• 6p22.1;
  • HIST1H2BJ;
  • PGBD1;
  • PRSS16;
  • schizophrenia


  1. Top of page
  2. Abstract
  8. Supporting Information

Recent GWAS demonstrated an association between candidate genes located at region 6p22.1 and schizophrenia. This region has been reported to house certain candidate SNPs, which may be associated with schizophrenia at HIST1H2BJ, PRSS16, and PGBD1. These genes may presumably be associated with pathophysiology in schizophrenia, namely epigenetics and psychoneuroimmunology. A three-step study was undertaken to focus on these genes with the following aims: (1) whether these genes may be associated in Japanese patients with schizophrenia by performing a 1st stage case–control study (514 cases and 706 controls) using Japanese tagging SNPs; (2) if the genetic regions of interest for the disease from the 1st stage of analyses were found, re-sequencing was performed to search for new mutations; (3) finally, a replication study was undertaken to confirm positive findings from the 1st stage were reconfirmed using a larger number of subjects (2,583 cases and 2,903 controls) during a 2nd stage multicenter replication study in Japan. Genotyping was performed using TaqMan PCR method for the selected nine tagging SNPs. Although three SNPs situated at the 3′ side of PGBD1; rs3800324, rs3800327, and rs2142730, and two-window haplotypes between rs3800327 and rs2142730 showed positive associations with schizophrenia, these associations did not have enough power to sustain significance during the 2nd stage replication study. In addition, re-sequencing for exons 5 and 6 situated at this region did not express any new mutations for schizophrenia. Taken together these results indicate that the genes HIST1H2BJ, PRSS16, and PGBD1 were not associated with Japanese patients with schizophrenia. © 2012 Wiley Periodicals, Inc.


  1. Top of page
  2. Abstract
  8. Supporting Information

Although rare, schizophrenia is a debilitating disease with a prevalence of approximately 0.5–1% within a given population. Accordingly, several studies have investigated the etiology of schizophrenia and conducted genetic analyses to identify specific candidate genes involved in the heritability of schizophrenia. Recent genome-wide association studies (GWAS) have shown that certain candidate genetic regions were associated with schizophrenia (see SZGene section of Schizophrenia Research Forum; Within the last decade, these studies, employing reliable methods such as meta-analyses and GWAS, demonstrated the existence of an association with schizophrenia at the 6p region [Schwab et al., 2000], and more recently at the 6p22.1 region [Shi et al., 2009; Stefansson et al., 2009]. In this region, the previous GWAS may demonstrate that some candidate single nucleotide polymorphisms (SNPs) may be associated with schizophrenia within a Caucasian population; the SNPs—rs6913660, rs13219354, rs6932590, and rs13211507 are situated at the following genes (or situated at a transition substitution region within a genomic SNP): Histone cluster 1, H2bj (HIST1H2BJ), protease serine 16 (thymus) (PRSS16), and piggyBac transposable element derived 1 (PGBD1), respectively [Shi et al., 2009; Stefansson et al., 2009]. In addition to genetic candidates, the genes within this region may be associated with a presumed pathophysiology for schizophrenia, namely epigenetics [Kan et al., 2004; Sharma, 2005; Mill et al., 2008; Akbarian and Huang, 2009; Iwamoto and Kato, 2009; Rutten and Mill, 2009; Pidsley and Mill, 2011] including transposons [Yolken et al., 2000; Lewis, 2001; Karlsson et al., 2004; Huang et al., 2006; Perron et al., 2008], psychoneuroimmunology [Muller et al., 1999; Miuller and Schwarz, 2007], and their interactions [Muller and Dursun, 2011].

