Genetic analysis of common variants in the CMYA5 (cardiomyopathy-associated 5) gene with schizophrenia

Progress in Neuro-Psychopharmacology & Biological Psychiatry 46 (2013) 64–69

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Genetic analysis of common variants in the CMYA5 (cardiomyopathy-associated 5) gene with schizophrenia Rui Zhang a,b,1, Huan Zhang d,1, Ming Li c, Hongbo Li a, Yue Li a, Robert K. Valenzuela e,f, Bing Su c, Jie Ma a,⁎ a

Department of Genetics and Molecular Biology, Xi'an Jiaotong University College of Medicine, Xi'an, Shaanxi 710061, China Xi'an Hong Hui Hospital, the Affiliated Hospital of Xi'an Jiaotong University College of Medicine, Xi'an, Shaanxi, China State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China d Psychiatry Department, Second Affiliated Hospital, Xi'an Jiaotong University College of Medicine, Xi'an, Shaanxi, China e Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore f Life Sciences Institute, National University of Singapore, Singapore b c

a r t i c l e

i n f o

Article history: Received 28 March 2013 Received in revised form 24 May 2013 Accepted 31 May 2013 Available online 15 June 2013 Keywords: Association CMYA5 Haplotype Schizophrenia SNP

a b s t r a c t Recently, CMYA5 was suggested as a susceptibility gene for schizophrenia based on two independent studies utilizing different ethnic samples. We designed a case–control study to examine whether 21 SNPs contained within CMYA5 were associated with the disorder in a western Han Chinese sample comprised of 488 schizophrenia patients and 516 healthy control subjects. The allele distribution of SNPs rs7714250, rs16877135 and rs13158477 showed significant association with schizophrenia (Puncorrected = 0.008, Puncorrected = 0.04, and Puncorrected = 0.009, respectively) as well as the genotype distribution in the Cochran–Armitage trend test (Puncorrected = 0.008, Puncorrected = 0.037 and Puncorrected = 0.011, respectively). After Bonferroni correction, rs7714250 showed a trend of association with schizophrenia both in allele distribution (Pcorrected = 0.088) and genotype distribution (Pcorrected = 0.088). Furthermore, significant associations were found in several two-, three-, four-, and five-SNP tests of haplotype analyses. Replications of the association of CMYA5 with schizophrenia across various studies suggest that it is very likely a potential common schizophrenia-related gene worldwide. Functional studies correlating CMYA5 with DTNBP1 and PKA warrant further investigation of the molecular basis of this gene in relationship to the signal transduction pathway(s) underlying the pathogenesis of schizophrenia. © 2013 Elsevier Inc. All rights reserved.

1. Introduction Schizophrenia (MIM 181500) has a lifetime risk of approximately 1% and is characterized by delusions, hallucinations, altered cognition, emotional reactivity, and disorganized behavior. Genetic factors account for more than 80% of the variance in susceptibility, and risk likely results from multiple loci with small effects (O'Donovan et al., 2008). Previous studies have indicated that genes such as Disrupted-inschizophrenia 1 (DISC1) and D-amino acid oxidase activator (DAOA or G72), as well as other genes might confer risk for this disease (Craddock et al., 2005; Devon et al., 2001; Ma et al., 2006; Yue et al., Abbreviations: CMYA5, cardiomyopathy-associated 5; DISC1, disrupted-in-schizophrenia 1; DAOA or G72, D-amino acid oxidase activator; ZNF804A, zinc finger protein 804A; MHC, major histocompatibility complex; DSM, the diagnostic and statistical manual of mental disorders; SNP, single nucleotide polymorphism; LD, linkage disequilibrium; MAF, minor allele frequency; CHB, Han Chinese population in Beijing; HWE, Hardy-Weinberg equilibrium; GWA, genome-wide association; TRIM, tripartite-motif; DTNBP1, dystrobrevin binding protein 1; BLOC-1, biogenesis of lysosome-related organelles complex 1; PKA, protein kinase A; cAMP, cyclic adenosine monophosphate. ⁎ Corresponding author at: Department of Genetics and Molecular Biology, Xi'an Jiaotong University College of Medicine, 76 West Yan Ta Road, Xi'an, Shaanxi 710061, China. E-mail address: [email protected] (J. Ma). 1 These authors contributed equally to this work. 0278-5846/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.pnpbp.2013.05.015

