Journal of Affective Disorders 158 (2014) 90–96

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Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad

Preliminary communication

Cognitive effects of the ANK3 risk variants in patients with bipolar disorder and healthy individuals Hiroaki Hori a,n, Noriko Yamamoto a, Toshiya Teraishi a, Miho Ota a, Takashi Fujii a, Daimei Sasayama a, Junko Matsuo a, Yukiko Kinoshita a, Kotaro Hattori a, Anna Nagashima a, Ikki Ishida a, Norie Koga a, Teruhiko Higuchi b, Hiroshi Kunugi a a b

Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan National Center of Neurology and Psychiatry, Tokyo, Japan

art ic l e i nf o

a b s t r a c t

Article history: Received 11 January 2014 Accepted 3 February 2014 Available online 10 February 2014

Background: Genetic variants within the ankyrin 3 gene (ANK3) have been identified as a risk factor for bipolar disorder. ANK3 influences action potential generation by clustering sodium gated channels and plays an integral role in neurotransmission. Thus, this gene may influence cognition, a process compromised in bipolar disorder. We investigated whether genetic variants of ANK3 would be associated with an array of cognitive functions in patients with bipolar disorder and healthy individuals. Methods: In a sample of 49 patients with bipolar disorder and 633 healthy subjects, we examined possible effects of 2 risk variants within ANK3, rs10994336 and rs10761482, on 7 neurocognitive domains. Results: Compared to healthy subjects, patients with bipolar disorder demonstrated significantly poorer performance on most of the cognitive domains examined. The risk C-allele of rs10761482 was significantly associated with worse performance on verbal comprehension, logical memory and processing speed in patients. This allele was significantly associated with worse performance on executive function and visual memory in healthy individuals. No significant association was observed between rs10994336 and cognition either in patients or healthy individuals. Limitations: The sample size of patients with bipolar disorder was small, and most of the patients were on psychotropic medication. Conclusions: These results indicate that a risk variant within ANK3 may have an impact on neurocognitive function, suggesting a mechanism by which ANK3 confers risk for bipolar disorder. & 2014 Elsevier B.V. All rights reserved.

Keywords: Bipolar disorder ANK3 Cognitive function Genetics Endophenotype

1. Introduction Bipolar disorder is a severe and chronic psychiatric condition with devastating consequences for afflicted individuals and the community. Although the pathophysiology of this disorder remains elusive, considerable evidence suggests that genetic factors play an important role, with the heritability estimated at 59–93% (McGuffin et al., 2003; Kieseppä et al., 2004; Lichtenstein et al., 2009). Over the past several years, genome-wide association studies of bipolar disorder have identified several common risk variants, including those within the ankyrin 3 gene (ANK3) (Ferreira et al., 2008; Scott et al., 2009; Smith et al., 2009; Sklar et al., 2011). Some evidence indicates that ANK3 is also associated n Correspondence to: Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, 4-1-1, Ogawahigashi, Kodaira, Tokyo, 187-8502, Japan. Tel.: þ81 42 341 2711; fax: þ 81 42 346 1744. E-mail address: [email protected] (H. Hori).

http://dx.doi.org/10.1016/j.jad.2014.02.008 0165-0327 & 2014 Elsevier B.V. All rights reserved.

with schizophrenia (Athanasiu et al., 2010; Yuan et al., 2012), lateonset Alzheimer's disease (Morgan et al., 2008) and posttraumatic stress disorder (Logue et al., 2013). ANK3 encodes the ankyrin G protein, a scaffolding protein located at the neuronal axon initial segments and the nodes of Ranvier. Ankyrin G is involved in action potential generation by clustering sodium gated channels and thus plays a fundamental role in neurotransmission (Zhou et al., 1998). The intronic singlenucleotide polymorphism (SNP) rs10994336 (C/T; risk allele T) of ANK3 is one of the genome-wide supported risk variants for bipolar disorder (Ferreira et al., 2008; Scott et al., 2009). Another intronic SNP rs10761482 (C/T; risk allele C) within ANK3, a marker not in linkage disequilibrium with rs10994336 (Athanasiu et al., 2010; Yuan et al., 2012), has also been reported to be associated with bipolar disorder (Gella et al., 2011) and schizophrenia (Athanasiu et al., 2010; Yuan et al., 2012). It is well known that patients with bipolar disorder, even in the euthymic state, show impairments in a range of cognitive

