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Genetic variation at the synaptic vesicle gene SV2A is associated with schizophrenia
Schizophrenia Research 141 (2012) 262–265
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Genetic variation at the synaptic vesicle gene SV2A is associated with schizophrenia Manuel Mattheisen a, b, c, 1, Thomas W. Mühleisen a, d, 1, Jana Strohmaier e, Jens Treutlein e, Igor Nenadic f, Margrieta Alblas a, d, Sandra Meier e, Franziska Degenhardt a, d, Stefan Herms a, d, Per Hoffmann a, d, Stephanie H. Witt e, Ina Giegling g, k, Heinrich Sauer f, Thomas G. Schulze h, Dan Rujescu g, k, Markus M. Nöthen a, d, i, Marcella Rietschel e, Sven Cichon a, d, j,⁎ a
Department of Genomics, Life&Brain Center, University of Bonn, Bonn, Germany Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA c Institute for Genomic Mathematics, University of Bonn, Bonn, Germany d Institute of Human Genetics, University of Bonn, Bonn, Germany e Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany f Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany g Division of Molecular and Clinical Neurobiology, Department of Psychiatry, Ludwig-Maximilians-University, Munich, Germany h Department of Psychiatry and Psychotherapy, Georg-August-University Göttingen, Göttingen, Germany i German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany j Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany k Department of Psychiatry, Martin-Luther-University, Halle, Germany b
a r t i c l e
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Article history: Received 17 March 2012 Received in revised form 31 July 2012 Accepted 27 August 2012 Available online 24 September 2012 Keywords: Neuropsychiatric disorder Single-nucleotide polymorphism Synapse Candidate gene GABA
a b s t r a c t Convergent evidence from pharmacological and animal studies suggests a possible role for the synaptic vesicle glycoprotein 2A gene (SV2A) in schizophrenia susceptibility. To test systematically all common variants in the SV2A gene region for an association with schizophrenia, we used a HapMap-based haplotype tagging approach and tested five SNPs in 794 patients and 843 controls. The SNP rs15931 showed evidence for an association with schizophrenia and was followed-up in an independent sample of 2581 individuals (overall p-value =0.0042, OR=0.779). Our study in the German population provides evidence, at a genetic level, for the involvement of the SV2A gene region in schizophrenia. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Schizophrenia (SCZ) is a severe psychiatric disorder with a point prevalence of about 0.4% and a lifetime morbid risk of 1% (Saha et al., 2005). Family, twin, and adoption studies have demonstrated the involvement of genetic factors in schizophrenia and estimate its heritability at approximately 80% (Sullivan et al., 2003). There is evidence from pharmacological and animal studies which makes the synaptic vesicle glycoprotein 2A (SV2A) gene a promising candidate gene for schizophrenia. SV2 molecules are integral proteins localized on the surface of synaptic vesicles in many types of neurons, and appear to have an important function in synaptic vesicle exocytosis and neurotransmitter release (Dardou et al., 2011). The SV2A protein is
⁎ Corresponding author at: Department of Genomics, Life & Brain Center, University of Bonn, Sigmund-Freud-Strasse 25, D-53127 Bonn, Germany. Tel.: +49 228 6885 405; fax: +49 228 6885 401. E-mail address: [email protected] (S. Cichon). 1 These authors contributed equally. 0920-9964/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.schres.2012.08.027
the primary binding site for the antiepileptic drug levetiracetam (Lynch et al., 2004). Similar to other antiepileptic drugs, levetiracetam is claimed to have further therapeutic properties, such as ameliorating anxious, depressive, and also manic symptoms (Grunze et al., 2003; Muralidharan and Bhagwgar, 2006; Kinrys et al., 2007). These symptoms are highly prevalent in schizophrenia and bipolar disorder, which partially share common genetic etiologies (Lichtenstein et al., 2009; Van Snellenberg and de Candia, 2009). Further evidence for the potential role of SV2A in schizophrenia comes from functional studies. Homozygous knock-out mice for SV2A show reduced hippocampal GABAergic neurotransmission (Crowder et al., 1999). Such a deficit in GABAergic neurotransmission has also been observed in the hippocampus, cerebellum, and prefrontal cortex of patients with schizophrenia by independent research groups (Benes et al., 2007; Mudge et al., 2008; Nowack et al., 2010). Mudge et al. (2008) described altered synaptic vesicular transport in post-mortem cerebellums of patients with schizophrenia and found expression changes in several genes. Interestingly, SV2A expression was found to be down-regulated. Based on these findings, it is tempting to speculate that the known pharmacological
