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. 2016 Feb 25;3:16001. doi: 10.1038/hgv.2016.1

Polymorphisms in the TMEM132D region are associated with panic disorder in HLA-DRB1*13:02-negative individuals of a Japanese population

Mihoko Shimada-Sugimoto 1, Takeshi Otowa 2,*, Taku Miyagawa 1,3, Seik-Soon Khor 1, Yosuke Omae 1, Licht Toyo-oka 1, Nagisa Sugaya 4, Yoshiya Kawamura 5, Tadashi Umekage 6, Akinori Miyashita 7, Ryozo Kuwano 7, Hisanobu Kaiya 8, Kiyoto Kasai 9, Hisashi Tanii 10, Yuji Okazaki 11, Katsushi Tokunaga 1, Tsukasa Sasaki 12
PMCID: PMC4766370  PMID: 27081567

Abstract

We herein report an association between TMEM132D and panic disorder (PD) in a Japanese population, evaluating the effects of HLA-DRB1*13:02, which we previously reported as a susceptibility genetic factor for PD. SNPs in TMEM132D showed significant associations with PD in subjects without HLA-DRB1*13:02 (rs4759997; P=5.02×10−6, odds ratio=1.50) but not in those with the HLA allele. TMEM132D might have a role in the development of PD in subjects without HLA-DRB1*13:02.

Panic disorder (PD) is an anxiety disorder characterized by panic attacks and anticipatory anxiety. PD is relatively common; the lifetime prevalence is reported to be 1–3%.1 According to a previous twin study, the heritability of PD is estimated to be 0.43,2 which suggests that both genetic and environmental factors have a role in the pathogenesis of PD. To date, several studies that applied a candidate-gene approach have reported susceptibility genes of PD, but many of them have not been successfully replicated in subsequent studies.3 Recently, a genome-wide association study (GWAS) of European ancestry identified single-nucleotide polymorphisms (SNPs) in the transmembrane protein 132D gene (TMEM132D) associated with PD.4 This result was supported by a replication study and meta-analyses of European subjects, which confirmed that TMEM132D is a susceptibility gene of PD.5,6 However, in a Japanese GWAS of PD, SNPs in TMEM132D did not show a positive association with PD.7,8

We previously found associations between PD and human leukocyte antigen (HLA), especially the HLA-B and HLA-DRB1 genes, based on pathway analyses using the results from our Japanese GWAS of PD.8 HLA is the human version of the major histocompatibility complex, which presents endogenous antigens to CD8+ and CD4+ T cells. There is a great number of polymorphisms in the HLA genes. HLA genes have been reported to be involved in not only immune-related diseases9 but also several psychiatric disorders.10 We genotyped the HLA-B and HLA-DRB1 genes, and confirmed that the frequency of HLA-DRB1*13:02 was significantly higher in PD patients than in healthy individuals (case positivity: 18.1%; control positivity: 11.5%; P=2.62×10−5; odds ratio (OR)=1.70).11

