Literature DB >> 27081567

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

Mihoko Shimada-Sugimoto1, Takeshi Otowa2, Taku Miyagawa3, Seik-Soon Khor1, Yosuke Omae1, Licht Toyo-Oka1, Nagisa Sugaya4, Yoshiya Kawamura5, Tadashi Umekage6, Akinori Miyashita7, Ryozo Kuwano7, Hisanobu Kaiya8, Kiyoto Kasai9, Hisashi Tanii10, Yuji Okazaki11, Katsushi Tokunaga1, Tsukasa Sasaki12.   

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.

Entities:  

Year:  2016        PMID: 27081567      PMCID: PMC4766370          DOI: 10.1038/hgv.2016.1

Source DB:  PubMed          Journal:  Hum Genome Var        ISSN: 2054-345X


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 diseases[9] 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 software[15] 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 SNPHLA-DRB1*13:02 negative
HLA-DRB1*13:02 positive
  MAF
P-valueORMAF
P-valueOR
  PDControl  PDControl  
130185851rs15675090.2830.2101.01×10−5 b 1.490.2110.2030.8201.05
130186374rs73111620.2790.2055.87×10−6 b 1.500.1990.1980.9751.01
130187014rs2644630.1050.0644.79×10−5 1.730.0500.0540.8540.93
130187283rs13975040.2810.2086.92×10−6 b 1.490.1990.2000.9891.00
130187566rs2644640.1040.0635.30×10−5 1.730.0500.0540.8540.93
130188352rs2644650.1050.0634.19×10−5 1.730.0580.0610.9080.96
130188504rs79626500.2790.2067.32×10−6 b 1.490.1940.2000.8760.97
130189452rs672089220.1040.0635.46×10−5 1.720.0500.0540.8330.92
130189478rs2644680.1040.0635.46×10−5 1.720.0500.0540.8330.92
130189868rs107736960.2790.2068.65×10−6 b 1.490.1940.2000.8760.97
130190130rs73128120.2790.2071.19×10−5 b 1.480.1940.1990.8880.97
130190285rs15108200.2790.2079.10×10−6 b 1.480.1940.2000.8760.97
130191111rs71327910.2790.2079.10×10−6 b 1.480.1940.2000.8760.97
130191332rs2644720.1040.0635.90×10−5 1.720.0500.0560.7450.88
130191567rs23984670.1040.0635.90×10−5 1.720.0490.0560.7250.87
130191851rs5293953890.1040.0636.92×10−5 1.710.0490.0560.7160.87
130192489rs5887610.1040.0635.90×10−5 1.720.0490.0560.7160.87
130193038rs47599970.2820.2085.02×10−6 b 1.500.1990.2000.9891.00
130193940rs6630710.1040.0649.67×10−5 1.690.0490.0560.7160.87
130195133rs674083830.1040.0636.03×10−5 1.720.0490.0560.7160.87
130195225rs73040930.2790.2081.31×10−5 1.470.1940.2000.8760.97
130199905rs64864970.3560.2868.73×10−5 1.380.2570.2930.3560.84
130201128rs107444300.3660.2923.19×10−5 1.410.2770.2960.6300.91
130210550rs768010350.0550.0279.36×10−5 2.070.0250.0200.7381.21

Abbreviations: MAF, minor allele frequency; OR, odds ratio; PD, panic disorder; SNP, single-nucleotide polymorphism.

Physical position (according to GRCh37/hg19).

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

Figure 1

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.
  19 in total

Review 1.  The quest for better understanding of HLA-disease association: scenes from a road less travelled by.

Authors:  Joseph Holoshitz
Journal:  Discov Med       Date:  2013-09       Impact factor: 2.970

2.  A haplotype map of the human genome.

Authors: 
Journal:  Nature       Date:  2005-10-27       Impact factor: 49.962

Review 3.  Genome-wide association studies: findings at the major histocompatibility complex locus in psychosis.

Authors:  Aiden Corvin; Derek W Morris
Journal:  Biol Psychiatry       Date:  2013-09-29       Impact factor: 13.382

4.  TMEM132D, a new candidate for anxiety phenotypes: evidence from human and mouse studies.

Authors:  A Erhardt; L Czibere; D Roeske; S Lucae; P G Unschuld; S Ripke; M Specht; M A Kohli; S Kloiber; M Ising; A Heck; H Pfister; P Zimmermann; R Lieb; B Pütz; M Uhr; P Weber; J M Deussing; M Gonik; M Bunck; M S Kebler; E Frank; C Hohoff; K Domschke; P Krakowitzky; W Maier; B Bandelow; C Jacob; J Deckert; S Schreiber; J Strohmaier; M Nöthen; S Cichon; M Rietschel; T Bettecken; M E Keck; R Landgraf; B Müller-Myhsok; F Holsboer; E B Binder
Journal:  Mol Psychiatry       Date:  2010-04-06       Impact factor: 15.992

5.  A review and meta-analysis of the genetic epidemiology of anxiety disorders.

Authors:  J M Hettema; M C Neale; K S Kendler
Journal:  Am J Psychiatry       Date:  2001-10       Impact factor: 18.112

6.  Comparison of clinical characteristics among narcolepsy with and without cataplexy and idiopathic hypersomnia without long sleep time, focusing on HLA-DRB1( *)1501/DQB1( *)0602 finding.

