Browsing by Subject "Face"

Now showing 1 - 10 of 10
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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.
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    A Cephalometric Analysis Comparing Incremental Skeletal Growth in the Adolescent Face with Projected Growth
    (1973) Wilkins, Don M.
    This study investigated the correlation between predicted growth in cranial base, maxilla, and mandible and the actual growth in these structures over a two-year period. The treatment sample consisted of 13 males and 16 females who prior to orthodontic treatment had a Class I skeletal relationship and an Angle Class I arch length discrepancy. The developmental age varied from 11.0 to 17.0 years of age in males and from 9.5 to 15.0 years of age in females. The control group of 14 males and 16 females had Class I skeletal patterns and Angle Class I occlusions. All subjects were Caucasians. To determine the actual growth values for the treatment sample, a standardized technique was used for taking two lateral cephalometric headplates: one at the beginning of orthodontic treatment and another approximately two years later. A wristplate was also taken from which the developmental age of each subject was determined. Two year growth prediction increments were calculated for each structure in the treatment sample based on the individual's developmental age. These prediction increments represent the average growth of the corresponding structure in the control sample. With the exception of the female mandible, when the predicted growth increments were compared to actual growth, the correlation coefficients were not large enough to justify using mean growth values as predictors of individual craniofacial growth. It was concluded that the individual variation in growth rate precludes the use of a group statistic, such as a mean increment, for predicting facial changes.
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    An Analysis of Possible Factors Affecting the Soft Tissue Response in Postadolescent Orthodontic Patients
    (1975) Cowan, Richard Edward; Garner, LaForrest D.; Potter, Rosario H.; Mitchell, David F.; Tomich, Charles E.; Hutton, Charles E.; Weinberg, R. Bernd
    This study was carried out to evaluate the factors which may vary the soft tissue response in non-growing subjects. Pretreatment and post-treatment lateral cephalometric radiographs of twenty-nine postadolescent orthodontic patients were measured with a sonic digitizer using facial plane as the reference. Stepwise multiple regression analysis was performed to select those factors from the original set of 6 according to the statistical significance of their contribution in the prediction of the soft tissue response. It was found that 30.84% of the horizontal upper lip response is due statistically to the maxillary incisor change and the pretreatment upper lip thickness at the vermillion border. This study also revealed that 67.76% of the horizontal lower lip response is due statistically to the mandibular incisor change, the pretreatment upper lip thickness at A-Point, and the mandibular postural change. Additionally, 16.50% of the vertical upper lip response is due statistically to the mandibular incisor change. Further, 33.39% of the vertical lower lip response is due statistically to the mandibular postural change and the pretreatment upper lip thickness at A-Point. Finally, the majority of the total variation in lip response is still not accounted for and therefore further research is needed.
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    Enhancing Our Genetic Knowledge of Human Iris Pigmentation and Facial Morphology
    (2019-12) Eller, Ryan; Walsh, Susan; Berbari, Nicolas; Lapish, Christopher; Picard, Christine; Roper, Randall
    The biological underpinnings that control iris pigmentation and facial morphology are two areas of research that over the last decade are becoming more thoroughly investigated due to the increased affordability of genotyping and advances in technology allowing for more advanced analysis techniques. Despite the ease of access to the data and the tools required to perform iris pigmentation and facial morphological studies, there are still numerous challenges researchers must overcome when exploring the genetics of these complex phenotypes. Some of these challenges include difficulty in working with the bioinformatic programs designed to analyze genetic associations, the inability to define a phenotype that captures the true nature of these traits, and analysis techniques that fail to model complex gene-gene interactions and their effect on a phenotype or phenotypes of interest. In this body of work, I attempted to address these challenges by designing a bioinformatic pipeline, Odyssey, that bridges the communication gaps between various data preparation programs and the programs that analyze genomic data. With this program, genome-wide association studies (GWAS) could be conducted in a quicker, more efficient, and easier manner. I also redefined iris color as a quantitative measurement of pre-defined color classes. In this way it is possible to define and quantify the unique and intricate mixtures of color, which allows for the identification of known and novel variants that affect individual iris color. I also improved upon current prediction models by developing a neural network model capable of predicting a quantitative output to four pre-defined classes; blue/grey, light brown (hazel), perceived green, and dark brown. I examined the effects of defining a simple facial morphology phenotype that more accurately captures the lower face and jaw shape. I then analyzed this phenotype via a GWAS and found several novel variants that may be associated with a square and diamond shaped face. Lastly, I demonstrated that structural equation modeling can be used in combination with traditional GWAS to examine interactions amongst associated variants, which unearths potential biological relationships that impact the multifaceted phenotype of facial morphology.
