Synopsis
Vitiligo is “complex disorder” (also termed polygenic and multifactorial), reflecting simultaneous contributions of multiple genetic risk factors and environmental triggers. Large-scale genome-wide association studies, principally in European-derived whites and in Chinese, have discovered approximately 50 different genetic loci that contribute to vitiligo risk, some of which also contribute to other autoimmune diseases that are epidemiologically associated with vitiligo. At many of these vitiligo susceptibility loci the corresponding relevant genes have now been identified, and for some of these genes the specific DNA sequence variants that contribute to vitiligo risk are also now known. A large fraction of these genes encode proteins involved in immune regulation, a number of others play roles in cellular apoptosis, and still others are involved in regulating functions of melanocytes. For this last group, there appears to be an opposite relationship between susceptibility to vitiligo and susceptibility to melanoma, suggesting that vitiligo may engage a normal mechanism of immune surveillance for melanoma. While many of the specific biologic mechanisms through which these genetic factors operate to cause vitiligo remain to be elucidated, it is now clear that vitiligo is an autoimmune disease involving a complex relationship between programming and function of the immune system, aspects of the melanocyte autoimmune target, and dysregulation of the immune response.
Keywords: Vitiligo, Autoimmunity, Gene, Genomewide association study, Genetic linkage, Genetic epidemiology
Introduction, background, and genetic epidemiology
The disorder now known as vitiligo was first described by Claude Nicolas Le Cat in 1765 [1]. However, the first specific consideration of a genetic component in vitiligo did not come until 1950, when Stűttgen [2] and Teindel [3] simultaneously reported a total of eight families with multiple relatives affected by vitiligo. Stűttgen noted that in his affected family, vitiligo appeared to exhibit dominant inheritance, after intermarriage to a family with apparent recessive thyroid disease, a very early recognition of what would now be considered complex (polygenic, multifactorial) inheritance. Mohr [4], Siemens [5], and Vogel [6] subsequently reported concordant identical twin-pairs affected by vitiligo, pointing to a major role for genetic factors. Early clinical case series reported a frequency of vitiligo in probands’ relatives of 11 to 38 percent [7–10], highlighting the importance of genetic factors even in typical vitiligo cases.
Nevertheless, formal genetic epidemiologic studies of vitiligo came much later. Hafez [11] and Das [12] suggested a polygenic, multifactorial mode of inheritance, and estimated vitiligo heritability at 46% [12] to 72% [11]. Subsequent investigations likewise supported a polygenic, multifactorial model [13–18], with heritability approximately 50% [18]. A twin study of vitiligo in European-derived whites [17] found that the concordance of vitiligo was 23% in monozygotic twins, underscoring the importance of non-genetic factors as well as genetic factors in vitiligo pathogenesis. In this same study, large-scale genetic epidemiologic analyses [17] indicated that in European-derived whites, the overall frequency of vitiligo in probands’ first-degree relatives was 7%, with the risk 7.8% in probands’ parents and 6.1% in siblings, consistent with polygenic, multifactorial inheritance and age-dependency of vitiligo onset. Importantly, among vitiligo probands’ affected relatives, the frequency of vitiligo was equal in males and females, eliminating the female sex bias found in most vitiligo clinical case series. Moreover, a careful study of families with multiple relatives affected by vitiligo [19] showed earlier age-of-onset and greater skin surface involvement than in singleton cases [17], as well as greater frequency of other autoimmune diseases, suggesting that in such “multiplex families” genes likely contribute more to vitiligo risk than in singleton cases.
