Tracey M. Ferrara

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.

Genome-Wide Association Study Reveals Multiple Loci Influencing Normal Human Facial Morphology

Numerous lines of evidence point to a genetic basis for facial morphology in humans, yet little is known about how specific genetic variants relate to the phenotypic expression of many common facial features. We conducted genome-wide association meta-analyses of 20 quantitative facial measurements derived from the 3D surface images of 3118 healthy individuals of European ancestry belonging to two US cohorts. Analyses were performed on just under one million genotyped SNPs (Illumina OmniExpress+Exome v1.2 array) imputed to the 1000 Genomes reference panel (Phase 3). We observed genome-wide significant associations (p < 5 x 10−8) for cranial base width at 14q21.1 and 20q12, intercanthal width at 1p13.3 and Xq13.2, nasal width at 20p11.22, nasal ala length at 14q11.2, and upper facial depth at 11q22.1. Several genes in the associated regions are known to play roles in craniofacial development or in syndromes affecting the face: MAFB, PAX9, MIPOL1, ALX3, HDAC8, and PAX1. We also tested genotype-phenotype associations reported in two previous genome-wide studies and found evidence of replication for nasal ala length and SNPs in CACNA2D3 and PRDM16. These results provide further evidence that common variants in regions harboring genes of known craniofacial function contribute to normal variation in human facial features. Improved understanding of the genes associated with facial morphology in healthy individuals can provide insights into the pathways and mechanisms controlling normal and abnormal facial morphogenesis.

Next-Generation DNA Re-Sequencing Identifies Common Variants of TYR and HLA-A that Modulate the Risk of Generalized Vitiligo via Antigen Presentation

TO THE EDITOR Generalized vitiligo (GV) is a common autoimmune disease resulting from the destruction of melanocytes in the involved areas, epidemiologically associated with elevated prevalence of certain other autoimmune diseases (Picardo and Taı̈eb, 2010). In a recent genome-wide association study (GWAS) of GV, carried out in European-derived whites (EUR), we identified 16 loci that contribute to GV risk (Jin et al., 2010a,b; Birlea et al., 2011). Within the major histocompatibility complex (MHC), a major GV association signal localized to HLA-A, in the class I gene region. Outside the MHC, the strongest GV association was with TYR, which encodes tyrosinase (TYR). At HLA-A, the most highly associated single-nucleotide polymorphism (SNP) was rs12206499 (P1⁄41.24 10 , odds ratio (OR)1⁄41.58), which tags HLA-A*02 (r1⁄40.964, D0 1⁄41.0) in the EUR population (Jin et al., 2010a). At TYR, the strongest association was with rs1393350 (P1⁄43.24 10 , OR1⁄4 0.65), which is in linkage disequilibrium (r1⁄40.79. D0 1⁄41) with a common nonsynonymous TYR variant, R402Q (rs1126809; Giebel et al., 1991). TYR is the major GV autoimmune antigen (Song et al., 1994), and TYR peptide antigens are predominantly presented on the melanocyte surface by HLA-A*02:01 (Brichard et al., 1993). The TYR R402Q substitution results in a temperaturesensitive tyrosinase TYR polypeptide (Tripathi et al., 