SCHRES-06613; No of Pages 7 Schizophrenia Research xxx (2015) xxx–xxx

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BDNF polymorphisms are associated with schizophrenia onset and positive symptoms Xiang Yang Zhang a,b,⁎, Da-Chun Chen a, Yun-Long Tan a, Shu-ping Tan a, Xingguang Luo c, Lingjun Zuo c, Jair C. Soares b a b c

Psychiatry Research Center, Beijing HuiLongGuan Hospital, Peking University, Beijing, China Department of Psychiatry and Behavioral Sciences, Harris County Psychiatric Center, The University of Texas Health Science Center at Houston, Houston, TX, USA Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA

a r t i c l e

i n f o

Article history: Received 22 July 2015 Received in revised form 7 November 2015 Accepted 10 November 2015 Available online xxxx Keywords: Schizophrenia Symptoms BDNF Polymorphism Haplotype Association

a b s t r a c t Numerous studies have showed that brain-derived neurotrophic factor (BDNF) may be involved in the pathogenesis and pathophysiology of schizophrenia. The purposes of this study were to investigate the potential association of BDNF gene polymorphisms with susceptibility to schizophrenia and the psychopathological symptoms in patients with schizophrenia in a Han Chinese population. Four polymorphisms (rs6265, rs12273539, rs10835210 and rs2030324) of the BDNF gene were analyzed in a case–control study of 1887 Han Chinese individuals (844 patients and 1043 controls). We assessed 825 patients for psychopathology using the Positive and Negative Syndrome Scale. In single marker analyses the BDNF rs10835210 mutant A allele was significantly associated with schizophrenia. Haplotype analyses revealed higher frequencies of haplotypes containing the mutant A allele of the rs10835210 in schizophrenia than controls. We also found that this polymorphism rs10835210 was associated with positive symptoms, and the patients carrying the mutational allele A showed more positive symptoms. These findings suggest the role of these BDNF gene variants in both susceptibility to schizophrenia and in clinical symptom severity. © 2015 Elsevier B.V. All rights reserved.

1. Introduction The neurodevelopmental and neurodegenerative models of schizophrenia are currently two leading hypotheses to explain the etiology and clinical course of this disorder (Kochunov and Hong, 2014). Brainderived neurotrophic factor (BDNF), a member of the neurotrophin family of growth factors, is widely expressed in the adult mammalian brain and plays a critical role in development, regeneration, survival and maintenance of neurons (Adachi et al., 2014). Increasing evidence suggest that BDNF could be implicated in the pathophysiology of schizophrenia (Nurjono et al., 2012; Ahmed et al., 2015). For example, the majority of studies have reported decreased BDNF serum or plasma levels in chronic antipsychotic-treated, neuroleptic-free or neuroleptic-naïve, first-episode patients with schizophrenia (Chen da et al., 2009; Xiu et al., 2009; Pillai et al., 2010; Rizos et al., 2010; Nurjono et al., 2012), or decrease BDNF mRNA in the postmortem brain of patients (Rao et al., 2015), although some authors failed to replicate these findings in both medicated and antipsychotic-naïve patients (Green et al., 2011). The most recent meta-analysis has shown that peripheral ⁎ Corresponding author at: Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, 1541 East Road, Houston, TX 77054, USA. E-mail address: [email protected] (X.Y. Zhang).

BDNF levels are reduced in both medicated and drug-naïve patients with schizophrenia (Fernandes et al., 2014). Interestingly, BDNF has been found to be associated with positive symptoms (Buckley et al., 2007; Xiu et al., 2009), negative symptoms (Rizos et al., 2010; Chen da et al., 2009), tardive dyskinesia (TD) (Yang et al., 2011; Zhang et al., 2012a) and cognitive deficits (Zhang et al., 2012b) in schizophrenia. Since Egan et al. reported that BDNF Val66Met (rs6265) single nucleotide polymorphism (SNP) altered the intracellular trafficking and activity dependent secretion of mature BDNF and affected hippocampal function (Egan et al., 2003), this polymorphism has been studied most extensively. One most recent meta-analysis study reported a significant association between BDNF Val66Met polymorphism and schizophrenia (Kheirollahi et al., 2015); however, another meta-analysis study did not confirm this result (Zhao et al., 2015). Several other SNPs were tested for the association with schizophrenia, such as SNP C270T and a (GT)n dinucleotide repeat, with conflicting results (Watanabe et al., 2013). A few studies have examined the association between the BDNF haplotypes and schizophrenia. For example, a case–control study carried out in a large sample of Chinese found a highly statistically significant association between a common four-locus haplotype A-274-C-T for rs6265–(GT)n–rs2030324–rs2883187 and schizophrenia (Qian et al., 2007). However, the subsequent studies did not find the association between the BDNF haplotypes and schizophrenia (Lencz et al., 2009; Suchanek et al., 2012; Li et al., 2013).

http://dx.doi.org/10.1016/j.schres.2015.11.009 0920-9964/© 2015 Elsevier B.V. All rights reserved.

