Overall trends vs. individual trajectories in the second‐to‐fourth digit (2D:4D) and metacarpal (2M:4M) ratios during puberty and adolescence

Králík, Miroslav; Ingrová, Pavlína; Koziel, Sławomir; Hupková, Adela; Klíma, Ondřej

doi:10.1002/ajpa.23153

“…It is also unclear why the association between DRM and affected status did not emerge until young-adulthood, given that NDD-related outcomes emerge in early childhood. Longitudinal studies of typically developing children show that digit ratio tends to increase (i.e., becomes more feminine) across puberty [ 73 , 74 ], however the rank order of inter-individual differences remain stable. No study to date has examined the developmental trajectory of DRM in individuals with NDDs, or longitudinally compared groups of individuals with and without NDDs, so further research in this area may be useful.…”

Section: Discussionmentioning

confidence: 99%

Genetic and morphological estimates of androgen exposure predict social deficits in multiple neurodevelopmental disorder cohorts

McKenna

¹

,

Huang

²

,

Vervier

³

et al. 2021

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Background Neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) display a strong male bias. Androgen exposure is profoundly increased in typical male development, but it also varies within the sexes, and previous work has sought to connect morphological proxies of androgen exposure, including digit ratio and facial morphology, to neurodevelopmental outcomes. The results of these studies have been mixed, and the relationships between androgen exposure and behavior remain unclear. Methods Here, we measured both digit ratio masculinity (DRM) and facial landmark masculinity (FLM) in the same neurodevelopmental cohort (N = 763) and compared these proxies of androgen exposure to clinical and parent-reported features as well as polygenic risk scores. Results We found that FLM was significantly associated with NDD diagnosis (ASD, ADHD, ID; all $$p<0.05$$ p < 0.05 ), while DRM was not. When testing for association with parent-reported problems, we found that both FLM and DRM were positively associated with concerns about social behavior ($$\rho =0.19$$ ρ = 0.19 , $$p=0.004$$ p = 0.004 ; $$\rho =0.2$$ ρ = 0.2 , $$p=0.004$$ p = 0.004 , respectively). Furthermore, we found evidence via polygenic risk scores (PRS) that DRM indexes masculinity via testosterone levels ($$t=4.0$$ t = 4.0 , $$p=8.8\times 10^{-5}$$ p = 8.8 × 10 - 5 ), while FLM indexes masculinity through a negative relationship with sex hormone binding globulin (SHBG) levels ($$t=-3.3$$ t = - 3.3 , $$p=0.001$$ p = 0.001 ). Finally, using the SPARK cohort (N = 9419) we replicated the observed relationship between polygenic estimates of testosterone, SHBG, and social functioning ($$t=-2.3$$ t = - 2.3 , $$p=0.02$$ p = 0.02 , and $$t=4.2$$ t = 4.2 , $$p={3.2\times 10^{-5}}$$ p = 3.2 × 10 - 5 for testosterone and SHBG, respectively). Remarkably, when considered over the extremes of each variable, these quantitative sex effects on social functioning were comparable to the effect of binary sex itself (binary male: $$-0.22\pm 0.05$$ - 0.22 ± 0.05 ; testosterone: $$-0.35\pm 0.15$$ - 0.35 ± 0.15 from 0.1%-ile to 99.9%-ile; SHBG: $$0.64\pm 0.15$$ 0.64 ± 0.15 from 0.1%-ile to 99.9%-ile). Limitations In the devGenes and SPARK cohorts, our analyses rely on indirect, rather than direct measurement of androgens and related molecules. Conclusions These findings and their replication in the large SPARK cohort lend support to the hypothesis that increasing net androgen exposure diminishes capacity for social functioning in both males and females.

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“…This sex difference is established in utero, probably at the end of the first trimester (Galis, Ten Broek, Van Dongen, & Wijnaendts, 2010;Malas, Dogan, Evcil, & Desdicioglu, 2006), but the sex difference appears largely unaffected by puberty (Králík, Ingrová, Kozieł, Hupková, & Klíma, 2017;McIntyre, Ellison, Lieberman, Demerath, & Towne, 2005;Trivers, Manning, & Jacobson, 2006). 2D:4D shows longitudinal stability (Králík et al, 2017;McIntyre, Cohn, & Ellison, 2006;McIntyre, Ellison, Lieberman, Demerath, & Towne, 2005;Wong & Hines, 2016), but see Knickmeyer, Woolson, Hamer, Konneker, and Gilmore (2011) for an exception. Probably the best evidence that 2D:4D reflects prenatal T effects stems from individuals who were exposed to atypical T effects during early development: Females with high prenatal T levels due to CAH have strongly masculinized 2D:4D (Brown, Hines, Fane, & Breedlove, 2002;Hönekopp & Watson, 2010;Kocaman et al, 2017;Rivas et al, 2014); similarly, men affected by Klinefelter's syndrome, which causes low T levels throughout development, show strongly feminized 2D:4D (Manning, Kilduff, & Trivers, 2013); finally, genetic males affected by CAIS show moderately feminized 2D:4D (Berenbaum, Bryk, Nowak, Quigley, & Moffat, 2009;van Hemmen, Cohen-Kettenis, Steensma, Veltman, & Bakker, 2017).…”

