G30 with schizophrenia in the Chinese population

BBRC Biochemical and Biophysical Research Communications 319 (2004) 1281–1286 www.elsevier.com/locate/ybbrc

Association of G72/G30 with schizophrenia in the Chinese population Xiaoyan Wang,a,b,1 Guang He,b,1 Niufan Gu,c,1 Jiandong Yang,a,b Junxia Tang,a,b Qi Chen,b Xinmin Liu,b Yifeng Shen,c Xueqing Qian,a,b Wei Lin,b Yun Duan,a,b Guoyin Feng,c and Lin Heb,a,* a b

Institute of Nutritional Sciences, SIBS, Chinese Academy of Sciences, 294 Taiyuan Road, Shanghai 200031, PR China Bio-X Life Science Research Center, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, PR China c Shanghai Institute of Mental Health, 600 South Wan Ping Road, Shanghai 200030, PR China Received 19 March 2004 Available online 4 June 2004

Abstract Recently, the G72 gene was reported to be associated with schizophrenia in the French Canadian and Russian populations. Here, we report the results obtained from the study of six single-nucleotide polymorphisms (SNPs: rs3916965, rs3916967, rs2391191, rs1935062, rs778293, and rs3918342), which span an 82-kb region covering the complementary DNA sequences of G72 and G30, in 537 schizophrenia cases and 538 controls of the Han Chinese. In this work, we have identified statistically significant differences in allele distributions of two markers rs3916965 (P ¼ 0:019) and rs2391191 (P ¼ 0:0010), and a highly significant association between haplotype AGAC of the G72/G30 locus (P ¼ 1:7
104 ) and schizophrenia. Our data provide further evidence that markers of the G72/G30 genes are associated with schizophrenia in a non-Caucasian population. Ó 2004 Elsevier Inc. All rights reserved. Keywords: Schizophrenia; Genetics; Association; Haplotype

Schizophrenia (MIM 181500) is a debilitating mental disorder that affects nearly 1% of population throughout the world. Although genetic factors are known to be important in the etiology of schizophrenia, the search for chromosomal loci and genes has been slow and frustrating. One of the explanations is that there are multiple susceptibility genes, each with small effect, which interact with one another and with environmental factors to influence susceptibility to the disease [1]. In a number of systematic linkage scans, however, positive linkages in several genomic regions have been reported. One of these regions or so-called ‘hot spots’ is 13q22–q34 [2–6]. A recent study has reported that two human genes G72 (MIM 607408) and G30 (MIM 607415), which overlaps with G72 on complementary chromosomal strands, located on 13q33 may confer susceptibility to schizophrenia [7]. Significant association with schizo-

phrenia was found in several SNPs and haplotypes, and replicated in a Russian sample with two of the same SNPs [7]. In expression and functional studies, G72 interacted with the gene for D -amino acid oxidase (DAAO) (MIM 124050) located on 12q24, which regulates glutaminergic signaling through the N-methyl-D aspartate (NMDA) receptor pathway [7] thought to be involved in the pathogenesis model of schizophrenia [8]. Another recent study reported that the G72/G30 gene locus is also associated with bipolar disorder [9] although further independent work is necessary. In this study, we have demonstrated association between several SNPs and haplotypes in the region of the G72/G30 gene and schizophrenia in a cohort of the Chinese casecontrol samples. Materials and methods

*

Corresponding author. Fax: +21-62822491. E-mail address: [email protected] (L. He). 1 The first three authors have contributed equally to this work. 0006-291X/$ - see front matter Ó 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.bbrc.2004.05.119

Subjects. All unrelated schizophrenia patients (283 males and 254 females, mean age 41.7  17.40 years), who met diagnostic and statistical manual of mental disorder, third revised edition (DSM-III-R)