Please cite this article as: Zhang, X.Y., et al., BDNF polymorphisms are associated with schizophrenia onset and positive symptoms, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.11.009

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X.Y. Zhang et al. / Schizophrenia Research xxx (2015) xxx–xxx

Some researchers suggest that clinical phenotypes rather than the whole spectrum of schizophrenia would be more closely related to certain susceptive genes, and exploring the genotype–phenotype correlations of schizophrenia may lead to better understanding of this disease (Papiol et al., 2011). However, to our surprise, few studies have examined the relationship of BDNF genotypes and haplotypes to clinical symptoms in schizophrenia. Therefore, this study aimed to investigate the BDNF genotype-phenotype relationship and haplotype– phenotype relationships in chronic schizophrenia. For this, we analyzed the presence of one of most commonly studied BDNF SNP-Val66Met, as well as that of 3 other tag-SNPs located in the gene (rs12273539, rs2030324 and rs10835210), which have been previously suggested to impact different psychiatric disorders and/or serum levels of BDNF (Licinio et al., 2009; Pae et al., 2012; Terracciano et al., 2013; Yang et al., 2013; Kwon et al., 2015). For example, a previous study showed that rs12273539 polymorphism and the haplotype including the allele of this polymorphism was associated with major depressive disorder (MDD) (Licinio et al., 2009). Another study reported a significant association between rs2030324 and schizophrenia (Yang et al., 2013). Recently, rs10835210 was found to be associated with bipolar disorder, schizophrenia (Pae et al., 2012) as well as attention deficit hyperactivity disorder (ADHD) (Kwon et al., 2015). Hence, we had chosen these four polymorphisms and hypothesized that the BDNF gene variants may play a role in susceptibility to schizophrenia and in its clinical symptom severity. 2. Methods 2.1. Subjects We recruited 844 schizophrenia inpatients from Beijing Hui-LongGuan hospital, a Beijing-city-owned psychiatric hospital, and Hebei Province Veteran Psychiatric Hospital in BaoDing City, 50 miles from Beijing. All patients met the DSM-IV diagnosis of schizophrenia, which was confirmed by 2 psychiatrists using the Chinese version of Structured Clinical Interview for DSM-IV-TR Axis I Disorders-Patient Edition (SCID-I/P), which is standardized for the Chinese population and has been shown to be reliable and valid in China (Phillips et al., 2009). All schizophrenic patients were Han Chinese and between 25 and 75 years old (average: 47.8 ± 9.7 years). They were of the chronic type, with at least 5 years of illness (average: 24.3 ± 9.4 years). All patients had been receiving stable doses of oral antipsychotic drugs for at least 6 months before entry into the study. Antipsychotic drug treatment consisted mainly of monotherapy with clozapine (n = 396), risperidone (n = 178), chlorpromazine (n = 62), sulpiride (n = 44), perphenazine (n = 41), quetiapine (n = 34), aripiprazole (n = 25), haloperidol (n = 20), loxepine (n = 14) and other typicals (n = 15) or other atypicals (n = 15). Mean antipsychotic dose (in chlorpromazine equivalents) was 466 ± 429 mg/day. We also recruited 1043 normal controls from the local community. Current mental status and personal or family history of any mental disorder was assessed by unstructured interviews. None of them had any personal or family history nor demonstrated any clinical psychiatric disorders. All were Han Chinese from the Beijing area. All subjects were in good physical health, and any subjects with major medical illnesses or drug and alcohol abuse/dependence were excluded. All subjects gave written informed consent, which was approved by the Institutional Review Board of Beijing Hui-Long-Guan hospital. 2.2. Clinical symptom assessment Four psychiatrists who were blind to the clinical status assessed the patient's psychopathology with the PANSS (Kay et al., 1987) on the day of the blood sampling. To ensure consistency and reliability of ratings across the study, these four psychiatrists, who had worked at least 5 years in clinical practice, simultaneously attended a training session

in using the PANSS before the start of the study. After training, they maintained an inter-rater correlation coefficient greater than 0.8 for the PANSS total score.