Section: D:4d Digit Ratiomentioning

confidence: 97%

“…A suite of observations suggests that 2D:4D might be a useful measure of prenatal T effects: 2D:4D shows a moderate sex difference across numerous countries studied (Grimbos, Dawood, Burriss, Zucker, & Puts, 2010;Hönekopp & Watson, 2010). This sex difference is established in utero, probably at the end of the first trimester (Galis, Ten Broek, Van Dongen, & Wijnaendts, 2010;Malas, Dogan, Evcil, & Desdicioglu, 2006), but the sex difference appears largely unaffected by puberty (Králík, Ingrová, Kozieł, Hupková, & Klíma, 2017;McIntyre, Ellison, Lieberman, Demerath, & Towne, 2005;Trivers, Manning, & Jacobson, 2006). 2D:4D shows longitudinal stability (Králík et al, 2017;McIntyre, Cohn, & Ellison, 2006;McIntyre, Ellison, Lieberman, Demerath, & Towne, 2005;Wong & Hines, 2016), but see Knickmeyer, Woolson, Hamer, Konneker, and Gilmore (2011) for an exception.…”

Section: D:4d Digit Ratiomentioning

confidence: 99%

2D:4D Suggests a Role of Prenatal Testosterone in Gender Dysphoria

Sadr

¹

,

Khorashad

²

,

Talaeı

³

et al. 2020

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Gender dysphoria (GD) reflects distress caused by incongruence between one's experienced gender identity and one's natal (assigned) gender. Previous studies suggest that high levels of prenatal testosterone (T) in natal females and low levels in natal males might contribute to GD. Here, we investigated if the 2D:4D digit ratio, a biomarker of prenatal T effects, is related to GD. We first report results from a large Iranian sample, comparing 2D:4D in 104 transwomen and 89 transmen against controls of the same natal sex. We found significantly lower (less masculine) 2D:4D in transwomen compared to control men. We then conducted random-effects meta-analyses of relevant studies including our own (k = 6, N = 925 for transwomen and k = 6, N = 757 for transmen). In line with the hypothesized prenatal T effects, transwomen showed significantly feminized 2D:4D (d ≈ 0.24). Conversely, transmen showed masculinized 2D:4D (d ≈ − 0.28); however, large unaccounted heterogeneity across studies emerged, which makes this effect less meaningful. These findings support the idea that high levels of prenatal T in natal females and low levels in natal males play a part in the etiology of GD. As we discuss, this adds to the evidence demonstrating the convergent validity of 2D:4D as a marker of prenatal T effects.

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“…To what extent can finger ridge‐count variation be used as a marker of fetal origin of postnatal morphology or behavior? Postnatal changes in 2d:4d have been documented (McIntyre et al, 2005) leading to the suggestion there may be a postnatal hormone response (Králík et al, 2017). But because ridge‐counts experience no postnatal modification at all, or even prenatal modification beyond about 10 gestational weeks, the association with 2d:4d supports early prenatal hormone exposure as its principal determinant.…”

Section: Discussionmentioning

confidence: 99%

Finger ridge‐counts correlate with the second to fourth digit ratio (2d:4d)

Jantz

¹

2021

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Objectives This study examines the relationship of finger ridge‐counts to second to fourth digit ratio, which has not yet been definitively demonstrated. The related question of sex dimorphism in finger ridge‐counts is further elucidated. Methods A sample of Germans, including 1134 males and 1031 females, was examined for sex dimorphism in the finger ridge‐counts. Second and fourth digit lengths were measured in a sub‐sample of 91 males and 100 females to compute second to fourth digit ratio. Principal component scores were obtained to investigate sex dimorphism and the correlation between ridge‐counts and digit ratio. Regression and analysis of covariance were used to investigate relationships. Results Males generally have higher ridge‐counts than females but subtle dimorphic features emerge from the principal components, such as a contrast between digits 2 and 4, suggesting a ratio analogous to the digit ratio. The most dimorphic feature is digit 1 directional asymmetry, males exhibiting a stronger right bias than females. Digit ratio is significantly related to four principal components, expressing various contrasts among digits. Other relationships involve contrasts between digits 3 and 5 and asymmetry on digit 2. Conclusions This paper provides definitive evidence that finger ridge‐counts correlate with second to fourth digit ratio. The most important finding is that associations of ridge‐counts with digit ratio do not involve commonly used summary counts over all digits. Rather, associations act more locally, in ways paralleling the digit ratio, in others reflecting asymmetry. The results support the idea that prenatal sex hormones affect finger ridge‐counts.

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Overall trends vs. individual trajectories in the second‐to‐fourth digit (2D:4D) and metacarpal (2M:4M) ratios during puberty and adolescence

Cited by 17 publications

References 37 publications

Genetic and morphological estimates of androgen exposure predict social deficits in multiple neurodevelopmental disorder cohorts

Genetic and morphological estimates of androgen exposure predict social deficits in multiple neurodevelopmental disorder cohorts

2D:4D Suggests a Role of Prenatal Testosterone in Gender Dysphoria

Finger ridge‐counts correlate with the second to fourth digit ratio (2d:4d)

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