The Association between COMT, BDNF, and NRG1 and Premorbid Social Functioning in Patients with Psychosis, Their Relatives, and Controls

Walshe, Muriel; Vassos, Evangelos; Picchioni, Marco; Shaikh, Madiha; Toulopoulou, Timothea; Collier, David; McDonald, Colm; Murray, Robin; Bramon, Elvira

doi:https://doi.org/10.6064/2012/560514

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Abstract Introduction Materials and Methods Results Discussion Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2012 | Article ID 560514 | https://doi.org/10.6064/2012/560514

The Association between COMT, BDNF, and NRG1 and Premorbid Social Functioning in Patients with Psychosis, Their Relatives, and Controls

Muriel Walshe,¹Evangelos Vassos,¹Marco Picchioni,¹Madiha Shaikh,¹Timothea Toulopoulou,¹David Collier,¹Colm McDonald,²Robin Murray,¹and Elvira Bramon¹

Academic Editor: A. Evers, C. Toni, M. A. Niznikiewicz

Received22 Apr 2012

Accepted15 May 2012

Published28 Jun 2012

Abstract

We investigated the influences of putative candidate genes for psychosis on premorbid social adjustment and on premorbid schizoid-schizotypal traits. A family-based sample was used including 177 patients with schizophrenia or bipolar I disorder with a history of psychotic symptoms, 86 of their unaffected relatives, and 116 unrelated healthy controls. Association analyses on the combined sample were conducted using the Statistical Analysis for Genetic Epidemiology software (SAGE) and adjusting for age, sex, clinical group, and the family-based nature of the data. The COMT Val¹⁵⁸Met and BDNF Val⁶⁶Met polymorphisms showed no evidence of association with either phenotype. The SNP rs221533 of the NRG1 gene was significantly associated with premorbid adjustment in adolescence with TT homozygous subjects having a poorer performance than C allele carriers. In the context of neurodevelopmental disorders such as schizophrenia and other psychoses, this finding is plausible; however, it is preliminary and requires replication in an independent sample. In a broader sense, the use of intermediate quantitative phenotypes such as the ones presented in this study may be of help to understand the mechanism of action of genetic risk factors.

1. Introduction

Premorbid social dysfunction in patients with psychosis is well documented [1–3], but recent reporting of early social deficits in their unaffected relatives suggests that such impairments may be endophenotypic markers (indicators of shared genetic risk) for the disorder [4–6]. Catechol-o-methyl transferase (COMT), brain-derived neurotrophic factor (BDNF), and neuregulin 1 (NRG1) have all been implicated in the pathophysiology of schizophrenia [7–9] and bipolar disorder (BD) [7, 10]. There is also evidence supporting the association of the following single-nucleotide polymorphisms (SNPs) with risk for both disorders: COMT Val¹⁵⁸Met [11, 12]; BDNF Val⁶⁶Met [13, 14]; NRG1 rs221533 [15]. Investigating quantitative phenotypes that characterise psychotic disorders could increase the power to identify susceptibility genes and help to understand their mechanism of action [16, 17]. While the role of these particular SNPs has been investigated in neuroimaging [18–21], neurophysiology [22–24], and cognition endophenotypes [25–28], no study to date has tested their potential effects on early social function and personality traits.

We tested whether premorbid social functioning (PSF) and personality development in childhood and adolescence are impacted upon by variation within SNPs from three genes previously reported for their association with psychosis: NRG1 rs221533, COMT Val¹⁵⁸Met, and BDNF Val⁶⁶Met in patients with psychosis, their unaffected relatives, and community controls.

2. Materials and Methods

2.1. Description of Sample

The sample included 379 Caucasian subjects recruited from the Maudsley Family Psychosis Study (M : F = 132 : 82; mean age 33, sd 7.75) and the Maudsley Twin Study (M : F = 75 : 90; mean age 35, sd 10.71) whose mothers were interviewed about their social development using the premorbid adjustment scale (PAS) and premorbid schizoid-schizotypal Traits (PSST) scale [4, 29]. A total of 177 patients fulfilled DSM-III-R or DSM-IV diagnostic criteria for a psychotic disorder, including schizophrenia and bipolar disorder with a history of psychotic symptoms [30]. Unaffected first-degree relatives () were free from psychotic illness (other psychiatric disorders were not an exclusion factor). Controls () were included if they did not have a personal or family history of psychosis. A history of alcohol or substance dependence in the last 12 months, neurological diseases, and severe head injury were exclusion criteria for all groups. All participants gave their written informed consent. The study was approved by the Joint Ethical Committee for Research at the Institute of Psychiatry and South London and Maudsley NHS Foundation Trust. Table 1 summarises the demographic characteristics of this sample.

