Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

The genetic validation of heterogeneity in schizophrenia

The genetic validation of heterogeneity in schizophrenia Introduction: Schizophrenia is a heritable disorder, however clear genetic architecture has not been detected. To overcome this state of uncertainty, the SZGene database has been established by including all published case- control genetic association studies appearing in peer-reviewed journals. In the current study, we aimed to determine if genetic variants strongly suggested by SZGene are associated with risk of schizophrenia in our case- control samples of Japanese ancestry. In addition, by employing the additive model for aggregating the effect of seven variants, we aimed to verify the genetic heterogeneity of schizophrenia diagnosed by an operative diagnostic manual, the DSM-IV. Methods: Each positively suggested genetic polymorphism was ranked according to its p-value, then the seven top-ranked variants (p < 0.0005) were selected from DRD2, DRD4, GRIN2B, TPH1, MTHFR, and DTNBP1 (February, 2007). 407 Schizophrenia cases and 384 controls participated in this study. To aggregate the vulnerability of the disorder based on the participants’ genetic information, we calculated the “risk-index” by adding the number of genetic risk factors. Results: No statistically significant deviation between cases and controls was observed in the genetic risk-index derived from all seven variants on the top-ranked polymorphisms. In fact, the average risk-index score in the schizophrenia group (6.5+/-1.57) was slightly lower than among controls (6.6+/-1.39). Conclusion: The current work illustrates the difficulty in identifying universal and definitive risk-conferring polymorphisms for schizophrenia. Our employed number of samples was small, so we can not preclude the possibility that some or all of these variants are minor risk factors for schizophrenia in the Japanese population. It is also important to aggregate the updated positive variants in the SZGene database when the replication work is conducted. Keywords: schizophrenia, gene, Schizophrenia Gene Database (SZGene), heterogeneity, Japanese, DRD2, DRD4, GRIN2B, TPH1, MTHFR, DTNBP1, and Risk-Index Introduction expected to have a small effect on risk for the disorder. Schizophrenia is a highly heritable disorder, but even its Although many positive results were reported, most are genetic architecture still remains unclear [1]. In order to never replicated extensively. To overcome this state of reveal the genetic involvement in the etiology, several uncertainty, Bertram et al. assembled the SZGene data- research designs have been adopted. Linkage studies base to aggregate the evidence for those genetic poly- have not, however, found strongly linked loci [2]. Alter- morphisms with the best, most reliable evidence for natively, many association studies of schizophrenia have association with schizophrenia [3,4]. SZGene is charac- been performed because genetic association methods are terized by the inclusion of all published case-control a more powerful means for finding genes that are genetic association studies appearing in peer-reviewed journals, and each association is evaluated using a uni- form method of meta-analysis. This inclusive and con- * Correspondence: psy052@poh.osaka-med.ac.jp Department of Neuropsychiatry; Osaka Medical College; Osaka, Japan sistent database renders sometimes ambiguous or Full list of author information is available at the end of the article © 2011 Tsutsumi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 2 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 amorphous bodies of evidence concrete, and highlights committee at Osaka Medical College. The cases were some of the most promising avenues for continued recruited from inpatients in two mental hospitals and research by schizophrenia geneticists. From this data- oneuniversityhospitallocated in thewestern areaof base, we picked the most reliably associated variants, Japan, and the controls were recruited among hospital and sought to determine if these variants would be asso- staff. The details of the samples are described in the ciated with risk for schizophrenia in our own case-con- Table 2. No statistical difference was observed in the trol sample of Japanese ancestry. Consistent with a male/female ratio of the participants, while the patients common-disease/common-variant hypothesis of the dis- were significantly younger than the controls. All of the participants lived in the western area of Japan, and were order, we would not hypothesize that each variant iden- tified in SZGene would be a necessary component of self-reported ethnically Japanese. the risk profile for schizophrenia in our sample, so we With regard to the genotyping procedure, Single evaluated the independent and joint effects of the top nucleotide polymorphisms (SNPs) on the genomic DNA seven variants. The objectives of this study were: 1) to extracted from venous blood were identified by FRET determine if the top candidate genes for schizophrenia method (Roche Diagnostics, Japan) according to the would show replicated evidence for a contribution to manufacture’s protocol. The 120 bp Tandem Repeat risk for the disorder; and 2) to see if the aggregate effect polymorphism in DRD4 was detected by restriction frag- of these seven top variants was stronger than the indivi- ment length polymorphism. Each primer and probe was dual effects of each variant alone. provided on demand. In addition to the analysis of each single polymorph- Methods ism, we sought to aggregate the vulnerability of the dis- Based on the information in SZGene as of February order based on the participants’ genetic information. 