The Trotter collection: A review of Mildred Trotter's hair research and an update for studies of human variation

OBJECTIVES

Mildred Trotter was an anatomist and physical anthropologist whose studies on hair morphology, growth, somatic distribution, and trait relationships to age and ethnogeographic population were foundational to the field of microscopical hair analysis. The collection of human hair samples she assembled for her research has been an underutilized resource for studies on human hair variation. We applied updated methods and reviewed Trotter's original data to reassess the relationship hair traits have to diverse population labels.

METHODS

Hair form and pigmentation patterns were measured from a subset of the hair samples accumulated by Trotter and we compared our data to Trotter's original results. Variability in hair traits were tested within individuals, within populations, and among ethnogeographic groups.

RESULTS

Measured hair cross-section dimensions and melanosome density and distribution revealed substantial variability within individuals and ethnogeographic populations. Hair traits were found to not be distinctly separable by ancestry but instead showed continuous variation across human populations. Trotter's measurements were precise and the dataset she compiled remains valid, though the conclusions should be reviewed in light of our current understanding of human variation.

DISCUSSION

Our findings support moving away from categorical ancestry classifications and eliminating the use of outdated racial typologies in favor of more descriptive trait analysis. Detailed analysis of trait pattern distributions are presented that may be useful for future research on human variation. We point to the need for additional research on human variation and hair trait relationships with reference to known population affinity.

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity

Introduction: Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Methods: Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. Results: We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. The clustering derived from netMUG achieved an adjusted Rand index of 1 with respect to the synthesized true labels. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these subgroups. Discussion: netMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.

Joint multi-ancestry and admixed GWAS reveals the complex genetics behind human cranial vault shape

The cranial vault in humans is highly variable, clinically relevant, and heritable, yet its genetic architecture remains poorly understood. Here, we conduct a joint multi-ancestry and admixed multivariate genome-wide association study on 3D cranial vault shape extracted from magnetic resonance images of 6772 children from the ABCD study cohort yielding 30 genome-wide significant loci. Follow-up analyses indicate that these loci overlap with genomic risk loci for sagittal craniosynostosis, show elevated activity cranial neural crest cells, are enriched for processes related to skeletal development, and are shared with the face and brain. We present supporting evidence of regional localization for several of the identified genes based on expression patterns in the cranial vault bones of E15.5 mice. Overall, our study provides a comprehensive overview of the genetics underlying normal-range cranial vault shape and its relevance for understanding modern human craniofacial diversity and the etiology of congenital malformations.

Interpreting SNP heritability in admixed populations

SNP heritability is defined as the proportion of phenotypic variance explained by genotyped SNPs and is believed to be a lower bound of heritability ( h 2 ), being equal to it if all causal variants are known. Despite the simple intuition behind , its interpretation and equivalence to h 2 is unclear, particularly in the presence of population structure and assortative mating. It is well known that population structure can lead to inflation in estimates. Here we use analytical theory and simulations to demonstrate that estimated with genome-wide restricted maximum likelihood (GREML) can be biased in admixed populations, even in the absence of confounding and even if all causal variants are known. This is because admixture generates linkage disequilibrium (LD), which contributes to the genetic variance, and therefore to heritability. GREML implicitly assumes this component is zero, which may not be true, particularly for traits under divergent or stabilizing selection in the source populations, leading under- or over-estimates of relative to h 2 . For the same reason, GREML estimates of local ancestry heritability will also be biased. We describe the bias in and as a function of admixture history and the genetic architecture of the trait and discuss its implications for genome-wide association and polygenic prediction.

Data-driven trait heritability-based extraction of human facial phenotypes

A genome-wide association study (GWAS) of a complex, multi-dimensional morphological trait, such as the human face, typically relies on predefined and simplified phenotypic measurements, such as inter-landmark distances and angles. These measures are predominantly designed by human experts based on perceived biological or clinical knowledge. To avoid use handcrafted phenotypes (i.e., a priori expert-identified phenotypes), alternative automatically extracted phenotypic descriptors, such as features derived from dimension reduction techniques (e.g., principal component analysis), are employed. While the features generated by such computational algorithms capture the geometric variations of the biological shape, they are not necessarily genetically relevant. Therefore, genetically informed data-driven phenotyping is desirable. Here, we propose an approach where phenotyping is done through a data-driven optimization of trait heritability, defined as the degree of variation in a phenotypic trait in a population that is due to genetic variation. The resulting phenotyping process consists of two steps: 1) constructing a feature space that models shape variations using dimension reduction techniques, and 2) searching for directions in the feature space exhibiting high trait heritability using a genetic search algorithm (i.e., heuristic inspired by natural selection). We show that the phenotypes resulting from the proposed trait heritability-optimized training differ from those of principal components in the following aspects: 1) higher trait heritability, 2) higher SNP heritability, and 3) identification of the same number of independent genetic loci with a smaller number of effective traits. Our results demonstrate that data-driven trait heritability-based optimization enables the automatic extraction of genetically relevant phenotypes, as shown by their increased power in genome-wide association scans.

