Literature DB >> 25470816

Possible single-nucleotide polymorphism loci associated with systemic sclerosis susceptibility: a genetic association study in a Chinese Han population.

Chang Shu1, Wei Du1, Xiaofei Mao1, Yun Li1, Qin Zhu1, Wei Wang1, Nan Wu2, Xuming Mao3, Hongzhong Jin1, Qiuning Sun1.   

Abstract

OBJECTIVE: The aim of this study was to confirm the association of RHOB and FAM167A-BLK gene polymorphisms with susceptibility to systemic sclerosis (SSc) in a Chinese Han population.
METHODS: A total of 248 SSc patients and 251 healthy controls of Chinese Han ethnicity, which visited the department of dermatology of Peking Union Medical College Hospital, were included in the study. Six selected single nucleotide polymorphisms (SNPs) in the RHOB and FAM167A-BLK regions were selected as markers and were genotyped using a MassARRAY system, which is based on the matrix-assisted laser desorption/ionization time of flight mass spectrometry technique.
RESULTS: Three SNPs in the coding regions of the RHOB and FAM167A-BLK genes displayed an association with SSc: (1) rs1062292T, which is a newly discovered SNP in the RHOB gene (P = 0.03, odds ratio [OR] = 1.62, 95% confidence interval (CI) = 1.05-2.50), (2) rs2736340T (P = 0.03, OR = 1.39, 95%CI = 1.03-1.85), and (3) rs13277113A (P = 0.04, OR = 1.34, 95%CI = 1.01-1.76), both in the FAM167A-BLK gene. Our results support previous findings that vaiants in the RHOB and FAM167A-BLK genes may be associated with susceptibility to SSc. However, the loci of the SNPs in RHOB region that displayed an association with SSc are quite different from the loci which were identified in studies of Caucasian populations.
CONCLUSION: Our results confirm that RHOB and FAM167A-BLK polymorphisms exist in Chinese Han SSc patients. Therefore, variants of the RHOB and FAM167A-BLK genes are promising genetic markers for SSc.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25470816      PMCID: PMC4254283          DOI: 10.1371/journal.pone.0113197

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Scleroderma or systemic sclerosis (SSc) is a chronic, connective tissue disease characterized by widespread fibrosis of the skin and internal organs, small-vessel vasculopathy, and immune dysregulation with or without production of autoantibodies. SSc patients have markedly shorter life span than that of the age- and sex-matched general population. In a recently published meta-analysis, the overall pooled standardized mortality ratio of patients with SSc was 3.53 [1]. During the past few years, knowledge of the genetic basis of SSc has increased rapidly because of large and well-powered candidate gene association studies [2], [3] as well as genome-wide association studies (GWASs) [4]–[6]. Currently, it is widely accepted that different genetic factors contribute to the development and prognosis of SSc. Further, GWASs have been a useful tool for studying the genetic basis of autoimmune and other complex diseases. Radstake et al. [4] performed the first SSc GWAS in a Caucasian population, which also represented the first large-scale GWAS in an SSc cohort. In a recent GWAS in a French Caucasian SSc discovery cohort [5] 17 single-nucleotide polymorphisms (SNPs) displaying tier two associations were selected for follow-up in independent cohorts. Three of the selected SNPs were located within the human leukocyte antigen (HLA) region corresponding to the HLA-DQB1 and PSORS1C1 genes. The remaining SNPs were located in six independent non-HLA loci. After the replication step, six SNPs located in three loci (TNIP1, RHOB, and PSORS1C1) were proposed as novel SSc risk factors. However, later, in a large independent replication study by a Spanish group, TNIP1, but not RHOB and PSORS1C1, was confirmed to be associated with SSc [7]. The associations identified in a single GWAS, despite crossing established statistical significance thresholds, tend to display inflated effect sizes. This effect size is called the winner's curse, and it affects the predictive ability of the discovered associations and the estimation of the risk variance based on the associations. Thus, it is essential to replicate these studies in independent comparable populations for firmly establishing a genotype-phenotype association. On the other hand, China has a large SSc patient population, and genotyping data is lacking for this population. Peking Union Medical College Hospital (PUMCH) is believed to have the largest SSc patient group in China, and a large portion of this group regularly visits the dermatology department. We collected SSc data for more than three years, including data on two major subgroups: limited (lcSSc) and diffuse systemic sclerosis (dcSSc), the latter of which has the worse prognosis. Therefore, we performed a replication study in a previously unexamined SSc population to confirm the results of previous GWAS and candidate gene association studies. RHOB is the ras homolog gene family member B that regulates protein signaling and intracellular protein trafficking. It was first reported in a GWAS study, but signal of association was weaker at this locus [5]. Replication denied that RHOB was associated with SSc in Caucasian population [7]. We were wondering if such association could be examined in another ethnic group such as Chinese population. Also as a small gene, only several tag-SNPs would be chosen, and this would be easier for us to start such an exploration with a limited expense. FAM167A (family with sequence similarity 167 member A) and BLK (B lymphoid tyrosine kinase) also known as C8orf13-BLK, was identified as a susceptibility locus for SSc and analyzed in different SSc cohorts. In the first report of BLK influence in SSc genetic predisposition, the combined analysis of Caucasian US and European cohorts revealed the association of the minor allele of two genetic variants (rs13277113 and rs2736340) with increased susceptibility to SSc, and specifically with the lcSSc and Anti-centromere antibody (ACA) positive subsets [3]. Analysis of rs13277113 polymorphism in a Japanese cohort showed association of this marker with the whole disease independently of the subtype or autoantibody subgroup [2]. The differences of minor allele frequency (MAF) in the two loci between the two ethnic groups drove us to put the two loci into our study.