2007, each positively associated genetic polymorphism The risk alleles of each of the seven top polymorphisms in the database was ranked according to its p-value shown in SZGene were summated, such that an indivi- from a chi-square test of association with the disorder. dual homozygous for a polymorphism’s risk alleles was The p-values of the seven top-ranked polymorphisms quantified as having a value of “2”. The heterozygous were all less than 0.005 (Table 1). We chose these seven genotype was given the value of “1”,and thehomozy- variants for the pragmatic reason of cost and effort. To gote of non-risk alleles was coded “0”.Thisscoring evaluate these selected polymorphisms, we recruited 407 imparted an additive effect onto each variant, which was patients diagnosed with schizophrenia by multiple psy- supported by the meta-analytic results in SZGene chiatric doctors according to DSM-IV TR criteria and (although this may not be the true mode of inheritance of each gene’s effect on risk, misspecification by an addi- 384 normal controls without any medical record in psy- chiatry. Every participant gave written and oral informed tive model is less costly than misspecification by other consent, and this study was approved by the ethical models). Each of the participants was additively scored Table 1 Derived data from SZGene for investigated genes and polymorphisms Gene Polymorphism Denomination p-value OR 95%CI Cases Control m/m m/M M/M Sum m/m m/M M/M Sum 1 DRD2 rs6277(C/T) 5.71.E-06 1.4 (1.2-1.63) 178 266 130 574 225 484 332 1041 2 DRD2 rs1801028(G/C) 8.24.E-06 1.34 (1.11-1.61) 9 270 3770 4049 8 254 5420 5682 3 GRIN2B rs1019385(T/G) (200T/G) 4.70.E-05 0.69 (0.54-0.88) 85 256 161 502 114 257 95 466 4 TPH1 rs1800532(A/C) 7.99.E-05 1.25 (1.08-1.44) 324 609 306 1239 344 851 513 1708 5 MTHFR rs1801133(T/C) (C677T) 2.15.E-04 1.14 (1.03-1.25) 490 1672 1708 3870 550 2265 2536 5351 6 DTNBP1 rs2619528(A/G) (P1765) 4.08.E-04 1.25 (1.01-1.56) 90 558 1049 1697 79 641 1485 2205 7 DRD4 120-bpTR(S/L) 3.80.E-03 0.81 (0.7-0.94) 55 374 807 1236 77 412 710 1199 8 PLXNA2 rs1327175(G/C) 0.043 0.76 (0.58-0.99) 12 221 1478 1711 15 280 1475 1770 9 DAOA rs3916971(T/C) 0.045 0.84 (0.73-0.96) 169 401 274 844 213 457 252 922 10 HP HP1/2 0.044 0.88 (0.8-0.98) 184 647 515 1346 324 995 699 2018 Abbreviation: DRD2 = dopamine receptor D2, GRIN2B = glutamate receptor, ionotropic, N-methyl D-aspartate 2B, TPH1 = tryptophan hydroxylase 1, MTHFR = methylenetetrahydrofolate reductase, DTNBP1 = dystrobrevin binding protein 1, DRD4 = dopamine receptor D4, PLXNA2 = plexin A2, DAOA = D-amino acid oxidase activator, HP = haptoglobin SCZ = Schizophrenia, NCs = Normal Controls, rs = Reference Single Nucleotide Polymorphism, bpTR = base pair Tandem Repeat, m = wild allele, M = mutant allele, S = Short allele, L = Long allele, SZGene = Schizophrenia Gene Database (http://www.szgene.org/), OR = Odds Ratio, CI = Confidential Interval Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 3 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 Table 2 Demographic Samples Number Male Mean Age PANSS Average Paranoid form Hebephrenic form Catatonic form SCZ 407 221(54.3%) 47.2 80.2 76.4% 13.5% 3.1% NCs 384 194(50.5%) 42.1 - - - - Abbreviation: SCZ = Schizophrenia, NCs = Normal Controls, PANSS = Positive and Negative Syndrome Scale from 0 to 14 according to their genetic vulnerability SZGene. Again, a negative result was obtained when information from across all seven variants. This score risk-allele carriers (risk-allele homozygotes and risk- was then entered as a predictor of case status in a logis- allele heterozygotes) were pooled, suggesting that tic regression model, with the type-I-error rate fixed at neither an additive nor a dominant model of the joint 0.05. effects of these seven variants could be supported. Results Discussion and Conclusion The distribution of no single polymorphism was signifi- In this study, we utilized the evidence from the SZGene cantly different between schizophrenia and control database to build very strong hypotheses of independent groups at a p-value less than 0.05 (Fisher’s exact test for and joint effects of the top seven most strongly sup- each variant and t-test for aggregated seven variants, ported risk genes for schizophrenia. These hypotheses Table 3). Moreover, no statistically significant deviation were roundly unsupported. While