 0.500 29 C/C 0.190 11 58 G 0.560 65 C 0.440 51 116
rs8057927 JPT T/T 0.478 54 C/T 0.425 48 C/C 0.097 11 113 T 0.690 156 C 0.310 70 226
CHB T/T 0.478 65 C/T 0.412 56 C/C 0.110 15 136 T 0.684 186 C 0.316 86 272
CHD T/T 0.514 56 C/T 0.394 43 C/C 0.092 10 109 T 0.711 155 C 0.289 63 218
GIH T/T 0.901 91 C/T 0.089 9 C/C 0.010 1 101 T 0.946 191 C 0.054 11 202
CEU T/T 0.876 99 C/T 0.124 14 C/C 0 0 113 T 0.938 212 C 0.062 14 226
TSI T/T 0.853 87 C/T 0.147 15 C/C 0 0 102 T 0.926 189 C 0.074 15 204
ASW T/T 0.632 36 C/T 0.351 20 C/C 0.018 1 57 T 0.807 92 C 0.193 22 114
LWK T/T 0.620 67 C/T 0.324 35 C/C 0.056 6 108 T 0.782 169 C 0.218 47 216
MKK T/T 0.692 108 C/T 0.250 39 C/C 0.058 9 156 T 0.817 255 C 0.183 57 312
YRI T/T 0.623 91 C/T 0.336 49 C/C 0.041 6 146 T 0.791 231 C 0.209 61 292
MEX T/T 0.807 46 C/T 0.175 10 C/C 0.018 1 57 T 0.895 102 C 0.105 12 114
rs8049308 JPT T/T 0.455 20 C/T 0.500 22 C/C 0.045 2 44 T 0.705 62 C 0.295 26 88
CHB T/T 0.364 16 C/T 0.477 21 C/C 0.159 7 44 T 0.602 53 C 0.398 35 88
CEU T/T 0.650 39 C/T 0.333 20 C/C 0.017 1 60 T 0.817 98 C 0.183 22 120
YRI T/T 0.583 35 C/T 0.383 23 C/C 0.033 2 60 T 0.775 93 C 0.225 27 120

Note: Genotype frequencies and allele frequencies data were determined by the HapMap database (HapMap data release 28, Phase 2+3, August 10), on NCBI B36 assembly, dbSNP b126 (http://hapmap.ncbi.nlm.nih.gov/).

Abbreviations: ASW, African ancestry in southwest USA; CDH13, cadherin13; CEU, residents of UT, USA with Northern and Western European ancestry, from the Centre d’Etude du Polymorphisme Humain collection; CHB, Han Chinese in Beijing, People’s Republic of China; CHD, Chinese in metropolitan Denver, CO, USA; freq, frequency; GIH, Gujarati Indians in Houston, TX, USA; JPT, Japanese in Tokyo, Japan; LWK, Luhya in Webuye, Kenya; MEX, Mexican ancestry in Los Angeles, CA, USA; MKK, Maasai in Kinyawa, Kenya; SNP, single nucleotide polymorphism; TSI, Tuscan in Italy; YRI, Yoruba in Ibadan, Nigeria.

Table S2.

Haplotype frequencies of CDH13 SNPs (rs12925602–rs7204454) in different ethnic populations1

JPT CHB CHD GIH CEU TSI ASW LWK MKK YRI MEX
GACGG 0.355 0.351 0.347 0.233 0.244 0.335 0.286 0.289 0.231 0.287 0.394
CGCAC 0.285 0.220 0.206 0.085
AACAG 0.151 0.161 0.194 0.119 0.081 0.114 0.127 0.106 0.091 0.130 0.154
GGTAC 0.128 0.179 0.135 0.142 0.162 0.114 0.103 0.167 0.154 0.087 0.106
GGCAG 0.070 0.077 0.076
GGCGG 0.012 0.006 0.018 0.006
GACAG 0.006 0.071 0.067 0.024 0.126 0.010
AACGG 0.006 0.017
GGCGC 0.012
AGCAG 0.006
AACAC 0.004
GACGC 0.017 0.006 0.008 0.004
GGCAC 0.009 0.008 0.003 0.019
AGTAC 0.008
GGTGG 0.014
GGTGC 0.006 0.014 0.022 0.010
GACAC 0.006 0.392 0.500 0.415 0.389 0.367 0.469 0.343 0.308

Note: Haplotype frequencies data were determined by the Haploview software program (version 4.2; Broad Institute, Cambridge, MA, USA) (http://www.broad.mit.edu/mpg/haploview/).

