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Journal of Scleroderma and Related Disorders logoLink to Journal of Scleroderma and Related Disorders
. 2020 Apr 19;5(3):192–201. doi: 10.1177/2397198320913695

Genetics of systemic sclerosis

Yuki Ishikawa 1,2, Chikashi Terao 2,3,4,✉
PMCID: PMC8922623  PMID: 35382527

Abstract

Systemic sclerosis is an autoimmune disease characterized by generalized fibrosis in connective tissues and internal organs as consequences of microvascular dysfunction and immune dysfunctions, which leads to premature death in affected individuals. The etiology of systemic sclerosis is complex and poorly understood, but as with most autoimmune diseases, it is widely accepted that both environmental and genetic factors contribute to disease risk. During the last decade, the number of genetic markers convincingly associated with systemic sclerosis has exponentially increased. In this article, we briefly mention the genetic components of systemic sclerosis. Then, we review the classical and novel genetic associations with systemic sclerosis, analyzing the firmest and replicated signals within non–human leukocyte antigen genes, identified by both candidate gene approach and genome-wide association studies. We also provide an insight into the future perspectives that will shed more light into the complex genetic background of the disease. Despite the remarkable advance of systemic sclerosis genetics during the last decade, the use of the new genetic technologies such as next-generation sequencing, as well as the deep phenotyping of the study cohorts, to fully characterize the genetic component of this disease is imperative to identify causal variants, which leads to more targeted and effective treatment of systemic sclerosis.

Keywords: Systemic sclerosis, genetics, single-nucleotide polymorphism, genome-wide association study, candidate gene analysis, ImmunoChip analysis, genome-wide significance, non–human leukocyte antigen genes, human leukocyte antigen genes

Introduction

Systemic sclerosis (SSc) is an autoimmune disease (AID) characterized by generalized fibrosis in connective tissues and internal organs as consequences of microvascular dysfunction and immune dysfunctions, which leads to premature death in affected individuals.

As clinical phenotypes, SSc is divided into limited cutaneous systemic sclerosis (lcSSc) and diffuse cutaneous systemic sclerosis (dcSSc). 1 SSc is also classified according to supposedly mutually exclusive and disease-specific autoantibodies (anti-centromere antibodies (ACAs) and anti-topoisomerase antibodies (ATAs)), which are found in approximately 50%–70% of SSc cases. 2 Each of these autoantibodies is a marker for relatively distinct clinical subgroups of SSc; ACA is typically associated with lcSSc, uncommon pulmonary fibrosis (PF), late-onset pulmonary hypertension, and generally an overall good prognosis, while ATA is a marker for dcSSc and clinically significant PF with a resultant poorer prognosis than an ACA(+) subtype. 3

The etiology of SSc is complex and poorly understood, but as with most AIDs, such as rheumatoid arthritis (RA), it is widely accepted that gene–environment interactions trigger SSc onset. 4

The most frequent type of DNA variation is a single-nucleotide polymorphism (SNP). The resultant changes in the DNA sequence may or may not influence the protein function due to modification in the gene expression or alteration in the resulting protein. Two basic approaches often used for genetic association studies are the candidate gene approach (CGA) and the genome-wide association study (GWAS). Both modalities identify SNPs and determine the likelihood that the variant occurs more or less frequently in the cases than in the controls. For both approaches, association is first tested in a discovery cohort and then repeated in a non-overlapping group of cases and controls.

In CGA, candidate genes are selected based on either their association with other AIDs or their involvement in certain pathways hypothesized to be important for the disease pathogenesis. Thus, we can test for a particular SNP with known functional consequences,4,5 but CGA cannot identify new loci that have not been discovered yet due to the nature of its hypothesis-driven approach.

On the other hand, GWAS scans the entire genome for SNPs associated with a certain disease without any assumptions, and thus is an unbiased approach. In fact, GWAS has made possible the identification of new loci that would not have been discovered. 6 However, because most GWAS provide approximately 80% coverage for common polymorphisms in the human genome, they often miss unusual or rare variants. 4 Moreover, GWAS usually investigates SNPs that are in strong linkage disequilibrium (LD) with other SNPs and serve as proxies for them, and thus the identified SNPs by GWAS are regarded as just a tag for the yet-to-be-identified causal allele. Thus, the next step in genomic analyses will be whole genome sequencing, which covers all nucleotides in the genome.

ImmunoChip array is another type of SNP genotyping with high-density mapping of 196,524 variants across 186 known AID-risk loci in European-Caucasian populations.7,8 It also includes several rare variants supposed to have significant functional effects that might have been previously overlooked. 9 This approach has recently shown promising results in various autoimmune- and immune-related diseases including SSc.7,8 These studies resulted in not only the identification of susceptibility genes but also the narrowing of the associations in previously reported risk loci for large cohorts at reduced costs. Moreover, these reports increased the number of shared genetic markers between the different disorders, further supporting the common genetic component of autoimmunity.

In this review article, we provide an overview of the known SSc-related genetic factors and address their possible functional implication in the pathogenic events. Specifically, we briefly mention the heritability of SSc first. Then, we present genes outside major histcompatibility complex (MHC) region, of which SNPs had association with SSc or its phenotypes at genome-wide significant (GWS) levels (p < 5.0 × 10−8). Recent advances in epigenetic studies have accumulated several evidences that epigenetic modifications of certain genes are also involved in SSc pathogenesis, 10 which have been precisely reviewed in several articles and thus is beyond the scope of this review.