2.2. PSA, PSST, and Clinical Scales

All participants (including controls) underwent a structured clinical interview with either the Schedule for Affective Disorders and Schizophrenia (SADS) or the Structured Clinical Interview for DSM Disorders (SCID) [30, 31] to allow for a DSM-IV diagnosis to be ascertained or ruled out. In addition, wherever available, clinical records were consulted for the patients. In order for the sample to be representative of the general population, nonpsychotic disorders such as a history of depression, anxiety, and other axis I disorders did not constitute exclusion criteria for any participant group. The unadjusted means and standard deviations for PSA and PSST scores are presented in Table 1.

A modified premorbid adjustment scale (PAS) was used to examine childhood and adolescent premorbid social function and personality development [32, 33]. The PAS scale assessed five areas of functioning (socialization, peer relations, academic achievement, school adaptation, andhobbies) over two consecutive time periods: 5–11 years(childhood—PAS1) and 12–16 years (adolescence—PAS2) [5]. Premorbid behavior and personality (age 12–16 years) were assessed using the premorbid schizoid and schizotypal traits (PSST) scale [34]. For both scales, higher scores denoted increased abnormality.

2.3. Genotype Analysis

Genomic DNA was extracted from saliva and blood samples using established procedures. The genotyping was performed in house on an ABI 7900 HT real-Time PCR system (Applied Biosystems) with standard Taqman allelic discrimination assays and under contract by KBiosciences (http://www.kbioscience.co.uk/). Quality control measures included placing three blank control samples on each plate and a minimum of four interplate and intraplate duplicated samples. Calling was performed using the SDS Software, and in cases of ambiguous calling, the genotyping was repeated. Genotype frequencies by clinical group are presented in Table 1.

2.4. Statistical Analysis

For the association of the premorbid scales with subsequent affection status (patients, relatives, controls), multivariate analysis was carried out with generalized estimating equations (GEEs) [35] with robust Hubert White sandwich estimators to accommodate intrafamilial correlations. Multiple linear GEE regression was used to compare log-transformed PAS and PSST scores of the patient and relative groups with the control group, controlling for age and gender. Statistical analyses were carried out in Stata v 10 [36] and SPSS v 15 [37]. All tests were two tailed using a 0.05 level of significance.

A separate analysis of the three groups (patients, relatives, and controls), although desirable, would lead to small, underpowered subsamples for an association study; therefore, we decided a priori to analyze the combined sample, controlling for age, gender, and affection status. Since the samples contained related individuals, tests of quantitative association of PAS and PSST with the three polymorphisms in pedigree data were conducted with the George-Elston regression method, which allows for familial (residual) association [38]. The primary association was performed employing an additive model of inheritance, and only significant findings were explored further with post hoc analyses under the dominant and recessive models. As the sample included monozygotic (MZ) twin pairs who have identical genotype, we randomly included only one twin from each MZ pair (60 MZ twins), while the dizygotic twins were treated as regular siblings. For this analysis, we utilized the ASSOC routine in the Statistical Analysis for Genetic Epidemiology software [39].

3. Results

3.1. PAS and PSST Group Comparisons

In a univariate analysis, there were statistically significant differences between the groups (patients, relatives, and controls) for PAS1 (, , ), PAS2 (, , ), and PSST (, , ). In the multivariate linear regression analysis controlling for age and gender, patients had worse scores than controls on the PAS1 (, , ); PAS2 (); PSST (, , ). The relatives group had worse scores than controls for PAS1 (, , ) and PAS2 (, , ) but not for PSST (, , ). Table 1 summarises the demographic characteristics of this sample, the PAS and PSST scores as well as genotype frequencies by clinical group.

