IU Indianapolis ScholarWorks :: Browsing by Author "Peeters, Hilde"

Browsing by Author "Peeters, Hilde"

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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 Science
The 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.
Advancing Genotype-Phenotype Analysis through 3D Facial Morphometry: Insights from Cri-du-Chat Syndrome
(medRxiv, 2025-06-01) Vanneste, Michiel; Matthews, Harold; Sleyp, Yoeri; Hammond, Peter; Shriver, Mark; Weinberg, Seth M.; Marazita, Mary L.; Walsh, Susan; Hallgrímsson, Benedikt; Klein, Ophir D.; Spritz, Richard A.; Van Den Bogaert, Kris; Claes, Peter; Peeters, Hilde; Biology, School of Science
Purpose: Facial dysmorphism is a feature of many monogenic disorders, and is important in diagnostics, variant interpretation and nosology. Nevertheless, comprehensively assessing the complex facial shape changes associated with specific syndromes remains challenging. Here, we present 3D morphometric approaches to overcome these limitations, utilizing Cri-du-Chat syndrome (CdCS) as a model. Methods: We analyzed 3D facial photos from 24 individuals with CdCS, 4540 unaffected controls and 5 individuals with rare 5p15.33-15.32 deletions, incorporating two methods to account for age- and sex-related facial variation. We quantified phenotypic variation within and between groups and explored genotype-phenotype correlations in CdCS. Results: We identified changes in the characteristic facial features of CdCS with age and found that facial shape in CdCS differed from controls in highly consistent directions, but with varying magnitudes of effect. 5p15.33-15.32 heterozygotes had non-specific dysmorphic features that were objectively different from those in CdCS, delineating multiple critical regions for facial dysmorphism on chromosome 5p. Conclusion: This work explores 3D facial morphometry to complement the standard clinical assessment of facial dysmorphism. It provides insights into the genetic basis of facial shape in CdCS and highlights the potential of 3D morphometric techniques to facilitate clinical diagnostics, variant interpretation, and delineation of syndrome nosology.
Insights into the genetic architecture of the human face
(Springer Nature, 2021) White, Julie D.; Indencleef, Karlijne; Naqvi, Sahin; Eller, Ryan J.; Hoskens, Hanne; Roosenboom, Jasmien; Lee, Myoung Keun; Li, Jiarui; Mohammed, Jaaved; Richmond, Stephen; Quillen, Ellen E.; Norton, Heather L.; Feingold, Eleanor; Swigut, Tomek; Marazita, Mary L.; Peeters, Hilde; Hens, Greet; Shaffer, John R.; Wysocka, Joanna; Walsh, Susan; Weinberg, Seth M.; Shriver, Mark D.; Claes, Peter; Biology, School of Science
The human face is complex and multipartite, and characterization of its genetic architecture remains challenging. Using a multivariate genome-wide association study meta-analysis of 8,246 European individuals, we identified 203 genome-wide-significant signals (120 also study-wide significant) associated with normal-range facial variation. Follow-up analyses indicate that the regions surrounding these signals are enriched for enhancer activity in cranial neural crest cells and craniofacial tissues, several regions harbor multiple signals with associations to different facial phenotypes, and there is evidence for potential coordinated actions of variants. In summary, our analyses provide insights into the understanding of how complex morphological traits are shaped by both individual and coordinated genetic actions.
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.
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.
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants
(Oxford University Press, 2025) Yuan, Meng; Goovaerts, Seppe; Lee, Myoung K.; Devine, Jay; Richmond, Stephen; Walsh, Susan; Shriver, Mark D.; Shaffer, John R.; Marazita, Mary L.; Peeters, Hilde; Weinberg, Seth M.; Claes, Peter; Biology, School of Science
Genotype-phenotype (G-P) analyses for complex morphological traits typically utilize simple, predetermined anatomical measures or features derived via unsupervised dimension reduction techniques (e.g. principal component analysis (PCA) or eigen-shapes). Despite the popularity of these approaches, they do not necessarily reveal axes of phenotypic variation that are genetically relevant. Therefore, we introduce a framework to optimize phenotyping for G-P analyses, such as genome-wide association studies (GWAS) of common variants or rare variant association studies (RVAS) of rare variants. Our strategy is two-fold: (i) we construct a multidimensional feature space spanning a wide range of phenotypic variation, and (ii) within this feature space, we use an optimization algorithm to search for directions or feature combinations that are genetically enriched. To test our approach, we examine human facial shape in the context of GWAS and RVAS. In GWAS, we optimize for phenotypes exhibiting high heritability, estimated from either family data or genomic relatedness measured in unrelated individuals. In RVAS, we optimize for the skewness of phenotype distributions, aiming to detect commingled distributions that suggest single or few genomic loci with major effects. We compare our approach with eigen-shapes as baseline in GWAS involving 8246 individuals of European ancestry and in gene-based tests of rare variants with a subset of 1906 individuals. After applying linkage disequilibrium score regression to our GWAS results, heritability-enriched phenotypes yielded the highest SNP heritability, followed by eigen-shapes, while commingling-based traits displayed the lowest SNP heritability. Heritability-enriched phenotypes also exhibited higher discovery rates, identifying the same number of independent genomic loci as eigen-shapes with a smaller effective number of traits. For RVAS, commingling-based traits resulted in more genes passing the exome-wide significance threshold than eigen-shapes, while heritability-enriched phenotypes lead to only a few associations. Overall, our results demonstrate that optimized phenotyping allows for the extraction of genetically relevant traits that can specifically enhance discovery efforts of common and rare variants, as evidenced by their increased power in facial GWAS and RVAS.
