Abstract
Prenatal androgenization associates sex-dependently with behavior and mental health in adolescence and adulthood, including risk-taking, emotionality, substance use, and depression. However, still little is known on how it affects underlying neural correlates, like frontal brain control regions. Thus, we tested whether prenatal androgen load is sex-dependently related to frontal cortex volumes in a sex-balanced adolescent sample. In a cross-sectional magnetic resonance imaging study, we examined 61 adolescents (28 males, 33 females; aged 14 or 16 years) and analyzed associations of frontal brain region volumes with the second-to-fourth digit length ratio (2D:4D), an established marker for prenatal androgenization, using voxel-based morphometry in a region-of-interest approach. Lower 2D:4D (indicative of higher prenatal androgen load) correlated significantly with smaller volumes of the right anterior cingulate cortex (r-ACC; β = 0.45) in male adolescents and with larger volumes of the left inferior frontal gyrus orbital part (l-IFGorb; β = – 0.38) in female adolescents. The regression slopes of 2D:4D on the r-ACC also differed significantly between males and females. The study provides novel evidence that prenatal androgenization may influence the development of the frontal brain in a sex- and frontal brain region-specific manner. These effects might contribute to the well-known sex differences in risk-taking, emotionality, substance use, and depression. Future research is needed to elucidate the role of prenatal androgenization within the biopsychosocial model.
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Introduction
The prenatal window is a sensitive developmental period, during which the exposure to sex hormones organizes the brain with lasting neurobiological and behavioral effects. Animal experiments have established causal evidence that prenatal exposure to sex hormones influences sex-typical behavior, brain structures, and gene expression with effects that persist into adulthood [1,2,3]. In humans, androgenization during the prenatal development is thought to sex-specifically shape adult behaviors such as risk-taking, aggression [4,5,6], sociability [7], reduced impulse control [8], and emotional instability [9]. It was also suggested to influence regional brain morphology [10], enhanced reactivity to positive relative to negatively valenced facial cues [11] in young males, and P2a response to motivational stimuli in a predominantly female cohort [12]. Moreover, prenatal exposure to androgens further interacts sex-specifically with the risk for and symptoms of mental illnesses in adolescence and adulthood [13], including addictive disorders [14,15,16], suicidal behaviors [17], depression [18, 19], and eating disorders [20,21,22]. On the brain level, this could be particularly related to the structure and function of the prefrontal cortex, which plays a central role in cognitive control, modulates these behaviors, and associates with mental illness symptoms [23,24,25,26,27,28]. These relationships are also subject to sex differences [29].
However, there is only little knowledge on how prenatal androgen load shapes human frontal brain structure during developmental sensitive periods like adolescence [30]. Here, frontal brain regions are important for top-down cognitive control, and the temporal dissociation of the development of frontal and subcortical brain regions [31] promotes higher risk-taking behavior and stronger sensation seeking. These behaviors increase the risk for substance abuse [32], attention-deficit/hyperactivity disorder [33], suicidal behaviors [17], and depressive disorders [34]. Moreover, the incidence rates of these disorders typically peak during adolescence [35].
To investigate the effects of prenatal androgen exposure on behavioral phenotypes and brain structure, research has widely used the second-to-fourth digit length ratio (2D:4D) as an easily accessible proxy for prenatal androgen exposure [36]. Lower 2D:4D indicates higher prenatal androgenization. Males have lower 2D:4D than females [37], the fetal amniotic testosterone / estradiol ratio correlates negatively with the children’s 2D:4D at the age of two years [38], and higher maternal plasma testosterone collected at amniocentesis associates with lower 2D:4D in the newborn infants [39]. Moreover, it is assumed that 2D:4D is established during the first trimester and changes only little afterwards [40, 41] (but see also [42,43,44,45]). 2D:4D does not significantly correlate with peripheral sex hormone levels in adulthood and should thus be independent from direct androgen effects [46]. Some evidence suggests that right-hand 2D:4D (R2D:4D) might be a better marker for prenatal androgenization than left-hand 2D:4D (L2D:4D) [37] and that R2D:4D and L2D:4D are oppositely associated with handedness [47]. The validity of 2D:4D as a marker of prenatal androgen effects is further underlined by experimental rodent studies [48, 49] (but see also [50]) and human data based on conditions with altered prenatal androgen exposure such as congenital adrenal hyperplasia [51], Klinefelter’s syndrome [52, 53], androgen insensitivity syndrome [54], and the twin testosterone transfer [55]. The 2D:4D therefore is thought to give specific insight into the prenatal sex steroid milieu.
It is also important to note that research has established sex-specific associations of 2D:4D with risk for, symptoms of, and severity of mental disorders [13]. For example, a recent meta-analysis supports lower 2D:4D in substance-related and non-substance-related addictions with stronger effects in males than in females [14]. Supporting translational evidence established that in male mice the prenatal androgen receptor antagonism with flutamide decreases alcohol intake of the adult animals, whereas in female mice prenatal androgen treatment increases later alcohol intake. These prenatal androgen receptor modulations also cause differences in expression of genes relevant to addictive behaviors in the adult rodent brain [3]. Moreover, externalizing symptoms [56], aggression [6], and suicide [57] have been related to lower 2D:4D in males, but not in females, and higher 2D:4D has been associated with risk for and symptom severity of depression in females (but not in males) [18, 19] and bulimia nervosa in females [20, 21].
