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
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