Patients and Methods

Subjects

This study was approved by the Ethics Committee of Peking Union Medical College Hospital. Both patients and controls were included in the study after providing written informed consent. DNA was obtained from patients and controls using standard methods. We performed a case-control association study in 248 SSc patients from the outpatient dermatology and rheumatology departments at the PUMCH. Two hundred and fifty-two controls were recruited from the physical examination center of PUMCH. All subjects were of Chinese Han ethnicity and from the mainland of China. All the patients fulfilled the 1980 American College of Rheumatology classification criteria for SSc. Among the 248 patients, 109 (44%) were dcSSc and 139(56%) were lcSSc. The control population consisted of unrelated healthy individuals who were from the same geographical regions as the SSc patients and who were matched by age group and sex with the SSc patients, as shown in Table 1.
Table 1

Demographic information of the patients and controls.

FeaturesSSc patientsHealthy controls
Patients248252
Age <181010
Age 18–44131133
Age 45–598385
Age >602424
Average age (year)42.742.7
Age range (year)14–8120–77
Male (%)11.311.1
Diffuse (%)44.0-

Genotyping

The rs1062292, rs13021401, rs342054, and rs342070 alleles were selected as genetic markers of RHOB. rs342070 and rs13021401 were previously identified in a GWAS [5], and the other two were selected via tagger SNP analysis implemented in HaploView 4.2 [8] at an r2 threshold of 0.80 and an LOD threshold for multi-marker tests of 3.0. rs2736340 and rs13277113 in FAM167A-BLK have been previously reported to be associated with SSc in a Japanese population [2], [3]; therefore, we decided to confirm whether the same association exists in a Chinese population. Genomic DNA was extracted from the peripheral blood of each subject. The six SNPs were genotyped using a matrix-assisted laser desorption/ionization time of flight mass spectrometry genotyping assay using the MassARRAY platform from Sequenome following the manufacturer's suggestions (Foster City, CA, USA). The genotyping call rate was larger than 95% for all six SNPs.

