Browsing by Author "Claes, Peter"
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Item 3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties(IEEE, 2021) Mahdi, Soha Sadat; Nauwelaers, Nele; Joris, Philip; Bouritsas, Giorgos; Gong, Shunwang; Bokhnyak, Sergiy; Walsh, Susan; Shriver, Mark D.; Bronstein, Michael; Claes, Peter; Biology, School of ScienceFace recognition is a widely accepted biometric verification tool, as the face contains a lot of information about the identity of a person. In this study, a 2-step neural-based pipeline is presented for matching 3D facial shape to multiple DNA-related properties (sex, age, BMI and genomic background). The first step consists of a triplet loss-based metric learner that compresses facial shape into a lower dimensional embedding while preserving information about the property of interest. Most studies in the field of metric learning have only focused on 2D Euclidean data. In this work, geometric deep learning is employed to learn directly from 3D facial meshes. To this end, spiral convolutions are used along with a novel mesh-sampling scheme that retains uniformly sampled 3D points at different levels of resolution. The second step is a multi-biometric fusion by a fully connected neural network. The network takes an ensemble of embeddings and property labels as input and returns genuine and imposter scores. Since embeddings are accepted as an input, there is no need to train classifiers for the different properties and available data can be used more efficiently. Results obtained by a to-fold cross-validation for biometric verification show that combining multiple properties leads to stronger biometric systems. Furthermore, the proposed neural-based pipeline outperforms a linear baseline, which consists of principal component analysis, followed by classification with linear support vector machines and a Naïve Bayes-based score-fuser.Item 3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies(Public Library of Science, 2021-05-13) Hoskens, Hanne; Liu, Dongjing; Naqvi, Sahin; Lee, Myoung Keun; Eller, Ryan J.; Indencleef, Karlijne; White, Julie D.; Li, Jiarui; Larmuseau, Maarten H. D.; Hens, Greet; Wysocka, Joanna; Walsh, Susan; Richmond, Stephen; Shriver, Mark D.; Shaffer, John R.; Peeters, Hilde; Weinberg, Seth M.; Claes, Peter; Biology, School of ScienceThe analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.Item Automated 3D Landmarking of the Skull: A Novel Approach for Craniofacial Analysis(bioRxiv, 2024-02-12) Wilke, Franziska; Matthews, Harold; Herrick, Noah; Dopkins, Nichole; Claes, Peter; Walsh, Susan; Biology, School of ScienceAutomatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising 9,999 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (>0.988), and automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.Item Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data(Oxford University Press, 2025) Li, Zuqi; Windels, Sam F. L.; Malod-Dognin, Noël; Weinberg, Seth M.; Marazita, Mary L.; Walsh, Susan; Shriver, Mark D.; Fardo, David W.; Claes, Peter; Pržulj, Nataša; Van Steen, Kristel; Biology, School of ScienceMotivation: Combining omics and images can lead to a more comprehensive clustering of individuals than classic single-view approaches. Among the various approaches for multi-view clustering, nonnegative matrix tri-factorization (NMTF) and nonnegative Tucker decomposition (NTD) are advantageous in learning low-rank embeddings with promising interpretability. Besides, there is a need to handle unwanted drivers of clusterings (i.e. confounders). Results: In this work, we introduce a novel multi-view clustering method based on NMTF and NTD, named INMTD, which integrates omics and 3D imaging data to derive unconfounded subgroups of individuals. According to the adjusted Rand index, INMTD outperformed other clustering methods on a synthetic dataset with known clusters. In the application to real-life facial-genomic data, INMTD generated biologically relevant embeddings for individuals, genetics, and facial morphology. By removing confounded embedding vectors, we derived an unconfounded clustering with better internal and external quality; the genetic and facial annotations of each derived subgroup highlighted distinctive characteristics. In conclusion, INMTD can effectively integrate omics data and 3D images for unconfounded clustering with biologically meaningful interpretation. Availability and implementation: INMTD is freely available at https://github.com/ZuqiLi/INMTD.Item Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morp(Annual Reviews, 2022) Naqvi, Sahin; Hoskens, Hanne; Wilke, Franziska; Weinberg, Seth M.; Shaffer, John R.; Walsh, Susan; Shriver, Mark D.; Wysocka, Joanna; Claes, Peter; Biology, School of ScienceVariations in the form of the human face, which plays