Relationships between 2D:4D, body and canine size and body and canine dimorphism were not significant after controlling for phylogenetic relatedness but exhibited trends in the predicted direction; lower ratios were associated with higher levels of dimorphism.
Relationships were stronger for canine size dimorphism than body size dimorphism. Lower 2D:4D ratios were associated with bigger groups but not significantly so. There were no
associations with brain size measures. The results suggest that 2D:4D is a poor predictor of the effects on PAE on programming sexually selected anatomical characteristics. These findings are in stark contrast to strong relationships between 2D:4D and sexual selection indexed by social systems and competition levels in Chapter 3.
Weak relationships between digit ratio and body measures might be expected as 2D:4D is largely fixed in utero and target variables are commonly obtained on adult individuals. Body size changes radically through growth and growth trajectories are influenced by many postnatal factors (e.g., sociality, diet, latitude, climate). In Cercopithecus aethiops variation in body mass dimorphism across wild Kenyan populations was found to be associated with changes in female body mass responding to increased food availability, latitude and rainfall (Turner et al. 1997). These effects were only evident in females and no differences in males could be detected. In humans height varies between populations in accordance with sexual selection (see Kanazawa & Novak 2005 for a review; but see Gray & Wolfe 1980) but is also impacted by environmental factors (Gray & Wolfe 1980; Ruff 1994). For example, low protein availability within some societies has been shown to have a bigger impact on male height (stunts growth) then female height (Gray & Wolfe 1980). These environmental effects on sex-linked growth trajectories can alter sexually dimorphic height patterns across
populations. Relationships between 2D:4D and stature in humans are weak (Lippa 2003; Barut et al. 2008) or non-significant (Rahman et al. 2005; Hönekopp & Watson 2010) and body weight shows a similar relationships (Fink et al. 2003; Rahman et al. 2005; but see Danborno et al. 2008). Poor correlations between 2D:4D and body size in humans and other primates may reflect the impact of postnatal environmental variability growth trajectories (e.g., Turner et al. 1997; Diverse Populations Collaborative Group 2005).
If PAE does impact growth trajectories we might expect to see stronger relationships between 2D:4D and neonatal size and dimorphism, as extraneous postnatal influences (e.g., pubertal growth, postnatal environmental factors) can be discounted a potential confounds. Sexual dimorphism in neonatal body size is evident in most primates and these measures correlate with adult levels of body dimorphism across species (Smith & Leigh 1998). Variation in birth weight is largely governed by the intra-uterine environment (Penrose 1952) and prenatal androgens have been proposed as possible candidates for greater male size at birth in primates (Smith & Leigh 1998). In humans sex differences in body size and 2D:4D have been detected as early as 8-12 weeks (Bukowski et al. 2007; Malas et al. 2006; Galis et al. 2010). This corresponds to a sharp rise in foetal testosterone as the testes begin to function (McIntyre 2006). In a sample of Nigerian (human) newborns, lower 2D:4D
was associated with higher birth weight in females (Danborno et al. 2010). No associations with birth weight were found in a smaller sample from the UK (Ronalds et al. 2002), although decreasing size (crown-to-heel length) was associated with increased 2D:4D (PAE decreased) in males. Birth weight is an important indicator of subsequent health status in adult humans; lower birth weight and size dimensions are strongly associated with chronic disease in later life (Loos et al. 2001; 2002; Fowden & Forhead 2004). The health status of an individual has consequences for evolutionary fitness as healthy males are more able to compete for females and are more likely to be chosen as mates (Rhodes et al. 2003; Roberts & Little 2007). This is also likely to be the case for other primates. Across haplorhines 2D:4D and neonatal body size and size dimorphism did exhibited weak trend in the expected direction; low 2D:4D was associated with higher neonatal weight and size dimorphism. However these relationships were not significant which suggests that prenatal growth factors, other than PAE, have already influenced body size before birth (e.g., insulin-like growth factor; Bernstein et al. 1997; Loos et al. 2001; 2002). A recent study in humans reported no differences in birth weight in neonates subsequently diagnosed with genetic and medical abnormalities (e.g., congenital adrenal hyperplasia) linked to extreme levels (high and low) of prenatal androgens (Miles et al. 2010).
