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. 2020 Sep 23;11:559210. doi: 10.3389/fpsyt.2020.559210

Solute Carrier Family 1 (SLC1A1) Contributes to Susceptibility and Psychopathology Symptoms of Schizophrenia in the Han Chinese Population

Wenqiang Li 1,2,†, Xi Su 1,2,†, Tengfei Chen 1,2, Zhen Li 1,2, Yongfeng Yang 1,2, Luwen Zhang 1,2, Qing Liu 1,2, Minglong Shao 1,2, Yan Zhang 1,2, Minli Ding 1, Yanli Lu 1, Hongyan Yu 1, Xiaoduo Fan 3, Meng Song 1,2,*, Luxian Lv 1,2,*
PMCID: PMC7538510  PMID: 33173509

Abstract

Objective

Schizophrenia (SZ) is a common and complex psychiatric disorder that has a significant genetic component. The glutamate hypothesis describes one possible pathogenesis of SZ. The solute carrier family 1 gene (SLC1A1) is one of several genes thought to play a critical role in regulating the glutamatergic system and is strongly implicated in the pathophysiology of SZ. In this study, we identify polymorphisms of the SLC1A1 gene that may confer susceptibility to SZ in the Han Chinese population.

Methods

We genotyped 36 single-nucleotide polymorphisms (SNPs) using Illumina GoldenGate assays on a BeadStation 500G Genotyping System in 528 paranoid SZ patients and 528 healthy controls. Psychopathology was rated by the Positive and Negative Symptom Scale.

Results

Significant associations were found in genotype and allele frequencies for SNPs rs10815017 (p = 0.002, 0.030, respectively) and rs2026828 (p = 0.020, 0.005, respectively) between SZ and healthy controls. There were significant associations in genotype frequency at rs6476875 (p = 0.020) and rs7024664 (p = 0.021) and allele frequency at rs3780412 (p = 0.026) and rs10974573 (p = 0.047) between SZ and healthy controls. Meanwhile, significant differences were found in genotype frequency at rs10815017 (p = 0.015), rs2026828 (p = 0.011), and rs3780411 (p = 0.040) in males, and rs7021569 in females (p = 0.020) between cases and controls when subdivided by gender. Also, significant differences were found in allele frequency at rs2026828 (p = 0.003), and rs7021569 (p = 0.045) in males, and rs10974619 in females (p = 0.044). However, those associations disappeared after Bonferroni’s correction (p’s > 0.05). Significant associations were found in the frequencies of four haplotypes (AA, CA, AGA, and GG) between SZ and healthy controls (χ 2 = 3.974, 7.433, 4.699, 4.526, p = 0.046, 0.006, 0.030, 0.033, respectively). There were significant associations between rs7032326 genotypes and PANSS total, positive symptoms, negative symptoms, and general psychopathology in SZ (p = 0.002, 0.011, 0.028, 0.008, respectively).

Conclusion

The present study provides further evidence that SLC1A1 may be not a susceptibility gene for SZ. However, the genetic variations of SLC1A1 may affect psychopathology symptoms.

Keywords: schizophrenia, SLC1A1, single-nucleotide polymorphisms, psychopathology symptoms, association

Introduction

Schizophrenia (SZ) is a complex disease with multiple susceptibility genes (1). The pathogenesis of SZ is unknown, and the glutamate hypothesis is one possible suggestion (2). Previously, our studies have revealed susceptibility genes (e.g., SCL1A6) in the glutamate pathway (3). This suggests that research on the glutamate pathway can provide important evidence for the pathogenesis of SZ. At present, a large number of genome-wide association study (GWAS) have revealed that SZ is a complex disease involving multiple genes (4–8). However, there are no consistent results for the important genetic susceptibility genes of SZ. Therefore, identifying SZ susceptibility genes from numerous candidates is an ongoing challenge.

Glutamate is a key primary excitatory neurotransmitter that plays a critical role in synaptic plasticity, neuronal toxicity, neuronal development, and signal transduction in the brain (9), and glutamatergic dysfunction could be involved in the pathogenesis of SZ (2, 10). The glutamatergic dysfunction hypothesis, supported by previous and our recent studies that involved glutamate receptor genes, such as GRIN2A (11), GRIN2B (12), and NRG1 (13, 14), and genes related to glutamatergic transmission, e.g., SCL1A6 (3) and SLC1A3 (15). Thus, further exploration of the genes of the glutamate pathway is important for the research of susceptibility genes for SZ.