3.2. Genetic Association Analysis

We conducted an association study of the combined sample, controlling for age, gender, and affection status. All three SNPs studied were in Hardy-Weinberg equilibrium (). We found a nominal association between variation in NRG1 and PAS2 () but not with PAS1 or PSST (). Subjects with the TT genotype had worse premorbid functioning in adolescence. Post hoc analysis under the recessive model (TT versus C allele carriers) marginally increased the significance of this association (). With the exception of a trend for the COMT val/val variant to be associated with higher PSST scores (), we found no other significant associations for BDNF or COMT. There was no significant association between the 3 SNPs and the presence of psychosis. Since the traits under study (PAS and PSST) are correlated, a multiple testing adjustment for the three loci investigated would suffice, and indeed, the association with NRG1 does remain after such adjustment.

4. Discussion

While impaired PSF has been shown to be associated with genetic risk for schizophrenia, only a few studies have attempted to investigate associations between PSF and genetic variation in candidate genes for psychosis [40, 41]. Goghari and Sponheim [42] found no link between scores on the PAS and COMT similar to our study. We failed to find an association between BDNF and PSF, but with no other published studies investigating this, no firm conclusions can be drawn here. COMT Val¹⁵⁸Met and BDNF Val⁶⁶Met polymorphisms have long been identified as candidate genes for schizophrenia, but recent meta-analyses and large-scale genome-wide association studies of schizophrenia [43–45] and bipolar disorder [46, 47] have failed to confirm their direct role in the etiology of these diseases. However, the effect of these two loci in cognition remains a strong and well replicated finding [48–52], which would make their role in social functioning and personality development plausible. Our negative findings, however, do not lend support to this hypothesis.

Our study has a number of limitations. Firstly, our sample, which includes both patients with schizophrenia and with bipolar disorder, was not large enough to subdivide it by disease, and thus, only a combined analysis could be undertaken. A heterogeneous sample like this (rather than a more specific disease focused one) could have reduced the power of the study to find associations between the candidate genes and the clinical phenotype. While our study was cross-sectional with retrospective assessments, to assess dynamic concepts like social function and personality, a prospective cohort approach would have been preferable.

Our preliminary findings suggest that NRG1 rs221533 could influence premorbid adjustment during adolescence, with the T allele being associated with poorer performance. This result is supported under the recessive model (TT versus TC and CC) and survives a multiple testing adjustment (for the three SNPs investigated). While the C allele was originally proposed as the risk allele for schizophrenia, no allelic variant of this SNP has been homogeneously implicated in subsequent replication studies [53]. For instance, the T allele was found to be overtransmitted in a Dutch schizophrenia sample [54] and in childhood onset schizophrenia [55] and to predict worse response to antipsychotics than the C allele [56]. In short, the role of NRG1 rs221533 in psychosis as well as in neurodevelopment is still not fully understood, and its expression may be influenced by other genetic, epigenetic, or environmental factors [53].

Finally, in this study, no significant association between the three SNPs selected and psychosis was observed. Of course our sample was clearly underpowered to test this kind of association due to the small effect size of common SNPs contributing to disease susceptibility [57–60]. The effect of NRG1 on a quantitative trait like PAS is probably stronger, hence the association observed in our study. Clearly, this is a preliminary study, and our finding that the T allele is associated with impaired social functioning in adolescence is exploratory and needs to be replicated in an independent sample. Nevertheless, we believe that intermediate phenotypes for psychotic disorders, like the ones we presented here as well as other measures of brain development and function, have the potential to help towards our understanding of the mechanisms by which genetic variation leads to the onset of the disease.

Conflict of Interests

The authors of this paper do not have any commercial associations that might pose a conflict of interests in connection with this paper.

Authors’ Contribution

M. Walshe and E. Vassos contributed equally to this work.

Acknowledgments

The authors are grateful to all the families who participated in this research. Dr. M. Walshe is supported by the Psychiatric Research Trust, and Dr. E. Bramon holds an MRC New Investigator Award. We also thank NARSAD (Young Investigator Awards for Dr. T. Toulopoulou and Dr. E. Bramon), the Wellcome Trust (Research Training Fellowships for Professor C. McDonald, Dr. M. Picchioni, and Dr. E. Bramon), and NIHR (postdoctoral fellowship to Dr E. Bramon). This work received additional support from the Wellcome Trust, the Stanley Medical Research Institute, the Schizophrenia Research Fund, and the British Medical Association.