Epigenetics has been implicated in several complex diseases including schizophrenia [Akbarian et al., 1996]. Indeed, parallel to findings from genetic studies, environmental factors have also been implicated to play an integral role in schizophrenia. Namely, hypotheses regarding changes in gene expression/protein activity reported in the brains of schizophrenia have been suggested to occur through epigenetic mechanisms without any alternations within the DNA sequence. A recent comprehensive study on methylation profiling investigated the epigenetic mechanisms reported an altered methylation status within patients with major psychosis [Mill et al., 2008]. In schizophrenia, abnormal DNA or histone methylation at specific gene sites and promoters may be associated with changes in RNA expression in the prefrontal cortex [Akbarian et al., 2005; Huang and Akbarian, 2007; Huang et al., 2007; Akbarian, 2010a, b]. Thus, histones thereby play a central role in transcription regulation, DNA repair, DNA replication, and chromosomal stability, functions which may be disrupted in the brains of patients with schizophrenia [Akbarian, 2010b]. The gene, HIST1H2BJ, has been purported to be implicated in schizophrenia research through both genetic and environmental factors. HIST1H2BJ has been found in the histone microcluster of chromosome 6p21.33 and is said to be intronless and encodes a member of the histone H2B family, which is one of the core components of nucleosome [Wyrick and Parra, 2009]. The second gene, PRSS16, is situated at 6p22–p21.3 near the major histocompatibility complex (MHC) class I region, and contains 12 exons and a serine protease expressed exclusively within the thymus. It is also thought to play an integral role in the alternative antigen-presenting pathway. MHC is purported to be associated with neuropsychoimmunological pathophysiology in schizophrenia [Samaroo et al., 2010; Kano et al., 2011; Singh et al., 2011]. Furthermore, considerable attention has been given to MHC candidate gene associated with schizophrenia in GWAS and especially with brain morphology [Agartz et al., 2011; Williams et al., 2011]. Previously, a case–control study using an Asian population showed an association between MHC and schizophrenia [Li et al., 2010]. The third gene, PGBD1, falls within one of the families of transposases related to transposons, and belongs to the subfamily of PGBD genes. This gene product is specifically expressed within the brain; however, its exact function is still unknown, but is purportedly involved in Alzheimer disease [Belbin et al., 2011]. Transposons are said to be involved in the development of schizophrenia. Specifically, human endogenous retroviruses (HERVs) related to transposons may be emerging pathogens in schizophrenia [Karlsson et al., 2001; Karlsson et al., 2004; Frank et al., 2005; Huang et al., 2006; Yao et al., 2008]. As previously demonstrated, DNA methylation has been involved in the mechanism of retroposon [Kuramochi-Miyagawa et al., 2008; Reuter et al., 2009]. Thus, PGBD1 may be related to an important aspect of the pathophysiology of schizophrenia as in epigenetics, especially in retroposon.

The present study aimed to investigate the following three genes which have previously been implicated in GWAS of schizophrenia: HIST1H2BJ, PRSS16, and PGBD1 at 6p22.1 using a Japanese sample of patients with schizophrenia. Thus, the present study's aims were threefold: (1) examine whether the aforementioned genes were associated with schizophrenia in Japanese patients by performing a 1st stage case–control genetic study using Japanese common tag SNPs; 2) if positive associations and coding regions were found within the genetic region(s) of interest for the disease during the 1st stage of the study, then re-sequencing was performed to search for new mutations in schizophrenia within Japanese patients; and 3) finally, positive findings from the 1st stage were reconfirmed using a 2nd stage replication study including a larger number of patients and controls.


  1. Top of page
  2. Abstract
  8. Supporting Information


For the 1st stage of the study, a case–control genetic association was performed using 514 unrelated Japanese patients with schizophrenia (279 males, 235 females; mean age 39.2 years, S.D. ± 13.5). All patients met criteria for schizophrenia based on structured clinical interviews from the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). A total of 706 healthy controls (335 males, 371 females; mean age 46.1 years, S.D. ± 17.9) were also included and examined. Healthy controls did not meet current or past criteria for any Axis I disorder (from the DSM-IV). Additionally, all participants met the following criteria: (1) no evidence of systemic or neurological diseases; (2) no prior head trauma with loss of consciousness; and 3) no lifetime history of alcohol or substance dependency. Patients and controls were recruited from two geographic regions in Japan: Saitama and Tokyo. For the 1st stage case–control genetic study, the mean age for the patients with schizophrenia was significantly lesser than that of the control group (Student's t-test: t = 7.33, P < 0.001). Additionally, the distribution between males and females within the two groups was significantly different (χ2 = 5.55, P = 0.018).