2011). More recently, genome-wide association studies (GWASs) of schizophrenia have identified several susceptibility loci, such as ZNF804A, MicroRNA-137 and loci within the extended major histocompatibility complex (MHC) region (Chen et al., 2011; O'Donovan et al., 2008; Ripke et al., 2011; Yue et al., 2011). As a result of the genetic heterogeneity of schizophrenia among different populations, the susceptibility loci for this disorder have often failed to replicate across studies (Yue et al., 2011). Furthermore, the pathways or biological mechanisms that underlie susceptibility of schizophrenia are still largely unknown (Shi et al., 2011). CMYA5 was initially reported by Chen et al. where they detected CMYA5 as the susceptibility gene for schizophrenia by utilizing a two-stage approach. In the first hypothesis-generating stage, three SNPs (rs3828611, rs10043986, and rs4704591) were identified by using two different data sets. In the second evaluating stage, rs10043986 and rs4704591 were validated and found to be in low LD in 23 independent data sets of multiple non-Asian populations by utilization of a standard meta-analysis method. rs3828611 was dropped without further investigation due to conflicting results obtained from Irish samples (Chen et al., 2011). Subsequently, Li et al. replicated the previous findings of these SNPs in three independent Han Chinese samples of Kunming and Yuxi in

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southwestern China, and Beijing in northern China, respectively. They found an association between rs3828611 and schizophrenia, which was more pronounced in the southern Han Chinese samples (Li et al., 2011). Both rs3828611 and rs10043986 are non-synonymous SNPs that may have direct functional consequences (Chen et al., 2011). To further explore the susceptibility of CMYA5 and its possible related biology function in schizophrenia, we designed a case–control study selecting 21 common SNPs from the HapMap website (http://hapmap. ncbi.nlm.nih.gov) which encompassed CMYA5 gene and its flanking sequences to examine whether the non-synonymous, rs3828611 and rs10043986, and other SNPs of CMYA5 were associated with the disorder in the western Han Chinese population. 2. Materials and methods 2.1. Subjects The study was approved by the local psychiatry research ethics committees and informed consent was obtained from all participates. A total of 994 unrelated individuals were recruited from the Northwest China that included 488 patients (264 males, mean age = 34.17 ± 12.0, age of onset = 24.29 ± 7.38; 222 females, mean age = 33.04 ± 13.74, age of onset = 24.96 ± 8.71) with schizophrenia and 516 healthy controls (289 males, mean age = 28.97 ± 14.09; 227 females, mean age = 28.70 ± 13.70). All patients were diagnosed by the Psychiatry Department of the First Affiliated Hospital of Xi'an Jiaotong University College of Medicine according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria for schizophrenia. The diagnosis was checked and confirmed by independent senior psychiatrists who reviewed the psychiatric case records and excluded those with organic brain disease, short-term drug-induced psychoses, or other symptomatic psychoses. All the cases were outpatients or stable inpatients from a mental health center in Shaanxi province that had at least a two year history of schizophrenia. Healthy controls were drawn from a combination of local volunteers and blood transfusion donors. Subjects with a personal and/or family history of mental illness were excluded from the study by psychiatric colleagues. All subjects were Han Chinese in origin. 2.2. Genotyping Based on frequency data obtained from the International HapMap Project, 21 SNPs (Table 1) were selected by using the criteria that the Minor Allele Frequency (MAF) for each SNP is greater than 5% in the Han Chinese population in Beijing (CHB) population. 17 of them are non-synonymous variants and the SNPs were nearly evenly distributed across the CMYA5. Human genomic DNA was isolated from whole blood using the DNA Isolation Kit for Mammalian Blood (Tiangen Biotech CO., LTD). Genotypes were obtained using the Sequenom iPLEX assay (Sequenom, Cambridge, MA). Locus-specific PCR primers and allele-specific detection primers were designed using the MassARRAY Assay Design 3.0 software (Sequenom) (Sladek et al., 2007). PCR products were desalted and transferred to a 384-element SpectroCHIP array. Allele detection was performed using MALDI-TOF MS. The mass spectrograms were analyzed by the MassARRAY TYPER software (Sequenom) (Zhang et al., 2009). On each sample plate, there were two negative controls (water), and two blinded duplicates. All SNPs showed a very high call rate (>95%, the median of call rate >97%), and a very high consistency rate between blind duplicates (>97%) (Zheng et al., 2009). 2.3. Statistical analysis Hardy–Weinberg equilibrium (HWE) for all the SNPs was assessed using the software program Finetti (http://ihg2.helmholtz-muenchen. de/cgi-bin/hw/hwa1.pl). Allele frequencies and pair-wise marker LD

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Table 1 Markers and primers used for MassARRAY genotyping. SNPs

