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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Autoimmun. Author manuscript; available in PMC Mar 1, 2011.
Published in final edited form as:
PMCID: PMC2821978

Association of the C8orf13-BLK Region with Systemic Sclerosis in North-American and European Populations



Genetic studies in the systemic sclerosis (SSc), an autoimmune disease that clinically manifests with dermal and internal organ fibrosis and small vessel vasculopathy, have identified multiple susceptibility genes including HLA-class II, PTPN22, IRF5, and STAT4 which have also been associated with other autoimmune diseases, such as systemic lupus erythematosus (SLE). These data suggest that there are common autoimmune disease susceptibility genes. The current report sought to determine if polymorphisms in the C8orf13-BLK region (chromosome 8p23.1-B lymphoid tyrosine kinase), which is associated with SLE, are associated also with SSc.


Two variants in the C8orf13-BLK region (rs13277113 & rs2736340) were tested for association with 1050 SSc cases and 694 controls of North Americans of European descent and replicated in a second series 589 SSc cases and 722 controls from Spain.


The “T” allele at rs2736340 variant was associated with SSc in both the U.S. and Spanish case-control series (P=6.8×10−5, OR 1.27, 95%CI 1.1–1.4). The “A” allele at rs13277113 variant was associated with SSc in the U.S. series only (P=3.6×10−4, OR 1.32, 95%CI 1.1–1.6) and was significant in the combined analyses of the two series (P=2.0×10−3; OR 1.20, 95%CI 1.1–1.3). Both variants demonstrated an association with the anti-centromere antibody (P=2.2×10−6 and P=5.5×10−4, respectively) and limited SSc (P=3.3×10−5 and P=2.9×10−3, respectively) in the combined analysis. Peripheral blood gene expression profiles suggest that B-cell receptor and NFκB signaling are dysregulated based on the risk haplotype of these variants.


We identify and replicate the association of the C8orf13-BLK region as a novel susceptibility factor for SSc, placing it in the category of common autoimmune disease susceptibility genes.

Keywords: Scleroderma, Systemic Sclerosis/SSc, Polymorphism/SNP, BLK, C8orf13, Anti- Topoisomerase-I, Anti-Centromere, Genetics, Autoantibody, rs13277113, rs2736340


Scleroderma (systemic sclerosis, SSc) is a chronic, multisystem autoimmune disease clinically characterized by progressive fibrosis of the skin and internal organs. Pathologically, SSc exhibits three cardinal features: inflammation and autoimmunity, vasculopathy and excessive extracellular matrix production and deposition. How the disease process is triggered, remains to be established, but current paradigms point towards immune dysregulation as a central process in the pathogenesis of SSc.

Multiple lines of evidence, in patients as well as animal models of dermal fibrosis, point to dysregulation of the immune system and autoimmunity in the pathogenesis of SSc. Alterations in T-cell profiles and cytokines have been demonstrated.[1] In addition, the B-cell lineage is implicated.[1;2] CD19 deficient mice have reduced dermal fibrosis after subcutaneous bleomycin administration.[3] The presence of multiple SSc-associated autoantibodies, most commonly anti-centromere (ACA), anti-topoisomerase I (ATA), and anti-RNA polymerase III (ARA), has been well described in SSc patients and provides indirect evidence for the importance of the B-cell lineage in SSc.[46] Interestingly, the SSc-associated autoantibodies correlate with distinct clinical subsets characterized by extent of cutaneous involvement and pattern of organ involvement.[7;8] For example, pulmonary arterial hypertension is more common in patients with anti-centromere antibodies (ACA), pulmonary fibrosis is more common in patients with anti-topoisomerase antibodies (ATA), and scleroderma renal crisis is more common in patients with anti-RNA polymerase III antibodies (ARA).[7]

Recently, several genetic polymorphisms have been associated with SSc in susceptibility.[915] Many of these genes are susceptibility factors for other autoimmune diseases suggesting that they are common autoimmune disease susceptibility genes. These data support the paradigm of common dysregulated pathways across multiple autoimmune diseases. Interestingly, some of these genetic variants associated with SSc are associated with susceptibility to developing SSc, while others increase risk only in specific autoantibody subsets seen in SSc.[9;10]

Two genome wide association studies in systemic lupus erythematosus (SLE) have implicated the C8orf13-BLK (B lymphoid tyrosine kinase gene) region of chromosome 8p23.1 as a susceptibility locus for SLE.[16;17] These findings were further replicated in a Japanese population.[18] B lymphoid kinase (Blk), encoded by the BLK gene is a member of the Src family kinases (SFKs) which includes Blk, Lck, Fyn, Lyn, c-Src, c-Yes, Fgr, and Hck.[19] Blk is the only SFK that is exclusively expressed in B cells and thymocytes and not in mature T cells.[2022] Blk transduces signals downstream of the B cell receptor (BCR) and plays a role in BCR signaling and B cell development.[23;24] B cell development is dependent upon the activation of the transcription factor nuclear factor κB (NFκB) by SFKs (Blk, Fyn, Lyn).[23] The C8orf13 gene is ubiquitously expressed but its exact function is currently unknown.