During the 2nd stage replication study, positive findings obtained from the 1st stage were further investigated using a stage 2 case–control genetic association study as a multicenter study in Japan. Analyses were performed using 2,583 unrelated Japanese patients with schizophrenia [1,397 males, 1,168 females (information on sex for 18 patients was missing); with a mean age of 46.4 years, S.D. ± 15.6] who met DSM-IV criteria for a diagnosis of schizophrenia. A total of 2,903 unrelated healthy controls were also recruited [1,324 males, 1,578 females (information on sex for one control subject was missing); with a mean age of 45.8 years, S.D. ± 18.9]. Patients and controls were recruited using the same criteria for the 1st stage of the study from the following four geographic regions of Japan: Osaka, Aichi, Saitama, and Tokyo. Of these participants, 514 patients with schizophrenia and 706 healthy controls were analyzed during the 1st stage study; the remaining patients and controls were new to the 2nd stage replication study. The mean age between patients and controls were not significantly different, but the distribution of males and females within the two groups was significantly different (χ2 = 42.6, P < 0.001). Written informed consent was obtained from all subjects after the procedures had been fully explained. The present study was carried out in compliance to the World Medical Association's Declaration of Helsinki and approved by the Research Ethical Committees of Juntendo University, Osaka University, Fujita Health University, and Nagoya University.

SNP Selection and Genotyping

Genomic DNA was extracted from peripheral white blood cells using a QIAamp® DNA Blood Maxi kit (Qiagen, Courtaboeuf, France). For the selection of SNPs, tag SNPs for each gene [r2 > 0.8, minor allele frequencies (MAF) > 0.05] were chosen from the International HapMap Project database (release 27 PhaseII + III, Feb 2009, on NCBI B36 assembly, dbSNP b126) using the TAGGER algorithm with a successful TaqMan probe design. Additionally, if the MAF was >0.05, reported missense SNPs were also chosen as candidate SNPs within the three genes from the dbSNP database ( Although HIST1H2BJ did not display missense SNPs, two missense mutations; rs5030965 in PRSS16 (G > T, Ser104Ile) was previously found with an MAF > 0.05 in an African-American population, rs3800324, (G > A, Gly244Glu) in PGBD1 and showed an MAF > 0.05 within a Japanese population. Therefore, these SNPs were also analyzed using TaqMan® technology (Assay-by-Design™). Thus, the following nine SNPs were investigated for the HIST1H2BJ gene: rs6456469 and rs6456768, PRSS16; rs5030965, rs10946904, and rs2295603, PGBD1: rs2142731, rs3800324, rs3800327, and rs2142730 (the “rs” notation in front of each SNP represents the identification from the US National Center for Biotechnology Information SNP cluster within the dbSNP database; As previously noted, rs5030965 found in PRSS16 and rs3800324 found in PGBD1 were missense SNPs, rs6456769 was located in the upstream of HIST1H2BJ and covered the 5′ side of this gene, similar to intron 1 of an adjoining family gene, HIST1H2K. All other SNPs were intronic tag SNPs. The distance between each SNP, the genomic structure, and the location of the investigated SNPs are presented in Figure 1. All investigated SNPs were typed using TaqMan® technology using an ABI7500 system (Applied Biosystems, Foster City, CA). All probes and primers were designed by the Assay-by-Design™ service for Applied Biosystems. The polymerase chain reaction (PCR) was done using the standard PCR MasterMix reagent kit using a 4-µl volume. Additionally, to ensure the quality of the results, we confirmed the SNPs from a few randomly chosen subjects using a direct DNA sequencing method to check for errors through the TaqMan method (see Supplement 1). All genotypes determined by direct sequencing were in agreement with the genotypes obtained from TaqMan methods for all investigated SNPs. Detailed information on PCR conditions and primer pairs is available upon request.