Relationship to other autoimmune diseases
The genetic basis of vitiligo is deeply intertwined with the genetic basis of other autoimmune diseases with which vitiligo is epidemiologically associated. Indeed, the earliest clue to the autoimmune origin of vitiligo came in the original 1855 report of Addison’s disease [20], which included a patient with idiopathic adrenal insufficiency, generalized vitiligo, and pernicious anemia, a co-occurrence of autoimmune diseases that suggested shared etiologic factors. Subsequently, the co-occurrence of different autoimmune diseases, including vitiligo, was reported by many investigators, particularly Schmidt [21], and key combinations of concomitant autoimmune diseases were later codified by Neufeld and Blizzard [22]. Beginning with the vitiligo case series reported by Steve [23], numerous investigators have since documented prevalent co-occurrence of vitiligo with various other autoimmune diseases, particularly autoimmune thyroid disease (both Hashimoto’s disease and Graves’ disease), pernicious anemia, Addison’s disease, systemic lupus erythematosus [17], rheumatoid arthritis, adult-onset type 1 diabetes mellitus, and perhaps psoriasis [19]. Of particular importance, these same vitiligo-associated autoimmune diseases also occur at increased frequency in first-degree relatives of vitiligo probands who do not themselves have vitiligo, indicating that these autoimmune diseases share at least some of their genetic underpinnings with vitiligo [19].
Early genetic marker studies
The earliest attempts to identify genetic markers associated with vitiligo began in the mid-1960s, assaying polymorphic blood proteins such as the ABO and other blood group antigens [24–30], secretor status [26,27,31], and later serum alpha 1-antitrypsin and haptoglobin phenotypes [32], with no positive results. A decade later, numerous investigators reported association studies of vitiligo with HLA types, which have also been associated with many other autoimmune diseases. Initial association studies of vitiligo and HLA yielded inconsistent and largely spurious findings due to testing different ethnic groups, inadequate statistical power, and inadequate correction for multiple-testing of many different HLA types [33–37]. Nevertheless, Foley and co-workers [38] correctly identified association of the HLA-DR4 class II serotype with vitiligo, borne out by subsequent studies, the first known genetic association for vitiligo. Importantly, HLA-DR4 is also strongly associated with several other autoimmune diseases.
A large number of additional HLA association studies of vitiligo were published subsequently, again with generally inconsistent findings. Nevertheless, Liu and co-workers [39] conducted a careful meta-analysis of eleven previous studies of HLA class I serotypes, and found robust association of vitiligo with HLA-A2 with odds ratio (OR) 2.07, a finding borne out by subsequent studies. Specific associations of vitiligo with the class I and class II gene regions of the Major Histocompatibility Complex (MHC) were subsequently replicated and refined by detailed molecular genetic and genomewide association studies (GWAS), even to the point of identifying apparently causal genetic variation, as will be discussed below.
Non-MHC candidate gene association studies
The development of DNA technology in the late 1970s ushered in an era of testing candidate genes for association with a great many diseases, including vitiligo. Unfortunately, numerous retrospective studies have shown that well over 95% of published case-control genetic association studies represent false-positives, due to inadequate sample size and statistical fluctuation, genotyping errors, occult population stratification, inadequate correction for multiple-testing, and publication bias of positive results [40,41]. As the result, this type of study is no longer considered appropriate for primary “discovery” of genetic association. Accordingly, of the approximately 70 genes for which association with vitiligo is claimed on the basis of such studies, this review will discuss only those two non-MHC candidate gene associations that have received widespread independent confirmation, including by unbiased GWAS.
Kemp et al. [42] reported the first vitiligo non-MHC candidate gene association with CTLA4, which encodes a T-cell co-receptor involved in regulation of T-cell activation and which is associated with several of the other autoimmune diseases that are epidemiologically associated with vitiligo. In fact, CTLA4 association was strongest in vitiligo patients who also had other concomitant autoimmune diseases [43], a finding subsequently replicated by another study and meta-analysis [44]. Association of CTLA4 with vitiligo has been variable among studies of different populations, but at least in European-derived whites has been demonstrated by GWAS.
A second important non-MHC candidate gene association, also reported by Kemp [45], was with PTPN22, encoding LYP protein tyrosine phosphatase, which likewise has been genetically associated with many different autoimmune diseases. Again, this association was replicated in most other studies of European-derived whites [46,47], and by GWAS, but not in most other populations. Thus, along with HLA class II, CTLA4 and PTPN22 likely are two of the genes that underlie epidemiologic association of vitiligo with other autoimmune diseases, at least in European-derived whites.