References

D. N. Allen, L. V. Frantom, G. P. Strauss, and D. P. Van Kammen, “Differential patterns of premorbid academic and social deterioration in patients with schizophrenia,” Schizophrenia Research, vol. 75, no. 2-3, pp. 389–397, 2005.
View at: Publisher Site | Google Scholar
M. Cannon, P. Jones, C. Gilvarry et al., “Premorbid social functioning in schizophrenia and bipolar disorder: similarities and differences,” The American Journal of Psychiatry, vol. 154, no. 11, pp. 1544–1550, 1997.
View at: Google Scholar
M. Isohanni, P. Jones, L. Kemppainen et al., “Childhood and adolescent predictors of schizophrenia in the Northern Finland 1966 birth cohort—a descriptive life-span model,” European Archives of Psychiatry and Clinical Neuroscience, vol. 250, no. 6, pp. 311–319, 2000.
View at: Publisher Site | Google Scholar
M. M. Picchioni, M. Walshe, T. Toulopoulou et al., “Genetic modelling of childhood social development and personality in twins and siblings with schizophrenia,” Psychological Medicine, vol. 40, no. 8, pp. 1305–1316, 2010.
View at: Publisher Site | Google Scholar
M. Walshe, M. Taylor, K. Schulze et al., “Familial liability to schizophrenia and premorbid adjustment,” The British Journal of Psychiatry, vol. 191, no. 3, pp. 260–261, 2007.
View at: Publisher Site | Google Scholar
D. I. Shapiro, S. Marenco, E. H. Spoor, M. F. Egan, D. R. Weinberger, and J. M. Gold, “The Premorbid Adjustment Scale as a measure of developmental compromise in patients with schizophrenia and their healthy siblings,” Schizophrenia Research, vol. 112, no. 1–3, pp. 136–142, 2009.
View at: Publisher Site | Google Scholar
N. Craddock, M. C. O'Donovan, and M. J. Owen, “Genes for schizophrenia and bipolar disorder? Implications for psychiatric nosology,” Schizophrenia Bulletin, vol. 32, no. 1, pp. 9–16, 2006.
View at: Publisher Site | Google Scholar
M. J. Owen, N. Craddock, and M. C. O'Donovan, “Schizophrenia: genes at last?” Trends in Genetics, vol. 21, no. 9, pp. 518–525, 2005.
View at: Publisher Site | Google Scholar
E. M. Tunbridge, P. J. Harrison, and D. R. Weinberger, “Catechol-o-methyltransferase, cognition, and psychosis: Val¹⁵⁸Met and beyond,” Biological Psychiatry, vol. 60, no. 2, pp. 141–151, 2006.
View at: Publisher Site | Google Scholar
J. H. Barnett and J. W. Smoller, “The genetics of bipolar disorder,” Neuroscience, vol. 164, no. 1, pp. 331–343, 2009.
View at: Google Scholar
Z. Zhang, K. Lindpaintner, R. Che et al., “The Val/Met functional polymorphism in COMT confers susceptibility to bipolar disorder: evidence from an association study and a meta-analysis,” Journal of Neural Transmission, vol. 116, no. 10, pp. 1193–1200, 2009.
View at: Publisher Site | Google Scholar
S. J. Glatt, S. V. Faraone, and M. T. Tsuang, “Association between a functional catechol O-methyltransferase gene polymorphism and schizophrenia: meta-analysis of case-control and family-based studies,” The American Journal of Psychiatry, vol. 160, no. 3, pp. 469–476, 2003.
View at: Publisher Site | Google Scholar
P. Sklar, S. B. Gabriel, M. G. McInnis et al., “Family-based association study of 76 candidate genes in bipolar disorder: BDNF is a potential risk locus,” Molecular Psychiatry, vol. 7, no. 6, pp. 579–593, 2002.
View at: Publisher Site | Google Scholar
M. Neves-Pereira, J. K. Cheung, A. Pasdar et al., “BDNF gene is a risk factor for schizophrenia in a Scottish population,” Molecular Psychiatry, vol. 10, no. 2, pp. 208–212, 2005.
View at: Publisher Site | Google Scholar