Abbreviations: ASW, African ancestry in southwest USA; CDH13, cadherin13; CEU, residents of UT, USA with Northern and Western European ancestry, from the Centre d’Etude du Polymorphisme Humain collection; CHB, Han Chinese in Beijing, People’s Republic of China; CHD, Chinese in metropolitan Denver, CO, USA; GIH, Gujarati Indians in Houston, TX, USA; JPT, Japanese in Tokyo, Japan; LWK, Luhya in Webuye, Kenya; MEX, Mexican ancestry in Los Angeles, CA, USA; MKK, Maasai in Kinyawa, Kenya; SNPs, single nucleotide polymorphisms; TSI, Tuscan in Italy; YRI, Yoruba in Ibadan, Nigeria.

Table S3.

Putative transcription factor binding site in each SNP on the promoter region of CDH13

SNP ID Allele Sequence Predicted TF Binding site Function
rs12925602 A TCTGCCTACATC[A]
AGGAAATTCAGA
c-Ets- ATCAAGGAAATT Regulates numerous genes and involved in stem cell development, cell senescence and death, and tumorigenesis
GATA-1 CATCAAGGA Regulates the switch of fetal hemoglobin to adult hemoglobin for erythroid development
CdxA CA TCAAG A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes
G TCTGCCTACATC[G]
AGGAAATTCAGA
c-Ets- ATCGAGGAAATT Regulates numerous genes and involved in stem cell development, cell senescence and death, and tumorigenesis
GATA-1 CATCGAGGA Regulates the switch of fetal hemoglobin to adult hemoglobin for erythroid development
rs7193788 A GCACGCAGCAGT[A]
AAAATACAGAAA
CdxA TAAAAATAAAAATA A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes
AhR/Ar GAGCACGCAGCAGTAA A ligand-activated transcription factor involved in the regulation of biological responses to planar aromatic hydrocarbons
Sox5 GTAAAAATAC A transcription factor involved in the regulation of embryonic development and in the determination of cell fate
G GCACGCAGCAGT[G]
AAAATACAGAAA
AhR/Ar ACGCAGCAGTGAAAA A ligand-activated transcription factor involved in the regulation of biological responses to planar aromatic hydrocarbons
rs736719 C CAGGAAGAAACA[C]
GAAGCAGTGTTT
SRY AAACACG A transcription factor and a member of the HMG-box family of DNA binding proteins, which may directly generate some male-specific properties of the brain
T CAGGAAGAAACA[T]
GAAGCAGTGTTT
SRY AAACATG A transcription factor and a member of the HMG-box family of DNA binding proteins, which may directly generate some male specific properties of the brain
HNF-3b GAAGAAACA TGA A transcription factor and a member of the forkhead class of DNA-binding proteins
rs6565051 A ACCTTCCCTGGA[A]
TGGAGAAAAGTC
C/EBPb GAATG GAGAAAAGT A transcription factor that can bind as a homodimer to certain DNA regulatory regions and can also form heterodimers with other C/EBP
G ACCTTCCCTGGA[G]
TGGAGAAAAGTC
C/EBPb GAGTG GAGAAAAGT A transcription factor that can bind as a homodimer to certain DNA regulatory regions and can also form heterodimers with other C/EBP
MZF1 AGTG GAGA A member of the SCAN domain family transcription factors that form dimers through their highly conserved SCAN motifs
rs7204454 C GTGAGTTCAGTA[C]
AATTTGTGTTTT
CdxA TACAATT A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes
G GTGAGTTCAGTA[G]
AATTTGTGTTTT
CdxA TAGAATT A transcription factor that binds to DNA to regulate the expression of genes, in particular the Hox genes

Abbreviations: CDH13, cadherin13; SNP, single nucleotide polymorphism; SNP ID, single nucleotide polymorphism identification; TF, transcription factor.


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