The solute carrier family 1 gene (SLC1A1), a member of the neuronal high-affinity glutamate transporter family, is located at 9p24.2 and codes for the excitatory amino acid transporter (EAAT) 3 (16), and is expressed throughout the central nervous system, especially in the forebrain (17). Previous studies have reported that SLC1A1 is associated with risk of SZ (16, 18–20). Expression changes of SLC1A1 transcripts in SZ have strongly implicated it in SZ pathophysiology (16). Moreover, a 5-generation Palauan family study revealed that an SLC1A1 mutation and co-segregation correlated with the pathophysiology of SZ (20). Recent GWAS also suggested this gene as an SZ susceptibility gene (21). Some studies have reported that SLC1A1 SNP rs2228622 (15) and rs7022369 (19) were susceptibility markers involved in the pathogenesis of SZ. Meanwhile, rs16921385 of SLC1A1 was found to be associated with treatment response to risperidone in SZ (22). Those studies provide more evidence that variation of SLC1A1 may play a critical role in SZ pathogenesis. However, the findings were inconsistent and scarce (15, 19, 23). Therefore, we further explored the association between SLC1A1 and SZ in the Chinese Han population.

Materials and Methods

Subjects

SZ patients were recruited as inpatients of the Second Affiliated Hospital of Xinxiang Medical University (China) from March of 2005 to December of 2008. The diagnostic criteria of SZ were according to the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV). Psychopathology symptoms were measured by Positive and Negative Symptom Scale (PANSS) (24). As in our previous studies (3, 12), family history (FH) was used to explore genetic susceptibility. Inclusion and exclusion criteria of SZ patients and healthy controls were in line with our previous studies (12, 25). Inclusion of SZ: 1) patients with paranoid SZ according to DSM-IV; 2) PANSS ≥ 60; 3) male vs. female = 1:1; 4) Age range from 18 to 55 years old; 5) Han Chinese population. Inclusion of healthy controls: 1) Han Chinese population; 2) male vs. female = 1:1; 3) Age range from 18 to 55 years old. Both SZ and healthy controls were born and lived in the north of Henan Province (China), and unrelated individuals of Chinese Han population. Individuals with other psychiatric disorders, substance dependence, organic brain disease, and severe medical complications were excluded. In the sample collection, the clinical raters had rich experience in administering psychopathological tests and ensure the inter-rater consistency of diagnoses and test results through the training of every 6 months. This study protocol was approved by the Ethics Committee of the Second Affiliated Hospital of Xinxiang Medical University (China). All subjects were informed and signed a written informed consent form.

SNP Selection

In this study, we used the FASTSNP online service (26) to perform functional analysis, and all 36 SNPs covering the genomic region chr9: 4477575 - 4576808. Meanwhile, those SNPs were a minor allele frequency ≥0.05 and highly ranked risk in the Chinese Beijing population at the HapMap database.

eQTL Analysis

Further, explore significant SNPs affect the expression level of SLC1A1 gene in brain tissues according to public eQTL databases (BrainSeq Phase 1: http://eqtl.brainseq.org/phase1/eqtl/; BrainSeq Phase 2: http://eqtl.brainseq.org/phase2/eqtl/; Brain xQTL: http://mostafavilab.stat.ubc.ca/xQTLServe/snp_query/).

Genotyping

Peripheral blood samples were collected from SZ and healthy controls by using evacuated tubes containing EDTA anticoagulant. RelaxGene Blood DNA System (Tiangen Biotech, Beijing, China) was used to extract genomic DNA from white blood cells. The method of genotyping was described in our previous studies that use the Illumina GoldenGate assays on a BeadStation 500G Genotyping System (Illumina, San Diego, CA, USA) (3, 12, 25).