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Figure 1. The presentation of a genomic map (A) and structures of the human genes HIST1H2BJ (B), PRSS16 (C), and PGBD1 (D), including the location for the SNPs and linkage disequilibrium (D' value) between the SNPs of each gene. D' value between the SNPs are indicated in each diamond symbol for control subjects (left) and patients with schizophrenia (right). Exons are denoted by boxes, un-translated regions are presented in white, and translated regions are presented in black.

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Re-Sequencing of Coding Regions in Genetic Regions of Interests

Coding regions as well as exon–intron boundaries were considered to be genetic regions of interests based on results obtained from the 1st stage case–control study, and were further examined for disease-specific mutations through direct sequencing of the PCR methods. PCR primers for direct sequencing for these coding regions of interests were shown in electrical supplement materials (see Supplement 2). Detailed information on PCR conditions is available upon request. Sequencing of PCR products were performed by BigDye Terminator methods using a Sequencing Reaction Kit (Applied Biosystems, Foster City, CA) on an ABI7500 system (Applied Biosystems, Foster City, CA). Single strands from 24 patients with schizophrenia were read through this process.

Statistical Analysis

Differences in age between healthy controls and patients were examined using the two-tailed Student's t-test. Chi-square (χ2) tests were used to assess for differences in the distribution of males and females. For the case–control association study, Hardy–Weinberg equilibrium (HWE) tests for the SNPs was run using SNPAlyze Ver. 7.0 Pro (Dynacom, Yokohama, Japan). The HWE tests were carried out for all loci in patients and controls. Differences in genotypic and allelic frequencies were evaluated using χ2 difference tests. Linkage disequilibrium (LD), denoted as D′, was calculated from haplotype frequencies using an expectation–maximization algorithm. The LD block was also identified using SNPAlyse Ver. 7.0 Pro when D′ was greater than 0.75. Case–control haplotype analyses were also performed using SNPAlyse software. Permutation analyses were used to determine empirical significance and calculations for the P-values were based on 10,000 replications. Global P-values represented the overall significance for the χ2-difference tests when both the observed versus expected frequencies for all haplotypes were simultaneously considered. Additionally, individual haplotypes were tested for associations by grouping all other haplotypes together and running χ2-tests using 1 df. All reported P-values are two-tailed. Statistical significance was defined at P < 0.05.

Furthermore, power calculations were conducted using the Power Calculator for Two Stage Association Studies ( Power estimates were based on allelic frequencies for associated markers ranging from 0.20 (rs10946904) to 0.41 (rs3800327), with odds ratios ranging from 1.044 (rs2142731) to 1.228 (rs3800327) for the investigated SNPs with an alpha level of 0.05. Power was calculated using a prevalence rate below 0.01 with an additive or a multiplicative model, assuming various degrees of allelic frequencies and the odds ratios for the SNPs.


  1. Top of page
  2. Abstract
  8. Supporting Information

First Stage Genetic Case–Control Analyses

The minor allele (A) for the missense SNP, rs5030965 in PRSS16, was not found in Japanese participants (in 380 cases and 380 controls); thus, we concluded that this SNP was not a major SNP within the Japanese population and excluded it from further genetic analyses.

Ultimately, eight SNPs in HIST1H2BJ, PRSS16, and PGBD1 were genotyped in 514 patients with schizophrenia and in 706 controls with a genotyping completeness that ranged between 99.2 and 99.8%. Results for power analyses demonstrated that the power ranged from 7% (rs2142731) to 71% (rs3800327). A deviation from HWE was found in patients with rs6456768 (Table I). No other deviations from HWE in either patient or control samples were observed (all P > 0.05, Table I). While no single SNP in PRSS16 showed any significant association between their allelic or genotypic frequencies and schizophrenia; a SNP, rs6456768 in HIST1H2BJ, and three SNPs situated at the 3′ side of PGBD1; rs3800324, rs3800327, and rs2142730 resulted in a positive association with schizophrenia (Table I). After conducting strict tests for multiple comparisons, the results became insignificant (eight comparisons were performed, P < 0.00625 was considered as statistically significance using a Bonferroni correction).