H. Hori et al. / Journal of Affective Disorders 158 (2014) 90–96

domains, including verbal and visual memory, attention, working memory, executive function and processing speed (Robinson et al., 2006; Arts et al., 2008; Bora et al., 2011; Solé et al., 2011; Sasayama et al., 2012). Such cognitive dysfunction is considered as a proxy for genetic research, or endophenotype, of bipolar disorder (Frantom et al., 2008; Bora et al., 2009; Glahn et al., 2010). It is suggested that genetic contributions to brain/cognitive processes underlying bipolar disorder can be greater than those to the risk for the disorder itself, which encompasses broad and complex phenotypes (Cannon and Keller, 2006). Based on this concept, a number of candidate genes for bipolar disorder have been examined in relation to cognitive function (Burdick et al., 2007; Soronen et al., 2008; Soeiro-de-Souza et al., 2012). For ANK3, rs10994336 (or another SNP in strong linkage disequilibrium with it) has been shown to be associated with sustained attention in bipolar disorder and healthy individuals (Ruberto et al., 2011; Hatzimanolis et al., 2012), set-shifting and decision making in healthy individuals (Linke et al., 2012), verbal memory, working memory, attention and cortical thickness in first-episode psychosis (Cassidy et al., 2014), and ventral prefrontal cortical activation and visual-prefrontal effective connectivity in bipolar disorder (Dima et al., 2013). However, there are also studies that show no significant effect of this SNP on verbal memory, working memory, executive function or general intelligence (Roussos et al., 2011; Ruberto et al., 2011; Hatzimanolis et al., 2012). Concerning rs10761482, no studies have examined the possible effect on cognitive function in bipolar disorder. The present study investigated how the ANK3 risk variants of interest, rs10994336 and rs10761482, affect various cognitive domains in patients with bipolar disorder and in healthy individuals. In addition, we conducted a genetic association analysis between the ANK3 variants and bipolar disorder.

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psychiatrist were excluded: past or current regular contact to psychiatric services, having a history of regular use of psychotropics or substance abuse/dependence, presenting other obvious self-reported signs of past primary psychotic and mood disorders, and having a prior medical history of central nervous system disease or severe head injury. Of the subjects genotyped, neuropsychological data were available for 49 patients with bipolar disorder (11 patients with bipolar I disorder and 38 with bipolar II disorder) and 633 controls. Given that none of the patients were in a clinically significant manic state, depressive symptoms were assessed in all patients, using the Japanese version of the GRID Hamilton Rating Scale for Depression, 21-item version (HAMD-21; Hamilton, 1967). Manic symptoms were assessed in 23 (46.9%) of the 49 patients, using the Young Mania Rating Scale (YMRS; Young et al., 1978). The present experiments on our participants were conducted in accordance with the Declaration of Helsinki. After the nature of the study procedures had been fully explained, written informed consent was obtained from all participants. The study was approved by the ethics committee of NCNP. 2.2. Genotyping Genomic DNA was prepared from venous blood according to standard procedures. Rs10994336 and rs10761482 were genotyped using the TaqMan 50 -exonuclease allelic discrimination assay. The thermal cycling conditions for polymerase chain reaction were as follows: 1 cycle at 95 1C for 10 min followed by 50 cycles of 92 1C for 15 s and 60 1C for 1 min. The allele-specific fluorescence was measured with ABI PRISM 7900 Sequence Detection Systems (Applied Biosystems, Foster City, CA). Ambiguous genotype data were not included in the analysis. 2.3. Neurocognitive test battery