Human scalp hair as a thermoregulatory adaptation

Humans are unique among mammals in having a functionally naked body with a hair-covered scalp. Scalp hair is exceptionally variable across populations within Homo sapiens. Neither the function of human scalp hair nor the consequences of variation in its morphology have been studied within an evolutionary framework. A thermoregulatory role for human scalp hair has been previously suggested. Here, we present experimental evidence on the potential evolutionary function of human scalp hair and variation in its morphology. Using a thermal manikin and human hair wigs at different wind speeds in a temperature and humidity-controlled environment, with and without simulated solar radiation, we collected data on the convective, radiative, and evaporative heat fluxes to and from the scalp in relation to properties of a range of hair morphologies, as well as a naked scalp. We find evidence for a significant reduction in solar radiation influx to the scalp in the presence of hair. Maximal evaporative heat loss potential from the scalp is reduced by the presence of hair, but the amount of sweat required on the scalp to balance the incoming solar heat (i.e., zero heat gain) is reduced in the presence of hair. Particularly, we find that hair that is more tightly curled offers increased protection against heat gain from solar radiation.

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity

Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these classes. NetMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.

Using data-driven phenotyping to investigate the impact of sex on 3D human facial surface morphology

The effects of sex on human facial morphology have been widely documented. Because sexual dimorphism is relevant to a variety of scientific and applied disciplines, it is imperative to have a complete and accurate account of how and where male and female faces differ. We apply a comprehensive facial phenotyping strategy to a large set of existing 3D facial surface images. We investigate facial sexual dimorphism in terms of size, shape, and shape variance. We also assess the ability to correctly assign sex based on shape, both for the whole face and for subregions. We applied a predefined data-driven segmentation to partition the 3D facial surfaces of 2446 adults into 63 hierarchically linked regions, ranging from global (whole face) to highly localized subparts. Each facial region was then analyzed with spatially dense geometric morphometrics. To describe the major modes of shape variation, principal components analysis was applied to the Procrustes aligned 3D points comprising each of the 63 facial regions. Both nonparametric and permutation-based statistics were then used to quantify the facial size and shape differences and visualizations were generated. Males were significantly larger than females for all 63 facial regions. Statistically significant sex differences in shape were also seen in all regions and the effects tended to be more pronounced for the upper lip and forehead, with more subtle changes emerging as the facial regions became more granular. Males also showed greater levels of shape variance, with the largest effect observed for the central forehead. Classification accuracy was highest for the full face (97%), while most facial regions showed an accuracy of 75% or greater. In summary, sex differences in both size and shape were present across every part of the face. By breaking the face into subparts, some shape differences emerged that were not apparent when analyzing the face as a whole. The increase in facial shape variance suggests possible evolutionary origins and may offer insights for understanding congenital facial malformations. Our classification results indicate that a high degree of accuracy is possible with only parts of the face, which may have implications for biometrics applications.

Exploring regional aspects of 3D facial variation within European individuals

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.

Hybrid autoencoder with orthogonal latent space for robust population structure inference

Analysis of population structure and genomic ancestry remains an important topic in human genetics and bioinformatics. Commonly used methods require high-quality genotype data to ensure accurate inference. However, in practice, laboratory artifacts and outliers are often present in the data. Moreover, existing methods are typically affected by the presence of related individuals in the dataset. In this work, we propose a novel hybrid method, called SAE-IBS, which combines the strengths of traditional matrix decomposition-based (e.g., principal component analysis) and more recent neural network-based (e.g., autoencoders) solutions. Namely, it yields an orthogonal latent space enhancing dimensionality selection while learning non-linear transformations. The proposed approach achieves higher accuracy than existing methods for projecting poor quality target samples (genotyping errors and missing data) onto a reference ancestry space and generates a robust ancestry space in the presence of relatedness. We introduce a new approach and an accompanying open-source program for robust ancestry inference in the presence of missing data, genotyping errors, and relatedness. The obtained ancestry space allows for non-linear projections and exhibits orthogonality with clearly separable population groups.

Decoding the Human Face: Challenges and Progress in Understanding the Genetics of Craniofacial Morphology

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.

