Open Access

Genetic risk between the CACNA1I gene and schizophrenia in Chinese Uygur population

Contributed equally
Hereditas2017155:5

https://doi.org/10.1186/s41065-017-0037-1

Received: 25 April 2017

Accepted: 7 June 2017

Published: 17 July 2017

Abstract

Background

Schizophrenia (SCZ) is a common mental disorder with high heritability, and genetic factors play a major role in the pathogenesis. Recent researches indicated that the CACNA1I involved in calcium channels probably affect the potential pathogenesis of SCZ.

Results

In this study, we attempted to investigate whether the CACNA1I gene contributes the risk to SCZ in the Uighur Chinese population, and performed a case-control study involving 985 patient samples and 1218 normal controls to analyze nine SNPs within the CACNA1I gene. Among these sites, six SNPs were significantly associated with SCZ in the allele distribution: rs132575 (adjusted P allele  = 0.039, OR = 1.159), rs713860 (adjusted P allele  = 0.039, OR = 0.792), rs738168 (adjusted P allele  = 0.039, OR = 0.785), rs136805 (adjusted P allele  = 0.014, OR = 1.212), rs5757760 (adjusted P allele  = 0.042, OR = 0.873) and rs5750871 (adjusted P allele  = 0.039, OR = 0.859). In addition, two SNPs turned to be risk factors for SCZ not only in the allele distribution, but also in the genotype distribution: rs132575 (adjusted P genotype  = 0.037) and rs136805 (adjusted P genotype  = 0.037).

Conclusions

Overall, the present study provided evidence that significant association exists between the CACNA1I gene and SCZ in the Uighur Chinese population, subsequent validation of functional analysis and genetic association studies are needed to further extend this study.

Keywords

Schizophrenia, CACNA1I gene, Case-control study, Uighur Chinese

Background

Schizophrenia (SCZ) is one of enigmatic, complex psychotic mental disease that characterized by abnormalities in the perception or expression of reality, causing a substantial burden on patients and public expenditure [1, 2]. The lifetime prevalence of SCZ is generally estimated to be 1%, and genetic risks account for up to 80% occurrences [3]. This chronic disorder poses series of typical manifestations resembling auditory hallucinations, delusions, and behavioral dysfunction [4, 5]. A lot of crucial developments in neuropathology, epidemiology, and medications are emerged, triggering better identification of etiology and effective therapeutics. Analysis of the genetic epidemiologic in family, twin, and adoption, the conclusion suggest that hereditary loci for which linkage to the SCZ play a critical role in the development of the disease [6].

With the deepening research of gene detection and disease mechanism, CACNA1I (calcium voltage-gated channel subunit alpha1 I) has been identified as a candidate gene for SCZ. Recently, a primary GWAS conducted by the Psychiatric Genomics Consortium-Schizophrenia Workgroup (PGC-SCZ) has made encouraging progress in identifying genetic susceptibility loci, and the CACNA1I gene is reported as a new locus for SCZ in Caucasian [7]. CACNA1I is located at 22p13.1, spanning about 118 kb genomic region, and consists of 38 exons. This gene encodes Cav3.3 isoform that contains a pore-forming alpha subunit, and the coding product of CACNA1I is a member of low-threshold (T-type) Ca2+ channels [8, 9]. The CACNA1I gene is abundantly expressed in the thalamic reticular nucleus, and delineates the distinctive physiological properties of neuronal firing [10, 11]. There are three subtypes of low threshold voltage-activated T-type Ca2+ channels have been implicated and designated α1G (Cav3.1), α1H (Cav3.2) and α1I (Cav3.3) by previous reports, which endow typical kinetic features and involve in different signatures of T-currents, respectively [12]. In view of the exploration of the thalamic reticular and relay neurons activities, increasing results point to Cav3.1 and Cav3.2 channels represent short burst firing and small conductance, while Cav3.3 leads to slower activation and inactivation [13, 14].

The normal physiological activities of human beings need to be maintained through the action potential discharge of specific ion channels. Ion exchange is responsible for the level of intracellular Ca2+, carry out a series of electrical, chemical, and physical function [15]. Evidence demonstrates that CACNA1I mRNA is ubiquitously expressed in brain regions, and Cav3.3 channel provoked by small membrane depolarization can elicit spontaneous discharge. The channel encoded by CACNA1I plays a central role in the thalamic spindle generator [16], alongside reduced sleep spindles associate with SCZ [17]. Abnormalities of sleep spindles and disturbances in thalamic neurons, are found in people with schizophrenia. It is noteworthy that the encode proteins has been reported can meet the druggable target of SCZ [18]. Moreover, T-type calcium channels have been shown to be a crucial cause of insomnia and neuropathic pain [19]. There is evidence that a single copy of Chr22:39665939G > A CACNA1I triggers calcium channel disorder and is associated with the pathogenesis of SCZ [20]. These profound findings have prompted us to open up promising research idea that CACNA1I might regulates signaling pathways in SCZ.