Statistical Analyses

Statistical analyses were in line with and described in our previous studies (3, 12, 25). G*Power software was used to calculate power (http://www.gpower.hhu.de/). The Haploview V4.1 program was used to assess alleles, genotypes, and haplotype frequency (27). One-way analysis of variance (ANOVA) tests were used for association analyses between PANSS scores and different genotype (SPSS version 25.0, SPSS, Inc. Chicago, IL, USA). Statistical significance was set as p < 0.05. Bonferroni correction was used to adjust for multiple testing.

Results

A total of 1,056 subjects, 528 SZ and 528 healthy controls, were included in this study. There were no significant differences in age or gender between cases and healthy controls (p = 0.095, 1.000, respectively) ( Table 1 ).

Table 1.

Demographics of the schizophrenia patients and healthy controls.

Variables SZ HC p
N 528 528
Age (years) 27.32 ± 8.03 27.73 ± 8.01 0.95
Age of Onset (years) 23.47 ± 8.26 NA
Duration of Illness (years) 6.18 ± 5.91 NA
Gender (male/female) 1.00
    Male 264 264
    Female 264 264
Family history
    Yes 82 0
    No 446 528
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The genotypes of 36 SNPs were detected in 1056 samples, with a genotyping success rate of 99.79%. There were significant associations in genotype frequency and allele frequency at rs10815017 (p = 0.002, 0.030; respectively) and rs2026828 (p = 0.020, 0.005, respectively) between cases and healthy controls. Additionally, there were significant associations in genotype frequency at rs6476875 and rs7024664 between cases and healthy controls (p = 0.020, 0.021, respectively), and significant associations in allele frequency at rs3780412 and rs10974573 between cases and healthy controls (p = 0.026, 0.047, respectively). Meanwhile, there was an association trend in genotype frequency at rs7021569 and rs4742007 between SZ and health controls (p = 0.05 for both). Those associations disappeared after Bonferroni’s correction (p’s > 0.05). There were no significant associations in genotype frequency or allele frequency at the other 28 SNPs between the two groups ( Table 2 ).

Table 2.

Genotype and allele frequencies of 36 SNPs in the SLC1A1 gene in SZ patients and healthy controls.

