Elsevier

Psychiatry Research

Volume 241, 30 July 2016, Pages 104-107
Psychiatry Research

Short communication
Analysis of the association of VIPR2 polymorphisms with susceptibility to schizophrenia

https://doi.org/10.1016/j.psychres.2016.04.084Get rights and content

Highlights

  • We investigated the association of VIPR2 variants with the risk of schizophrenia.

  • No significant association was observed in overall samples.

  • SNP-SNP interaction signals were significantly associated with the risk of SCZ.

  • The SNP rs3812311 was nominally associated with the risk of schizophrenia in male samples.

Abstract

In a previous study, we confirmed that copy number variants (CNVs) within the VIPR2 gene in Han Chinese individuals exhibit an increased risk of schizophrenia (SCZ). Herein, we further analyzed the association of eight tagged single nucleotide polymorphisms (tagSNPs) from the HapMap database with SCZ susceptibility. However, we found no significant positive signals in overall association and haplotypes analyses. Interestingly, significant SNP-SNP interaction signals associated with the risk of SCZ were observed using Multifactor Dimensionality Reduction (MDR) analysis. Furthermore, the ‘CC’ genotype of the VIPR2 gene was nominally associated with an increased risk of SCZ in male patients.

Introduction

Schizophrenia (SCZ) is an idiopathic, devastating, and chronic psychiatric disorder that affects ~1% of the global population. The heritability of SCZ has been estimated to be ~64–80% (Thaker and Carpenter, 2001, Lichtenstein et al., 2009). However, to date, our understanding of the genetic architecture of SCZ has not been sufficient to uncover the precise etiology and genetic mechanisms involved. Genome-wide association studies (GWASs) have identified many loci of susceptibility for SCZ (O’Donovan et al., 2008, Stefansson et al., 2009, Yue et al., 2011, Shi et al., 2011, Ripke et al., 2013; Psychiatric Genomics Consortium, 2014). A recent study revealed copy number variation (CNV) within the vasoactive intestinal peptide receptor 2 (VIPR2) gene, which may be involved in the risk of SCZ (Vacic et al., 2011). VIPR2 is a class II G protein-coupled receptor encoded by the VIPR2 gene in humans, which is involved in regulating neurodevelopment, behavior (Harmar et al., 2002, Chaudhury et al., 2008), and circadian rhythm (Pauls et al., 2014;). We confirmed that microduplications in the VIPR2 gene were significantly associated with susceptibility to SCZ in the Han Chinese population. Based on the findings of our previous study, this present study aimed to investigate whether single nucleotide polymorphisms (SNPs) within the VIPR2 gene are associated with the risk of SCZ.

Section snippets

Study population

All participants were individuals of Han Chinese descent, A total of 1434 patients (539 women and 895 men, aged 45.9±11.5 years at recruitment) including paranoid type (70%) and other types (30%) and 1154 unrelated healthy controls (512 women and 642 men, aged 44.9±10.3 years at recruitment) were enrolled.

Diagnoses of SCZ was confirmed by interviews with two or more experienced psychiatrists using the Structured Clinical Interview for DSM-IV (SCID-I) in accordance with criteria in the

Results

In the HWE for all eight tagSNPs, the P-values exceeded 0.05 for all normal controls (data not shown). The power of this present study for each allele was estimated to be ~70% using PS software (assumption condition: α=0.05, P0=0.2, n=1434, m=0.8, Ψ=1.25). In addition, the power was only estimated to be ~20% for lower OR (Ψ=1.1).

In an association analysis, neither allelic nor genotypic modeling revealed a significant association between the risk of SCZ and any of eight tagSNPs (Table 1). An

Discussion

In this case-control study of Han Chinese individuals, we failed to identify a significant association between the eight tagSNPs within VIPR2 and the risk of SCZ in all of the samples. A stratified analysis by gender showed that the distribution frequency of the ‘CC’ genotype of rs3812311 occurred at 13.2% in male SCZ patients (n=895) and 9.3% in healthy controls (n=642). Unfortunately, the difference in frequency was not significant after multiple testing, although this may be a consequence of

Conflicts of interest

The authors have no conflicts of interest to disclose.

Acknowledgements

This study was supported by the National Natural Science Foundation of China (No. 81301147), the Wuxi Hospital Management Center Foundation (No. YGZXG1403), and Excellent Young Talents Project of Wuxi Municipal Health Bureau.