Uygur is one of the minority nationalities in China, and mainly distributes in Xinjiang Province. The region located in the northwest border area of China, and the hinterland of the Eurasian continent. As a part of the ancient Silk Road, the mutual migration between the countries, the typical diets, and the different lifestyles play the important role in shaping the genetic structure [21, 22]. The Uygur populations therefore are results of admixture of Han Chinese and Western Europe [23], and also is the highlight of the current study.

To date, there have been no studies that CACNA1I SNPs association with SCZ in the Uygur Chinese population reported, so it is the first study which performed CACNA1I in the Uygur Chinese population. A total of nine SNPs were selected in CACNA1I, including eight tag SNPs which were examined to provide a good coverage of this region, and one positive SNP which identified from a genome-wide association study was selected [24].

Methods

Subjects

In total, 985 unrelated patients with SCZ (612 males and 373 females), and 1218 control individuals (629 males and 589 females) were enrolled from Xinjiang Province. The mean age of SCZ cases was 39.45 years (±12.12), and normal controls was 43.07 years (±13.14). The data was illustrated as Table 1.
Table 1

Demographic detail of sample set

 

Patients with schizophrenia

Healthy controls

Total sample(N)

985

1218

Male

Female

Male

Female

612

373

629

589

Mean age ± SD

39.45 ± 12.12

43.07 ± 13.14

All eligible subjects selected were the native population of Xinjiang province. Clinical diagnosis were carried out in strict accordance with DSM-IV criteria (Diagnostic and Statistical Manual of Mental Disorders, the fourth edition) based on SCID-I (Structured Clinical Interview for DSM-IV Axis I Disorders) by interviewed with two independent psychiatrists. The healthy controls were randomly selected from the general Uighur population. All participants signed informed consent. This study obtained the consent of the local ethnic ethics, and undertaken the support of its support.

Genomic assay

According to QuickGene DNA whole blood kit L (FUJIFILM), genomic DNA was isolated from the peripheral blood of the subjects. Eight tag SNPs (rs132567, rs738168, rs713860, rs11705208, rs132575, rs136805, rs5757760, rs5750871) are obtained through Haploview software version 4.2, with pair-wise r 2 threshold ≥0.5 and minor allele frequency ≥ 0.05 [25]. Besides, we put a positive site of the previous research (rs9607658) into the experiment. The specific information of these 9 SNPs is listed in Table 2, while, the nine SNPs in the relative position of CACNA1I gene is also shown in Fig. 1. All samples were subjected to genotyping by the Sequenom MassARRAY matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry platform (Sequenom Inc., San Diego, CA).
Table 2

The information of 9 SNPs in CACNA1I gene

SNP ID

rs9607658

rs132567

rs132575

rs713860

rs738168

rs136805

rs11705208

rs5757760

rs5750871

Position

39,561,735

39,577,521

39,586,716

39,612,821

39,615,692

39,622,207

39,646,048

39,648,397

39,673,444

Function

intron

intron

intron

intron

intron

intron

intron

intron

intron

Polymorphism

C/T

A/G

C/T

C/T

A/G

C/T

C/T

C/T

A/G

Fig. 1

Relative positions in gene CACNA1I of nine SNPs

Statistical analysis

Powerful SHEsis software provides a set of processing parameters for maximum benefit, including allele and genotype frequencies, Hardy-Weinberg equilibrium, association tests and haplotype analysis (http://shesisplus.bio-x.cn/SHEsis.html) [26, 27]. This is a comprehensive platform for processing association study, and perform expectation maximization algorithm in haplotype reconstruction and frequency estimation. Allele and genotype frequencies refer to the percentage of allele and genotype in a population, and show the diversity and abundance of the gene in a population. FDR correction is a conservative method to explain multiple comparisons. All outputted tests were two-tailed, the P value standard of the statistical significance were set to be less than 0.05.

Results

Single site analysis

The genotype P values of the 9 SNPs in Hard–Weinberg equilibrium test (HWE) were all larger than 0.05 in both patients and healthy controls. So they all did not deviate from Hard–Weinberg equilibrium, and demonstrated the genetic properties of this sample population remained relatively stable. Call rates of all loci exceeded 99% in all samples. Detailed information is referenced in Table 3.
Table 3

The call rate (%) and HWE test of 9 SNPs in SCZ patients and control

SNP ID

rs9607658

rs132567

rs132575

rs713860

rs738168

rs136805

rs11705208

rs5757760

rs5750871

case

control

case

control

case

control

case

control

case

control

case

control

case

control

case

control

case

control

call rate%

0.996

0.997

0.996

0.996

0.997

0.991

0.997

0.992

0.992

HWE-P

0.904

0.654

0.549

0.222

0.231

0.483

0.515

0.929

0.729

0.955

0.973

0.837

0.658

0.999

0.999

0.989

0.58

0.78

In Table 4, all the allele and genotype P values for the 9 SNPs in the patient samples and normal controls are shown. rs132575 and rs136805 were significant in both allele and genotype distributions [rs132575: adjusted P allele  = 0.039, adjusted P genotype  = 0.037; rs136805: adjusted P allele  = 0.014, adjusted P genotype  = 0.037]. In addition, rs713860, rs738168, rs5757760 and rs5750871 were significantly associated with SCZ in the allele distributions [rs713860: adjusted P allele  = 0.039, OR[95% CI] = 0.792[0.652–0.963]; rs738168: adjusted P allele  = 0.039, OR[95% CI] = 0.785[0.651–0.947]; rs5757760: adjusted P allele  = 0.042, OR[95% CI] = 0.873 [0.773–0.985]; rs5750871: adjusted P allele  = 0.039, OR[95% CI] = 0.859 [0.76–0.97]]. It is notable that rs738168 showed genotypic significance with SCZ before FDR correction [P genotype  = 0.03, P genotype  = 0.084 after FDR correction].
Table 4