Given the importance of B-cells and autoantibodies in the pathogenesis of SSc as well as SLE and the emerging paradigm that autoimmune diseases may share common susceptibility genes, the current study sought to investigate the potential association of the C8orf13-BLK region variants with SSc in two large, independent, and well-described case-control series. Herein we demonstrate a significant association of both C8orf13-BLK region variants with susceptibility to SSc and more strongly with the anti-centromere antibody subset of SSc in both case-control series. We observe a dysregulation of the B- cell receptor and NFκB signaling based on the risk haplotype of these variants in peripheral blood gene expression arrays.


SSc Patients and Controls

In this study, we combined 1050 patients of North Americans of European descent with SSc and 694 unrelated healthy controls of North Americans of European descent from the Scleroderma Family Registry and DNA Repository, the Genetics versus Environment in Scleroderma Outcomes Study (GENISOS), and from SSc patients evaluated in the University of Texas Rheumatology Division, dating from 1986 to present, as previously described.[8;25] For a replication cohort, an independent Spanish case-control series of 589 SSc patients and 722 healthy controls was included to confirm the genetic association. The control population was matched by age, sex and ethnicity with the SSc patients group, as previously described.[15] All SSc patients fulfilled American College of Rheumatology (ACR) preliminary criteria for disease classification or had at least 3 of the 5 CREST features (Calcinosis, Raynaud’s phenomenon, Esophageal dysfunction, Sclerodactyly, and Telangiectasias).[9;10;26;27] Patients were classified as limited (cutaneous changes distal to the elbow) and diffuse (cutaneous changes proximal to the elbow) as defined by Leroy et al.[28] Clinical and serologic characteristics of the SSc patients are presented in Table 1. All study subjects provided written informed consent and the study was approved by the institutional review board (IRB) of the University of Texas Health Science Center at Houston and the corresponding IRB in Spain.

Table 1
Clinical and Serologic Characteristics of Patients with Systemic Sclerosis and Gender Distribution in Controls*

Autoantibody Analysis

All SSc patients were tested for anti-nuclear antibodies using indirect immunofluorescence (IIF) and HEp- 2 cells as antigen substrate (Antibodies Inc., Davis, CA). Titers of 1/80 and higher were considered positive. Anti-centromere antibodies (ACA) were determined by their distinctive IIF pattern on HEp-2 cells. Autoantibodies to topoisomerase I (ATA) were determined by passive immunodiffusion against calf thymus extract using a commercially available kit (Inova Diagnostics, San Diego, CA) and read on an Electronic RID Plate Reader AD001.c (The Binding Site, San Diego, CA) and magnified visual inspection. Anti-RNA polymerase III antibodies (ARA) were determined using a commercially available enzyme-linked immunoassay (EIA) kit (MBL Co. Ltd, Nagoya, Japan). For ARA, the cutoff was defined as 2.5 standard deviations above the mean of 40 healthy controls.

SNP selection and genotyping

The two C8orf13-BLK gene region variants (rs13277113 and rs2736340) showing the strongest association with SLE in a genome wide study were selected for genotyping(13). Genomic DNA was extracted from peripheral blood according to the manufacturer’s protocol with the PureGene genomic DNA isolation kit (Gentra Systems). The two variants were genotyped using a predesigned TaqMan SNP genotyping assay from Applied Biosystems (ABI, Foster City, CA). PCR amplification was performed and the genotypes were automatically attributed by measuring the allele-specific fluorescence in the ABI 7900HT system (ABI). Automated allele calling was performed by allelic discrimination plots using SDS 2.3 software from ABI. Standard control DNA (CEPH 1347-02 from ABI) was added in replicates to minimize error and check genotyping quality.

