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The impact of glycogen synthase kinase 3β gene on psychotic mania in bipolar disorder patients
Progress in Neuro-Psychopharmacology & Biological Psychiatry 35 (2011) 1303–1308
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Progress in Neuro-Psychopharmacology & Biological Psychiatry j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p n p
The impact of glycogen synthase kinase 3β gene on psychotic mania in bipolar disorder patients Youn-Jung Lee a, Yong-Ku Kim a,b,⁎ a b
Department of Psychiatry, College of Medicine, Korea University, Ansan, Republic of Korea Division of Brain Korea 21 Biomedical Science, Korea University, Ansan, Republic of Korea
a r t i c l e
i n f o
Article history: Received 11 January 2011 Received in revised form 4 April 2011 Accepted 18 April 2011 Available online 23 April 2011 Keywords: − 1727A/T − 50C/T Bipolar disorder Glycogen synthase kinase 3β (GSK3β) gene polymorphism
a b s t r a c t Objective: The aim of this study was to examine the relationships between glycogen synthase 3β gene polymorphisms and bipolar I disorder, manic in a Korean sample. Methods: Patients with bipolar disorder (n = 118) and a control group (n = 158) were assessed by genotyping for GSK3β single nucleotide polymorphisms (SNPs) − 1727A/T and − 50C/T. The patients were divided into two groups according to the presence of psychotic symptoms (psychotic mania, n = 92; non-psychotic mania, n = 26) and also divided based on gender and age of onset. The severity of symptoms was measured using the Young Mania Rating Scale (YMRS) and the Brief Psychiatric Rating Scale (BPRS). Results: There were no significant differences in the genotype distributions or allelic frequencies of GSK3β polymorphisms and gender between patients with bipolar disorder and a normal control group. According to haplotype analysis, there was no association between these two groups. However, analysis of the age of onset of bipolar disorder revealed significant differences in genotype and allele distributions among the patients. Patients who were homozygous for the wild-type variant (TT) had an older age of onset than carriers of the mutant allele (A/A: 27.4 ± 9.1; A/T: 30.1 ± 11.8; T/T: 42.3 ± 19.9; p = 0.034). We detected differences in allele frequencies of the GSK3β − 1727A/T polymorphism between the psychotic mania group and the nonpsychotic mania group. Conclusion: This study suggests that GSK3β polymorphisms are not associated with bipolar disorder. However, the GSK3β SNP − 1727A/T is associated with age of onset and presence of psychotic symptoms in bipolar disorder. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Although the lifetime prevalence of bipolar disorder is approximately 1%, the morbidity rate among relatives of patients with bipolar disorder is 5–10% (Smoller and Finn, 2003). Therefore, it has been proposed that there is a stronger genetic component of bipolar disorder than other mood disorders; however genes associated with the disorder have not been identified. Lithium and valproic acid are representative mood stabilizers used to treat acute-phase and maintenance-phase bipolar disorders. Although the mechanism of lithium has not yet been fully identified,
Abbreviations: GSK3β, Glycogen Synthase Kinase 3-beta; YMRS, Young Mania Rating Scale; BPRS, Brief Psychiatric Rating Scale; SNP, Single Nucleotide Polymorphism; DSM-IV, diagnosis criteria of Diagnostic and Statistical Manual of Mental Disorders-IV; SCID-I, Structured Clinical Interview for DSM-IV Axis I Disorder; DNA, deoxyribonucleic acid; PCR, polymerase chain reaction; HTR, haplotype trend regression. ⁎ Corresponding author at: Department of Psychiatry, Korea University Ansan Hospital, Ansan, Gojan Dong, 516, Kyunggi Province, 425-020, Republic of Korea. Tel.: + 82 31 412 5140; fax: + 82 31 412 5144. E-mail address: [email protected] (Y.-K. Kim). 0278-5846/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.pnpbp.2011.04.006
(Klein and Melton (1996) suggested that lithium was effective in the treatment of bipolar disorder through direct inhibition of glycogen synthase kinase 3β (GSK3β). Valproic acid not only hinders GSK-3 directly, like lithium, but also suppresses it indirectly through phosphorylation of serine-9 of the protein (Chen et al., 1999; De Sarno et al., 2002; Grimes and Jope, 2001a; Kim et al., 2005). Therefore, results demonstrating that medications used for effective treatment of acute-phase and maintenance-phase bipolar disorders commonly suppress GSK3β imply that GSK3β plays a key role in the therapeutic action for bipolar disorder. The GSK3β gene contains single nucleotide polymorphisms (SNP), which are found most frequently at − 1727A/T and − 50C/T positions relative to the transcriptional start site and upstream of the coding sequence. Functional studies are required to evaluate these findings, because there is no obvious consensus sequence in the predicted promoter region for known transcription factor binding sites (Russ et al., 2002). GSK3β is a serine/threonine kinase found in the cell cytoplasm, and activation of this kinase regulates the activity of substrates via the addition of phosphoric acid to either a serine or threonine residue of the substrate (Jope and Roh, 2006). GSK3β is important in three signaling pathways: the Wnt signaling pathway, the MAP kinase pathway, and
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the phosphatidylinositol-3 kinase pathway. Through these pathways, GSK-3 is known to control functions such as metabolism, gene expression, neuroplasticity, cell survival and death, neurogenesis and circadian rhythms in neurons (Grimes and Jope, 2001b). The GSK3β gene is located on 3q13.3–21.1, and a previous study by Bailer et al. found that a potential gene related to bipolar disorder was also located on chromosome 3q. Therefore, it has been hypothesized that the GSK3β gene has a high possibility of being related to bipolar disorder (Bailer et al., 2002; Hansen et al., 1997). Many researchers have studied this possible relationship, but these studies have showed conflicting results. Lesort et al. (1999) reported autopsy data indicating that there were no differences in the amount and the activity of GSK3β protein compared to normal brain tissue in bipolar patients, and Nishiguchi et al. (2006) reported that the frequencies of the −1727A/T and −50T/C mutations of GSK-3β were not significantly different