Heritability

Feghali-Bostwick et al. 11 performed a classical twin study and found a similar SSc concordance between monozygotic and dizygotic twins, suggesting a low heritability of SSc. However, this study contained a quite limited number of twins and the subjects had a wide range of age.

On the other hand, Bossini-Castillo et al. 12 calculated SSc heritability with the use of a mixed model (GREML) 13 applying to two large-scale GWASs.7,14 While they found that SSc heritability (liability-scale) is lower than in other AIDs, such as inflammatory bowel disease (IBD) or type 1 diabetes,13,15 they also confirmed that the twin concordance study above 11 had underestimated heritability of SSc. 12

Arnett et al. 16 showed that the first-degree relatives of SSc patients had a 13 times higher SSc risk than the general population and 15 times higher in the case of SSc patients’ siblings, while the absolute risk of developing SSc is only 1.5%–1.7% in these relatives compared with 0.026% in the general population. These studies indicated that a positive family history of SSc is a strong risk of SSc, but the absolute risk of each family member remains still low (~1%), which was consistent with the estimated prevalence of SSc in first-degree family members by Englert et al. 17

Intriguingly, Arora-Singh et al. 18 showed an increased familial risk to develop other AIDs such as hypothyroidism, hyperthyroidism, systemic lupus erythematosus (SLE), or some of SSc manifestations including Raynaud’s phenomenon or interstitial lung disease, implicating genetic contribution to SSc development, and shared genetic components between SSc and other AIDs.

To sum up, it has been indicated that the heritability of SSc might be lower than other AIDs; 12 however, it is also evident that genetic component plays important roles for pathogenesis of SSc. Thus, estimating precise heritability and clarifying genetic roles in pathogenesis are of the future interests in the genetic study of SSc.

Not only human leukocyte antigen genes but also genes outside MHC region significantly associated with SSc

As seen in other AIDs, human leukocyte antigen (HLA) genes or haplotypes identified in SSc genetic studies have been shown to be associated with SSc susceptibility, autoantibody profiles, disease subtypes, or certain SSc clinical features. Several large-scale studies indicated that HLA-DQB1 and genes in LDs with HLA-DQB1 are strongly associated with SSc susceptibility and the effects are dependent on autoantibody status mainly in European-Caucasian descents3,7,14,19,20 More specifically, the associations of HLA-DPB1*13:01 with ATA, HLA-DQB1*05:01, and HLA-DQB1 alleles encoding a non-leucine residue at position 26 (DQB1*26 epi) with ACA, and HLA-DRB1*04:04, HLA-DRB1*11, and HLA-DQB1*03 with anti-RNA polymerase III antibody (ARA) were reported by Arnett et al. 21 Not surprisingly, these associations can be common in different ethnicities, while others are specific to certain populations. 22

Multiple non-HLA loci have been reported as SSc susceptibility genes with varying significance. However, most of them were based on the small-scale analyses and were not replicable. Recent advances, such as well-powered CGAs and replication studies together with the GWAS, have led to the establishment of multiple non-HLA loci as SSc susceptibility genes at the GWS levels. There have been 15 firmly established SSc-associated genes among non-HLA genes, which are involved in various functions, with the most robust associations including genes for B- and T-cell activation and innate immunity (Table 1). In the following sections, we focus more on some of these confirmed non-HLA genes.

Table 1.

Non-HLA genes outside HLA region significantly associated with SSc.