Gene Expression Array of Peripheral White Blood Cells

Blood samples were drawn directly into PAXgene tubes (PreAnalytix, Franklin Lakes, NJ). The protocol was modified by adding RNase inhibitor to the Paxgene tubes during thawing and total RNA was isolated according to manufacturer’s protocol utilizing PAXgene RNA kit. The RNA quality and yield were assessed by Agilent 2100 Bioanalyzer (Agilent Technologies, Inc., Palo Alto, CA) and NanoDrop ND-1000 Spectrophotometer (NanoDrop Technologies, Wilmington, DE). Two hundred nanograms of total RNA were amplified and purified using Illumina Total Prep RNA Amplification Kit (Applied Biosystems/Ambion, Austin, TX). The amplified cRNA was hybridized on Illumina Human Ref-8 v2 arrays and the data were extracted with Illumina Beadstudio software suite (Illumina Inc, SanDiego, CA).

Gene Expression Array Data Analysis

The initial analysis was performed with Illumina’s Beadstudio. Raw data were also analyzed in BRB- ArrayTools version 3.7 (NCI) developed by Dr. Richard Simon and BRB-ArrayTools Development Team (National Cancer Institute, USA). Any gene whose signal detection p-value was not significantly different from the negative controls (p<0.05) was removed from the analysis. Data were normalized using the median over the entire array. A gene was defined as differentially expressed when the significance level for the comparison was p≤0.05. BRB array tools was used for class comparison analysis and these sets of differentially expressed genes were modeled in Ingenuity Pathway Analysis (IPA) (Ingenuity Systems, www.ingenuity.com).

Statistical analysis

Statistical analyses were performed using SAS 9.1.3 (SAS Institute Inc., Cary, NC, USA) software. Allelic and genotypic associations were calculated using the standard Pearson’s chi-square test or, when appropriate, Fisher’s exact test. Odds ratios and 95% confidence intervals were calculated. The two series were also combined and tested for association using Mantel Haenszel test to increase the power to detect an association and reduce chances of false positive associations. Significance was calculated at alpha value ≤ 0.05. Logistic regression analysis was performed to identify significant independent risk factors and to evaluate the role of the genetic variability of C8orf13-BLK region polymorphisms in SSc and its autoantibody and phenotypic subsets. Measures of pairwise LD were determined using Haploview (Whitehead Institute for Biomedical Research, Cambridge, MA).


SNP Genotyping, Linkage Disequilibrium, and Haplotype Block Structure

The C8orf13-BLK gene region variants (rs13277113-rs2736340) were in Hardy-Weinberg Equilibrium in both the North American and Spanish control samples. CEPH DNA samples were used as controls to improve the accuracy of allele calling on Taqman 5′ genotyping assay. The SNP call rate for both the SNPs in both the case-control series was greater than 97%. Pairwise LD was calculated by both D′ and r2 between rs13277113-rs2736340 variants in both the control series. The SNPs demonstrated strong LD in both the North American and Spanish healthy control series (r2 =0.97 and r2 =0.86, respectively).

C8orf13-BLK gene region variant – rs2736340 Association Analysis

Case-control comparisons of the rs2736340 variant for association with SSc and its subsets were performed in the North American series (Table 2). The “TT” genotype frequency was significantly increased in the SSc cases (9.8%) as compared to controls (7.4%) with a P=1.4×10−2. The “TT” genotype was significantly increased in the limited skin subset and the ACA autoantibody subset of SSc. The “T” allele was increased in SSc cases (29.5%) as compared to controls (24.9%) with a P=3.0×10−3, OR 1.26 [95% CI 1.1–1.5]. The “T” allele was significantly increased in both the limited and diffuse skin subsets of SSc but had the highest increase in the ACA autoantibody subset.

Table 2
Genotypic and Allelic Distribution of the rs2736340 variant in North American and Spanish SSc patients and healthy controls*

The independent case-control series of Spanish samples also demonstrated an increase in the “TT” genotype in SSc cases (7.3%) as compared to controls (5.3%) with a P=3.0×10−2. The “T” allele frequency was also increased in the Spanish SSc cases (26.9%) as compared to the controls (P=8.0×10−3, OR 1.27. 95 %CI 1.1–1.5). and in both the limited skin subset and ACA autoantibody subset of SSc (P=4.2×10−3, OR 1.36, 95%CI 1.1–1.7 and P=4.6×10−3, OR 1.42, 95% CI 1.1–1.8, respectively). The combined Mantel- Haenszel analysis of the two case-control series confirmed the association with SSc. This analysis also emphasized the strongest association of this variant with the ACA-positive subset of SSc. Logistic regression analysis revealed an additive model as the best fit model. The “TT” and “CT” genotypes were independent risk factors for SSc after controlling for the confounding effects of gender and the two case-control series with an OR 1.71 [95% CI 1.2–2.4] and OR 1.31 [95% CI 1.1–1.5], respectively (Figure 1D,E,F). The ACA positive autoantibody subset of SSc demonstrated the highest risk by logisitic regression analysis with an OR=2.27 [95%CI 1.5–3.5] for “TT” genotype and an OR=1.6 [95%CI 1.2–2.0] for “CT” genotype. These data demonstrate a role of rs2736340 variant in the risk for SSc.