M. Mattheisen et al. / Schizophrenia Research 141 (2012) 262–265
interaction between levetiracetam and SV2A may produce some of the schizophrenia-like adverse reactions that were described in clinical studies (White et al., 2003; Kuehn, 2008; Aggarwal et al., 2011). Given the above evidence strongly suggesting that deregulation of SV2A influences the development of schizophrenia, we hypothesized that common genetic variants in the SV2A gene region might be risk factors for schizophrenia. We therefore conducted a systematic, HapMap-based association analysis including all common haplotypes of the SV2A locus on chromosome 1. In particular, we tested five independent haplotype-tagging single-nucleotide polymorphisms (htSNPs) in a large German case–control sample and replicated these findings with a significant p-value in an independent German follow-up sample. Our results suggest an involvement of genetic variation in the SV2A gene region in the development of schizophrenia. 2. Methods 2.1. Subjects The patients of the discovery sample (n = 794) were recruited from consecutive admissions to the inpatient units of the Central Institute of Mental Health in Mannheim, and the Departments of Psychiatry and Psychotherapy at the Universities of Bonn and Jena, Germany. The population-based sample of controls (n = 843) was established with the help of the local Census Bureau of the city of Bonn (North Rhine-Westphalia, Germany). The inclusion criteria for our patients and controls have been described elsewhere (Treutlein et al., 2009). The follow-up sample was recruited in the Munich area, Germany, representing an independent 913 patients with a DSM-IV diagnosis of schizophrenia and 1688 controls. Further details have been described previously (Rietschel et al., 2012). The combined sample (discovery and follow-up) comprised 1707 patients and 2511 controls for analysis of SNP rs15931 after quality control (QC). Approval for this study was obtained from the respective local ethics committees. Written informed consent was obtained after detailed study information was provided. 2.2. Genotyping and quality control Within a 47.3-kb region containing the entire SV2A gene (rs15931–rs12078573, chr1:147072932–147120191, NCBI34/hg16), we selected five htSNPs present in two haplotype blocks with frequencies of 1% in the Centre d'Etude du Polymorphisme Humain (CEPH) project's Utah (CEU) population using HapMap phase I + II data (HapMap release 20, International HapMap consortium, 2005). The blocks were defined by the algorithm implemented in Haploview 3.32 (Barrett et al., 2005) and described in Gabriel et al. (2002). Genomic DNA was extracted from venous blood samples using a conventional salting-out procedure (Miller et al., 1988). The discovery sample was genotyped using a GoldenGate Genotyping Assay (Illumina Inc. San Diego, CA, USA) following the manufacturer's protocol. Only call rates per individual of at least 80% were accepted (17 individuals were excluded). A total of 1637 individuals, including 794 cases (358 females and 436 males) and 843 controls (360 females and 483 males) were incorporated in this analysis. The following QC protocol was applied at the SNP level: (i) call rate >96%, (ii) p-value for exact test regarding deviation from Hardy–Weinberg-Equilibrium >0.001 in controls and >0.00001 in cases, (iii) a minor allele frequency in cases and/or controls > 0.01, and (iv) a non-significant difference (p > 0.05) in patterns of non-random missingness in cases vs. controls per SNP. One SNP (rs17643644) was excluded due to a low call rate; thus four SNPs could be incorporated into the association analysis. Genotyping of the follow-up sample for rs15931, the SNP showing the strongest association with schizophrenia in the discovery sample,