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criteria [10], were recruited from the Shanghai Mental Health Center. All probands were given a diagnosis of schizophrenia before admitting to hospital. The diagnosis was checked and verified by two independent senior psychiatrists in reviewing psychiatric case records. The control individuals (266 males and 272 females, mean age 38.8  15.78 years) screened for absence of major mental illness were recruited from the same geographical regions of the cases. Written informed consent reviewed and approved by the Shanghai Ethical Committee of Human Genetic Resources was obtained from all participating subjects. All subjects were Han Chinese in origin. SNP genotyping. In the present association and individual haplotypic analysis, we chose five SNPs (rs3916965, rs3916967, rs2391191, rs778293, and rs3918342) around the G72/G30 gene locus from a list showing a significant allelic association with schizophrenia in the French Canadian population [7], and one SNP (rs1935062) between rs2391191 and rs778293 from a study elsewhere [9]. The SNPs were genotyped by allele-specific PCR for specifically amplifying the reference allele or its variant in separate PCRs [11]. The PCR primers used in this study were designed by a tetra-primer ARMS-PCR primer design program [12]. Only one pair of outer primer and inner primer was chosen from the four output primers for PCR. The primer sequences can be found from Table 1. The assay combining kinetic (real-time quantitative) PCR with allele-specific amplification was performed as described by Germer et al. [13]. In the real-time PCR, two PCRs for each sample were carried out in a total volume of 5 ll containing 10 ng genomic DNA, 2.5 ll Taqman Universal PCR Master Mix (Applied Biosystems), 0.2 lM allele-specific primer, 0.2 lM common primer, and 0.2
SYBR Green I (Molecular Probe) on an ABI PRISM 7900 Sequence Detection System (Applied Biosystems). To reduce well-to-well variability in PCR conditions, an automated dispenser (Hydra microdispenser, Robbins Scientific) and digital multi-channel pipettes (Thermo Labsystems) were used. After an initial 2-min at 50 °C to activate the AmpErase uracil-N-glycosylase (UNG) and a step of 12 min at 95 °C to deactivate UNG and activate AmpliTaq Gold enzyme, 50 cycles consisting of 15 s at 95 °C and 30 s at annealing temperature, followed by a final stage of dissociation of checking PCR product, were programmed. Allele calling that is identical to the previous research of our laboratory [14] was manually performed. Statistical analysis. Differences in allelic distributions were estimated using the program CLUMP 1.9 [15] with more than 10,000 simulations. The P values reported were two tailed and significance was set at P < 0:05. Tests for haplotypic association with schizophrenia were performed using the program FASTEHPLUS [16] with a permutation test to obtain the empirical significance levels. FASTEHPLUS was used to perform model-free analysis and permutation test(s) of allelic association based on EH and EHPLUS [17], which use

marker genotypes from a group of unrelated individuals or from the case-control samples to employ gene-counting algorithm in estimation of haplotype frequencies, output asymptotic, and permutation test statistics. We also estimated haplotype frequencies by the program PHASE [18], a software that implements a Bayesian statistical method for reconstructing haplotypes from population genotype data, which shows the consistent haplotype frequencies (Supplementary data) as estimated by FASTEHPLUS. PHASE also listed the most likely pairs of haplotypes for each individual, together with their probability (Supplementary data). The pairwise linkage disequilibrium (LD) values, as measured by D0 [19], were estimated using software 2LD [20]. To test for departure from Hardy–Weinberg equilibrium, an online calculator was recruited in both case and control groups. Bonferroni corrections were applied for all multiple statistical tests. Power calculations were performed using the G*Power program [21].

Results Genotype distributions of all the six SNPs in both cases and controls were in Hardy–Weinberg equilibrium. Results from analysis of individual SNPs using CLUMP are presented in Table 2. Between 537 case and 538 control individuals, we observed statistically significant differences in allele distributions on SNP markers rs2391191 (P ¼ 0:0010; OR ¼ 1:33; 95% CI 1.12–1.58) and rs3916965 (P ¼ 0:019; OR ¼ 1:23; 95% CI 1.04–1.46). After Bonferroni correction, rs2391191 still showed significant difference (P ¼ 0:0060). Furthermore, modest association was found between SNP rs3916965 and schizophrenia in women (P ¼ 0:045; OR ¼ 1:29; 95% CI 1.01–1.65) but not in men; However, SNP rs2391191 was found to be significantly associated with schizophrenia in both women (P ¼ 0:021; OR ¼ 1:34; 95% CI 1.05–1.71) and men (P ¼ 0:020; OR ¼ 1:33; 95% CI 1.05–1.69). The results of linkage disequilibrium between each pair of all SNPs are shown in Table 3. The LD analysis revealed that four SNPs between rs3916965 and rs1935062 were in an LD block (D0 > 0:7). In analysis of frequency of the haplotypes with the four SNPs rs3916965–rs3916967– rs2391191–rs1935062 and three SNPs rs3916965– rs3916967–rs2391191 (D0 > 0:85) (Table 4) in 537 cases