Genomewide studies
Candidate gene analyses carry an intrinsic a priori bias by selection of genes for study. In contrast, genomewide analyses of polygenic, multifactorial diseases are in principle unbiased beyond the assumption that genetic factors play some role. There are three approaches to genomewide genetic analysis. Genomewide linkage analysis tests for co-segregation of polymorphic markers with disease within families with multiple affected relatives and across such families. Such families are uncommon, the genetic resolution of linkage is low, and the genetic analyses require several important assumptions that may not be correct. Genomewide association studies, the current “gold standard”, require large numbers of cases and controls, but are reasonably powerful, can detect many genotyping errors, can provide fine-mapping, can detect population outliers and correct for population stratification, can appropriately account for multiple-testing, and require independent replication and a stringent “genomewide significance” criterion (P < 5 × 10−8) to declare “discovery”. For reasons that are not clear, linkage and GWAS often do not detect the same genetic signals. Genomewide or exome DNA sequencing studies can be configured similarly to linkage or GWAS, but are far more expensive and have not yet been applied to vitiligo.
Genetic linkage studies
Initial linkage studies of vitiligo were not genomewide, focusing on the MHC and other specific candidate regions of the genome, and will not be discussed here. The first genomewide linkage study of vitiligo was indirect; Nath and co-workers mapped [48] a locus on chromosome 17p13 called they called SLEV1 in a subset of lupus families that also had relatives with vitiligo. Spritz and co-workers [49] subsequently confirmed the SLEV1 linkage signal by genomewide linkage analysis of vitiligo families in which various other autoimmune diseases also occurred, and that group eventually fine-mapped and identified the corresponding gene as NLRP1 [50], which encodes an inflammasome regulatory protein.
In a unique large European-derived white kindred with near autosomal dominant vitiligo, Spritz and co-workers [51,52] used genomewide linkage to map a locus they termed “Autoimmune Susceptibility 1” (AIS1) at chromosome 1p31.3–p32.2. That group subsequently identified the corresponding gene as FOXD3 [53], encoding a key regulator of melanoblast differentiation. This vitiligo kindred was found to segregate a private sequence variant in the FOXD3 promoter that up-regulated transcription in vitro, which would be expected to reduce melanoblast differentiation. Recently, Schunter and co-workers [54] identified another FOXD3 promoter variant associated with vitiligo that also increases transcriptional activity. Spritz and co-workers also mapped two additional vitiligo linkage signals in European-derived white vitiligo families, AIS2 on chromosome 7 and AIS3 on chromosomes 8 [49,52,55]. Specific genes corresponding to AIS2 and AIS3 have not yet been identified.
In parallel linkage studies of Han Chinese vitiligo families, Zhang and co-workers identified three loci, AIS4 on chromosome 4q12–q21 [56] and two unnamed loci on 6p21–p22 and 22q12 [57]. These investigators suggested that AIS4 might be PDGFRA [58], though this seems much less likely than KIT. The chromosome 6 locus may correspond to the MHC. And Ren et al. [59] found that the chromosome 22 locus may correspond to XBP1.
Genomewide association studies
The first GWAS of vitiligo was of a unique population isolate in Romania in which there is a very high prevalence of vitiligo and other autoimmune diseases [60]. This study identified association with a SNP within SMOC2 on chromosome 6q27, in close vicinity to IDDM8, a linkage and association signal for type 1 diabetes mellitus and rheumatoid arthritis [61].
The Spritz group has also carried out three successive GWAS of vitiligo of USA and European-derived whites [62–65]. As shown in Table 1, these analyses have identified confirmed associations of vitiligo with 48 distinct loci, altogether accounting for 22.5% of vitiligo heritability in European-derived whites, as well as several additional loci with suggestive significance [65]. About half of the confirmed vitiligo loci encode immunoregulatory proteins, consistent with the autoimmune nature of vitiligo, a number of others encode regulators of apoptosis, and at least six encode either melanocyte components or regulators of melanocyte function. Of this last group, all have also been implicated in both normal pigmentary variation and risk of melanoma, and all show a remarkable inverse genetic relationship between vitiligo risk and melanoma risk [62,63,65], suggesting that vitiligo may result from dysregulation of a normal mechanism of immune surveillance for melanoma [66,67]. Many of these proteins encoded by the confirmed vitiligo genes interact directly in functional biological pathways that are key to vitiligo pathogenesis (Figure 1), suggesting that a majority of the pathways involved in vitiligo susceptibility may have already been discovered.