Previous studies have reported that the genetic factors and clinical features of several HLA-associated diseases differ between HLA allele-positive and -negative patients. Narcolepsy, with and without cataplexy, was associated with HLA-DQB1*06:02,12 and the severity of narcolepsy without cataplexy was higher in HLA-DQB1*06:02-positive patients than in HLA-DQB1*06:02-negative patients.12,13 HLA-B*51 was strongly associated with risk factors for Behçet’s disease,14 and a significant association between one SNP in the ERAP1 locus was observed only in HLA-B*51-positive patients.14 Hence there is a possibility that the genetic backgrounds might differ in PD subjects with or without HLA-DRB1*13:02. To account for these effects of HLA alleles, we focused on a candidate PD gene, TMEM132D, and investigated the SNPs in the TMEM132D region in both HLA-DRB1*13:02-positive and -negative subjects. In this analysis, genotyping data for the SNPs were generated using the Genome-Wide Human SNP Array 6.0 (Affymetrix, Santa Clara, CA, USA). Inclusion criteria for quality control were SNP call rate >0.95, Hardy–Weinberg equilibrium (HWE) test P>0.001, and minor allele frequency (MAF)>0.05. We defined ‘gene region’ as the region located 50 kb upstream to 50 kb downstream of TMEM132D (chr12: 129556271–130388212 (GRCh37/hg19)). The SNP genotype data were subdivided into two data sets, those of HLA-DRB1*13:02-positive subjects (cases: N=103; controls: N=198) and those of HLA-DRB1*13:02-negative subjects (cases: N=438; controls: N=1,341). An imputation analysis was also performed to evaluate the potential association of ungenotyped SNPs in the TMEM132D region of both subgroups. IMPUTE2 software15 was used to estimate SNP genotypes using the reference data set from 1000 Genomes Phase 3 haplotypes.15 We filtered out low-quality imputed SNPs by applying the following conditions: SNP call rate ⩾0.95, HWE test P>0.0001, and probability of imputation certainty ⩾0.9. After filtering, a total of 8,070 SNPs remained for subsequent analysis. Using the genotype data of these SNPs, case–control association tests were performed to examine whether SNPs in TMEM132D showed an association with PD in each subgroup. We set the significance level after multiple testing correction to α=1.26×10−5, which was calculated from 0.05 divided by the number of SNPs (N=3,978) pruned by high linkage disequilibrium (LD; r 2>0.8) with PLINK SNP pruning procedure (window size in SNPs=100, the number of SNPs to shift the window=1).16

In the analysis of the HLA-DRB1*13:02-negative subgroup, nine SNPs in the TMEM132D region showed significant associations, and SNP rs4759997 had the lowest P value (P=5.02×10−6, OR=1.50; Table 1 and Figure 1). In contrast, these SNPs were found to have no association with PD in the HLA-DRB1*13:02-positive group (Table 1 and Supplementary Figure 1). To find other SNPs potentially associated with PD in the HLA-DRB1*13:02-negative group, logistic regression analysis adjusting for the effect of rs4759997 was also performed. The analysis showed that none of the SNPs in the TMEM132D region had an association that reached the threshold level of significance, which suggested that the nominal associations of SNPs in this region were derived from LD with rs4759997 (Supplementary Figure 2).

Table 1. SNPs with P-value <10−4 in the TMEM132D region.

Positiona SNP HLA-DRB1*13:02 negative
 HLA-DRB1*13:02 positive
    MAF
 P-value OR MAF
 P-value OR
    PD Control     PD Control    
130185851 rs1567509 0.283 0.210 1.01×10−5 b 1.49 0.211 0.203 0.820 1.05
130186374 rs7311162 0.279 0.205 5.87×10−6 b 1.50 0.199 0.198 0.975 1.01
130187014 rs264463 0.105 0.064 4.79×10−5 1.73 0.050 0.054 0.854 0.93
130187283 rs1397504 0.281 0.208 6.92×10−6 b 1.49 0.199 0.200 0.989 1.00
130187566 rs264464 0.104 0.063 5.30×10−5 1.73 0.050 0.054 0.854 0.93
130188352 rs264465 0.105 0.063 4.19×10−5 1.73 0.058 0.061 0.908 0.96
130188504 rs7962650 0.279 0.206 7.32×10−6 b 1.49 0.194 0.200 0.876 0.97
130189452 rs67208922 0.104 0.063 5.46×10−5 1.72 0.050 0.054 0.833 0.92
130189478 rs264468 0.104 0.063 5.46×10−5 1.72 0.050 0.054 0.833 0.92
130189868 rs10773696 0.279 0.206 8.65×10−6 b 1.49 0.194 0.200 0.876 0.97
130190130 rs7312812 0.279 0.207 1.19×10−5 b 1.48 0.194 0.199 0.888 0.97
130190285 rs1510820 0.279 0.207 9.10×10−6 b 1.48 0.194 0.200 0.876 0.97
130191111 rs7132791 0.279 0.207 9.10×10−6 b 1.48 0.194 0.200 0.876 0.97
130191332 rs264472 0.104 0.063 5.90×10−5 1.72 0.050 0.056 0.745 0.88
130191567 rs2398467 0.104 0.063 5.90×10−5 1.72 0.049 0.056 0.725 0.87
130191851 rs529395389 0.104 0.063 6.92×10−5 1.71 0.049 0.056 0.716 0.87
130192489 rs588761 0.104 0.063 5.90×10−5 1.72 0.049 0.056 0.716 0.87
130193038 rs4759997 0.282 0.208 5.02×10−6 b 1.50 0.199 0.200 0.989 1.00
130193940 rs663071 0.104 0.064 9.67×10−5 1.69 0.049 0.056 0.716 0.87
130195133 rs67408383 0.104 0.063 6.03×10−5 1.72 0.049 0.056 0.716 0.87
130195225 rs7304093 0.279 0.208 1.31×10−5 1.47 0.194 0.200 0.876 0.97
130199905 rs6486497 0.356 0.286 8.73×10−5 1.38 0.257 0.293 0.356 0.84
130201128 rs10744430 0.366 0.292 3.19×10−5 1.41 0.277 0.296 0.630 0.91
130210550 rs76801035 0.055 0.027 9.36×10−5 2.07 0.025 0.020 0.738 1.21
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Abbreviations: MAF, minor allele frequency; OR, odds ratio; PD, panic disorder; SNP, single-nucleotide polymorphism.