SNP# dbSNP ID Allele(D/d) a SZ HCs P value
N b HWE (p) Genotype Allele MAF Nb HWE (p) Genotype Allele MAF Genotype Allele
DD Dd dd D d DD Dd dd D D
1 rs10815017 G/A 528 0.021 391 119 18 901 155 0.147 528 0.111 348 168 12 864 192 0.182 0.002 (0.08) * 0.030 (1.00) *
2 rs2026828 A/G 528 0.240 204 238 86 646 410 0.388 528 0.716 163 257 108 583 473 0.448 0.020 (0.73) * 0.005 (0.22) *
3 rs6476875 A/G 528 0.001 353 143 32 849 207 0.196 526 0.906 316 184 26 816 236 0.224 0.020 (0.71) * 0.111
4 rs7024664 T/A 527 0.000 258 174 95 690 364 0.345 523 0.000 283 132 108 698 348 0.333 0.021 (0.76) * 0.540
5 rs7021569 C/G 528 0.877 309 189 30 807 249 0.236 526 0.003 295 180 51 770 282 0.268 0.050 0.088
6 rs4742007 A/G 528 0.041 131 287 110 549 507 0.480 527 0.240 139 250 138 528 526 0.499 0.051 0.384
7 rs3780412 A/G 528 0.832 323 181 24 827 229 0.217 527 0.665 292 198 37 782 272 0.258 0.078 0.026 (0.94) *
8 rs10974573 A/C 528 0.364 338 173 17 849 207 0.196 528 0.748 369 146 13 884 172 0.163 0.124 0.047 (1.00) *
9 rs7860087 G/C 528 0.555 387 132 9 906 150 0.142 528 0.375 416 103 9 935 121 0.115 0.099 0.059
10 rs2039291 C/A 528 0.529 174 252 102 600 456 0.432 528 0.994 148 263 117 559 497 0.471 0.186 0.073
11 rs2228622 G/A 528 0.858 320 183 25 823 233 0.221 528 0.605 297 195 36 789 267 0.253 0.200 0.082
12 rs10739062 G/C 528 0.359 246 222 60 714 342 0.324 528 0.799 219 240 69 678 378 0.358 0.235 0.098
13 rs10974619 G/A 528 0.522 464 61 3 989 67 0.063 528 0.353 448 75 5 971 85 0.080 0.329 0.130
14 rs12682807 A/C 527 0.805 292 202 33 786 268 0.254 528 0.857 316 184 28 816 240 0.227 0.334 0.147
15 rs2072657 A/C 526 0.107 254 234 38 742 310 0.295 527 0.613 285 202 40 772 282 0.268 0.124 0.166
16 rs16921385 A/G 528 0.177 377 143 8 897 159 0.151 528 0.413 366 144 18 876 180 0.170 0.134 0.213
17 rs10491731 A/C 528 0.687 309 192 27 810 246 0.233 528 0.087 300 186 42 786 270 0.256 0.175 0.224
18 rs3780413 G/C 528 0.089 276 222 30 774 282 0.267 528 0.558 304 190 34 798 258 0.244 0.130 0.231
19 rs188537 C/A 528 0.628 396 124 8 916 140 0.133 528 0.194 410 114 4 934 122 0.116 0.368 0.235
20 rs10814995 A/C 528 0.369 265 212 51 742 314 0.297 528 0.676 242 234 52 718 338 0.320 0.343 0.258
21 rs3087879 G/C 528 0.219 422 97 9 941 115 0.109 526 0.697 405 112 9 922 130 0.124 0.491 0.293
22 rs301432 A/T 528 0.540 327 174 27 828 228 0.216 527 0.427 308 194 25 810 244 0.231 0.421 0.390
23 rs12378107 G/C 506 0.776 396 104 6 896 116 0.115 499 0.101 385 102 12 872 126 0.126 0.345 0.423
24 rs3780411 G/C 528 0.077 131 284 113 546 510 0.483 527 0.632 135 258 134 528 526 0.499 0.213 0.460
25 rs10814991 A/G 528 0.201 152 276 100 580 476 0.451 527 0.292 162 271 94 595 459 0.435 0.760 0.480
26 rs7021409 G/A 528 0.661 267 214 47 748 308 0.292 527 0.643 274 209 44 757 297 0.282 0.884 0.616
27 rs7032326 A/G 528 0.138 213 232 83 658 398 0.377 528 0.893 212 244 72 668 388 0.367 0.581 0.653
28 rs1471786 G/A 528 0.820 152 265 111 569 487 0.461 527 0.807 156 264 107 576 478 0.454 0.939 0.724
29 rs301430 G/A 528 0.211 213 255 60 681 375 0.355 528 0.584 218 238 72 674 382 0.362 0.420 0.751
30 rs6476879 C/A 528 0.284 212 254 62 678 378 0.358 527 0.312 216 251 60 683 371 0.352 0.957 0.775
31 rs10758624 G/A 528 0.247 347 167 14 861 195 0.185 528 0.086 353 150 25 856 200 0.189 0.131 0.780
32 rs10758632 C/G 528 0.437 197 244 87 638 418 0.396 527 0.267 195 241 91 631 423 0.401 0.943 0.797
33 rs3780415 A/G 528 0.671 373 140 15 886 170 0.161 527 0.527 376 136 15 888 166 0.157 0.966 0.827
34 rs7045401 A/C 528 0.277 196 261 71 653 403 0.382 528 0.889 203 250 75 656 400 0.379 0.791 0.893
35 rs301431 C/G 528 0.678 284 209 35 777 279 0.264 527 0.380 281 213 33 775 279 0.265 0.946 0.979
36 rs972519 G/C 528 0.547 452 72 4 976 80 0.076 528 0.547 452 72 4 976 80 0.076 1.000 1.000
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SZ, schizophrenia; HCs, healthy controls.

a

Major and minor alleles are denoted by D and d, respectively.

b

Number of samples with successful genotype.

*p value of Bonferroni correction.

The bold value indicates a value less than 0.05.

When the subjects were divided by sex, we found significant differences in genotype frequency at rs10815017 (p = 0.015), rs2026828 (p =0.011), and rs3780411 (p = 0.040) in males, and rs7021569 in females (p = 0.020) between cases and controls. Also, significant differences were found in allele frequency at rs2026828 and rs7021569 in males (p = 0.003, 0.045, respectively), and rs10974619 in females (p = 0.044) ( Supplementary Table 1 ).