Allele and genotype frequencies of 9 Loci in SCZ

SNP ID

Alleles

 

OR [95% CI]

P-value

P-FDR

Genotypes

  

P-value

P-FDR

rs9607658

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 Case

618(0.314)

1350(0.685)

1.101 [0.968 ~ 1.253]

0.142

0.178

94(0.095)

430(0.436)

460(0.467)

0.218

0.245

 Control

711(0.293)

1711(0.706)

   

111(0.091)

489(0.403)

611(0.504)

  

rs132567

A(freq)

G(freq)

   

A/A(freq)

A/G(freq)

G/G(freq)

  

 Case

1073(0.545)

895(0.454)

0.917 [0.814 ~ 1.034]

0.159

0.178

284(0.288)

505(0.513)

195(0.198)

0.054

0.084

 Control

1271(0.523)

1155(0.476)

   

348(0.286)

575(0.474)

290(0.239)

  

rs132575

A(freq)

G(freq)

   

A/A(freq)

A/G(freq)

G/G(freq)

  

 Case

1295(0.658)

673(0.341)

1.159 [1.021 ~ 1.316]

0.021

0.039

414(0.42)

467(0.474)

103(0.104)

0.008

0.037

 Control

1674(0.69)

750(0.309)

   

587(0.484)

500(0.412)

125(0.103)

  

rs713860

C(freq)

T(freq)

   

C/C(freq)

C/T(freq)

T/T(freq)

  

 Case

1779(0.904)

187(0.095)

0.792 [0.652 ~ 0.963]

0.019

0.039

808(0.821)

163(0.165)

12(0.012)

0.056

0.084

 Control

2142(0.882)

284(0.117)

   

947(0.78)

248(0.204)

18(0.014)

  

rs738168

C(freq)

A(freq)

   

C/C(freq)

C/A(freq)

A/A(freq)

  

 Case

1763(0.895)

205(0.104)

0.785 [0.651 ~ 0.947]

0.011

0.039

792(0.804)

179(0.181)

13(0.013)

0.03

0.084

 Control

2115(0.871)

313(0.128)

   

920(0.757)

275(0.226)

19(0.015)

  

rs136805

C(freq)

T(freq)

   

C/C(freq)

C/T(freq)

T/T(freq)

  

 Case

1001(0.509)

965(0.49)

1.212 [1.075 ~ 1.365]

0.001

0.014

253(0.257)

495(0.503)

235(0.239)

0.006

0.037

 Control

1339(0.556)

1065(0.443)

   

378(0.314)

583(0.485)

241(0.2)

  

rs11705208

C(freq)

T(freq)

   

C/C(freq)

C/T(freq)

T/T(freq)

  

 Case

1775(0.901)

193(0.098)

1.039 [0.849 ~ 1.27]

0.708

0.708

803(0.816)

169(0.171)

12(0.012)

0.771

0.771

 Control

2198(0.905)

230(0.094)

   

995(0.819)

208(0.171)

11(0.009)

  

rs5757760

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 case

766(0.389)

1200(0.61)

0.873 [0.773 ~ 0.985]

0.028

0.042

149(0.151)

468(0.476)

366(0.372)

0.09

0.116

 control

1017(0.422)

1391(0.577)

   

216(0.179)

585(0.485)

403(0.334)

  

rs5750871

G(freq)

A(freq)

   

G/G(freq)

G/A(freq)

A/A(freq)

  

 case

748(0.38)

1218(0.619)

0.859 [0.76 ~ 0.97]

0.014

0.039

150(0.152)

448(0.455)

385(0.391)

0.051

0.084

 control

1003(0.416)

1403(0.583)

   

215(0.178)

573(0.476)

415(0.344)

  

Italics represent P-values < 0.05

According to the gender of the subjects, the two sample sets were obtained separately. Detailed analysis results are illustrated in Tables 5 and 6. For male samples, there are seven ninths of the genes significantly associated with SCZ. rs132575, rs136805, rs5757760 and rs5750871 showed association towards SCZ in both allele and genotype distributions, meanwhile, rs9607658, rs713860, rs738168 revealed stronger positive results in the allele distributions. Interestingly, there was no significant association between CACNA1I and SCZ in the female sample, all the P values of 9 SNPs were greater than 0.05.
Table 5

SNP analysis in men

SNP ID

Alleles

 

OR [95% CI]

P-value

P-FDR

Genotypes

  

P-value

P-FDR

rs9607658

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 Case

394(0.322)

828(0.677)

1.218 [1.025 ~ 1.447]

0.024

0.031

59(0.096)

276(0.451)

276(0.451)

0.065

0.084

 Control

350(0.28)

896(0.719)

