Fluctuating and directional asymmetry are aspects of morphological variation widely used to infer environmental and genetic factors affecting facial phenotypes. However, the genetic basis and environmental determinants of both asymmetry types is far from being completely known. The analysis of facial asymmetries in admixed individuais can be of help to characterize the impact of a genome's heterozygosity on the deveiopmental basis of both fl.uctuating and directional asymmetries. Here we characterize the association between genetic ancestry and individual asymmetry on a sample of Latin-American admixed populations. To do so, three-dimensional (3D) facial shape attributes were explored on a sample of 4,104 volunteers aged between 18 and 85 years. Individual ancestry and heterozygosity was estimated using more than 730,000 genome-wide markers. Multivariate techniques applied to geometric morphometric data were used to evaluate the magnitude and significance of directional and ftuctuating asymmetry (FA), as well as correiations and multipie regressions aimed to estimate the relationship between facial FA scores and heterozygosity and a set of covariates. Resuits indicate that directional and FA are both signi:ficant, the former being the strongest expression of asymmetry in this sample. In addition, our analyses suggest that there are some specific patterns of facial asymmetries characterizing the different ancestry groups. Finally, we find that more heterozygous individuais exhibit lower leveis of asymmetry. Our results highlight the importance of including ancestry-admixture estimators, especially when the analyses are aimed to compare leveis of asymmetries on groups differing on socioeconomic leveis, as a proxy to estimate developmental noise. Am J Phys Anthropol 000:000--000, 2015.
Accurate gathering of phenotypic information is a key aspect in several subject matters, including biometrics, biomedical analysis, forensics, and many other. Automatic identification of anatomical structures of biometric interest, such as fingerprints, iris patterns, or facial traits, are extensively used in applications like access control and anthropological research, all having in common the drawback of requiring intrusive means for acquiring the required information. In this regard, the ear structure has multiple advantages. Not only the ear's biometric markers can be easily captured from the distance with non intrusive methods, but also they experiment almost no changes over time, and are not influenced by facial expressions. Here we present a new method based on Geometric Morphometrics and Deep Learning for automatic ear detection and feature extraction in the form of landmarks. A convolutional neural network was trained with a set of manually landmarked examples. The network is able to provide morphometric landmarks on ears' images automatically, with a performance that matches human landmarking. The feasibility of using ear landmarks as feature vectors opens a novel spectrum of biometrics applications.
The expression of facial asymmetries has been recurrently related with poverty and/or disadvantaged socioeconomic status. Departing from the developmental instability theory, previous approaches attempted to test the statistical relationship between the stress experienced by individuals grown in poor conditions and an increase in facial and corporal asymmetry. Here we aim to further evaluate such hypothesis on a large sample of admixed Latin Americans individuals by exploring if low socioeconomic status individuals tend to exhibit greater facial fluctuating asymmetry values. To do so, we implement Procrustes analysis of variance and Hierarchical Linear Modelling (HLM) to estimate potential associations between facial fluctuating asymmetry values and socioeconomic status. We report significant relationships between facial fluctuating asymmetry values and age, sex, and genetic ancestry, while socioeconomic status failed to exhibit any strong statistical relationship with facial asymmetry. These results are persistent after the effect of heterozygosity (a proxy for genetic ancestry) is controlled in the model. Our results indicate that, at least on the studied sample, there is no relationship between socioeconomic stress (as intended as low socioeconomic status) and facial asymmetries.
Both modern humans (MHs) and Neanderthals successfully settled across western Eurasian cold-climate landscapes. Among the many adaptations considered as essential to survival in such landscapes, changes in the nasal morphology and/or function aimed to humidify and warm the air before it reaches the lungs are of key importance. Unfortunately, the lack of soft-tissue evidence in the fossil record turns difficult any comparative study of respiratory performance. Here, we reconstruct the internal nasal cavity of a Neanderthal plus two representatives of climatically divergent MH populations (southwestern Europeans and northeastern Asians). The reconstruction includes mucosa distribution enabling a realistic simulation of the breathing cycle in different climatic conditions via computational fluid dynamics. Striking across-specimens differences in fluid residence times affecting humidification and warming performance at the anterior tract were found under cold/dry climate simulations. Specifically, the Asian model achieves a rapid air conditioning, followed by the Neanderthals, whereas the European model attains a proper conditioning only around the medium-posterior tract. In addition, quantitative-genetic evolutionary analyses of nasal morphology provided signals of stabilizing selection for MH populations, with the removal of Arctic populations turning covariation patterns compatible with evolution by genetic drift. Both results indicate that, departing from important craniofacial differences existing among Neanderthals and MHs, an advantageous species-specific respiratory performance in cold climates may have occurred in both species. Fluid dynamics and evolutionary biology independently provided evidence of nasal evolution, suggesting that adaptive explanations regarding complex functional phenotypes require interdisciplinary approaches aimed to quantify both performance and evolutionary signals on covariation patterns.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.