Gene Locus SNP Phenotypes Samples Study type Genotyping Ethnicity First author Publication Ref.
IRF5 7q32.1 rs2004640 SSc, ATA+ dcSSc, PF 427 cases/380 HCs (discovery) CGA TaqMan Caucasian Dieude 2009 20
454 cases/380 HCs (replication)
SSc Allanore et al. 19 and Ito et al. (Arthritis Rheum, 2009) Meta-analysis – Caucasian, Asian Xu 2016 23
rs10488631 SSc 2296 cases/5171 HCs (discovery)
2753 cases/4659 HCs (replication)
GWAS Illumina HumanCNV370K BeadChip Caucasian Arnett 2010 14
SSc 564 cases/1776 HCs (discovery)
1682 cases/3926 HCs (replication)
GWAS Illumina Human610-Quad BeadChip Caucasian Allanore 2011 19
rs3757385 “R” haplotype (C-T-A) for dcSSc
“P” haplotype (A-G-G) for dcSSc and PF
827 cases/989 HCs CGA Kaspar genotyping Caucasian Dieude 2009 20
rs10954213
rs2004640
IRF8 16q24.1 rs11642873 lcSSc 2296 cases/5171 HCs (discovery)
3175 cases/4971 HCs (replication)
GW AS Immuno Chip Caucasian Gorlova 2011 3
SSc 1280 cases/3593 HCs (discovery)
3156 cases/5148 HCs (replication)
GWAS a Caucasian, Asian Terao 2017 22
rs2280381 SSc 415 cases/16,891 HCs (discovery)
315 cases/21,054 HCs (replication)
CGA TaqMan Asian Terao 2013 24
rs11117432 SSc 1616 cases/3621 HCs CGA Kaspar genotyping Caucasian Arismendi 2015 –
STAT4 2q32.2-q32.3 rs7574865 lcSSc 332 cases/1296 HCs (discovery)
985 cases/1817 HCs (replication)
CGA TaqMan Caucasian Rueda 2009 25
ATA+ SSc, PF, dcSSc 453 cases/534 HCs CGA TaqMan Asian Yi 2013 26
SSc, lcSSc, dcSSc Allanore et al., 19 Nguyen et al., 27 Abelson et al., 28 and Tsuchiya et al. (Ann Rheum Dis, 2009) Meta-analysis – Caucasian, Asian Xu 2016 23
SSc 1280 cases/3593 HCs (discovery)
3156 cases/5148 HCs (replication)
GWAS a Caucasian, Asian Terao 2017 22
SSc 440 cases/485 HCs (discovery)
445 cases/485 HCs (replication)
CGA Kaspar genotyping Caucasian Dieude 2009 29
rs3821236 SSc 2296 cases/5171 HCs (discovery)
2753 Cases/4659 HCs (replication)
GWAS TaqMan Caucasian Arnett 2010 16
SSc 564 cases/1776 HCs (discovery)
1682 cases/3926 HCs (replication)
GWAS Illumina Human610-Quad BeadChip Caucasian Allanore 2015 19
rs10168266 ACA+ SSc, PF 453 cases/534 HCs CGA TaqMan Asian Yi 2013 26
IL12A 3q25.33 rs77583790 SSc, ACA+ lcSSc 1833 cases/3466 HCs (discovery)
4017 cases/5935 HCs (replication)
ImmunoChip ImmunoChip for discovery sets; TaqMan for replication sets Caucasian Mayes 2014 7
IL12RB1 19p13.11 rs2305743 SSc 1871 case/3636 HCs (discovery)
3181 cases/5076 HCs (replication)
CGA ND Caucasian Lopez-Isac 2014 30
rs8109496
rs436857
rs11668601
IL12RB2 1p31.3 rs3790566 SSc 2296 cases/5171 HCs (discovery)
2753 cases/4659 HCs (replication)
GWAS TaqMan Caucasian Arnett 2010 16
rs924080
rs3790567 SSc 2296 cases/5171 HCs (discovery)
2753 cases/4659 HCs (replication)
GWAS TaqMan Caucasian Arnett 2010 16
SSc 3344 cases/3848 HCs (discovery)
597 cases/1139 (replication)
CGA TaqMan Caucasian Bossini-Castillo 2012 31
CD247 1q24.2 rs2056626 SSc 2296 cases/5171 HCs (discovery)
2753 cases/4659 HCs (replication)
GWAS TaqMan Caucasian Arnett 2010 16
SSc 1031 cases/1014 HCs CGA Kaspar genotyping Caucasian Dieude 2011 32
PRDM1 6q21 rs4134466 SSc 1280 cases/3593 HCs (discovery)
3156 cases/5148 HCs (replication)
GWAS a Caucasian, Asian Terao 2017 22
ATG5 6q21 rs9373839 SSc 1833 cases/3466 HCs (discovery)
4017 cases/5935 HCs (replication)
ImmunoChip ImmunoChip for discovery sets; TaqMan for replication sets Caucasian Mayes 2014 7
TNIP1 5q33.1 rs2233287 SSc 564 cases/1776 HCs (discovery)
1682 cases/3926 HCs (replication)
GWAS Illumina Human610-Quad BeadChip Caucasian Allanore 2015 19
SSc 4389 cases/7611 HCs CGA b Caucasian Bossini-Castillo 2013 33
rs4958881 SSc 564 cases/1776 HCs (discovery)
1682 cases/3926 HCs (replication)
GWAS Illumina Human610-Quad BeadChip Caucasian Allanore 2015 19
SSc 4389 cases/7611 HCs CGA b Caucasian Bossini-Castillo 2013 33
rs3792783 SSc 564 cases/1776 HCs (discovery)
1682 cases/3926 HCs (replication)
GWAS Illumina Human610-Quad BeadChip Caucasian Allanore 2015 19
SSc 4389 cases/7611 HCs CGA b Caucasian Bossini-Castillo 2013 33
TNFAIP3 6q23.3 rs5029939 SSc, dcSSc, ATA+, PF, PH 1018 cases/1012 HCs (discovery)
649 cases/306 HCs (replication)
CGA Kaspar genotyping for a discovery set, TaqMan for a replication set Caucasian Dieude 2010 34
rs117480515 SSc 985 cases/1011 HCs (discovery)
662 cases/493 HCs (replication)
CGA Kaspar genotyping for a discovery set, TaqMan for a replication set Caucasian Koumakis 2012 35
rs2230926 SSc 3237 cases/6097 HCs CGA Illumina GoldenGate array/Illumina iScan system Caucasian Martin 2012 36
SSc 1280 cases/3593 HCs (discovery)
3156 cases/5148 HCs (replication)
GWAS a Caucasian, Asian Terao 2017 22
rs6932056 SSc 415 cases/16,891 HCs (discovery)
315 cases/21,054 HCs (replication)
CGA TaqMan Asian Terao 2013 24
rs892999 SSc for Caucasians 1833 cases/3466 HCs (Whites)
291 cases/260 HCs (Blacks)
CGA ImmunoChip Caucasian, Black Gorlova 2018 37
rs10223636 SSc for African American CGA ImmunoChip Caucasian, Black Gorlova 2018 37
CSK 15q24.1 rs1378942 SSc 3237 cases/6097 HCs CGA Illumina GoldenGate array/Illumina iScan system Caucasian Martin 2012 36
DNASE1 L3 3p14.3 rs35677470 SSc 1833 cases/3466 HCs (discovery)
4017 cases/5935 HCs (replication)
ImmunoChip ImmunoChip for discovery sets; TaqMan for replication sets Caucasian Mayes 2014 7
SSc 1280 cases/3593 HCs (discovery)
3156 cases/5148 HCs (replication)
GWAS a Caucasian, Asian Terao 2017 22
TYK2 19p13.2 rs2304256 SSc 2118 cases/4742 HCs (discovery)
4985 cases/7478 HCs (replication)
CGA TaqMan Caucasian Lopez-Isac 2015 –
SSc 1280 cases/3593 HCs (discovery)
3156 cases/5148 HCs (replication)
GWAS a Caucasian, Asian Terao 2017 22
GSDMA 17q21.1 rs3894194 SSc 1280 cases/3593 HCs (discovery)
3156 cases/5148 HCs (replication)
GWAS a Caucasian, Asian Terao 2017 22
57 patients/15 HCs CGA Illumina Infinium Omni2.5–8 1.3 platform Caucasian, Black, Caribbean, Indian Moreno-Moral 2018 38

