Sheri L. Riccardi

Variant of TYR and Autoimmunity Susceptibility Loci in Generalized Vitiligo

BACKGROUND Generalized vitiligo is an autoimmune disease characterized by melanocyte loss, which results in patchy depigmentation of skin and hair, and is associated with an elevated risk of other autoimmune diseases. METHODS To identify generalized vitiligo susceptibility loci, we conducted a genomewide association study. We genotyped 579,146 single-nucleotide polymorphisms (SNPs) in 1514 patients with generalized vitiligo who were of European-derived white (CEU) ancestry and compared the genotypes with publicly available control genotypes from 2813 CEU persons. We then tested 50 SNPs in two replication sets, one comprising 677 independent CEU patients and 1106 CEU controls and the other comprising 183 CEU simplex trios with generalized vitiligo and 332 CEU multiplex families. RESULTS We detected significant associations between generalized vitiligo and SNPs at several loci previously associated with other autoimmune diseases. These included genes encoding major-histocompatibility-complex class I molecules (P=9.05x10(-23)) and class II molecules (P=4.50x10(-34)), PTPN22 (P=1.31x10(-7)), LPP (P=1.01x10(-11)), IL2RA (P=2.78x10(-9)), UBASH3A (P=1.26x10(-9)), and C1QTNF6 (P=2.21x10(-16)). We also detected associations between generalized vitiligo and SNPs in two additional immune-related loci, RERE (P=7.07x10(-15)) and GZMB (P=3.44x10(-8)), and in a locus containing TYR (P=1.60x10(-18)), encoding tyrosinase. CONCLUSIONS We observed associations between generalized vitiligo and markers implicating multiple genes, some associated with other autoimmune diseases and one (TYR) that may mediate target-cell specificity and indicate a mutually exclusive relationship between susceptibility to vitiligo and susceptibility to melanoma.

Genome-wide association analyses identify 13 new susceptibility loci for generalized vitiligo

We previously reported a genome-wide association study (GWAS) identifying 14 susceptibility loci for generalized vitiligo. We report here a second GWAS (450 individuals with vitiligo (cases) and 3,182 controls), an independent replication study (1,440 cases and 1,316 controls) and a meta-analysis (3,187 cases and 6,723 controls) identifying 13 additional vitiligo-associated loci. These include OCA2-HERC2 (combined P = 3.80 × 10−8), MC1R (P = 1.82 × 10−13), a region near TYR (P = 1.57 × 10−13), IFIH1 (P = 4.91 × 10−15), CD80 (P = 3.78 × 10−10), CLNK (P = 1.56 × 10−8), BACH2 (P = 2.53 × 10−8), SLA (P = 1.58 × 10−8), CASP7 (P = 3.56 × 10−8), CD44 (P = 1.78 × 10−9), IKZF4 (P = 2.75 × 10−14), SH2B3 (P = 3.54 × 10−18) and TOB2 (P = 6.81 × 10−10). Most vitiligo susceptibility loci encode immunoregulatory proteins or melanocyte components that likely mediate immune targeting and the relationships among vitiligo, melanoma, and eye, skin and hair coloration.

Common variants in FOXP1 are associated with generalized vitiligo

In a recent genome-wide association study of generalized vitiligo, we identified ten confirmed susceptibility loci. By testing additional loci that showed suggestive association in the genome-wide study, using two replication cohorts of European descent, we observed replicated association of generalized vitiligo with variants at 3p13 encompassing FOXP1 (rs17008723, combined P = 1.04 × 10−8) and with variants at 6q27 encompassing CCR6 (rs6902119, combined P = 3.94 × 10−7).

Genome-Wide Analysis Identifies a Quantitative Trait Locus in the MHC Class II Region Associated with Generalized Vitiligo Age of Onset

Generalized vitiligo is a common autoimmune disease in which acquired patchy depigmentation of skin, hair, and mucous membranes results from loss of melanocytes from involved areas. Previous genetic analyses have focused on vitiligo susceptibility, and have identified a number of genes involved in disease risk. Age of onset of generalized vitiligo also involves a substantial genetic component, but has not previously been studied systematically. In this study, we report a genome-wide association study of vitiligo age of onset in 1,339 generalized vitiligo patients, with replication in an independent cohort of 677 cases. We identified a quantitative trait locus for vitiligo age of onset in the major histocompatibility complex (MHC) class II region, located near c6orf10-BTNL2 (rs7758128; P=8.14 × 10(-11)), a region that is also associated with generalized vitiligo susceptibility. In contrast, there was no association of vitiligo age of onset with any other MHC or non-MHC loci that are associated with vitiligo susceptibility. These findings highlight the differing roles played by genes involved in vitiligo susceptibility versus vitiligo age of onset, and illustrate that genome-wide analyses can be used to identify genes involved in quantitative aspects of disease natural history, as well as disease susceptibility per se.