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    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.
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    Individualized, Computerized Growth Prediction
    (1970) Fortuño Buxó, Jorge
    This investigation was conducted to individualize growth prediction by use of regression formulas and therefore supplement the present method of using mean incremental data obtained from case study. There were 30 normal individuals, ages 8 to 19 years, 14 males and 16 females. Based on the analysis of serial headplates, the incremental growth change for 12 variables to be used in growth prediction was calculated for each individual for each 3 year period until adulthood was reached. Cephalometric measurements, consisting of 39 variables, were made at the beginning of each 3 year period. For every age group the following information was fed into a computer: a.) The known incremental growth change for each 3 year for the 12 variables to be used in prediction. b.) The known measurements of the 39 variables at the beginning of each 3 year period. The computer selected from the 39 variables only those which best predicted the already known incremental growth change of the 12 variables to be used in prediction. A total of 101 regression formulas of a possible 108 was obtained for males, and 102 for females, with a high multiple correlation. A sign test at .05 level of confidence was used to determine if this regression formula method was significantly better than the mean incremental method presently used at Indiana University. The results showed that, in the majority of the cases, the regression method proved to be significantly better than the mean incremental method. In none of the cases was the man incremental method significantly better.
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    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.
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    Mapping of Segmental and Partial Segmental Infantile Hemangiomas of the Face and Scalp
    (American Medical Association, 2021) Endicott, Alyson A.; Chamlin, Sarah L.; Drolet, Beth A.; Mancini, Anthony J.; Siegel, Dawn H.; Vitcov, Sterling; Mathes, Erin F.; Frieden, Ilona J.; Haggstrom, Anita N.; Dermatology, School of Medicine
    Importance: Recognizing segmental infantile hemangioma (IH) patterns is important for risk stratification and provides clues to pathogenesis. Previously, segmental hemangiomas were mapped to 4 facial regions, 3 corresponding to known facial metameres. Objectives: To refine existing maps of facial segmental IHs, examine so-called indeterminate hemangiomas as they relate to known segmental patterns, and define a novel pattern of segmental scalp hemangiomas. Design, setting, and participants: This retrospective cohort study was conducted at 4 pediatric dermatology centers (University of California, San Francisco; Indiana University; Medical College of Wisconsin; and Northwestern University/Ann & Robert H. Lurie Children's Hospital of Chicago) using photographic archives of patients younger than 12 years with segmental and indeterminate hemangiomas on the face and scalp. Clinical images were used to map hemangioma distribution onto standardized facial templates. Heat map densiometry identified recurrent patterns that were compared with previously published patterns of facial segmental hemangiomas. Patterns of indeterminate hemangiomas were compared with those of segmental hemangiomas. Data collection took place in 2017, and analysis took place from 2017 to 2019. Main outcomes and measures: Distribution and patterning of segmental and indeterminate IHs of the face and scalp. Results: A total of 549 IHs were mapped. The borders of the frontotemporal (S1) and frontonasal (S4) segments agreed with previous segmental maps; however, the maxillary (S2) and mandibular (S3) segment borders differed with respect to the preauricular skin. In contrast with previous reports, preauricular skin segregated with the mandibular (S3) rather than the maxillary (S2) segment. Indeterminate hemangiomas occurred within and respected the same borders as segmental hemangiomas. Hemangiomas on the lateral scalp commonly occurred in a C shape extending from the posterior auricular region. Conclusions and relevance: This cohort study provides an updated map of facial segmental IHs with redefined maxillary (S2) and mandibular (S3) segment borders. It provides evidence that indeterminate hemangiomas are partial segmental hemangiomas respecting anatomic boundaries of their larger segmental counterparts. A newly recognized C-shaped pattern of segmental scalp hemangioma is reported.
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    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.
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    The Integumental Profile: A Study of Acceptable Adolescent Faces
    (1957-07) Lehman, David G.; Adams, J. William; Mulher, Joseph; Van Huysen, Grant; McDonald, Ralph; Shafer, William; Phillips, Ralph