HLA: human leukocyte antigen; SSc: systemic sclerosis; dcSSc: diffuse cutaneous systemic sclerosis; lcSSc: limited cutaneous systemic sclerosis; ACA: anti-centromere antibody; ATA: anti-topoisomerase I antibody; PF: pulmonary fibrosis; PH: pulmonary hypertension; GWAS: genome-wide association study; CGA: candidate gene approach; SNP: single-nucleotide polymorphism; HCs: healthy controls; PCR: polymerase chain reaction; ND: not described.

a

Same as Allanore et al. 19 for French samples; genotyped with a competitive allele-specific PCR for European replication samples; genotyped in Kyoto University and University of Tsukuba for Japanese samples.

b

Illumina Human550K, Illumina Human CNV370K, Illumina Human CytoSNP-12, Illumina Human 1M-Duo, and TaqMan.

IRF5

Interferon regulatory factor 5 (IRF5) is a crucial regulator of type I interferon (IFN) signaling. IFN signatures, IFN-inducible genes, similar to those of SLE in the peripheral blood cells of SSc patients have also been determined. 39

Dieude et al. 20 found an association between the IRF5 intron 1 rs2004640T allele and SSc, especially the ATA(+) dcSSc with fibrosing alveolitis (FA) in French population, suggesting that the rs2004640 could influence the fibrotic phenotype via type I IFN activation. They further performed genotype–phenotype–haplotype correlation analyses of IRF5 with the SNPs rs3757385, rs2004640, and rs10954213, and found that the “R” haplotype (C-T-A) conferred susceptibility to SSc, especially dcSSc, and the “P” haplotype (A-G-G) had protective effect on both dcSSc and FA. 40 The “R” haplotype is known to infer the CGGGG insertion risk allele, which leads to increased binding of SP1 transcriptional factor and also known as the causative variant of SLE and Sjogren syndrome. 41 As all single markers failed to detect association signals, the study suggested the haplotype analyses may be more informative than single-marker analyses.

Association of IRF5 with SSc was also confirmed in the GWAS of SSc,14,19 and the meta-analysis conducted by Xu et al., 23 suggesting its association beyond populations. Collectively, these studies strongly indicated a key role of IRF5 in SSc pathogenesis.

STAT4

Signal transducer activator transcriptional factor 4 (STAT4) is a member of the STAT transcription factor family and is essential in mediating interleukin-12 (IL-12) signaling, as well as in helper T-cell differentiation. 42 STAT4 also links the innate and the adaptive immune responses through type I IFN-mediated IFN-γ production. 27

Rueda et al. 25 first reported the association of STAT4 in their Caucasian case–control study. The tag SNP rs7574865 (intron 3) T allele, which is correlated with STAT4 mRNA expression 28 and known for its association with other AIDs, 23 significantly associated with susceptibility to lcSSc as well as lacked the association with dcSSc. A dosage effect was also observed (rs7574865 TT genotype, p = 1.02 × 10−7). Subsequent two Caucasian GWASs14,19 also showed significant associations, although the study conducted by Allanore et al. might include populations overlapped with the first case–control study.

On the other hand, a Chinese case–control study conducted by Yi et al. reported different results. The T-allele carriers of rs7574865 as well as rs10168266 were associated with ATA (p = 0.0012 and p = 3.1 × 10−4, respectively) and PF (p = 1.2 × 10−4 and p = 7.7 × 10−4, respectively), as well as with dcSSc (p = 6.4 × 10−4 and p = 0.0015, respectively). The presence of ACA and lcSSc did not show significant association with any of the examined SNPs in this study. 26

According to a meta-analysis of six case–control studies including the studies above conducted by Xu et al., the rs7574865T allele showed a significant association with SSc susceptibility (p < 0.00001) in the overall population, and both lcSSc and dcSSc showed a significant association with each of the genetic models (lcSSc, p < 1.0 × 10−5; dcSSc, p < 5.0 × 10−4 to 1.0 × 10−5). 23

Furthermore, our transethnic meta-analysis of GWAS in the Japanese and European populations found a GWS association of rs7574865T allele with overall SSc. 22

The different effects of rs7574865T allele on SSc subtypes and autoantibody profiles among different ethnicities indicated that an association of the rs7574865T allele with ACA(+) SSc may be limited in European populations while that in Asian populations remained questionable partly because of small sample size of the studies. It might also be possible that different SNPs might be more important for non-European populations.

Notably, Dieude et al. observed that additive effects of STAT4 rs7574865 and IRF5 rs2004640 polymorphisms on susceptibility to both SSc and SSc-related FA. 29 The STAT4 rs7574865T allele and the IRF5 rs2004640T allele resulted in 1.28-fold higher risk of SSc and the odds ratio (OR) for SSc was 2.72 (1.86–3.99) for combinations of genotypes with ⩾3 risk alleles.