between bipolar patients and normal persons. However, Scassellati et al. (2007) suggested that GSK3β gene is unlikely to have a major effect on the genetic susceptibility to bipolar disorder, even when gender and age at onset of the disorder are taken into account. Benedetti et al. (2004) revealed that no association was detected between GSK3β −50T/C SNP and the presence of bipolar disorder, and GSK3β −50T/C homozygotes for the wild-type variant (T/T) displayed an earlier age at onset than did carriers of the mutant allele. Interestingly, Szczepankiewicz et al. (2006) found that a correlation between the C allele of −50C/T and T/C genotypes was observed in female patients with bipolar disorder type 2 but not in males. In a previous study, we examined the relationship between −1727A/T and −50C/T polymorphisms of GSK3β with mood disorders in 258 Korean patients with schizophrenia and bipolar disorder, and observed that the distributions of GSK3β gene polymorphisms and allelic frequencies were not significantly different between the patient group and a control group (Lee et al., 2006). Further research on the relationship between GSK3β and bipolar disorder in the Korean population is needed to elucidate the contradictory results found by these previous studies. The present study investigated the relationship between GSK3β and bipolar disorder in a Korean sample, and determined whether a connection between GSK3β and psychotic symptoms could be assessed using clinical characteristics such as age of onset and haplotype. 2. Subjects and methods 2.1. Subjects The subjects of this study were 118 Korean psychiatric patients with bipolar disorder type 1 who were admitted for hospitalization at Korea University Ansan Hospital, Ansan, Korea through the outpatient
clinic or emergency center. All subjects met the criteria of the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) for bipolar disorder (APA, 1994). Each patient was assessed by a psychiatrist using the Structured Clinical Interview for DSM-IV Axis I Disorder (SCID-I) on the first day of hospitalization, and patients who did not cooperate in initial interviews were evaluated within three days of hospitalization (First et al., 1998). Exclusion criteria included other psychiatric disorders based on DSM-IV definitions, such as schizophrenia, alcohol abuse, substance abuse and personality disorders, organic brain disease and physical disease. Data regarding age of onset, duration, and numbers of illness episode were collected through reviews of medical histories and interviews with family members. The normal control group included 158 persons who visited the health promotion center of Korea University Ansan Hospital and volunteers who participated in this study. Individuals with psychiatric or family histories of psychiatric disease, and/or histories of taking psychiatric medications, were excluded from the control group. All study participants gave informed consent for participation. We assessed the severity of manic symptoms using the Young Mania Rating Scale (YMRS; Young et al., 1978) and psychotic symptoms were assessed using the Brief Psychiatric Rating Scale (BPRS; Bech et al., 1988). The YMRS and BPRS were assessed on the first day of hospitalization. Patients who did not cooperate in the initial interview were assessed within three days of hospitalization. The presence of psychotic symptoms was evaluated by the existence of auditory hallucinations or delusions based on DSM-IV criteria and assessed via interviews with patients and reviews of medical records. This study was approved by the Institutional Review Board of Korea University Ansan Hospital. 2.2. Genotyping DNA was extracted from blood leukocytes using the Wizard Genomic DNA purification kit (Promega, USA). Polymerase chain reaction (PCR) was performed to genotype the 1727A/T SNP of the GSK-3β gene with the forward primer 5′-TCA CAC AAA AAT CCA ATT TTG T-3′ and the reverse primer 5′-ACA GTG AGG TAT GGC TAC GTC A-3′. The amplification mixture contained 1 μl of 100 ng/μl DNA, 2.5 μl of 10× Ex Taq buffer, 2 μl of 2.5 mM Ex dNTP mixture, 1 μl primer, 18.375 μl distilled water, and 0.125 μl Taq polymerase (TaKaRa, Japan). Samples were amplified using a Thermocycler (GeneAmp PCR system 2700, Applied Biosystems, Foster City, CA, USA) for 36 cycles. After an initial 5 min at 95 °C, each cycle consisted of 45 s at 95 °C, 45 s at 54 °C, and 45 s at 72 °C. After a final 10 min at 72 °C, the reaction was terminated at 4 °C. The amplified DNA was digested with the restriction enzyme MseI (New England Biolabs), which targets the -1727A site, and the product
Table 1 Demographic characteristics of patients and normal control subjects. Characteristic
Age (years) Age of onset (years) Number of episodes Years of education (years) Duration of illness (month) Baseline YMRS Baseline BPRS
Female (sex)
Patients without psychotic features (N = 26)
Normal controls (N = 158)
Patients with psychotic features (N = 92)
Mean ± SD
Mean ± SD
Mean ± SD
35.6 ± 8.6
33.8 ± 10.9 28.4 ± 10.2 2.5 ± 3.0 12.4 ± 2.9 63.0 ± 84.4 33.3 ± 10.3 21.3 ± 9.3
34.4 ± 12.5 29.0 ± 11.5 2.6 ± 2.2 12.9 ± 1.6 100.0 ± 144.3 30.4 ± 12.5 16.1 ± 8.3
13.7 ± 2.2
N 96
% 58.9
N 51
% 76.1
SD: standard deviation, YMRS: Young Mania Rating Scale, BPRS: Brief Psychiatric Rating Scale. a t-test between normal controls and patients with bipolar disorder. b t-test between patients with psychotic features and patients without psychotic features. ⁎ p b 0.05.
N 16
% 23.9
Analysis
t
p
0.06 0.04 0.03 0.54 1.53 1.31 5.73
0.81a 0.84b 0.87b 0.46b 0.22b 0.25b 0.019⁎,b
χ2(df = 2) 0.31
p 0.58a
Y.-J. Lee, Y.-K. Kim / Progress in Neuro-Psychopharmacology & Biological Psychiatry 35 (2011) 1303–1308
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Table 2 Genotype and allele frequencies of two SNPs GSK3bbetaNin normal controls and patients with bipolar disorder. GSK3bbetaNgene promoter − 1727A/T
Genotype A/A
A/T
Normal controls (N = 158)
117 74.0% 86 72.9%
38 24.0% 29 24.6%
C/C
C/T 88 55.7% 68 57.6%
Bipolar disorder patients (N = 118)
GSK3bbetaNgene promoter − 50C/T Normal controls (N = 158) Bipolar disorder patients (N = 118)
40 25.3% 34 28.8%
Analysis
Allele
χ2 (df = 2)
p
A
0.15
0.928
272 86.1% 201 85.2%
T/T
χ2 (df = 2)
p
C
30 19.0% 16 13.6%
1.55
0.461
168 53.2% 136 57.6%
T/T 3 2.0% 3 2.5%
Analysis χ2 (df = 1)
p
0.09
0.764
T
χ2 (df = 1)
p
148 46.8% 100 42.4%
1.09
0.297
T 44 13.9% 35 14.8%
GSK: glycogen synthase kinase.
