Association between C-Maf-inducing protein gene rs2287112 polymorphism and schizophrenia

Introduction

Schizophrenia (SCZ) is a severely multifactorial neuropsychiatric disorder that affects almost 1% of adults around the world. A recent study found that the lifetime prevalence of SCZ patients in China was 0.6% (Huang et al., 2019). SCZ has devastating impacts on patients’ and their families’ quality of life. It also has an enormous financial cost. SCZ is a prototypical multifactorial disorder caused by both genetic and environmental factors. Genetic factors play a major role in SCZ etiology (Owen, Sawa & Mortensen, 2016) and genetic variations in chromosome 16 are associated with a variety of neuropsychiatric disorders. Some rare, common, and copy number variants on chromosome 16p have been found to be associated with SCZ (Chang et al., 2017; Giaroli et al., 2014). Regions on chromosome 16q, highly specific to a single psychometric measure, are also associated with neuropsychiatric disorders. Previous studies found that regions on chromosome 16q may increase susceptibility to SCZ (Lewis et al., 2003), bipolar disorder (Lewis et al., 2003), and autism (Wassink et al., 2008). Furthermore, large-scale genome-wide association studies (GWAS) conducted by Bigdeli et al. (2020) and Pardiñas et al. (2018) respectively showed two (rs34753377 and rs6500603) and three (rs17465671, rs12447542 and rs2161711) single-nucleotide polymorphisms (SNPs), located on chromosome 16 that were associated with SCZ.

C-Maf-inducing protein (CMIP) is an important gene located on 16q23 that is mainly expressed in human brains, encodes an 86-kDa protein 7-9, and plays a role in the T-cell signaling pathway (Liu et al., 2015). CMIP contributes to several biological pathways and is involved in various diseases such as glioma, gastric cancer, kidney disease, and dyslipidemia (Li et al., 2019; Mo et al., 2018; Wang & Wu, 2017; Zhang et al., 2017), as well as major depressive disorder, syndromic autism spectrum disorders, and specific language impairments (Eicher & Gruen, 2015; Gedik, 2017; Luo et al., 2017; Wang et al., 2015). However, no studies have documented the relationship between CMIP and SCZ.

Based on chromosome 16’s biological function and previous studies on CMIP, we hypothesized that CMIP may have a relationship with SCZ. Additionally, gender-specific associations between gene SNPs (i.e., RELN, GABRB3 and MTHFR) and SCZ have been found in several other studies (Sozuguzel & Sazci, 2019; Wan et al., 2019; Liu et al., 2018). We conducted a genetic association study stratified by gender to examine the association between tag SNPs of the CMIP gene and SCZ in the Han Chinese population.

Materials & Methods

Results

LD and haplotype analysis

As shown in Fig. 1, the R² values were 19 across total subjects (A) and male (B) and female subjects (C). LD was not observed across these SNPs according to the criteria (R² > 0.8). The four SNPs’ position relationship in CMIP according to the National Center for Biotechnology Information (NCBI, https://www.ncbi.nlm.nih.gov/) gene structure are shown in Fig. 1D. We conducted haplotype association analysis with SCZ across all participants because the LD analysis results were similar between the male and female groups. The haplotype analysis results (Table 4) indicated that the haplotype made of all four SNPs (rs12925980–rs2287112–rs3751859–rs77700579) had a significantly different distribution between SCZ patients and healthy controls (P_adj = 0.018). Furthermore, we estimated nine common haplotypes with a frequency >1% in detail. The results showed that the haplotype TTGT was significantly associated with SCZ (OR = 0.42, 95% CI [0.19–0.94], P = 0.032), but when FDR-adjusted the P-value was greater than 0.05 (Table 5).

Table 5:

Association between rs12925980–rs2287112–rs3751859–rs77700579 haplotype and schizophrenia.

rs12925980–rs2287711–	Frequency			OR (95%CI)	P	Padj
rs3751859–rs77700579	Total	Control	Case
CTGA	0.3426	0.3548	0.329	1
CTAA	0.1782	0.1758	0.179	1.07 [0.83–1.38]	0.620		0.620
TTGA	0.1681	0.163	0.173	1.11 [0.85–1.44]	0.440		0.620
TGGA	0.0945	0.0908	0.099	1.10 [0.80–1.51]	0.550		0.620
TTAA	0.082	0.0769	0.09	1.26 [0.90–1.74]	0.170		0.453
CTGT	0.0402	0.0357	0.047	1.33 [0.82–2.17]	0.250		0.500
TGAA	0.0279	0.0309	0.025	0.83 [0.46–1.51]	0.540		0.620
CTAT	0.0249	0.0307	0.019	0.60 [0.30–1.22]	0.160		0.453
TTGT	0.0234	0.0317	0.013	0.42 [0.19–0.94]	0.032*		0.272

DOI: 10.7717/peerj.11907/table-5

Notes:

* P < 0.05.