The functional role in SSc pathogenesis was also tested in Stat4-knockout mice, which presented decreased cytokine production and protection from skin fibrosis in bleomycin-induced model. 43 Despite several questions remaining to be answered, all the studies above further strongly supported functional consequences caused by STAT4 polymorphisms and their roles in SSc pathophysiology.

IL12, IL12RB1, and IL12RB2

The protein encoded by IL12, the p35 subunit, promotes type 1 helper T-cell differentiation and in combination with IFN-γ antagonizes type 2 helper T-cell differentiation. 44

IL12A was one of the non-HLA loci identified by ImmunoChip study conducted by Mayes et al. The missense SNP rs77583790 in an intergenic region between IL12A and SCHIP1 encoding schwannomin interacting protein 1 was significantly associated with overall SSc, and the association was also significant in the lcSSc and ACA(+) subgroup. 7

IL12RB1 and IL12RB2 encode both chains of the IL-12 receptor, and both of genes showed suggestive associations with SSc in Caucasian GWAS. 14 Bossini-Castillo et al. 31 subsequently conducted a follow-up study using an independent cohort and observed GWS association of an intronic SNP rs3790567 of IL12RB2 with SSc. The SNP may be a tag of certain functional variant or may have a yet unknown functional implication.

According to the suggestive association signals of IL12RB1 locus in immunoChip study, 7 Lopez-Isac et al. 30 conducted a follow-up study, in which four SNPs showed GWS associations with SSc susceptibility (rs8109496, rs2305743, rs436857, and rs11668601). They also suggested that SNP rs436857 in IL12RB1 promoter region was the most likely causal variant. The minor allele of this SNP showed a protective effect and was located in an IL12RB1 cis-eQTL that decreased IL12RB1 expression, 45 which would lead to a reduced IL-12 response consistent with a lower SSc susceptibility. 12 Furthermore, they also reported an association of a common variant (V362F) of TYK2, which encodes tyrosine kinase 2 involved in IL-12 pathway, with SSc susceptibility. 46

Collectively, these data in conjunction with those of STAT4, IL-12/STAT4 axis are further implicated as parts of the central roles in the pathogenesis of SSc.

CD247

CD247 encodes CD3ζ chain, 47 and altered low expression of CD3ζ chain results in impaired immune response. 48 Genetic variants in the 3′ untranslated region of this gene have shown functional implications leading to a reduced expression of the CD3ζ chain that could be manifested in systemic autoimmunity. 49

Radstake et al. 14 identified CD247 (rs2056626) as a susceptibility locus for SSc by European ancestry GWAS. An independent French study confirmed the association and indicated that the minor allele rs2056656G was associated with a protective effect. 32 In sharp contrast, there was no association between the same variant and SSc or any SSc subtypes in a Han Chinese cohort, 50 and our transethnic meta-GWAS analysis also failed to replicate the association observed in the European studies above. 22 Further studies to better explain the exact role of CD247 in SSc in different ethnic populations will be of great interest.

PRDM1

PRDM1, B-lymphocyte-induced maturation protein 1, also known as BLIMP1, is a transcription factor influencing a broad range of genes involved with cell proliferation and immune systems. PRDM1 is also critical for epithelial and B-cell differentiation and associated with immune functions and other AIDs. 51

Our meta-GWAS analysis in the Japanese and European populations identified a significant association of PRDM1 rs4134466 with SSc susceptibility. 22 The rs4134466 was not dependent on rs9373839 in ATG5, a previously reported susceptibility gene to SSc. 7 Intriguingly, the rs4134466 provided the highest score of H3K4me3 in naïve CD4+ T cell among the SSc susceptibility variants, suggesting a functional consequence of this variant.

Tumor necrosis factor-α-related genes

TNFAIP3 and TNIP1 encode for tumor necrosis factor (TNF)-α-induced protein (A20) 52 and TNFAIP3-interacting protein, respectively. Both A20 and TNIP1 are involved in negatively regulating the TNF-induced nuclear factor (NF)-κB signaling pathway. 53

A European GWAS conducted by Allanore et al. found a significant association of TNIP1 rs4958881 with SSc. 19 They also observed a markedly reduced expression of the TNIP1 gene and its protein product both in skin lesions and in cultured dermal fibroblasts from SSc patients. Furthermore, TNIP1 showed in vitro inhibitory effects on inflammatory cytokine-induced collagen production. On the other hand, Bossini-Castillo et al. 33 conducted a replication study in independent Caucasian populations and confirmed the association of rs4958881 (p = 3.26 × 10−5) as well as other variants (rs2233287, p = 1.94 × 10−4; rs3792783, p = 2.16 × 10−4) with SSc and its subgroups.

Multiple studies with different ethnicities have repeatedly reported the associations of TNFAIP3 SNP variants with susceptibility of SSc and its subtypes.22,24,34 –37 However, only one of them reached GWS in its association with dcSSc. 34 Considering the close relationship between TNIP1 and TNFAIP3 as described above, it may be important to consider the effects of both of these gene polymorphisms simultaneously.

