Schizophrenia (SCZ) is a severe and heritable psychiatric disorder that is characterized by positive and negative symptoms, and it affects almost 1% of the general population worldwide (Thaker and Carpenter, 2001). Although the heritability rate for SCZ has been estimated to be 64–81%, the environmental factor is considered another pathogenic factor (Sullivan et al., 2003; Lichtenstein et al., 2009). Despite the high prevalence of SCZ and many decades of research, the precise etiology and genetic mechanism of this illness are still unknown.
The Forkhead-box P2 (FOXP2) gene is located on chromosome 7q31, and it encodes a transcription factor. The first evidence that FOXP2 carried a heterozygous missense mutation was based on the investigation of a large three-generation pedigree (the KE family), in which approximately half of the individuals had a severe speech and language disorder (Fisher et al., 1998; Lai et al., 2001). FOXP2 was proven to directly affect Childhood Apraxia of Speech; however, several reports have identified that there are potential genes that are regulated by FOXP2 in other communication disorders (Spiteri et al., 2007; Vernes et al., 2007, 2011; Konopka et al., 2009). As many studies have reported, brain tissues show broad expression of the FOXP2 transcript (Ferland et al., 2003; Lai et al., 2003; Takahashi et al., 2003). In the cerebellar neural circuit, Foxp2 expression was crucial for synaptic plasticity in Foxp2 (R552H) knockin mice (Groszer et al., 2008). Foxp2 knockout mice showed a reduced size of the cerebellum and poor dendritic arbors of these neurons, which impaired motor function and the ability to communicate (Shu et al., 2005; Fujita et al., 2008).
There are some evidences for FOXP2 interacting with schizophrenia-related genes. FOXP2 directly suppressed the transcription of the DISC1 gene; however, two FOXP2 mutations decreased the inhibition of DISC1 expression (Walker et al., 2012). A balanced t(1;11) translocation disrupted the DISC1 gene in a Scottish family, which showed a significant linkage for SCZ (Blackwood et al., 2001). In addition, several studies have confirmed the role of DISC1 in psychiatric disorders (Brandon and Sawa, 2011; Porteous et al., 2011). DISC1 can has been implicated in GSK3β/β-catenin signaling pathways, which create alterations in early neurodevelopment and synaptic regulation (Mao et al., 2009). Furthermore, FOXP2 produced regulation in the transcript levels of the CNTNAP2 gene (Zhao et al., 2015). The phenotypes associated with CNTNAP2 mutations were usually complex and associated with autism, SCZ, intellectual disability, seizures, and language regression (Rodenas-Cuadrado et al., 2014). In both human patients and mouse models, CNTNAP2 played an important role in regulating neuronal development (Penagarikano et al., 2011). Thus, FOXP2 may promote neurodevelopment by regulating DISC1, CNTNAP2, and other downstream targets.
Language and communication are commonly considered the two core signs of normally developed human beings. In addition, deficits in language and speech are important features of many psychiatric disorders, and the specific language circuits have been found to be affected early in psychiatric disorders such as SCZ (Li et al., 2009). Thus, FOXP2 can be considered a good candidate gene for an indicator of mental diseases. The FOXP2 polymorphism related to SCZ has been identified in many studies. For example, Sanjuán et al. (2006) identified a significant associated single nucleotide polymorphism (SNP) rs2396753 and a haplotype with SCZ patients with auditory hallucinations. Furthermore, they found a significant association between FOXP2 rs2253478 and SCZ patients (Tolosa et al., 2010). Gong et al. (2004) found a significant association between autistic disorder and FOXP2 rs1456031. Taken together, these findings suggest that FOXP2 gene polymorphisms may play an important role in the pathogenesis of SCZ.
A study of FOXP2 rs10447760 has been carried out previously by Li et al. (2013) in the Chinese Han population. They focused on the relationship between the gene FOXP2 and SCZ in 1135 schizophrenic patients and 1135 normal controls. They found statistically significant differences in allele frequencies (P=0.00069, 0.00838 after Bonferroni correction) at rs10447760 (Li et al., 2013). Subsequently, the most recent study failed to find differences in the genotype and allele frequencies between the chronic SCZ patients and healthy controls, but they found significant differences in the Positive and Negative Syndrome Scale total, positive symptom score, and general psychopathology (Rao et al., 2017). However, these findings have produced both negative and positive results in the previous studies. Therefore, in our study, to evaluate the association of FOXP2 rs10447760 with SCZ, we replicated the case–control study in an independent Han Chinese population from Jiangsu province.