2.3. Genotyping Genomic DNA was extracted from the venous blood samples using standard procedures. We used a restriction fragment length polymorphism (RFLP) method for genotyping the 4 tag SNPs as previously described (Jönsson et al., 2006). Briefly, first, DNA fragments containing each polymorphism were amplified with a polymerase chain reaction (PCR). Thereafter, PCR products were digested with restriction enzymes according to the manufacturer's instructions, loaded on a 4% agarose gel and visualized by ethidium bromide staining. Genotyping was duplicated by two investigators independently for accuracy and carried out blind to the clinical status. If the two investigators' genotype assignments did not agree, the samples were repeated. Also, genotyping error checks were conducted by re-genotyping within a subsample (n = 50), and reproducibility was routinely N0.99.

2.4. Statistical analysis Differences in clinical characteristics between patients and controls or between genotype groups were analyzed using chi-squared for categorical variables and the Student's t-test or one-way analysis of variance (ANOVA) for continuous variables using the PASW Statistics 18.0 software (SPSS Inc., Chicago, IL, USA). Deviation from the Hardy–Weinberg equilibrium (HWE) was tested separately in cases and controls using chi-square (χ2) goodness-of-fit test. The difference in the allele and genotype frequencies for the BDNF gene polymorphisms between patients and normal controls was analyzed using the χ2 test. The number of effective independent SNPs assayed was estimated to correct for multiple testing by the spectral decomposition method of Nyholt using the SNPSpD software (Nyholt, 2004). A logistic regression analysis was conducted to examine the independent association of each genotype (0: M/M, 1:M/m, 2:m/m; M: major allele, m: minor allele) on the categorical diagnosis of schizophrenia (0: control, 1: patient) after adjusting for the confounders, including gender, age, education, body mass index (BMI) and smoking. Bonferroni corrections were applied to each test to adjust for multiple testing. The genotype statuses and confounders were included in the model as independent variables, and diagnosis was included as a dependent variable. Pairwise linkage disequilibrium (LD) between four BDNF markers was analyzed in patients and normal controls. Haploview 4.2 was used to compute pairwise LD statistics for markers, haplotype block, haplotype frequency, and haplotype association. We used a 2 ~ 4-window fashion analysis. Rare haplotypes found in less than 1% were excluded from the association analysis. To control haplotype analyses for multiple testing, 10,000 permutations were performed for the most significant tests to determine the empirical significance. The quantitative trait test was performed using UNPHASED 3.1.5, which examined the association of gene polymorphisms with symptom severity. The effects of the BDNF genotypes on the clinical symptom in patients with schizophrenia were analyzed by one-way analysis of covariance (ANCOVA) to adjust for clinical confounding factors using the PASW Statistics 18.0 software. Standardized effect sizes were calculated using Cohen's d method. The power (power defined as the chance that true differences will actually be detected) of the sample was calculated using Quanto Software (Gauderman, 2002), with known risk allele frequencies and a schizophrenia population prevalence of 0.01, and we examined log additive, recessive and dominant models. Finally, to examine whether there was population stratification in our sample, which might lead to false positive results, we also calculated Z statistics using a panel of SNPs (Lee, 2003).

Please cite this article as: Zhang, X.Y., et al., BDNF polymorphisms are associated with schizophrenia onset and positive symptoms, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.11.009

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Table 1 showed significant differences in gender, age, education, body mass index (BMI) and smoking between cases and controls (all p b 0.05), which were adjusted in the following analyses as confounders. The smoking prevalence was 64% for the patients with schizophrenia and 36% for the control group, with an OR of 3.17 (95% CI: 2.62–3.84; X2 = 145.4, df = 1, p b 0.001). This difference remained significant after using logistic regression to control for the socio-demographic confounds, such as gender, age, education, and BMI (X2 = 121.6, p b 0.001, adjusted odds ratio = 2.78; 95% confidence interval, 2.23–3.35).

than male controls (p b 0.05) or in female patients than female controls (p b 0.05). However, we did not find significant differences in the allele frequencies of other 3 SNPs between male patients and controls or female patients and female controls (all p N 0.05). Two-four SNP sliding window haplotype analysis revealed a significant association of this gene with schizophrenia (the lowest global X2 = 41.34, p b 0.0001, SNP1–SNP2–SNP3), and the G–T–A haplotype frequency was greatest compared with other haplotypes of SNP1–SNP2– SNP3 (lowest X2 = 20.2, p b 0.0001). In addition, we found no association of any haplotypes with the clinical parameters, including gender, age, smoking, duration of illness, and dose, type (atypical vs typical antipsychotics) and duration of antipsychotic treatment (all p N 0.05).