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      On the other hand, genes with the most direct biological roles in affecting synapses, such as DAO, DAOA, and RGS4, seem to have the weakest association with the disease. In addition to DTNBP1, NRG1, COMT, GRM3, DAO, DAOA (G72), AKT1, BDNF, Reelin, GAD 67, DISC1, SELENBP1, and RGS4 genes, genome-wide association studies have previously identified that protein phosphatase 3 catalytic subunit gamma (PPP3CC) (Harrison and Weinberger, 2005; Harrison and Law, 2006), Proline dehydrogenase (PRODH2) (Gogos et al., 1999; Jacquet et al., 2002; Liu et al., 2002a, 2002b), DARPP32 (Albert et al., 2002; Svenningsson et al., 2004), CHRNA7 (Freedman et al., 1997, 2000; Leonard et al., 2002; Mexal et al., 2010; Luo et al., 2014), GSK3α, BTG1, HLA- DRB1, HNRPA3, SFRS1 (Glatt et al., 2005), GSK-3β (Kozlovsky et al., 2000, 2002, 2004; Emamian et al., 2004), guanine nucleotide-binding protein G subunit alpha O (GNAO1) (Vawter et al., 2004; Yao et al., 2008; Yamamori et al., 2011), MDH1 (Vawter et al., 2004), neuropeptide Y receptor Y1 (NPY1R) (Kuromitsu et al., 2001; Vawter et al., 2004; Hashimoto et al., 2008; Yamamori et al., 2011), DRD2, DRD3, 5-HT2A (Schmauss et al., 1993; Schmauss, 1996; Schindler et al., 2002; Glatt et al., 2003; Abdolmaleky et al., 2004a; Jonsson et al., 2004; Owen et al., 2004a; Li et al., 2006), leucyl-tRNA synthetase 2, mitochondrial (LARS2), SRY-related homeobox gene 10 (SOX10) (Munakata et al., 2005), phosphoprotein enriched in astrocytes 15 (PEA-15), calcium binding protein A1 (S100), myelin and lymphocyte protein (MAL), myelin basic protein (MBP), myelin-oligodendrocyte basic protein (MOBP) (Hakak et al., 2001; Tkachev et al., 2003; Prabakaran et al., 2004; Sugai et al., 2004), g-protein inhibitory alpha1 (Giα1), glutamate receptor 3 (GluR3), N-methyl-d-aspartate 1 (NMDA1), synaptophysin, phospholemman (Hemby et al., 2002), chondrex, histamine releasing factor, heat domain and rcc1-like domain 2 (HERC2), HSP 70 (Chung et al., 2003), myelin associated glycoprotein (MAG), PLLP (TM4SF11), PLP1, erb-b2 receptor tyrosine kinase 3 (ErbB3), myelin-oligodendrocytic protein (MOG), tumor necrosis factor receptor associated factor 4 (TRAF4), neurogenic differentiation 1 (Neurod1), histone deacetylase-3 (Hakak et al., 2001; Tkachev et al., 2003; Aston et al., 2004; Prabakaran et al., 2004), alpha-1-antichymotrypsin A3 (SERPINA3), interferon induced protein with tetratricopeptide repeats 1, 2 and 3 (IFITM1, IFITM2 and IFITM3), chitinase 3 like1 (CHI3L1), metallothionein 2A (MT2A), cell differentiation 14 (CD14), heat shock protein beta 1 (HSPB1), HSPA1B, HSPA1A, cholecystokinin (CCK) (Arion et al., 2007; Hashimoto et al., 2008), apolipoprotein L1 (apo L1), ApoL2, ApoL4 (Mimmack et al., 2002), cyclic nucleotide phosphodiesterase (CNP), heregulin-3 (HER3), growth associated protein-43 (GAP-43), myristolated alanine-rich C-kinase substrate (MARCKS), GABA-A (Hakak et al., 2001), N-ethyl-maleimide sensitive fusion protein (NSF), Synapsin II, glutamate receptor 1-2 (GluR1-2) (Mirnics et al., 2000; Faludi and Mirnics, 2011), TAF13, SETD1A (Fromer et al., 2014; Takata et al., 2014, 2016; Singh et al., 2016), Neurexin 1 (NRXN1), vasoactive intestinal peptide receptor 2 (VIPR2), p21 (RAC1) activated kinase 7 (PAK7), FMO5, NIPA1, CYFIP1, GJA8, NDE1, SNAP29, GJA5, BCL9, NTAN1, PRKAB2, VIPR2, PARK2, DLG2, ABCC1, RTN4R, ZDHHC8, CRKL, THAP7, DGCR6L, ACP6, TUBGCP5, A2BP1, KLHL22, MYH11 (Sudhof, 2008; Luo et al., 2014; Morris et al., 2014; Yuan et al., 2014; Jenkins et al., 2016; Jin et al., 2016), and Calcineurin (Sik et al., 1998; Cousin and Robinson, 2001; Winder and Sweatt, 2001; Groth et al., 2003; Miyakawa et al., 2003) genes are potentially associated with Scz. However, we describe the biomarkers that have been reported repeatedly in previous studies.

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