Positiona

Name

rs73121501 78,984,789 1st-PCRP 2nd-PCRP UEP_SEQ rs7714250 78,993,484 1st-PCRP 2nd-PCRP UEP_SEQ rs4371733 79,010,573 1st-PCRP 2nd-PCRP UEP_SEQ rs62621858 79,025,028 1st-PCRP 2nd-PCRP UEP_SEQ rs1366271 79,025,634 1st-PCRP 2nd-PCRP UEP_SEQ rs16877133 79,028,513 1st-PCRP 2nd-PCRP UEP_SEQ rs16877135 79,028,586 1st-PCRP 2nd-PCRP UEP_SEQ rs13158477 79,028,726 1st-PCRP 2nd-PCRP UEP_SEQ rs74935252 79,029,311 1st-PCRP 2nd-PCRP UEP_SEQ rs1019762 79,029,594 1st-PCRP 2nd-PCRP UEP_SEQ rs1428225 79,029,749 1st-PCRP 2nd-PCRP UEP_SEQ rs73773429 79,030,638 1st-PCRP 2nd-PCRP UEP_SEQ rs76702556 79,030,926 1st-PCRP 2nd-PCRP UEP_SEQ rs28362541 79,032,666 1st-PCRP 2nd-PCRP UEP_SEQ rs59212409 79,032,978 1st-PCRP 2nd-PCRP UEP_SEQ rs2278239 79,033,306 1st-PCRP 2nd-PCRP UEP_SEQ rs3828611 79,034,662 1st-PCRP 2nd-PCRP UEP_SEQ rs12514461 79,041,057 1st-PCRP 2nd-PCRP UEP_SEQ rs1129770 79,086,883 1st-PCRP 2nd-PCRP UEP_SEQ rs10043986 79,095,417 1st-PCRP 2nd-PCRP UEP_SEQ rs4704591 79,103,471 1st-PCRP 2nd-PCRP UEP_SEQ a

Primers ACGTTGGATGACGGTTGCCTAACAGGCCAT ACGTTGGATGTCTGGGCGACAAGAGCAAG ATCAAAAAAAAAAAAAGAGTAGACAG ACGTTGGATGGAAATGATGATGGTTCCAGC ACGTTGGATGAGACAGCTGGTAAGTAGCAC GCACAGCTAGCATTCTAA ACGTTGGATGAGGCATGAGTGACCATGCG ACGTTGGATGGTGTGACATATGCTTCAATAG AAACCTAGAATGTGCAAAAGGC ACGTTGGATGGTTGGAACATCTTGGGATTC ACGTTGGATGTCAAAGCATGGTTCACCATC GTCACCATCATTACGCC ACGTTGGATGACATCTGCATTGGAGCACAC ACGTTGGATGGAATGCCTGAGCTGTATTCC CTCCTTGTTCTGCTCTG ACGTTGGATGCAGCAGTGAAAATGGAGATG ACGTTGGATGGAGGAAGCTGAATGAAGCAC GCACTATAGGTGTAGTTGTTA ACGTTGGATGATTTCTTCTGACAAAGCTG ACGTTGGATGATTCAGCTTCCTCAGGAGTG AACATGGTCCACCTG ACGTTGGATGCTTAACCAGAGCAGTAAAAG ACGTTGGATGGTTAAGACTGGACGATCTAC CTAATACTGGACGATCTACAGGAGTGA ACGTTGGATGCCCAAAAGGCAAAGATGAGG ACGTTGGATGTGTTGGGGCTAAACCTGATG GGGCTAAACCTGATGCTAAAT ACGTTGGATGCAAGCAAAGTCTCCCATAAC ACGTTGGATGTTTCCTTCTCTGCTCCTAAG GTCGCTGGGCCTTTTTCT ACGTTGGATGCAGAGGCAGGTGGTTCTTTC ACGTTGGATGGGAGGAATCTCAGAATGAAG GAAATTAAACCTTTCTCTCCCAAGATC ACGTTGGATGTTGGAAGGCCAGGAAAGCTC ACGTTGGATGGGGAAGGAGATTCATTCTTTG CATTCTTTGATGGAGAGTG ACGTTGGATGGAGAAGCCATTGGAAGAATC ACGTTGGATGCAGGTGATGGTTTCTTTCCC CCCCTCATCAGCATCATCA ACGTTGGATGGAGTCAGAGCTATCGAAAGG ACGTTGGATGACTGCCTTTTCTTGAAATCC CCCCCTCTTGAAATCCTTGTTTCACA ACGTTGGATGATATGGCGGTGTTTCTGAGC ACGTTGGATGCCATCTAAAGAATCCGAAAGG TTTAGCCGAAAGGACTTTAGCTC ACGTTGGATGCATATGTGTCTTCAGGTTCC ACGTTGGATGCTAATACATCAGCAAGCAATG CAGCAAGCAATGCTGATAA ACGTTGGATGTGAAGACACCCATCATGTTC ACGTTGGATGTCTGGACTTGCATTTCCGAC CCCATTTCCGACTTCATTACC ACGTTGGATGTCAGAAGTGGGCTTTTTTGC ACGTTGGATGCCTCATTCTGTTCTTCTAGC TCTTCTAGCCTTTTCTCATTTT ACGTTGGATGTCAAGTGGGACAGTGATCAG ACGTTGGATGATCAGCCCACTTGTGCTTTC CTACTTACTCCGTCAGC ACGTTGGATGCTTTGCCCTGGAGAAACCTG ACGTTGGATGAGGATCACTTGTGCCTTAC CTCGCACTTGTGCCTTACAGAATCC ACGTTGGATGTTGACTATCACAGGCTTCCC ACGTTGGATGAGGCTGCCTACCTGTCAAAC TTGTCAAACTCCACATTCTCAA