our results alone are in the genetic vulnerability index derived from all seven not enough to invalidate the conclusions gleaned from variants was found within the seven top-ranked poly- the large body of evidence collated in SZGene, they do morphisms. In fact, the average risk-index score in the cast doubt about the strength of the documented asso- schizophrenia group (6.5 ± 1.57) was slightly lower than ciations. Several potential confounders may be able to among controls (6.6 ± 1.39) (Figure 1). This is consis- explain our results. tent with the negative results from the logistic regres- Chiefly, our failure to find significant associations sion analysis of the risk-index score, which found a couldbearesultofinsufficientsamplesizeand less- non-significant (p = 0.783) and slightly negative (b = than-optimal statistical power.Ouraverage powerwas -0.02) effect of increments in the risk-index on likeli- 6.72% on the assessment of Genetic Power Calculator hood of being in the schizophrenia group. Our failure to (type-I error rate at 0.05, and the prevalence of the dis- find a higher-order genetic effect of these seven variants order at 0.008, http://pngu.mgh.harvard.edu/~purcell/ on vulnerability to schizophrenia persisted when we rea- gpc/, Table 4). This level of power is not enough to con- nalyzed the data after assigning a weight to each risk fidently refute the claims of significant association for allele proportional to its odds ratio as indicated in these seven variants. The minor allele frequencies of Table 3 P-value for the Individual SNPs and the Aggregation of Seven Variants Gene SNP SCZ NCs Individual SNPs(Fisher’s exact test) Aggregation of Seven SNPs(t-test) p-value for Additive effect p-value for Additive effect DRD2 rs1801028 C/C C/G G/G C/C C/G G/G 0.275 390 14 8 354 23 7 DRD2 rs6277 C/C C/T T/T C/C C/T T/T 0.362 367 38 1 341 43 2 GRIN2B rs101938 T/T T/G G/G T/T T/G G/G 0.67 91 206 110 81 204 100 TPH1 rs1800532 A/A A/C C/C A/A A/C C/C 0.635 0.189 105 219 90 108 200 78 MTHFR rs1801133 T/T T/C C/C T/T T/C C/C 0.519 69 184 160 64 183 138 DTNBP1 rs2619528 G/G G/A A/A G/G G/A A/A 0.193 326 77 4 323 60 1 DRD4 120bpTR S/S S/L S/L S/S S/L L/L 0.095 24 138 248 16 158 211 Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 4 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 could be calculated additively (however, we also evalu- ated a dominant model with similar negative results). It could be suspected that the mode of inheritance of schi- zophrenia is not simply additive, however no definitive model is identified so far [1,5,6]. Re-analyses of these data with other modes of inheritance specified (e.g., recessive, multiplicative) may have yielded different Figure 1 Numbers of the samples with each Risk-Index. X-axis is results more consistent with expectations based on “Risk Index”, and Y-axis is the Numbers of the samples. The average SZGene. and standard deviation of “Risk Index” for schizophrenia was 6.5 ± A third caveat regarding interpretation of our study is 1.57, while 6.6 ± 1.39 for normal controls. Abbreviation: SCZ = the ancestry of our sample. All of our subjects were Schizophrenia, NCs = Normal Controls derived from a sample of Asian ancestry, Japanese, although the top seven variants were selected based on some of these seven variants (in particular, rs1801028 their collective evidence from all ancestral groups on DRD2) are quite low (e.g., f = 0.05), which has (though SZGene represents more Caucasian samples adverse effects on the inferential power to detect the than Asian ones). Given the possibility that the current effects of those variants. Furthermore, this negative lack of detection derived from this discrepancy, we impact on power is likely to be compounded when recalculated the top variants in SZGene from samples of investigating the joint effects of the seven SNPs. How- only Asian ancestry. Within the seven variants, the ever, the direction of the effects identified in our sample majority of variants (four out of seven) were still signifi- was, for five of the variants (rs1801028 on DRD2, cant in the Asian-only subsamples, and the other three rs1019385 on GRIN2B, rs1800532 on TPH1, rs2619528 variants had only been examined in Asian-ancestry sam- on DTNBP1, and rs1801133 on MTHFR), in the oppo- ples once or twice previously, precluding definitive site direction of that documented in SZGene. Thus, answers. These data imply that the investigated variants even with the addition of more subjects, our sample were deserving of further research both in general and likely would not yield any semblance of significant asso- in Asian samples specifically. Nevertheless our currently ciation for these five variants. For the remaining two employed samples will not generalize to all samples variants (120bpTR on DRD4 and rs6277 on DRD2)our evaluated by the schizophrenia geneticists so far. detected effects were in the same direction as those With regard to the deviation from Hardy-Weinberg reported in SZGene, suggesting that our data may in Equilibrium (HWE), the