Statistical analysis

SHEsis [9] was used for the individual population association tests (significance was calculated using 2×2 contingency tables and Fisher's exact test or a χ2-test when necessary).SHEsis is a web-based platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphic loci designed by YongYong Shi from Shanghai Jiao Tong University. The software calculations are based on an expectation-maximization algorithm [9], [10]. The odds ratios (OR) and their 95% confidence intervals (CI) were also reported by the software. All cohorts were in Hardy–Weinberg equilibrium (HWE) at a significance level of 0.05 for all the included SNPs. Power was calculated using the software Power Calculator for Genetic Studies 2006 and assuming an additive model at the 5% significance level. For RHOB, with an OR of 1.5, taking into account the expected frequency of the rare allele of rs1062292, the set has a power of 78%. Similarly, for rs13021401, the set has a power of 78%; for rs342054, the set has a power of 75%; for rs342070, the set has a power of 79%. For FAM167A-BLK, with an OR of 1.5, the set for rs2736340 has a power of 79%, and the set for rs13277113 has a power of 79%.

Results

Frequencies of Alleles and Genotypes in Patients and Controls

The genotype distribution of the six SNPs was in HWE in the controls (P>0.05). The results of the association are shown in Table 2. As the data indicate, the rs1062292T allele showed a higher prevalence in SSc patients (91.9%) than in controls (87.6%), thereby indicating a statistically significant association between the rs1062292T allele and SSc risk (P = 0.03, OR = 1.62, 95%CI = 1.05–2.50) in the χ2 test. The rs2736340T allele was associated with higher risk of SSc in patients (74.9%) than in controls (68.3%, P = 0.03, OR = 1.39, 95%CI = 1.03–1.85). Similarly, the rs13277113A allele was associated with higher risk of SSc in patients (72.6%) than in controls (66.5%, P = 0.04, OR = 1.34, 95%CI = 1.01–1.76). No significant differences were observed between the SSc patients and controls for the other SNPs. For the limited sample size and small number of SNPs which were tested, also the power is also not as high as a usual study requested, no further correction for multiple testing has been performed, and therefore less false negative would not be dropped. That is the reason of unadjusted P-value is presented here. Linkage disequilibrium analysis was also made among SNPs that were tested in the RHOB region using HaploView 4.2. Between rs1062292 found here and both two SNPs previoiusly reported by Allanore et al. showed no significant linkage (D′ = 0.31, r2 = 0.03).
Table 2

Frequencies of Alleles in Patients and Controls.

Gene regionSNPMinor AlleleCases n = 238Controls n = 245 P valueOR (95%CI)
RHOB rs1062292G37(0.081)57(0.124) 0.03 T: 1.62 (1.05–2.50)
RHOB rs13021401C162(0.352)174(0.378)0.41
RHOB rs342054T23(0.049)25(0.052)0.86
RHOB rs342070A178(0.376)187(0.383)0.81
FAM167A-BLK rs2736340C111(0.251)144(0.317) 0.03 T: 1.39 (1.03–1.85)
FAM167A-BLK rs13277113G130(0.274)163(0.335) 0.04 A: 1.34 (1.01–1.76)