Rare deleterious mutations of HNRNP genes result in shared neurodevelopmental disorders
(BMC, 2021-04-19) Gillentine, Madelyn A.; Wang, Tianyun; Hoekzema, Kendra; Rosenfeld, Jill; Liu, Pengfei; Guo, Hui; Kim, Chang N.; De Vries, Bert B.A.; Vissers, Lisenka E.L.M.; Nordenskjold, Magnus; Kvarnung, Malin; Lindstrand, Anna; Nordgren, Ann; Gecz, Jozef; Iascone, Maria; Cereda, Anna; Scatigno, Agnese; Maitz, Silvia; Zanni, Ginevra; Bertini, Enrico; Zweier, Christiane; Schuhmann, Sarah; Wiesener, Antje; Pepper, Micah; Panjwani, Heena; Torti, Erin; Abid, Farida; Anselm, Irina; Srivastava, Siddharth; Atwal, Paldeep; Bacino, Carlos A.; Bhat, Gifty; Cobian, Katherine; Bird, Lynne M.; Friedman, Jennifer; Wright, Meredith S.; Callewaert, Bert; Petit, Florence; Mathieu, Sophie; Afenjar, Alexandra; Christensen, Celenie K.; White, Kerry M.; Elpeleg, Orly; Berger, Itai; Espineli, Edward J.; Fagerberg, Christina; Brasch-Andersen, Charlotte; Hansen, Lars Kjærsgaard; Feyma, Timothy; Hughes, Susan; Thiffault, Isabelle; Sullivan, Bonnie; Yan, Shuang; Keller, Kory; Keren, Boris; Mignot, Cyril; Kooy, Frank; Meuwissen, Marije; Basinger, Alice; Kukolich, Mary; Philips, Meredith; Ortega, Lucia; Drummond-Borg, Margaret; Lauridsen, Mathilde; Sorensen, Kristina; Lehman, Anna; Lopez-Range, Elena; Levy, Paul; Lessel, Davor; Lotze, Timothy; Madan-Khetarpal, Suneeta; Sebastian, Jessica; Vento, Jodie; Vats, Divya; Benman, L. Manace; Mckee, Shane; Mirzaa, Ghayda M.; Muss, Candace; Pappas, John; Peeters, Hilde; Romano, Corrado; Elia, Maurizio; Galesi, Ornella; Simon, Marleen E.H.; Van Gassen, Koen L.I.; Simpson, Kara; Stratton, Robert; Syed, Sabeen; Thevenon, Julien; Palafoll, Irene Valenzuela; Vitobello, Antonio; Bournez, Marie; Faivre, Laurence; Xia, Kun; Earl, Rachel K.; Nowakowski, Tomasz; Bernier, Raphael A.; Eichler, Evan E.; Pediatrics, School of Medicine
Background: With the increasing number of genomic sequencing studies, hundreds of genes have been implicated in neurodevelopmental disorders (NDDs). The rate of gene discovery far outpaces our understanding of genotype-phenotype correlations, with clinical characterization remaining a bottleneck for understanding NDDs. Most disease-associated Mendelian genes are members of gene families, and we hypothesize that those with related molecular function share clinical presentations. Methods: We tested our hypothesis by considering gene families that have multiple members with an enrichment of de novo variants among NDDs, as determined by previous meta-analyses. One of these gene families is the heterogeneous nuclear ribonucleoproteins (hnRNPs), which has 33 members, five of which have been recently identified as NDD genes (HNRNPK, HNRNPU, HNRNPH1, HNRNPH2, and HNRNPR) and two of which have significant enrichment in our previous meta-analysis of probands with NDDs (HNRNPU and SYNCRIP). Utilizing protein homology, mutation analyses, gene expression analyses, and phenotypic characterization, we provide evidence for variation in 12 HNRNP genes as candidates for NDDs. Seven are potentially novel while the remaining genes in the family likely do not significantly contribute to NDD risk. Results: We report 119 new NDD cases (64 de novo variants) through sequencing and international collaborations and combined with published clinical case reports. We consider 235 cases with gene-disruptive single-nucleotide variants or indels and 15 cases with small copy number variants. Three hnRNP-encoding genes reach nominal or exome-wide significance for de novo variant enrichment, while nine are candidates for pathogenic mutations. Comparison of HNRNP gene expression shows a pattern consistent with a role in cerebral cortical development with enriched expression among radial glial progenitors. Clinical assessment of probands (n = 188-221) expands the phenotypes associated with HNRNP rare variants, and phenotypes associated with variation in the HNRNP genes distinguishes them as a subgroup of NDDs. Conclusions: Overall, our novel approach of exploiting gene families in NDDs identifies new HNRNP-related disorders, expands the phenotypes of known HNRNP-related disorders, strongly implicates disruption of the hnRNPs as a whole in NDDs, and supports that NDD subtypes likely have shared molecular pathogenesis. To date, this is the first study to identify novel genetic disorders based on the presence of disorders in related genes. We also perform the first phenotypic analyses focusing on related genes. Finally, we show that radial glial expression of these genes is likely critical during neurodevelopment. This is important for diagnostics, as well as developing strategies to best study these genes for the development of therapeutics.