current result of genotyping in fact be consistent with the hypothesis of some effect of cases for 120bp Tandem Repeat in DRD4, and both in these variants on risk for the disorder in a global sense cases and controls for rs1801028 in DRD2 has shown (though not necessarily a significant effect in our the deviation from HWE (Table 4). Our finding on this sample). article is not the simple positive association, therefore Another caveat in interpreting our results regards the these deviations will not have a major influence on our analytic models we employed. In the present study, in overall conclusion. Although it is possible to expect that order to reduce the complexity, it was simply hypothe- the deviated three group have false-negative association, sized that the attributable odds ratio for each poly- we still conclude that our main finding will not be morphism was 2, and we hypothesized that vulnerability forced to change the fundamental direction. Given these potential confounders it is keenly neces- sary to repeat this investigation in a larger, ethnically Table 4 The deviation from Hardy-Weinberg Equilibrium (X , more than 3.84 represents the significant deviation diversepopulationinorder to validate (or invalidate) from HWE at 0.05 p-value) and genetic power for our model further. It is also important to aggregate the investigated samples (prevalence = 0.008, type II error = updated positive variants in the SZGene database when 0.80, general 2df, alpha = 0.05) the replication work is conducted. Much work is needed SCZ NCs Power in a collaborative effort in order to generate power to DRD2 rs1801028 0.67 4.16 0.0504 identify potential genetic markers for schizophrenia that transcend ethnicities and populations worldwide, if such DRD2 rs6277 109.57 46.21 0.0919 exist. Studies of schizophrenia inevitably inherit the GRIN2B rs101938 0 0.26 0.0525 weaknesses of the current psychiatric nosology, which TPH1 rs1800532 0.09 1.5 0.0806 clinical observation (symptomatology) demands when MTHFR rs1801133 1.46 0.7 0.0563 we aimed to select the sample due to the lack of biologi- DTNBP1 rs2619528 1.66 0.06 0.069 cal markers. Our current findings that there is no statis- DRD4 120bpTR 0.05 1.07 0.0698 tically significant deviation in the possession of “risk- Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 5 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 conferring” alleles between schizophrenia and controls may have a chance to highlight the profound heteroge- neity of the disorder of interest. Author details Department of Neuropsychiatry; Osaka Medical College; Osaka, Japan. Department of Psychiatry and Behavioral Sciences, and Medical Genetics Research Center; SUNY Upstate Medical University; 750 East Adams Street; Syracuse, NY, 13210, USA. Graduate School of Letters, Kansai University; Osaka, Japan. Laboratory of Pharmacotherapy; Osaka University of Pharmaceutical Sciences; Osaka, Japan. Authors’ contributions TK and SJG designed the study and collaborated in the writing of the final version of the manuscript. SK, AT, and HK wrote the protocol, and managed the genotyping. SK wrote the first draft. HU and SJG undertook the statistical analysis. AH, TK, MM, and JK worked for the sample recruitment. HM, and HY assisted in conceptualizing the study, provided laboratory space and resources for data collection, and collaborated in the writing of the final version of the manuscript. All authors contributed to and have approved the final manuscript. Competing interests The authors declare that they have no competing interests. Received: 2 October 2010 Accepted: 7 October 2011 Published: 7 October 2011 References 1. Wray NR, Visscher PM: Narrowing the boundaries of the genetic architecture of schizophrenia. Schizophr Bull 2010, 36:14-23. 2. Crow TJ: How and why genetic linkage has not solved the problem of psychosis: review and hypothesis. Am J Psychiatry 2007, 164:13-21. 3. Allen NC, Bagade S, McQueen MB, Ioannidis JP, Kavvoura FK, Khoury MJ, Tanzi RE, Bertram L: Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nat Genet 2008, 40:827-834. 4. Bertram L: Genetic research in schizophrenia: new tools and future perspectives. Schizophr Bull 2008, 34:806-812. 5. Gough SC, O’Donovan MC: Clustering of metabolic comorbidity in schizophrenia: a genetic contribution? J Psychopharmacol 2005, 19:47-55. 6. Gejman PV, Sanders AR, Duan J: The role of genetics in the etiology of schizophrenia. Psychiatr Clin North Am 2010, 33:35-6. doi:10.1186/1744-9081-7-43 Cite this article as: Tsutsumi et al.: The genetic validation of heterogeneity in schizophrenia. Behavioral and Brain Functions 2011 7:43. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Behavioral and Brain Functions Springer Journals

The genetic validation of heterogeneity in schizophrenia

Download PDF
5 pages

Loading next page...
 
/lp/springer-journals/the-genetic-validation-of-heterogeneity-in-schizophrenia-nF05nW94oH

References (18)

Publisher
Springer Journals
Copyright
Copyright © 2011 by Tsutsumi et al; licensee BioMed Central Ltd.