Although PAE may not significantly influence birth weight in humans (Miles et al. 2010; clinical sample) this may not be the case for species with higher levels of sexual selection. Evidence from 2D:4D alludes to the possibility that PAE may be implicated in programming growth trajectories in species with higher levels sexual selection because as 2D:4D decreases (PAE increases) body dimorphism increases. However, non significant results suggest that these relationships are weak and may not be straightforward (Berinstein et al. 2007; 2008). Adult size and dimorphism in primates can be the product of different growth processes, even between closely related species (Leigh 1992). For example, levels of body size dimorphism in bonobos and chimpanzees are similar (Lindenfors & Tullberg 1998), but developmental trajectories differ. In bonobos (Pan paniscus) males extend growth in relation to females. In chimpanzees, development is delayed in females, but is accelerated in males (Leigh 1992; Leigh & Shea 1995). These differences may arise in chimpanzees as a
consequence of feeding competition in females (delaying maturity) and male involvement in coalitions associated with territorial patrols (speeding maturity; Reno et al. 2003). 2D:4D also differs between these two species with bonobos having higher ratios (closer to human values), than chimpanzees (McIntyre et al. 2009; Fig. 4.1). Chimpanzees also exhibit an increase in sexual dimorphism in 2D:4D from around 7-8 years of age; female ratios increased with age while male ratios decreased. These changes coincide with the sharp increase in testosterone in male chimpanzees and the onset of puberty in both males and
females at around 8 years of age (Martin et al. 1977; Goodall 1986). This suggests that circulating sex hormones may influence digit morphology and in adult chimpanzees.
Bonobos, in contrast, showed stability in sex differences in 2D:4D across the same age range and in this respect they follow the human pattern (Manning 2002a; Manning et al. 2004a). Sex-linked age-related changes in adult 2D:4D in some species (e.g., chimpanzees), but not others (e.g., bonobos and humans) will weaken cross-species correlations with target variables (see below). This suggests that 2D:4D may be a better reflector of PAE in some species but not in others.
Results indicate stronger relationships between 2D:4D and canine dimorphism (but not canine size) than between 2D:4D and body size measures. They also suggest that PAE may be more influential in programming male and female differences in canine development in species with higher levels of sexual selection because lower 2D:4D (inferred higher PAE) is associated with higher male-male competition and promiscuous social systems (see Chapter 3). As the formation of the permanent dentition begins in utero (Harila-Kaera 2001) we might expect to see correlations between 2D:4D and canine measures. Relationships were in the predicted direction and approached significance after the removal of an outlier (M. leucophaeus); low 2D:4D (inferred higher PAE) was associated with higher measures of canine dimorphism (Fig. 4.6). However, genetic influences cannot be discounted. In a study of same-sex (SS) and opposite-sex (OS) twins, females with a male co-twin had significantly larger teeth than females with a SS twin (Dempsey et al. 1999). This effect was attributed hormonal transfer of androgens from the male to the female twin, and implies that PAE are implicated in early sexual dimorphism of the human dentition. However, canine size exhibited the least size change in the OS twin (Dempsey et al. 1999), which may be
indicative of the high genetic constraints on canine size (Harila-Kaera 2001; but see Kaushal 2007). Evidence from human studies may not be a good comparative model for other
haplorhines, especially those species with high levels of sexual selection. Schwartz and Dean (2001) demonstrated that although canine crown formation times between males and females did not differ in humans, they did significantly differed in promiscuous great apes.
Brain size in primates is positively related to higher levels of sexual selection and group size (Sawaguchi 1996; Dunbar 1998; Shultz & Dunbar 2007). As 2D:4D also co-varies with social system and competitive behaviour (Chapter 3) we might expect to find that species with lower 2D:4D (inferred higher PAE) that live in larger groups to have bigger brains. This was not found. Across the whole sample relationships between 2D:4D and ECV and brain size dimorphism (based on ECV measures) were not significant after body size was controlled for.
Prenatal androgens influence the internal architecture of the brain (McClusky & Naftolin 1981; Arnold & Gorski 1984) and, in humans PAE have been linked to social development (e.g., Baron-Cohen 2002; Knickmeyer et al. 2005) and are reflected in 2D:4D (e.g., Manning et al. 2001; 2010). These sex-effects may be linked to androgenic effects on neural pathways linked to social bonding and social reward (van Honk et al. 2011; van Wingen et al. 2010; Rilling et al. in press). In non-human primates, operational and ethical difficulties preclude investigations of size differences in brain structures between males and females (see Lindenfors 2005; Lindenfors et al. 2007), however there is good evidence to show that sexual selection exerts a strong selective force on neural tissue producing sex-linked differences in brain architecture (e.g., Jacobs 1996; Gur et al. 1999; Lindenfors et al. 2007; Yan et al. 2010). Furthermore, variation in 2D:4D in females has been shown to be
associated with masculinisation in sub-regions of hippocampus; low 2D:4D (inferred high PAE) was linked to male-typical smaller, left-side volumes in the posterior hippocampus (Kallai et al. 2005). However no differences were found in other asymmetric structures such as the amygdales and total hippocampal formation, which are known to be replete with estrogen and androgen receptors (Pomerantz et al. 1985; O’Keefe et al. 1993; Cooke et al. 2003). This evidence suggests that, while 2D:4D may not be informative about the
evolutionary development of total brain size or brain size dimorphism; it may be insightful about the impact of sex hormones on brain architecture, although these patterns are likely to be complex and difficult to investigate at the species-level.