Shared heritability of human face and brain shape
(Springer Nature, 2021) Naqvi, Sahin; Sleyp, Yoeri; Hoskens, Hanne; Indencleef, Karlijne; Spence, Jeffrey P.; Bruffaerts, Rose; Radwan, Ahmed; Eller, Ryan J.; Richmond, Stephen; Shriver, Mark D.; Shaffer, John R.; Weinberg, Seth M.; Walsh, Susan; Thompson, James; Pritchard, Jonathan K.; Sunaert, Stefan; Peeters, Hilde; Wysocka, Joanna; Claes, Peter; Biology, School of Science
Evidence from model organisms and clinical genetics suggests coordination between the developing brain and face, but the role of this link in common genetic variation remains unknown. We performed a multivariate genome-wide association study of cortical surface morphology in 19,644 individuals of European ancestry, identifying 472 genomic loci influencing brain shape, of which 76 are also linked to face shape. Shared loci include transcription factors involved in craniofacial development, as well as members of signaling pathways implicated in brain-face cross-talk. Brain shape heritability is equivalently enriched near regulatory regions active in either forebrain organoids or facial progenitors. However, we do not detect significant overlap between shared brain-face genome-wide association study signals and variants affecting behavioral-cognitive traits. These results suggest that early in embryogenesis, the face and brain mutually shape each other through both structural effects and paracrine signaling, but this interplay may not impact later brain development associated with cognitive function.
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.
The Intersection of the Genetic Architectures of Orofacial Clefts and Normal Facial Variation
(Frontiers Media, 2021-02-22) Indencleef, Karlijne; Hoskens, Hanne; Lee, Myoung Keun; White, Julie D.; Liu, Chenxing; Eller, Ryan J.; Naqvi, Sahin; Wehby, George L.; Moreno Uribe, Lina M.; Hecht, Jacqueline T.; Long, Ross E., Jr.; Christensen, Kaare; Deleyiannis, Frederic W.; Walsh, Susan; Shriver, Mark D.; Richmond, Stephen; Wysocka, Joanna; Peeters, Hilde; Shaffer, John R.; Marazita, Mary L.; Hens, Greet; Weinberg, Seth M.; Claes, Peter; Biology, School of Science
Unaffected relatives of individuals with non-syndromic cleft lip with or without cleft palate (NSCL/P) show distinctive facial features. The presence of this facial endophenotype is potentially an expression of underlying genetic susceptibility to NSCL/P in the larger unselected population. To explore this hypothesis, we first partitioned the face into 63 partially overlapping regions representing global-to-local facial morphology and then defined endophenotypic traits by contrasting the 3D facial images from 264 unaffected parents of individuals with NSCL/P versus 3,171 controls. We observed distinct facial features between parents and controls across 59 global-to-local facial segments at nominal significance (p ≤ 0.05) and 52 segments at Bonferroni corrected significance (p < 1.2 × 10–3), respectively. Next, we quantified these distinct facial features as univariate traits in another dataset of 8,246 unaffected European individuals and performed a genome-wide association study. We identified 29 independent genetic loci that were associated (p < 5 × 10–8) with at least one of the tested endophenotypic traits, and nine genetic loci also passed the study-wide threshold (p < 8.47 × 10–10). Of the 29 loci, 22 were in proximity of loci previously associated with normal facial variation, 18 were near genes that show strong evidence in orofacial clefting (OFC), and another 10 showed some evidence in OFC. Additionally, polygenic risk scores for NSCL/P showed associations with the endophenotypic traits. This study thus supports the hypothesis of a shared genetic architecture of normal facial development and OFC.

Browsing by Author "Peeters, Hilde"

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