Subject
Biomedicine; Neurosciences; Neurology; Behavioral Therapy; Psychiatry
eISSN
1744-9081
DOI
10.1186/1744-9081-7-43
pmid
21981786
Publisher site
See Article on Publisher Site

Abstract

Introduction: Schizophrenia is a heritable disorder, however clear genetic architecture has not been detected. To overcome this state of uncertainty, the SZGene database has been established by including all published case- control genetic association studies appearing in peer-reviewed journals. In the current study, we aimed to determine if genetic variants strongly suggested by SZGene are associated with risk of schizophrenia in our case- control samples of Japanese ancestry. In addition, by employing the additive model for aggregating the effect of seven variants, we aimed to verify the genetic heterogeneity of schizophrenia diagnosed by an operative diagnostic manual, the DSM-IV. Methods: Each positively suggested genetic polymorphism was ranked according to its p-value, then the seven top-ranked variants (p < 0.0005) were selected from DRD2, DRD4, GRIN2B, TPH1, MTHFR, and DTNBP1 (February, 2007). 407 Schizophrenia cases and 384 controls participated in this study. To aggregate the vulnerability of the disorder based on the participants’ genetic information, we calculated the “risk-index” by adding the number of genetic risk factors. Results: No statistically significant deviation between cases and controls was observed in the genetic risk-index derived from all seven variants on the top-ranked polymorphisms. In fact, the average risk-index score in the schizophrenia group (6.5+/-1.57) was slightly lower than among controls (6.6+/-1.39). Conclusion: The current work illustrates the difficulty in identifying universal and definitive risk-conferring polymorphisms for schizophrenia. Our employed number of samples was small, so we can not preclude the possibility that some or all of these variants are minor risk factors for schizophrenia in the Japanese population. It is also important to aggregate the updated positive variants in the SZGene database when the replication work is conducted. Keywords: schizophrenia, gene, Schizophrenia Gene Database (SZGene), heterogeneity, Japanese, DRD2, DRD4, GRIN2B, TPH1, MTHFR, DTNBP1, and Risk-Index Introduction expected to have a small effect on risk for the disorder. Schizophrenia is a highly heritable disorder, but even its Although many positive results were reported, most are genetic architecture still remains unclear [1]. In order to never replicated extensively. To overcome this state of reveal the genetic involvement in the etiology, several uncertainty, Bertram et al. assembled the SZGene data- research designs have been adopted. Linkage studies base to aggregate the evidence for those genetic poly- have not, however, found strongly linked loci [2]. Alter- morphisms with the best, most reliable evidence for natively, many association studies of schizophrenia have association with schizophrenia [3,4]. SZGene is charac- been performed because genetic association methods are terized by the inclusion of all published case-control a more powerful means for finding genes that are genetic association studies appearing in peer-reviewed journals, and each association is evaluated using a uni- form method of meta-analysis. This inclusive and con- * Correspondence: psy052@poh.osaka-med.ac.jp Department of Neuropsychiatry; Osaka Medical College; Osaka, Japan sistent database renders sometimes ambiguous or Full list of author information is available at the end of the article © 2011 Tsutsumi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 2 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 amorphous bodies of evidence concrete, and highlights committee at Osaka Medical College. The cases were some of the most promising avenues for continued recruited from inpatients in two mental hospitals and research by schizophrenia geneticists. From this data- oneuniversityhospitallocated in thewestern areaof base, we picked the most reliably associated variants, Japan, and the controls were recruited among hospital and sought to determine if these variants would be asso- staff. The details of the samples are described in the ciated with risk for schizophrenia in our own case-con- Table 2. No statistical difference was observed in the trol sample of Japanese ancestry. Consistent with a male/female ratio of the participants, while the patients common-disease/common-variant hypothesis of the dis- were significantly younger than the controls. All of the participants lived in the western area of Japan, and were order, we would not hypothesize that each variant iden- tified in SZGene would be a necessary component of self-reported ethnically Japanese. the risk profile for schizophrenia in our sample, so we With regard to the genotyping procedure, Single evaluated the independent and joint effects of the top nucleotide polymorphisms (SNPs) on the genomic DNA seven variants. The objectives of this study were: 1) to extracted