   

49(0.078)

252(0.404)

322(0.516)

  

rs132567

A(freq)

G(freq)

   

A/A(freq)

A/G(freq)

G/G(freq)

  

 Case

674(0.551)

548(0.448)

0.892 [0.761 ~ 1.044]

0.156

0.176

176(0.288)

322(0.527)

113(0.184)

0.167

0.188

 Control

655(0.523)

597(0.476)

   

172(0.274)

311(0.496)

143(0.228)

  

rs132575

A(freq)

G(freq)

   

A/A(freq)

A/G(freq)

G/G(freq)

  

 Case

790(0.646)

432(0.353)

1.266 [1.07 ~ 1.498]

0.005

0.013

247(0.404)

296(0.484)

68(0.111)

0.008

0.02

 Control

873(0.698)

377(0.301)

   

307(0.491)

259(0.414)

59(0.094)

  

rs713860

C(freq)

T(freq)

   

C/C(freq)

C/T(freq)

T/T(freq)

  

 Case

1111(0.91)

109(0.089)

0.731 [0.563 ~ 0.95]

0.018

0.028

507(0.831)

97(0.159)

6(0.009)

0.053

0.079

 Control

1104(0.881)

148(0.118)

   

486(0.776)

132(0.21)

8(0.012)

  

rs738168

C(freq)

A(freq)

   

C/C(freq)

C/A(freq)

A/A(freq)

  

 Case

1101(0.9)

121(0.099)

0.724 [0.564 ~ 0.928]

0.01

0.019

497(0.813)

107(0.175)

7(0.011)

0.028

0.051

 Control

1087(0.868)

165(0.131)

   

470(0.75)

147(0.234)

9(0.014)

  

rs136805

C(freq)

T(freq)

   

C/C(freq)

C/T(freq)

T/T(freq)

  

 Case

600(0.49)

622(0.509)

1.292 [1.102 ~ 1.513]

0.001

0.013

149(0.243)

302(0.494)

160(0.261)

0.007

0.02

 Control

688(0.554)

552(0.445)

   

194(0.312)

300(0.483)

126(0.203)

  

rs11705208

C(freq)

T(freq)

   

C/C(freq)

C/T(freq)

T/T(freq)

  

 Case

1099(0.899)

123(0.1)

1 [0.769 ~ 1.299]

0.998

0.998

498(0.815)

103(0.168)

10(0.016)

0.315

0.315

 Control

1126(0.899)

126(0.1)

   

505(0.806)

116(0.185)

5(0.007)

  

rs5757760

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 case

464(0.379)

758(0.62)

0.79 [0.673 ~ 0.929]

0.004

0.013

86(0.14)

292(0.477)

233(0.381)

0.004

0.02

 control

541(0.436)

699(0.563)

   

103(0.166)

335(0.54)

182(0.293)

  

rs5750871

G(freq)

A(freq)

   

G/G(freq)

G/A(freq)

A/A(freq)

  

 case

454(0.371)

768(0.628)

0.794 [0.675 ~ 0.933]

0.005

0.013

92(0.15)

270(0.441)

249(0.407)

0.009

0.02

 control

530(0.426)

712(0.573)

   

110(0.177)

310(0.499)

201(0.323)

  

Italics represent P-values < 0.05

Table 6

SNP analysis in women

SNP ID

Alleles

 

OR [95% CI]

P-value

P-FDR

Genotypes

  

P-value

P-FDR

rs9607658

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 Case

224(0.3)

522(0.699)

0.968 [0.793 ~ 1.182]

0.755

0.907

35(0.093)

154(0.412)

184(0.493)

0.835

0.835

 Control

361(0.306)

815(0.693)

   

62(0.105)

237(0.403)

289(0.491)

  

rs132567

A(freq)

G(freq)

   

A/A(freq)

A/G(freq)

G/G(freq)

  

 Case

399(0.534)

347(0.465)

0.96 [0.798 ~ 1.153]

0.664

0.907

108(0.289)

183(0.49)

82(0.219)

0.407

0.808

 Control

616(0.524)

558(0.475)

   

176(0.299)

264(0.449)

147(0.25)

  

rs132575

A(freq)

G(freq)

   

A/A(freq)

A/G(freq)

G/G(freq)

  

 Case

505(0.676)

241(0.323)

1.024 [0.841 ~ 1.247]

0.806

0.907

167(0.447)

171(0.458)

35(0.093)

0.302

0.808

 Control

801(0.682)

373(0.317)

   

280(0.477)

241(0.41)

66(0.112)

  

rs713860

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 Case

78(0.104)

668(0.895)

0.891 [0.663 ~ 1.196]

0.443

0.907

6(0.016)

66(0.176)

301(0.806)

0.718

0808

 Control

136(0.115)

1038(0.884)

   

10(0.017)

116(0.197)

461(0.785)

  

rs738168

A(freq)

C(freq)

   

A/A(freq)

A/C(freq)

C/C(freq)

  

 Case

84(0.112)

662(0.887)

0.881 [0.662 ~ 1.172]

0.384

0.907

497(0.813)

72(0.193)

295(0.79)

0.646

0808

 Control

148(0.125)

1028(0.874)