We also observed significant differences in genotype frequency at rs10814991 (p = 0.015) and rs1471786 (p = 0.046) between patients with and without family histories (FH) of SZ. A difference trend was found in genotype frequency at rs3780411 between FH (+) and FH (−) in SZ but was not significant ( Supplementary Table 2 ).

As shown in Figure 1 , 9 LD blocks and 32 haplotypes were formed from 36 SNPs. There were significant associations in the frequencies of four haplotypes (AA, CA, AGA, and GG) between SZ and healthy control (χ 2 = 3.974, 7.433, 4.699, 4.526, p = 0.046, 0.006, 0.030, 0.033, respectively) ( Table 3 ).

Figure 1.

Figure 1

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Haplotype block structure of the SLC1A1 gene in both SZ patients and HCs. The index association SNP is represented by a diamond. The colors of the remaining SNPs (circles) indicate LD with the index SNP based on pairwise r2 values from our data.

Table 3.

Associated haplotype frequencies of 36 SNPs in the SLC1A1 gene between SZ and healthy controls.

Block Haplotype Frequencies SZ Frequencies HC Frequencies Chi Square P Value
1 GA 0.544 0.545 0.543 0.017 0.896
GC 0.380 0.379 0.382 0.018 0.893
CA 0.076 0.076 0.076 0.001 1.000
2 GGG 0.523 0.525 0.521 0.029 0.864
GGA 0.187 0.189 0.184 0.099 0.753
AGG 0.163 0.171 0.154 1.217 0.270
ACG 0.123 0.110 0.137 3.443 0.064
3 AA 0.534 0.512 0.556 3.974 0.046
CA 0.306 0.317 0.294 1.361 0.243
AG 0.157 0.168 0.147 1.681 0.195
4 CA 0.541 0.512 0.571 7.433 0.006
GA 0.249 0.264 0.233 2.688 0.101
CG 0.207 0.220 0.193 2.326 0.127
5 AAG 0.576 0.545 0.606 7.940 0.005
CGG 0.240 0.251 0.229 1.405 0.236
AGA 0.162 0.180 0.145 4.699 0.030
AGG 0.016 0.017 0.014 0.276 0.600
6 GA 0.509 0.500 0.517 0.580 0.447
CA 0.254 0.241 0.266 1.708 0.191
GG 0.236 0.255 0.216 4.526 0.033
7 AC 0.457 0.453 0.461 0.134 0.714
GC 0.278 0.282 0.275 0.147 0.702
GG 0.264 0.265 0.264 0.001 0.981
8 CG 0.525 0.522 0.529 0.108 0.743
AG 0.354 0.352 0.357 0.050 0.823
CC 0.120 0.126 0.115 0.692 0.406
9 CAGG 0.502 0.495 0.510 0.477 0.490
CAGG 0.502 0.495 0.510 0.477 0.490
CTCG 0.217 0.227 0.207 1.185 0.276
AACG 0.121 0.112 0.130 1.509 0.219
CACC 0.112 0.120 0.104 1.241 0.265
CACG 0.038 0.038 0.037 0.003 0.959
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Block 1: rs972519- rs7045401; Block 2: rs7021409-rs7860087-rs10758624; Block 3: rs10814995-rs16921385;

Block 4: rs7021569-rs6476875; Block 5: rs10491731-rs2026828-rs1081507; Block 6: rs3780413-rs3780412;

Block 7: rs1471786-rs301431; Block 8: rs6476879-rs12378107; Block 9: rs188537-rs301432-rs3780411-rs3087879.

The bold value indicates a value less than 0.05.

Further, we make association analysis in six significant SNPs of the SLC1A1 gene in the PGC samples, including European and East Asian population ( Supplementary Table 3 ). We found significant associations at rs10974573 in European population (p = 0.008, OR=1.031). Meanwhile, there no significant associations at six SNPs affect the expression level of SLC1A1 gene in main brain tissues, including frontal cortex and hippocampus (p’s > 0.05, Supplementary Table 4 ).