Table I. Distribution and Statistical Analysis of the HIST1H2BJ, PRSS16, and PGBD1 Gene Polymorphisms, and Their Two, Three, and Four SNP-Based Haplotype Analyses
 Genotype frequency (%)P-valueHWE c/sAllele frequency (%)χ2P-valueOdds ratio (95%CI)Haplotype analysis (global P-value)
          2 SNP-based3 SNP-based4 SNP-based
  • *

    P < 0.05.

 schizophrenia223 (45.8)228 (46.8)36 (7.4)674 (69.2)300 (30.8)2.3190.1281.152 (0.960–1.381)   
 controls347 (52.6)258 (39.1)55 (8.3)952 (72.1)368 (27.9)   0.126  
 schizophrenia268 (55.0)190 (39.0)29 (6.0)726 (74.5)248 (25.5)3.4750.0621.203 (0.990–1.460)   
 controls402 (60.9)224 (33.9)34 (5.2)1,028 (77.9)292 (22.1)      
 schizophrenia291 (59.8)171 (35.1)25 (5.1)753 (77.3)221 (22.7)1.6640.1971.141 (0.934–1.395)   
 controls426 (64.5)198 (30.0)36 (5.5)1,050 (79.5)270 (20.4)   0.572  
 schizophrenia286 (58.7)176 (36.1)25 (5.1)748 (76.8)226 (23.2)1.9670.1611.153 (0.945–1.408)   
 controls423 (64.1)200 (30.3)37 (5.6)1,046 (79.2)274 (20.8)      
 schizophrenia291 (59.8)164 (33.7)32 (6.6)746 (76.6)228 (23.4)0.1820.671.044 (0.858–1.270)   
 controls390 (59.1)241 (36.5)29 (4.4)1,021 (77.3)299 (22.7)   0.130  
 schizophrenia191 (39.2)218 (44.8)78 (8.0)600 (61.6)374 (38.4)4.0470.044*1.193 (1.005–1.417) 0.121 
 controls285 (43.2)297 (45.0)78 (11.8)867 (65.7)453 (34.3)   0.052 0.385
 schizophrenia145 (29.8)232 (47.6)110 (22.6)522 (53.4)452 (46.4)5.7990.016*1.228 (1.039–1.450) 0.101 
 controls223 (33.8)328 (49.7)109 (16.5)774 (58.6)546 (41.4)   0.047*  
 schizophrenia246 (50.5)197 (40.5)44 (9.0)689 (70.7)285 (29.3)3.9920.046*0.833 (0.696–0.997)   
 controls294 (44.5)294 (44.5)72 (10.9)882 (66.8)438 (33.2)      

D′ > 0.75 was assumed to represent a strong LD, and results indicated that all investigated SNPs for each gene displayed a strong LD block in controls and patients with schizophrenia (see Fig. 1). Additionally, case–control haplotype association analysis using windows of two, three, or four SNPs were performed (minor haplotypes with frequencies less than 3% in both the schizophrenia cases and controls were omitted), and a two-window haplotype analysis between rs3800327 and rs2142730 in PGBD1, where each SNP may show significant associations in its genetic/allelic frequency with schizophrenia, again demonstrated a significant association with schizophrenia within its haplotype (see Table I); however, this significant effect disappeared after Bonferroni corrections were applied (with P < 0.01 considered to be statistically significant). For each haplotype, the frequency of haplotype CC, heterozygous for the minor–major allele demonstrated a significant increase and was denoted as a risky haplotype for schizophrenia [frequencies; in schizophrenia patients = 0.464, in healthy controls = 0.414, P = 0.016, odd's ratio (OR) = 0.82, 95% confidential interval (CI) = 0.69–0.96], while GT, heterozygous for the major–minor allele demonstrated a significant decrease and was a protective haplotype in schizophrenia [frequencies; schizophrenia = 0.293, controls = 0.332, P = 0.044, OR = 1.20, 95% CI = 1.06–1.44]. However, these results did not reach significance when using strict Bonferroni corrections (e.g., four haplotypes showed their frequencies more than 3% in both patients and controls, four-time comparisons were performed in two-window haplotype analysis; thus, P < 0.0125 was considered significant). In addition, three- and four-window haplotype analyses including these SNPs did not result in any associations. All other case–control haplotype associations including, three- and four-window haplotype analyses failed to show significant associations with schizophrenia (see Table I).