Discussion

Allanore et al. identified RHOB to be associated with SSc susceptibility in a GWAS aimed at identifying loci associated with SSc risk. [5] We confirmed the association of RHOB with SSc, but the loci identified are slightly different from the ones identified by Allanore et al. However, in a replication study of the same GWAS in Caucasians [7], association between RHOB and SSc was not observed. This interesting contradiction may be explained by the genetic heterogeneity among human races. rs1062292, which displayed an association with SSc in our study, is an SNP located in the 3′-untranslated region (3′-UTR) of RHOB. This region is commonly involved in post-transcriptional regulation. The exact roles that this SNP plays require further exploration. The RhoB protein mediates apoptosis in neoplastically-transformed cells after DNA damage [11]. RHOB is not essential for development but affects cell adhesion and growth factor signaling in transformed cells [12].This gene is also required for stability and nuclear trafficking of AKT1/AKT, which promote endothelial cell survival during vascular development and may play a role in SSc pathogenesis [13]. The SNP identified in this study has not been reported previously. It appears that the polymorphism at this locus is distinctive in Chinese SSc patients. Concerning the limited sample size of this study, larger case-control group and denser SNP genotyping are required before association with SSc can be definitely made. FAM167A (previously referred to as C8orf13)-BLK is a region in chromosome 8. BLK encodes a nonreceptor tyrosine kinase of the src family of proto-oncogenes, which are typically involved in cell proliferation and differentiation. The protein plays a role in B-cell receptor signaling and B-cell development [14], [15]. The association of SNPs in the FAM167A-BLK region with systemic lupus erythematosus (SLE) has been demonstrated in Caucasians and Asians. The SNP in this region was first found to be associated with SLE through a GWAS [16]. Previous findings indicate that the rs2736340C and rs13277113A alleles are associated not only with SLE but also with SSc in European and Japanese populations [2], [3] and that the SNP polymorphisms of FAM167A-BLK region are a common genetic risk factor for both SLE and SSc. The association of these two SNPs with SSc was also confirmed in our study. It was also confirmed in this study that both the allele frequency for rs2736340T and rs13277113A was 74.9% and 72.6% in cases, and 68.3% and 66.5% in controls respectively, indicating that the high LD between the two associated SNPs located near the 5′ ends of FAM167A and BLK. The similar result has been reported by Gourh P et al. Interestingly, rs2736340T and rs13277113A which identified as the minor allele in Caucasians are the major allele in Asians but give similar strengths of associations. In addition, polymorphisms in this region have been determined to be associated with other immune diseases such as Kawasaki disease, Sjögren's syndrome, and rheumatoid arthritis (RA) [17]–[19]. These results suggest that the B-cell receptor signaling pathway may play an important role in the pathogenesis of multiple immune diseases. Other genes such as STAT4 and loci in HLA regions which associated with SSc in Caucasian and Japanese population were also confirmed in Chinese population [20], [21]. The genes that associated with SSc are mostly involved in immune regulation and inflammation. Many of these genes also have been found to be associated with other autoimmune diseases such as SLE and RA [22]. The use of the new genetic technologies such as immunochip might be more efficient and replicable to fully characterize the genetic component of SSc in a new ethnic group[23]. Hopefully, genetic screening of the patients might provide valuable help in understanding this complex disease.

Conclusion

Our results confirm that RHOB and FAM167A-BLK polymorphisms exist in Chinese Han SSc patients, which indicates that RHOB and FAM167A-BLK variants may be associated with susceptibility to SSc. However, the SNPs in RHOB region that displayed an association with SSc are quite different from those in Caucasian populations. Moreover, we observed a new SNP, rs1062292T, which was significantly associated with the higher risk of SSc in Chinese Han populations. This information may help us to identify future molecular targets for disease diagnosis and therapy.
  23 in total

1.  RhoB is required to mediate apoptosis in neoplastically transformed cells after DNA damage.

Authors:  G J Cerniglia; E J Bernhard; G C Prendergast
Journal:  Proc Natl Acad Sci U S A       Date:  2001-05-15       Impact factor: 11.205

2.  RhoB controls Akt trafficking and stage-specific survival of endothelial cells during vascular development.

Authors:  Irit Adini; Isaac Rabinovitz; Jing Fang Sun; George C Prendergast; Laura E Benjamin
Journal:  Genes Dev       Date:  2003-11-01       Impact factor: 11.361

3.  Haploview: analysis and visualization of LD and haplotype maps.

Authors:  J C Barrett; B Fry; J Maller; M J Daly
Journal:  Bioinformatics       Date:  2004-08-05       Impact factor: 6.937

4.  SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci.

Authors:  Yong Yong Shi; Lin He
Journal:  Cell Res       Date:  2005-02       Impact factor: 25.617

5.  A partition-ligation-combination-subdivision EM algorithm for haplotype inference with multiallelic markers: update of the SHEsis (http://analysis.bio-x.cn).

Authors:  Zhiqiang Li; Zhao Zhang; Zangdong He; Wei Tang; Tao Li; Zhen Zeng; Lin He; Yongyong Shi
Journal:  Cell Res       Date:  2009-04       Impact factor: 25.617

6.  RhoB is dispensable for mouse development, but it modifies susceptibility to tumor formation as well as cell adhesion and growth factor signaling in transformed cells.