There were significant associations between rs7032326 genotypes and PANSS total, positive symptoms, negative symptoms, or general psychopathology in SZ (p = 0.002, 0.011, 0.028, 0.008, respectively). There were significant associations between rs7860087 genotypes and PANSS total, negative symptoms, or general psychopathology in SZ (p = 0.011, 0.015, 0.041, respectively). Genotypes of rs2039291 and rs4742007 were associated with positive symptoms (p = 0.029, 0.039, respectively). Genotypes of rs301430 were associated with negative symptoms (p = 0.031) ( Table 4 ).

Table 4.

Association analyses between SNPs and sub-scores of PANSS in SZ patients.

SNP Genotype N PANSS Total Positive Symptoms Negative Symptoms General Psychopathology
Mean SD Mean SD Mean SD Mean SD
rs7032326 AA 98 92.86 23.57* 26.17 6.46* 22.20 8.33* 44.48 13.34*
AG 107 83.62 18.88 23.93 5.80 19.86 6.94 39.82 11.40
GG 32 97.50 23.35 26.50 7.18 23.09 7.24 47.91 12.94
rs7860087 GG 188 87.74 20.15* 24.86 5.87 20.69 7.07* 42.20 11.96*
CG 46 96.93 28.01 26.76 8.06 23.74 9.54 46.43 15.00
CC 3 70.67 5.86 23.33 3.79 19.33 5.51 28.00 5.29
rs2039291 AA 49 90.82 22.71 26.71 6.47* 20.04 7.51 44.06 13.33
AC 119 88.27 20.48 23.95 5.84 21.45 7.54 42.87 11.97
CC 69 90.04 24.53 26.30 6.78 21.83 8.00 41.91 13.67
rs4742007 AA 69 86.28 21.11 23.75 6.35* 21.20 7.72 41.32 11.71
AG 107 92.40 23.25 26.19 6.49 21.85 7.64 44.36 13.60
GG 61 87.33 20.78 25.13 5.89 20.31 7.67 41.89 12.17
rs301430 AA 28 84.82 15.29 26.25 5.69 18.36 6.91* 40.21 7.98
AG 106 92.20 24.02 25.33 6.66 22.52 7.76 44.35 14.09
GG 103 87.56 21.42 24.80 6.22 20.77 7.55 42.00 12.21
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*p < 0.05, compared with other genotypes; LSD tests, Bonferroni.

Discussion

We investigated SLC1A1 mutations associated with the pathogenesis and psychopathology symptoms of SZ in a Han Chinese population. None significant differences were found in genotype and allele frequencies of rs10815017 and rs2026828 between SZ patients and healthy controls after Bonferroni’s correction. Therefore, our study suggests that SLC1A1 may be not a susceptibility gene for SZ. However, we found that rs7032326 genotypes were associated with psychopathology symptoms of SZ.

Previous studies reported the decreased EAAT3 (encoded product of SLC1A1) transcript expression (28), and increased expression of transcripts encoding EAAT1 and EAAT2 (29) in SZ. These findings suggested that the glutamate receptors and related molecules were abnormally expressed in glutamatergic synapses in SZ. In addition, expression of SLC1A1 was decreased following chronic antipsychotic treatment in animal models. Some studies have also reported that SNP rs2228622 and rs7022369 in the SLC1A1 gene were susceptibility gene sites for SZ (15, 19). Moreover, the SNP rs16921385, located in an intron of SLC1A1, was found to be associated with risperidone treatment response (22, 30). Therefore, SLC1A1 variation was associated with the pathogeny of SZ. However, there were little studies to explore this association (15, 19, 23) and the mechanism of variation in SLC1A1 still unknown.