Table 1.
Chr. | Locus | Protein | Function |
---|---|---|---|
1 | RERE | Arginine-Glutamic acid dipeptide repeats | regulator of apoptosis |
1 | PTPN22 | protein tyrosine phosphatase, non-receptor type | alters responsiveness of T cell receptors |
1 | FASLG | FAS ligand | regulator of immune apoptosis |
1 | PTPRC | protein tyrosine phosphatase, receptor type C | regulator of T- and B-cell antigen receptor signaling |
2 | PPP4R3B | protein phosphatase 4 regulatory subunit 3B | Unknown |
2 | BCL2L11? | BCL2 like 11 | regulator of apoptosis in thymocyte negative selection |
2 | IFIH1 | interferon induced with helicase C domain 1 | innate immune receptor |
2 | CTLA4 | cytotoxic T-lymphocyte-associated protein 4 | T lymphocyte checkpoint regulator |
2 | FARP2-STK25 | ? | ? |
3 | UBE2E2 | ubiquitin-conjugating enzyme E2 E2 | Protein ubiquitination pathway; damage response |
3 | FOXP1 | forkhead box protein P1 | transcriptional regulator of B-cell development |
3 | CD80 | T-lymphocyte activation antigen CD80 | T-cell co-stimulatory signal |
3 | LPP | lipoma-preferred partner | Unknown |
3 | FBXO45-NRROS | ? | ? |
4 | PPP3CA | Serine/threonine-protein phosphatase 2B catalytic subunit alpha isoform |
T lymphocyte calcium-dependent, calmodulin-stimulated protein phosphatase |
6 | IRF4 | interferon regulatory factor 4 | transcriptional activator in immune cells and melanocytes |
6 | SERPINB9 | serpin B9 | endogenous inhibitor of granzyme B |
6 | HLA-A | HLA class I histocompatibility antigen, A | presents peptide antigens to the immune system |
6 | HLA-DRB1/DQA1 | HLA class II histocompatibility antigens, DRB1 and DQA1 |
present peptide antigens to the immune system |
6 | BACH2 | BTB domain and CNC homolog 2 | transcriptional activator, regulator of apoptosis |
6 | RNASET2-FGFR1OP-CCR6 | ? | ? |
7 | CPVL | probable serine carboxypeptidase CPVL | inflammatory protease; trims antigens for presentation |
8 | SLA | Src-like-adapter | regulator of T cell antigen receptor signaling |
9 | NEK6 | NIMA-related serine/threonine-protein kinase Nek6 | regulator of apoptosis |
10 | IL2RA | interleukin-2 receptor subunit alpha | IL2 receptor; regulates regulator T lymphocytes |
10 | ARID5B | AT-rich interactive domain-containing protein 5B | transcriptional co-activator |
10 | ZMIZ1 | zinc finger MIZ domain-containing protein 1 | possible PIAS-family transcriptional or sumoylation regulator |
10 | CASP7 | caspase-7 | apoptosis executor protein |
11 | CD44 | CD44 antigen | regulator of FOXP3 expression |
11 |
PPP1R14B-PLCB3-BAD-GPR137-KCNK4- TEX40-ESRRA-TRMT112-PRDX5 |
? | ? |
11 | TYR | Tyrosinase | melanocyte melanogenic enzyme; vitiligo autoantigen |
11 | Gene desert | ? | ? |
12 | PMEL | pre-melanosome protein PMEL | melanocyte melanosomal type I transmembrane glycoprotein |
12 | IKZF4 | zinc finger protein Eos | transcriptional repressor; regulates FOXP3 transcription in regulatory T lymphocytes |
12 | SH2B3 | SH2B adapter protein 3 | links T lymphocyte receptor activation signal to phospholipase C-gamma- 1, GRB2 and phosphatidylinositol 3-kinase |
13 | TNFSF11 | tumor necrosis factor ligand superfamily member 11 | T lymphocyte cytokine that binds to TNFRSF11A and TNFRSF11B |
14 | GZMB | granzyme B | apoptosis executioner protein of cytotoxic T lymphocytes |
15 | OCA2-HERC2 | oculocutaneous albinism 2 | melanocyte melanogenic protein; vitiligo autoantigen |
16 | MC1R | melanocortin 1 receptor | melanocyte melanogenic protein; vitiligo autoantigen |
17 | KAT2A-HSPB9-RAB5C | ? | ? |
18 | TNFRSF11A | tumor necrosis factor receptor superfamily member 11A |
regulates interactions between T lymphocytes and dendritic cells |
19 | TICAM1 | TIR domain-containing adapter molecule 1 | TLR3/TLR4 adapter; mediates NF-kappa-B and interferon-regulatory factor (IRF) activation; induces apoptosis |
