Extant African papioninans are distinguished from macaques by the presence of excavated facial fossae; however, facial excavation differs among taxa. Mangabeys (Cercocebus, Rungwecebus, and Lophocebus) exhibit fossae that invade the zygomatic forming pronounced suborbital fossae (SOFs). Larger-bodied Papio, Mandrillus, and Theropithecus have lateral rostral fossae with minimal/absent suborbital fossae. Because prior studies have shown that mangabeys exhibit adaptations to anterior dental loading (e.g., palatal retraction), it is plausible that mangabey SOFs represent structural accommodation to masticatory-system shape rather than facial allometry, as commonly hypothesized. We analyzed covariation between zygomaxillary-surface shape, masticatory-system shape, and facial size in 141 adult crania of Macaca fascicularis, Papio kindae, Cercocebus, and Lophocebus. These taxa represent the range of papionin SOF expression while minimizing size variation (narrow allometry). Masticatory-system landmarks (39) registered palate shape, bite points, masticatory muscle attachments, and the tempo-romandibular joint. Semilandmarks (450) captured zygomaxillary-surface shape. Following Procrustes superimposition with semilandmark sliding and principal components analyses, multivariate regression was used to explore allometry, and two-block partial least-squares analyses (within-configuration and separate-blocks) were used to examine covariation patterns. Scores on principal components 1e2 and the first partial least-square (PLS1) separate mangabeys from Macaca and Papio. Both zygomaxillary-surface shape and masticatory-system shape are correlated with size within taxa and facial morpho-types; however, regression distributions indicate morphotype shape differences are non-allometric. PLS1 accounts for-95% of shape covariance (p < 0.0001) and shows strong linear correlations (r-PLS 1/4-0.95, p < 0.0001) between blocks. Negative PLS1 scores in mangabeys reflect deep excavation of the suborbital malar surface, palatal retraction, and anterior displacement of jaw adductor muscles and the temporo-mandibular joint. Neither PC1 nor PLS1 scores ordinate specimens by facial size. Taken together, these results fail to support the allometric hypothesis but suggest that mangabey zygomaxillary morphology is closely linked with adaptations to hard-object feeding.(C) 2021 Elsevier Ltd. All rights reserved.

OBJECTIVES Standard methods of recording occlusal dental wear are problematic in that they either do not allow for individual variation of wear or are not designed to allow for comparisons of wear patterns. In this article, we (a) present a novel method for recording and analyzing molar wear, and (b) evaluate this method in light of existing methods. MATERIALS AND METHODS Eighty-two lower mandibular first molars from two regions (medieval Denmark, prehistoric Ohio Valley) were used to assess the method for replicability (intra and inter observer error) and accuracy (comparison to established methods of recording wear). Wear scores were recorded using the MolWear Android App (Beta) by both authors, and established methods of Smith and Scott by the first author. Intraobserver and interobserver error and comparison of the three methods were compared using Spearman's correlation coefficients. RESULTS The MolWear method presented high intraobserver (r = 0.985, p < 0.01) and interobserver (r = 0.978, p < 0.01) repeatability. Compared to other methods, the method was strongly correlated with Smith (r = 0.962, p < 0.01) and Smith (r = 0.891, p < 0.01). DISCUSSION The new MolWear method provides an improved way of measuring occlusal molar wear. This method bridges the gaps between established methods, performing comparatively while capturing more information about the distribution of wear in addition to the extent of wear. This method should be used for research comparing interpopulation or intrapopulation quantity of dental wear. While designed for a bioarchaeological population, this method could extend to any Y5 molar including nonhuman primates and hominins.