Table 1 Primers used for allele-specific PCR SNP rs3916965 rs3916967 rs2391191 rs1935062 rs778293 rs3918342

Primer sequencea 0

5 -GCTTGTAGGATTACTCATTTACA/G 50 -AATACAGGGAAAAAAGTGATGACA 50 -GGGTCCCTGGCTAATCTTTCAACTA/G 50 -GTTATTCTTCTCTCCTCATATTCAA 50 -CTACTTCATAGGTTTTCCAAA/G 50 -AGATAAAGAGTAACATACCAATAGA 50 -TTGAGAGTATTTCCATATTAACCT/G 50 -TTAGGGTGAAGAATATTACATTATG 50 -AAAATTCAGCTTTAAAATCACTCC/T 50 -TAGGATGTCAGACTTTATTCTAA 50 -CATTCACTATCTTAGCATGACCCG/A 50 -GGATATAGGATACTAAAATCTGAG

Annealing temperature (°C) 58 58 56 56 58 58

a An additional mismatch was deliberately put at position )3 from the 30 terminus of the allele-specific primer to confer the specificity of PCR amplification.

X. Wang et al. / Biochemical and Biophysical Research Communications 319 (2004) 1281–1286

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Table 2 Statistical analysis for SNPs SNPa

Polymorphismb

Distancec (kb)

Sex

Allele frequency (%) Casesd

Controlsd

P valuee

Odds ratio (95% CI)

rs3916965

AG

0.0

All Male Female

61.7(663) 61.4(349) 62.1(314)

56.7(610) 57.5(306) 55.9(304)

0.019 0.20 0.045

1.23(1.04–1.46) 1.18(0.93–1.50) 1.29(1.01–1.65)

rs3916967

AG

14.0

All Male Female

62.1(667) 61.1(347) 63.2(320)

61.5(662) 61.1(325) 61.9(337)

0.80 1.00 0.70

1.03(0.86–1.22) 1.00(0.79–1.28) 1.06(0.82–1.36)

rs2391191

AG

16.1

All Male Female

61.6(662) 61.4(349) 61.9(313)

54.6(588) 54.5(290) 54.8(298)

0.0010 0.020 0.021

1.33(1.12–1.58) 1.33(1.05–1.69) 1.34(1.05–1.71)

rs1935062

AC

24.8

All Male Female

59.7(641) 58.6(333) 60.9(308)

56.2(605) 56.0(298) 56.4(307)

0.11 0.39 0.15

1.15(0.97–1.37) 1.11(0.88–1.41) 1.20(0.94–1.54)

rs778293

AG

65.8

All Male Female

39.3(422) 39.6(225) 38.9(197)

36.2(390) 36.1(192) 36.4(198)

0.16 0.24 0.41

1.14(0.96–1.34) 1.16(0.91–1.48) 1.11(0.87–1.43)

rs3918342

CT

82.4

All Male Female

49.0(526) 47.0(267) 51.2(259)

45.8(493) 44.4(236) 47.2(257)

0.16 0.40 0.22

1.14(0.96–1.35) 1.11(0.88–1.41) 1.17(0.92–1.49)

a

SNPs rs3916965, rs3916967, rs2391191, rs778293, and rs3918342 correspond to M-12, M-14, M-15, M-22, and M-23, respectively, of [7]. The allele with increased frequency in cases compared to controls is underlined. c Positions of SNPs are shown as distances from rs3916965, where G72 and G30 are located in the range of 14.9–40.0 kb and 8.1–54.7 kb. d Number of alleles for each SNP is given in parentheses. e Significant P values (<0.05) are in boldface. b

Table 3 Pairwise LD results Pairwise LD Resultsa rs3916965 rs3916965 rs3916967 rs2391191 rs1935062 rs778293 rs3918342 a

rs3916967

rs2391191

rs1935062

rs778293

—

0.86 0.86 0.70 0.22 0.17

—

0.87 0.77 0.20 0.18

—

0.70 0.20 0.19

—

0.20 0.17

—

0.26

For each pair of SNPs, the standardized D0 is shown. D0 values P 0.7 are in boldface.