Figure 1
Estimated risk of rs2736340 (A,B,C) and rs13277113 (D,E,F) variants in SSc patients versus controls, by logistic regression analysis. A,D- North American samples controlling for the confounding effects of gender. B,E- Spanish samples controlling for the ...

C8orf13-BLK gene region variant - rs13277113 Association Analysis

On genotypic comparisons of the rs13277113 variant with SSc and its subsets the “AA” genotype frequency was significantly increased in the SSc cases (10.3%) as compared to controls (6.6%) in the North American series with a p=2.3×10−3 (Table 3). The “AA” genotype was significantly increased in the limited and diffuse skin subsets and also in the ACA and ARA autoantibody subsets of SSc. No significant association was observed with the ATA autoantibody subset of SSc with this variant. The “A” allele was present in 30.1% of SSc cases as compared to 24.6% in controls with a P=3.6×10−4, OR 1.32 [95% CI 1.1– 1.6]. The “A” allele was also significantly increased in the limited and diffuse skin subsets. Both genotypic and allelic comparisons revealed no statistically significant association with SSc or any of its subsets for the rs13277113 variant in the Spanish series. However, on combining the two series by Mantel-Haenszel analysis the association with SSc was reproduced (genotypic-P=2.5×10−3, OR 1.25 [95% CI 1.1–1.4] and allelic- P=2.0×10−3, OR 1.20 [95% CI 1.1–1.3]). This analysis also highlighted the strongest association of this variant with ACA-positive subset of SSc. Logistic regression analysis showed an additive model as the best fit model. The “AA” and “AG” genotypes were independent risk factors for SSc after controlling for the confounding effects of gender and the two case-control series with an OR 1.57 [95% CI 1.1–2.2] and OR 1.23 [95% CI 1.04–1.5], respectively (Figure 1A,B,C).

Table 3
Genotypic and Allelic Distribution of the rs13277113 variant in North American and Spanish SSc patients and healthy controls*

Functional role of C8orf13-BLK gene region variants

To further elucidate the role of C8orf13-BLK gene region variants in SSc, we analyzed the whole blood gene expression profile of SSc patients from our gene expression data repository. Gene expression and genotyping data were available on 15 SSc patients of North American European descent. Eight of these were heterozygous for the rs13277113-rs2736340 variants (“AG”/”CT”) and the other seven carried the wildtype genotype (“GG”/”CC”). A comparison of SSc patients with heterozygous genotype versus wildtype genotype demonstrated 582 differentially expressed transcripts at P<0.05. The top 20 genes differentially expressed are ranked according to p-value in Table 4A. The top ten up regulated transcripts by fold change included FLT3 which is involved in B cell lymphopoiesis and the top ten down regulated transcripts included SH2D2A, which is involved in normal differentiation and activation of T cells (Table 4B). The BLK mRNA transcript level was −1.14 fold lower in the heterozygotes as compared to wildtypes but the difference was not significant at P<0.05. Similarly, the C8orf13 mRNA transcript were increased 1.13 fold in the heterozygotes as compared to wildtypes but the difference was not significant at P<0.05 either. Modeling of these data in the IPA canonical pathway knowledge base revealed the B cell receptor signaling pathway as the second most significantly dysregulated pathway with a P=1.59×10−14 (Figure 2A, ,3A)3A) in heterozygous individuals. The NFκB signaling pathway was the most significantly dysregulated with a P=9.5×10−8 in the IPA molecular toxicology knowledge base (Figure 2B, ,3B).3B). These data suggest a role for BLK in regulating BCR signaling and downregulation of NFκB pathway based on the risk heterozygote haplotype of C8orf13-BLK.

Figure 2
Top Pathways which discriminate SSc peripheral blood cells stratified by C8orf13-BLK variants modeling on the IPA canonical pathway knowledge base (A) and the IPA molecular toxicology knowledge base (B). Comparisons between the rs2736340-rs13277113 heterozygote ...
Figure 3
Comparison of gene expression in peripheral blood cells stratified by the C8orf13-BLK variants rs2736340-rs13277113 heterozygote versus homozygote in SSc demonstrates alterations in B Cell Receptor Signaling Pathway (A) and NFκB Signaling Pathway ...