2. Methods 2.1. Participants Subjects of the genetic association part of this study comprised 215 patients with bipolar disorder (108 men and 107 women; mean age7standard deviation (SD): 48.0 715.1 years) and 1158 healthy controls (398 men and 760 women; mean age7SD: 45.7 716.2 years). All subjects were biologically unrelated Japanese. Patients were recruited from the outpatient clinic and inpatient ward of the National Center of Neurology and Psychiatry (NCNP) Hospital, Japan, which is located at the western part of Tokyo, or through advertisements in free local magazines and our website announcement. Most of the patients recruited via advertisements or website announcement were regularly attending to a nearby hospital or clinic. Consensus diagnoses were made based on clinical interviews, observations and case notes by at least two experienced psychiatrists. For those patients under treatment at the NCNP Hospital, the diagnosis was confirmed using the Structured Clinical Interview for DSM-IV Axis I disorders (First et al., 1997). For the remaining patients under treatment at a nearby hospital/clinic, the diagnosis made by his/her attending doctor was confirmed by the Mini-International Neuropsychiatric Interview (MINI; Sheehan et al., 1998; Otsubo et al., 2005) by a research psychiatrist. Healthy individuals were recruited from the same geographical area via the free local magazines and our website announcement. They were interviewed using the MINI by a research psychiatrist, and only those who demonstrated no current Axis I psychiatric disorders were enrolled in the study. In addition, those individuals who demonstrated one or more of the following conditions in a non-structured interview performed by an experienced

A neurocognitive test battery, comprising the Wechsler Memory Scale-Revised (WMS-R; Wechsler, 1987; Sugishita, 2001), the Wechsler Adult Intelligence Scale (WAIS; Wechsler, 1981; Shinagawa et al., 1990; Wechsler, 1997; Fujita et al., 2006) and the Wisconsin Card Sorting Test (WCST; Heaton, 1981; Kashima et al., 1987), was administered, as described elsewhere (Hori et al., 2012a, 2012b; Hori et al., 2014). While there were 27 subtests in the 3 neuropsychological tests, main analyses were conducted using 7 cognitive factors, or summary measures, i.e., verbal comprehension, WCST, paired-associate memory, working memory, visual memory, logical memory, and processing speed, which we had identified previously (Hori et al., 2012a, 2012b). 2.4. Statistical analysis Averages are reported as means 7SD. For demographic and clinical characteristics, categorical variables were compared using the χ2 test or Fisher's exact test where appropriate. The t-test was used to examine differences between groups. Deviations of genotype distributions from Hardy–Weinberg equilibrium were assessed using the χ2 test for goodness of fit. Genotype and allele distributions were compared between patients and controls by using the χ2 test for independence. For the cognitive endophenotype analysis, individuals with CT and TT genotypes were combined within each diagnostic group for both SNPs, given the rarity of the TT genotype particularly in the patient group (i.e., 3 patients with TT for rs10994336 and 1 patient with TT for rs10761482), as in previous studies (Roussos et al., 2011; Ruberto et al., 2011; Dima et al., 2013). Mean scores of the 7 cognitive factors were normalized to the z-score using the control group data. The two-way analysis of

0.79 0.95

0.61 0.13

rs10761482 10

C/T

rs10994336

Abbreviations: CHR, chromosome; SNP, single nucleotide polymorphism; CI, confidence interval; HWE, Hardy–Weinberg equilibrium; OR, odds ratio; df, degree of freedom.

0.26 0.27 0.80 76 (6.6) 448 (38.7) 634 (54.7) 16 (7.4) 86 (40.0)

0.33 0.12 153 (13.2) 547 (47.2) 458 (39.6) 29 (13.5) 86 (40.0)

100 (46.5) 113 (52.6)

TT CT

10

C/T

TT CC CC

CT

Control subjects (n¼ 1158)

0.51

0.86 (0.69–1.07) 1.08 (0.86–1.36) 0.37

Controls Patients

Minor allele frequency χ2 P-value (df ¼2) Genotype counts (frequency) Alleles SNP