Participants and methods
The ethnicity of all participants was Han Chinese. The patients with SCZ were recruited from the Wuxi Mental Health Center and diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV). Healthy controls without a current or a previous psychiatric diagnosis or a family history of mental illness were recruited from the general population by advertisements. Before enrollment, signed informed consent was obtained from every participant or their guardians if the participant was a minor or could not provide consent. The study protocols were performed according to the principles of the Declaration of Helsinki. This study was approved by the Ethics Committees of the Wuxi Mental Health Center.
The study sample included 1405 patients with SCZ (875 men and 530 women; mean age=45.93 years at recruitment, SD=11.45) and 1137 matched unrelated healthy controls (630 men and 507 women; mean age=44.91 years at recruitment, SD=10.30), drawn from a population of individuals of Han descent (Table 1).
DNA extraction and SNP genotyping
Blood samples were collected from all participants using K2EDTA tubes and DNA was extracted from whole blood using a blood genotyping DNA extraction kit (Tiangen Biotech, Beijing, China). DNA samples were stored at−80°C until genotype analysis, in which we used the ligase detection reaction–PCR method (Yi et al., 2009; Yuan et al., 2015) from Shanghai Biowing Applied Biotechnology Co. Ltd. (http://www.biowing.com.cn).
Genomic DNA extracted from the clinical samples was first subjected to multiplex PCR to obtain a PCR product including rs10447760. The PCR primers were 5′-AACACTGCAGGCTTTGTTCG-3′ (forward) and 5′-TTTGGAGTCAGCTAGCACAG-3′ (reverse). This PCR product and the LDR probes (CGGCTGCTGCTGGAACTGGCCG for ‘C’ allele detection; TCGGCTGCTGCTGGAACTGGCCA for ‘T’ allele detection) were then subjected to a multiplex LDR reaction, with a DNA sequencer used to detect the products.
Statistical and bioinformatics analysis
The online software platform SHEsis (http://analysis.bio-x.cn/myAnalysis.php) was used to carry out all statistical analyses (Shi and He, 2005), including association studies, Hardy–Weinberg equilibrium (HWE) tests, and the calculation of genotype and allele frequencies between patients with SCZ and healthy controls. A logistic regression adjusted for age and sex was applied to evaluate how these factors influence the distribution of the SNP rs10447760. Power calculations to determine the appropriate sample size were carried out using PS software (http://biostat.mc.vanderbilt.edu/wiki/Main/PowerSampleSize) (Dupont and Plummer, 1990, 1998). All of the P values less than 0.05 were used as the threshold of statistical significance. Odds ratio (OR) and 95% confidence intervals (95% CI) were determined to assess the influence of any difference in heterogeneity. Meta-analysis was carried out using the Review Manager 5.3 (The Nordic Cochrane Centre for The Cochrane Collaboration, Copenhagen, Denmark) and STATA 12.0 (Stata Corp., College Station, Texas, USA). The significance of the pooled ORs was determined using a Z-test. Between-study heterogeneity was assessed by the Q-test and I2-statistic; P less than 0.10 and I2 greater than 50% indicated evidence of heterogeneity (Higgins and Thompson, 2002). A random-effect model or a fixed-effect model was chosen to calculate the subtotal OR and 95% CI on the basis of whether there was a significant difference in heterogeneity among these studies.
In this study, we analyzed the data from 1405 patients with SCZ and 1137 unrelated healthy controls. The total genotyping rate in all individuals was 100%. HWE tests indicated that the genotype and allele frequency distribution of FOXP2 rs10447760 did not deviate significantly from HWE (P=0.970 for cases; P=0.961 for controls) (Table 2). In addition, the power calculation using the OR (Ψ = 0.377) from previous study (published by Li et al., 2013) determined whether our sample size was enough under well-recognized genetic effect threshold. The power of the present study for the SNP was estimated to be ∼80% using PS software (assumption condition: α=0.05, P0=0.01, n=2810, m=0.809, Ψ=0.377).
Our results of the association study suggested that the minor allele T of SNP rs10447760 within FOXP2 was not associated significantly with SCZ risk (P=0.387, OR=0.772, 95% CI: 0.429–1.389) in a Han Chinese sample (Table 2). In addition, logistic regression models adjusted for age and sex failed to support any positive association between SCZ and the SNP rs10447760 (Table 3). For the meta-analysis, we combined and analyzed data from three independent studies, including the current study. Random-effects models were adopted as significant heterogeneity was present in the current meta-analysis (P=0.01, I2=77%). The statistical results suggested that the SNP rs10447760 in FOXP2 might not be a risk locus for susceptibility to SCZ in Han Chinese populations using a random-effect model (pooled OR=1.44, 95% CI: 0.63–3.31, P=0.39) (Fig. 1).