Genomewide Association Study of African Children Identifies Association of SCHIP1 and PDE8A with Facial Size and Shape

The human face is a complex assemblage of highly variable yet clearly heritable anatomic structures that together make each of us unique, distinguishable, and recognizable. Relatively little is known about the genetic underpinnings of normal human facial variation. To address this, we carried out a large genomewide association study and two independent replication studies of Bantu African children and adolescents from Mwanza, Tanzania, a region that is both genetically and environmentally relatively homogeneous. We tested for genetic association of facial shape and size phenotypes derived from 3D imaging and automated landmarking of standard facial morphometric points. SNPs within genes SCHIP1 and PDE8A were associated with measures of facial size in both the GWAS and replication cohorts and passed a stringent genomewide significance threshold adjusted for multiple testing of 34 correlated traits. For both SCHIP1 and PDE8A, we demonstrated clear expression in the developing mouse face by both whole-mount in situ hybridization and RNA-seq, supporting their involvement in facial morphogenesis. Ten additional loci demonstrated suggestive association with various measures of facial shape. Our findings, which differ from those in previous studies of European-derived whites, augment understanding of the genetic basis of normal facial development, and provide insights relevant to both human disease and forensics.

Fine-Mapping of Vitiligo Susceptibility Loci on Chromosomes 7 and 9 and Interactions with NLRP1 (NALP1)

Generalized vitiligo is the most common pigmentation disorder, the result of autoimmune loss of melanocytes from the skin and hair, with a high frequency of other autoimmune diseases in vitiligo patients and their relatives. We previously reported the linkage signals on chromosomes 1, 7, and 17 in Caucasian families with generalized vitiligo and associated autoimmune diseases and identified the risk loci of chromosomes 17 and 1 as NLRP1 (NALP1) and FOXD3, respectively. Here, we describe fine-scale genetic association analyses in two independent series of Caucasian multiplex families, refining localization of the chromosome 7 locus and a locus on chromosome 9. Three susceptibility signals, represented by single-nucleotide polymorphisms (SNPs) rs6960920 in 7p13, rs734930 in 7q11, and rs4744411 in 9q22, were significantly associated with vitiligo and other autoimmune diseases. We also detected significant three-way interaction effects of chromosome 7 SNP rs6960920, chromosome 9 SNP rs4744411, and NLRP1 SNP rs6502867 on both the vitiligo phenotype and an expanded autoimmune disease phenotype, and significant three-way interaction effects of both chromosome 7 SNPs and NLRP1 SNP rs6502867 on the vitiligo phenotype. These support the validity of the chromosomes 7 and 9 linkage/association signals and underscore the utility of gene-gene interaction analysis in characterizing the genetic effects of candidate association signals.

Analysis of genomewide association signals for nonsyndromic cleft lip/palate in a Kenya African cohort

Nonsyndromic cleft lip with or without cleft palate is a common birth defect with a wide range of prevalence among different populations, apparently highest in Asians and Amerindians and lowest in Africans. Recent genomewide association studies of European‐derived and Asian populations have identified six confirmed loci for this phenotype: 1p22.1, 1q32.2 (IRF6), 8q24, 10q25.3, 17q22, and 20q12. However, there have thus far been no studies of these loci in African patients with nonsyndromic cleft lip with or without cleft palate. We carried out association analysis of SNPs in these six candidate chromosomal regions in 128 nonsyndromic cleft lip with or without cleft palate cases and 105 controls from the Rift Valley of Kenya. We observed no apparent association of this phenotype with any of these SNPs, though there was strong statistical power only for 8q24. These results indicate that at least the 8q24 locus does not play a major role in the pathogenesis of nonsyndromic cleft lip with or without cleft palate in east Africa, supporting locus heterogeneity for susceptibility to this phenotype among different major populations of the world.

Association of generalized vitiligo with MHC class II loci in patients from the Indian subcontinent.