3.2. Linkage disequilibrium (LD) analysis

3.4. Genotype and haplotype effects on clinical symptoms

LD analyses were performed for all polymorphism pairs in both case and control subjects. All four polymorphisms are in modest LD with each other in both control (D′ = 0.79 ~ 0.94; r2 = 0.06 ~ 0.48) and patient groups (D′ = 0.73 ~ 0.86, r2 = 0.04–0.44) (Fig. 1).

PANSS data were available from 825 patients. Table 3 shows that the three genotypes significantly differed on the PANSS positive symptom subscore for BDNF rs10835210 (F = 4.99, df = 8,22, p = 0.007; Bonferroni corrected p = 0.028), but not for the other three SNPs. Both AA (p = 0.004; effect size = 0.29) and AC (p = 0.045; effect size = 0.06) genotypes showed a significantly higher positive symptom scores than the CC genotype. Thus, a BDNF rs10835210 variant allele may produce an effect on positive symptoms of the patients. Further significant associations were identified between positive symptoms and the following haplotypes: rs12273539 (C)–rs10835210(A) (frequency 28.9%; x2 = 4.30, p = 0.038), rs6265(A)–rs12273539 (C)–rs10835210 (A) (frequency 27.1%; x2 = 5.17, p = 0.022) and rs6265(A)– rs12273539 (C)–rs10835210(A)–rs2030324(T) (frequency 23.9%; x2 = 3.89, p = 0.045). However, all these results did not remain statistically significant after 10,000 permutations (adjusted all p N 0.039).

3. Results 3.1. Subject characteristics

3.3. Genotype effects on risk for schizophrenia The genotype and allele frequencies of 4 SNPs located in the BDNF gene are summarized in Table 2. No deviation from HWE was detected in the cases or controls (all p N 0.05). No interaction was found between sex and genotypes for all 4 SNPs either for the whole group or when the normal controls and patients were examined separately (all p N 0.05). Significant differences in the genotype and allele frequencies between patients and controls were observed for rs10835210 (genotype X2 = 7.46, p = 0.024, allele X2 = 7.26, p = 0.007). After the SNPSpD correction (the effective number of independent marker loci: 3.12) for multiple SNP tests, the allelic association remained significant (p = 0.03), but not for genotypic association (p = 0.08). The frequency of the A allele (minor allele) of rs10835210 was higher in patients than in controls. There was no allelic or genotypic association between the other three SNPs and schizophrenia (Table 2). Because the gender ratio, as well as age, education, BMI and smoking, were not matched in this sample, a logistic regression analysis was performed for these four SNPs to control for these confounders. We found that the A allele of rs10835210 was significantly more frequent in cases than in controls and continued to be significantly associated with schizophrenia (p b 0.05). We then performed stratified analysis by gender. When a separate analysis for each gender was performed, we found a significantly more frequent A alleles of rs10835210 in male patients Table 1 Demographic characteristics in patients with schizophrenia and normal controls. Variable

Schizophrenia (n = 844)

Normal controls (n = 1043)

Statistic (P value)

Sex (male/female) Age (years) Education (years) Body mass index (kg/m2) Smoking Smoker Nonsmoker Age of onset (years) Number of hospitalization Antipsychotic types Typicals Atypicals Antipsychotic dose PANSS P subscore N subscore G subscore Total score

663/181 47.8 ± 9.7 8.9 ± 2.7 24.5 ± 3.9

586/457 44.9 ± 13.6 9.5 ± 3.3 25.0 ± 3.8

194.3 (b.001) 19.7 (b.001) 11.7 (b.001) 4.21 (b0.05) 145.4 (b.001)

541(64%) 303 (36%) 23.5 ± 5.4 4.2 ± 2.6

366 (36%) 650 (64%)

