Dating back at least as far as Charles Darwin, scientists have discussed the “greater male variability” (GMV) seen in many species, with males tending to show more variability than females on a range of behavioral and morphological measures [1,2,3,4,5]. Most of the research on GMV has focused on humans and specifically on human brains and cognitive abilities. However, research on other species and other phenotypic properties indicates that GMV is not limited to humans [6, 7] or brains [4]. In addition, GMV has been identified across the lifespan beginning at birth, suggesting that genetic and possibly in utero developmental factors may interact to play an important role in these sex-linked differences. Measures showing evidence of GMV across the lifespan include body weight (at birth and in adults), blood parameters, and a range of measures of brain structure [4, 8, 9]. An improved understanding of the factors underlying the GMV seen in many human characteristics should benefit our understanding of sex differences in vulnerability to disease and in a range of additional phenotypic traits and anatomic characteristics.

Evolutionary mechanisms associated with natural and sexual selection have been posited as contributing to or accounting for GMV [1, 6, 10,11,12]. However, a mechanism that predates extant mammalian species by more than 100 million years may make an important contribution to GMV in phenotypic traits of placental mammals. That mechanism is the different patterns of X-chromosome activation across cells of females vs. males [7, 13, 14].

In placental mammals, the sex chromosomes are heterogametic (XY) for males and homogametic (XX) for females. The Y chromosome contains a very limited number of genes including the SRY gene that provides instructions for the development of male gonads. The X chromosome, on the other hand, contains over 1000 genes influencing many phenotypic properties [15]. For males, the single X chromosome is activated in every cell throughout the body. For females, very early in prenatal development, each cell of the embryo inactivates one of its two X chromosomes, at random, and all subsequent daughter cells follow the “decision” made by their progenitor cell. The purpose of this inactivation is “dosage compensation” [16]. Because males have only one X chromosome, every gene on that chromosome must be fully capable of producing the effects it is designed for, and if both X chromosomes were functional in females, they would receive a “double dose”, which could be problematic if not lethal. Accordingly, females inactivate one of the X chromosomes in every cell of their bodies. One result of the early, random inactivation of one or the other X chromosome is that females exhibit mosaic patterns of X-gene expression across their bodies but males do not (see Fig. 1). This male–female difference is an attractive candidate as possibly contributing to GMV given that, like GMV, it is present across eutherian species, across anatomical regions, and is present early in development (in utero).

Schematic representation of X-chromosome activation in males vs. females. In placental mammals, females show a mosaic pattern of activation with one of the two X chromosomes activated in each cell. Males show consistent activation of the single (maternally contributed) X chromosome across all cells

For a range of X-linked syndromes and diseases, GMV is the result of more males being in the negative tails of distributions. Specifically, males are affected more severely than females in more than 500 X-linked diseases [17]. A considerable amount of research has focused on this tail of various distributions when discussing GMV [17,18,19]. If GMV influenced only the negative tail of a given distribution, the mean of the male distribution always should be shifted lower than for females. However, in many instances, GMV on a given trait is present without clear differences in the means. In still other cases, GMV is paired with higher mean values for males than females. Overall there does not appear to be any consistent association between sex-related differences in variability and in mean scores [19, 20]. For many traits and morphological measures, GMV is characterized by more males being present in both the positive and negative tails of distributions that are flatter than those for females [6, 21].