was analyzed by electrophoresis in 3% agarose gels and stained with ethidium bromide. Homozygous genotypes were identified by the presence of a single 350, 116, or 28 bp band (A/A), or bands of 378 and 116 bp (T/T). The heterozygous genotype had four bands: 378, 350, 116, and 28 bp (A/T). PCR was performed to genotype the 50C/T SNP of the GSK-3β gene with the forward primer 5′-GAC GTC CGT GAT TGG CTC-3′ and the reverse primer 5′-AGC CCA GAC CCC TGT CAG-3′. Samples were amplified as described above with the alteration of a binding step at 64.2 °C. The amplified DNA was digested with the restriction enzyme AluI (New England Biolabs), which targets the −50T site, and the product was analyzed as described above. Homozygous genotypes were identified by the presence of a single 344 bp band (C/C), or bands of 220 and 124 bp (T/T). The heterozygous genotype had three bands: 344, 220, and 124 bp (C/T). 2.3. Statistical analysis Hardy–Weinberg equilibrium was assessed with chi-square tests and clinical records including age, age of onset, numbers of illness episodes, educational background and duration of episodes were analyzed with t-tests. Chi-square tests were used to compare genotype and allele frequencies between bipolar disorder patients and normal controls. Fisher exact tests were used when the number of samples was less than 5. In addition, the bipolar disorder group was divided into two subgroups with and without psychotic symptoms and chi-square tests were used to compare their genotype and allelic frequencies with those of the control group, and to evaluate the relationships between severity of symptoms (YMRS, BPRS) and progression of disease (age of onset, numbers of illness episode). Haplotype correlations were examined by haplotype trend regression (HTR) analysis. Statistical analyses were performed using SAS version 9.2 and PowerMarker (http://statgen.ncsu.edu/powermarker/index.html). P-values less than 0.05 were considered to be statistically significant. Considering the less frequent allele of −1727 A/T and −50C/T and a significance level of 0.05, the study had powers of 88.9 and 97.8% (OR = 2.0; log-additive, dominant), respectively, calculated using the QUANTO 1.2.4 program (http://hydra.usc.edu/gxe). Table 3 Haplotype frequency estimation of two SNPs of GSK3bbetaN between normal control and patients with bipolar disorder. GSK3bbetaN gene promoter − 1727A/T
GSK3bbetaN gene promoter -50C/T
A C A T T C T T Haplotype trend regression p-value: 0.686 GSK: glycogen synthase kinase.
Normal controls (N = 158)
Bipolar disorder patients (N = 118)
0.46 0.40 0.12 0.02
0.43 0.42 0.13 0.02
3. Results 3.1. Sociodemographic characteristics Age and gender were not significantly different between bipolar disorder and control groups (Table 1), and age of onset, number of illness episodes, educational background, duration of episodes, YMRS and BPRS scores were not significantly different between groups with and without psychotic symptoms. However, psychotic mania patients recorded significantly higher BPRS scores than non-psychotic mania patients (psychotic mania: 21.3 ±9.3 vs. non-psychotic mania: 16.1 ± 8.2). 3.2. Genotype and allelic frequencies of bipolar disorder and control groups SNPs of interest were in Hardy–Weinberg equilibrium in both bipolar disorder and control groups. No significant differences in the distributions and allelic frequencies of the two polymorphisms were observed between the groups (Table 2). Comparisons of the haplotypes of − 1727A/T and − 50C/T also showed no significant differences between groups (Table 3). 3.3. Correlation between age of onset and gene polymorphisms in bipolar disorder patients We next examined whether there was a correlation between gene polymorphisms and age of onset of disease. At the −1727A/T locus, the TT genotype was associated with older age of onset than other genotypes (A/A: 27.4 ± 9.1; A/T: 30.1 ± 11.8; T/T: 42.3 ± 19.9; p = 0.034). However, no correlations between gene polymorphisms
Table 4 Comparison of clinical variables in bipolar disorder. GSK3bbetaN gene promoter −1727A/T
Genotype A/A
A/T
T/T
ANOVA F
p
Age of onset (years) Number of episode Baseline YMRS Baseline BPRS
27.4 ± 9.1 2.6 ± 3.2 32.8 ± 11.2 20.0 ± 9.1
30.1 ± 11.8 2.0 ± 1.9 31.7 ± 9.9 20.6 ± 10.6
42.3 ± 19.9 2.0 ± 2.0 36.3 ± 13.5 18.0 ± 4.6
3.52 0.39 0.26 0.11
0.034⁎ 0.68 0.774 0.895
GSK3bbetaN gene promoter − 50C/T
C/C
C/T
T/T
F
P
Age of onset (years) Number of episode Baseline YMRS Baseline BPRS
28.8 ± 11.2 2.2 ± 1.9 32.2 ± 11.2 17.8 ± 9.1
28.5 ± 10.7 2.7 ± 3.4 32.7 ± 11.3 20.7 ± 9.1
28.1 ± 8.5 2.3 ± 2.4 33.4 ± 9.0 21.7 ± 10.3
0.02 0.31 0.06 1.18
0.980 0.732 0.938 0.313
YMRS: Young Mania Rating Scale, BPRS: Brief Psychiatric Rating Scale, and ANOVA: analysis of variance. ⁎ p b 0.05.
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70.00
1.00: A/A genotype 2.00: A/T genotype 3.00: T/T genotype
60.00
Age of onset
50.00
40.00
30.00
20.00
10.00
0.00 1.00
1.50
2.00
2.50
3.00
GSK–3β 1727A/T Fig. 1. Comparison of clinical variables in bipolar disorder. Correlation between GSK3β − 1727A/T polymorphisms and age of onset of disease.
and BPRS or YMRS scores, or numbers of illness episode were observed (Table 4, Figs. 1 and 2).
3.4. Genotype and allelic frequency in bipolar disorder patients with and without psychotic symptoms The two subgroups with and without psychotic symptoms differed in genotype and allelic frequencies of the − 1727A/T SNP (Table 5). In particular, the psychotic mania group showed higher A allelic frequency (genotype: χ2 = 12.191, p = 0.0023; allele: χ2 = 7.721, p = 0.0055). On the contrary, the genotype distributions and allelic frequencies of the − 50C/T SNP were not significantly different between the two subgroups.
4. Discussion This study investigated the relationships of GSK3β gene polymorphisms with bipolar disorder and the presence of psychotic symptoms. According to these results, genotype distributions and allelic frequencies of GSK3β polymorphisms were not significantly different between bipolar disorder and control groups. Moreover, GSK3β haplotypes were not related to bipolar disorder. These findings were consistent with those of our previous study (Lee et al., 2006). This study revealed correlations between GSK3β polymorphisms and age of onset of bipolar disorder. Benedetti et al. (2004) reported that, among bipolar disorder patients there is a higher frequency of the T allele in GSK3β −50C/T in patients with significantly younger age of onset. The present study detected a correlation between the −1727A/T
70.00
1.00: C/C genotype 2.00: C/T genotype 3.00: T/T genotype
60.00
Age of onset
50.00
40.00
30.00
20.00
10.00
0.00 1.00
1.50
2.00
2.50
3.00
GSK–3β 50 C/T Fig. 2. Comparison of clinical variables in bipolar disorder. Correlation between GSK3β − 50C/T polymorphisms and age of onset of disease.