182 (22%) 662 (78%) 466 ± 429 11.7 ± 5.2 22.8 ± 8.4 25.2 ± 6.4 59.8 ± 15.8

3.5. Power and population stratification This total sample had 0.99 power for rs6265, rs10835210 and rs2030324, as well as 0.75–0.99 for rs12273539 to detect dominant, recessive and log additive polymorphic inheritance in schizophrenia with an odds ratio (OR) of 2 or greater (alpha = 0.05, two tailed test). Finally, we found no evidence for hidden population stratification, the Z statistic on the basis of the four SNPs was 1.65 for schizophrenia and 1.72 for healthy controls. 4. Discussion Two major findings evolved from the present study. (1) The BDNF gene rs10835210 polymorphism seems to contribute to the susceptibility to schizophrenia in a Chinese Han population. (2) The BDNF gene rs10835210 polymorphism may be associated with positive symptoms in schizophrenia patients. 4.1. BDNF gene polymorphisms and susceptibility to schizophrenia To our knowledge, this is the first study to find an association between schizophrenia and the BDNF gene polymorphism rs10835210 or the haplotype formed by this polymorphism and other polymorphisms. While most BDNF association studies have used individual markers, we used polymorphism-based haplotypes and LD analysis to show that both patients and controls shared a homogeneous LD pattern. This LD suggests that these variants segregate together in a Chinese population. In the present study, we found that rs10835210, an intronic variant located 16 kb away from rs6265, showed the most significant association with schizophrenia. The frequencies of mutational allele A, as well as genotypes AA and CA were higher in patients than normal controls, suggesting that mutational allele A may be a risk factor while ancestral allele C may be protective for schizophrenia. This finding is consistent

Please cite this article as: Zhang, X.Y., et al., BDNF polymorphisms are associated with schizophrenia onset and positive symptoms, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.11.009

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Fig. 1. Genomic structure of BDNF, including relative location of 4 SNPs studied and linkage disequilibrium (LD) of these 4 SNPs in the patients with schizophrenia and control groups. The LD between pairwise SNPs, using D′ (left, red color) and r2 (right, gray color) values, are shown separately for cases and controls. High levels of LD are represented by increasing scale intensity from 0 to 100, as shown by the bars. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

with a similar association for bipolar disorder (BD) and schizophrenia in Koreans, in which the rs10835210 AA and CA genotype frequencies were higher in BD and schizophrenia patients than in healthy and major depression subjects (Pae et al., 2012). However, there is still no functional analysis for this polymorphism. Whether this polymorphism affects BDNF levels or activity is still unknown and deserves further investigation. Haplotypes can be more specific risk markers than single alleles, and their use reduces false-positive associations that can occur because common psychiatric disorders are likely to associate with common alleles (Lohmueller et al., 2003). Since the four markers analyzed were in the same haplotype block, we performed the two-four SNP sliding window haplotype analysis (Gabriel et al., 2002). We found that the frequencies of all the haplotypes which contain the minor alleles of rs10835210 (A) were significantly more common in patients than in controls (all p b 0.01). Thus, the haplotype analyses further supported the results of the single polymorphism rs10835210. The polymorphism rs6265 (Val66Met) has been attractive as a functional polymorphism, since this polymorphism has been associated with altered intracellular trafficking of pro-BDNF and secretion of the mature peptide (Egan et al., 2003; Chen et al., 2006). In the present study, we did not find that this polymorphism contributed directly to the susceptibility to schizophrenia, which is consistent with the major of previous studies, including the recent meta-analysis (Rosa et al., 2006; Kawashima et al., 2009). Only a few case–control studies (Neves-Pereira et al., 2005; Suchanek et al., 2012), and a family-based study (Rosa et al., 2006) showed significant results. A possible explanation for this inconsistency is a difference in ethnic background. For example, the Met allele frequency of this polymorphism in Chinese