CSK

C-Src kinase, CSK, is a tyrosine-protein kinase that negatively regulates lymphocyte activation through phosphorylation of the Src-family kinases. 54 It has been reported that Src kinases play a central role in the activation of fibroblasts and in the development of experimental fibrosis and Src kinase inhibition reduced the transcriptional activity of COL1A1, COL1A2, and FN1 (which encode collagen type 1 α1, α2 chains, and fibronectin 1) and prevented experimental dermal fibrosis. 55

In the GWAS follow-up study conducted by Martin et al., 36 CSK was newly identified as a gene associated with SSc with genome-wide significance (rs1378942). Although the functional relevance of the CSK associated SNP is unknown, genetic variants affecting its inhibitory effect may contribute to the uncontrolled fibroblast activation in SSc pathogenesis. 12

GSDMA

Our transethnic meta-GWAS analysis identified a missense variant rs3894194 in GSDMA, which encodes gasdermin A, was associated with overall SSc as well as lcSSc. 22 GSDMA also showed a significant association with other AIDs including RA 56 and IBD.57,58 Importantly, the rs3894194 showed enhancer activity and enrichment of histone marks, and strongly associated with expression of neighboring genes, GSDMB, and ORMDL3, encoding gasdermin B and ORMDL sphingolipid biosynthesis regulator 3, respectively, suggesting this variant as a potential causative SNP. On the other hand, Moreno-Moral et al. 38 recently reported that the rs3894194 conferred changes of transcriptome signatures in SSc macrophages. Although lack of GWS or replications, TLR (toll-like receptor) 59 and NLRP (NLR family pyrin domain) 60 were also reported to be associated with SSc and encoding proteins as well as gasdermin A are essential components for inflammasome formation and pyroptosis induction, implicating their roles in the innate immune/inflammasome pathway underlying SSc pathogenesis.

Concluding remarks

Recent advances of knowledge and technology of the genetic study have enabled us to discover numbers of novel and significant genes associated with susceptibility of SSc and its subtypes and autoantibody profiles in SSc patients (Figure 1). Of note, several SNPs of HLA and non-HLA genes, which have not reached GWS but have been replicated in independent studies, are not described in this review. Despite the recent advances, only a small proportion of the heritability of SSc has been explained yet due to the limitations of available technologies, such as what we described with regard to GWAS in the “Introduction” section. As potentially powerful tools in near future, ongoing studies include fine mapping and sequencing studies together with CRISPR-Cas technology to pinpoint causal variants, whereas other studies focus on functional consequences of these variants to identify the link between these genetic variants and disease susceptibility. Such knowledge should lead to more targeted and effective treatment of SSc.

Figure 1.

Figure 1.

Different kinds of cells, including antigen presenting cells (APC), T cells, B cells, fibroblasts, and endothelial cells, play roles for SSc pathogenesis. Gene polymorphisms associated with SSc susceptibility may affect functions of these cells, leading to endothelial dysfunction, excessive deposition of extracellular matrix, and ultimately organ dysfunction.