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was performed using the MassARRAY system (Sequenom Inc., San Diego, CA, USA). After application of the aforementioned QC filters, 913 cases (342 females and 571 males; mean age at onset = 37.7 ± 11.7) and 1668 controls (858 females and 810 males; mean age = 49.5 ± 16.0) were analyzed. 2.3. Association analysis All single-marker analyses were conducted using the Cochran Armitage Test for linear trend (ATT, 1 degree of freedom) as implemented in PLINK (Purcell et al., 2007). 3. Results Of the four htSNPs, single-marker analysis yielded a p-value of 0.0061 for rs15931 in the discovery sample (two-sided, minor allele [MA]: T, odds ratio [OR] = 0.698). This p-value withstood Bonferroni correction for the number of markers tested (p = 0.0244). We replicated this finding in an independent follow-up sample and found significant association in the same direction as in the discovery sample (p = 0.0425, one-sided, MA: T, OR = 0.816). The combined analysis of both samples strengthened the overall association (p = 0.0042, two-sided, MA: T, OR = 0.779). A detailed overview of the results is provided in Table 1. 4. Discussion This is, to our knowledge, the first study that reports an association between schizophrenia and a common genetic variant in the SV2A gene region (1q21.2). Given several lines of evidence for the deregulation of SV2A possibly influencing the development of schizophrenia, and our hypothesis that common genetic variants in the SV2A gene might be risk factors for schizophrenia, we applied a focused HapMap-based candidate gene approach which has superior power to detect disease-associated variants with small effects as compared to genome-wide association studies with similar sample sizes. We followed a comprehensive two-step strategy: (i) the analysis of a discovery sample, and (ii) a replication study for the significant SNPs (robust to correction for multiple testing) in an independent sample. We found that the T-allele of rs15931 was significantly associated with schizophrenia in the discovery (p = 0.0061, OR = 0.698) and
Table 1 Results of association analysis for discovery step (a) and the downstream analysis of SNP rs15931 (b). The minor allele (MA) is given together with its frequency in cases (f_ca) and controls (f_co), respectively. The uncorrected p-value for the Cochran Armitage Trend Test (pATT) is given together with the odds ratio (OR) and the 95% confidence interval (L95 and U95) for the discovery step. The p-values are highlighted (bold and italic text) if they withstood correction for multiple testing. For the downstream analysis of rs15931, the pATT was two-sided for the discovery and the combined samples, and one-sided for the follow-up sample. (a) Chr SNP
Positiona
1 1 1 1
148122974 148148774 148153009 148159746
rs15931 rs626785 rs4926386 rs11205277
MA
f_ca
f_co
T G A G
0.065 0.174 0.131 0.420
0.091 0.198 0.116 0.450
pATT
OR
L95
U95
0.0061 0.0774 0.1825 0.0780
0.698 0.851 1.152 0.882
0.539 0.711 0.935 0.766
0.905 1.018 1.420 1.014
(b) rs15931 Sample
MA
Discovery Follow-up Combined
T T T
a
f_ca
f_co
pATT
OR
L95
O95
0.065 0.061 0.063
0.091 0.073 0.079
0.0063 0.0425 0.0042
0.698 0.816 0.779
0.539 0.647 0.656
0.905 1.029 0.925
Position according to build NCBI36/hg18.
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M. Mattheisen et al. / Schizophrenia Research 141 (2012) 262–265
the replication sample (p = 0.0425, OR = 0.816). This association comes with an over-representation of the major allele C in patients compared to controls and thus suggesting a protective effect of the minor allele T. The combined analysis yielded p = 0.0042 (OR = 0.779). Although the association seems to be stronger in males compared to females (data not shown), this difference is not large enough to unequivocally point to sex specific differences in the association between rs15931 and schizophrenia. The selected htSNPs cover a broader genomic region of 47.3 kb, which, apart from the SV2A gene, contains 6 additional RefSeq genes (HIST2H2BE, HIST2H2AB, HIST2HAC, BOLA1, SF3B4, and MTMR11). Although SV2A appears to be the best functional candidate gene in the region, detailed follow-up studies will be necessary to show whether the T-allele of rs15931 influences the function of this gene. This SNP is located in the 3′UTR of HIST2H2BE, which is part of a histone gene cluster that covers the genomic region proximal to SV2A. Interestingly, genes encoding core histone proteins have also been implicated in the etiology of schizophrenia (Dong et al., 2008; Akbarian, 2010). Previous studies investigated the gene encoding the core protein H3 (Dong et al., 2008; Akbarian, 2010), which is located at 1q42.13 and is thus not linked to the SV2A gene locus. The possible functional implications of SNP rs15931 are unclear at this point. Further, this SNP may not be functional itself but may be in linkage disequilibrium (LD) with a functionally relevant SNP which we have not directly genotyped in our study. We used the SNAP tool (Johnson et al., 2008) to identify such putative functional SNPs (r 2 > 0.8, based on HapMap CEU Phase II and III