19 | SCAF1-IRF3-BCL2L12 | ? | ? |
20 | RALY- ASIP | agouti signaling protein | regulator of melanocytes via MC1R |
20 | PTPN1 | tyrosine-protein phosphatase non-receptor type 1 | dephosphorylates JAK2 and TYK2 kinases; cellular response to interferon? |
21 | UBASH3A | ubiquitin-associated and SH3 domain-containing protein A |
promotes accumulation of activated T cell receptors on surface |
22 | C1QTNF6 | complement C1q tumor necrosis factor-related protein 6 |
Unknown |
22 | ZC3H7B-TEF | ? | ? |
X | IL1RAPL1 | Interleukin-1 receptor accessory protein-like 1 | Unknown |
X | CCDC22-FOXP3-GAGE | ? | FOXP3 regulates development and inhibitory function of regulatory T- lymphocytes |
Fine-mapping and functional analyses of these vitiligo loci identified in European-derived whites indicates that, for vitiligo as for other complex diseases, about half of causal variants appear to affect gene regulatory regions, while only about 15% are located within exons, many resulting in missense substitutions. The Spritz group has shown that for both MHC class I (HLA-A) [68,69] and MHC class II (HLA-DRB1/-DQA1) [70,71], the vitiligo-associated causal SNPs are located in transcriptional enhancer elements that up-regulate expression of the corresponding MHC genes, resulting in gain of function. Interestingly, the MHC class II association signal also constitutes a quantitative trait locus (QTL) for vitiligo age-of-onset [72]. For NLRP1, which encodes an inflammasome regulatory component, the vitiligo-associated causal SNPs constitute haplotypes of missense variants in almost complete linkage disequilibrium, which together synergize to result in constitutive gain of NLRP1 function and thus activation of interleukin-1 beta [73]. For GZMB, encoding granzyme B, an apoptotic effector protein used by cytotoxic T-cells to kill their targets, the causal vitiligo-associated SNP is a common missense variant R55Q [74] that alters GZMB function. For TYR, encoding tyrosinase, a key melanogenic enzyme and the major vitiligo autoimmune antigen, the vitiligo-associated SNPs are protective, and represent the missense variants S192Y and R402Q that are common in European-derived whites but not in other populations and which reduce thermal stability and catalytic function [75].
In addition to studies in European-derived whites, there have been several GWAS of vitiligo in Asian populations. Zhang and co-workers carried out a large GWAS of vitiligo in the Han and Uygur populations of China, detecting complex association signals in the class I and class II regions of the MHC and with the RNASET2-FGFR1OP-CCR6 region of chromosome 6q24 [76]. Deeper analysis of this GWAS [77] detected additional association signals in the region of PMEL, 10q22.1 and a nearby locus suggested to be ZMIZ1 [78], and 11q23.3. Of these associations in Chinese, only that in the RNASET2-FGFR1OP-CCR6 region corresponds to an association detected in Caucasian patients [63]. Indeed, while MHC class I and class II region associations were detected in Caucasians [62,65,68,69,71] and Chinese [76], the specific underlying associations appear to be somewhat different. This is surprising, as a GWAS of vitiligo in Japanese [79] detected an MHC class I association with HLA-A*02:01 that appears identical to that in European-derived whites, while an immunocentric GWAS of vitiligo in Asian Indian and Pakistani patients detected an MHC class II association that similar to that European-derived whites [80], though more detailed MHC analysis in Indians [81] found class II association that was the same as in Chinese [76]. A very small GWAS of vitiligo in Koreans [82] was severely underpowered, and detected no association signals that met the genomewide significance threshold.