Re-Sequencing of Coding Regions Within Genetic Regions of Interests

The genetic regions consist of SNPs (rs3800324, rs3800327, and rs2142730), situated at the 3′ site of PGBD1, that showed marginal associations with schizophrenia in their genetic/allelic/haplotype frequencies (see Table I); these regions also contain two exons (exon 5 and 6). Thus, these coding regions and their exon–intron boundaries were considered to be genetic regions of interest for the disease, and were re-sequenced through PCR-direct sequencing to search for new mutations in Japanese patients with schizophrenia. Results from direct sequencing in exons 5 and 6 in the gene, PGBD1, in 24 patients with schizophrenia did not express any new mutations when compared to reported SNPs from the US National Center for Biotechnology Information SNP cluster from the dbSNP database; apart from an already known SNP, rs3800324, which was already included and analyzed in the present study (see Supplement 1).

Replication Analyses for Significant Findings Obtained During the 1st Stage Case–Control Genetic Study

To further investigate the marginally positive associations observed between three SNPs situated at the 3′ side of PGBD1 (rs3800324, rs3800327, and rs2142730) and schizophrenia, we reinvestigated the association between the three aforementioned SNPs and schizophrenia using adequate statistical power as a multicenter 2nd stage study in Japan. Power was calculated using a prevalence rate of 0.01 and below using an additive or a multiplicative model, which was based on allelic frequencies for associated markers that ranged from 0.33 (rs2142730) to 0.41 (rs3800327), while odds ratios ranged from 1.193 (rs3800324) to 1.228 (rs3800327) for the SNPs investigated during the 1st stage of analyses using an alpha level of 0.05. Results for power analyses exhibited sufficient power (>99%) for all three SNPs.

The three SNPs in PGBD1 were genotyped in 2,583 patients with schizophrenia and in 2,903 controls during a 2nd stage multicenter replication study. No deviations from HWE in either patients or controls were observed, and no single SNP showed a significant association between their allelic or genotypic frequencies and schizophrenia (see Table II). Similarly, the three SNPs showed a strong LD; however, the case–control haplotype association analyses (minor haplotypes with frequencies less than 3% in either group were omitted) using windows of two or three SNPs failed to show a significant association with schizophrenia in a Japanese population (Table II).

Table II. Distribution and Statistical Analysis of the Three SNPs on PGBD1 in 2nd Stage Replication Study
PGBD1Genotype frequency (%)P-valueAllele frequency (%)χ2P-valueOdds ratio (95%CI)Haplotype analysis (global P-value)
         2 SNP-based3 SNP-based
 schizophrenia1,097 (42.9)1,118 (43.7)343 (13.4)3,312 (64.7)1,804 (35.3)0.5810.4461.031 (0.953–1.116)  
 controls1,251 (43.2)1,288 (44.5)357 (12.3)3,790 (65.4)2,002 (34.6)   0.810 
 schizophrenia857 (33.5)1,221 (47.7)480 (18.8)2,935 (57.4)2,181 (42.6)0.4590.4981.027 (0.951–1.108) 0.613
 controls963 (33.3)1,434 (49.5)499 (17.2)3,360 (58.1)2,432 (41.9)   0.258 
 schizophrenia1,205 (47.1)1,094 (42.8)259 (10.1)3,504 (68.5)1,612 (31.5)2.6170.1050.936 (0.863–1.014)  
 controls1,294 (44.7)1,295 (44.7)307 (10.6)3,883 (67.9)1,909 (33.0)     


  1. Top of page
  2. Abstract
  8. Supporting Information

The present study investigated whether the genes, HIST1H2BJ, PRSS16, and PGBD1, which have previously been implicated in GWAS of schizophrenia situated at arisen region 6p22.1 from GWAS, are also associated with schizophrenia in Japanese patients. Prior to the discussion, we must mention some of the limitations of the present study. First, statistical type I or type II errors cannot be completely ruled out due to the small power obtained for some SNPs (e.g., rs2142731) in the 1st stage genetic case–control analysis. In addition, the difference in the mean age between the groups in the 1st stage case–control genetic study, and the difference in gender distribution between the two groups in the 1st and 2nd stage genetic case–control analyses were also limitations of the present study.