One way of accounting for more males in both the positive and negative tails of the distribution for a given trait is to posit separate mechanisms for the two tails. For example, increased vulnerability to X-linked diseases in males, based on an adverse mutation on their single X chromosome, will place more males in the negative tails for these diseases, while sexual selection by females of males with extreme variants of various traits may place more males in the positive tails of these distributions [11, 22, 23]. However, a single mechanism, the mosaic pattern of X-inactivation of two X chromosomes in females and the activation of a single X chromosome in males, may lead to more values in both tails of male distributions. Figure 2 illustrates one way this could occur. A starting assumption in this account is that the quantity or quality of some trait is coded by genes on X chromosomes of the parents of a son or daughter. The left hand panels of the figure represent the quantity or quality of this trait based on the contribution of the X chromosome from each parent. The upper panels represent Group 1 where the X chromosome contributed by the father (Xpaternal = Xp) encodes a higher quantity or quality for the trait than the X chromosome from the mother (Xmaternal = Xm). For daughters, the resulting quantity or quality on the trait is based on an averaging of these two distributions—represented by the curve for females in the upper middle panel of the figure. The curve for males in this panel is based only on the contribution from Xm and is lower than the curve for females. The lower panels represent Group 2 where the situation is reversed and Xm encodes a higher quantity or quality on the trait than Xp. For females, quantity or quality on the trait is again based on an averaging of the two curves so the curve for females in the lower middle panel matches the same curve in the panel above it. However, for Group 2, males are at an advantage relative to the females since their curve is entirely based on Xm which contains alleles that encode a higher quantity of or quality on the trait than Xp. The right-hand panel of the figure combines the distributions for Group 1 and Group 2. In these combined distributions, the distribution for males is flatter with more values in each tail.

Combined influence of two X chromosomes can reduce phenotypic variability in females relative to males. For X-linked traits, the combined influence of two X chromosomes in females vs. the influence of a single X chromosome in males can produce GMV in trait quantity or quality (see text)

It should be noted that the averaging of the Xm and Xp distributions to produce the distributions for females in the center panels of Fig. 2 weighted the Xm and Xp distributions equally. This is appropriate when random selection of Xm or Xp for inactivation produces approximately equal contributions from Xm and Xp across cells. This may occur in about 50% of the female population [24]. Imbalanced (skewed) patterns of activation, resulting in greater contributions from either Xm or Xp, are also common in many females. However, this imbalance rarely approaches 100%, unlike males where it is always 100%. A study examining X-inactivation patterns in blood samples from 1005 females reported that only 8% showed imbalances of 80% or more [25]. Based on the current account, the subset of females showing strong imbalance in the expression of Xm vs. Xp would be expected to show greater variability, more similar to variability in males, than females as a whole.Footnote 1

For listeners with hearing thresholds within the normal range, females often show a small advantage in absolute hearing sensitivity, detecting slightly lower-amplitude tones at threshold [26,27,28]. If these differences reflect a benefit from a mosaic pattern of activation of two X chromosomes for tone detection, and if the absence of mosaic activation in males is linked to GMV, then tone detection thresholds should show greater variability in males than females, even among listeners with normal hearing. We report hearing data below that examine this hypothesis.

Visual comparison of the mosaic vs. uniform X-activation patterns for females vs. males in Fig. 1 might lead to an expectation of greater female than male variability due to the greater variability in the X-activation pattern within females than within males. Note, however, that this greater female variability is within an individual female relative to an individual male, rather than variability between males relative to variability between females. The variable (mosaic) pattern of X-activation within a given female vs. the uniform pattern in a given male leads to the prediction that correlations among different, related measures should be higher for males than females. These higher correlations in males re: females have been reported for various anatomical measures across brain regions and have been linked to influences of mosaic X-activation in females on these correlations [6, 8, 9, 21]. Greater correlations across related measures in males than in females (greater male correlations—GMCs) and GMV across subjects each may suggest an X-linked influence on a given behavioral or morphological characteristic.

Auditory hair cells in the cochlea transduce displacements of cochlear fluid into electrochemical neural signals that are then propagated to higher auditory centers in the brain. Wu et al. [29] reported that in female mice, these auditory hair cells show a mosaic pattern characterized by “fine-grained intermingling” of hair cells with either the maternally or paternally contributed X chromosome activated. These findings make auditory processing a good place to look for the proposed links between X-inactivation, GMV, and GMCs. We examined variability in hearing thresholds in data from two large data sets containing data from more than 8500 normally hearing male and female listeners (Grant et al. (2021) and NHANES datasets [30, 31]). Variability in performance across males vs. across females was compared in each measure with the expectation of GMV (prediction 1). In addition, correlations between related measures (e.g., hearing thresholds at 500 and 1000 Hz) were examined within males vs. within females with the expectation that males would show higher correlations if differences in X-chromosome-activation patterns between males and females influence performance (GMCs—prediction 2). Finally, mean hearing thresholds were compared for males vs. females to determine if the better hearing sensitivity reported for females in previous studies was replicated in the current data.