a

Physical position (according to GRCh37/hg19).

b

The significance level after multiple testing correction was set as α=1.26×10−5.

Figure 1.

Figure 1

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Results of the HLA-DRB1*13:02-negative subgroup analysis in the TMEM132D region. Physical positions are based on GRCh37/hg19. The blue line represents the significance threshold (α=1.26×10−5).

A previous study identified two SNPs, rs7309727 and rs11060369, in TMEM132D as susceptibility variants for PD in populations of European ancestry.4 The two SNPs were also associated with higher anxiety and larger amygdala volumes.17 In addition, the risk genotype of rs11060369 was found to enhance TMEM132D mRNA expression in the brain.4 These two SNPs identified in populations of European ancestry were located in intron 3 of TMEM132D, while the SNPs found in our study, rs4759997 and the surrounding SNPs with significant P values, were located in intron 1. The SNP with the lowest P value, rs4759997, was not in LD with either rs7309727 or rs11060369 in individuals of Japanese ancestry (Japanese; rs7309727, r 2=0.001; rs11060369, r 2=0.003), while in individuals of European ancestry, SNP rs4759997 had very low frequency (MAF=0.009) according to HapMap data.18,19 In addition, imputation analysis revealed that the two SNPs, rs7309727 and rs11060369, were not associated with PD in HLA-DRB1*13:02-negative Japanese subjects (rs7309727: case MAF=0.36, control MAF=0.39, P=0.124; rs11060369: case MAF=0.46, control MAF=0.46, P=0.826). Such results, showing that different SNPs in TMEM132D are associated with PD in individual populations, might be derived from differences in the LD structure between the populations of Japanese and European ancestry (Supplementary Figure 3). Therefore, targeted resequencing of this gene is required in a future study.

Our study provides initial evidence that SNPs in TMEM132D show significant associations with PD in a HLA-DRB1*13:02-negative group of Japanese individuals. Specifically, TMEM132D might affect PD in HLA-DRB1*13:02-negative individuals. Further replication studies in independent and larger HLA-typed population samples are required to confirm these associations.

Acknowledgments

We thank all the participants in this study. This study was supported by JSPS KAKENHI (No. 25461723; No. 26461712) and Grants-in-Aid for Scientific Research on Priority Areas ‘Comprehensive Genomics’ and ‘Applied Genomics’ (No. 17019029), and Innovative Areas (No. 22133008), from the Ministry of Education, Culture, Sports, Science and Technology of Japan.

Footnotes

Supplementary Information for this article can be found on the Human Genome Variation website (http://www.nature.com/hgv)

The authors declare no conflict of interest.

Supplemental material
Click here for additional data file. (502KB, doc)

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Data Citations

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Otowa Takeshi.HGV Database. 2015. 10.6084/m9.figshare.hgv.771. [DOI]

Supplementary Materials

Supplemental material
Click here for additional data file. (502KB, doc)

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