Footnotes

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

  • 1. LeRoy EC, Black C, Fleischmajer R, et al. Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol 1988; 15(2): 202–205. [PubMed] [Google Scholar]
  • 2. Steen VD. Autoantibodies in systemic sclerosis. Semin Arthritis Rheum 2005; 35: 35–42. [DOI] [PubMed] [Google Scholar]
  • 3. Gorlova O, Martin JE, Rueda B, et al. Identification of novel genetic markers associated with clinical phenotypes of systemic sclerosis through a genome-wide association strategy. PLoS Genet 2011; 7(7): e1002178. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Salazar G, Mayes MD. Genetics, epigenetics, and genomics of systemic sclerosis. Rheum Dis Clin North Am 2015; 41(3): 345–366. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Broen JC, Coenen MJ, Radstake TR. Genetics of systemic sclerosis: an update. Curr Rheumatol Rep 2012; 14: 11–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Mayes MD. The genetics of scleroderma: looking into the postgenomic era. Curr Opin Rheumatol 2012; 24(6): 677–684. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Mayes MD, Bossini-Castillo L, Gorlova O, et al. Immunochip analysis identifies multiple susceptibility loci for systemic sclerosis. Am J Hum Genet 2014; 94(1): 47–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Cortes A, Brown MA. Promise and pitfalls of the immunochip. Arthritis Res Ther 2011; 13(1): 101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Polychronakos C. Fine points in mapping autoimmunity. Nat Genet 2011; 43(12): 1173–1174. [DOI] [PubMed] [Google Scholar]
  • 10. Aslani S, Sobhani S, Gharibdoost F, et al. Epigenetics and pathogenesis of systemic sclerosis; the ins and outs. Hum Immunol 2018; 79(3): 178–187. [DOI] [PubMed] [Google Scholar]
  • 11. Feghali-Bostwick C, Medsger TA, Jr, Wright TM. Analysis of systemic sclerosis in twins reveals low concordance for disease and high concordance for the presence of antinuclear antibodies. Arthritis Rheum 2003; 48(7): 1956–1963. [DOI] [PubMed] [Google Scholar]
  • 12. Bossini-Castillo L, Lopez-Isac E, Martin J. Immuno-genetics of systemic sclerosis: defining heritability, functional variants and shared-autoimmunity pathways. J Autoimmun 2015; 64: 53–65. [DOI] [PubMed] [Google Scholar]
  • 13. Lee SH, Wray NR, Goddard ME, et al. Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet 2011; 88(3): 294–305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Radstake TR, Gorlova O, Rueda B, et al. Genome-wide association study of systemic sclerosis identifies CD247 as a new susceptibility locus. Nat Genet 2010; 42(5): 426–429. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Chen GB, Lee SH, Brion MJ, et al. Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and immunochip data. Hum Mol Genet 2014; 23(17): 4710–4720. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Arnett FC, Cho M, Chatterjee S, et al. Familial occurrence frequencies and relative risks for systemic sclerosis (scleroderma) in three United States cohorts. Arthritis Rheum 2001; 44(6): 1359–1362. [DOI] [PubMed] [Google Scholar]
  • 17. Englert H, Small-McMahon J, Chambers P, et al. Familial risk estimation in systemic sclerosis. Aust N Z J Med 1999; 29(1): 36–41. [DOI] [PubMed] [Google Scholar]
  • 18. Arora-Singh RK, Assassi S, del Junco DJ, et al. Autoimmune diseases and autoantibodies in the first degree relatives of patients with systemic sclerosis. J Autoimmun 2010; 35(1): 52–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Allanore Y, Saad M, Dieude P, et al. Genome-wide scan identifies TNIP1, PSORS1C1, and RHOB as novel risk loci for systemic sclerosis. PLoS Genet 2011; 7(7): e1002091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Dieude P, Guedj M, Wipff J, et al. Association between the IRF5 rs2004640 functional polymorphism and systemic sclerosis: a new perspective for pulmonary fibrosis. Arthritis Rheum 2009; 60(1): 225–233. [DOI] [PubMed] [Google Scholar]
  • 21. Arnett FC, Gourh P, Shete S, et al. Major histocompatibility complex (MHC) class II alleles, haplotypes and epitopes which confer susceptibility or protection in systemic sclerosis: analyses in 1300 Caucasian, African-American and Hispanic cases and 1000 controls. Ann Rheum Dis 2010; 69(5): 822–827. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Terao C, Kawaguchi T, Dieude P, et al. Transethnic meta-analysis identifies GSDMA and PRDM1 as susceptibility genes to systemic sclerosis. Ann Rheum Dis 2017; 76(6): 1150–1158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Xu Y, Wang W, Tian Y, et al. Polymorphisms in STAT4 and IRF5 increase the risk of systemic sclerosis: a meta-analysis. Int J Dermatol 2016; 55(4): 408–416. [DOI] [PubMed] [Google Scholar]
  • 24. Terao C, Ohmura K, Kawaguchi Y, et al. PLD4 as a novel susceptibility gene for systemic sclerosis in a Japanese population. Arthritis Rheum 2013; 65(2): 472–480. [DOI] [PubMed] [Google Scholar]
  • 25. Rueda B, Broen J, Simeon C, et al. The STAT4 gene influences the genetic predisposition to systemic sclerosis phenotype. Hum Mol Genet 2009; 18(11): 2071–2077. [DOI] [PubMed] [Google Scholar]
  • 26. Yi L, Wang JC, Guo XJ, et al. STAT4 is a genetic risk factor for systemic sclerosis in a Chinese population. Int J Immunopathol Pharmacol 2013; 26(2): 473–478. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Nguyen KB, Watford WT, Salomon R, et al. Critical role for STAT4 activation by type 1 interferons in the interferon-gamma response to viral infection. Science 2002; 297(5589): 2063–2066. [DOI] [PubMed] [Google Scholar]
  • 28. Abelson AK, Delgado-Vega AM, Kozyrev SV, et al. STAT4 associates with systemic lupus erythematosus through two independent effects that correlate with gene expression and act additively with IRF5 to increase risk. Ann Rheum Dis 2009; 68(11): 1746–1753. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Dieude P, Guedj M, Wipff J, et al. STAT4 is a genetic risk factor for systemic sclerosis having additive effects with IRF5 on disease susceptibility and related pulmonary fibrosis. Arthritis Rheum 2009; 60(8): 2472–2479. [DOI] [PubMed] [Google Scholar]
  • 30. Lopez-Isac E, Bossini-Castillo L, Guerra SG, et al. Identification of IL12RB1 as a novel systemic sclerosis susceptibility locus. Arthritis Rheumatol 2014; 66(12): 3521–3523. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Bossini-Castillo L, Martin JE, Broen J, et al. A GWAS follow-up study reveals the association of the IL12RB2 gene with systemic sclerosis in Caucasian populations. Hum Mol Genet 2012; 21(4): 926–933. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Dieude P, Boileau C, Guedj M, et al. Independent replication establishes the CD247 gene as a genetic systemic sclerosis susceptibility factor. Ann Rheum Dis 2011; 70(9): 1695–1696. [DOI] [PubMed] [Google Scholar]