Demographic characteristics and clinical variables of patients with bipolar disorder and healthy control subjects included in the cognitive endophenotype analysis, stratified by the ANK3 genotypes, are presented in Table 2. Age (t¼1.98, P¼0.020) and sex (χ2 ¼6.90, P¼0.009), but not education level (t¼0.48, P¼0.63), differed significantly between patients (n¼ 49) and controls (n¼ 633). Education level was significantly different between the rs10761482 genotypes in the patient group and marginally significantly different between the rs10994336 genotypes in controls; thus, we controlled for education, in addition to age and gender, in all ANCOVA analyses. As the use of benzodiazepines was significantly different between the rs10994336 genotypes in patients, this variable was also controlled for in the ANCOVA where relevant. Results of the association between the rs10994336 genotype and cognition are shown in Fig. 1a for patients with bipolar disorder and Fig. 1b for healthy individuals. The two-way ANCOVA on the 7 cognitive factors, controlling for age, gender and education, showed that the main effect of diagnosis was significant for paired-associate memory, working memory, visual memory, logical memory and processing speed (all P o0.001), but not for verbal comprehension or WCST (both P4 0.05). The main effect of genotype and genotype-by-diagnosis interaction were not significant for any of the 7 cognitive factors (all P 40.05). The one-way ANCOVA in patients, controlling for age, gender, education and benzodiazepine use, revealed no significant main effect of genotype (all P 40.1). The one-way ANCOVA in healthy individuals, controlling for age, gender and education, showed no significant main effect of genotype (all P4 0.05). Results of the association between the rs10761482 genotype and cognition are shown in Fig. 1c for patients and Fig. 1d for controls. The two-way ANCOVA on the 7 cognitive factors, controlling for age, gender and education, again showed the significant main effect of diagnosis on paired-associate memory, working memory, visual memory, logical memory and processing speed (all P o0.001). The main effect of genotype was significant for verbal comprehension [F(1,675) ¼9.34, P ¼0.002], logical memory [F(1,675) ¼ 4.86, P ¼0.028] and processing speed [F(1,675)¼5.34,

CHR

3.2. Association of the ANK3 variants with cognition

Table 1 Genotype and allele distributions for the ANK3 polymorphisms rs10994336 and rs10761482 in patients with bipolar disorder and healthy controls.

3.1. Association of the ANK3 variants with bipolar disorder

0.19

χ2 P-value (df ¼ 1)

3. Results

In the case-control genetic association sample, genotype frequencies did not deviate from the Hardy–Weinberg equilibrium in patients with bipolar disorder or healthy controls, either for rs10994336 or rs10761482 (Table 1). No significant differences were seen in genotype or allele frequencies between the patients and controls, either for rs10994336 or rs10761482. For the linkage disequilibrium between these two markers, D0 was 0.56 and r2 was 0.064 in the total sample, indicating that the linkage disequilibrium was not strong.

Patients

OR (95%CI)

HWE P-value (df ¼ 1)

covariance (ANCOVA), with genotype (major C-allele homozygotes vs. minor T-allele carriers) and diagnosis (patients vs. controls) as fixed factors and potential confounder(s), in addition to age and gender, as covariates, was performed to compare the 7 factor scores. To further explore the simple effect of genotype, we conducted one-way ANCOVA with confounders as covariates, separately for patient and control groups. Statistical significance was set at two-tailed P o0.05. Analyses were performed using the Statistical Package for the Social Sciences version 21.0 (SPSS Japan, Tokyo). Linkage disequilibrium was calculated using Haploview version 4.2 software (Barrett et al., 2005).

Controls

H. Hori et al. / Journal of Affective Disorders 158 (2014) 90–96

Bipolar patients (n¼ 215)

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Table 2 Demographic and clinical variables of patients and controls included in the cognitive experiment, stratified by the ANK3 genotype. Characteristics

Patients with bipolar disorder (n¼ 49)

Healthy subjects (n¼ 633)

Age, years: mean 7 SD Gender, female: n (%) Education, years: mean7 SD FH of any psychiatric disorder: yes, n (%) Age at onset, years: mean 7 SD History of psychiatric hospitalization: yes, n (%)

rs10761482 CTþ TT (n ¼28)

Statistics

P

CC (n¼ 27)

CT þTT (n¼ 22)

Statistics

P

CC (n¼ 253)

CTþ TT (n ¼380)

Statistics P

CC (n¼ 365)

CTþ TT (n ¼268)