data, International HapMap consortium, 2005) and found that a non-synonymous coding variant in the BolA-like protein 1 gene (BOLA1) is in strong LD (rs1044808, r 2 > 0.9) with rs15931. BOLA1 encodes a protein which seems to play a role in cell proliferation or cell-cycle regulation (Kasai et al., 2004), but the precise molecular function remains unknown to date. Using the Developmental Transcriptome data from the BrainSpan database (http://www.brainspan.org/rnaseq/search/ index.html), we found that BOLA1 as well as SV2A expression patterns are present in the brain throughout life (monitored between the 8 post-conceptional week to 40 years of age). Overall, BOLA1 shows lower expression levels compared to SV2A for all brain structures available through BrainSpan. Although SV2A is a very interesting functional candidate gene for schizophrenia and was the initial focus of our interest, the localization of the top-associated SNP in the 3′UTR of HISTH2B2BE and the strong LD with a non-synonymous coding variant in the functionally uncharacterized BOLA1 gene make it difficult to pinpoint the disease-relevant susceptibility gene purely on the basis of genetic data. However, SV2A has an interesting functional characteristic which distinguishes it from HISTH2B2BE and BOLA1 (and the other genes in the broader genomic region of 47.3 kb, tagged by the htSNPs selected for this study): SV2A is a predicted target for the microRNA 137 (miR-137). Genetic variation in miR-137 produced the strongest association signal in the largest GWAS of schizophrenia performed to date, by the Psychiatric GWAS Consortium (PGC, Ripke et al., 2011). It has been speculated, that a miR-137-mediated dysregulation network is involved in the etiology of schizophrenia, since another four genes associated with schizophrenia at the level of genome-wide significance contained predicted targets for miR-137 (Ripke et al., 2011). It is reasonable to speculate that our finding for an association between schizophrenia and SNP rs15931 may be due to an underlying functional variation in SV2A. SV2A represents an additional member of the miR-137-mediated dysregulation network involved in the etiology of schizophrenia. In summary, results of our candidate gene study suggest that genetic variation at a locus containing the functional candidate gene SV2A is associated with schizophrenia in two patient–control samples of German origin. Independent studies are now warranted to further support our finding.
Role of funding source This study was supported by the German Federal Ministry of Education and Research (BMBF), within the context of the German National Genome Research Network plus (NGFNplus), and the Integrated Genome Research Network (IG) MooDS (grant 01GS08144 to Sven Cichon and Markus M. Nöthen, grant 01GS08147 to Marcella Rietschel). This work was supported by grants U01 HL089856, R01 MH087590 and R01 MH081862. Igor Nenadic was supported by a Junior Scientist Grant of the IZKF, Medical School, Jena University Hospital. Igor Nenadic, Heinrich Sauer, Markus M. Nöthen, and Sven Cichon were additionally supported through an EU grant (EUTwinsS network, RTN, FP6). Jana Strohmaier was supported by the German Research Foundation (GRK 793). The above mentioned funding sources had no involvement in the study design, the analysis and interpretation of data, the writing of the report, or the decision to submit the paper for publication.
Contributors Manuel Mattheisen, Thomas W. Mühleisen, Marcella Rietschel, Markus M. Nöthen, and Sven Cichon contributed to the study design. Marcella Rietschel, Thomas G. Schulze, Jana Strohmaier, Sandra Meier, Dan Rujescu, Igor Nenadic, Heinrich Sauer recruited and diagnosed the patients. Ina Giegling, Franziska Degenhardt, and Sandra Meier compiled the clinical data. Stephanie Witt, Jens Treutlein, Margrieta Alblas, and Per Hoffmann prepared the DNA and performed the genotyping. Manuel Mattheisen and Stefan Herms performed the statistical analysis. Manuel Mattheisen, Thomas W. Mühleisen, Marcella Rietschel, Markus M. Nöthen, and Sven Cichon analyzed and interpreted the data. Manuel Mattheisen, Thomas W. Mühleisen, Markus Nöthen, Marcella Rietschel, and Sven Cichon prepared the manuscript, with feedback from the other authors.
Conflict of interest statement The authors declare that they have no competing financial or other interests that might be perceived to influence the results and discussion reported in this paper.
Acknowledgements We are grateful to all of the patients and controls who contributed to this study. We also thank Jennifer A. Lee for carefully reading the manuscript.