UCSC Browser, Feb 2009; http://genome,ucsc.edu/cgi-bin/hgGateway.

were analyzed using the software program Haploview 4.1 (Barrett et al., 2005) and the software program Epi_Info (http://www.cdc.gov/ epiinfo/). Genotype frequencies, genetic models and haplotype frequencies were estimated using the software program PLINK, version 2.05 (Purcell et al., 2007). Haplotype frequencies that were less than 3% in both case and control subjects were excluded from further analysis. Bonferroni corrections were applied to all multiple statistical tests. We applied Bonferroni correction to single-marker analysis for 11

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tests and to haplotype analysis for tests of haplotype numbers plus 11 allelic comparisons. Statistical power of the case–control sample was calculated using the G*Power program (Faul et al., 2007). The sample had >88% power (two-tail) to detect a significant association (α = 0.05), when an effect size index corresponding to a “weak” effect (0.2) was used. The structural and functional effects of non-synonymous variants on CMYA5 were predicted by the software program PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/) (Adzhubei et al., 2010). Recent association studies that included rs3828611 and rs10043986 were summarized and allele frequencies of the control samples of this study and the available data in the HapMap website were used to compare the difference in allele frequencies between populations. 3. Results The primers of genotyping for each SNP are listed in Table 1. We found 8 SNPs to be lower variants (MAF b 1%) and excluded them from further analyses. Of the 13 SNPs, rs1428225 and rs2278239 were not in HWE (P b 0.05) and were not examined further, and the other SNPs, rs7714250, rs4371733, rs1366271, rs16877133, rs16877135, rs13158477, rs28362541, rs3828611, rs12514461, rs1129770 and rs4704591, were all in HWE (P > 0.05) in both case and control samples. Statistical analyses of the 11 markers are presented in Table 2 (allele analysis) and Table 3 (genotype analysis). In the analysis of allele frequency distribution between patients and healthy controls, rs7714250, rs16877135 and 13158477 showed significant differences (Puncorrected = 0.008, Puncorrected = 0.04 and Puncorrected = 0.009, respectively). The latter two SNPs were non-synonymous variants and their corresponding amino acid alterations were predicted to be benign by PolyPhen-2. After multiple-testing correction, rs7714250 showed a trend of association with schizophrenia (Pcorrected = 0.088), as well as rs13158477 (Pcorrected = 0.099). In the Cochran–Armitage trend test, rs7714250, rs16877135 and rs13158477 also showed significant association with the disorder (Puncorrected = 0.008, Puncorrected = 0.037 and Puncorrected = 0.011, respectively), and after Bonferroni correction, rs7714250 also showed a trend of association with the disorder (Pcorrected = 0.088). Moreover, in the genetic model analysis (Table 3), a significantly positive result was observed for the C-allele genotypes of rs7714250 in the dominant model (Puncorrected = 7.9e-006), and the C-allele frequency of rs7714250 was increased in cases compared with controls. After Bonferroni correction, the difference observed for rs7714250 (Pcorrected = 8.7e-005) remained significant. The results of the pair-wise LD are shown in Fig. 1. Strong pair-wise linkage disequilibrium demonstrated that rs16877133– rs16877135 as well as rs28362541–rs3828611 were in two different