(around 50%) (Zhou et al., 2010; Yi et al., 2011) is notably different from that in Caucasian subjects (around 20%) (Naoe et al., 2007; Varnas et al., 2008). Thus, interethnic differences in the genotype frequencies of the BDNF Val66Met polymorphism may play an important role in accounting for the inconsistent results across the different populations. Several other factors may also account for these divergent results, for example, small gene effects, heterogeneity of the schizophrenia diagnosis, and population stratification. In addition, epigenetic modifications of DNA in BDNF gene promoters, for example, DNA-methylation and DNA-demethylation, as well as chromatin remodeling that induce covalent modification of histone lysine, induced by environmental factors is associated with altered BDNF expression regulation (Mitchelmore and Gede, 2014; Dong et al., 2015). There is substantial evidence that decreased neural BDNF levels in patients with schizophrenia are often associated with increased DNA methylation at the specific BDNF promoters. Importantly, observed DNA methylation changes are consistent across tissues including brain and peripheral blood (Ikegame et al., 2013; Dong et al., 2015). Hence, the differential epigenetic factors and methyliosis as a result of different environmental activities in different studies may be associated with altered BDNF gene expression. Recently, a number of genome-wide association studies (GWAS) have made encouraging progress in identifying a spectrum of common and rare genetic risk variants that contribute to schizophrenia susceptibility (Giusti-Rodríguez and Sullivan, 2013.). A recent study using pathway analysis to compare hypothesis-driven candidate genes with GWAS results from the International Schizophrenia Consortium (ISC), the largest and most comprehensive schizophrenia GWAS published to date found that the most studied hypothesis-driven candidate

Table 2 Genotypic and allelic distributions for SNPs in the BDNF gene between patients with schizophrenia and controls. Marker

M/m

SNP ID

Chromosome position

rs6265

27679916

G/A

rs12273539

27683311

T/C

rs10835210

27695910

C/A

rs2030324

27726915

C/T

Group

SCH NC SCH NC SCH NC SCH NC

Genotype

Allele

M/M

M/m

m/m

X2

p

M

m

X2

p

211 (0.25) 271 (0.26) 582 (0.69) 709 (0.68) 397 (0.47) 553 (0.53) 279 (0.33) 344 (0.33)

456 (0.54) 532 (0.51) 236 (0.28) 313 (0.30) 371 (0.44) 417 (0.40) 430 (0.51) 542 (0.52)

177 (0.21) 240 (0.23) 25 (0.03) 21 (0.02) 76 (0.09) 73 (0.07) 135 (0.16) 156 (0.15)

1.87

0.39

0.75

0.29

7.46

0.024⁎

0.42

0.81

810 (0.48) 1012 (0.49) 286 (0.17)0.002 355 (0.17) 523 (0.31) 563 (0.27) 700 (0.41) 854 (0.41)

0.10

2.46

878 (0.52) 1074 (0.51) 1400 (0.83) 1731 (0.83) 1165 (0.69) 1523 (0.73) 988 (0.59) 1230 (0.59)

0.96 7.26

0.007⁎⁎

0.09

0.76

Note: The unit of measure is n (%). P values b0.05 are in bold. Abbreviations: SCH = schizophrenia; NC = normal controls; M = major allele; m = minor allele; SNP = single-nucleotide polymorphism. ⁎ p b 0.05. ⁎⁎ p b 0.01.

Please cite this article as: Zhang, X.Y., et al., BDNF polymorphisms are associated with schizophrenia onset and positive symptoms, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.11.009

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Table 3 The association of BDNF genotypes with clinical symptoms in schizophrenia. SNP SNP1 P N G Total SNP2 P N G Total SNP3 P N G Total SNP44 P N G Total

