Fluctuating asymmetry, a measure of small random deviations from perfect bodily symmetry, was previously considered an honest indicator of genetic quality, but this paper says it is not

Formal models for the study of the relationship between fluctuating asymmetry and fitness in humans. Arodi Farrera. American Journal of Biological Anthropology, July 21 2022. https://doi.org/10.1002/ajpa.24588

Abstract

Objectives: To evaluate three of the main verbal models that have been proposed to explain the relationship between fluctuating asymmetry and fitness in humans: the “good genes,” the “good development,” and the “growth” hypotheses.

Materials and Methods: A formal model was generated for each verbal model following three steps. First, based on the literature, a theoretical causal model and the theoretical object of inquiry were outlined. Second, an empirical causal model and the targets of inference were defined using observational data of facial asymmetries and life-history traits related to fitness. Third, generalized linear models and causal inference were used as the estimation strategy.

Results: The results suggest that the theoretical and empirical assumptions of the “good genes” hypothesis should be reformulated. The results were compatible with most of the empirical assumptions of “the good development” hypothesis but suggest that further discussion of its theoretical assumptions is needed. The results were less informative about the “growth” hypothesis, both theoretically and empirically. There was a positive association between facial fluctuating asymmetry and the number of offspring that was not compatible with any of the empirical causal models evaluated.

Conclusions: Although the three hypotheses focus on different aspects of the link between asymmetry and fitness, their overlap opens the possibility of a unified theory on the subject. The results of this study make explicit which assumptions need to be updated and discussed, facilitating the advancement of this area of research. Overall, this study elucidates the potential benefit of using formal models for theory revision and development.

4 DISCUSSION

In this contribution, I evaluated three of the most common verbal models used to understand the relationship between FA and fitness in humans: the “good genes,” the “good development,” and the “growth” hypotheses. For this purpose, I generated formal models (i.e., estimands and causal frameworks) for each hypothesis and tested them in the particular case of facial asymmetries and reproductive success.

4.1 Theoretical assumptions

The present study shows that even if the approaches are different, some of the theoretical assumptions overlap across hypotheses (Figure 1), opening the opportunity for a unified formal model. Nonetheless, they show differences in two key assumptions. First, these hypotheses differ in whether they consider that FA reflects some cost to the individual, distinguishing between FA as a reliable signal of DS that reflects the quality of the individual (H1 and H2: symmetrical traits are costly) and as a reliable signal that requires no additional cost because it is tightly associated with some attribute of the individual (H3: allometric constraints that link body size and FA). This distinction has been discussed mainly in the framework of signaling theory (Barker et al., 2019), but in the context of human asymmetries and fitness, this discussion is currently problematic primarily because the way these concepts have been applied overlooks recent conceptual advances.

From the framework of signaling theory, attributes other than physiological information are recognized as signals (e.g., embodied capital or noetic attributes, Barker et al., 2019). A broader concept like this would allow for more comprehensive verbal models of the relationship between FA and fitness in humans, in which cultural practices such as the use of makeup (Killian et al., 2018), and social norms like standards of beauty (Kleisner et al., 2017) are also included in the interpretation and scope of the research. Signaling theory also recognizes that the way multiple signals are integrated with each other and with socioecological factors is an important source of information (Patricelli & Hebets, 2016). This would promote studying asymmetry along with other types of signals, as has been done during the last decade on topics such as mate choice (Jones & Jaeger, 2019; van Dogen et al., 2020) or the individual's health status (Foo et al., 2017; Mogilski & Welling, 2017). Addressing multiple signals as an integrated signaling phenotype or explaining how they are theoretically related to each other (e.g., Luoto et al., 2021) could improve and extend our understanding of the topic. Moreover, instead of being considered a static measurement (i.e., values computed at one point in time), individual asymmetries could be explored over different timescales. In the dynamic context of face-to-face interaction, for instance, asymmetric facial movement can be perceived as unattractive, regardless of the static asymmetry score of the individual (Hughes & Aung, 2018) because, for example, it conveys information about the sender's age (Kamachi et al., 2019). Taking into account that the causes and effects of asymmetry can be different in static and dynamic contexts could also clarify some of the contradictory evidence on the subject.

Another theoretical assumption in which the hypotheses evaluated differ is whether they highlight the role of developmental plasticity (i.e., phenotypic adjustments in response to the environment) on the expression of phenotypic variation and, particularly, on the production of asymmetric traits. Specifically, this assumption differentiates between research on FA variation that focuses on its genetic basis (H1: symmetry reflects good genes) and research that focuses on the development pathways that lead to such within-individual variation (H2 and H3: symmetry reflects the interplay between the organism and its circumstances). Although the former ignores the idea that has been present since the 1980s in the field of evolutionary developmental biology (Müller, 2007) that the influence of genotype on the phenotype is structured by developmental processes, the role of development in the latter is not entirely clear either. New verbal and formal models with a different set of theoretical assumptions are needed to get a better, refined representation of the role of development in the relationship between FA and fitness in humans.