L. Georgieva, A. Dimitrova, D. Ivanov et al., “Support for neuregulin 1 as a susceptibility gene for bipolar disorder and schizophrenia,” Biological Psychiatry, vol. 64, no. 5, pp. 419–427, 2008.
View at: Publisher Site | Google Scholar
B. I. Turetsky, M. E. Calkins, G. A. Light, A. Olincy, A. D. Radant, and N. R. Swerdlow, “Neurophysiological endophenotypes of schizophrenia: the viability of selected candidate measures,” Schizophrenia Bulletin, vol. 33, no. 1, pp. 69–94, 2007.
View at: Publisher Site | Google Scholar
D. L. Braff, R. Freedman, N. J. Schork, and I. I. Gottesman, “Deconstructing schizophrenia: an overview of the use of endophenotypes in order to understand a complex disorder,” Schizophrenia Bulletin, vol. 33, no. 1, pp. 21–32, 2007.
View at: Publisher Site | Google Scholar
A. Dutt, C. McDonald, E. Dempster et al., “The effect of COMT, BDNF, 5-HTT, NRG1 and DTNBP1 genes on hippocampal and lateral ventricular volume in psychosis,” Psychological Medicine, vol. 39, no. 11, pp. 1783–1797, 2009.
View at: Publisher Site | Google Scholar
D. Prata, G. Breen, S. Osborne, J. Munro, D. S. Clair, and D. Collier, “Association of DAO and G72(DAOA)/G30 genes with bipolar affective disorder,” American Journal of Medical Genetics B, vol. 147, no. 6, pp. 914–917, 2008.
View at: Publisher Site | Google Scholar
G. Winterer, A. Konrad, G. Vucurevic, F. Musso, P. Stoeter, and N. Dahmen, “Association of $5^{'}$ end neuregulin-1 (NRG1) gene variation with subcortical medial frontal microstructure in humans,” NeuroImage, vol. 40, no. 2, pp. 712–718, 2008.
View at: Publisher Site | Google Scholar
D. P. Prata, A. Mechelli, C. H. Y. Fu et al., “Epistasis between the DAT $3^{'}$ UTR VNTR and the COMT Val¹⁵⁸Met SNP on cortical function in healthy subjects and patients with schizophrenia,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 32, pp. 13600–13605, 2009.
View at: Publisher Site | Google Scholar
E. Bramon, E. Dempster, S. Frangou et al., “Is there an association between the COMT gene and P300 endophenotypes?” European Psychiatry, vol. 21, no. 1, pp. 70–73, 2006.
View at: Publisher Site | Google Scholar
E. Bramon, E. Dempster, S. Frangou et al., “Neuregulin-1 and the P300 waveform—a preliminary association study using a psychosis endophenotype,” Schizophrenia Research, vol. 103, no. 1–3, pp. 178–185, 2008.
View at: Publisher Site | Google Scholar
M. Shaikh, M. H. Hall, K. Schulze et al., “Do COMT, BDNF and NRG1 polymorphisms influence P50 sensory gating in psychosis?” Psychological Medicine, vol. 41, no. 2, pp. 263–276, 2011.
View at: Publisher Site | Google Scholar
E. Dempster, T. Toulopoulou, C. McDonald et al., “Association between BDNF val66 met genotype and episodic memory,” American Journal of Medical Genetics B, vol. 134, no. 1, pp. 73–75, 2005.
View at: Publisher Site | Google Scholar
J. L. Roffman, A. P. Weiss, T. Deckersbach et al., “Interactive effects of COMT Val108/158Met and MTHFR C677T on executive function in schizophrenia,” American Journal of Medical Genetics B, vol. 147, no. 6, pp. 990–995, 2008.
View at: Publisher Site | Google Scholar
A. H. Neuhaus, C. Opgen-Rhein, C. Urbanek et al., “COMT Val¹⁵⁸Met polymorphism is associated with cognitive flexibility in a signal discrimination task in schizophrenia,” Pharmacopsychiatry, vol. 42, no. 4, pp. 141–144, 2009.
View at: Publisher Site | Google Scholar
V. Nieratschker, J. Frank, T. W. Mühleisen et al., “The catechol-O-methyl transferase (COMT) gene and its potential association with schizophrenia: findings from a large German case-control and family-based sample,” Schizophrenia Research, vol. 122, no. 1–3, pp. 24–30, 2010.
View at: Publisher Site | Google Scholar