Y.-J. Lee, Y.-K. Kim / Progress in Neuro-Psychopharmacology & Biological Psychiatry 35 (2011) 1303–1308
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Table 5 Genotype and allele frequencies in psychotic bipolar disorder group and non-psychotic bipolar disorder group. GSK-3β − 1727A/T. GSK3bbetaN gene promoter − 1727A/T
Normal controls (N = 158) Patients with psychotic features (N = 92) Patients without psychotic features (N = 26)
GSK3bbetaNgene promoter − 50C/T Normal controls (N = 158) Patients with psychotic features (N = 92) Patients without psychotic features (N = 26)
Genotype
Analysis
A/A
A/T
T/T
117 74.0% 71 77.17% 15 57.69%
38 24.0% 21 22.83% 8 30.77%
3 2.0% 0 0% 3 11.54%
C/C
C/T
T/T
88 55.7% 56 60.87% 12 46.15%
30 19.0% 10 10.87% 6 23.08%
40 25.3% 26 28.26% 8 30.77%
χ2 (df = 2) 0.15
Allele p
A
0.928
272 86.1% 163 88.59% 38 73.08%
Analysis T 44 13.9% 21 11.41% 14 26.92%
χ2 (df = 1)
p
0.09
0.764
7.721
0.0055⁎
12.191
0.0023⁎
χ2 (df = 2)
p
C
T
χ2 (df = 1)
p
1.55
0.461
0.297
0.2194
148 46.8% 76 41.3% 24 46.15%
1.09
3.034
168 53.2% 108 58.7% 28 53.85%
0.391
0.5321
C = Normal control, P = Patients with psychotic features, and N = Patients without psychotic features. ⁎ p b 0.016.
SNP of GSK3β and age of onset, as patients with the A allele had a younger age of onset on average than those with T allele. This result is meaningful, considering the results of a previous study that found that relatives of patients with younger age of onset displayed higher morbidity rates from bipolar disorder as well as younger ages of onset than relatives of patients with older age of onset (Baron et al., 1981). Although Szczepankiewicz et al. (2006) reported that the allelic frequency of −50C/T was significantly different in females with bipolar disorder type 2, but we did not detect any significant differences in expression of genotypes by gender in the present study. Associations between GSK-3β gene polymorphisms and psychotic symptoms can be inferred due to three possible roles. Three mechanistic possibilities are changes in the dopamine system, potential disturbance of the Akt/GSK-3β signaling pathway and abnormal Wnt signaling pathways (Alimohamad et al., 2005; Gil et al., 2003; Ikeda et al., 2004; McMahon and Bradley, 1990, Sep). Many researchers have insisted that the GSK3β gene influences psychotic symptoms of psychiatric disorders, but only a few studies exist investigating the relationship between bipolar disorder and psychotic symptoms. Serretti et al. (2008) found that the genotype GSK3β-50T/C was related to delusion and personality traits of harm, avoidance, and self-transcendence among mood disorder patients. The present study also detected differences in distributions of the GSK3β-1727A/T genotype and allelic frequencies between bipolar disorder patients with and without psychotic symptoms. In particular, the frequency of the A allele differed according to the presence of psychotic symptoms. Limitations of this study are as follows. First, the small sample size of this study was insufficient to fully detect correlations between GSK3β gene polymorphisms and bipolar disorder. More studies with larger samples are considered to be necessary in the future. Second, this study examined only two of many polymorphisms associated with the GSK3β gene. Future studies of the relationships between other GSK3β polymorphisms and psychiatric disorders may shed light on the role of this important gene (Ikeda et al., 2005; Russ et al., 2001). Third, the relationship of the −1727A/T SNP with age at onset is indicated by only three TT cases. Although a statistical significance is observed, the number of the cases is too small to say that this result is meaningful. However, as mentioned before, that is caused by small sample size. Previous studies of the relationships between GSK3β polymorphisms and psychiatric disorders have yielded conflicting findings. These discrepancies highlight the need for further research. The present study investigated the relationships between bipolar disorder and two GSK3β polymorphisms, and did not find any statistically significant associations between them. However, we found that the −1727A/T SNP
of GSK3β was related to age of onset of bipolar disorder and the presence of psychotic mania. In the future, studies building on these findings should eventually reveal the roles of GSK3β gene polymorphisms in psychiatric disorders. Acknowledgments This research was performed as a part of master's thesis (in Medicine) by Dr. Lee Y-J. References Alimohamad H, Rajakumar N, Seah YH, Rushlow W. Antipsychotics alter the protein expression levels of beta-catenin and GSK-3 in the rat medial prefrontal cortex and striatum. Biol Psychiatry 2005;57:533–42. APA. Diagnostic and statstical manual of mental disorders4th edition. . Washington DC: American Psychiatric Press; 1994. Bailer U, Leisch F, Meszaros K, Lenzinger E, Willinger U, Strobl R, et al. Genome scan for susceptibility loci for schizophrenia and bipolar disorder. Biol Psychiatry 2002;52: 40–52. Baron M, Mendlewicz J, Klotz J. Age-of-onset and genetic transmission in affective disorders. Acta Psychiatr Scand 1981;64:373–80. Bech P, Larsen JK, Andersen J. The BPRS: psychometric developments. Psychopharmacol Bull 1988;24:118–21. Benedetti F, Bernasconi A, Lorenzi C, Pontiggia A, Serretti A, Colombo C, et al. A single nucleotide polymorphism in glycogen synthase kinase 3-beta promoter gene influences onset of illness in patients affected by bipolar disorder. Neurosci Lett 2004;355:37–40. Chen G, Huang LD, Jiang YM, Manji HK. The mood-stabilizing agent valproate inhibits the activity of glycogen synthase kinase-3. J Neurochem 1999;72:1327–30. De Sarno P, Li X, Jope RS. Regulation of Akt and glycogen synthase kinase-3 beta phosphorylation by sodium valproate and lithium. Neuropharmacology 2002;43: 1158–64. First MSR, Gibbon M, William JB. Structured clinical interview for DSM-IV axis I disorder-patient edition (SCID-I/NP, version 2.0). New York: Biometrics Research Department, New York State Psychiatric Institute; 1998. Gil M, Zhen X, Friedman E. Prenatal cocaine exposure alters glycogen synthase kinase3beta (GSK3beta) pathway in select rabbit brain areas. Neurosci Lett 2003;349: 143–6. Grimes CA, Jope RS. CREB DNA binding activity is inhibited by glycogen synthase kinase-3 beta and facilitated by lithium. J Neurochem 2001a;78:1219–32. Grimes CA, Jope RS. The multifaceted roles of glycogen synthase kinase 3beta in cellular signaling. Prog Neurobiol 2001b;65:391–426. Hansen L, Arden KC, Rasmussen SB, Viars CS, Vestergaard H, Hansen T, et al. Chromosomal mapping and mutational analysis of the coding region of the glycogen synthase kinase-3alpha and beta isoforms in patients with NIDDM. Diabetologia 1997;40:940–6. Ikeda M, Iwata N, Suzuki T, Kitajima T, Yamanouchi Y, Kinoshita Y, et al. Association of AKT1 with schizophrenia confirmed in a Japanese population. Biol Psychiatry 2004;56:698–700. Ikeda M, Iwata N, Suzuki T, Kitajima T, Yamanouchi Y, Kinoshita Y, et al. No association of GSK3beta gene (GSK3B) with Japanese schizophrenia. Am J Med Genet B Neuropsychiatr Genet 2005;134B:90–2. Jope RS, Roh MS. Glycogen synthase kinase-3 (GSK3) in psychiatric diseases and therapeutic interventions. Curr Drug Targets 2006;7:1421–34.