   

470(0.75)

128(0.217)

450(0.765)

  

rs136805

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 Case

343(0.461)

401(0.538)

1.085 [0.902 ~ 1.305]

0.384

0.907

75(0.201)

193(0.518)

104(0.279)

0.47

0808

 Control

513(0.44)

651(0.559)

   

115(0.197)

283(0.486)

184(0.316)

  

rs11705208

T(freq)

C(freq)

   

T/T(freq)

T/C(freq)

C/C(freq)

  

 Case

70(0.093)

676(0.906)

1.067 [0.776 ~ 1.466]

0.687

0.907

2(0.005)

66(0.176)

305(0.817)

0.523

0808

 Control

104(0.088)

1072(0.911)

   

6(0.01)

92(0.156)

490(0.833)

  

rs5757760

C(freq)

T(freq)

   

C/C(freq)

C/T(freq)

T/T(freq)

  

 case

442(0.594)

302(0.405)

0.993 [0.823 ~ 1.197]

0.943

0.943

133(0.357)

176(0.473)

63(0.169)

0.363

0808

 control

692(0.592)

476(0.407)

   

221(0.378)

250(0.428)

113(0.193)

  

rs5750871

A(freq)

G(freq)

   

A/A(freq)

A/G(freq)

G/G(freq)

  

 case

450(0.604)

294(0.395)

0.954 [0.79 ~ 1.151]

0.626

0.907

136(0.365)

178(0.478)

58(0.155)

0.563

0808

 control

691(0.593)

473(0.406)

   

214(0.367)

263(0.451)

105(0.18)

  

Linkage disequilibrium

The pairwise linkage disequilibrium (LD) values among the all investigated SNPs were subjected to calculate in all subjects. A total of 4 haplotype blocks of CACNA1I (rs132575-rs713860, rs713860-rs738168, rs713860-rs11705208, rs11705208-rs5750871) were identified when SNPs with D′ > 0.95 were classified in the same block, as presented in Fig. 2.
Fig. 2

Linkage disequilibrium among 5 SNPs of the CACNA1I gene

Haplotype analysis

There were two haplotypes (A-T: adjusted P = 0.038, OR [95% CI] = 0.804 [0.661–0.977]; G-C: adjusted P = 0.025, OR[95% CI] = 1.175 [1.035–1.334]) in the block rs132575-rs713860, which were significantly associated with SCZ, haplotype A-T proved to be a protective factor, and haplotype G-C showed it was risk factor. In the block rs713860-rs738168, haplotype C-C and T-A demonstrated protective factor and risk factor of SCZ, respectively (C-C: adjusted P = 0.007, OR [95% CI] =1.299 [1.079–1.564]; T-A: adjusted P = 0.023, OR[95% CI] = 0.797 [0.656–0.969]). In the block rs11705208-rs5750871, one haplotype C-G presented protective factor of SCZ (adjusted P = 0.038, OR [95% CI] =0.873 [0.773–0.986]), another haplotype, C-A, was risk factor after data analysis (adjusted P = 0.015, OR [95% CI] = 1.174 [1.042–1.322]). The result of haplotype analysis is suggested in Table 7.
Table 7

Haplotype Analysis for CACNA1I Gene in SCZ

Blocks with D’ > 0.95

Haplotype

Case(freq)

Control(freq)

Chi 2

OR [95% CI]

P-value

P-FDR

rs132575-rs713860

A-C

1107(0.563)

1393(0.575)

0.435

0.96 [0.851 ~ 1.082]

0.52

0.509

A-T

187(0.095)

281(0.116)

4.788

0.804 [0.661 ~ 0.977]

0.03

0.038

G-C

672(0.341)

745(0.307)

6.216

1.175 [1.035 ~ 1.334]

0.013

0.025

rs713860-rs738168

C-C

1762(0.896)

2112(0.87)

7.714

1.299 [1.079 ~ 1.564]

0.006

0.007

T-A

187(0.095)

283(0.116)

5.161

0.797 [0.656 ~ 0.969]

0.023

0.023

rs713860-rs11705208

C-C

1588(0.807)

1913(0.788)

2.883

1.136 [0.98 ~ 1.317]

0.091

0.134

C-T

191(0.097)

229(0.094)

0.109

1.034 [0.845 ~ 1.266]

0.757

0.757

T-C

187(0.095)

284(0.117)

5.352

0.794 [0.653 ~ 0.965]

0.021

0.062

rs11705208-rs5750871

C-G

745(0.379)

1000(0.417)

4.761

0.873 [0.773 ~ 0.986]

0.03

0.038

T-A

191(0.097)

225(0.093)

0.268

1.055 [0.861 ~ 1.292]

0.604

0.604

C-A

1027(0.522)

1172(0.488)

7.041

1.174 [1.042 ~ 1.322]

0.008

0.015

Italics represent P-values < 0.05

Discussion

SCZ is a genetically complex neuropsychiatric disorder, but the specific etiology of this disease is still vague. SCZ is highly heritable, and the genes that contribute to the disorder play an important role [28]. In this context, we have attempted to confirm an association of CACNA1I variants with SCZ. We discovered nine variation sites within the CACNA1I locus, as well as one previously studied by Aiden Corvin et al. [24]. This is first study which replicated genetic susceptibility of CACNA1I gene in the Uygur Chinese population.

