Risk of generalized vitiligo is associated with the common 55R-94A-247H variant haplotype of GZMB (encoding granzyme B).

In generalized vitiligo (GV), patches of depigmented skin and overlying hair (Picardo and Taieb, 2010) result from autoimmune destruction of melanocytes by skin-homing auto-reactive cytotoxic T-lymphocytes (CTLs) (Ogg et al., 1998). In two genome-wide association studies (GWAS) to identify GV susceptibility loci in European-derived white (EUR) patients (GWAS1, GWAS2; Jin et al., 2010, 2012) we detected association with GZMB, encoding granzyme B, a serine protease marker of activated CTLs (Sattar et al., 2003). In concert with perforin, GZMB mediates direct and caspase-mediated apoptosis of target cells (Granville, 2010; Ewen et al., 2012), as well as proteolytic cleavage of autoantigens, creating or exposing autoimmune epitopes that may initiate or propagate the autoimmune process (Darrah and Rosen, 2010). Meta-analysis of GWAS1, GWAS2, and replication study data for SNPs genotyped in the GZMB region (Jin et al., 2012) showed greatest association with rs8192917-C (P = 5.60 × 10−9, OR 1.22), a common non-synonymous SNP (R55Q) that is in very strong linkage disequilibrium with two other common non-synonymous SNPs, rs11539752 (P94A; r2 = 0.99) and rs2236338 (Y247H; r2 = 0.93). Together, these three variants define two predominant haplotypic multi-variant GZMB polypeptide isoforms 55Q-94P-247Y (termed “QPY”) versus 55R-94A-247H (“RAH”) (McIlroy et al., 2003; Zaitsu et al., 2004). To carry out higher-resolution analysis of association of GV with SNPs in the GZMB region, we first imputed genotypes for all SNPs in the 1000 Genomes Project phase 1 integrated variant call set (June 21, 2012 release) across the 160 kb region (chr14:25045130-25204958) showing even nominal association with GV in the combined GWAS1 and GWAS2 dataset (Jin et al., 2010, 2012), from 101.5 kb upstream of GZMB through 55 kb downstream. After quality control procedures, there were 464 genotyped or imputed SNPs in 7202 total subjects (Supplementary Table S1 online). In this analysis, the most significant SNP was rs10909625 (P = 1.03 × 10−8), a synonymous variant at codon K80 (Table 1). To determine which SNPs in the GZMB region might be causal for GV susceptibility, we then carried out logistic regression, individually testing each of 463 SNPs conditional on rs10909625. This analysis indicated there is only one primary association signal in the GZMB region, represented by nine SNPs (Table 1) whose effects cannot be distinguished (Supplementary Table 2) due to very strong linkage disequilibrium (Supplementary Figure 1). These include rs8192917 (R55Q) and rs11539752 (P94Q); none of the other seven primary associated SNPs (rs6573910, rs6573911, rs45628336, rs113822535, rs45442494, rs1126639, rs10909625) are predicted to have functional consequences. In contrast, the associations of rs2236338 (Y247H), as well as that of another potentially functional SNP rs2273844 (stop codon within the 5′ untranslated region), were found to be secondary. Table 1 Association of GV with SNPs in the GZMB region of chromosome 14q12 Analysis of the haplotypes defined by the three non-synonymous SNPs rs8192917-rs11539752-rs2236338 similarly indicated that principal association with GV is with the haplotype comprised of rs8192917-C—rs11539752-C. As shown in Table 2, this constitutes the higher-risk haplotype (OR 1.27; P = 4.42 × 10−8), compared to the haplotype that also includes the high-risk G allele of rs2236338 (OR 1.26; P = 3.26 × 10−7). Nevertheless, it is difficult to completely exclude any effect of rs2236338, as the haplotypes containing this SNP (C-C-G and C-C-A) are also associated with elevated risk for GV. Table 2 Analysis of haplotypes of GZMB non-synonymous SNPs rs8192917 (R55Q), rs11539752 (P94A), and rs2236338 (Y247H) Genotypes of a number of uncommon (MAF < 0.01) potentially functional SNPs in the GZMB region could not be imputed with high confidence (MaCH r2 < 0.3). To assess whether association of GV with GZMB