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The impact of glycogen synthase kinase 3β gene on psychotic mania in bipolar disorder patients Youn-Jung Lee a, Yong-Ku Kim a,b,⁎ a b
Department of Psychiatry, College of Medicine, Korea University, Ansan, Republic of Korea Division of Brain Korea 21 Biomedical Science, Korea University, Ansan, Republic of Korea
a r t i c l e
i n f o
Article history: Received 11 January 2011 Received in revised form 4 April 2011 Accepted 18 April 2011 Available online 23 April 2011 Keywords: − 1727A/T − 50C/T Bipolar disorder Glycogen synthase kinase 3β (GSK3β) gene polymorphism
a b s t r a c t Objective: The aim of this study was to examine the relationships between glycogen synthase 3β gene polymorphisms and bipolar I disorder, manic in a Korean sample. Methods: Patients with bipolar disorder (n = 118) and a control group (n = 158) were assessed by genotyping for GSK3β single nucleotide polymorphisms (SNPs) − 1727A/T and − 50C/T. The patients were divided into two groups according to the presence of psychotic symptoms (psychotic mania, n = 92; non-psychotic mania, n = 26) and also divided based on gender and age of onset. The severity of symptoms was measured using the Young Mania Rating Scale (YMRS) and the Brief Psychiatric Rating Scale (BPRS). Results: There were no significant differences in the genotype distributions or allelic frequencies of GSK3β polymorphisms and gender between patients with bipolar disorder and a normal control group. According to haplotype analysis, there was no association between these two groups. However, analysis of the age of onset of bipolar disorder revealed significant differences in genotype and allele distributions among the patients. Patients who were homozygous for the wild-type variant (TT) had an older age of onset than carriers of the mutant allele (A/A: 27.4 ± 9.1; A/T: 30.1 ± 11.8; T/T: 42.3 ± 19.9; p = 0.034). We detected differences in allele frequencies of the GSK3β − 1727A/T polymorphism between the psychotic mania group and the nonpsychotic mania group. Conclusion: This study suggests that GSK3β polymorphisms are not associated with bipolar disorder. However, the GSK3β SNP − 1727A/T is associated with age of onset and presence of psychotic symptoms in bipolar disorder. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Although the lifetime prevalence of bipolar disorder is approximately 1%, the morbidity rate among relatives of patients with bipolar disorder is 5–10% (Smoller and Finn, 2003). Therefore, it has been proposed that there is a stronger genetic component of bipolar disorder than other mood disorders; however genes associated with the disorder have not been identified. Lithium and valproic acid are representative mood stabilizers used to treat acute-phase and maintenance-phase bipolar disorders. Although the mechanism of lithium has not yet been fully identified,
Abbreviations: GSK3β, Glycogen Synthase Kinase 3-beta; YMRS, Young Mania Rating Scale; BPRS, Brief Psychiatric Rating Scale; SNP, Single Nucleotide Polymorphism; DSM-IV, diagnosis criteria of Diagnostic and Statistical Manual of Mental Disorders-IV; SCID-I, Structured Clinical Interview for DSM-IV Axis I Disorder; DNA, deoxyribonucleic acid; PCR, polymerase chain reaction; HTR, haplotype trend regression. ⁎ Corresponding author at: Department of Psychiatry, Korea University Ansan Hospital, Ansan, Gojan Dong, 516, Kyunggi Province, 425-020, Republic of Korea. Tel.: + 82 31 412 5140; fax: + 82 31 412 5144. E-mail address: [email protected] (Y.-K. Kim). 0278-5846/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.pnpbp.2011.04.006
(Klein and Melton (1996) suggested that lithium was effective in the treatment of bipolar disorder through direct inhibition of glycogen synthase kinase 3β (GSK3β). Valproic acid not only hinders GSK-3 directly, like lithium, but also suppresses it indirectly through phosphorylation of serine-9 of the protein (Chen et al., 1999; De Sarno et al., 2002; Grimes and Jope, 2001a; Kim et al., 2005). Therefore, results demonstrating that medications used for effective treatment of acute-phase and maintenance-phase bipolar disorders commonly suppress GSK3β imply that GSK3β plays a key role in the therapeutic action for bipolar disorder. The GSK3β gene contains single nucleotide polymorphisms (SNP), which are found most frequently at − 1727A/T and − 50C/T positions relative to the transcriptional start site and upstream of the coding sequence. Functional studies are required to evaluate these findings, because there is no obvious consensus sequence in the predicted promoter region for known transcription factor binding sites (Russ et al., 2002). GSK3β is a serine/threonine kinase found in the cell cytoplasm, and activation of this kinase regulates the activity of substrates via the addition of phosphoric acid to either a serine or threonine residue of the substrate (Jope and Roh, 2006). GSK3β is important in three signaling pathways: the Wnt signaling pathway, the MAP kinase pathway, and
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the phosphatidylinositol-3 kinase pathway. Through these pathways, GSK-3 is known to control functions such as metabolism, gene expression, neuroplasticity, cell survival and death, neurogenesis and circadian rhythms in neurons (Grimes and Jope, 2001b). The GSK3β gene is located on 3q13.3–21.1, and a previous study by Bailer et al. found that a potential gene related to bipolar disorder was also located on chromosome 3q. Therefore, it has been hypothesized that the GSK3β gene has a high possibility of being related to bipolar disorder (Bailer et al., 2002; Hansen et al., 1997). Many researchers have studied this possible relationship, but these studies have showed conflicting results. Lesort et al. (1999) reported autopsy data indicating that there were no differences in the amount and the activity of GSK3β protein compared to normal brain tissue in bipolar patients, and Nishiguchi et al. (2006) reported that the frequencies of the −1727A/T and −50T/C mutations of GSK-3β were not significantly different between bipolar patients and normal persons. However, Scassellati et al. (2007) suggested that GSK3β gene is unlikely