4.2 Empirical assumptions

This study also shows some similarities and differences between hypotheses when the results are compared with the expectations derived from the empirical assumptions. In the case of the “good genes” hypothesis, the corresponding empirical causal model expects that individuals with greater facial FA values have less reproductive success than individuals with less asymmetry. Moreover, it expects that part of the phenotypic variance of facial FA is explained by genetic variation. In contrast, I found that individuals with greater facial FA values have more offspring and a heritability close to zero (i.e., almost none or little facial FA variation is explained by genetic variation). The latter result is the first report of heritability of FA in the human face and is consistent with previous research showing very low or no heritability of other traits in humans and other species (Johnson et al., 2008; Leamy & Klingenberg, 2005). These results suggest that the empirical causal model for this hypothesis needs to be revised and refined.

The empirical causal model derived from the “good development” hypothesis posits that because FA is the result of poor health, no direct link should be found between facial FA and the number of offspring. In contrast, the results showed a positive effect of facial FA on the number of offspring. On the other hand, based on the intergenerational maternal effect (Wells, 2018), this empirical causal model assumes that the short stature of some individuals is the result of a suboptimal maternal niche and that individuals who develop under these conditions may favor quantity over quality of offspring, and vice versa. The results of this study were compatible with this assumption. Specifically, it was found that, regardless of asymmetry, individuals with poor health status (measured as adult height) had more children, an effect reported in some previous studies (e.g., Krzyzanowska et al., 2015), but not in others (e.g., Helle, 2008). The results were also compatible with the expected negative effect of height on facial FA in this hypothesis, an effect reported in previous studies (Kirchengast, 2019; Özener & Ertuğrul, 2011) using FA measurements of non-facial traits. In other words, these results are compatible with most of the assumptions derived from the empirical causal model for this hypothesis, except for the assumption of no direct link between facial FA and the number of offspring, which should be refined to include potential mechanisms that may explain the relationship between these variables.

The empirical assumptions of the “growth” hypothesis are unclear as to whether facial FA directly and/or indirectly influences the number of offspring, what would be the expected direction of this effect, or what mechanism would be responsible. Therefore, it is currently not possible to interpret the results obtained on this assumption. Nonetheless, this empirical causal model posits two additional assumptions. First, that body and face size are allometrically related in adults and that facial FA is a by-product of individual growth. In contrast to previous studies (e.g., Gateño et al., 2018; Mitteroecker et al., 2013), the results were compatible, with high uncertainty, with an effect close to zero. These results suggest that more discussion is needed on the empirical causal model derived for this hypothesis.

In all hypotheses, I found a positive association between facial FA and the number of offspring, which is not consistent with any of the three empirical causal models evaluated. This result suggests that additional explanatory variables should be formally included in these models to further understand and test this relationship. One candidate variable could be the age-dependent pattern of FA expression (e.g., Wilson & Manning, 1996). Since facial FA can be a by-product of soft tissue aging, older individuals may express higher values. Further, this link could be related to the number of offspring in two ways. First, in line with the “good development” hypothesis, since reproduction takes time and considerable metabolic demands, individuals who have reproduced more and are older may also be more asymmetric. Second, in line with the “growth” hypothesis, fully developed (older and bigger) and therefore more asymmetric individuals could be those who have also had more opportunities to reproduce. Datasets collected specifically for testing these verbal models and updated formal models are needed to confirm the role of aging or any other variable outside those proposed in this work.

There are at least two factors related to the estimation strategy that limit the interpretation of these results (section 4.2). One of them is the sample over which inferences were drawn. The dataset used in this study was not explicitly collected to answer the theoretical object of inquiry (i.e., the relationship between FA and fitness), and thus, the empirical causal models were designed after data collection, instead of before as required to warrant causal claims (Rohrer, 2018). Other potential factors are related to bias in the computation of FA values, which have been extensively reviewed elsewhere (Graham, 2021b; Graham et al., 2010), including the presence of other forms of asymmetry, measurement error, or mixtures of additive and multiplicative errors. These limitations suggest that these results (section 4.1) must be replicated using more rigorous estimation strategies and other databases that allow comparing the three hypotheses.

Future studies could further benefit from revising, in light of theory development, the statistical practice associated with FA. For instance, rethinking isolated FA values as a target of inquiry when evidence suggests that in some contexts it is common to find different forms of asymmetry together (e.g., human face: Farrera et al., 2015; Quinto-Sánchez et al., 2015). Formal models of descriptive explanations that instead address the dynamics that could give rise to patterns of asymmetric mixtures (e.g., Graham et al., 1993; Hallgrímsson, 1998) could shed new light on the topic or clarify existent evidence.