haplo-blocks (r2 = 0.87 and r2 = 0.92, respectively), therefore we selected rs16877135 and rs3828611 as the relevant tagging markers for haplotype analysis. Several two-, three-, four-, and five-SNP tests of haplotype association were significantly positive (Table 4). Haplotypes containing the C-allele of rs7714250 were higher in frequency in cases compared to controls. After Bonferroni correction, most of the corrected P values remained significant (Table 4). Of the three recent association studies involving SNPs of CMYA5, two provided detailed data for rs3828611 and rs4704594 obtained from Han Chinese samples. When we combined all the samples of Han Chinese origin, a significant difference was found between patients and controls for rs3828611 (Pcorrected = 0.004), and this SNP showed the same direction of association for the C-allele in different population sample sets. SNP rs4704594 was not associated with schizophrenia in the Chinese samples, in contrast to the significant association found in studies utilizing samples of European origin (Table 5). In addition, the MAF of these SNPs were similar between Chinese samples, especially the northern China and western China, whereas they were very different between the Han Chinese and the European (rs3828611: ~ 43.5% vs. 5.8%; rs4704594: ~ 23.5% vs. 38.6%). 4. Discussion Chen et al. adapted a two-stage approach, leading to the identification of the association of SNPs rs10043986 and rs4704591 of CMYA5 with schizophrenia. In the first stage of GWA data-mining analyses the procedures they employed combined statistical and biological evaluations of markers with emphasis on the relevance of potential functions in disease. SNP rs3828611 was also identified in the first stage, however it failed to replicate in a case–control and family study utilizing Irish samples (Chen et al., 2011). Li et al. observed a strong association of rs3828611 with schizophrenia in southern Han Chinese samples from Kunming and Yuxi, but did not observe an association for northern Han Chinese samples from Beijing (Li et al., 2011). The varying results within and between populations are indicative of genetic heterogeneity. When we compared the MAF of the two common SNPs of rs3828611 and rs4704591 in these three studies, the results also reflected a similar genetic heterogeneity among samples of different ethnic origin. In the current study, we analyzed 11 common SNPs across CMYA5 in the western Han Chinese population from Shaanxi province. Of these SNPs, rs7714250, rs16877135 and rs13158477 showed significant allelic differences between cases and controls, whereas after multipletesting correction, only rs7714250 and rs13158477 demonstrated a trend of association with schizophrenia. In the genetic model analysis, a significantly positive result was observed for the C-allele genotypes of rs7714250 in the dominant model (Pcorrected = 8.7e-005).

Table 2 Allelic analysis of selected SNPs in CMYA5. Marker

rs7714250 rs4371733 rs1366271 rs16877133 rs16877135 rs13158477 rs28362541 rs3828611 rs12514461 rs1129770 rs4704591

CMYA5

Intron 1 Intron 1 Exon 2 Exon 2 Exon 2 Exon 2 Exon 2 Exon 2 Exon 4 Exon 11 3′ near gene

Positiona

78,993,484 79,010,573 79,025,634 79,028,513 79,028,586 79,028,726 79,032,666 79,034,662 79,041,057 79,086,883 79,103,471

Alleleb

TC CT AG GA TC CA TC GC GA AG CG

Frequency (%) Cases

Controls

73.3 60.7 55.5 55.8 57.8 98.9 56.5 56.5 7.3 89.6 78.7

67.9 59.3 53.9 53.5 53.3 97.3 54.3 54.4 5.8 88.9 76.1

AA: amino acid. a UCSC Browser, Feb 2009; http://genome,ucsc.edu/cgi-bin/hgGateway. b The allele with increased frequency in cases compared to controls is underlined. c Significant P values (b0.05) are in boldface.

X2

P-valuec

Corrected P-value

7.06 0.41 0.50 1.11 4.21 6.78 0.99 0.93 1.62 0.27 1.80

0.008 0.522 0.479 0.292 0.040 0.009 0.320 0.335 0.203 0.605 0.180

0.088

0.44 0.099

PolyPhen-2 prediction AA change

Effect

p.G349D p.I1309V p.A1333V p.I1380V p.T2693I p.H3358Q p.K3583E p.R3927Q

Benign Benign Benign Benign Benign Benign Probably damaging Probably damaging

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Table 3 Analysis of the genetic models. Marker

Sample

Genotypea

11 rs7714250 rs4371733 rs1366271 rs16877133 rs16877135 rs13158477 rs28362541 rs3828611 rs12514461 rs1129770 rs4704591 a b c d e f g

Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls

248 247 169 175 143 145 146 142 159 139 461 480 142 143 141 147 3 0 380 399 284 290

Genetic modelb

Cochran–Armitage trend test 12 215 201 248 252 249 261 243 254 243 262 10 25 261 268 263 264 63 60 93 105 167 186