to have a major effect on the genetic susceptibility to bipolar disorder, even when gender and age at onset of the disorder are taken into account. Benedetti et al. (2004) revealed that no association was detected between GSK3β −50T/C SNP and the presence of bipolar disorder, and GSK3β −50T/C homozygotes for the wild-type variant (T/T) displayed an earlier age at onset than did carriers of the mutant allele. Interestingly, Szczepankiewicz et al. (2006) found that a correlation between the C allele of −50C/T and T/C genotypes was observed in female patients with bipolar disorder type 2 but not in males. In a previous study, we examined the relationship between −1727A/T and −50C/T polymorphisms of GSK3β with mood disorders in 258 Korean patients with schizophrenia and bipolar disorder, and observed that the distributions of GSK3β gene polymorphisms and allelic frequencies were not significantly different between the patient group and a control group (Lee et al., 2006). Further research on the relationship between GSK3β and bipolar disorder in the Korean population is needed to elucidate the contradictory results found by these previous studies. The present study investigated the relationship between GSK3β and bipolar disorder in a Korean sample, and determined whether a connection between GSK3β and psychotic symptoms could be assessed using clinical characteristics such as age of onset and haplotype. 2. Subjects and methods 2.1. Subjects The subjects of this study were 118 Korean psychiatric patients with bipolar disorder type 1 who were admitted for hospitalization at Korea University Ansan Hospital, Ansan, Korea through the outpatient
clinic or emergency center. All subjects met the criteria of the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) for bipolar disorder (APA, 1994). Each patient was assessed by a psychiatrist using the Structured Clinical Interview for DSM-IV Axis I Disorder (SCID-I) on the first day of hospitalization, and patients who did not cooperate in initial interviews were evaluated within three days of hospitalization (First et al., 1998). Exclusion criteria included other psychiatric disorders based on DSM-IV definitions, such as schizophrenia, alcohol abuse, substance abuse and personality disorders, organic brain disease and physical disease. Data regarding age of onset, duration, and numbers of illness episode were collected through reviews of medical histories and interviews with family members. The normal control group included 158 persons who visited the health promotion center of Korea University Ansan Hospital and volunteers who participated in this study. Individuals with psychiatric or family histories of psychiatric disease, and/or histories of taking psychiatric medications, were excluded from the control group. All study participants gave informed consent for participation. We assessed the severity of manic symptoms using the Young Mania Rating Scale (YMRS; Young et al., 1978) and psychotic symptoms were assessed using the Brief Psychiatric Rating Scale (BPRS; Bech et al., 1988). The YMRS and BPRS were assessed on the first day of hospitalization. Patients who did not cooperate in the initial interview were assessed within three days of hospitalization. The presence of psychotic symptoms was evaluated by the existence of auditory hallucinations or delusions based on DSM-IV criteria and assessed via interviews with patients and reviews of medical records. This study was approved by the Institutional Review Board of Korea University Ansan Hospital. 2.2. Genotyping DNA was extracted from blood leukocytes using the Wizard Genomic DNA purification kit (Promega, USA). Polymerase chain reaction (PCR) was performed to genotype the 1727A/T SNP of the GSK-3β gene with the forward primer 5′-TCA CAC AAA AAT CCA ATT TTG T-3′ and the reverse primer 5′-ACA GTG AGG TAT GGC TAC GTC A-3′. The amplification mixture contained 1 μl of 100 ng/μl DNA, 2.5 μl of 10× Ex Taq buffer, 2 μl of 2.5 mM Ex dNTP mixture, 1 μl primer, 18.375 μl distilled water, and 0.125 μl Taq polymerase (TaKaRa, Japan). Samples were amplified using a Thermocycler (GeneAmp PCR system 2700, Applied Biosystems, Foster City, CA, USA) for 36 cycles. After an initial 5 min at 95 °C, each cycle consisted of 45 s at 95 °C, 45 s at 54 °C, and 45 s at 72 °C. After a final 10 min at 72 °C, the reaction was terminated at 4 °C. The amplified DNA was digested with the restriction enzyme MseI (New England Biolabs), which targets the -1727A site, and the product
Table 1 Demographic characteristics of patients and normal control subjects. Characteristic
Age (years) Age of onset (years) Number of episodes Years of education (years) Duration of illness (month) Baseline YMRS Baseline BPRS
Female (sex)
Patients without psychotic features (N = 26)
Normal controls (N = 158)
Patients with psychotic features (N = 92)
Mean ± SD
Mean ± SD
Mean ± SD
35.6 ± 8.6
33.8 ± 10.9 28.4 ± 10.2 2.5 ± 3.0 12.4 ± 2.9 63.0 ± 84.4 33.3 ± 10.3 21.3 ± 9.3
34.4 ± 12.5 29.0 ± 11.5 2.6 ± 2.2 12.9 ± 1.6 100.0 ± 144.3 30.4 ± 12.5 16.1 ± 8.3
13.7 ± 2.2
N 96
% 58.9
N 51
% 76.1
SD: standard deviation, YMRS: Young Mania Rating Scale, BPRS: Brief Psychiatric Rating Scale. a t-test between normal controls and patients with bipolar disorder. b t-test between patients with psychotic features and patients without psychotic features. ⁎ p b 0.05.
N 16
% 23.9
Analysis
t
p
0.06 0.04 0.03 0.54 1.53 1.31 5.73
0.81a 0.84b 0.87b 0.46b 0.22b 0.25b 0.019⁎,b
χ2(df = 2) 0.31
p 0.58a
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Table 2 Genotype and allele frequencies of two SNPs GSK3bbetaNin normal controls and patients with bipolar disorder. GSK3bbetaNgene promoter − 1727A/T
Genotype A/A
A/T
Normal controls (N = 158)
117 74.0% 86 72.9%
38 24.0% 29 24.6%
C/C
C/T 88 55.7% 68 57.6%
Bipolar disorder patients (N = 118)
GSK3bbetaNgene promoter − 50C/T Normal controls (N = 158) Bipolar disorder patients (N = 118)
40 25.3% 34 28.8%
Analysis
Allele
χ2 (df = 2)
p
A
0.15
0.928
272 86.1% 201 85.2%
T/T
χ2 (df = 2)
p
C
30 19.0% 16 13.6%
1.55
0.461
168 53.2% 136 57.6%
T/T 3 2.0% 3 2.5%
Analysis χ2 (df = 1)
p
0.09
0.764
T
χ2 (df = 1)
p
148 46.8% 100 42.4%
1.09
0.297
T 44 13.9% 35 14.8%
GSK: glycogen synthase kinase.