might result from rare deleterious variants “hitchhiking” on the most associated haplotype of common SNPs, we therefore carried out next-generation DNA re-sequencing of a total 8.3 kb across the GZMB locus, spanning 3.2 kb upstream of the gene, the five exons and intervening sequences (with a single 783 nt gap within intervening sequence 1), to 3.1 kb downstream, in 114 unrelated EUR GV patients from GWAS1 (Jin et al., 2010). As shown in Supplementary Table S3 online, in these 228 alleles we observed a total of 41 variants. In addition to the three aforementioned common non-synonymous SNPs, we observed one additional rare non-synonymous SNP, rs185979723 (M225L) in a single heterozygote, predicted to be functionally benign. There were no nonsense, frameshift, or splice junction mutations, and no indels or other apparent rearrangements. We also observed five previously unreported variants intergenic and intronic variants, none of which were of predicted functional significance. Our findings thus suggest a major role for the common rs8192917-C—rs11539752-C (rs2236338-G) haplotype in genetic association of GZMB with GV, with no evidence for a major contributation attributable to rare causal variants. The mechanism by which the GZMB rs8192917-C—rs11539752-C—(rs2236338-G) haplotype increases GV risk is not yet known, as functional correlates of the corresponding 55R-94A-(247H) and 55Q-94P-(247Y) GZMB protein variant isoforms remain uncertain. Individually, the R55Q, A94P, and Y247H substitutions are each predicted to be benign (not shown); however, in silico functional predictions of individual amino acid variants are of unknown validity in the context of such multi-variant haplotypes. We speculate that the 55R-94A-247H and 55R-94A-247Y GZMB polypeptides may both increase risk of GV, the former perhaps to a greater degree than the latter. The GZMB QPY and RAH alleles exhibit similar expression, stability, and proteolytic activity of the corresponding alternative GZMB polypeptide isoforms (McIlroy et al., 2003). However, there have been conflicting claims regarding their possible differential effects on CTL effector functions. Homozygotes for the rs8192917-T (55Q) allele have been reported to express a greater proportion of GZMB-positive cells after mitogen stimulation (Girnita et al., 2009), while two studies reported reduced apoptotic induction by RAH versus QPY GZMB (McIlroy et al., 2003; Gaafar et al., 2009), and another found no difference (Sun et al., 2004). Regardless, we cannot exclude the alternative possibility that association of all GZMB coding variants with GV is secondary to LD with an as-yet unidentified causal non-coding SNP. GZMB has not been genetically associated with other autoimmune diseases, specifically including juvenile idiopathic arthritis (Donn et al., 2008) and Behcet’s disease (Kucuksezer et al., 2009). This suggests the possibility that GZMB may be relatively specific for melanocyte-directed autoimmune susceptibility. In addition to the effector function of GZMB in target cell killing by CTLs, perhaps particularly relevant to GV may be the role played by GZMB cleavage in activating autoantigens in autoimmune disease (Darrah and Rosen, 2010). GZMB cleaves target proteins at aspartic acid residues (Odake et al., 1991), including both caspases associated with induction of apoptosis and most target cell autoantigens, potentially enhancing presentation of cryptic epitopes and leading to activation of self reactive T-cells (Sercarz et al., 1993). GZMB cleavage sites of GV melanocyte autoantigens have not yet been defined experimentally. However, in silico analysis of the principal human GV autoantigens using GRASVM 1.0 (Wee et al., 2011) predicts one high-probability GZMB cleavage site in each of TYR and TYRP1, three in TYRP2, two in SOX10, one in PMEL, and none in MC1R. These findings thus suggest that in vivo GZMB cleavage of melanocyte proteins that constitute GV autoantigens may contribute to initiation and propagation of autoimmunity directed against melanocytes.