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Contents lists available at SciVerse ScienceDirect
Schizophrenia Research journal homepage: www.elsevier.com/locate/schres
Genetic variation at the synaptic vesicle gene SV2A is associated with schizophrenia Manuel Mattheisen a, b, c, 1, Thomas W. Mühleisen a, d, 1, Jana Strohmaier e, Jens Treutlein e, Igor Nenadic f, Margrieta Alblas a, d, Sandra Meier e, Franziska Degenhardt a, d, Stefan Herms a, d, Per Hoffmann a, d, Stephanie H. Witt e, Ina Giegling g, k, Heinrich Sauer f, Thomas G. Schulze h, Dan Rujescu g, k, Markus M. Nöthen a, d, i, Marcella Rietschel e, Sven Cichon a, d, j,⁎ a
Department of Genomics, Life&Brain Center, University of Bonn, Bonn, Germany Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA c Institute for Genomic Mathematics, University of Bonn, Bonn, Germany d Institute of Human Genetics, University of Bonn, Bonn, Germany e Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany f Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany g Division of Molecular and Clinical Neurobiology, Department of Psychiatry, Ludwig-Maximilians-University, Munich, Germany h Department of Psychiatry and Psychotherapy, Georg-August-University Göttingen, Göttingen, Germany i German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany j Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany k Department of Psychiatry, Martin-Luther-University, Halle, Germany b
a r t i c l e
i n f o
Article history: Received 17 March 2012 Received in revised form 31 July 2012 Accepted 27 August 2012 Available online 24 September 2012 Keywords: Neuropsychiatric disorder Single-nucleotide polymorphism Synapse Candidate gene GABA
a b s t r a c t Convergent evidence from pharmacological and animal studies suggests a possible role for the synaptic vesicle glycoprotein 2A gene (SV2A) in schizophrenia susceptibility. To test systematically all common variants in the SV2A gene region for an association with schizophrenia, we used a HapMap-based haplotype tagging approach and tested five SNPs in 794 patients and 843 controls. The SNP rs15931 showed evidence for an association with schizophrenia and was followed-up in an independent sample of 2581 individuals (overall p-value =0.0042, OR=0.779). Our study in the German population provides evidence, at a genetic level, for the involvement of the SV2A gene region in schizophrenia. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Schizophrenia (SCZ) is a severe psychiatric disorder with a point prevalence of about 0.4% and a lifetime morbid risk of 1% (Saha et al., 2005). Family, twin, and adoption studies have demonstrated the involvement of genetic factors in schizophrenia and estimate its heritability at approximately 80% (Sullivan et al., 2003). There is evidence from pharmacological and animal studies which makes the synaptic vesicle glycoprotein 2A (SV2A) gene a promising candidate gene for schizophrenia. SV2 molecules are integral proteins localized on the surface of synaptic vesicles in many types of neurons, and appear to have an important function in synaptic vesicle exocytosis and neurotransmitter release (Dardou et al., 2011). The SV2A protein is
⁎ Corresponding author at: Department of Genomics, Life & Brain Center, University of Bonn, Sigmund-Freud-Strasse 25, D-53127 Bonn, Germany. Tel.: +49 228 6885 405; fax: +49 228 6885 401. E-mail address: [email protected] (S. Cichon). 1 These authors contributed equally. 0920-9964/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.schres.2012.08.027
the primary binding site for the antiepileptic drug levetiracetam (Lynch et al., 2004). Similar to other antiepileptic drugs, levetiracetam is claimed to have further therapeutic properties, such as ameliorating anxious, depressive, and also manic symptoms (Grunze et al., 2003; Muralidharan and Bhagwgar, 2006; Kinrys et al., 2007). These symptoms are highly prevalent in schizophrenia and bipolar disorder, which partially share common genetic etiologies (Lichtenstein et al., 2009; Van Snellenberg and de Candia, 2009). Further evidence for the potential role of SV2A in schizophrenia comes from functional studies. Homozygous knock-out mice for SV2A show reduced hippocampal GABAergic neurotransmission (Crowder et al., 1999). Such a deficit in GABAergic neurotransmission has also been observed in the hippocampus, cerebellum, and prefrontal cortex of patients with schizophrenia by independent research groups (Benes et al., 2007; Mudge et al., 2008; Nowack et al., 2010). Mudge et al. (2008) described altered synaptic vesicular transport in post-mortem cerebellums of patients with schizophrenia and found expression changes in several genes. Interestingly, SV2A expression was found to be down-regulated. Based on these findings, it is tempting to speculate that the known pharmacological