Sampling bias appears to impact correlations with 2D:4D. In G. gorilla and M. leucophaeus males had higher mean 2D:4D ratios than females. This is contrary to the expected pattern. This pattern (higher ratios in males then females) was also evident in several other species in the dataset (signalled by positive Cohen’s d values; Table 4.1) and has also been reported in a small group of captive guinea baboons (Papio papio; Roney et al. 2004). In humans there is considerable overlap in 2D:4D values between the sexes, but on average male digit ratio is lower than female digit ratio within populations (Manning 2002a; Mills 2002). How can 2D:4D ratios be higher in males than females when males are exposed to higher PAE? Circulating androgens (e.g., testosterone) vary within and between primate species (Coe et al. 1992) and are highly responsive to environmental factors (social and biological; e.g., Whitten & Turner 2004; Schulz et al. 2009). Although PAE are likely to vary less than circulating testosterone in adults due to maternal buffering of the intra-uterine environment, it is likely that taxonomic differences in prenatal sex hormones will still be evident. Intra- specific levels of PAE are additionally influenced at a local level by maternal effects which contribute to foetal programming (Mousseau & Fox 1998; Kaiser & Sachser 2009).
Foetal programming is a physiological process that prepares the foetus for extra-uterine life. Cellular-level changes occur as a response to subtle variations in placental function which alters in accordance to external stimuli such as dietary insufficiency, disease and stress (Phillips 2002; Fowden & Forhead 2009; Matthews and Philips 2010). Females are highly responsive to changes in nutrient availability and ecological variables such as climate, latitude and rainfall (Turner et al. 1997) and these factors are also likely to impact pregnant females. Changes in nutrition and health are known to influence placental function and this gives rise to foetal programming (see Phillips 2002; Fowden & Forhead 2004; 2009; Fowden et al. 2008). If local environmental effects induce changes in PAE via maternal effects on foetal programming then 2D:4D may differ between populations. Thus sampling of males and females from different populations could skew sex-differences in 2D:4D.
The social status of an individual may also impact PAE via maternal effects. For example in humans, males and females with lower 2D:4D (inferred higher PAE) consider themselves as more dominant and exhibit more aggression than males and females with higher 2D:4D (Benderlioglu & Nelson 2004; Bailey & Hurd 2004; Manning & Fink 2008). PAE has been inferred to be higher in foetuses of more socially dominant female hyenas based on
measurements of maternal faecal testosterone (Dloniak et al. 2006; but see East et al. 2009). Faecal testosterone levels positively correlate with maternal rank and with levels of
aggression in the hyena pups (Dloniak et al. 2006). If dominance is linked to variation in PAE within populations then a skewed pattern of sexual dimorphism in 2D:4D may arise if a dataset samples 2D:4D from many submissive males (high 2D:4D) and many dominant females (low 2D:4D). Ecological and dominance effects may not be mutually exclusive as more dominant individuals have priority access to food and are therefore likely to grow faster and be heavier than lower status individuals (Zehr et al. 2005).
Weaknesses in correlations with 2D:4D may also arise as a consequence of correlations between data derived from captive and from wild animals. 2D:4D data were predominantly taken from captive primates, while measurements of anatomical characteristics were mostly taken from wild-caught individuals (published sources; Lindenfors & Tullberg 1998; Smith & Jungers 1997; Thoren et al. 2006; Isler et al. 2008). Comparatively high nutritional intake and low energy expenditure of captive animals compared to wild animals may lead to differences in growth and development (see Smith & Jungers 1997, p 526), although Isler et al. (2008) found no significant differences in ECV between individuals that were captive bred and wild caught in their sample and I could not detect significant differences in 2D:4D ratios of captive female rhesus macaques (Macaca mulatta) and free-living population. It is
possible, however, that rearing conditions impact 2D:4D in some captive-born species and this serves to weaken relationships with measures of anatomical characters measured in wild-born individual.
4.4.1: Summary
Sexual selection has, without doubt, had a significant influence on the evolution of sexually selected body size in haplorhines (Plavcan 2001; Shultz & Dunbar 2007). Sexual dimorphism in body size is impacted by a myriad of intrinsic and extrinsic factors that serve to increase variation in this characters (e.g., Turner et al. 1997; Harila-Kaera 2001; Leigh et al. 2008). A key finding from reviewing ontogenetic studies is that although body, brain and canine size may correlate (to a greater or lesser degree) across primate species, the development of these structures can be de-coupled from each other (Clegg & Aiello 1999; Schwartz & Dean 2001; Herculano-Houzel 2009). It appears that body size is much freer to vary with postnatal factors than brain or canine size (Smith 1989; Martin et al. 1994; Schwartz & Dean 2001; Herculano-Houzel 2009) and, as such, body size and body dimorphism is a much weaker proxy of sexual selection (Plavcan 2001).