was analyzed by electrophoresis in 3% agarose gels and stained with ethidium bromide. Homozygous genotypes were identified by the presence of a single 350, 116, or 28 bp band (A/A), or bands of 378 and 116 bp (T/T). The heterozygous genotype had four bands: 378, 350, 116, and 28 bp (A/T). PCR was performed to genotype the 50C/T SNP of the GSK-3β gene with the forward primer 5′-GAC GTC CGT GAT TGG CTC-3′ and the reverse primer 5′-AGC CCA GAC CCC TGT CAG-3′. Samples were amplified as described above with the alteration of a binding step at 64.2 °C. The amplified DNA was digested with the restriction enzyme AluI (New England Biolabs), which targets the −50T site, and the product was analyzed as described above. Homozygous genotypes were identified by the presence of a single 344 bp band (C/C), or bands of 220 and 124 bp (T/T). The heterozygous genotype had three bands: 344, 220, and 124 bp (C/T). 2.3. Statistical analysis Hardy–Weinberg equilibrium was assessed with chi-square tests and clinical records including age, age of onset, numbers of illness episodes, educational background and duration of episodes were analyzed with t-tests. Chi-square tests were used to compare genotype and allele frequencies between bipolar disorder patients and normal controls. Fisher exact tests were used when the number of samples was less than 5. In addition, the bipolar disorder group was divided into two subgroups with and without psychotic symptoms and chi-square tests were used to compare their genotype and allelic frequencies with those of the control group, and to evaluate the relationships between severity of symptoms (YMRS, BPRS) and progression of disease (age of onset, numbers of illness episode). Haplotype correlations were examined by haplotype trend regression (HTR) analysis. Statistical analyses were performed using SAS version 9.2 and PowerMarker (http://statgen.ncsu.edu/powermarker/index.html). P-values less than 0.05 were considered to be statistically significant. Considering the less frequent allele of −1727 A/T and −50C/T and a significance level of 0.05, the study had powers of 88.9 and 97.8% (OR = 2.0; log-additive, dominant), respectively, calculated using the QUANTO 1.2.4 program (http://hydra.usc.edu/gxe). Table 3 Haplotype frequency estimation of two SNPs of GSK3bbetaN between normal control and patients with bipolar disorder. GSK3bbetaN gene promoter − 1727A/T
GSK3bbetaN gene promoter -50C/T
A C A T T C T T Haplotype trend regression p-value: 0.686 GSK: glycogen synthase kinase.
Normal controls (N = 158)
Bipolar disorder patients (N = 118)
0.46 0.40 0.12 0.02
0.43 0.42 0.13 0.02
3. Results 3.1. Sociodemographic characteristics Age and gender were not significantly different between bipolar disorder and control groups (Table 1), and age of onset, number of illness episodes, educational background, duration of episodes, YMRS and BPRS scores were not significantly different between groups with and without psychotic symptoms. However, psychotic mania patients recorded significantly higher BPRS scores than non-psychotic mania patients (psychotic mania: 21.3 ±9.3 vs. non-psychotic mania: 16.1 ± 8.2). 3.2. Genotype and allelic frequencies of bipolar disorder and control groups SNPs of interest were in Hardy–Weinberg equilibrium in both bipolar disorder and control groups. No significant differences in the distributions and allelic frequencies of the two polymorphisms were observed between the groups (Table 2). Comparisons of the haplotypes of − 1727A/T and − 50C/T also showed no significant differences between groups (Table 3). 3.3. Correlation between age of onset and gene polymorphisms in bipolar disorder patients We next examined whether there was a correlation between gene polymorphisms and age of onset of disease. At the −1727A/T locus, the TT genotype was associated with older age of onset than other genotypes (A/A: 27.4 ± 9.1; A/T: 30.1 ± 11.8; T/T: 42.3 ± 19.9; p = 0.034). However, no correlations between gene polymorphisms
Table 4 Comparison of clinical variables in bipolar disorder. GSK3bbetaN gene promoter −1727A/T
Genotype A/A
A/T
T/T
ANOVA F
p
Age of onset (years) Number of episode Baseline YMRS Baseline BPRS
27.4 ± 9.1 2.6 ± 3.2 32.8 ± 11.2 20.0 ± 9.1
30.1 ± 11.8 2.0 ± 1.9 31.7 ± 9.9 20.6 ± 10.6
42.3 ± 19.9 2.0 ± 2.0 36.3 ± 13.5 18.0 ± 4.6
3.52 0.39 0.26 0.11
0.034⁎ 0.68 0.774 0.895
GSK3bbetaN gene promoter − 50C/T
C/C
C/T
T/T
F
P
Age of onset (years) Number of episode Baseline YMRS Baseline BPRS
28.8 ± 11.2 2.2 ± 1.9 32.2 ± 11.2 17.8 ± 9.1
28.5 ± 10.7 2.7 ± 3.4 32.7 ± 11.3 20.7 ± 9.1
28.1 ± 8.5 2.3 ± 2.4 33.4 ± 9.0 21.7 ± 10.3
0.02 0.31 0.06 1.18
0.980 0.732 0.938 0.313
YMRS: Young Mania Rating Scale, BPRS: Brief Psychiatric Rating Scale, and ANOVA: analysis of variance. ⁎ p b 0.05.
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70.00
1.00: A/A genotype 2.00: A/T genotype 3.00: T/T genotype
60.00
Age of onset
50.00
40.00
30.00
20.00
10.00
0.00 1.00
1.50
2.00
2.50
3.00
GSK–3β 1727A/T Fig. 1. Comparison of clinical variables in bipolar disorder. Correlation between GSK3β − 1727A/T polymorphisms and age of onset of disease.
and BPRS or YMRS scores, or numbers of illness episode were observed (Table 4, Figs. 1 and 2).
3.4. Genotype and allelic frequency in bipolar disorder patients with and without psychotic symptoms The two subgroups with and without psychotic symptoms differed in genotype and allelic frequencies of the − 1727A/T SNP (Table 5). In particular, the psychotic mania group showed higher A allelic frequency (genotype: χ2 = 12.191, p = 0.0023; allele: χ2 = 7.721, p = 0.0055). On the contrary, the genotype distributions and allelic frequencies of the − 50C/T SNP were not significantly different between the two subgroups.
4. Discussion This study investigated the relationships of GSK3β gene polymorphisms with bipolar disorder and the presence of psychotic symptoms. According to these results, genotype distributions and allelic frequencies of GSK3β polymorphisms were not significantly different between bipolar disorder and control groups. Moreover, GSK3β haplotypes were not related to bipolar disorder. These findings were consistent with those of our previous study (Lee et al., 2006). This study revealed correlations between GSK3β polymorphisms and age of onset of bipolar disorder. Benedetti et al. (2004) reported that, among bipolar disorder patients there is a higher frequency of the T allele in GSK3β −50C/T in patients with significantly younger age of onset. The present study detected a correlation between the −1727A/T
70.00
1.00: C/C genotype 2.00: C/T genotype 3.00: T/T genotype
60.00
Age of onset
50.00
40.00
30.00
20.00
10.00
0.00 1.00
1.50
2.00
2.50
3.00
GSK–3β 50 C/T Fig. 2. Comparison of clinical variables in bipolar disorder. Correlation between GSK3β − 50C/T polymorphisms and age of onset of disease.