We found nominally association between several SNPs of CACNA1I and SCZ. There are four SNPs, rs713860, rs738168, rs5757760 and rs5750871 identified to be associated with SCZ in the allele distributions. In addition, both rs132575 and rs136805 were found to be significantly associated in allelic and genotype analysis. Before FDR correction, rs738168 was associated with schizophrenia in the genotype distribution. Most of the investigated SNPs were positive in our subjects.

rs9607658 was reported as a risk factor for SCZ in population of Ireland in a genome–wide association study (GWAS) by Aiden Corvin et al. (combined P = 3.3 × 10−5, OR[95% CI] = 1.21[1.10–1.33]) [24]. However, rs9607658 did not confer susceptibility in the present study (adjusted P = 0.142, OR[95% CI] = 1.101[0.968–1.253]). This is likely to be caused by racial differences between Uygur and Ireland populations, and the existence of genetic heterogeneity can lead to such a result. A study on Uygur genetic characteristics suggest Uygur population from northern and southern Xinjiang Province share different proportions of ancestors from the European and Han population, so they are the results of admixture the anthropological features of the East and West [29, 30]. The minor allele frequency (MAF = T) in the Han Chinese population is 0.03, whereas in the Ireland population it is 0.54. The results of these two different populations are profound discrepancy, and Uighur population as mixture of the European and Han population also produce certain differences in MAF. Besides, the accuracy of the result is related to the sample size, and the small sample size in this study is used as a limitation for the significant analysis.

In addition, the result has been adopted segregation analysis of sex as a research strategy. We found that male had more susceptibility loci for SCZ, but all the SNPs were negative in the female group. This may be due to a difference in the prevalence and symptoms of psychiatric disorders from a gender standpoint. Previous literature also shows that the existence of significant gender differences in animal models of mental illness [31]. Compared with women SCZ patients, men with SCZ have a high rate of mortality (death, suicide) and earlier onset in the study of gender differences by Mao-Sheng Ran et al. [32]. For the present study, a total of 373 women in the patient sample, 589 women were recruited in the control group. Sample size is a critical factor in gender analysis, thus, there is a need for a larger sample to validate the association between gender and SCZ.

Although these nine SNPs are located in the intron region of CACNA1I gene, and they are not directly involved in the biological functions and characteristics of T-type calcium channel, intronic variations may provide some auxiliary cis-acting elements for gene expression regulation, which plays a role in modifying gene transcription efficiency. The protein encoded by CACNA1I is widely expressed in the nucleus reticularis thalami, different splice variants can affect the normal discharge of neurons [33]. Besides, we evaluated the protein interaction of CACNA1I gene by the version 10.0 of STRING [34], the result showed the CACNB2 gene involved in SCZ interacts with CACNA1I gene, Whether different splice variants or protein-protein interactions, they may confers risk for SCZ.

The CACNA1I gene encodes the alpha-1 subunit of the T-type voltage-gated calcium channel Cav3.3, presenting series of function of calcium ion channel that are involved in the neural development and synapse formation [35]. Gene related to Ca2+ signaling, such as CACNA1I that encode VGCC subunits is associated with schizophrenia and other psychiatric disorders [36]. Evidence suggested that this gene is significantly associated with psychiatric disorders such as autism spectrum disorders. rs5750860, located in CACNA1I, has been reported to be associated with autism spectrum disorders by using existing genome-wide association study (GWAS) data and imputation methods [37] . Previous study indicated CACNA1I plays a crucial role in spindle activity by participating in the synchronous oscillation of thalamic cortical neurons, and expected to serve as a novel treatment biomarker associated with impaired cognition for individuals with SCZ by treating spindle deficits [17]. The release of neurotransmitters involved in the pathological process of SCZ, and simultaneously there is the research indicated that the CACNA1I gene triggers synaptic plasticity in reticular thalamic neurons. Presynaptic neurotransmitter release and postsynaptic receptor signal transduction play an important role in the transmission of information in the brain [38].

Conclusion

For this study, our efforts on mental illness represent a promising beginning. This is the first time that genetic factors of the CACNA1I gene have been verified to be associated with SCZ in the Uygur Chinese population. Obviously, CACNA1I plays a key role in the pathogenesis of SCZ. However, the present study remains a major bottleneck in the validation of larger samples, and a larger sample size could be better demonstrate the role of the CACNA1I gene in the etiology of schizophrenia. In addition, the Uighur Chinese population has been verified in the present study, and genetic association of other ethnic groups are suggested. Further functional studies of the CACNA1I gene are encouraged to conduct, especially in other ethnic groups. All the analysis will facilitate new therapeutic route for SCZ and may provide new insight into the pathogenesis of psychiatric illnesses.