from venous blood were identified by FRET determine if the top candidate genes for schizophrenia method (Roche Diagnostics, Japan) according to the would show replicated evidence for a contribution to manufacture’s protocol. The 120 bp Tandem Repeat risk for the disorder; and 2) to see if the aggregate effect polymorphism in DRD4 was detected by restriction frag- of these seven top variants was stronger than the indivi- ment length polymorphism. Each primer and probe was dual effects of each variant alone. provided on demand. In addition to the analysis of each single polymorph- Methods ism, we sought to aggregate the vulnerability of the dis- Based on the information in SZGene as of February order based on the participants’ genetic information. 2007, each positively associated genetic polymorphism The risk alleles of each of the seven top polymorphisms in the database was ranked according to its p-value shown in SZGene were summated, such that an indivi- from a chi-square test of association with the disorder. dual homozygous for a polymorphism’s risk alleles was The p-values of the seven top-ranked polymorphisms quantified as having a value of “2”. The heterozygous were all less than 0.005 (Table 1). We chose these seven genotype was given the value of “1”,and thehomozy- variants for the pragmatic reason of cost and effort. To gote of non-risk alleles was coded “0”.Thisscoring evaluate these selected polymorphisms, we recruited 407 imparted an additive effect onto each variant, which was patients diagnosed with schizophrenia by multiple psy- supported by the meta-analytic results in SZGene chiatric doctors according to DSM-IV TR criteria and (although this may not be the true mode of inheritance of each gene’s effect on risk, misspecification by an addi- 384 normal controls without any medical record in psy- chiatry. Every participant gave written and oral informed tive model is less costly than misspecification by other consent, and this study was approved by the ethical models). Each of the participants was additively scored Table 1 Derived data from SZGene for investigated genes and polymorphisms Gene Polymorphism Denomination p-value OR 95%CI Cases Control m/m m/M M/M Sum m/m m/M M/M Sum 1 DRD2 rs6277(C/T) 5.71.E-06 1.4 (1.2-1.63) 178 266 130 574 225 484 332 1041 2 DRD2 rs1801028(G/C) 8.24.E-06 1.34 (1.11-1.61) 9 270 3770 4049 8 254 5420 5682 3 GRIN2B rs1019385(T/G) (200T/G) 4.70.E-05 0.69 (0.54-0.88) 85 256 161 502 114 257 95 466 4 TPH1 rs1800532(A/C) 7.99.E-05 1.25 (1.08-1.44) 324 609 306 1239 344 851 513 1708 5 MTHFR rs1801133(T/C) (C677T) 2.15.E-04 1.14 (1.03-1.25) 490 1672 1708 3870 550 2265 2536 5351 6 DTNBP1 rs2619528(A/G) (P1765) 4.08.E-04 1.25 (1.01-1.56) 90 558 1049 1697 79 641 1485 2205 7 DRD4 120-bpTR(S/L) 3.80.E-03 0.81 (0.7-0.94) 55 374 807 1236 77 412 710 1199 8 PLXNA2 rs1327175(G/C) 0.043 0.76 (0.58-0.99) 12 221 1478 1711 15 280 1475 1770 9 DAOA rs3916971(T/C) 0.045 0.84 (0.73-0.96) 169 401 274 844 213 457 252 922 10 HP HP1/2 0.044 0.88 (0.8-0.98) 184 647 515 1346 324 995 699 2018 Abbreviation: DRD2 = dopamine receptor D2, GRIN2B = glutamate receptor, ionotropic, N-methyl D-aspartate 2B, TPH1 = tryptophan hydroxylase 1, MTHFR = methylenetetrahydrofolate reductase, DTNBP1 = dystrobrevin binding protein 1, DRD4 = dopamine receptor D4, PLXNA2 = plexin A2, DAOA = D-amino acid oxidase activator, HP = haptoglobin SCZ = Schizophrenia, NCs = Normal Controls, rs = Reference Single Nucleotide Polymorphism, bpTR = base pair Tandem Repeat, m = wild allele, M = mutant allele, S = Short allele, L = Long allele, SZGene = Schizophrenia Gene Database (http://www.szgene.org/), OR = Odds Ratio, CI = Confidential Interval Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 3 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 Table 2 Demographic Samples Number Male Mean Age PANSS Average Paranoid form Hebephrenic form Catatonic form SCZ 407 221(54.3%) 47.2 80.2 76.4% 13.5% 3.1% NCs 384 194(50.5%) 42.1 - - - - Abbreviation: SCZ = Schizophrenia, NCs = Normal Controls, PANSS = Positive and Negative Syndrome Scale from 0 to 14 according to their genetic vulnerability SZGene. Again, a negative result was obtained when information from across all seven variants. This score risk-allele carriers (risk-allele homozygotes and risk- was then entered as a predictor of case status in a logis- allele heterozygotes) were pooled, suggesting that tic regression model, with the type-I-error rate fixed at neither an additive nor a dominant model of the joint 0.05. effects of these seven variants could be supported. Results Discussion and Conclusion The distribution of no single polymorphism was signifi- In this study, we utilized the evidence from the SZGene cantly different between schizophrenia and control database to build very strong hypotheses of independent groups at a p-value less than 0.05 (Fisher’s exact test for and joint effects of the top seven most strongly sup- each variant and t-test for aggregated seven variants, ported risk genes for