IU Indianapolis ScholarWorks :: Browsing by Author "Shaffer, John R."

Browsing by Author "Shaffer, John R."

Now showing 1 - 10 of 11

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.
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 Science
Variations 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.
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 Science
Large-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.
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 Science
Facial 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.
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 Science
Facial 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.
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.
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.
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.
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 "Shaffer, John R."

Results Per Page

Sort Options