a role in our individual identities and societal interactions, have fascinated scientists and artists alike. Here, we review our current understanding of the genetics underlying variation in craniofacial morphology and disease-associated dysmorphology, synthesizing decades of progress on Mendelian syndromes in addition to more recent results from genome-wide association studies of human facial shape and disease risk. We also discuss the various approaches used to phenotype and quantify facial shape, which are of particular importance due to the complex, multipartite nature of the craniofacial form. We close by discussing how experimental studies have contributed and will further contribute to our understanding of human genetic variation and then proposing future directions and applications for the field.Item Effects of Male Facial Masculinity on Perceived Attractiveness(Springer Nature, 2021) Ekrami, Omid; Claes, Peter; Shriver, Mark D.; Weinberg, Seth M.; Marazita, Mary L.; Walsh, Susan; Van Dongen, Stefan; Biology, School of ScienceStudies suggest that high levels of masculinity in men can be a signal of 'better genes' as well as low parental investment. It is the trade-off between these two qualities that has led to the hypothesis that women's preferences for male masculinity are condition-dependent, yet, not all studies support this hypothesis. In addition, there is evidence that more average faces would be perceived as more attractive. Here we study the variation in masculinity preferences of a cohort of heterosexual women (n=769), using manipulated 3D faces of male subjects. We used linear mixed models to test for effects of various covariates such as relationship status, use of hormonal contraception, sociosexual orientation and self-perceived attractiveness on preference for masculinity. Our results show that women's sociosexual orientation has a positive correlation with masculinity preference while using hormonal contraception decreases this preference. None of the other covariates displayed any significant effect on masculinity preference. The initial level of masculinity of the faces (very low, low, average, high and very high) was also shown to affect this preference, where we found a significant preference for higher masculinity in the very low and average group, while no preference was found in the other groups. Our findings support the notion that condition-dependent variables have very small effects, if any, on women's preference for masculinity in men.Item Enhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS(Springer Nature, 2025-03-15) Goovaerts, Seppe; Naqvi, Sahin; Hoskens, Hanne; Herrick, Noah; Yuan, Meng; Shriver, Mark D.; Shaffer, John R.; Walsh, Susan; Weinberg, Seth M.; Wysocka, Joanna; Claes, Peter; Biology, School of ScienceLarge-scale GWAS studies have uncovered hundreds of genomic loci linked to facial and brain shape variation, but only tens associated with cranial vault shape, a largely overlooked aspect of the craniofacial complex. Surrounding the neocortex, the cranial vault plays a central role during craniofacial development and understanding its genetics are pivotal for understanding craniofacial conditions. Experimental biology and prior genetic studies have generated a wealth of knowledge that presents opportunities to aid further genetic discovery efforts. Here, we use the conditional FDR method to leverage GWAS data of facial shape, brain shape, and bone mineral density to enhance SNP discovery for cranial vault shape. This approach identified 120 independent genomic loci at 1% FDR, nearly tripling the number discovered through unconditioned analysis and implicating crucial craniofacial transcription factors and signaling pathways. These results significantly advance our genetic understanding of cranial vault shape and craniofacial development more broadly.Item Exploring regional aspects of 3D facial variation within European individuals(Springer Nature, 2023-03-06) Wilke, Franziska; Herrick, Noah; Matthews, Harold; Hoskens, Hanne; Singh, Sylvia; Shaffer, John R.; Weinberg, Seth M.; Shriver, Mark D.; Claes, Peter; Walsh, Susan; Biology, School of ScienceFacial ancestry can be described as variation that exists in facial features that are shared amongst members of a population due to environmental and genetic effects. Even within Europe, faces vary among subregions and may lead to confounding in genetic association studies if unaccounted for. Genetic studies use genetic principal components (PCs) to describe facial ancestry to circumvent this issue. Yet the phenotypic effect of these genetic PCs on the face has yet to be described, and phenotype-based alternatives compared. In anthropological studies, consensus faces are utilized as they depict a phenotypic, not genetic, ancestry effect. In this study, we explored