Childhood obesity rates in the United States have demonstrated a marked increase since the late 20th century. Current research has suggested that obesity can cause increases in bone density and an acceleration of skeletal growth. While studies have shown that obesity may be associated with altered craniofacial form, the mechanism and associated factors through which this interaction operates remains poorly understood. This study explores a potential link between obesity and craniofacial skeletal form as a function of the Hippo signaling pathway, an important regulator of organ size, tissue development, and craniofacial development.Lateral cephalograms from a sample of n=64 patients between the ages 7 to 17 were obtained from the Midwestern University Multispecialty Clinic. BMI percentile was computed for all children in the study following CDC guidelines (normal weight n=37, overweight n=9, obese n=18). 45 2D landmarks were registered via Generalized Procrustes Analysis (GPA) in order to facilitate a geometric morphometric (GM) analysis. Healthy Eating Index (HEI) scores obtained from Block Food Frequency Questionnaire (FFQ) surveys were used to control for the effects of diet in all subsequent analyses. Shape residuals were submitted to Principal Components Analysis (PCA) and Canonical Variate Analysis (CVA) to identify which aspects of skeletal form differentiate individual phenotypes based on BMI. Finally, associations between these phenotypes and 23 single nucleotide polymorphisms (SNPs) in seven genes within the Hippo signaling pathway were explored.Principal Components (PCs) accounting for at least 1% of facial shape variation were examined in order to determine components that differentiate between normal and obese groups. Based on this, suggestive/significant differences were found in PC 8 (p=0.056) and PC12 (p=0.012) based on BMI category. PC 8 (accounting for 3.6% of the total shape variation) indicates that chin projection, nose length, and mandibular morphology differentiate between normal and obese children. SNPs in TEAD3 (p=0.04) and FAT4 (p = 0.02) were significantly associated with shape variation along PC8. PC 12 (2.6% of the total shape variation) showed significant variation in chin projection and decreased incisor size in the obese group relative to the normal weight group. Additionally, a SNP within LATS2 (p = 0.04) was significantly correlated with shape variation along PC12. Finally, results from the CVA identified two components with CV2 indicating a significant relationship with LEF1 (p= 0.02). CV2 demonstrates increased facial projection in individuals with obesity.Across all analyses, we found a consistent pattern in mandibular length, facial projection, and incisor size that differentiated between normal and obese individuals. SNPs within key genes in the Hippo signaling pathway were associated with these phenotypes, indicating a potential causative relationship. Future studies will explore this relationship further.

Humans, like all bilaterian organisms, follow a symmetric body plan during growth and development. Deviations from symmetry during growth arise as a function of developmental instability caused by biological and environmental stressors such as poor diet and illness. Fluctuating asymmetry (FA) refers to random left/right asymmetries and is considered a quantifiable proxy for developmental stress. This study will investigate the patterning of facial asymmetry in a large population to highlight aspects of facial asymmetry within and between age groups. We also quantify FA across the sample to test the hypothesis that facial asymmetry increases as a function of age.To determine whether levels of facial asymmetry vary with age, a cross‐sectional sample of n=900 facial scans representing four age groups (child: 3–10 y/o, adolescent: 11–18 y/o, young adult: 19–27 y/o, and older adult: 28–40 y/o) from the University of Pittsburgh Center for Craniofacial and Dental Genetics 3D Facial Norms study were analyzed. 34 landmarks were captured along facial structures including the eyes, nose, mouth, and chin, superimposed using Generalized Procrustes Analysis (GPA), and analyzed using geometric morphometrics (GM) in MorphoJ. Following GPA, the asymmetric component of facial shape was examined using both Principal Components Analysis (PCA) and Canonical Variate Analysis (CVA) to evaluate patterns of overall facial asymmetry and whether or not different facial asymmetry patterns exist between age groups. Finally, a Procrustes ANOVA was employed to calculate a fluctuating asymmetry (FA) score for each individual and scores were regressed against age to test whether facial asymmetry increases with age.PCA results identified 43 principal components (PCs), of which the first three components accounted for nearly 42% of the overall facial asymmetric shape variation. PC1 confirmed that 19.7% of the asymmetries occurred in eye position, accounting for the largest aspect of facial asymmetry in the combined sample. PC2 and PC3, accounting for 12.8% and 9.4% of the asymmetric shape variation respectively, occurred mostly in the lower face and jaw