Matching 3D Facial Shape to Demographic Properties by Geometric Metric Learning: A Part-Based Approach

Face recognition is a widely accepted biometric identifier, as the face contains a lot of information about the identity of a person. The goal of this study is to match the 3D face of an individual to a set of demographic properties (sex, age, BMI, and genomic background) that are extracted from unidentified genetic material. We introduce a triplet loss metric learner that compresses facial shape into a lower dimensional embedding while preserving information about the property of interest. The metric learner is trained for multiple facial segments to allow a global-to-local part-based analysis of the face. To learn directly from 3D mesh data, spiral convolutions are used along with a novel mesh-sampling scheme, which retains uniformly sampled points at different resolutions. The capacity of the model for establishing identity from facial shape against a list of probe demographics is evaluated by enrolling the embeddings for all properties into a support vector machine classifier or regressor and then combining them using a naive Bayes score fuser. Results obtained by a 10-fold cross-validation for biometric verification and identification show that part-based learning significantly improves the systems performance for both encoding with our geometric metric learner or with principal component analysis.

Stimulus Preference Assessment Decision-Making System (SPADS): A Decision-Making Model for Practitioners

A stimulus preference assessment (SPA) is a fundamental tool used by practitioners to predict stimuli that function as reinforcers. The Behavior Analyst Certification Board (BACB) requires that all certified behavior analysts and behavioral technicians be trained in SPA methodology (BACB, 2017). SPA procedures are used by nearly 9 out of 10 behavior analysts in the field (Graff & Karsten, 2012). Over the last 4 decades, there has been a litany of research on SPA procedures. Despite the universality of training, application, and research, discussions on the selection of SPA procedures have been sparse. Two peer-reviewed articles have focused on clinical decision making in the selection of SPA procedures. Karsten et al. (2011) introduced an in situ decision-making model, whereas Virues-Ortega et al. (2014) developed an a priori algorithm based on client and stimuli characteristics. The SPADS addresses the limitations of prior models by considering the effects of stimuli dimensions, client characteristics, relative administration times, and the outcomes agreement between two potentially efficacious, context-specfic SPA procedures.

Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations

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.

Genetic factors play an important role in shaping human facial features. Over the last decade, studies have identified numerous genes associated with various facial traits. The vast majority of these studies have focused on European or Asian populations, while African populations have been underrepresented. Increasing the diversity of these analyses can reveal novel associations and cross-population analyses can help deepen our understanding of known genetic associations. We therefore performed a genome scan of 3D facial features in African children from Tanzania and then compared our results to Europeans. We found 20 regions of the genome associated with facial shape in Tanzanian children, 10 of which were also present in Europeans, indicating evidence for a partly shared genetic basis for human facial shape across populations. In addition, about half of the genetic associations observed in Tanzanians were not present in Europeans, and some of the shared signals differed between populations in the specific genetic variants associated or specific facial traits affected. These results shed light on the shared and population-specific genetic contributors to normal-range facial variation.

Shared heritability of human face and brain shape

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.

High-throughput phenotyping methods for quantifying hair fiber morphology

Quantifying the continuous variation in human scalp hair morphology is of interest to anthropologists, geneticists, dermatologists and forensic scientists, but existing methods for studying hair form are time-consuming and not widely used. Here, we present a high-throughput sample preparation protocol for the imaging of both longitudinal (curvature) and cross-sectional scalp hair morphology. Additionally, we describe and validate a new Python package designed to process longitudinal and cross-sectional hair images, segment them, and provide measurements of interest. Lastly, we apply our methods to an admixed African-European sample (n = 140), demonstrating the benefit of quantifying hair morphology over classification, and providing evidence that the relationship between cross-sectional morphology and curvature may be an artefact of population stratification rather than a causal link.

3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies

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.

The Intersection of the Genetic Architectures of Orofacial Clefts and Normal Facial Variation

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.

Insights into the genetic architecture of the human face

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.

Effects of Male Facial Masculinity on Perceived Attractiveness

Studies suggest that high levels of masculinity in men can be a signal of 'better genes' as well as low parental investment. It is the trade-off between these two qualities that has led to the hypothesis that women's preferences for male masculinity are condition-dependent, yet, not all studies support this hypothesis. In addition, there is evidence that more average faces would be perceived as more attractive. Here we study the variation in masculinity preferences of a cohort of heterosexual women (n=769), using manipulated 3D faces of male subjects. We used linear mixed models to test for effects of various covariates such as relationship status, use of hormonal contraception, sociosexual orientation and self-perceived attractiveness on preference for masculinity. Our results show that women's sociosexual orientation has a positive correlation with masculinity preference while using hormonal contraception decreases this preference. None of the other covariates displayed any significant effect on masculinity preference. The initial level of masculinity of the faces (very low, low, average, high and very high) was also shown to affect this preference, where we found a significant preference for higher masculinity in the very low and average group, while no preference was found in the other groups. Our findings support the notion that condition-dependent variables have very small effects, if any, on women's preference for masculinity in men.