In conclusion, the predictions of this study were not met. That fact that relationships between 2D:4D and target variables were mostly in the expected direction, even though statistic parameters were achieved, suggests that some of these characters are probably programmed by PAE within the same critical prenatal phases. However, these effects are obscured over growth due to radical changes in allometry of anatomical characters. These findings are in line with weak or non significant relationships between 2D:4D and anatomical variables in humans. In the light of these results, and those of the Chapter 3, it can be concluded that 2D:4D is not a good predictor of PAE on sexually selected anatomical traits but may be more informative about PAE on the brain, specifically in programming core species-level differences in neural structures linked to potentiating social behaviour.
Chapter 5
2D:4D, female dominance rank and
heritability in rhesus macaques
12
5.1: Introduction
Cross-species studies in haplorhines have show that 2D:4D co-varies with social system and intra-sexual competition (Chapter 3), but not anatomical traits linked to sexual selection (Chapter 4). This chapter investigates relationships between 2D:4D and social behaviour by looking to see if relationships exist at the intra-specific level in a haplorhine primate species. Specifically, a case study is presented investigating relationships between 2D:4D and social dominance rank in female rhesus macaques (Macaca mulatta). It also calculates heritability levels of 2D:4D by analysing variation in mother macaques and their infant offspring.
5.1.1: 2D:4D: An anatomical marker for prenatal androgens effects
In humans 2D:4D is sexually dimorphic from nine weeks of prenatal life (Malas et al. 2006; also see Galis et al. 2010). Lower 2D:4D ratios are inferred to be associated with higher PAE and 2D:4D tends to be lower in males than females within a population (Manning 2002a; McIntyre et al. 2005). 2D:4D has been shown to correlate negatively with direct and indirect measures of prenatal androgens (Manning et al. 2007a). The mechanisms underlying these relationships are not clear, but are believed to be linked to common developmental pathways between the fingers and reproductive system. The distal limb buds (digits) and the genital bud are controlled by the same groups of phylogenetically conserved HOX genes (Zákány et al. 1997; Kondo et al. 1997; Montavon et al. 2008) and HOX gene transcription appears to be sensitive to sex hormones (Soto & Sonneschein 1999; Daftery & Taylor 2006). As HOX genes are strongly phylogenetically conserved within and between taxonomic groups (Zákány et al. 1997), it has been proposed that genetic association between 2D:4D and PAE should be common across four-limbed vertebrates (Manning 2002a, p 17).
12 Citations for this chapter: Nelson, E., Hoffman, C.L., Gerald, M.S. & Shultz, S. 2010. Finger length
ratios (2D:4D) and dominance rank in female rhesus macaques from Cayo Santiago. Behavioral Ecology and Sociobiology, 64:1001-1009.
Nelson, E. & Voracek, M. 2010. Heritability of digit ratio (2D:4D) in rhesus macaques (Macaca
Studies of heritability of digit ratios support this contention. Twin studies of 2D:4D have found high narrow-sense (genetic effects on phenotypic variance) heritability for 2D:4D (h² =50-80%) and shared environmental influences (non-genetic effects) on 2D:4D to be small (Paul et al. 2006b; Voracek & and Dressler 2007c; Gobrogge et al. 2008; Medland & Loehlin 2008). Similar results have been found for familial relationships in humans, such as mother-offspring and sibling-sibling comparisons, which yield heritability values of between 41% and 69% (Ramesh & Murty 1977; Marshall 2000; Manning 2002a; Voracek & Dressler 2009). High heritability levels have also been calculated for zebra finches (h² =70-80%; Forstmeier 2005; Forstmeier et al. 2008). The moderate to high heritability levels quoted in these studies suggest that non-shared environmental influences on 2D:4D (such as maternal effects and epigenetic factors) are low to moderate (see Gobrogge et al. 2008). Additionally, there is some evidence to suggest that birth order and sex of older siblings may influence PAE/2D:4D relationships (Williams et al. 2000; Saino et al. 2006), possibly via interactions between maternal physiology and parity, and this might impact on familial resemblance (Williams et al. 2000; James 2001; Saino et al. 2006; also see Fowden & Forhead 2009, p 617). Comparisons of 2D:4D between siblings and parent-offspring dyads in both humans and non-human animals (zebra finches) also show similarities and suggest that heritability of 2D:4D may also generalise across taxa (see Voracek & Dressler 2009). Genetic estimates combined with indirect links between digit ratios and PAE (outlined above), have led to