In the present study, there were no significant association with SZ at SNPs rs10815017, rs6476875, rs7024664, and rs10974573. These SNPs are novel gene site findings that have not been reported previously. Further, there had a consistent finding in East Asian population of PGC samples. However, significant association was found at rs10974573 in European population indicated that this SNP may be a susceptibility gene site for SZ. Our study also found that rs3087879, rs301430, rs972519, rs10814991, rs7032326, rs7860087, rs3780415, rs3780413, and rs2072657 were not the susceptibility gene sites for SZ, a result that is consistent with previous reports (15, 19, 23). Meanwhile, we found SNPs rs2026828 and rs3780412 were not susceptibility markers for SZ, which is consistent with previous studies (15, 23). Previous studies reported rs2228622 (15) and rs10814995 (19) of SLC1A1 were susceptibility markers for SZ in a Japanese population, which is inconsistent with our present finding. However, our finding for rs2228622 is in line with research in the Chinese population (23).

In current, there are only three studied (15, 19, 23) reported SNPs of SLC1A1 in SZ. Thus, our study provides further evidences for the susceptibility of SLC1A1 in SZ. As is well known, SZ is highly heterogeneous at genetic and symptomatic levels. Haplotypes of AA, CA, AGA, and GG were also associated with SZ and provided further evidence for the susceptibility of SLC1A1 in SZ. Compared with previous studies (15, 19, 23), our study has the following innovation and advantages: 1) SZ patient selection: only paranoid SZ patients were included and examined; 2) all subjects were living in the north Henan provinces of China and belonged to the same population group, this ensure the consistency of genetic background; 3) more SNP sites (36 SNPs) were tested than previous studies were including 8 SNPs (15), 19 SNPs (19), and 4 SNPs (23). Therefore, our studies were not only reduced the influence of phenotypic heterogeneity, improved the numbers of SNPs for examination.

SZ is characterized by positive symptoms, negative symptoms, disorganization of thoughts, behaviors, and cognitive deficits. Our previous studies observed the genetic basis for SZ psychopathology symptoms, such as GRIN2B was related to cognition deficit symptoms (12), and CDNF2 was related to negative symptoms (25). However, there are few studies regarding the association between SZ psychopathology symptoms and SLC1A1 (15, 19, 23). In this study, we found SNP rs7032326 was related to positive symptoms, negative symptoms, and general psychopathology. In addition, another four SNPs (rs7860087, rs2039291, rs4742007, and rs301430) were also related to clinical subtype symptoms. Although these SNPs were not the susceptibility markers for SZ, our finding also provided some evidence for the genetic basis for SZ psychopathology symptoms.

The present study also had some limitations. First, independent samples are needed to verify the finding. Second, the sample size that included PANSS scores was small and insufficient, and should be expanded to further explore the association between genotypes and psychopathology symptoms.

Conclusion

In conclusion, our study provides further evidence that SLC1A1 may be not a susceptibility gene for SZ in Chinese Han population. These suggesting the variation of SLC1A1 may be not a genetic mechanism of SZ. However, the genetic variations of SLC1A1 may affect psychopathology symptoms. Therefore, further studies need to explore other susceptibility genes of SZ.

Data Availability Statement

The original contributions presented in the study are publicly available. This data can be found here: https://www.oebiotech.com/Article/slc1a1jyyj.html.

Ethics Statement

The studies involving human participants were reviewed and approved by Ethics Committee of the Second Affiliated Hospital of Xinxiang Medical University (China). The patients/participants provided their written informed consent to participate in this study.

Author Contributions

Author LL designed the study protocol. Authors TC, YY, YZ, MD, YL, and HY conducted sample selection and data management. Authors XS, ZL, LZ, QL, MLS, and XF undertook the genotyping identify and statistical analysis, and authors WL and MS wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.

Funding

This work was supported in part by the National Natural Science Foundation of China (81671330 and 81971252 to LL), Medical Science and Technology Research Project of Henan Province (2018020373 to HY), National Key Research and Development Program of China (2016YFC1307001), High Scientific and Technological Research Fund of Xinxiang Medical University (2017ZDCG-04 to LL), and the support project for the Disciplinary group of Psychiatry and Neuroscience, Xinxiang Medical University.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors thank the patients, their families, and the healthy volunteers for their participation, and the physicians who collect clinical data and blood samples in the Second Affiliated Hospital of Xinxiang Medical University.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2020.559210/full#supplementary-material

Click here for additional data file. (24.4KB, docx)

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Data Availability Statement

The original contributions presented in the study are publicly available. This data can be found here: https://www.oebiotech.com/Article/slc1a1jyyj.html.

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