Microscopical discrimination of human head hairs sharing a mitochondrial haplogroup

In forensic analyses, determining the level of consensus among examiners for hair comparison conclusions and ancestry identifications is important for assessing the scientific validity of microscopical hair examinations. Here, we present data from an interlaboratory study on the accuracy of microscopical hair comparisons among a subset of experienced hair examiners currently analyzing hair in forensic laboratories across the United States. We examined how well microscopical analysis of hair can reliably be used to differentiate hair samples, many of which were macroscopically similar. Using cut hair samples, many sharing similar macroscopic and microscopic features, collected from individuals who share the same mitochondrial haplogroup as an indication of genetic relatedness, we tested multiple aspects that could impact hair comparisons. This research tested the extent to which morphological features related to ancestry and hair length influence conclusions. Microscopical hair examinations yielded accurate assessments of inclusion/exclusion relative to the reference samples among 85% of the pairwise comparisons. We found shorter hairs had reduced levels of accuracy and hairs from populations examiners were not familiar with may have impacted their ability to resolve features. The reliability of ancestry determinations is not yet clear, but we found indications that the existing categories are only somewhat related to current ethnic and genetic variation. Our results provide support for the continued utility of microscopical comparison of hairs within forensic laboratories and to advocate for a combined analytical approach using both microscopical analysis and mtDNA data on all forensic analyses of hair.

Sources of variation in the 3dMDface and Vectra H1 3D facial imaging systems

As technology advances and collaborations grow, our ability to finely quantify and explore morphological variation in 3D structures can enable important discoveries and insights into clinical, evolutionary, and genetic questions. However, it is critical to explore and understand the relative contribution of potential sources of error to the structures under study. In this study, we isolated the level of error in 3D facial images attributable to four sources, using the 3dMDface and Vectra H1 camera systems. When the two camera systems are used separately to image human participants, this analysis finds an upper bound of error potentially introduced by the use of the 3dMDface or Vectra H1 camera systems, in conjunction with the MeshMonk registration toolbox, at 0.44 mm and 0.40 mm, respectively. For studies using both camera systems, this upper bound increases to 0.85 mm, on average, and there are systematic differences in the representation of the eyelids, nostrils, and mouth by the two camera systems. Our results highlight the need for careful assessment of potential sources of error in 3D images, both in terms of magnitude and position, especially when dealing with very small measurements or performing many tests.

A Multivariate Approach to Determine the Dimensionality of Human Facial Asymmetry

Many studies have suggested that developmental instability (DI) could lead to asymmetric development, otherwise known as fluctuating asymmetry (FA). Several attempts to unravel the biological meaning of FA have been made, yet the main step in estimating FA is to remove the effects of directional asymmetry (DA), which is defined as the average bilateral asymmetry at the population level. Here, we demonstrate in a multivariate context that the conventional method of DA correction does not adequately compensate for the effects of DA in other dimensions of asymmetry. This appears to be due to the presence of between-individual variation along the DA dimension. Consequently, we propose to decompose asymmetry into its different orthogonal dimensions, where we introduce a new measure of asymmetry, namely fluctuating directional asymmetry (F-DA). This measure describes individual variation in the dimension of DA, and can be used to adequately correct the asymmetry measurements for the presence of DA. We provide evidence that this measure can be useful in disentangling the different dimensions of asymmetry, and further studies on this measure can provide valuable insight into the underlying biological processes leading to these different asymmetry dimensions.

Hunting for genes that shape human faces: Initial successes and challenges for the future

There is ample evidence from heritability studies, genetic syndromes and experimental animal models that facial morphology is strongly influenced by genes. In this brief review, we present an up-to-date overview of the efforts to identify genes associated with the size and shape of human facial features. We discuss recent methodological advances that have led to breakthroughs, but also the multitude of challenges facing the field. We offer perspective on possible applications of this line of research, particularly in the context of the precision genomics movement.