the effects of regional differences on facial ancestry in 744 Europeans using genetic and anthropological approaches. Both showed similar ancestry effects between subgroups, localized mainly to the forehead, nose, and chin. Consensus faces explained the variation seen in only the first three genetic PCs, differing more in magnitude than shape change. Here we show only minor differences between the two methods and discuss a combined approach as a possible alternative for facial scan correction that is less cohort dependent, more replicable, non-linear, and can be made open access for use across research groups, enhancing future studies in this field.Item Fluctuating Asymmetry and Sexual Dimorphism in Human Facial Morphology: A Multi-Variate Study(MDPI, 2021-02) Ekrami, Omid; Claes, Peter; Van Assche, Ellen; Shriver, Mark D.; Weinberg, Seth M.; Marazita, Mary L.; Walsh, Susan; Van Dongen, Stefan; Biology, School of ScienceBackground: Fluctuating asymmetry is often used as an indicator of developmental instability, and is proposed as a signal of genetic quality. The display of prominent masculine phenotypic features, which are a direct result of high androgen levels, is also believed to be a sign of genetic quality, as these hormones may act as immunosuppressants. Fluctuating asymmetry and masculinity are therefore expected to covary. However, there is lack of strong evidence in the literature regarding this hypothesis. Materials and methods: In this study, we examined a large dataset of high-density 3D facial scans of 1260 adults (630 males and 630 females). We mapped a high-density 3D facial mask onto the facial scans in order to obtain a high number of quasi-landmarks on the faces. Multi-dimensional measures of fluctuating asymmetry were extracted from the landmarks using Principal Component Analysis, and masculinity/femininity scores were obtained for each face using Partial Least Squares. The possible correlation between these two qualities was then examined using Pearson's coefficient and Canonical Correlation Analysis. Results: We found no correlation between fluctuating asymmetry and masculinity in men. However, a weak but significant correlation was found between average fluctuating asymmetry and masculinity in women, in which feminine faces had higher levels of fluctuating asymmetry on average. This correlation could possibly point to genetic quality as an underlying mechanism for both asymmetry and masculinity; however, it might also be driven by other fitness or life history traits, such as fertility. Conclusions: Our results question the idea that fluctuating asymmetry and masculinity should be (more strongly) correlated in men, which is in line with the recent literature. Future studies should possibly focus more on the evolutionary relevance of the observed correlation in women.Item Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations(Public Library of Science, 2021-08-19) Liu, Chenxing; Lee, Myoung Keun; Naqvi, Sahin; Hoskens, Hanne; Liu, Dongjing; White, Julie D.; Indencleef, Karlijne; Matthews, Harold; Eller, Ryan J.; Li, Jiarui; Mohammed, Jaaved; Swigut, Tomek; Richmond, Stephen; Manyama, Mange; Hallgrímsson, Benedikt; Spritz, Richard A.; Feingold, Eleanor; Marazita, Mary L.; Wysocka, Joanna; Walsh, Susan; Shriver, Mark D.; Claes, Peter; Weinberg, Seth M.; Shaffer, John R.; Biology, School of ScienceFacial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Previous genome scans have revealed more than 100 genetic loci associated with different aspects of normal-range facial variation. Most of these loci have been detected in Europeans, with few studies focusing on other ancestral groups. Consequently, the degree to which facial traits share a common genetic basis across diverse sets of humans remains largely unknown. We therefore investigated the genetic basis of facial morphology in an East African cohort. We applied an open-ended data-driven phenotyping approach to a sample of 2,595 3D facial images collected on Tanzanian children. This approach segments the face into hierarchically arranged, multivariate features that capture the shape variation after adjusting for age, sex, height, weight, facial size and population stratification. Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10-8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation. Two of these associations were in highly conserved regions showing craniofacial-specific enhancer activity during embryological development (5q31.1 and 12q21.31). Six of the 20 loci surpassed a stricter threshold accounting for multiple phenotypes with study-wide significance (p < 6.25 × 10-10). Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci. Taken together, these results may point to both shared and population-specific components to the genetic architecture of facial variation.