Authors:  A X Liu; N Rane; J P Liu; G C Prendergast
Journal:  Mol Cell Biol       Date:  2001-10       Impact factor: 4.272

7.  Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX.

Authors:  Geoffrey Hom; Robert R Graham; Barmak Modrek; Kimberly E Taylor; Ward Ortmann; Sophie Garnier; Annette T Lee; Sharon A Chung; Ricardo C Ferreira; P V Krishna Pant; Dennis G Ballinger; Roman Kosoy; F Yesim Demirci; M Ilyas Kamboh; Amy H Kao; Chao Tian; Iva Gunnarsson; Anders A Bengtsson; Solbritt Rantapää-Dahlqvist; Michelle Petri; Susan Manzi; Michael F Seldin; Lars Rönnblom; Ann-Christine Syvänen; Lindsey A Criswell; Peter K Gregersen; Timothy W Behrens
Journal:  N Engl J Med       Date:  2008-01-20       Impact factor: 91.245

8.  Structure and developmental regulation of the B-lymphoid tyrosine kinase gene blk.

Authors:  S M Dymecki; P Zwollo; K Zeller; F P Kuhajda; S V Desiderio
Journal:  J Biol Chem       Date:  1992-03-05       Impact factor: 5.157

9.  Association of the C8orf13-BLK region with systemic sclerosis in North-American and European populations.

Authors:  Pravitt Gourh; Sandeep K Agarwal; Ezequiel Martin; Dipal Divecha; Blanca Rueda; Haley Bunting; Shervin Assassi; Gene Paz; Sanjay Shete; Terry McNearney; Hilda Draeger; John D Reveille; T R D J Radstake; Carmen P Simeon; Luis Rodriguez; Esther Vicente; Miguel A Gonzalez-Gay; Maureen D Mayes; Filemon K Tan; Javier Martin; Frank C Arnett
Journal:  J Autoimmun       Date:  2009-09-30       Impact factor: 7.094

10.  Mimicry of pre-B cell receptor signaling by activation of the tyrosine kinase Blk.

Authors:  Theresa Tretter; Ashley E Ross; Dominic I Dordai; Stephen Desiderio
Journal:  J Exp Med       Date:  2003-12-08       Impact factor: 14.307

View more
  5 in total

Review 1.  Genetics of systemic sclerosis.

Authors:  Lara Bossini-Castillo; Elena López-Isac; Maureen D Mayes; Javier Martín
Journal:  Semin Immunopathol       Date:  2015-06-02       Impact factor: 9.623

2.  Survival rate, causes of death, and risk factors in systemic sclerosis: a large cohort study.

Authors:  Xue Li; Yu-Quan Qian; Na Liu; Rong Mu; Yu Zuo; Guo-Chun Wang; Yuan Jia; Zhan-Guo Li
Journal:  Clin Rheumatol       Date:  2018-09-18       Impact factor: 2.980

Review 3.  Rho GTPase signaling in rheumatic diseases.

Authors:  Ruijie Zeng; Zewei Zhuo; Yujun Luo; Weihong Sha; Hao Chen
Journal:  iScience       Date:  2021-12-14

4.  BLK polymorphisms and expression level in neuromyelitis optica spectrum disorder.

Authors:  Bo-Wen Yin; Bin Li; Arshad Mehmood; Congcong Yuan; Shuang Song; Ruo-Yi Guo; Lu Zhang; Tianzhao Ma; Li Guo
Journal:  CNS Neurosci Ther       Date:  2021-10-12       Impact factor: 5.243

5.  B-cell lymphocyte kinase polymorphisms rs13277113, rs2736340, and rs4840568 and risk of autoimmune diseases: A meta-analysis.

Authors:  Chang Zeng; Cheng Fang; Hong Weng; Xiaoqing Xu; Tianyang Wu; Wenhua Li
Journal:  Medicine (Baltimore)       Date:  2017-09       Impact factor: 1.889

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.