m/m

M/m

M/M

F

df

p

11.4 ± 5.3 23.5 ± 8.9 25.1 ± 6.4 60.0 ± 16.6

11.8 ± 5.2 22.8 ± 8.0 25.2 ± 6.4 59.7 ± 15.3

11.8 ± 5.0 22.3 ± 9.2 25.3 ± 6.3 59.3 ± 16.4

0.51 0.97 0.04 0.04

2, 824 2, 820 2, 820 2, 820

0.60 0.38 0.96 0.92

12.2 ± 6.8 22.8 ± 9.9 26.3 ± 9.8 61.3 ± 24.3

11.6 ± 5.3 23.9 ± 8.6 25.4 ± 6.0 61.0 ± 15.5

11.6 ± 5.1 22.4 ± 8.3 25.0 ± 6.4 59.1 ± 15.6

0.12 2.35 0.69 1.25

2, 822 2, 820 2, 820 2, 820

0.89 0.097 0.51 0.29

12.4 ± 6.7 20.8 ± 8.7 26.3 ± 8.3 59.5 ± 19.3

12.1 ± 5.3 23.1 ± 8.4 25.7 ± 6.2 61.0 ± 15.6

11.0 ± 4.6 22.9 ± 8.5 25.2 ± 6.1 58.3 ± 15.6

4.99 2.25 3.48 2.63

2, 822 2, 820 2, 820 2, 820

0.007⁎⁎ 0.11 0.04⁎

11.0 ± 4.7 24.7 ± 9.4 25.1 ± 6.1 60.9 ± 16.1

11.9 ± 5.2 22.9 ± 7.9 25.3 ± 6.2 60.1 ± 15.0

11.4 ± 5.1 22.2 ± 8.9 24.9 ± 6.4 58.4 ± 15.6

1.81 3.60 0.34 1.30

2, 822 2, 820 2, 820 2, 820

0.16 0.028⁎ 0.71 0.27

Corrected pa

0.028⁎ 0.16

0.07

0.11

Note: SNP: single-nucleotide polymorphism. SNP1 = rs6265; SNP2 = rs12273539; SNP3 = rs10835210; SNP4 = rs2030324. M = major allele; m = minor allele; mm = homozygous minor allele; MM = homozygous major allele. P = positive symptom subscale; N = negative symptom subscale, G = general psychopathology subscale; Total = PANSS total score. a Corrected p refers to Bonferroni corrected p. ⁎ p b 0.05. ⁎⁎ p b 0.01.

genes (BDNF, COMT, DRD3, DRD2, HTR2A, NRG1, DTNBP1, and SLC6A4) had no notable results (Collins et al., 2012). Hence, our finding that the BDNF gene rs10835210 polymorphism and the haplotypes containing the minor alleles of this polymorphism were associated with schizophrenia in a Chinese Han population may be the result of false positives due to low statistical power by contemporary standards. Larger samples are required definitively to evaluate our finding. 4.2. BDNF gene polymorphisms and clinical symptoms of schizophrenia Our quantitative trait analysis showed that rs10835210 was associated with positive symptoms, and the patients carrying the mutational allele A at rs10835210 showed more positive symptoms. Further significant associations were identified between positive symptoms and the three haplotypes that all contained the allele A of rs10835210, which is consistent with the quantitative trait analysis for a single SNP. However, it is noteworthy that the effect sizes between the AA or AC genotype carrier and the CC genotype carrier for positive symptoms only were 0.06 and 0.29. Furthermore, the associations between positive symptoms and all the following haplotypes did not remain statistically significant after 10,000 permutations. These results suggest small gene effects. We postulate that the neurobiological mechanism for correlation between rs10835219 and positive symptoms of schizophrenia in our current study might be associated with the increased dopamine (DA) function caused by BDNF signaling. Studies have shown that BDNF interacts with the mesolimbic DA systems (Altar et al., 1997). For example, BDNF influences the release of DA in the mesolimbic dopamine system and the induction of DA-related behaviors (Narita et al., 2003), suggesting that endogenous BDNF may have a close relationship with DA systems (Nikulina et al., 2014). On the other hand, it is generally assumed that the positive symptoms of schizophrenia are associated with excess dopaminergic activity in the mesolimbic pathway (Lally and MacCabe, 2015). Therefore, we postulate that the correlation observed between rs10835219 and positive symptom of patients in the present study might be associated with abnormal interaction between BDNF signaling and DA systems. However, we still do not know whether this BDNF rs10835219, an intronic variant located 16 kb away from Val66Met is functional or not and whether it influences BDNF levels or

activity, since no study has assessed such issue. Although the precise neurobiological effect of the rs10835210 polymorphism presently unknown, the fact that other SNPs in the intronic regions of BDNF might regulate the level of serum (Terracciano et al., 2013), suggesting that this could be an underlying mechanism for the observed association between rs10835219 and positive symptoms of schizophrenia in our current study. Interestingly, some previous studies have shown a significant positive relationship between BDNF levels and positive symptoms in schizophrenia (Buckley et al., 2007; Chen da et al., 2009), supporting this hypothesis. However, this is only our speculation; whether this BDNF polymorphism can affect circulating levels of the protein and how BDNF and DA systems interact and then relate to positive symptoms of schizophrenia need to be explored with further detailed investigations. To our knowledge, this is the first study that examines the association between the BDNF haplotype and psychopathologic symptoms in schizophrenia patients. One previous study suggested that the Val/Val genotype of the BDNF Val66Met was associated with more positive symptoms compared to Met carriers in chronic hospitalized patients in a Japanese population (Numata et al., 2006). Another study found that Val homozygous patients displayed the highest negative symptom scores and Val/Met heterozygotes displayed the lowest, whereas Met homozygotes displayed symptom scores between these two genotypes among the Han Chinese population in northern Taiwan (Chang et al., 2009). In the present study, although we found the association of the two haplotypes including rs6265 Val allele with positive symptoms, we did not find a direct association between Val66Met and clinical symptoms. Such a discrepancy may be attributable to several reasons. First, the BDNF genotypes can be regarded as trait-dependent features, while the assessment of illness intensity by PANSS is state-dependent. Therefore, a comparison of genotypes with the intensity of illness at any different given time could be different. For example, our study's chronic schizophrenia inpatients had comparatively lower levels of clinical symptoms (PANSS total score 55.0) compared to the medicationfree schizophrenia patients (PANSS total score 99.7) in the study in Taiwan (Chang et al., 2009). Hence, the differences in severity of clinical symptoms might be responsible for the discrepancy. Second, inconsistency can arise from differences in clinical subtypes of schizophrenia, in stages of disease progression (acute vs. chronic or active phase vs.