line. Results from CVA found significant differences (p<0.02) in facial asymmetry between the age groups. CV1, accounting for 84% of the variation between groups identified asymmetries predominantly in the eyes and nose. CV2 (11.7% variation) demonstrated asymmetries of chin and lower face while CV3 (4.3%) indicated variations in asymmetry of the jaw line. Lastly, results from the Procrustes ANOVA confirmed a significant positive relationship between age and fluctuating asymmetry (p=0.0002, r2=0.014).This study identifies key aspects of facial asymmetry that exist between younger and older age groups, particularly increased asymmetries in the lower face of the adult groups compared to the younger age groups. Additionally, fluctuating asymmetry does increase slightly as a function of age, confirming our hypothesis. Future research will focus on specific factors that relate to these facial asymmetries, such as poor diet, using both cross‐sectional and longitudinal populations.Support or Funding InformationR01‐DE016148

Childhood obesity is a major public health concern in the US with a prevalence of nearly 19% for all children and adolescents. During growth, environmental factors such as poor diet can result in increased developmental stress. Given the symmetric patterning of facial growth in humans, any random deviations from symmetry, referred to as fluctuating asymmetry (FA), are considered a reflection of stress during growth. In this study, we examine whether childhood obesity serves as a source of developmental stress resulting in increased facial asymmetry. We hypothesize that a significant relationship between facial asymmetry and BMI exists, with higher BMI individuals demonstrating increased levels of facial asymmetry.To test our hypothesis, we obtained n=354 3D facial scans of children (age 3–19) from the University of Pittsburgh Center for Craniofacial and Dental Genetics. A total of n=286 facial scans represented children with a normal weight and n=68 faces were from children with obesity. Obesity status was determined using BMI values at or above the 95th percentile. Facial scans were digitized using 34 coordinate landmarks to capture asymmetry in the eyes, nose, mouth, and lower jaw. Coordinate data was submitted to a Generalized Procrustes Analysis (GPA) to align the facial landmarks and geometric morphometrics (GM) was then employed to quantify facial shape phenotypes in MorphoJ. Principal Component Analysis (PCA) was used to identify patterns of facial asymmetry throughout the entire sample. Canonical Variate Analysis (CVA) was then employed to identify differences in facial shape due to BMI. Lastly, a Procrustes ANOVA was ran to quantify levels of fluctuating asymmetry in the sample and the resulting FA scores were regressed against BMI percentile to test for a significant relationship.The results from the PCA identified 43 principal components (PCs), with the first three PCs accounting for 44.3% of total facial asymmetry. PC1 (accounting for 20.6% of facial asymmetry) identified asymmetry in the position of the eyes and a slight deviation of the nose, mouth and lower jaw to the left or right. PC2 (12.9%) demonstrated asymmetry primarily between the jaw and nose. PC3 (10.7%) further illustrated asymmetries through the eyes and jaw. The results of the CVA showed a significant difference (p=0.023) in overall asymmetry between normal weight children with children with obesity. Normal weight children demonstrated a trend toward facial symmetry while obese children showed marked asymmetry with respect to the eyes, nose, and chin. Finally, the results of the regression between FA scores and BMI percentile did not produce any significant association (p=0.72).While these results indicate a significant difference in the patterning of facial asymmetry between normal and obese children, evidence for increased FA levels (and therefore developmental instability) was not observed. Although we reject our hypothesis, the results demonstrate interesting facial asymmetries between BMI groups that may be promising for future analysis with longitudinal data.Support or Funding InformationGrant support: R01‐DE016148

Orofacial clefts are the most common congenital craniofacial anomaly affecting humans. Non‐syndromic clefts may result from decreased integration of the palate during fetal facial growth. This study will investigate whether this pattern is detectable in individuals who do not have a cleft, but do have a child with an orofacial cleft (and therefore carry genetic risk factors for clefting). In order to examine this, we hypothesize that 1) facial shape differences exist between unaffected parents of children with clefts (cases) compared to adults with no history of clefting (controls), and 2) cases will have lower facial integration values compared to controls. For this study, 3D facial scans were obtained from the University of Pittsburgh Center for Craniofacial and Dental Genetics (CCDG). 