Herein, we report the association of SSc with two variants (rs13277113 and rs2736340) in the C8orf13- BLK gene region in case-control subjects from North Americans of European descent and confirm this association in a Spanish case-control series. Studying a combined 1,639 SSc patients and 1,416 healthy controls we were able to demonstrate an additive effect of these variants for susceptibility to SSc. Furthermore, pathway analysis using the whole blood mRNA gene expression arrays highlighted dysregulation of BCR signaling and NFκB signaling based on the risk haplotype of the C8orf13-BLK gene region.

The rs13277113 and rs2736340 variants are located between C8orf13 and BLK genes, which have reading frames in the opposite directions. Previous work in SLE has shown that these two variants are not in LD with any known coding-region variants on either C8orf13 or BLK(13). In our combined analyses of two independent cohorts we find associations of both the “T” allele of the rs2736340 variant and the “A” allele of the rs13277113 variant. After controlling for gender and the case-control series an additive model was the best fit model and the ACA subset of SSc showed the strongest risk for susceptibility to SSc. These findings place C8orf13 and BLK gene region in the category of common autoimmunity susceptibility genes due to their association with SLE, rheumatoid arthritis and now SSc. This group of common autoimmune disease genes also includes PTPN22, IRF5, and STAT4.[15;17;29] These genetic data combined with immune studies that show the presence of a type I interferon signature as well as the importance of B-cells and autoantibodies in both SSc and SLE support the hypothesis that there are also overlapping immune alterations between SSc and SLE.[3036]

BLK expression is highly specific to B cell lineage. It is involved in both BCR signaling and B cell development. In murine models, blk transcripts are expressed in pro-B, pre-B, mature-B cell line but are undetectable at the plasma cell stage.[19] The rs13277113 variant in the SLE study showed an increased expression of C8orf13 and decreased expression of BLK mRNA based on the risk haplotype.[16] In the current report, we were able to compare only the heterozygotes with the wildtypes and observed similar trends with an increased C8orf13 expression and a decreased BLK expression based on the risk haplotype, albeit not statistically significant. BLK is downstream of the BCR but its cellular functions are poorly defined. Deficiency in blk, fyn and lyn (SFK deficient) reduces the number of pre-B cells and a substantial reduction in peripheral B cell numbers. It is intriguing that we observed that the BCR signaling pathway was the second most significantly dysregulated pathway based on comparing heterozygotes with the wildtypes on the pathway analysis. Another report suggests that BLK is a growth inhibitor signaling molecule and prevents apoptosis.[37] Consistent with his, in the current report “Death receptor signaling” was the fourth most dysregulated pathway on comparing heterozygotes with the wildtypes. Finally, SFKs play an important role in pre-BCR mediated NFκB activation and B cell development.[23] In B cells, the NFκB family of transcription factors are important regulators of immune and inflammatory responses.[38] SFK deficient mice completely abrogated pre-BCR mediated NFκB activation.[23] Thus, this dysregulation in BCR and NFκB signaling may alter the delicate immune balance and tolerance and predispose to autoimmunity. Interestingly, NFκB signaling pathway was the most dysregulated toxicological pathway on comparing heterozygotes with the wildtypes in the current report. Furthermore, all the functional NFκB transcription factors (p50, p52, RelA, RelB, c-Rel) were downregulated in the heterozygotes. Together the whole genome microarray expression data support a role for the C8orf13-BLK region variants in the regulation of B-cell function.

In summary, our study is the first to report an association of the C8orf13-BLK region variants with SSc in two independent case-control series comprised of North Americans of European descent and Spanish SSc patients. These genetic variations may lead to the development of a more sophisticated molecular classification of SSc. Although additional genetic studies of SSc will be useful for replication of our data in other ethnic groups with SSc, resolving this issue will likely require comprehensive functional evaluation of these polymorphisms. Lastly, our data support the emerging paradigm that similar alterations in immune pathways may be involved in the pathogenesis of multiple autoimmune diseases.


This study was supported by the NIH/NIAMS Center of Research Translation (CORT) in Scleroderma (P50AR054144) (Dr. Arnett ), the NIH/NIAMS Scleroderma Family Registry and DNA Repository (N01-AR-0-2251) (Dr Mayes), UTHSC-H Center for Clinical and Translational Sciences (Houston CTSA Program) (NIH/NCRR 3UL1RR024148) (Dr. Arnett). This study was also supported by grants SAF2006-00398, CTS-1180 and GENFER (Dr. Martin). B.R. is supported by the I3P CSIC program funded by the “Fondo Social Europeo”. T.R. was sponsored by an unrestricted Grant from the “LandelijkKatholiekReuma Centrum (LKRC)”, and VENI and VIDI laureate from the Dutch association of Research (NOW)


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