M. Mattheisen et al. / Schizophrenia Research 141 (2012) 262–265
interaction between levetiracetam and SV2A may produce some of the schizophrenia-like adverse reactions that were described in clinical studies (White et al., 2003; Kuehn, 2008; Aggarwal et al., 2011). Given the above evidence strongly suggesting that deregulation of SV2A influences the development of schizophrenia, we hypothesized that common genetic variants in the SV2A gene region might be risk factors for schizophrenia. We therefore conducted a systematic, HapMap-based association analysis including all common haplotypes of the SV2A locus on chromosome 1. In particular, we tested five independent haplotype-tagging single-nucleotide polymorphisms (htSNPs) in a large German case–control sample and replicated these findings with a significant p-value in an independent German follow-up sample. Our results suggest an involvement of genetic variation in the SV2A gene region in the development of schizophrenia. 2. Methods 2.1. Subjects The patients of the discovery sample (n = 794) were recruited from consecutive admissions to the inpatient units of the Central Institute of Mental Health in Mannheim, and the Departments of Psychiatry and Psychotherapy at the Universities of Bonn and Jena, Germany. The population-based sample of controls (n = 843) was established with the help of the local Census Bureau of the city of Bonn (North Rhine-Westphalia, Germany). The inclusion criteria for our patients and controls have been described elsewhere (Treutlein et al., 2009). The follow-up sample was recruited in the Munich area, Germany, representing an independent 913 patients with a DSM-IV diagnosis of schizophrenia and 1688 controls. Further details have been described previously (Rietschel et al., 2012). The combined sample (discovery and follow-up) comprised 1707 patients and 2511 controls for analysis of SNP rs15931 after quality control (QC). Approval for this study was obtained from the respective local ethics committees. Written informed consent was obtained after detailed study information was provided. 2.2. Genotyping and quality control Within a 47.3-kb region containing the entire SV2A gene (rs15931–rs12078573, chr1:147072932–147120191, NCBI34/hg16), we selected five htSNPs present in two haplotype blocks with frequencies of 1% in the Centre d'Etude du Polymorphisme Humain (CEPH) project's Utah (CEU) population using HapMap phase I + II data (HapMap release 20, International HapMap consortium, 2005). The blocks were defined by the algorithm implemented in Haploview 3.32 (Barrett et al., 2005) and described in Gabriel et al. (2002). Genomic DNA was extracted from venous blood samples using a conventional salting-out procedure (Miller et al., 1988). The discovery sample was genotyped using a GoldenGate Genotyping Assay (Illumina Inc. San Diego, CA, USA) following the manufacturer's protocol. Only call rates per individual of at least 80% were accepted (17 individuals were excluded). A total of 1637 individuals, including 794 cases (358 females and 436 males) and 843 controls (360 females and 483 males) were incorporated in this analysis. The following QC protocol was applied at the SNP level: (i) call rate >96%, (ii) p-value for exact test regarding deviation from Hardy–Weinberg-Equilibrium >0.001 in controls and >0.00001 in cases, (iii) a minor allele frequency in cases and/or controls > 0.01, and (iv) a non-significant difference (p > 0.05) in patterns of non-random missingness in cases vs. controls per SNP. One SNP (rs17643644) was excluded due to a low call rate; thus four SNPs could be incorporated into the association analysis. Genotyping of the follow-up sample for rs15931, the SNP showing the strongest association with schizophrenia in the discovery sample,