Statistics P

43.0 7 12.3 12 (57.1) 14.5 7 2.5 10 (47.6) 28.0 7 10.8

39.1 7 11.7 16 (57.1) 15.0 7 3.6 14 (50.0) 29.4 7 13.0

t¼ 1.1 χ2 ¼ 0.00 t¼ 0.50 χ2 ¼ 0.03 t¼ 0.38

0.26 1.00 0.62 0.87 0.70

42.6 7 12.2 13 (48.1) 13.6 7 2.9 15 (55.6) 29.2 7 13.4

38.5 7 11.7 15 (68.2) 16.2 7 3.0 9 (40.9) 28.4 7 10.4

t ¼1.2 χ2 ¼ 2.0 t ¼3.2 χ2 ¼ 1.0 t ¼0.24

0.23 0.16 0.003 0.31 0.81

44.0 714.9 181 (71.5) 15.2 7 2.8 42 (16.6) NA

45.8 7 15.0 290 (76.3) 14.8 7 2.5 52 (13.7) NA

t ¼ 1.5 χ2 ¼ 1.8 t ¼ 1.9 χ2 ¼ 1.0 NA

0.13 0.18 0.053 0.31 NA

45.0 7 15.1 270 (74.0) 14.9 7 2.6 59 (16.2) NA

45.2 714.7 201 (75.0) 15.17 2.7 35 (13.1) NA

t ¼ 0.18 χ2 ¼0.09 t ¼ 0.87 χ2 ¼ 1.2 NA

0.86 0.77 0.38 0.28 NA

8 (38.1)

6 (21.4)

χ2 ¼ 1.63

0.20

10 (37.0)

4 (18.2)

χ2 ¼ 2.11

0.15

NA

NA

NA

NA

NA

NA

NA

NA

Fisher's exact

0.072 1 (3.7)

2 (9.1)

Fisher's exact

0.58

NA

NA

NA

NA

NA

NA

NA

NA

0.67 12 (44.4) 0.090 12 (44.4)

6 (27.3) 7 (31.8)

0.21 0.37

NA NA

NA NA

NA NA

NA NA

NA NA

NA NA

NA NA

NA NA

3 (14.3)

0 (0.0)

Medication, n (%) Antipsychotic Antidepressant

7 (33.3) 11 (52.4)

11 (39.3) 8 (28.6)

Benzodiazepine HAMD-21 total score: mean 7 SD YMRS total scorea: mean7 SD

rs10761482

CC (n¼ 21)

Lifetime ECT: yes, n (%)

Lithium

rs10994336

7 (33.3)

4 (14.3)

15 (71.4) 12.2 7 8.4 1.5 7 1.6

11 (39.3) 14.5 7 8.7 2.7 7 3.1

χ2 ¼ 0.18 χ2 ¼ 2.9 Fisher's exact χ2 ¼ 5.0 t¼ 0.91 t¼ 1.1

0.17

6 (22.2)

0.026 16 (59.3) 0.37 12.8 7 9.1 0.28 2.5 7 3.0

5 (22.7) 10 (45.5) 14.5 7 8.0 1.8 7 2.1

χ2 ¼ 1.5 χ2 ¼ 0.81 Fisher's exact χ2 ¼ 0.93 t ¼0.66 t ¼0.63

1.00

NA

NA

NA

NA

NA

NA

NA

NA

0.34 0.51 0.54

NA NA NA

NA NA NA

NA NA NA

NA NA NA

NA NA NA

NA NA NA

NA NA NA

NA NA NA

H. Hori et al. / Journal of Affective Disorders 158 (2014) 90–96

rs10994336

Abbreviations: FH, family history; ECT, electroconvulsive therapy; HAMD-21, 21-item version of the Hamilton Depression Rating Scale; YMRS, Young Mania Rating Scale; NA, not applicable. Underlined figures represent significant results. a

Data were available for 23 patients with bipolar disorder.