and 538 controls, we observed that the overall frequencies were significant different (four-SNP haplotype: P ¼ 1:0
105 ; three-SNP haplotype: P ¼ 1:7
104 ). In three-SNP haplotypes, only AGA gave the significant association with schizophrenia (P ¼ 0:019; OR ¼ 1:22; 95% CI 1.03–1.45). In these four-SNP haplotypes, the most common haplotype AGAC was found to be strongly associated with schizophrenia due to its significantly increased frequency in cases compared to controls (P ¼ 1:7
104 ; OR ¼ 1:39; 95% CI 1.17–1.65). By contraries, however, haplotype AGAA was significantly associated with controls rather than cases (P ¼ 3:5
103 ; OR ¼ 0.58; 95% CI 0.40–0.83). After correction for multiple testing (16 haplotypes and 6 allelic comparisons), the differences observed for haplotype

AGAC (P ¼ 3:7
103 ) remain significant. Additionally, we made a breakdown comparison between cases and controls within different sex groups with haplotype frequencies. In female groups, although the overall frequencies were not significant different between 253 cases and 272 controls, the three above-mentioned haplotypes were found to be associated with schizophrenia too: AGA (P ¼ 0:023; OR ¼ 1:33; 95% CI 1.04–1.70), AGAC (P ¼ 6:8
104 ; OR ¼ 1.54; 95% CI 1.20–1.96), and AGAA (P ¼ 0:014; OR ¼ 0:54; 95% CI 0.32–0.91). In the male groups, there was no single haplotype associated with schizophrenia but the overall frequencies were significant different (four-SNP haplotype: P ¼ 0:0013; three-SNP haplotype: P ¼ 0:0020) in 284 cases and 266 controls.

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Table 4 Estimated haplotype frequencies and association significance Haplotype

P valuea

Frequency (%) All Cases

Male Controls

Cases

Controls

rs3916965–rs3916967–rs2391191–rs1935062 AAAA 0.6215 0.2295 0.411 AAAC 1.5409 1.0397 2.166 AAGA 1.8111 0.4736 2.7642 AAGC 0.2344 0.1431 0.0741 AGAA 4.5893 7.6599 4.6438 AGAC 51.0007 42.8653 49.9774 AGGA 0.7559 0.505 0.733 AGGC 1.1781 3.7753 0.6742 GAAA 0.7462 0.6029 0.9314 GAAC 0.7931 0.1907 0.7222 GAGA 29.9784 31.6241 30.4051 GAGC 2.17 4.1721 1.4344 GGAA 0.4178 0.0017 0.5253 GGAC 1.9292 2.0571 2.0665 GGGA 1.3964 2.6764 0.9594 GGGC 0.8369 1.9834 1.5119

0.2123 0.5854 0.381 0 6.9679 44.5481 1.0731 3.751 0.5955 0 33.3761 3.76 0.1941 1.4079 1.1849 1.9633

0.8007 0.8802 0.8503 0.3709 4.5551 52.1159 0.7336 1.7487 0.5425 0.8756 29.4799 2.9588 0.3394 1.7484 1.829 0.1711

0.1659 1.5381 0.6303 0.3335 8.044 41.5446 0.11 3.5161 0.5684 0.4154 29.8381 4.5618 0 2.5031 4.2095 2.0213

rs3916965–rs3916967–rs2391191 AAA 2.168 1.2455 AAG 2.048 0.6533 AGA 55.591 50.5601 AGG 1.9254 4.2326 GAA 1.5404 0.7931 GAG 32.139 35.784 GGA 2.3399 2.0482 GGG 2.2485 4.6834

0.8184 0.3657 51.492 4.8427 0.6007 37.125 1.6002 3.1553

1.6761 1.2284 56.6980 2.4529 1.4113 32.4431 2.0723 2.0179

1.6782 0.9532 49.6334 3.6176 0.9826 34.4375 2.4852 6.2123

a

Controls

Cases

Female

2.5928 2.7942 54.6138 1.4429 1.6645 31.857 2.5726 2.4623

All

Male

Female

0.000010

0.0013

0.052

0.0035 0.00017

0.093 0.08

0.014 0.00068

0.51

0.30

0.95

0.00017

0.0020

0.15

0.019

0.33

0.023

0.076

0.066

0.51

It only lists P values of haplotype with a frequency >0.05. Significant P values (<0.05) are in boldface.