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was performed using the MassARRAY system (Sequenom Inc., San Diego, CA, USA). After application of the aforementioned QC filters, 913 cases (342 females and 571 males; mean age at onset = 37.7 ± 11.7) and 1668 controls (858 females and 810 males; mean age = 49.5 ± 16.0) were analyzed. 2.3. Association analysis All single-marker analyses were conducted using the Cochran Armitage Test for linear trend (ATT, 1 degree of freedom) as implemented in PLINK (Purcell et al., 2007). 3. Results Of the four htSNPs, single-marker analysis yielded a p-value of 0.0061 for rs15931 in the discovery sample (two-sided, minor allele [MA]: T, odds ratio [OR] = 0.698). This p-value withstood Bonferroni correction for the number of markers tested (p = 0.0244). We replicated this finding in an independent follow-up sample and found significant association in the same direction as in the discovery sample (p = 0.0425, one-sided, MA: T, OR = 0.816). The combined analysis of both samples strengthened the overall association (p = 0.0042, two-sided, MA: T, OR = 0.779). A detailed overview of the results is provided in Table 1. 4. Discussion This is, to our knowledge, the first study that reports an association between schizophrenia and a common genetic variant in the SV2A gene region (1q21.2). Given several lines of evidence for the deregulation of SV2A possibly influencing the development of schizophrenia, and our hypothesis that common genetic variants in the SV2A gene might be risk factors for schizophrenia, we applied a focused HapMap-based candidate gene approach which has superior power to detect disease-associated variants with small effects as compared to genome-wide association studies with similar sample sizes. We followed a comprehensive two-step strategy: (i) the analysis of a discovery sample, and (ii) a replication study for the significant SNPs (robust to correction for multiple testing) in an independent sample. We found that the T-allele of rs15931 was significantly associated with schizophrenia in the discovery (p = 0.0061, OR = 0.698) and
Table 1 Results of association analysis for discovery step (a) and the downstream analysis of SNP rs15931 (b). The minor allele (MA) is given together with its frequency in cases (f_ca) and controls (f_co), respectively. The uncorrected p-value for the Cochran Armitage Trend Test (pATT) is given together with the odds ratio (OR) and the 95% confidence interval (L95 and U95) for the discovery step. The p-values are highlighted (bold and italic text) if they withstood correction for multiple testing. For the downstream analysis of rs15931, the pATT was two-sided for the discovery and the combined samples, and one-sided for the follow-up sample. (a) Chr SNP
Positiona
1 1 1 1
148122974 148148774 148153009 148159746
rs15931 rs626785 rs4926386 rs11205277
MA
f_ca
f_co
T G A G
0.065 0.174 0.131 0.420
0.091 0.198 0.116 0.450
pATT
OR
L95
U95
0.0061 0.0774 0.1825 0.0780
0.698 0.851 1.152 0.882
0.539 0.711 0.935 0.766
0.905 1.018 1.420 1.014
(b) rs15931 Sample
MA
Discovery Follow-up Combined
T T T
a
f_ca
f_co
pATT
OR
L95
O95
0.065 0.061 0.063
0.091 0.073 0.079
0.0063 0.0425 0.0042
0.698 0.816 0.779
0.539 0.647 0.656
0.905 1.029 0.925
Position according to build NCBI36/hg18.
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M. Mattheisen et al. / Schizophrenia Research 141 (2012) 262–265
the replication sample (p = 0.0425, OR = 0.816). This association comes with an over-representation of the major allele C in patients compared to controls and thus suggesting a protective effect of the minor allele T. The combined analysis yielded p = 0.0042 (OR = 0.779). Although the association seems to be stronger in males compared to females (data not shown), this difference is not large enough to unequivocally point to sex specific differences in the association between rs15931 and schizophrenia. The selected htSNPs cover a broader genomic region of 47.3 kb, which, apart from the SV2A gene, contains 6 additional RefSeq genes (HIST2H2BE, HIST2H2AB, HIST2HAC, BOLA1, SF3B4, and MTMR11). Although SV2A appears to be the best functional candidate gene in the region, detailed follow-up studies will be necessary to show whether the T-allele of rs15931 influences the function of this gene. This SNP is located in the 3′UTR of HIST2H2BE, which is part of a histone gene cluster that covers the genomic region proximal to SV2A. Interestingly, genes encoding core histone proteins have also been implicated in the etiology of schizophrenia (Dong et al., 2008; Akbarian, 2010). Previous studies investigated the gene encoding the core protein H3 (Dong et al., 2008; Akbarian, 2010), which is located at 1q42.13 and is thus not linked to the SV2A gene locus. The possible functional implications of SNP rs15931 are unclear at this point. Further, this SNP may not be functional itself but may be in linkage disequilibrium (LD) with a functionally relevant SNP which we have not directly genotyped in our study. We used the SNAP tool (Johnson et al., 2008) to identify such putative functional SNPs (r 2 > 0.8, based on HapMap CEU Phase II and III data, International HapMap consortium, 2005) and found that a