Facial recognition from DNA using face-to-DNA classifiers

Facial recognition from DNA refers to the identification or verification of unidentified biological material against facial images with known identity. One approach to establish the identity of unidentified biological material is to predict the face from DNA, and subsequently to match against facial images. However, DNA phenotyping of the human face remains challenging. Here, another proof of concept to biometric authentication is established by using multiple face-to-DNA classifiers, each classifying given faces by a DNA-encoded aspect (sex, genomic background, individual genetic loci), or by a DNA-inferred aspect (BMI, age). Face-to-DNA classifiers on distinct DNA aspects are fused into one matching score for any given face against DNA. In a globally diverse, and subsequently in a homogeneous cohort, we demonstrate preliminary, but substantial true (83%, 80%) over false (17%, 20%) matching in verification mode. Consequences of future efforts include forensic applications, necessitating careful consideration of ethical and legal implications for privacy in genomic databases.

MeshMonk: Open-source large-scale intensive 3D phenotyping

Dense surface registration, commonly used in computer science, could aid the biological sciences in accurate and comprehensive quantification of biological phenotypes. However, few toolboxes exist that are openly available, non-expert friendly, and validated in a way relevant to biologists. Here, we report a customizable toolbox for reproducible high-throughput dense phenotyping of 3D images, specifically geared towards biological use. Given a target image, a template is first oriented, repositioned, and scaled to the target during a scaled rigid registration step, then transformed further to fit the specific shape of the target using a non-rigid transformation. As validation, we use n = 41 3D facial images to demonstrate that the MeshMonk registration is accurate, with 1.26 mm average error, across 19 landmarks, between placements from manual observers and using the MeshMonk toolbox. We also report no variation in landmark position or centroid size significantly attributable to landmarking method used. Though validated using 19 landmarks, the MeshMonk toolbox produces a dense mesh of vertices across the entire surface, thus facilitating more comprehensive investigations of 3D shape variation. This expansion opens up exciting avenues of study in assessing biological shapes to better understand their phenotypic variation, genetic and developmental underpinnings, and evolutionary history.

Practical and Ethical Considerations of Using Personal DNA Tests with Middle-School-Aged Learners

Personalized genetic information is not widely utilized as a resource in learning environments, in part because of concerns about data privacy and the treatment of sensitive personal information. Here we describe the implementation of a curriculum centered on analyzing personalized genetic-ancestry test results during two-week science summer camps for middle-school-aged youth. Our research focused on how the examination of personalized DNA results affected learners' subsequent perceptions and performance, as measured by in-camp pre- and post-tests and surveys, analysis of voluntary student talk captured by audio and video recordings, and periodic one-on-one post-camp follow-ups. The curriculum was grounded in Next Generation Science Standards (NGSS) and focused around the central question of "Who am I?" Campers approached this question via guided lessons designed to shed light on their genetic uniqueness, the many attributes of their genotype and phenotype shared with others, their more distant genetic and evolutionary ancestries, and their roles as active agents in the healthy continuation of their lives. Data relevant to these questions came from edited subsets of ancestry-informative single-nucleotide polymorphisms (SNPs) and phenotype-related SNPs from the campers' genotype results, which their parents had received from a direct-to-consumer vendor. Our approaches to data privacy and the discovery, disclosure, and discussion of sensitive information on paternity, carrier status, and ancestry can be usefully applied and modified for many educational contexts. On the basis of our pilot implementations, we recommend additional and expanded research on how to incorporate personalized genetic ancestry information in a variety of learning contexts.

Measuring asymmetry from high-density 3D surface scans: An application to human faces

Perfect bilateral symmetry is the optimal outcome of the development of bilateral traits in the absence of developmental perturbations. Any random perturbation in this perfect symmetrical state is called Fluctuating Asymmetry (FA). Many studies have been conducted on FA as an indicator of Developmental Instability (DI) and its possible link with stress and individual quality in general and with attractiveness, health and level of masculinity or femininity in humans. Most human studies of facial asymmetry use 2D pictures and a limited number of landmarks. We developed a protocol to utilize high-density 3D scans of human faces to measure the level of asymmetry. A completely symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to validate the mapping precision. The protocol's accuracy in FA calculation is assessed, and results show that a spatially dense approach is more accurate. In addition, it generates an integrated asymmetry estimate across the entire face. Finally, the automatic nature of the protocol provides a great advantage by omitting the tedious step of manual landmark indication on the biological structure of interest.