Although SNPs, rs6456768 in HIST1H2BJ, and three SNPs situated at the 3′ side of PGBD1; rs3800324, rs3800327, and rs2142730 showed a marginal positive association with schizophrenia, these effects could not sustain significance when using strict corrections for multiple comparisons. In addition, a two-window haplotype analysis using the aforementioned SNPs, between rs3800327 and rs2142730 in PGBD1 (where include two coding regions; exons 5 and 6) also showed a marginal association with schizophrenia. Thus, we focused on this genetic region and re-investigated these findings during a 2nd stage replication multicenter study with adequate statistical power. However, positive associations obtained in PGBD1 during the 1st stage could not demonstrate any significant replications. Furthermore, re-sequencing for exons 5 and 6 situated around the PGBD1 region did not express any new mutations related to schizophrenia. Taken together, these results suggest that the genes, HIST1H2BJ, PRSS16, and PGBD1 were not associated with schizophrenia or its genetic risk factors in Japanese patients. Although previous GWAS reported positive associations between these genes and schizophrenia, our large case–control replication study and results failed to replicate the results reported and found by other studies. A reason for this may be due to the fact that the reported heritability of complex, neuropsychiatric diseases, including schizophrenia may not be parallel to findings from molecular studies of neuropsychiatric diseases [So et al., 2011]. Researchers have referred to this phenomenon as the “missing heritability” [Crow, 2011], which should lead to studies investigating the role of environmental factors involved in the onset of diseases, especially since genetic factors have been found [Rutten and Mill, 2009; Pidsley and Mill, 2011]. Recent reports indicated that epigenetically related molecules (e.g., methyl CpG binding protein 2, DNA-methyltransferase) showed an association with neuropsychiatric diseases, such as schizophrenia and autism [Shibayama et al., 2004; Zhubi et al., 2009]. Moreover, genes such as brain-derived neurotrophic factors (BDNF) that alter their expression/protein activity through epigenetic mechanisms [Buckley et al., 2011] also show genetic associations (mainly with Val66Met missense mutation) with some clinical features (e.g., severity of symptoms, effects of pharmacological medications) of neuropsychiatric diseases such as cognitive function in schizophrenia [Zhang et al., 2012] and depressive symptoms in mood disorders [Tsai et al., 2010; Kocabas et al., 2011]. In addition, multiple polymorphism action (Val66Met and other SNPs in BDNF) [Sears et al., 2011] and gene–gene interaction (Val66Met in BDNF and polymorphisms in serotonin transporter-linked promoter regions) [Quinn et al., 2012; Wang et al., 2012] might be related not only to disease onset, but also to disease modifying factors. Thus, it may be beneficial to focus on and investigate the genetic association, as well as gene–gene interactions for these epigenetically related genes in schizophrenia using larger samples of participants. Additionally, it may be helpful to directly investigate altered epigenetic effects (or deliberately altering its status according to the clinical course of a disease; e.g., methylation; reelin, glutamic acid decarboxylase 67, sex-determining region Y-box containing gene 10, catechol-o-methyltransferase) in order to clarify the pathophysiology of schizophrenia [Dong et al., 2005; Murphy et al., 2005; Abdolmaleky et al., 2006; Tochigi et al., 2008; Nohesara et al., 2011]. Additionally, studies investigating both epidemiological and environmental risk factors for schizophrenia during the course of development (prenatal as well as during childhood/adolescence)—(e.g., paternal age, urban environment) may also be warranted [Rutten and Mill, 2009]. Finally, a combination of genetic–epigenetic–environmental risk factors and their interaction should be further investigated to help shed light on the key risk factors for this complex disease, schizophrenia.

In conclusion, the three candidate genes investigated, HIST1H2BJ, PRSS16, and PGBD1 located at 6p22.1 showed no significant associations with schizophrenia in Japanese patients per se.


  1. Top of page
  2. Abstract
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