non-synonymous coding variant in the BolA-like protein 1 gene (BOLA1) is in strong LD (rs1044808, r 2 > 0.9) with rs15931. BOLA1 encodes a protein which seems to play a role in cell proliferation or cell-cycle regulation (Kasai et al., 2004), but the precise molecular function remains unknown to date. Using the Developmental Transcriptome data from the BrainSpan database (http://www.brainspan.org/rnaseq/search/ index.html), we found that BOLA1 as well as SV2A expression patterns are present in the brain throughout life (monitored between the 8 post-conceptional week to 40 years of age). Overall, BOLA1 shows lower expression levels compared to SV2A for all brain structures available through BrainSpan. Although SV2A is a very interesting functional candidate gene for schizophrenia and was the initial focus of our interest, the localization of the top-associated SNP in the 3′UTR of HISTH2B2BE and the strong LD with a non-synonymous coding variant in the functionally uncharacterized BOLA1 gene make it difficult to pinpoint the disease-relevant susceptibility gene purely on the basis of genetic data. However, SV2A has an interesting functional characteristic which distinguishes it from HISTH2B2BE and BOLA1 (and the other genes in the broader genomic region of 47.3 kb, tagged by the htSNPs selected for this study): SV2A is a predicted target for the microRNA 137 (miR-137). Genetic variation in miR-137 produced the strongest association signal in the largest GWAS of schizophrenia performed to date, by the Psychiatric GWAS Consortium (PGC, Ripke et al., 2011). It has been speculated, that a miR-137-mediated dysregulation network is involved in the etiology of schizophrenia, since another four genes associated with schizophrenia at the level of genome-wide significance contained predicted targets for miR-137 (Ripke et al., 2011). It is reasonable to speculate that our finding for an association between schizophrenia and SNP rs15931 may be due to an underlying functional variation in SV2A. SV2A represents an additional member of the miR-137-mediated dysregulation network involved in the etiology of schizophrenia. In summary, results of our candidate gene study suggest that genetic variation at a locus containing the functional candidate gene SV2A is associated with schizophrenia in two patient–control samples of German origin. Independent studies are now warranted to further support our finding.
Role of funding source This study was supported by the German Federal Ministry of Education and Research (BMBF), within the context of the German National Genome Research Network plus (NGFNplus), and the Integrated Genome Research Network (IG) MooDS (grant 01GS08144 to Sven Cichon and Markus M. Nöthen, grant 01GS08147 to Marcella Rietschel). This work was supported by grants U01 HL089856, R01 MH087590 and R01 MH081862. Igor Nenadic was supported by a Junior Scientist Grant of the IZKF, Medical School, Jena University Hospital. Igor Nenadic, Heinrich Sauer, Markus M. Nöthen, and Sven Cichon were additionally supported through an EU grant (EUTwinsS network, RTN, FP6). Jana Strohmaier was supported by the German Research Foundation (GRK 793). The above mentioned funding sources had no involvement in the study design, the analysis and interpretation of data, the writing of the report, or the decision to submit the paper for publication.
Contributors Manuel Mattheisen, Thomas W. Mühleisen, Marcella Rietschel, Markus M. Nöthen, and Sven Cichon contributed to the study design. Marcella Rietschel, Thomas G. Schulze, Jana Strohmaier, Sandra Meier, Dan Rujescu, Igor Nenadic, Heinrich Sauer recruited and diagnosed the patients. Ina Giegling, Franziska Degenhardt, and Sandra Meier compiled the clinical data. Stephanie Witt, Jens Treutlein, Margrieta Alblas, and Per Hoffmann prepared the DNA and performed the genotyping. Manuel Mattheisen and Stefan Herms performed the statistical analysis. Manuel Mattheisen, Thomas W. Mühleisen, Marcella Rietschel, Markus M. Nöthen, and Sven Cichon analyzed and interpreted the data. Manuel Mattheisen, Thomas W. Mühleisen, Markus Nöthen, Marcella Rietschel, and Sven Cichon prepared the manuscript, with feedback from the other authors.
Conflict of interest statement The authors declare that they have no competing financial or other interests that might be perceived to influence the results and discussion reported in this paper.
Acknowledgements We are grateful to all of the patients and controls who contributed to this study. We also thank Jennifer A. Lee for carefully reading the manuscript.
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