  • 33. Bossini-Castillo L, Martin JE, Broen J, et al. Confirmation of TNIP1 but not RHOB and PSORS1C1 as systemic sclerosis risk factors in a large independent replication study. Ann Rheum Dis 2013; 72: 602–607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Dieude P, Guedj M, Wipff J, et al. Association of the TNFAIP3 rs5029939 variant with systemic sclerosis in the European Caucasian population. Ann Rheum Dis 2010; 69(11): 1958–1964. [DOI] [PubMed] [Google Scholar]
  • 35. Koumakis E, Giraud M, Dieude P, et al. Brief report: candidate gene study in systemic sclerosis identifies a rare and functional variant of the TNFAIP3 locus as a risk factor for polyautoimmunity. Arthritis Rheum 2012; 64(8): 2746–2752. [DOI] [PubMed] [Google Scholar]
  • 36. Martin JE, Broen JC, Carmona FD, et al. Identification of CSK as a systemic sclerosis genetic risk factor through Genome Wide Association Study follow-up. Hum Mol Genet 2012; 21(12): 2825–2835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Gorlova OY, Li Y, Gorlov I, et al. Gene-level association analysis of systemic sclerosis: a comparison of African-Americans and White populations. PLoS ONE 2018; 13(1): e0189498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Moreno-Moral A, Bagnati M, Koturan S, et al. Changes in macrophage transcriptome associate with systemic sclerosis and mediate. Ann Rheum Dis 2018; 77(4): 596–601. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Tan FK, Zhou X, Mayes MD, et al. Signatures of differentially regulated interferon gene expression and vasculotrophism in the peripheral blood cells of systemic sclerosis patients. Rheumatology 2006; 45(6): 694–702. [DOI] [PubMed] [Google Scholar]
  • 40. Dieude P, Dawidowicz K, Guedj M, et al. Phenotype-haplotype correlation of IRF5 in systemic sclerosis: role of 2 haplotypes in disease severity. J Rheumatol 2010; 37(5): 987–992. [DOI] [PubMed] [Google Scholar]
  • 41. Kristjansdottir G, Sandling JK, Bonetti A, et al. Interferon regulatory factor 5 (IRF5) gene variants are associated with multiple sclerosis in three distinct populations. J Med Genet 2008; 45(6): 362–369. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Liang Y, Pan HF, Ye DQ. Therapeutic potential of STAT4 in autoimmunity. Expert Opin Ther Targets 2014; 18(8): 945–960. [DOI] [PubMed] [Google Scholar]
  • 43. Avouac J, Furnrohr BG, Tomcik M, et al. Inactivation of the transcription factor STAT-4 prevents inflammation-driven fibrosis in animal models of systemic sclerosis. Arthritis Rheum 2011; 63(3): 800–809. [DOI] [PubMed] [Google Scholar]
  • 44. Behzadi P, Behzadi E, Ranjbar R. IL-12 family cytokines: general characteristics, pathogenic microorganisms, receptors, and signalling pathways. Acta Microbiol Immunol Hung 2016; 63(1): 1–25. [DOI] [PubMed] [Google Scholar]
  • 45. Westra HJ, Peters MJ, Esko T, et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet 2013; 45(10): 1238–1243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Lopez-Isac E, Campillo-Davo D, Bossini-Castillo L, et al. Influence of TYK2 in systemic sclerosis susceptibility: a new locus in the IL-12 pathway. Ann Rheum Dis 2016; 75(8): 1521–1526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Call ME, Wucherpfennig KW. Molecular mechanisms for the assembly of the T cell receptor-CD3 complex. Mol Immunol 2004; 40(18): 1295–1305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Krishnan S, Kiang JG, Fisher CU, et al. Increased caspase-3 expression and activity contribute to reduced CD3zeta expression in systemic lupus erythematosus T cells. J Immunol 2005; 175(5): 3417–3423. [DOI] [PubMed] [Google Scholar]
  • 49. Gorman CL, Russell AI, Zhang Z, et al. Polymorphisms in the CD3Z gene influence TCRzeta expression in systemic lupus erythematosus patients and healthy controls. J Immunol 2008; 180(2): 1060–1070. [DOI] [PubMed] [Google Scholar]
  • 50. Wang J, Yi L, Guo X, et al. Lack of association of the CD247 SNP rs2056626 with systemic sclerosis in Han Chinese. Open Rheumatol J 2014; 8: 43–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Ott G, Rosenwald A, Campo E. Understanding MYC-driven aggressive B-cell lymphomas: pathogenesis and classification. Blood 2013; 122: 3884–3891. [DOI] [PubMed] [Google Scholar]
  • 52. Shembade N, Harhaj NS, Parvatiyar K, et al. The E3 ligase itch negatively regulates inflammatory signaling pathways by controlling the function of the ubiquitin-editing enzyme A20. Nat Immunol 2008; 9(3): 254–262. [DOI] [PubMed] [Google Scholar]
  • 53. Wertz IE, O’Rourke KM, Zhou H, et al. De-ubiquitination and ubiquitin ligase domains of A20 downregulate NF-kappaB signalling. Nature 2004; 430(7000): 694–699. [DOI] [PubMed] [Google Scholar]
  • 54. Ia KK, Mills RD, Hossain MI, et al. Structural elements and allosteric mechanisms governing regulation and catalysis of CSK-family kinases and their inhibition of Src-family kinases. Growth Factors 2010; 28(5): 329–350. [DOI] [PubMed] [Google Scholar]
  • 55. Skhirtladze C, Distler O, Dees C, et al. Src kinases in systemic sclerosis: central roles in fibroblast activation and in skin fibrosis. Arthritis Rheum 2008; 58(5): 1475–1484. [DOI] [PubMed] [Google Scholar]
  • 56. Okada Y, Wu D, Trynka G, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 2014; 506(7488): 376–381. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Anderson CA, Boucher G, Lees CW, et al. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. Nat Genet 2011; 43(3): 246–252. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Barrett JC, Hansoul S, Nicolae DL, et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat Genet 2008; 40(8): 955–962. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Broen JC, Bossini-Castillo L, van Bon L, et al. A rare polymorphism in the gene for Toll-like receptor 2 is associated with systemic sclerosis phenotype and increases the production of inflammatory mediators. Arthritis Rheum 2012; 64(1): 264–271. [DOI] [PubMed] [Google Scholar]
  • 60. Dieude P, Guedj M, Wipff J, et al. NLRP1 influences the systemic sclerosis phenotype: a new clue for the contribution of innate immunity in systemic sclerosis-related fibrosing alveolitis pathogenesis. Ann Rheum Dis 2011; 70(4): 668–674. [DOI] [PubMed] [Google Scholar]

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