Where are we now?
The main purpose of identifying genes associated with disease risk is that such genes are causal, providing solid starting points for defining pathobiological mechanisms and approaches to treatment. To date, approximately 50 different genetic loci have been discovered that contribute to risk of vitiligo, most in European-derived whites (Table 1). For most of these loci specific genes have been identified, which have moved us far along in our understanding of the biological causation of vitiligo. Almost all of the identified genes encode proteins involved in immunoregulation, apoptosis, and melanocyte function, underscoring the autoimmune basis of vitiligo, with dysregulated immune programming, cellular activation, and melanocyte target cell recognition and killing (Figure 1). Thus far, the vitiligo susceptibility genes that have been identified provide little or no support for various alternative non-autoimmunity theories that have been proposed for vitiligo causation, such as oxidative stress, neural mechanisms, melanocytorrhagy, and others.
As anticipated, many of the vitiligo susceptibility genes that encode proteins with immunoregulatory and apoptotic functions have also been associated with other autoimmune diseases with which vitiligo is epidemiologically associated (Figure 2). These shared genetic associations thus account for these long recognized clinical epidemiologic associations. Unexpectedly, however, most of vitiligo susceptibility genes that encode proteins involved in melanocyte function have also been associated with melanoma, and in some cases nonmelanoma skin cancers, in each case involving the same associated SNPs, but with opposite effects. While the precise meaning of this observation is not yet clear, it suggests that vitiligo might involve a dysregulated mechanism that has evolved for immune surveillance for melanoma [66,67] and other skin cancers, consistent with the approximately threefold reduced incidence of melanoma and nonmelanoma skin cancers observed in patients with pre-existing vitiligo [83,84]. Alternatively, it might be that gene variants that reduce skin pigmentation elevate risk for all forms of skin cancer, melanoma and nonmelanoma.
Most vitiligo susceptibility genes have been detected in European-derived whites. Some of these genes likewise contribute to vitiligo risk in Asian populations, whereas others apparently do not. In European-derived whites, altogether the identified genes and gene variants account for about 25% of total vitiligo genetic risk. It remains unknown whether the remainder of risk is attributable to additional unknown variation in these same genes, to additional unknown genes that exert smaller effects, to genetic interactions that potentiate gene effects, or to other causes. Understanding this will be essential to achieve personalized medicine for vitiligo, enabling reasonably accurate prediction of risks and classification of patients into genetically-based subgroups that may benefit from specialized approaches to vitiligo treatment or even prevention.
Key Points.
Vitiligo is a “complex disorder” (also termed polygenic and multifactorial), reflecting simultaneous contributions of multiple genetic risk factors and environmental triggers.
Large-scale genome-wide association studies, principally in European-derived whites and in Chinese, have discovered approximately 50 different genetic loci that contribute to vitiligo risk, some of which also contribute to other autoimmune diseases that are epidemiologically associated with vitiligo. At many of these vitiligo susceptibility loci the corresponding relevant genes have now been identified, and for some of these genes the specific DNA sequence variants that contribute to vitiligo risk are also now known.
A large fraction of these genes encode proteins involved in immune regulation, a number of others play roles in cellular apoptosis, and still others are involved in regulating functions of melanocytes.
While many of the specific biologic mechanisms through which these genetic factors operate to cause vitiligo remain to be elucidated, it is now clear that vitiligo is an autoimmune disease involving a complex relationship between programming and function of the immune system, aspects of the melanocyte autoimmune target, and dysregulation of the immune response.
Acknowledgments
They received no funding for writing this manuscript.
Footnotes
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