Browsing by Author "Klein, Ophir D."

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    Large-scale open-source three-dimensional growth curves for clinical facial assessment and objective description of facial dysmorphism
    (Springer Nature, 2021-06-09) Matthews, Harold S.; Palmer, Richard L.; Baynam, Gareth S.; Quarrell, Oliver W.; Klein, Ophir D.; Spritz, Richard A.; Hennekam, Raoul C.; Walsh, Susan; Shriver, Mark; Weinberg, Seth M.; Hallgrimsson, Benedikt; Hammond, Peter; Penington, Anthony J.; Peeters, Hilde; Claes, Peter D.; Biology, School of Science
    Craniofacial dysmorphism is associated with thousands of genetic and environmental disorders. Delineation of salient facial characteristics can guide clinicians towards a correct clinical diagnosis and understanding the pathogenesis of the disorder. Abnormal facial shape might require craniofacial surgical intervention, with the restoration of normal shape an important surgical outcome. Facial anthropometric growth curves or standards of single inter-landmark measurements have traditionally supported assessments of normal and abnormal facial shape, for both clinical and research applications. However, these fail to capture the full complexity of facial shape. With the increasing availability of 3D photographs, methods of assessment that take advantage of the rich information contained in such images are needed. In this article we derive and present open-source three-dimensional (3D) growth curves of the human face. These are sequences of age and sex-specific expected 3D facial shapes and statistical models of the variation around the expected shape, derived from 5443 3D images. We demonstrate the use of these growth curves for assessing patients and show that they identify normal and abnormal facial morphology independent from age-specific facial features. 3D growth curves can facilitate use of state-of-the-art 3D facial shape assessment by the broader clinical and biomedical research community. This advance in phenotype description will support clinical diagnosis and the understanding of disease pathogenesis including genotype–phenotype relations.
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    Mapping genes for human face shape: Exploration of univariate phenotyping strategies
    (Public Library of Science, 2024-12-02) Yuan, Meng; Goovaerts, Seppe; Vanneste, Michiel; Matthews, Harold; Hoskens, Hanne; Richmond, Stephen; Klein, Ophir D.; Spritz, Richard A.; Hallgrimsson, Benedikt; Walsh, Susan; Shriver, Mark D.; Shaffer, John R.; Weinberg, Seth M.; Peeters, Hilde; Claes, Peter; Biology, School of Science
    Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits.
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    Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population
    (Springer Nature, 2024-12-02) Vanneste, Michiel; Hoskens, Hanne; Goovaerts, Seppe; Matthews, Harold; Devine, Jay; Aponte, Jose D.; Cole, Joanne; Shriver, Mark; Marazita, Mary L.; Weinberg, Seth M.; Walsh, Susan; Richmond, Stephen; Klein, Ophir D.; Spritz, Richard A.; Peeters, Hilde; Hallgrímsson, Benedikt; Claes, Peter; Biology, School of Science
    Human craniofacial shape is highly variable yet highly heritable with numerous genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the general population. We compare three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores reveals a polygenic basis for facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples, both human and mouse, shows craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing insights into the genetic intersection of complex traits and Mendelian disorders.