Abbreviations

CACNA1I

Calcium voltage-gated channel subunit alpha1 I

DSM-IV: 

Diagnostic and Statistical Manual of Mental Disorders, the fourth edition

GWAS: 

Genome wide association study

HWE: 

Hardy–Weinberg equilibrium test

LD: 

Linkage disequilibrium; OR, odds ratio

MALDI-TOF: 

Matrix-assisted laser desorption ionization-time of flight

PGC-SCZ: 

Psychiatric Genomics Consortium -Schizophrenia Workgroup

SCID-I: 

Structured Clinical Interview for DSM-IV Axis I Disorders

SCZ: 

Schizophrenia

Declarations

Funding

We are deeply grateful to all the participants in the study. And we appreciate psychiatrists working on this project as well as the normal controls and patients. This work is supported by the 973 Program (2015CB559100), the 863 project (2012AA02A515), the Natural Science Foundation of China (31,325,014, 81,130,022, 81,272,302, 81,421,061), the National High Technology Research and Development Program of China (2012AA021802), the Program of Shanghai Academic Research Leader (15XD1502200), National Program for Support of Top-Notch Young Professionals, Shanghai Key Laboratory of Psychotic Disorders (13dz2260500), “Shu Guang” project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation (12SG17).

Availability of data and materials

Not applicable.

Authors’ contributions

Author Wei Xu, Yahui Liu and Jianhua Chen co-deigned this study, wrote the protocol, carried on all experiments and managed the literature searches and analyses. Juan Zhou and Zujia Wen conducted the sample collection and verification. Qingli Guo and Zhijian Song undertook the statistical analysis. Ke Liu and Zhaowei Zhou were responsible for platform coordination and management. Author Wei Xu wrote the first draft of the manuscript, while Yongyong Shi, Qizhong Yi and Lin He supervised the whole research process. All authors contributed to and have approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

The study was scrutinized and approved by the local ethical committee with all informed consent being accessible to subjects.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of biology, School of Life Science, Anhui Medical University
(2)
Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University
(3)
Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine
(4)
Psychological Medicine Center, The First Affiliated Hospital of Xinjiang Medical University

