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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A region on chromosome 17 has been associated with a range of epidemiologically associated autoimmune and autoinflammatory diseases, including vitiligo. Using two sets of genetic markers and two ...groups of patients, the authors have implicated variants of
NALP1
in susceptibility to autoimmune disease.
Autoimmune and autoinflammatory diseases are a group of about 80 disorders that can involve almost any tissue, organ, or system.
1
A major source of illness and death, these diseases together affect 15 to 25 million people in the United States,
2
particularly women,
3
,
4
in whom they rank among the top 10 causes of death.
5
The risk of autoimmune and autoinflammatory diseases is thought to depend on interactions between environmental factors and specific variants of specific genes, some of which may confer a risk that an individual disease will develop, and others a risk that several different diseases will develop.
6
Indeed, . . .
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.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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.
The results of a genomewide association study of generalized vitiligo implicate genes involved in the immune response and also a variant of
TYR,
which encodes tyrosinase. This variant of
TYR
encodes ...a protein that seems particularly likely to be detected by immune surveillance.
The results of a genomewide association study of generalized vitiligo implicate genes involved in the immune response and also a variant of TYR, which encodes tyrosinase.
Generalized vitiligo is a disease in which patchy depigmentation of skin and hair results from autoimmune loss of melanocytes.
1
,
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It is a complex disorder involving multiple susceptibility genes and unknown environmental triggers. Genetic linkage and candidate-gene association studies have implicated several potentially contributory loci, though few have been consistently supported by the data.
3
Patients with generalized vitiligo have elevated frequencies of other autoimmune diseases, including autoimmune thyroid disease, rheumatoid arthritis, psoriasis, adult-onset type 1 diabetes, pernicious anemia, systemic lupus erythematosus, and Addison's disease,
4
suggesting that these diseases involve shared genetic components. To identify susceptibility loci for generalized vitiligo, we . . .
Deep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30–40% of known genetic syndromes. Here, we determine whether syndromes can be ...diagnosed from 3D images of human faces.
We analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images.
Unrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative.
Deep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of “unaffected” relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance.
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.
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.
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).
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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.
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