1991) that is retained in the endoplasmic reticulum, is hypoglycosylated, and is preferentially degraded (Toyofuku et al., 2001). We therefore suggested that TYR R402Q might protect from GV by reducing the availability of TYR peptide for antigen presentation by HLA*02:01 (Jin et al., 2010a). To specifically define the HLA-A subtype associated with GV, we performed next-generation DNA re-sequencing of HLA-A exons 2, 3, and 4, which contain the sequence variations that define HLA-A subtypes (http://www.ebi.ac.uk/imgt/hla/), in 20 unrelated EUR GV patients. To maximize information, each patient was selected on the basis of homozygosity for rs12206499-G, which tags the GV-associated HLAA*02 type (r1⁄40.964, D0 1⁄41.0) in the EUR population (Jin et al., 2010a). As shown in Supplementary Table S1 online, of the 20 patients sequenced, 18 were homozygous HLA-A*02:01/ *02:01, 1 was heterozygous HLAA*02:01/*02:20:01, and 1 was HLAA*02:06:01/*02:30. (The allelic typing system does not distinguish between the common HLA-A*02:01:01:01 allele and the very rare HLAA*02:01:01:02L allele; to be conservative, here we represent these alleles using the standard four-digit nomenclature, HLA-A*02:01). This distribution of HLA-A*02 subtypes is similar to that in EUR control populations (http://www. ncbi.nlm.nih.gov/gv/mhc/main.cgi?cmd= init; http://www.allelefrequencies.net/), indicating that the predominant HLAA*02 GV risk subtype is HLA-A*02:01. To specifically identify TYR gene variants associated with GV, we carried out next-generation re-sequencing of 10.4 kb across the TYR locus, including 2.4 kb of promoter, the five exons and adjacent intron sequences, and 3.2 kb downstream, in 114 unrelated EUR GV patients. As shown in Supplementary Table S2 online, we identified 31 SNPs, with no indels or other rearrangements. Bioinformatic analyses predicted that only three of these are functionally significant. One, rs61754388 (T373K), is a known oculocutaneous albinism type 1 (OCA1) mutation (Spritz et al., 1990), seen in a single heterozygote, consistent with the expected carrier frequency of OCA1. The other two, rs1042602 (S192Y) and rs1126809 (R402Q), are common non-synonymous polymorphisms (Giebel and Spritz, 1990; Giebel et al., 1991) that occur almost exclusively in EUR populations (http://www.ncbi. nlm.nih.gov/projects/SNP/). In the GWAS, imputed rs1126809 genotypes demonstrated strongly protective association of the variant A allele with GV (P1⁄41.36 10 , OR1⁄4 0.65), whereas rs1042602 showed no association (P1⁄4 0.611, OR1⁄40.98). However, when both variants were considered simultaneously by logistic regression (Table 1A), rs1042602 was also significantly associated with GV (P1⁄41.23 10 ); when analyzed individually, association of rs1042602 was masked because its protective allele A is in linkage disequilibrium with the risk allele G of rs1126809; r between the two SNPs is 0.15. Furthermore, haplotype analysis of rs1042602 and rs1126809 (Table 1B) showed that, compared with the ancestral reference haplotype C-G, the other three rs1042602-rs1126809 variant haplotypes define a protective haplotypic series, the double-variant A-A haplotype reducing GV risk 3.7-fold: A-G, OR 0.83; C-A, OR 0.61; and A-A, OR 0.27. The overall

Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants

Vitiligo is an autoimmune disease in which depigmented skin results from the destruction of melanocytes, with epidemiological association with other autoimmune diseases. In previous linkage and genome-wide association studies (GWAS1 and GWAS2), we identified 27 vitiligo susceptibility loci in patients of European ancestry. We carried out a third GWAS (GWAS3) in European-ancestry subjects, with augmented GWAS1 and GWAS2 controls, genome-wide imputation, and meta-analysis of all three GWAS, followed by an independent replication. The combined analyses, with 4,680 cases and 39,586 controls, identified 23 new significantly associated loci and 7 suggestive loci. Most encode immune and apoptotic regulators, with some also associated with other autoimmune diseases, as well as several melanocyte regulators. Bioinformatic analyses indicate a predominance of causal regulatory variation, some of which corresponds to expression quantitative trait loci (eQTLs) at these loci. Together, the identified genes provide a framework for the genetic architecture and pathobiology of vitiligo, highlight relationships with other autoimmune diseases and melanoma, and offer potential targets for treatment.

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.

Autoimmune vitiligo is associated with gain-of-function by a transcriptional regulator that elevates expression of HLA-A*02:01 in vivo

Significance Vitiligo is an autoimmune disease in which spots of white skin and hair result from destruction of melanocytes. Vitiligo is associated with HLA-A*02:01, which presents multiple vitiligo melanocyte autoantigens. We localize vitiligo risk to a SNP haplotype 20 kb downstream of the HLA-A gene, spanning a transcriptional regulatory element. Blood cells from healthy subjects carrying the high-risk haplotype expressed more HLA-A RNA than subjects carrying only nonhigh-risk haplotypes. Vitiligo risk in the MHC class I region thus derives from combined quantitative and qualitative phenomena: an SNP haplotype in a transcriptional regulator that induces elevated expression of HLA-A RNA in vivo, and strong linkage disequilibrium with an HLA-A allele that confers *02:01 specificity. These combine to increase HLA-A2 available to present melanocyte autoantigens. HLA-A is a class I major histocompatibility complex receptor that presents peptide antigens on the surface of most cells. Vitiligo, an autoimmune disease in which skin melanocytes are destroyed by cognate T cells, is associated with variation in the HLA-A gene; specifically HLA-A*02:01, which presents multiple vitiligo melanocyte autoantigens. Refined genetic mapping localizes vitiligo risk in the HLA-A region to an SNP haplotype ∼20-kb downstream, spanning an ENCODE element with many characteristics of a transcriptional enhancer. Convergent CTCF insulator sites flanking the HLA-A gene promoter and the predicted transcriptional regulator, with apparent interaction between these sites, suggests this element regulates the HLA-A promoter. Peripheral blood mononuclear cells from healthy subjects homozygous for the high-risk haplotype expressed 39% more HLA-A RNA than cells from subjects carrying nonhigh-risk haplotypes (P = 0.0048). Similarly, RNAseq analysis of 1,000 Genomes Project data showed more HLA-A mRNA expressed in subjects homozygous for the high-risk allele of lead SNP rs60131261 than subjects homozygous for the low-risk allele (P = 0.006). Reporter plasmid transfection and genomic run-on sequence analyses confirm that the HLA-A transcriptional regulator contains multiple bidirectional promoters, with greatest activity on the high-risk haplotype, although it does not behave as a classic enhancer. Vitiligo risk associated with the MHC class I region thus derives from combined quantitative and qualitative phenomena: a SNP haplotype in a transcriptional regulator that induces gain-of-function, elevating expression of HLA-A RNA in vivo, in strong linkage disequilibrium with an HLA-A allele that confers *02:01 specificity.

Risk of Generalized Vitiligo Is Associated with the Common 55R-94A-247H Variant Haplotype of GZMB (Encoding Granzyme B)

Generalized vitiligo (GV) is characterized by autoimmune destruction of melanocytes by skin-homing cytotoxic T-cells (CTLs) that target melanocyte autoantigens. Two recent genomewide association studies (GWAS) of GV in European-derived whites (EUR) have demonstrated genetic association with GZMB, encoding granzyme B, a marker of activated CTLs that mediates target-cell apoptosis, as well as autoantigen activation and consequent initiation and propagation of autoimmunity. Here, we describe detailed genetic analyses of the GZMB region of chromosome 14q12 to identify genetic variation potentially causal for GV, implicating two non-synonymous SNPs in strong linkage disequilibrium that comprise part of a common multi-variant high-risk haplotype, rs8192917-C— rs11539752-C (55R-94A). To identify possible uncommon deleterious variants that might “hitchhike” on the high-risk haplotype, we then carried out “next-generation” DNA re-sequencing of GZMB in 114 EUR GV patients. Overall, our findings support a direct causal role for the GZMB rs8192917-C—rs11539752-C haplotype (55R-94A) in the pathogenesis of GV.

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.

Body size and allometric variation in facial shape in children

OBJECTIVES Morphological integration, or the tendency for covariation, is commonly seen in complex traits such as the human face. The effects of growth on shape, or allometry, represent a ubiquitous but poorly understood axis of integration. We address the question of to what extent age and measures of size converge on a single pattern of allometry for human facial shape. METHODS Our study is based on two large cross-sectional cohorts of children, one from Tanzania and the other from the United States (N = 7,173). We employ 3D facial imaging and geometric morphometrics to relate facial shape to age and anthropometric measures. RESULTS The two populations differ significantly in facial shape, but the magnitude of this difference is small relative to the variation within each group. Allometric variation for facial shape is similar in both populations, representing a small but significant proportion of total variation in facial shape. Different measures of size are associated with overlapping but statistically distinct aspects of shape variation. Only half of the size-related variation in facial shape can be explained by the first principal component of four size measures and age while the remainder associates distinctly with individual measures. CONCLUSIONS Allometric variation in the human face is complex and should not be regarded as a singular effect. This finding has important implications for how size is treated in studies of human facial shape and for the developmental basis for allometric variation more generally.