TO THE EDITOR Generalized vitiligo is a disease in which patches of depigmented skin and overlying hair result from autoimmune destruction of melanocytes in involved regions (Spritz, 2012). Clinic-based studies cite high prevalence of vitiligo in India, up to 8.8% (e.g. Handa and Kaur, 1999), though population-based surveys report much lower prevalence, 0.46% in Calcutta (Das et al., 1985) and 1.79% in South Gujarat (Mehta et al., 1973). Vitiligo is a distressing cosmetic problem in individuals of dark skin phototypes, due to striking contrast between lesions and unaffected skin. This may explain the reported high prevalence of vitiligo in India and negative impact on perceived quality of life in this population (Parsad et al., 2003). Indeed, vitiligo has long been recognized in India (Singh et al., 1974), the specific use of ultraviolet light treatment was pioneered in India (Menon, 1945), and some of the earliest genetic studies of vitiligo were carried out there: of ABO blood groups, α1-antitrypsin, and haptoglobin, and subsequent candidate gene studies, including GCH1, ACE, CAT, CTLA4, GPX1, IL4, MBL2, and PTPN22, most yielding negative or conflicting results. Recently, Singh et al. (2012) tested genetic association of vitiligo in Indian patients with HLA–A, -B, -C in the MHC class I region and HLA-DRB1 in the class II region, identifying primary genetic association with HLA-DRB1* 07:01. Here, we describe a more comprehensive genetic association study of generalized vitiligo on the Indian subcontinent, utilizing the Immunochip® (Cortes and Brown, 2011) to screen 196,524 SNPs in 128 loci previously implicated in autoimmune and inflammatory diseases, including 9441 SNPs spanning the extended major histocompatibility complex (MHC) on chromosome 6p. Our results suggest there are at least two independent association signals in the MHC class II region, one located upstream of HLA-DRA and the other located between HLA-DRB1 and HLA-DQA1, generally similar to what we previously found in a genomewide association study of vitiligo in European-derived whites (EUR) (Jin et al., 2010). Our initial study group consisted of 255 patients with generalized vitiligo and 377 unrelated non-vitiligo controls of Indian subcontinent (Pakistan, India, Sri Lanka, Bangladesh) derivation. After quality control procedures, data for 120,724 remaining SNPs from 251 remaining cases were compared to those from 349 remaining controls. Suggestive association signals were considered as clusters of nearby SNPs with trend P-values <10−5. The International Immunochip Consortium has agreed on a genomewide significance criterion of P<5 × 10−8 for studies utilizing the Immunochip (Cortes and Brown, 2011). As shown in Figure 1a and Supplementary Table S1, the only highly suggestive association signals were in the MHC class II gene region (Figure 1b), from rs3134942 (chr6:32168770) to rs2856674 (chr6:32659644), spanning the upstream part of NOTCH4 through HLA-DQB1. The principal region of association encompassed c6orf10--BTNL2--HLA-DRA--HLA-DRB5--HLA-DRB1--HLA-DQA1 (Figure 1b), with extensive LD through this region in this population (Figure 1c). One SNP, rs482044, located towards the centromeric end of the region, between HLA-DRB1 and HLA-DQA1, achieved genomewide significance (G allele; P=1.94 × 10−8, OR=1.93; Table 1), remaining significant (P = 4.86 × 10−8) even after correction for the observed genomic inflation factor λ = 1.06. Figure 1 Immunochip association results for generalized vitiligo Table 1 MHC class II region SNPs genotyped in Immunochip screening and in replication studies To determine which SNPs in the MHC class II region represent primary association with vitiligo versus are signals secondary to LD, we applied a backward regression procedure, comparing a model including the seven most significant MHC class II SNPs to alternative models in which each SNP was removed one by one. This analysis suggested that this region contains two independent associated loci, one represented by rs482044-G (located between HLA-DRB1 and HLA-DQA1) and the other represented by rs3129859-C (located 6680 nt upstream of HLA-DRA). Forward regression analysis of these two SNPs showed that the model composed of rs3129859 was significantly (P=4.4 × 10−5) improved by adding rs482044, and that the model composed of rs482044 was significantly improved (P=6.0 × 10−4) by adding rs3129859. In contrast to our previous findings in EUR (Jin et al., 2010), we observed no apparent association of vitiligo with SNPs in the MHC class I region in this Indian-Pakistani population (Figures 1a and 1b). Furthermore, considering loci represented on the Immunochip that have been reported to be associated with vitiligo in previous candidate gene studies from India, no SNPs in the ACE (3 SNPs), CTLA4 (505 SNPs), or IL4 (103 SNPs) gene regions showed even nominal association in the present study. To confirm association of generalized vitiligo with MHC class II region SNPs in the Indian subcontinent, we carried out a replication study of rs3129859 and rs482044, as well as the third most significant Immunochip SNP, rs3096691 (located just upstream of NOTCH4) (Fig. 1b). These three SNPs were genotyped in 685 unrelated generalized vitiligo cases and 774 unrelated controls from Gujarat state, India. All three were in Hardy-Weinberg equilibrium in the controls, and all three achieved at least nominal significance in the replication study (Table 1). Most significant association in the replication study was observed for rs3129859-C (P=9.48 × 10−9), with no significant heterogeneity of OR between the two studies (PBreslow-Day=1.15 × 10−1). Cochran-Mantel-Haenszel meta-analysis of the rs3129859 data from the Immunochip screen and replication study likewise yielded strongest overall association (P=4.30 × 10−14, OR=1.67; 95% C.I. 1.46–1.91). Association was also confirmed in the replication study for rs482044 (P= 1.11 × 10−4), with only nominal association for rs3096691 (P=2.32 × 10−2), although both of these SNPs exhibited heterogeneity of OR. Both rs482044 (P=1.58 × 10−2) and rs3129859 (P = 1.20 × 10−6) remained significant when each was conditioned on the other. Overall, our findings thus generally confirm association of vitiligo with at least two independent loci in the MHC class II region. In a previous genomewide-association study of generalized vitiligo in EUR subjects, we found that both vitiligo susceptibility (Jin et al., 2010) and age of onset (Jin et al., 2011) are likewise associated with at least two independent loci in the MHC class II region. To assess whether the MHC class II loci observed in the Indian subcontinent and EUR populations might correspond ancestrally, we carried out trans-ethnic meta-analysis using MANTRA (Morris, 2011), which indicated that the MHC association signal represented by rs482044 in the Indian subcontinent population apparently corresponds to the MHC signal represented by rs532098 in EUR (Jin et al., 2010) (Table S2). In contrast, rs3129859 is not significantly associated with vitiligo in EUR (Jin et al., 2010), and correspondence between the association signals upstream of HLA-DRA observed in both populations remains uncertain. Our findings thus highlight both similarity and differences of vitiligo MHC genetic associations in subjects from different major world populations. On the Indian subcontinent, this study and that of Singh et al. (2012) support association of vitiligo with loci in the MHC class II region, but show no primary association in the MHC class I region. Similarly, in the EUR population, vitiligo is also associated with multiple signals in the MHC class II region, at least one of which, between HLA-DRB1 and HLA-DQA1, appear to correspond to one in the Indian subcontinent population. However, in the EUR population vitiligo shows primary association with HLA-A in the distal class I region (Jin et al., 2010); specifically, HLA-A*02:01 (Jin et al., 2011). In addition, studies in Chinese show principal MHC association in the class III region (Quan et al., 2010) and in the proximal class I region, between HLA-B and HLA-C (Liu et al., 2012). Together, these similarities and differences of principal MHC genetic associations with generalized vitiligo among different populations may in part underlie differing prevalence of this autoimmune disease in different groups around the world.