C. McDonald, N. Marshall, P. C. Sham et al., “Regional brain morphometry in patients with schizophrenia or bipolar disorder and their unaffected relatives,” The American Journal of Psychiatry, vol. 163, no. 3, pp. 478–487, 2006.
View at: Publisher Site | Google Scholar
J. Endicott and R. L. Spitzer, “A diagnostic interview: the schedule for affective disorders and schizophrenia,” Archives of General Psychiatry, vol. 35, no. 7, pp. 837–844, 1978.
View at: Google Scholar
R. L. Spitzer, J. B. W. Williams, M. Gibbon, and M. B. First, “The structured clinical interview for DSM-III-R (SCID). I. History, rationale, and description,” Archives of General Psychiatry, vol. 49, no. 8, pp. 624–629, 1992.
View at: Google Scholar
H. E. Cannon-Spoor, S. G. Potkin, and R. J. Wyatt, “Measurement of premorbid adjustment in chronic schizophrenia,” Schizophrenia Bulletin, vol. 8, no. 3, pp. 470–484, 1982.
View at: Google Scholar
C. Hollis, “Developmental precursors of child- and adolescent-onset schizophrenia and affective psychoses: diagnostic specificity and continuity with symptom dimensions,” The British Journal of Psychiatry, vol. 182, no. 1, pp. 37–44, 2003.
View at: Publisher Site | Google Scholar
A. Foerster, S. Lewis, M. Owen, and R. Murray, “Pre-morbid adjustment and personality in psychosis. Effects of sex and diagnosis,” The British Journal of Psychiatry, vol. 158, pp. 171–176, 1991.
View at: Google Scholar
K. Y. Liang and S. L. Zeger, “Longitudinal data analysis using generalized linear models,” Biometrika, vol. 73, no. 1, pp. 13–22, 1986.
View at: Publisher Site | Google Scholar
StataCorp, STATA v.10.0 for Windows. Stata Corportation, College Station, Tex, USA, 2007.
SPSS, SPSS for Windows version 15. SPSS Inc, Chicago, Ill, USA, 2006.
V. T. George and R. C. Elston, “Testing the association between polymorphic markers and quantitative traits in pedigrees,” Genetic Epidemiology, vol. 4, no. 3, pp. 193–201, 1987.
View at: Google Scholar
S.A.G.E., Statistical Analysis for Genetic Epidemiology, Release 5.4.0, 2007.
A. M. Addington, M. Gornick, A. L. Sporn et al., “Polymorphisms in the 13q33.2 gene G72/G30 are associated with childhood-onset schizophrenia and psychosis not otherwise specified,” Biological Psychiatry, vol. 55, no. 10, pp. 976–980, 2004.
View at: Publisher Site | Google Scholar
M. C. Gornick, A. M. Addington, A. Sporn et al., “Dysbindin (DTNBP1, 6p22.3) is associated with childhood-onset psychosis and endophenotypes measured by the Premorbid Adjustment Scale (PAS),” Journal of Autism and Developmental Disorders, vol. 35, no. 6, pp. 831–838, 2005.
View at: Publisher Site | Google Scholar
V. M. Goghari and S. R. Sponheim, “Differential association of the COMT Val158Met polymorphism with clinical phenotypes in schizophrenia and bipolar disorder,” Schizophrenia Research, vol. 103, no. 1–3, pp. 186–191, 2008.
View at: Publisher Site | Google Scholar
G. Kirov, I. Zaharieva, L. Georgieva et al., “A genome-wide association study in 574 schizophrenia trios using DNA pooling,” Molecular Psychiatry, vol. 14, no. 8, pp. 796–803, 2009.
View at: Publisher Site | Google Scholar
E. Zintzaras, “Brain-derived neurotrophic factor gene polymorphisms and schizophrenia: a meta-analysis,” Psychiatric Genetics, vol. 17, no. 2, pp. 69–75, 2007.
View at: Publisher Site | Google Scholar
S. Ripke, A. R. Sanders, K. S. Kendler et al., “Genome-wide association study identifies five new schizophrenia loci,” Nature Genetics, vol. 43, no. 10, pp. 969–976, 2011.
View at: Publisher Site | Google Scholar