OR is abbreviation of Odds ratio, 95% CI is abbreviation of 95% confidence interval.

Discussion

Many studies have investigated the association between the CMIP gene and diseases such as mental neuropsychiatric disorder (Eicher & Gruen, 2015; Luo et al., 2017; Wang et al., 2015), cancer (Juan et al., 2019), and metabolic disease (Cao, Wang & Wu, 2018; Mo et al., 2018). In this study, we included 1,536 participants to study the association between four tag SNPs (rs12925980, rs22287112, rs3751859 and rs77700579) of the CMIP gene and SCZ. To the best of our knowledge, our study is the first of its kind to explore the correlation between CMIP and SCZ in the northeast CHB. We found that one loci (rs2287112) was associated with SCZ in females, indicating that CMIP was a potential risk genetic variant for SCZ. A large scale GWAS study conducted by Gedik (2017) found that the SNP rs77700579 in CMIP was associated with major depressive disorder (MDD), supporting the conclusion that CMIP was a potential candidate gene for neuropsychiatric disorders.

Several studies have detected sex-distinct gene polymorphisms with SCZ, including LTA, TNFA, IFNGR2 and PLA2G12A (Inoubli et al., 2018; Jemli et al., 2017; Yang et al., 2016). Yu et al. (2013) found eight genes with differential expression in female and male SCZ patients. Our research group also found a sex-specific SNP of gene RELN with SCZ in a previous study (Bai et al., 2019). Considering that SCZ’s sex-specific molecular phenotype has been observed in previous studies, we first explored the association between CMIP and SCZ in all samples and then separately tested the association for the male and female subgroups. We found that the SNP rs2287112 was significantly associated with SCZ in the whole group and female subgroup with a statistically significant value of 0.05. However, in the whole group the P value did not withstand FDR correction. The association between rs2287112 and SCZ only existed after P value correction in the female group. The association was not observed in the male group, providing more evidence that the molecular phenotype in SCZ is sex-specific. It should be noted that rs2287112 was not in HWE in the SCZ group, which suggested population stratification. The population structure evaluation showed no stratification and the control group conformed to HWE, ruling out the possibility of population admixture. The deviation from HWE may have been caused by the association with the disease that exerted a strong selection on the genome (Li et al., 2011).

Additionally, we carried out haplotype analysis to determine the association between the haplotype and SCZ and whether the combination of specific alleles could affect SCZ susceptibility. The TTGT haplotype (rs12925980–rs2287112–rs3751859–rs77700579) correlated with a lower risk of SCZ in our study population, but the association did not survive FDR correction. Similarly, the haplotype consisting of rs12929303–rs2287112–rs12925980 in CMIP was associated with developmental dyslexia in a Chinese population (Wang et al., 2015), suggesting that the haplotype including rs22287112 may contribute to disease susceptibility. The haplotype analysis further supported that rs2287112 allele G correlated with an increased SCZ risk.

Since this was a cross-sectional study, several limitations should be mentioned. First, this study was limited to interpreting the causal relationship between genetic risk factors and SCZ. Second, we only analyzed four SNPs in this study and may have missed some other loci associated with SCZ. Additionally, owing to the failure of demographic characteristic and in-depth clinical trait collection, we were not able to analyze the association of these SNPs with different SCZ clinical features. We were also limited to interaction analysis between genes and environment. Further studies that incorporate a large-scale sample size with more demographic characteristic information are warranted to further substantiate the association between CMIP gene polymorphism and SCZ susceptibility.

Conclusion

This study presented evidence that a CMIP variant is associated with SCZ susceptibility in northeast Han Chinese women. Considering the limitations of our work, additional functional genomics studies are required to further explain the role of SCZ-associated CMIP variants.

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