Human Facial Shape and Size Heritability and Genetic Correlations

The human face is an array of variable physical features that together make each of us unique and distinguishable. Striking familial facial similarities underscore a genetic component, but little is known of the genes that underlie facial shape differences. Numerous studies have estimated facial shape heritability using various methods. Here, we used advanced three-dimensional imaging technology and quantitative human genetics analysis to estimate narrow-sense heritability, heritability explained by common genetic variation, and pairwise genetic correlations of 38 measures of facial shape and size in normal African Bantu children from Tanzania. Specifically, we fit a linear mixed model of genetic relatedness between close and distant relatives to jointly estimate variance components that correspond to heritability explained by genome-wide common genetic variation and variance explained by uncaptured genetic variation, the sum representing total narrow-sense heritability. Our significant estimates for narrow-sense heritability of specific facial traits range from 28 to 67%, with horizontal measures being slightly more heritable than vertical or depth measures. Furthermore, for over half of facial traits, >90% of narrow-sense heritability can be explained by common genetic variation. We also find high absolute genetic correlation between most traits, indicating large overlap in underlying genetic loci. Not surprisingly, traits measured in the same physical orientation (i.e., both horizontal or both vertical) have high positive genetic correlations, whereas traits in opposite orientations have high negative correlations. The complex genetic architecture of facial shape informs our understanding of the intricate relationships among different facial features as well as overall facial development.

Rapid automated landmarking for morphometric analysis of three‐dimensional facial scans

Automated phenotyping is essential for the creation of large, highly standardized datasets from anatomical imaging data. Such datasets can support large‐scale studies of complex traits or clinical studies related to precision medicine or clinical trials. We have developed a method that generates three‐dimensional landmark data that meet the requirements of standard geometric morphometric analyses. The method is robust and can be implemented without high‐performance computing resources. We validated the method using both direct comparison to manual landmarking on the same individuals and also analyses of the variation patterns and outlier patterns in a large dataset of automated and manual landmark data. Direct comparison of manual and automated landmarks reveals that automated landmark data are less variable, but more highly integrated and reproducible. Automated data produce covariation structure that closely resembles that of manual landmarks. We further find that while our method does produce some landmarking errors, they tend to be readily detectable and can be fixed by adjusting parameters used in the registration and control‐point steps. Data generated using the method described here have been successfully used to study the genomic architecture of facial shape in two different genome‐wide association studies of facial shape.