References

  1. Walker ER, McGee RE, Druss BG. Mortality in mental disorders and global disease burden implications: a systematic review and meta-analysis. JAMA psychiatry. 2015;72(4):334–41.View ArticlePubMedPubMed CentralGoogle Scholar
  2. van Os J, Kapur S. Schizophrenia. Lancet (London, England). 2009;374(9690):635–45.View ArticleGoogle Scholar
  3. Burmeister M, McInnis MG, Zöllner S. Psychiatric genetics: progress amid controversy. Nat Rev Genet. 2008;9(7):527–40.View ArticlePubMedGoogle Scholar
  4. Freedman R. Schizophrenia. N Engl J Med. 2003;349(18):1738–49.View ArticlePubMedGoogle Scholar
  5. Javitt DC, Spencer KM, Thaker GK, Winterer G, Hajos M. Neurophysiological biomarkers for drug development in schizophrenia. Nat Rev Drug Discov. 2008;7(1):68–83.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Craddock N, O'Donovan MC, Owen MJ. The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J Med Genet. 2005;42(3):193–204.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Consortium SWGotPG. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511(7510):421–7.View ArticleGoogle Scholar
  8. Perez-Reyes E. Molecular characterization of T-type calcium channels. Cell Calcium. 2006;40(2):89–96.View ArticlePubMedGoogle Scholar
  9. Monteil A, Chausson P, Boutourlinsky K, Mezghrani A, Huc-Brandt S, Blesneac I, et al. Inhibition of Cav3.2 T-type calcium channels by its intracellular I-II loop. J Biol Chem. 2015;290(26):16168–76.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Lee SE, Lee J, Latchoumane C, Lee B, Oh SJ, Saud ZA, et al. Rebound burst firing in the reticular thalamus is not essential for pharmacological absence seizures in mice. Proc Natl Acad Sci U S A. 2014;111(32):11828–33.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Shin HS. T-type Ca2+ channels and absence epilepsy. Cell Calcium. 2006;40(2):191–6.View ArticlePubMedGoogle Scholar
  12. Wang CY, Lai MD, Phan NN, Sun Z, Lin YC. Meta-analysis of public microarray datasets reveals voltage-gated calcium Gene signatures in clinical cancer patients. PLoS One. 2015;10(7):e0125766.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Hildebrand ME, David LS, Hamid J, Mulatz K, Garcia E, Zamponi GW, et al. Selective inhibition of Cav3.3 T-type calcium channels by Galphaq/11-coupled muscarinic acetylcholine receptors. J Biol Chem. 2007;282(29):21043–55.View ArticlePubMedGoogle Scholar
  14. Cataldi M, Lariccia V, Marzaioli V, Cavaccini A, Curia G, Viggiano D, et al. Zn(2+) slows down ca(V)3.3 gating kinetics: implications for thalamocortical activity. J Neurophysiol. 2007;98(4):2274–84.View ArticlePubMedGoogle Scholar
  15. Sun H, Varela D, Chartier D, Ruben PC, Nattel S, Zamponi GW, et al. Differential interactions of Na+ channel toxins with T-type Ca2+ channels. J Gen Physiol. 2008;132(1):101–13.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Astori S, Wimmer RD, Prosser HM, Corti C, Corsi M, Liaudet N, et al. The ca(V)3.3 calcium channel is the major sleep spindle pacemaker in thalamus. Proc Natl Acad Sci U S A. 2011;108(33):13823–8.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Manoach DS, Pan JQ, Purcell SM, Stickgold R. Reduced sleep spindles in schizophrenia: a treatable Endophenotype that links risk genes to impaired cognition? Biol Psychiatry. 2016;80(8):599–608.View ArticlePubMedGoogle Scholar
  18. Lencz T, Malhotra AK. Targeting the schizophrenia genome: a fast track strategy from GWAS to clinic. Mol Psychiatry. 2015;20(7):820–6.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Yue J, Liu L, Liu Z, Shu B, Zhang Y. Upregulation of T-type Ca2+ channels in primary sensory neurons in spinal nerve injury. Spine. 2013;38(6):463–70.View ArticlePubMedGoogle Scholar
  20. Andrade A, Hope J, Allen A, Yorgan V, Lipscombe D, Pan JQ. A rare schizophrenia risk variant of CACNA1I disrupts CaV3.3 channel activity. Sci Rep. 2016;6:34233.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Yao YG, Kong QP, Wang CY, Zhu CL, Zhang YP. Different matrilineal contributions to genetic structure of ethnic groups in the silk road region in china. Mol Biol Evol. 2004;21(12):2265–80.View ArticlePubMedGoogle Scholar
  22. Luo M, Zhou X, Ji H, Ma W, Liu G, Dai D, et al. Population difference in the associations of KLOTH promoter Methylation with mild cognitive impairment in Xinjiang Uygur and Han populations. PLoS One. 2015;10(7):e0132156.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Comas D, Calafell F, Mateu E, Perez-Lezaun A, Bosch E, Martinez-Arias R, et al. Trading genes along the silk road: mtDNA sequences and the origin of central Asian populations. Am J Hum Genet. 1998;63(6):1824–38.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Control ISGCatWTC. 2 C: genome-wide association study implicates HLA-C*01:02 as a risk factor at the major histocompatibility complex locus in schizophrenia. Biol Psychiatry. 2012;72(8):620–8.View ArticleGoogle Scholar
  25. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2):263–5.View ArticlePubMedGoogle Scholar
  26. Li Z, Zhang Z, He Z, Tang W, Li T, Zeng Z, et al. A partition-ligation-combination-subdivision EM algorithm for haplotype inference with multiallelic markers: update of the SHEsis. Cell Res. 2009;19(4):519–23. http://Analysis.Bio-x.Cn View ArticlePubMedGoogle Scholar
  27. Shen J, Li Z, Chen J, Song Z, Zhou Z, Shi Y. SHEsisPlus, a toolset for genetic studies on polyploid species. Sci Rep. 2016;6:24095.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Cariaga-Martinez A, Saiz-Ruiz J, Alelu-Paz R. From linkage studies to Epigenetics: what we know and what we need to know in the neurobiology of schizophrenia. Front Neurosci. 2016;10:202.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Xu S, Huang W, Qian J, Jin L. Analysis of genomic admixture in Uyghur and its implication in mapping strategy. Am J Hum Genet. 2008;82(4):883–94.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Shan M, Wang X, Sun G, Ma B, Yao X, Ainy A, et al. A retrospective study of the clinical differences of Uygur breast cancer patients compared to Han breast cancer patients in the Xinjiang region of China. Int J Clin Exp Med. 2014;7(10):3482–90.PubMedPubMed CentralGoogle Scholar
  31. Kokras N, Dalla C. Sex differences in animal models of psychiatric disorders. Br J Pharmacol. 2014;171(20):4595–619.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Ran MS, Mao WJ, Chan CL, Chen EY, Conwell Y. Gender differences in outcomes in people with schizophrenia in rural China: 14-year follow-up study. Br J Psychiatry. 2015;206(4):283–8.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Murbartian J, Arias JM, Perez-Reyes E. Functional impact of alternative splicing of human T-type Cav3.3 calcium channels. J Neurophysiol. 2004;92(6):3399–407.View ArticlePubMedGoogle Scholar
  34. Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43(Database issue):D447–52.View ArticlePubMedGoogle Scholar
  35. Yunker AMR, Sharp AH, Sundarraj S, Ranganathan V, Copeland TD, McEnery MW. Immunological characterization of T-type voltage-dependent calcium channel CaV3.1 (alpha1G) and CaV3.3 (alpha1I) isoforms reveal differences in their localization, expression, and neural development. Neuroscience. 2003;117(2):321–35.View ArticlePubMedGoogle Scholar
  36. Nakao A, Miki T, Shoji H, Nishi M, Takeshima H, Miyakawa T, et al. Comprehensive behavioral analysis of voltage-gated calcium channel beta-anchoring and -regulatory protein knockout mice. Front Behav Neurosci. 2015;9:141.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Lu AT, Dai X, Martinez-Agosto JA, Cantor RM. Support for calcium channel gene defects in autism spectrum disorders. Molecular autism. 2012;3(1):18.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Astori S, Luthi A. Synaptic plasticity at intrathalamic connections via CaV3.3 T-type Ca2+ channels and GluN2B-containing NMDA receptors. J Neurosci. 2013;33(2):624–30.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s) 2017

Advertisement