Authors:  Taeko Sasai; Yuichi Inoue; Yoko Komada; Tatsuki Sugiura; Eisuke Matsushima
Journal:  Sleep Med       Date:  2009-05-01       Impact factor: 3.492

7.  Genome-wide association study of panic disorder in the Japanese population.

Authors:  Takeshi Otowa; Eiji Yoshida; Nagisa Sugaya; Shin Yasuda; Yukika Nishimura; Ken Inoue; Mamoru Tochigi; Tadashi Umekage; Taku Miyagawa; Nao Nishida; Katsushi Tokunaga; Hisashi Tanii; Tsukasa Sasaki; Hisanobu Kaiya; Yuji Okazaki
Journal:  J Hum Genet       Date:  2009-01-23       Impact factor: 3.172

Review 8.  The genetic basis of panic disorder.

Authors:  Hae-Ran Na; Eun-Ho Kang; Jae-Hon Lee; Bum-Hee Yu
Journal:  J Korean Med Sci       Date:  2011-05-18       Impact factor: 2.153

9.  Replication and meta-analysis of TMEM132D gene variants in panic disorder.

Authors:  A Erhardt; N Akula; J Schumacher; D Czamara; N Karbalai; B Müller-Myhsok; O Mors; A Borglum; A S Kristensen; D P D Woldbye; P Koefoed; E Eriksson; E Maron; A Metspalu; J Nurnberger; R A Philibert; J Kennedy; K Domschke; A Reif; J Deckert; T Otowa; Y Kawamura; H Kaiya; Y Okazaki; H Tanii; K Tokunaga; T Sasaki; J P A Ioannidis; F J McMahon; E B Binder
Journal:  Transl Psychiatry       Date:  2012-09-04       Impact factor: 6.222

10.  Higher anxiety and larger amygdala volumes in carriers of a TMEM132D risk variant for panic disorder.

Authors:  J Haaker; T B Lonsdorf; K A Raczka; M-L Mechias; N Gartmann; R Kalisch
Journal:  Transl Psychiatry       Date:  2014-02-04       Impact factor: 6.222

View more
  7 in total

1.  Efficient multiplexed genome engineering with a polycistronic tRNA and CRISPR guide-RNA reveals an important role of detonator in reproduction of Drosophila melanogaster.

Authors:  Cristin Chon; Grace Chon; Yurika Matsui; Huiqing Zeng; Zhi-Chun Lai; Aimin Liu
Journal:  PLoS One       Date:  2021-01-14       Impact factor: 3.240

Review 2.  Roles, molecular mechanisms, and signaling pathways of TMEMs in neurological diseases.

Authors:  Qinghong Chen; Junlin Fang; Hui Shen; Liping Chen; Mengying Shi; Xianbao Huang; Zhiwei Miao; Yating Gong
Journal:  Am J Transl Res       Date:  2021-12-15       Impact factor: 4.060

3.  TMEM132: an ancient architecture of cohesin and immunoglobulin domains define a new family of neural adhesion molecules.

Authors:  Luis Sanchez-Pulido; Chris P Ponting
Journal:  Bioinformatics       Date:  2018-03-01       Impact factor: 6.937

4.  The mediating role of transmembrane protein 132D methylation in predicting the occurrence of panic disorder in physical abuse.

Authors:  Qianmei Yu; Chiyue Wang; Huazheng Xu; Yun Wu; Huachen Ding; Na Liu; Ning Zhang; Chun Wang
Journal:  Front Psychiatry       Date:  2022-08-11       Impact factor: 5.435

5.  The Influence of HLA Alleles on the Affective Distress Profile.

Authors:  Mihaela Laura Vică; Cristian Delcea; Gabriela Alina Dumitrel; Mihaela Elvira Vușcan; Horea Vladi Matei; Cosmin Adrian Teodoru; Costel Vasile Siserman
Journal:  Int J Environ Res Public Health       Date:  2022-10-02       Impact factor: 4.614

6.  Genetic Biomarkers of Panic Disorder: A Systematic Review.

Authors:  Artemii Tretiakov; Alena Malakhova; Elena Naumova; Olga Rudko; Eugene Klimov
Journal:  Genes (Basel)       Date:  2020-11-04       Impact factor: 4.096

7.  The C. elegans homolog of human panic-disorder risk gene TMEM132D orchestrates neuronal morphogenesis through the WAVE-regulatory complex.

Authors:  Xin Wang; Wei Jiang; Shuo Luo; Xiaoyu Yang; Changnan Wang; Bingying Wang; Yongjun Dang; Yin Shen; Dengke K Ma
Journal:  Mol Brain       Date:  2021-03-16       Impact factor: 4.041

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.