22 22 64 66 81 90 105 90 107 83 106 0 1 79 99 78 102 409 454 3 4 16 27

X

2

Dominant model c

P value

6.93

0.008

1.02

d

X

2

P value

Recessive model c e

X2

P valuec

0.78

0.378

19.96

7.9e-006

0.535

0.99

0.319

0.02

0.891

0.53

0.468

0.53

0.466

0.22

0.640

1.13

0.287

0.94

0.331

0.60

0.439

2.31

0.128

3.40

0.065

f

4.35

0.037

6.54

0.011g

NA

NA

NA

NA

1.08

0.30

1.54

0.215

0.24

0.621

1.0

0.317

2.30

0.130

0.43

0.835

1.68

0.195

NA

NA

NA

NA

0.28

0.597

NA

NA

NA

NA

1.81

0.179

2.14

0.144

0.95

0.330

1: The allele with increased frequency in cases compared to controls; 2: The allele with decreased frequency in cases compared to controls. NA: Not Applicable. Significant P values (b0.05) are in boldface. Corrected P value = 0.088. Corrected P value = 8.7e-005. Corrected P value = 0.407. Corrected P value = 0.121.

In the analysis of haplotype frequencies, significant association was found in global haplotype comprised of two-, three-, four-, and five-SNP. The C-allele frequency of rs7714250 was increased in cases

and associated haplotypes containing the C-allele of rs7714250 were higher in frequency in cases compared to controls, suggesting this allele may be a risk factor in the disorder. According to the existing studies,

Fig. 1. LD between markers genotyped in the CMYA5 locus in a western Han Chinese sample. LD structure (r2) between marker pairs is indicated by the shaded matrices. The figure was generated using Haploview 4.1.

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Table 4 Estimated frequency of haplotype and association significance. No. of Markers

2

3 4 5 a b

Global Pa

Haplotype

rs7714250–rs4371733 rs16877133–rs16877135 rs16877135–rs13158477 rs13158477–rs28362541 rs28362541–rs3828611 rs7714250–rs4371733–rs1366271 rs16877135–rs13158477–rs3828611 rs7714250–rs4371733–rs1366271–rs16877135 rs16877135–rs13158477–rs3828611–rs12514461 rs7714250–rs4371733–rs1366271–rs16877135–rs13158477 rs16877135–rs13158477–rs3828611–rs12514461–rs1129770

0.037 0.002 0.002 0.008 >0.05 0.0003 1.26e-013 9.16e-012 8.11e-013 1.53e-011 1.38e-011

Alleles increasing in cases

C–T A–C C–A A–C C–C C–T–G T–A–C C–T–G–T C–A–G–A C–T–G–T–A C–A–G–A–G

Estimated haplotype frequency (%) Cases

Controls

46.79 55.46 56.40 56.14 56.64 22.39 14.42 12.06 15.23 12.24 13.53

41.59 51.31 50.80 51.96 54.45 15.89 8.74 6.22 7.41 6.42 6.81

P valuea

P valuea,b (corrected)

0.020 0.067 0.014 0.067 0.332 0.0002 6.97e-005 6.74e-006 3.43e-008 1.08e-005 7.89e-007

>0.05 >0.05

0.0038 0.0011 1.55e-004 6.17e-007 2.48e-004 1.66e-005

Significant P values (b0.05) are in boldface. Corrected P-value derived using the multiple test correction.

the haplotype linkage disequilibrium test has higher power and is more robust than the corresponding single-marker LD tests (Akey et al., 2001; Clayton and Jones, 1999). Associations may be missed because of the incomplete information provided by individual SNPs; negative results do not rule out association involving other nearby SNPs; and positive results do not always indicate the discovery of the causal SNP, but may simply be a marker in LD with at least one causal variant (Daly et al., 2001). Our results suggest that the haplotypes may encompass the susceptibility variant(s) for schizophrenia. The discrepancy in results of the SNPs between studies could be explained by the different genetic background of the study populations. For the non-synonymous variants, the predicted function of alteration of rs13158477 suggested benign in the current study, and Li et al. also indicated that rs3828611 itself may not have any functional role, but may be linked to the causal SNP (Li et al., 2011). Therefore, our results are consistent with the findings of two previous reports for the association of CMYA5 with schizophrenia, and that the genetic markers we analyzed may be mere indicators of the association. Evidence suggests that the product of CMYA5, or myospryn (cardiomyopathy-associated protein 5), directly interacts with proteins of two pathways that have also been reported to contribute to the development of schizophrenia. Myospryn is a large protein (423-kDa protein) that belongs to the superfamily of tripartite-motif (TRIM) proteins. A Y2H screen indicated that myospryn binds with the product of