34 landmarks were placed on n=230 case faces of unaffected parents from the Pitt Orofacial Cleft Study and n=490 control faces from the Pitt 3D Facial Norms Study. Landmarks were aligned using Generalized Procrustes Analysis (GPA) and geometric morphometrics were used for quantifying facial phenotypes. Facial shape differences as a function of age were removed prior to all analyses using linear regression. Canonical Variate Analysis (CVA) was employed to examine shape differences in three different subsets of facial landmarks: a midfacial nose and mouth dataset, a lower facial mouth and jaw dataset and a third dataset consisting of the nose and jaw. Two Block Partial Least Squares analysis (2B PLS) was used to measure the strength of integration by comparing RV coefficients between the case and control populations. Results from the CVA identify significant differences in facial morphology, including jaw width, chin projection, nasal height and mouth width, between cases and controls across all datasets (nose/mouth midfacial set p<0.001, mouth/jaw lower facial set p<0.001, and nose/jaw dataset p=0.028). 2B PLS results, however, showed overall equivalent or higher integration levels in case faces compared to the controls. When comparing levels of integration within the midface (nose and mouth dataset), case samples demonstrate significant (p<0.001) overall higher integration levels (RV=0.352) compared to control samples (RV=0.301). This pattern is also seen within the nose and jaw dataset, with cases (RV=0.614) showing increased integration compared to controls (RV=0.554). Interestingly, integration levels within the lower facial mouth and jaw dataset were nearly identical in both case samples (RV=0.444) and controls (RV=0.447). While facial shape differences exist between unaffected cleft relatives and controls with no family history of clefting, integration values were actually higher in case samples compared to control samples. This indicates that integration in facial soft tissue structures may not serve as a good indicator of cleft risk. Future studies will examine skeletal structures (such as the maxilla and mandible) to test if differences in integration are quantifiable in the facial skeleton only. Support or Funding Information NIDCR: R01‐DE016148, U01‐DE020078 This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Obesity rates have more than tripled in children and adolescents in recent years. While many studies have examined the relationship between obesity and chronic illnesses, the impact of obesity on craniofacial form is less understood. Research in this area has suggested that obesity and facial form are risk factors for illnesses such as sleep apnea, but a mechanism that links these risk factors has been elusive. In order to explore a potential mechanism for linking risk for obesity and craniofacial abnormalities, this study examines variation within the Hippo signaling pathway. The Hippo signaling pathway plays an important role in organ size and tissue growth, as well as regulating craniofacial morphogenesis and adipocyte formation. For this study, we investigate the potential relationship between facial shape and BMI as a function of genetic variation within the Hippo signaling pathway.A sample of n=482 individuals with an age range of 3 to 16 years was targeted for the study. 3D facial images were captured using a 3dMD stereophotogrammetric camera and 34 coordinate landmarks were placed along the eyes, nose, mouth, and lower jaw for each face. Landmark data was registered via Generalized Procrustes Analysis (GPA) and then allometrically scaled to control for shape variation as a function of age. These allometric residuals were submitted to Principal Components Analysis (PCA), Canonical Variate Analysis (CVA) and linear regression within the software package MorphoJ in order to identify patterns of facial variation associated with BMI. These phenotypes were then tested for association with 23 single nucleotide polymorphisms (SNPs) in seven genes involved in Hippo signaling.The phenotypic results from the PCA, CVA, and the linear regressions between facial shape and high BMI/percentile BMI are characterized by having the eyes and chin shifted inferiorly, along with the nose being smaller in comparison to the normal weight category. This association between facial shape and obesity is significant at p<0.001. Principal component 1 (PC1) and PC2 also illustrated the above phenotypic features and both PCs were significantly different based on weight status (p<0.001). Genetic association testing indicated that shape variation along PC2 was significantly associated after Bonferroni correction with two SNPs in TEAD3 (p=0.002). Additionally, suggestive evidence for an association between phenotypic variation along PC1 and three SNPs located in RUNX2 was also identified (p=0.007).These results indicate that BMI and facial form are linked, and that genetic variation in TEAD3 (and possibly RUNX2) in the Hippo signaling pathway may be important for this relationship. Based on these results, further examination of the Hippo signaling pathway in both obesity and craniofacial form is warranted.Support or Funding InformationNIDCR: U01‐DE020078, R01‐DE016148, and R01‐DE027023This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.