schizophrenia. These hypotheses Table 3). Moreover, no statistically significant deviation were roundly unsupported. While our results alone are in the genetic vulnerability index derived from all seven not enough to invalidate the conclusions gleaned from variants was found within the seven top-ranked poly- the large body of evidence collated in SZGene, they do morphisms. In fact, the average risk-index score in the cast doubt about the strength of the documented asso- schizophrenia group (6.5 ± 1.57) was slightly lower than ciations. Several potential confounders may be able to among controls (6.6 ± 1.39) (Figure 1). This is consis- explain our results. tent with the negative results from the logistic regres- Chiefly, our failure to find significant associations sion analysis of the risk-index score, which found a couldbearesultofinsufficientsamplesizeand less- non-significant (p = 0.783) and slightly negative (b = than-optimal statistical power.Ouraverage powerwas -0.02) effect of increments in the risk-index on likeli- 6.72% on the assessment of Genetic Power Calculator hood of being in the schizophrenia group. Our failure to (type-I error rate at 0.05, and the prevalence of the dis- find a higher-order genetic effect of these seven variants order at 0.008, http://pngu.mgh.harvard.edu/~purcell/ on vulnerability to schizophrenia persisted when we rea- gpc/, Table 4). This level of power is not enough to con- nalyzed the data after assigning a weight to each risk fidently refute the claims of significant association for allele proportional to its odds ratio as indicated in these seven variants. The minor allele frequencies of Table 3 P-value for the Individual SNPs and the Aggregation of Seven Variants Gene SNP SCZ NCs Individual SNPs(Fisher’s exact test) Aggregation of Seven SNPs(t-test) p-value for Additive effect p-value for Additive effect DRD2 rs1801028 C/C C/G G/G C/C C/G G/G 0.275 390 14 8 354 23 7 DRD2 rs6277 C/C C/T T/T C/C C/T T/T 0.362 367 38 1 341 43 2 GRIN2B rs101938 T/T T/G G/G T/T T/G G/G 0.67 91 206 110 81 204 100 TPH1 rs1800532 A/A A/C C/C A/A A/C C/C 0.635 0.189 105 219 90 108 200 78 MTHFR rs1801133 T/T T/C C/C T/T T/C C/C 0.519 69 184 160 64 183 138 DTNBP1 rs2619528 G/G G/A A/A G/G G/A A/A 0.193 326 77 4 323 60 1 DRD4 120bpTR S/S S/L S/L S/S S/L L/L 0.095 24 138 248 16 158 211 Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 4 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 could be calculated additively (however, we also evalu- ated a dominant model with similar negative results). It could be suspected that the mode of inheritance of schi- zophrenia is not simply additive, however no definitive model is identified so far [1,5,6]. Re-analyses of these data with other modes of inheritance specified (e.g., recessive, multiplicative) may have yielded different Figure 1 Numbers of the samples with each Risk-Index. X-axis is results more consistent with expectations based on “Risk Index”, and Y-axis is the Numbers of the samples. The average SZGene. and standard deviation of “Risk Index” for schizophrenia was 6.5 ± A third caveat regarding interpretation of our study is 1.57, while 6.6 ± 1.39 for normal controls. Abbreviation: SCZ = the ancestry of our sample. All of our subjects were Schizophrenia, NCs = Normal Controls derived from a sample of Asian ancestry, Japanese, although the top seven variants were selected based on some of these seven variants (in particular, rs1801028 their collective evidence from all ancestral groups on DRD2) are quite low (e.g., f = 0.05), which has (though SZGene represents more Caucasian samples adverse effects on the inferential power to detect the than Asian ones). Given the possibility that the current effects of those variants. Furthermore, this negative lack of detection derived from this discrepancy, we impact on power is likely to be compounded when recalculated the top variants in SZGene from samples of investigating the joint effects of the seven SNPs. How- only Asian ancestry. Within the seven variants, the ever, the direction of the effects identified in our sample majority of variants (four out of seven) were still signifi- was, for five of the variants (rs1801028 on DRD2, cant in the Asian-only subsamples, and the other three rs1019385 on GRIN2B, rs1800532 on TPH1, rs2619528 variants had only been examined in Asian-ancestry sam- on DTNBP1, and rs1801133 on MTHFR), in the oppo- ples once or twice previously, precluding definitive site direction of that documented in SZGene. Thus, answers. These data imply that the investigated variants even with the addition of more subjects, our sample were deserving of further research both in general and likely would not yield any semblance of significant asso- in Asian samples specifically. Nevertheless our currently ciation for these five variants. For the remaining two employed samples will not generalize to all samples variants (120bpTR on DRD4 and rs6277 on DRD2)our evaluated by the schizophrenia geneticists so far. detected