Many current reports have indicated that a prime candidate, FOXP2, is likely related to human language development (Fisher et al., 1998; Lai et al., 2001; Enard et al., 2002, 2009; Macdermot et al., 2005; Vernes et al., 2006, 2008). Language and communication are often disordered in patients with SCZ and some other mental diseases. Thus, FOXP2 can be considered a good candidate gene for an indicator of mental diseases.
In the previous studies, these findings showed an association between rs10447760 within the FOXP2 gene and SCZ, with conflicting results. It was first reported by Sanjuán et al. (2006) that a haplotype of FOXP2, which contained rs10447760, significantly correlated with SCZ by a permutation test (P=0.009). In addition, rs10447760 was also shown to have a significant correlation with SCZ in the study by Li et al. (2013) (allelic P=0.000698, and P=0.00838 after correction). However, Rao et al. (2017) failed to find significant differences in the genotype and allele frequencies between the chronic SCZ patients and healthy controls, but they found significant differences between the PANSS positive symptom score and general psychopathology (both P<0.05). Therefore, we repeated this experiment to confirm whether this SNP was associated with SCZ in the Han Chinese population. As a result, there was no statistically significant correlation between FOXP2 rs10447760 and SCZ in our study. Meanwhile, statistical results from the meta-analysis also indicated no significant correlation in the studies. Our results are consistent with the study by Rao et al. (2017) in the Han Chinese population.
The finding in this study may be the result of several limitations. One of the main limitations of our current study was that the participants were all recruited from Jiangsu province, whereas samples obtained from the study by Sanjuán et al. (2006) were drawn from Europe, Li et al. (2013) from Shanghai, and Rao et al. (2017) from Beijing. In the study by Sanjuán et al. (2006), all individuals were Whites of Spanish descent, and the frequency of the variant allele T at rs10447760 among the controls was 0.2406, which was much higher than that of Li et al. (2013), Rao et al. (2017), and this study (0.007, 0.006, and 0.01, respectively). Therefore, the differences in the rs10447760 polymorphism profiles suggested that the individuals from differently racial and geographic aspects might also show genetic heterogeneity of SCZ. Meanwhile, statistical results from the meta-analysis also indicated a significant heterogeneity between the studies, and different genotyping methodologies may affect the rare allele frequency, thereby causing the heterogeneity. In addition, sampling errors caused by differences in clinical diagnosis of SCZ cannot entirely be excluded.
Other limitations of our report should be considered. First, the most recent study showed that rs10447760 may be associated with clinical symptoms of SCZ (Rao et al., 2017). Because of insufficient clinical information, we could not assess the influence of these factors on the interaction between rs10447760 and SCZ. Second, our results may be influenced by the low statistical power and limited sample size because the allele T at rs10447760 is a rare variant. Third, other SNPs within the FOXP2 gene were not analyzed, and the likelihood of their modification on SCZ could not be ruled out. Fourth, the particular SNP rs10447760 is a rare variant in the study, and the P values of rare variants can be easily disturbed by a slight inaccuracy genotyping or other random factors.
In our study, no statistically significant association between FOXP2 rs10447760 and SCZ was discovered in a Chinese Han population, and consistent results were obtained compared with the most recent research. However, in this study, we failed to identify the potential risk within FOXP2 because we studied only the SNP rs10447760 in FOXP2 gene that could not fully elucidate the mechanism of the FOXP2 gene behind its influence on SCZ. Thus, other SNPs within the FOXP2 gene and large-scale genetic replication studies with different racial and geographic origins are needed in the future.
The authors thank the SCZ patients and healthy participants for their cooperation in the study. This work was supported by the National Natural Science Foundation of China (81471364).
Authors’ contributions: Conceived and designed the experiments: J.Y., N.J., J.Y. Performed the experiments: J.Y., N.J., Y.L., S.Y. Analyzed the data: J.Y., N.J., C.J. F.Z. Contributed reagents/materials/analysis tools: S.Y. J.W. Wrote the paper: J.Y. N.J. J.Y. All the authors read and approved the final manuscript.
Conflicts of interest
There are no conflicts of interest.
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