Please cite this article as: Zhang, X.Y., et al., BDNF polymorphisms are associated with schizophrenia onset and positive symptoms, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.11.009

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remission), in illness courses, and in exposure to different types, dosages and durations of antipsychotic medications. Several limitations of this study should be noted. First, although current mental status and personal or family history of any mental disorder was ruled out by unstructured interviews in the control group, we did not use a psychometric instrument, such as SCID or any other standardized instrument for this specific Chinese population. Hence, we cannot fully exclude the possibility that some healthy controls may exhibit psychotic symptoms but do not meet full criteria for schizophrenia. Future studies will need to address this question. Second, some important clinical parameters, such as martial and employee status had not been collected, and we did not know whether and how these confounds may influence our findings in current study. Third, studying a sample of schizophrenia patients at any point in treatment although convenient to obtain a large sample, is not as strong as studying young or ideally first episode patients for whom the genetic effects on behavioral phenotypes might be stronger since the confounds of chronic illness and deprivation and medication exposure are much smaller. Moreover, the BDNF genotypes can be regarded as trait-dependent features, while the assessment of illness intensity by PANSS is state-dependent. Thus, a comparison of genotypes with the intensity of illness at any given time could be misleading. Therefore, our results need to be replicated in a group of first-episode, never medicated patients with schizophrenia from different ethnic populations. Fourth, since our sample size provided only poor statistical power by contemporary standards, it is possible that we do see the false-positive results in the present study and our findings need to be considered cautiously. A replication study would be needed to include a large sample size. Moreover, although we had genotyped 4 polymorphisms in the present study, the coverage of genetic variation is too limited considering the total BDNF gene variants includes at least 50 polymorphisms. Therefore, it would be much better to use GWAS in larger samples to capture true positive results found in our present study. In summary, we report several convergent findings that implicate an effect of BDNF genotype on increased risk for schizophrenia and on severity of clinical symptoms using individual genotype and haplotype analyses. We found a potential genetic association of BDNF with risk for schizophrenia, especially the mutant A allele of the BDNF gene polymorphism rs10835210. Further, we found that this polymorphism rs10835210 was associated with positive symptoms, and the patients carrying the mutational allele A showed greater levels of positive symptoms. However, the findings in our present study remain preliminary due to the confounds of chronic illness and medication exposure in our patient subjects, limited sample size and our low statistical power, as well as poor coverage of genetic variations in BDNF, which require replication in larger samples of first-episode, never medicated patients with schizophrenia from different ethnic populations. Conflict of interest The authors have no conflicts to disclose.

Contributors Xiang Yang Zhang was responsible for study design, statistical analysis, manuscript preparation and writing the protocol and the paper. Da Chun Chen, Yun-Long Tan and Shu-Ping Tan were responsible for clinical data collection and lab experiments. Xingguang Luo, Lingjun Zuo and Jair C Soares were involved in evolving the ideas and editing the manuscript. All authors have contributed to and have approved the final manuscript.

Role of the funding source Funding for this study was provided by grants from the National Natural Science Foundation of China (81371477), the Beijing Municipal Natural Science Foundation (7132063 and 7072035), the NARSAD Independent Investigator Grant (20314), and the Stanley Medical Research Institute (03T-459 and 05T-726). These 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. Acknowledgments The authors would like to thank Mei Hong Xiu, Zhi Ren Wang, Wu Fang Zhang, Song Chen, Bao Hua Zhang, and Gui Gang Yang for all of their hard work and significant contributions toward the study.

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Please cite this article as: Zhang, X.Y., et al., BDNF polymorphisms are associated with schizophrenia onset and positive symptoms, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.11.009