effects were in the same direction as those With regard to the deviation from Hardy-Weinberg reported in SZGene, suggesting that our data may in Equilibrium (HWE), the current result of genotyping in fact be consistent with the hypothesis of some effect of cases for 120bp Tandem Repeat in DRD4, and both in these variants on risk for the disorder in a global sense cases and controls for rs1801028 in DRD2 has shown (though not necessarily a significant effect in our the deviation from HWE (Table 4). Our finding on this sample). article is not the simple positive association, therefore Another caveat in interpreting our results regards the these deviations will not have a major influence on our analytic models we employed. In the present study, in overall conclusion. Although it is possible to expect that order to reduce the complexity, it was simply hypothe- the deviated three group have false-negative association, sized that the attributable odds ratio for each poly- we still conclude that our main finding will not be morphism was 2, and we hypothesized that vulnerability forced to change the fundamental direction. Given these potential confounders it is keenly neces- sary to repeat this investigation in a larger, ethnically Table 4 The deviation from Hardy-Weinberg Equilibrium (X , more than 3.84 represents the significant deviation diversepopulationinorder to validate (or invalidate) from HWE at 0.05 p-value) and genetic power for our model further. It is also important to aggregate the investigated samples (prevalence = 0.008, type II error = updated positive variants in the SZGene database when 0.80, general 2df, alpha = 0.05) the replication work is conducted. Much work is needed SCZ NCs Power in a collaborative effort in order to generate power to DRD2 rs1801028 0.67 4.16 0.0504 identify potential genetic markers for schizophrenia that transcend ethnicities and populations worldwide, if such DRD2 rs6277 109.57 46.21 0.0919 exist. Studies of schizophrenia inevitably inherit the GRIN2B rs101938 0 0.26 0.0525 weaknesses of the current psychiatric nosology, which TPH1 rs1800532 0.09 1.5 0.0806 clinical observation (symptomatology) demands when MTHFR rs1801133 1.46 0.7 0.0563 we aimed to select the sample due to the lack of biologi- DTNBP1 rs2619528 1.66 0.06 0.069 cal markers. Our current findings that there is no statis- DRD4 120bpTR 0.05 1.07 0.0698 tically significant deviation in the possession of “risk- Tsutsumi et al. Behavioral and Brain Functions 2011, 7:43 Page 5 of 5 http://www.behavioralandbrainfunctions.com/content/7/1/43 conferring” alleles between schizophrenia and controls may have a chance to highlight the profound heteroge- neity of the disorder of interest. Author details Department of Neuropsychiatry; Osaka Medical College; Osaka, Japan. Department of Psychiatry and Behavioral Sciences, and Medical Genetics Research Center; SUNY Upstate Medical University; 750 East Adams Street; Syracuse, NY, 13210, USA. Graduate School of Letters, Kansai University; Osaka, Japan. Laboratory of Pharmacotherapy; Osaka University of Pharmaceutical Sciences; Osaka, Japan. Authors’ contributions TK and SJG designed the study and collaborated in the writing of the final version of the manuscript. SK, AT, and HK wrote the protocol, and managed the genotyping. SK wrote the first draft. HU and SJG undertook the statistical analysis. AH, TK, MM, and JK worked for the sample recruitment. HM, and HY assisted in conceptualizing the study, provided laboratory space and resources for data collection, and collaborated in the writing of the final version of the manuscript. All authors contributed to and have approved the final manuscript. Competing interests The authors declare that they have no competing interests. Received: 2 October 2010 Accepted: 7 October 2011 Published: 7 October 2011 References 1. Wray NR, Visscher PM: Narrowing the boundaries of the genetic architecture of schizophrenia. Schizophr Bull 2010, 36:14-23. 2. Crow TJ: How and why genetic linkage has not solved the problem of psychosis: review and hypothesis. Am J Psychiatry 2007, 164:13-21. 3. Allen NC, Bagade S, McQueen MB, Ioannidis JP, Kavvoura FK, Khoury MJ, Tanzi RE, Bertram L: Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nat Genet 2008, 40:827-834. 4. Bertram L: Genetic research in schizophrenia: new tools and future perspectives. Schizophr Bull 2008, 34:806-812. 5. Gough SC, O’Donovan MC: Clustering of metabolic comorbidity in schizophrenia: a genetic contribution? J Psychopharmacol 2005, 19:47-55. 6. Gejman PV, Sanders AR, Duan J: The role of genetics in the etiology of schizophrenia. Psychiatr Clin North Am 2010, 33:35-6. doi:10.1186/1744-9081-7-43 Cite this article as: Tsutsumi et al.: The genetic validation of heterogeneity in schizophrenia. Behavioral and Brain Functions 2011 7:43. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit

Journal

Behavioral and Brain Functions – Springer Journals

Published: Oct 7, 2011

There are no references for this article.