In the power calculation using G*Power program based on Cohen’s method [22], we found that the present sample size had >95% power for alleles and >85% power for haplotypes to detect a significant (a < 0:05) association, respectively, when an effect size index of 0.1 (corresponding to “weak” gene effect) is used.

Discussion In the present study, we have significantly demonstrated the evidence of association between two markers (rs3916965 and rs2391191) of the G72/G30 genes and schizophrenia in the Chinese population. In previous report, the two SNPs had been identified to be associated with schizophrenia in the French Canadian population [7]. In our study, one significant SNP was rs3916965 (P ¼ 0:019) situating 14.9 kb upstream of G72 exon 1 and 8.1 kb downstream of the last G30 exon, which was reported to be the most associated marker (P ¼ 0:007) before [7]. And another one was rs2391191 showing the strongest significant association effect (P ¼ 0:0010), which is in an intron of G30 and an untranslated region of G72 by the newly revised NCBI SNP database (Revised March 7, 2003). The most as-

sociated markers in both French Canadian and Russian populations were rs778293 (P ¼ 0:003) and rs3918342 (P ¼ 0:017), respectively. Conversely, rs778293 and rs3918342 were not significantly associated with schizophrenia in our sample. The differences may be explained as follows: (1) Schizophrenia is heterogeneous, with different loci influencing liability in different populations. (2) Individual SNPs, which are not very informative, are easier than haplotypes to give unstable frequencies among different populations in association study of the complex disorder. The three- and four-marker haplotypes covering components rs3916965, rs3916967, and rs2391191 were observed to be significantly associated with schizophrenia in this study, which was similarly reported in the French Canadian population presented by Chumakov et al. [7]. In our haplotype analysis, the most common four-marker haplotype AGAC, which was significantly more frequent in cases than in controls. Interestingly, by comparison, the haplotype AGAA, which presented higher occurrence in controls than in cases, contained a variant that was likely to be protective against the disorder. When we analyzed haplotypes with the former three markers, AGA still was significantly more frequent in cases than in controls, indicating it may carry one or

X. Wang et al. / Biochemical and Biophysical Research Communications 319 (2004) 1281–1286

more predisposing variants. Although there is not any non-synonymous SNP in the haplotype blocks, the location of positive SNPs within the area strongly implicates G72/G30 as susceptibility genes of schizophrenia. We made a comparison of alleles and haplotypes in male and female groups. The allele analysis did not show the significant difference between effect in men and in woman. Although the haplotype analysis showed some different effects between male and female groups, the results from this study were not clear enough to suggest sex-specific genetic effect. Recently, Hattori et al. [9] also discovered that the G72/G30 gene was associated with bipolar disorder. In their Decay of Haplotype Sharing (DHS) analysis [23], they found that the range of the 95% CI of association in the clinical neurogenetic pedigrees covered some of the SNPs that were associated with schizophrenia shown in the study of Chumakov et al. [7]. However, there were two SNPs, which were replicated for association in the Russian population [7], without being in this 78-kb region. But our results show a support for the work of Hattori et al. [9] due to our three- and four-marker haplotypes covered in the region, where schizophrenia and bipolar disorder may share a disease-susceptibility variant at G72/G30 locus. G72 was mentioned to interact with DAAO in regulation of glutaminergic signaling through the NMDA pathway [7], which may be especially involved in the pathogenesis model of schizophrenia [8]. In a recent review, several susceptibility genes of schizophrenia, such as NRG1 (MIM 142445), DTNBP1 (MIM 607145), G72, DAAO, RGS4 (MIM 602516), PRODH (MIM 606810), and COMT (MIM 116790), were described in direct or indirect interaction with NMDA receptors [1]. In our laboratory, the associations of NRG1 [24,25], DTNBP1 [14], and G72 with schizophrenia have been replicated in the Chinese Population. The discovery on the pathophysiological implication of NMDA pathway in schizophrenia may result from understanding of each predisposition gene that acts in the pathway.

Acknowledgments We are deeply grateful to all of the families who participated in this study, as well as the psychiatrists and mental health workers who helped us with identification of the families. This work was supported by grants from the national 973 and 863 Projects, the National Natural Science Foundation of China, Shanghai Municipal Commission for Science and Technology.

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