DTNBP1, or dysbindin (Benson et al., 2004; Ghiani and Dell'Angelica, 2011), which is an essential component of BLOC-1 (biogenesis of lysosome-related organelles complex 1) (Wei, 2006). Both DTNBP1 (Ayalew et al., 2012; Ghiani and Dell'Angelica, 2011; Owen et al., 2004; Straub et al., 2002; Williams et al., 2005) and BLOC-1 have also been reported to be involved in the pathogenesis of schizophrenia (Ghiani et al., 2010; Gokhale et al., 2012; Morris et al., 2008), hence, myospryn may potentially contribute along this pathway. Additionally, myospryn has also been reported to interact with proteins of the cAMP signaling transduction pathway, which have been reported to exhibit altered levels in schizophrenia patients (Molteni et al., 2009; Tardito et al., 2000). Specifically, studies suggest that myospryn interacts with protein kinase A (PKA) in the form of: a substrate, an anchor protein, and with a type II regulatory subunit (RIIα) of PKA (Reynolds et al., 2007, 2008). Hence, indicating another potential pathway that myospryn, or CMYA5, may contribute to the pathophysiology of schizophrenia. In summary, the allele distribution of the CMYA5 SNP rs7714250 was significantly different between schizophrenia patients and healthy controls, and the haplotype analysis indicated a strong association between CMYA5 and schizophrenia in the Han Chinese population. In consideration of the association of CMYA5 detected utilizing samples of various Han Chinese origin and European origin, in spite of potential genetic heterogeneity, it is very likely a potential common schizophrenia-relate

Table 5 Comparison of two SNPs (rs3828611 and rs4704591) between current and previous studies. Polymorphism

Studies

Ethnicity

Sample

MAFa in control (allele)

Risk allele

P valueb

rs3828611 (G/C)

Current study Li et al. (2011)

Chinese (western) Chinese (southern) Chinese (northern) European American CEU (European) CHB (Chinese) Chinese (western) Chinese (southern) Chinese (northern) European American CEU (European) CHB (Chinese)

Case–control Case–control Case–control Case–control Control Control Case–control Case–control Case–control Case–control Control Control

0.435 0.425 0.441 0.058 0.066 0.441 0.239 0.230 0.234 0.386 0.350 0.252

C C C Unknown Unknown Unknown G G G Unknown Unknown Unknown

0.335 b1.0 × 10−5 >0.05 0.022 Unknown Unknown 0.180 >0.05 >0.05 0.0003 Unknown Unknown

Chen et al. (2011) Hapmapd rs4704591 (C/G)

Current study Li et al. (2011) Chen et al. (2011) Hapmapd

a b c d

MAF: Minor Allele Frequency. Significant P value (b0.05) are in boldface. Corrected P value = 0.004. Hapmap: http://hapmap.ncbi.nlm.nih.gov/.

(G) (G) (G) (G) (G) (G) (C) (C) (C) (C) (C) (C)

P valueb (combined Chinese) 0.002c

>0.05

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gene worldwide. Further studies of the molecular basis of this gene in relationship to the complex pathways underlying schizophrenia pathogenesis are warranted. Acknowledgments We are indebted to all individuals who have participated in, or helped with, our research. This study was supported by funding from the Fundamental Research Funds for the Central Universities (No. 2012JDGZ07, No. XJJ2012124); the Key Project of International Scientific Cooperation of Shaanxi Province (No. 2013KW25-02) and the National Natural Science Foundation of China (No. U1202225). Reference Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Nat Methods 2010;7: 248–9. Akey J, Jin L, Xiong M. Haplotypes vs single marker linkage disequilibrium tests: what do we gain? Eur J Hum Genet 2001;9:291–300. Ayalew M, Le-Niculescu H, Levey DF, Jain N, Changala B, Patel SD, et al. Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction. Mol Psychiatry 2012;17:887–905. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21:263–5. Benson MA, Tinsley CL, Blake DJ. Myospryn is a novel binding partner for dysbindin in muscle. J Biol Chem 2004;279:10450–8. Chen X, Lee G, Maher BS, Fanous AH, Chen J, Zhao Z, et al. GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia. Mol Psychiatry 2011;16:1117–29. Clayton D, Jones H. Transmission/disequilibrium tests for extended marker haplotypes. Am J Hum Genet 1999;65:1161–9. Craddock N, O'Donovan MC, Owen MJ. The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J Med Genet 2005;42:193–204. Daly MJ, Rioux JD, Schaffner SF, Hudson TJ, Lander ES. High-resolution haplotype structure in the human genome. Nat Genet 2001;29:229–32. Devon RS, Anderson S, Teague PW, Burgess P, Kipari TM, Semple CA, et al. Identification of polymorphisms within Disrupted in Schizophrenia 1 and Disrupted in Schizophrenia 2, and an investigation of their association with schizophrenia and bipolar affective disorder. Psychiatr Genet 2001;11:71–8. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007;39:175–91. Ghiani CA, Dell'Angelica EC. Dysbindin-containing complexes and their proposed functions in brain: from zero to (too) many in a decade. ASN Neuro 2011;3:109–24. Ghiani CA, Starcevic M, Rodriguez-Fernandez IA, Nazarian R, Cheli VT, Chan LN, et al. The dysbindin-containing complex (BLOC-1) in brain: developmental regulation, interaction with SNARE proteins and role in neurite outgrowth. Mol Psychiatry 2010;15:204–15.