Shades of complexity: New perspectives on the evolution and genetic architecture of human skin

Like many highly variable human traits, more than a dozen genes are known to contribute to the full range of skin color. However, the historical bias in favor of genetic studies in European and European-derived populations has blinded us to the magnitude of pigmentation's complexity. As deliberate efforts are being made to better characterize diverse global populations and new sequencing technologies, better measurement tools, functional assessments, predictive modeling, and ancient DNA analyses become more widely accessible, we are beginning to appreciate how limited our understanding of the genetic bases of human skin color have been. Novel variants in genes not previously linked to pigmentation have been identified and evidence is mounting that there are hundreds more variants yet to be found. Even for genes that have been exhaustively characterized in European populations like MC1R, OCA2, and SLC24A5, research in previously understudied groups is leading to a new appreciation of the degree to which genetic diversity, epistatic interactions, pleiotropy, admixture, global and local adaptation, and cultural practices operate in population-specific ways to shape the genetic architecture of skin color. Furthermore, we are coming to terms with how factors like tanning response and barrier function may also have influenced selection on skin throughout human history. By examining how our knowledge of pigmentation genetics has shifted in the last decade, we can better appreciate how far we have come in understanding human diversity and the still long road ahead for understanding many complex human traits.

Six NSCL/P Loci Show Associations With Normal-Range Craniofacial Variation

Objectives: Orofacial clefting is one of the most prevalent craniofacial malformations. Previous research has demonstrated that unaffected relatives of patients with non-syndromic cleft lip with/without cleft palate (NSCL/P) show distinctive facial features, which can be an expression of underlying NSCL/P susceptibility genes. These results support the hypothesis that genes involved in the occurrence of a cleft also play a role in normal craniofacial development. In this study, we investigated the influence of genetic variants associated with NSCL/P on normal-range variation in facial shape.

Methods: A literature review of genome wide association studies (GWAS) investigating the genetic etiology of NSCL/P was performed, resulting in a list of 75 single nucleotide polymorphisms (SNPs) located in 38 genetic loci. Genotype data were available for 65 of these selected SNPs in three datasets with a combined sample size of 7,418 participants of European ancestry, whose 3D facial images were also available. The effect of each SNP was tested using a multivariate canonical correlation analysis (CCA) against 63 hierarchically-constructed facial segments in each of the three datasets and meta-analyzed. This allowed for the investigation of associations between SNPs known to be involved in NSCL/P and normal-range facial shape variations in a global-to-local perspective, without preselecting specific facial shape features or characteristics.

Results: Six NSCL/P SNPs showed significant associations with variation in normal-range facial morphology. rs6740960 showed significant effects in the chin area (p = 3.71 × 10⁻²⁸). This SNP lies in a non-coding area. Another SNP, rs227731 near the NOG gene, showed a significant effect in the philtrum area (p = 1.96 × 10⁻¹⁶). Three SNPs showed significant effects on the shape of the nose. rs742071 (p = 8.71 × 10⁻¹⁴), rs34246903 (p = 6.87 × 10⁻¹²), and rs10512248 (p = 8.4 × 10⁻⁹). Respectively, these SNPs are annotated to PAX7, MSX1, and PTCH1. Finally, rs7590268, an intron variant of THADA, showed an effect in the shape of the supraorbital ridge (p = 3.84 × 10⁻⁷).

Conclusions: This study provides additional evidence NSCL/P-associated genetic variants influence normal-range craniofacial morphology, with significant effects observed for the chin, the nose, the supraorbital ridges and the philtrum area.

SNPs Associated With Testosterone Levels Influence Human Facial Morphology

Many factors influence human facial morphology, including genetics, age, nutrition, biomechanical forces, and endocrine factors. Moreover, facial features clearly differ between males and females, and these differences are driven primarily by the influence of sex hormones during growth and development. Specific genetic variants are known to influence circulating sex hormone levels in humans, which we hypothesize, in turn, affect facial features. In this study, we investigated the effects of testosterone-related genetic variants on facial morphology. We tested 32 genetic variants across 22 candidate genes related to levels of testosterone, sex hormone-binding globulin (SHGB) and dehydroepiandrosterone sulfate (DHEAS) in three cohorts of healthy individuals for which 3D facial surface images were available (Pittsburgh 3DFN, Penn State and ALSPAC cohorts; total n = 7418). Facial shape was described using a recently developed extension of the dense-surface correspondence approach, in which the 3D facial surface was partitioned into a set of 63 hierarchically organized modules. Each variant was tested against each of the facial surface modules in a multivariate genetic association-testing framework and meta-analyzed. Additionally, the association between these candidate SNPs and five facial ratios was investigated in the Pittsburgh 3DFN cohort. Two significant associations involving intronic variants of SHBG were found: both rs12150660 (p = 1.07E-07) and rs1799941 (p = 6.15E-06) showed an effect on mandible shape. Rs8023580 (an intronic variant of NR2F2-AS1) showed an association with the total and upper facial width to height ratios (p = 9.61E-04 and p = 7.35E-04, respectively). These results indicate that testosterone-related genetic variants affect normal-range facial morphology, and in particular, facial features known to exhibit strong sexual dimorphism in humans.