P. Sklar, J. W. Smoller, J. Fan et al., “Whole-genome association study of bipolar disorder,” Molecular Psychiatry, vol. 13, no. 6, pp. 558–569, 2008.
View at: Publisher Site | Google Scholar
P. Sklar, S. Ripke, L. J. Scott et al., “Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4,” Nature Genetics, vol. 43, no. 10, pp. 977–983, 2011.
View at: Publisher Site | Google Scholar
A. Rosa, V. Peralta, M. J. Cuesta et al., “New evidence of association between COMT gene and prefrontal neurocognitive function in healthy individuals from sibling pairs discordant for psychosis,” The American Journal of Psychiatry, vol. 161, no. 6, pp. 1110–1112, 2004.
View at: Publisher Site | Google Scholar
M. F. Egan, M. Kojima, J. H. Callicott et al., “The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function,” Cell, vol. 112, no. 2, pp. 257–269, 2003.
View at: Publisher Site | Google Scholar
M. Gupta, H. Kaur, A. Jajodia et al., “Diverse facets of COMT: from a plausible predictive marker to a potential drug target for schizophrenia,” Current Molecular Medicine, vol. 11, no. 9, pp. 732–743, 2011.
View at: Publisher Site | Google Scholar
I. Rebollo-Mesa, M. Picchioni, M. Shaikh, E. Bramon, R. Murray, and T. Toulopoulou, “COMT (Val158/108Met) genotype moderates the impact ofantipsychotic medication on verbal IQ in twins with schizophrenia,” Psychiatric Genetics, vol. 21, no. 2, pp. 98–105, 2011.
View at: Publisher Site | Google Scholar
S. E. Harris and I. J. Deary, “The genetics of cognitive ability and cognitive ageing in healthy older people,” Trends in Cognitive Sciences, vol. 15, no. 9, pp. 388–394, 2011.
View at: Publisher Site | Google Scholar
P. J. Harrison and A. J. Law, “Neuregulin 1 and schizophrenia: genetics, gene expression, and neurobiology,” Biological Psychiatry, vol. 60, no. 2, pp. 132–140, 2006.
View at: Publisher Site | Google Scholar
S. C. Bakker, M. L. C. Hoogendoorn, J. P. Selten et al., “Neuregulin 1: genetic support for schizophrenia subtypes,” Molecular Psychiatry, vol. 9, no. 12, pp. 1061–1063, 2004.
View at: Publisher Site | Google Scholar
A. M. Addington, M. C. Gornick, P. Shaw et al., “Neuregulin 1 (8p12) and childhood-onset schizophrenia: susceptibility haplotypes for diagnosis and brain developmental trajectories,” Molecular Psychiatry, vol. 12, no. 2, pp. 195–205, 2007.
View at: Publisher Site | Google Scholar
O. Kampman, S. Anttila, A. Illi et al., “Neuregulin genotype and medication response in Finnish patients with schizophrenia,” NeuroReport, vol. 15, no. 16, pp. 2517–2520, 2004.
View at: Publisher Site | Google Scholar
M. J. Owen, N. Craddock, and M. C. O'Donovan, “Suggestion of roles for both common and rare risk variants in genome-wide studies of schizophrenia,” Archives of General Psychiatry, vol. 67, no. 7, pp. 667–673, 2010.
View at: Publisher Site | Google Scholar
S. M. Purcell, N. R. Wray, J. L. Stone et al., “Common polygenic variation contributes to risk of schizophrenia and bipolar disorder,” Nature, vol. 460, no. 7256, pp. 748–752, 2009.
View at: Publisher Site | Google Scholar
J. Hardy and N. C. Low, “Genes and environment in psychiatry: winner's curse or cure?” Archives of General Psychiatry, vol. 68, no. 5, pp. 455–456, 2011.
View at: Publisher Site | Google Scholar
P. F. Sullivan, “The psychiatric GWAS consortium: big science comes to psychiatry,” Neuron, vol. 68, no. 2, pp. 182–186, 2010.
View at: Publisher Site | Google Scholar

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Copyright © 2012 Muriel Walshe et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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