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Table 5 Genotype and allele frequencies in psychotic bipolar disorder group and non-psychotic bipolar disorder group. GSK-3β − 1727A/T. GSK3bbetaN gene promoter − 1727A/T
Normal controls (N = 158) Patients with psychotic features (N = 92) Patients without psychotic features (N = 26)
GSK3bbetaNgene promoter − 50C/T Normal controls (N = 158) Patients with psychotic features (N = 92) Patients without psychotic features (N = 26)
Genotype
Analysis
A/A
A/T
T/T
117 74.0% 71 77.17% 15 57.69%
38 24.0% 21 22.83% 8 30.77%
3 2.0% 0 0% 3 11.54%
C/C
C/T
T/T
88 55.7% 56 60.87% 12 46.15%
30 19.0% 10 10.87% 6 23.08%
40 25.3% 26 28.26% 8 30.77%
χ2 (df = 2) 0.15
Allele p
A
0.928
272 86.1% 163 88.59% 38 73.08%
Analysis T 44 13.9% 21 11.41% 14 26.92%
χ2 (df = 1)
p
0.09
0.764
7.721
0.0055⁎
12.191
0.0023⁎
χ2 (df = 2)
p
C
T
χ2 (df = 1)
p
1.55
0.461
0.297
0.2194
148 46.8% 76 41.3% 24 46.15%
1.09
3.034
168 53.2% 108 58.7% 28 53.85%
0.391
0.5321
C = Normal control, P = Patients with psychotic features, and N = Patients without psychotic features. ⁎ p b 0.016.
SNP of GSK3β and age of onset, as patients with the A allele had a younger age of onset on average than those with T allele. This result is meaningful, considering the results of a previous study that found that relatives of patients with younger age of onset displayed higher morbidity rates from bipolar disorder as well as younger ages of onset than relatives of patients with older age of onset (Baron et al., 1981). Although Szczepankiewicz et al. (2006) reported that the allelic frequency of −50C/T was significantly different in females with bipolar disorder type 2, but we did not detect any significant differences in expression of genotypes by gender in the present study. Associations between GSK-3β gene polymorphisms and psychotic symptoms can be inferred due to three possible roles. Three mechanistic possibilities are changes in the dopamine system, potential disturbance of the Akt/GSK-3β signaling pathway and abnormal Wnt signaling pathways (Alimohamad et al., 2005; Gil et al., 2003; Ikeda et al., 2004; McMahon and Bradley, 1990, Sep). Many researchers have insisted that the GSK3β gene influences psychotic symptoms of psychiatric disorders, but only a few studies exist investigating the relationship between bipolar disorder and psychotic symptoms. Serretti et al. (2008) found that the genotype GSK3β-50T/C was related to delusion and personality traits of harm, avoidance, and self-transcendence among mood disorder patients. The present study also detected differences in distributions of the GSK3β-1727A/T genotype and allelic frequencies between bipolar disorder patients with and without psychotic symptoms. In particular, the frequency of the A allele differed according to the presence of psychotic symptoms. Limitations of this study are as follows. First, the small sample size of this study was insufficient to fully detect correlations between GSK3β gene polymorphisms and bipolar disorder. More studies with larger samples are considered to be necessary in the future. Second, this study examined only two of many polymorphisms associated with the GSK3β gene. Future studies of the relationships between other GSK3β polymorphisms and psychiatric disorders may shed light on the role of this important gene (Ikeda et al., 2005; Russ et al., 2001). Third, the relationship of the −1727A/T SNP with age at onset is indicated by only three TT cases. Although a statistical significance is observed, the number of the cases is too small to say that this result is meaningful. However, as mentioned before, that is caused by small sample size. Previous studies of the relationships between GSK3β polymorphisms and psychiatric disorders have yielded conflicting findings. These discrepancies highlight the need for further research. The present study investigated the relationships between bipolar disorder and two GSK3β polymorphisms, and did not find any statistically significant associations between them. However, we found that the −1727A/T SNP
of GSK3β was related to age of onset of bipolar disorder and the presence of psychotic mania. In the future, studies building on these findings should eventually reveal the roles of GSK3β gene polymorphisms in psychiatric disorders. Acknowledgments This research was performed as a part of master's thesis (in Medicine) by Dr. Lee Y-J. References Alimohamad H, Rajakumar N, Seah YH, Rushlow W. Antipsychotics alter the protein expression levels of beta-catenin and GSK-3 in the rat medial prefrontal cortex and striatum. Biol Psychiatry 2005;57:533–42. APA. Diagnostic and statstical manual of mental disorders4th edition. . Washington DC: American Psychiatric Press; 1994. Bailer U, Leisch F, Meszaros K, Lenzinger E, Willinger U, Strobl R, et al. Genome scan for susceptibility loci for schizophrenia and bipolar disorder. Biol Psychiatry 2002;52: 40–52. Baron M, Mendlewicz J, Klotz J. Age-of-onset and genetic transmission in affective disorders. Acta Psychiatr Scand 1981;64:373–80. Bech P, Larsen JK, Andersen J. The BPRS: psychometric developments. Psychopharmacol Bull 1988;24:118–21. Benedetti F, Bernasconi A, Lorenzi C, Pontiggia A, Serretti A, Colombo C, et al. A single nucleotide polymorphism in glycogen synthase kinase 3-beta promoter gene influences onset of illness in patients affected by bipolar disorder. Neurosci Lett 2004;355:37–40. Chen G, Huang LD, Jiang YM, Manji HK. The mood-stabilizing agent valproate inhibits the activity of glycogen synthase kinase-3. J Neurochem 1999;72:1327–30. De Sarno P, Li X, Jope RS. Regulation of Akt and glycogen synthase kinase-3 beta phosphorylation by sodium valproate and lithium. Neuropharmacology 2002;43: 1158–64. First MSR, Gibbon M, William JB. Structured clinical interview for DSM-IV axis I disorder-patient edition (SCID-I/NP, version 2.0). New York: Biometrics Research Department, New York State Psychiatric Institute; 1998. Gil M, Zhen X, Friedman E. Prenatal cocaine exposure alters glycogen synthase kinase3beta (GSK3beta) pathway in select rabbit brain areas. Neurosci Lett 2003;349: 143–6. Grimes CA, Jope RS. CREB DNA binding activity is inhibited by glycogen synthase kinase-3 beta and facilitated by lithium. J Neurochem 2001a;78:1219–32. Grimes CA, Jope RS. The multifaceted roles of glycogen synthase kinase 3beta in cellular signaling. Prog Neurobiol 2001b;65:391–426. Hansen L, Arden KC, Rasmussen SB, Viars CS, Vestergaard H, Hansen T, et al. Chromosomal mapping and mutational analysis of the coding region of the glycogen synthase kinase-3alpha and beta isoforms in patients with NIDDM. Diabetologia 1997;40:940–6. Ikeda M, Iwata N, Suzuki T, Kitajima T, Yamanouchi Y, Kinoshita Y, et al. Association of AKT1 with schizophrenia confirmed in a Japanese population. Biol Psychiatry 2004;56:698–700. Ikeda M, Iwata N, Suzuki T, Kitajima T, Yamanouchi Y, Kinoshita Y, et al. No association of GSK3beta gene (GSK3B) with Japanese schizophrenia. Am J Med Genet B Neuropsychiatr Genet 2005;134B:90–2. Jope RS, Roh MS. Glycogen synthase kinase-3 (GSK3) in psychiatric diseases and therapeutic interventions. Curr Drug Targets 2006;7:1421–34.
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