High Levels of Copy Number Variation of Ampliconic Genes across Major Human Y Haplogroups

Because of its highly repetitive nature, the human male-specific Y chromosome remains understudied. It is important to investigate variation on the Y chromosome to understand its evolution and contribution to phenotypic variation, including infertility. Approximately 20% of the human Y chromosome consists of ampliconic regions which include nine multi-copy gene families. These gene families are expressed exclusively in testes and usually implicated in spermatogenesis. Here, to gain a better understanding of the role of the Y chromosome in human evolution and in determining sexually dimorphic traits, we studied ampliconic gene copy number variation in 100 males representing ten major Y haplogroups world-wide. Copy number was estimated with droplet digital PCR. In contrast to low nucleotide diversity observed on the Y in previous studies, here we show that ampliconic gene copy number diversity is very high. A total of 98 copy-number-based haplotypes were observed among 100 individuals, and haplotypes were sometimes shared by males from very different haplogroups, suggesting homoplasies. The resulting haplotypes did not cluster according to major Y haplogroups. Overall, only two gene families (RBMY and TSPY) showed significant differences in copy number among major Y haplogroups, and the haplogroup of a male could not be predicted based on his ampliconic gene copy numbers. Finally, we did not find significant correlations either between copy number variation and individual's height, or between the former and facial masculinity/femininity. Our results suggest rapid evolution of ampliconic gene copy numbers on the human Y, and we discuss its causes.

Genome-wide mapping of global-to-local genetic effects on human facial shape

Genome-wide association scans of complex multipartite traits like the human face typically use preselected phenotypic measures. Here we report a data-driven approach to phenotyping facial shape at multiple levels of organization, allowing for an open-ended description of facial variation while preserving statistical power. In a sample of 2,329 persons of European ancestry, we identified 38 loci, 15 of which replicated in an independent European sample (n = 1,719). Four loci were completely new. For the others, additional support (n = 9) or pleiotropic effects (n = 2) were found in the literature, but the results reported here were further refined. All 15 replicated loci highlighted distinctive patterns of global-to-local genetic effects on facial shape and showed enrichment for active chromatin elements in human cranial neural crest cells, suggesting an early developmental origin of the facial variation captured. These results have implications for studies of facial genetics and other complex morphological traits.

Focus on African diversity confirms complexity of skin pigmentation genetics

Renewed focus on African populations confirms the complexity of skin pigmentation genetics, and suggests future directions for pigmentation research.

Population genomics of Mesolithic Scandinavia: Investigating early postglacial migration routes and high-latitude adaptation

Scandinavia was one of the last geographic areas in Europe to become habitable for humans after the Last Glacial Maximum (LGM). However, the routes and genetic composition of these postglacial migrants remain unclear. We sequenced the genomes, up to 57× coverage, of seven hunter-gatherers excavated across Scandinavia and dated from 9,500–6,000 years before present (BP). Surprisingly, among the Scandinavian Mesolithic individuals, the genetic data display an east–west genetic gradient that opposes the pattern seen in other parts of Mesolithic Europe. Our results suggest two different early postglacial migrations into Scandinavia: initially from the south, and later, from the northeast. The latter followed the ice-free Norwegian north Atlantic coast, along which novel and advanced pressure-blade stone-tool techniques may have spread. These two groups met and mixed in Scandinavia, creating a genetically diverse population, which shows patterns of genetic adaptation to high latitude environments. These potential adaptations include high frequencies of low pigmentation variants and a gene region associated with physical performance, which shows strong continuity into modern-day northern Europeans.

The Scandinavian peninsula was the last part of Europe to be colonized after the Last Glacial Maximum. The migration routes, cultural networks, and the genetic makeup of the first Scandinavians remain elusive and several hypotheses exist based on archaeology, climate modeling, and genetics. By analyzing the genomes of early Scandinavian hunter-gatherers, we show that their migrations followed two routes: one from the south and another from the northeast along the ice-free Norwegian Atlantic coast. These groups met and mixed in Scandinavia, creating a population more diverse than contemporaneous central and western European hunter-gatherers. As northern Europe is associated with cold and low light conditions, we investigated genomic patterns of adaptation to these conditions and genes known to be involved in skin pigmentation. We demonstrate that Mesolithic Scandinavians had higher levels of light pigmentation variants compared to the respective source populations of the migrations, suggesting adaptation to low light levels and a surprising signal of genetic continuity in TMEM131, a gene that may be involved in long-term adaptation to the cold.