93

94

H. Hori et al. / Journal of Affective Disorders 158 (2014) 90–96

Rs10994336, Healthy individuals

Rs10994336, Patients with bipolar disorder Verbal comprehension

WCST

Paired-associate memory

Working memory

Verbal comprehension

Processing speed

Visual memory Logical memory

WCST

Paired-associate memory

Working memory

Visual memory Logical memory

Processing speed

0.15

0.6 0.4

0.10

0.2

z score

0.0

z score

-0.2 -0.4 -0.6

0.05

0.00

-0.8 -1.0

-0.05

-1.2 -1.4

CC (n = 21)

-1.6

CC (n = 253)

-0.10

CT+TT (n = 28)

Rs10761482, Healthy individuals

Rs10761482, Patients with bipolar disorder Verbal comprehension

WCST

Paired-associate memory

Working memory

CT+TT (n = 380)

Visual memory Logical memory

Verbal comprehension

Processing speed

WCST

Paired-associate memory

Working memory

Visual memory Logical memory

Processing speed

0.15

1.0 0.10

z score

0.5

z score

0.0 -0.5 -1.0

**

-1.5 -2.0

0.00 -0.05

* CC (n = 27)

0.05

-0.10

CT+TT (n = 22)

*

* *

-0.15

CC (n = 365)

CT+TT (n = 268)

Fig. 1. Estimated mean z scores, controlling for age, gender and education, of the 7 neurocognitive domains. Comparisons were made between rs10994336 C-allele homozygotes (white bars) and T-allele carriers (black bars) in patients with bipolar disorder (a) and in healthy individuals (b) and between rs10761482 C-allele homozygotes (white bars) and T-allele carriers (black bars) in patients with bipolar disorder (c) and in healthy individuals (d). Error bars represent standard errors of the mean. nPo 0.05; nn P o0.01 (according to the ANCOVA controlling for age, gender and education).

P ¼0.021]. Genotype-by-diagnosis interaction was significant for verbal comprehension [F(1,675)¼5.62, P¼ 0.018] and processing speed [F(1,675)¼4.36, P¼ 0.037]. The one-way ANCOVA in patients, controlling for age, gender and education, revealed that the main effect of genotype was significant for verbal comprehension [F(1,44) ¼ 9.98, P ¼0.003], logical memory [F(1,44) ¼ 6.39, P ¼0.015] and processing speed [F(1,44) ¼6.50, P ¼0.014]. The one-way ANCOVA in healthy subjects, controlling for age, gender and education, revealed a significant main effect of genotype on WCST [F(1,628) ¼ 4.67, P ¼0.031] and visual memory [F(1,628) ¼ 4.51, P ¼0.034]. All of these significant differences between rs10761482 genotypes indicated that cognitive performance was poorer in individuals homozygotes for the risk C-allele than in T-allele carriers across diagnoses (Fig. 1c and d).

4. Discussion We investigated the possible effects of ANK3 risk variants, rs10994336 and rs10761482, on a wide range of cognitive functions in patients with bipolar disorder and healthy individuals. Main findings were that the risk C-allele of rs10761482 was significantly associated with worse performance on verbal comprehension, logical memory and processing speed in patients with bipolar disorder. Furthermore, this allele was associated with worse performance on WCST and visual memory in healthy individuals. No significant association was observed between rs10994336 and cognition either in patients or healthy subjects. To begin with, our results confirmed the well-known impairments in several cognitive domains in bipolar disorder, including

verbal/visual memory, working memory and processing speed (Robinson et al., 2006; Arts et al., 2008; Bora et al., 2011; Solé et al., 2011). With respect to the association between the ANK3 risk variants and neurocognition, this is the first study that reports a significant association between the risk C-allele of rs10761482 and worse cognitive performance. The observed effect of the ANK3 polymorphism on verbal comprehension in patients with bipolar disorder supports the evidence that ANK3 is associated with intellectual functioning (Iqbal et al., 2013). Indeed, a body of evidence suggests that intellectual functioning is affected by genetic factors (Plomin, 1999; Deary et al., 2006). The other cognitive domains that were found to be associated with rs10761482, namely memory, processing speed and executive function, are demonstrated to be a valid neurocognitive endophenotype for bipolar disorder (Frantom et al., 2008; Bora et al., 2009; Glahn et al., 2010; Daban et al., 2012). Thus, the present finding suggests a mechanism whereby ANK3 is associated with risk for bipolar disorder and may serve as a step toward elucidating the functional significance of bipolar risk genes. On the other hand, the absence of significant association between rs10994336 and cognitive functions examined, i.e., verbal/visual memory, working memory, executive function, processing speed and general intelligence, is consistent with previous studies (Roussos et al., 2011; Ruberto et al., 2011; Hatzimanolis et al., 2012). Rather, this variant has been shown to specifically affect sustained attention (Ruberto et al., 2011; Hatzimanolis et al., 2012). Large-scale genome-wide association studies for bipolar disorder have reported that ANK3 rs10994336 surpasses the genomewide significance threshold (Ferreira et al., 2008; Scott et al., 2009). We failed to find the significant association between this