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Gokhale A, Larimore J, Werner E, So L, Moreno-De-Luca A, Lese-Martin C, et al. Quantitative proteomic and genetic analyses of the schizophrenia susceptibility factor dysbindin identify novel roles of the biogenesis of lysosome-related organelles complex 1. J Neurosci 2012;32:3697–711. Li M, Luo XJ, Zhang X, Yang ZH, Xiang K, Xiao X, et al. A common variant of the cardiomyopathy associated 5 gene (CMYA5) is associated with schizophrenia in Chinese population. Schizophr Res 2011;129:217–9. Ma J, Qin W, Wang XY, Guo TW, Bian L, Duan SW, et al. Further evidence for the association between G72/G30 genes and schizophrenia in two ethnically distinct populations. Mol Psychiatry 2006;11:479–87. Molteni R, Calabrese F, Racagni G, Fumagalli F, Riva MA. Antipsychotic drug actions on gene modulation and signaling mechanisms. Pharmacol Ther 2009;124: 74–85. Morris DW, Murphy K, Kenny N, Purcell SM, McGhee KA, Schwaiger S, et al. Dysbindin (DTNBP1) and the biogenesis of lysosome-related organelles complex 1 (BLOC-1): main and epistatic gene effects are potential contributors to schizophrenia susceptibility. Biol Psychiatry 2008;63:24–31. O'Donovan MC, Craddock N, Norton N, Williams H, Peirce T, Moskvina V, et al. Identification of loci associated with schizophrenia by genome-wide association and follow-up. Nat Genet 2008;40:1053–5. Owen MJ, Williams NM, O'Donovan MC. Dysbindin-1 and schizophrenia: from genetics to neuropathology. J Clin Invest 2004;113:1255–7. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559–75. Reynolds JG, McCalmon SA, Tomczyk T, Naya FJ. Identification and mapping of protein kinase A binding sites in the costameric protein myospryn. Biochim Biophys Acta 2007;1773:891–902. Reynolds JG, McCalmon SA, Donaghey JA, Naya FJ. Deregulated protein kinase A signaling and myospryn expression in muscular dystrophy. J Biol Chem 2008;283: 8070–4. Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA, et al. Genome-wide association study identifies five new schizophrenia loci. Nat Genet 2011;43:969–76. Shi Y, Li Z, Xu Q, Wang T, Li T, Shen J, et al. Common variants on 8p12 and 1q24.2 confer risk of schizophrenia. Nat Genet 2011;43:1224–7. Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 2007;445:881–5. Straub RE, Jiang Y, MacLean CJ, Ma Y, Webb BT, Myakishev MV, et al. Genetic variation in the 6p22.3 gene DTNBP1, the human ortholog of the mouse dysbindin gene, is associated with schizophrenia. Am J Hum Genet 2002;71:337–48. Tardito D, Tura GB, Bocchio L, Bignotti S, Pioli R, Racagni G, et al. Abnormal levels of cAMP-dependent protein kinase regulatory subunits in platelets from schizophrenic patients. Neuropsychopharmacology 2000;23:216–9. Wei ML. Hermansky–Pudlak syndrome: a disease of protein trafficking and organelle function. Pigment Cell Res 2006;19:19–42. Williams NM, O'Donovan MC, Owen MJ. Is the dysbindin gene (DTNBP1) a susceptibility gene for schizophrenia? Schizophr Bull 2005;31:800–5. Yue WH, Wang HF, Sun LD, Tang FL, Liu ZH, Zhang HX, et al. Genome-wide association study identifies a susceptibility locus for schizophrenia in Han Chinese at 11p11.2. Nat Genet 2011;43:1228–31. Zhang XJ, Huang W, Yang S, Sun LD, Zhang FY, Zhu QX, et al. Psoriasis genome-wide association study identifies susceptibility variants within LCE gene cluster at 1q21. Nat Genet 2009;41:205–10. Zheng W, Long J, Gao YT, Li C, Zheng Y, Xiang YB, et al. Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1. Nat Genet 2009;41:324–8.