Investigating the case of human nose shape and climate adaptation

The evolutionary reasons for variation in nose shape across human populations have been subject to continuing debate. An import function of the nose and nasal cavity is to condition inspired air before it reaches the lower respiratory tract. For this reason, it is thought the observed differences in nose shape among populations are not simply the result of genetic drift, but may be adaptations to climate. To address the question of whether local adaptation to climate is responsible for nose shape divergence across populations, we use Qst–Fst comparisons to show that nares width and alar base width are more differentiated across populations than expected under genetic drift alone. To test whether this differentiation is due to climate adaptation, we compared the spatial distribution of these variables with the global distribution of temperature, absolute humidity, and relative humidity. We find that width of the nares is correlated with temperature and absolute humidity, but not with relative humidity. We conclude that some aspects of nose shape may indeed have been driven by local adaptation to climate. However, we think that this is a simplified explanation of a very complex evolutionary history, which possibly also involved other non-neutral forces such as sexual selection.

The study of human adaptation is essential to our understanding of disease etiology. Evolutionary investigations into why certain disease phenotypes such as sickle-cell anemia and lactose intolerance occur at different rates in different populations have led to a better understanding of the genetic and environmental risk factors involved. Similarly, research into the geographical distribution of skin pigmentation continues to yield important clues regarding risk of vitamin D deficiency and skin cancer. Here, we investigate whether variation in the shape of the external nose across populations has been driven by regional differences in climate. We find that variation in both nares width and alar base width appear to have experienced accelerated divergence across human populations. We also find that the geospatial distribution of nares width is correlated with temperature, and absolute humidity, but not with relative humidity. Our results support the claim that local adaptation to climate may have had a role in the evolution of nose shape differences across human populations.

Are there vocal cues to human developmental stability? Relationships between facial fluctuating asymmetry and voice attractiveness

Fluctuating asymmetry (FA), deviation from perfect bilateral symmetry, is thought to reflect an organism's relative inability to maintain stable morphological development in the face of environmental and genetic stressors. Previous research has documented negative relationships between FA and attractiveness judgments in humans, but scant research has explored relationships between the human voice and this putative marker of genetic quality in either sex. Only one study (and in women only) has explored relationships between vocal attractiveness and asymmetry of the face, a feature-rich trait space central in prior work on human genetic quality and mate choice. We therefore examined this relationship in three studies comprising 231 men and 240 women from two Western samples as well as Hadza hunter-gatherers of Tanzania. Voice recordings were collected and rated for attractiveness, and FA was computed from two-dimensional facial images as well as, for a subset of men, three-dimensional facial scans. Through meta-analysis of our results and those of prior studies, we found a negative association between FA and vocal attractiveness that was highly robust and statistically significant whether we included effect sizes from previously published work, or only those from the present research, and regardless of the inclusion of any individual sample or method of assessing FA (e.g., facial or limb FA). Weighted mean correlations between FA and vocal attractiveness across studies were -.23 for men and -.29 for women. This research thus offers strong support for the hypothesis that voices provide cues to genetic quality in humans.

The Munroe-Meyer Approach: Continuous Integration of Didactic Instruction, Research, and Clinical Practice

Increased demand for applied behavior analysis (ABA) services has increased the need for additional masters-level practitioners and doctoral-level academicians and clinical directors. Based on these needs, the University of Nebraska Medical Center's (UNMC) Munroe-Meyer Institute has developed a PhD program. The academic structure at UNMC allowed us to create our PhD program in a relatively quick and efficient manner. Our PhD program has many unique features, including (a) close integration of didactic instruction with clinical and research training provided by leading experts in ABA in which students immediately apply concepts introduced in the classroom during coordinated clinical and research practica; (b) structured grant writing training in which students learn to write and submit an NIH-level grant;

Evaluation of increasing antecedent specificity in goal statements on adherence to positive behavior-management strategies

We evaluated the impact of antecedent specificity in goal statements on adherence to positive behavior-management strategies. Teaching staff were recruited from 2 different school settings where there were routine expectations to use behavior-specific praise in the classroom, but adherence was poor. In a concurrent multiple baseline design, the use of behavior-specific praise by 4 participants was found to be unaffected by goal statements that increasingly specified the behavior to be used and the conditions under which the behavior should occur. However, adherence by 3 of the 4 participants did change when goal statements included teacher-specified frequencies with which the behavior should occur. Results were systematically replicated in a second study in which, in a concurrent multiple baseline design, 3 participants showed marked increases in adherence when goal statements specified the target behavior, the conditions under which it should occur, and the frequency with which it should occur.