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SNP and bipolar disorder; however, this result is in line with several previous studies (Takata et al., 2011; Kloiber et al., 2012; Green et al., 2013). Such a failure to replicate the significant association in targeted association studies may be due, at least in part, to different ethnicities and/or small sample sizes. Alternatively, the originally reported associations exceeding the genomewide significance threshold might have inflated effect sizes, a phenomenon called “winner's curse” (Zollner and Pritchard, 2007; Ioannidis et al., 2009). The other SNP examined in the present study, rs10761482, was not significantly associated with bipolar disorder either. Only one study with a modest sample size found this variant to be associated with bipolar disorder (Gella et al., 2011), while there are two studies associating it with schizophrenia (Athanasiu et al., 2010; Yuan et al., 2012). More studies are therefore needed to test the association of this SNP with bipolar disorder and schizophrenia. Nonetheless, the significant effect of this SNP on cognitive function observed here is in accordance with the notion that endophenotypes can be genetically less complex than the disorders they affect, which implies that genes that influence a given endophenotype tend to be fewer in number than those affecting the disorder per se, and/or that the effect size of a particular gene will be greater for the endophenotype than for the disorder (Cannon and Keller, 2006). Several limitations should be acknowledged. The main caveat was probably the low statistical power due to the relatively small size of the sample, particularly for the patient group. Second, most of our patients were on psychotropic medication at the time of the neuropsychological testing, although this factor was statistically controlled for where necessary. Third, although two SNPs and 7 cognitive domains were examined, we did not correct for multiple comparisons. We would like to note, however, that the main effect of the rs10761482 genotype for verbal comprehension in the ANCOVAs was significant even after the Bonferroni correction (P o0.05/14 ¼0.0036). Besides, different cognitive domains are likely to be correlated; indeed, 13 out of 21 combinations of correlations among the 7 cognitive indices in healthy individuals showed at least weak correlations (i.e., r 4 0.2, all P o0.001). Fourth, as there is no information on whether the polymorphism within the ANK3 gene found to be associated with cognition (i.e., rs10761482) is itself causal, bioinformatics and sequencing analyses may be necessary to identify truly causal variant(s). Another limitation was that we did not take into account any gene-gene interaction effect, or epistatic effect, on neurocognition. In summary, our results indicate that the ANK3 risk variant rs10761482 may impact cognitive function, pointing to a mechanism by which ANK3 confers risk for bipolar disorder. This finding adds to the literature that susceptibility genes for bipolar disorder may cause the disorder by influencing endophenotypic traits. Further studies that link ANK3 variants to (endo)phenotypic information are needed.

Role of funding source This study was supported by Health and Labor Sciences Research Grants, Grantin-Aid for Scientific Research from the Japan Society for the Promotion of Science (JSPS), Intramural Research Grant for Neurological and Psychiatric Disorders of NCNP, (H.K.), JSPS KAKENHI Grant no. 23791372 and Grant from Research Group for Schizophrenia (H.H.); these funding sources had no further role in study design, in the collection, analysis and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication.

Conflict of interest All authors declare no conflict of interest.

Acknowledgments We wish to thank all participants who took part in the study.

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Cognitive effects of the ANK3 risk variants in patients with bipolar disorder and healthy individuals.

Genetic variants within the ankyrin 3 gene (ANK3) have been identified as a risk factor for bipolar disorder. ANK3 influences action potential generat...
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