In summary, there is growing evidence for a sex-specific impact of prenatal androgenization (assessed via 2D:4D) on human behavior and mental health. Thus, 2D:4D should also sex-specifically associate with brain function and structure. Previously, Kallai et al. [58] found that lower (i.e., prenatally androgenized) 2D:4D is related to smaller posterior and larger middle hippocampus volumes of the left side. However, the sample consisted of healthy adult females and frontal regions were not the targeted brain areas. We lack knowledge on how prenatal androgenization associates with frontal brain volumes, which are related to behavioral control in male and female adolescents.
Study aims
In this cross-sectional study, we tested whether the mean of right-hand and left-hand 2D:4D (M2D:4D) relates to brain volumes of frontal cortex regions in males and females aged 14 or 16 years. Because of the previously demonstrated sex-dependent effects, we conducted sex-separated analyses in a first step. Then, we investigated whether R2D:4D is superior to L2D:4D in the statistical models and how 2D:4D and sex interact to influence the brain volumes. Problematic alcohol use is one of the main previously reported risk factors related to 2D:4D. Thus, we were also interested in whether the observed relations between 2D:4D and frontal brain volumes might be a consequence of alcohol consumption, and tested in sensitivity analyses whether alcohol use patterns affect the observed associations. Here, we did not expect and hence not analyze correlations between 2D:4D and alcohol use per se, as the participants in our sample were rather young and had low Alcohol Use Disorder Identification Test (AUDIT) scores.
Methods
Sample
The participants were part of the IMAC-Mind subproject 2 (for details see [59]) and recruited via advertising in regional schools and social networks as well as via the registration office of Mannheim, Germany. Inclusion criteria for participation were fluency in speaking German, no psychological or acute / chronic physical diseases, and no medication use. We excluded non-right-handed individuals because of evidence suggesting a relationship between handedness and 2D:4D [47, 60]. For alcohol use no in- / exclusion criteria were applied. Overall, 75 participants aged 14 or 16 years were enrolled. We grouped the participants into females and males according to their biological sex. There was no transgender person in our sample.
The cross-sectional study was approved by the ethical review committee II of the Medical Faculty Mannheim Heidelberg University. Participants were contacted by letter and informed about the study. After telephone screening for inclusion criteria, given detailed study information, and written informed consent of primary caregivers and adolescents, participants were invited to the Central Institute of Mental Health (CIMH) Mannheim, where MRI and 2D:4D measurements were done as part of a larger test battery. Additionally, questionnaires, including the AUDIT [61], were done at home via the online platform SoSci Survey [62]. The measurements and questionnaires for the present project took about 45 min.
Second-to-fourth digit length ratio (2D:4D)
We scanned the participants’ right and left hands using an Epson Perfection V370 Photo scanner in gray level with 300 DPI resolution. The participants were instructed to remove all jewelry from their hands, slightly spread the fingers, and have contact to the scanner with every finger segment. We used the GNU Image Manipulation Program (GIMP; www.gimp.org) to quantify the length of the second (2D) and fourths (4D) digits, i.e. distance from the middle of the basal crease to the tip of the fingers. Three independent raters (RBJ, BA, AS) measured each finger three times (nine times in total) and were uninformed about sex, age, and brain volumes. We defined M2D:4D as our primary predictor. R2D:4D and L2D:4D were also tested as further predictors. The inter-rater reliabilities (two-way random inter-rater correlation coefficient; absolute agreement) were very high: M2D:4D: n = 61, 0.969; R2D:4D: n = 61, 0.956; L2D:4D: n = 61, 0.963.
Structural MRI
MRI image acquisition and preprocessing
T1-weighted anatomical images were acquired on a 3-T Siemens PRISMA Scanner at the CIMH Mannheim using a 64 channel head coil and an MPRAGE (Magnetization-Prepared Rapid-Gradient Echo) Sequence with 208 slices, TR = 1800 ms, FOV = 250 mm, sagittal orientation, slice thickness = 0.85 mm, Flip angle = 8 degrees, GRAPPA acceleration factor = 3, matrix = 256 × 256 mm and 0.9 × 0.9 × 0.9 mm isometric voxels. Images were preprocessed using the Computational Anatomy Toolbox (CAT12; http://www.neuro.uni-jena.de/cat/) in the Statistical Parametric Mapping software (SPM12; https://www.fil.ion.ucl.ac.uk/spm/) on MATLAB (R2020a; www.mathworks.com). Preprocessing steps included tissue segmentation, spatial registration, bias-correction, and smoothing using a FWHM (Full Width at Half Maximum) 8 mm gaussian kernel. Modulated normalized images were used to extract grey matter volumes in the following ten regions of interest (ROI) in frontal and orbital control areas. These regions are involved in behavioral regulation and mental health, and they are particularly relevant during adolescence [30, 31, 63, 64]: Medial frontal cortex (MFC), medial (MOrG) and anterior (AOrG) orbital gyrus, orbital part of the inferior frontal gyrus (IFGorb), and anterior cingulate cortex (ACC). ROIs were obtained using the neuromorphometrics atlas in CAT12.
Statistical analyses
Voxel-based morphometry ROI analyses
Mean grey matter volumes in each of the ten ROIs for each participant were analyzed in R (https://www.r-project.org/) in the framework of multiple linear regression models for each ROI. Each model included the scaled values of M2D:4D as regressor of interest and age and total intercranial volume (TIV) as nuisance variables. Models were calculated separately for male and female adolescents, as M2D:4D differed significantly between the sexes and to provide evidence separately for males and females. To test how alcohol use affects the observed associations between 2D:4D and frontal brain volumes, we included AUDIT scores as a factor and computed the models again. As it is still debated whether R2D:4D or L2D:4D is superior, we defined M2D:4D as our primary predictor and offer Supplementary Materials showing model outcomes using R2D:4D and L2D:4D. One female participant had to be excluded from these additional analyses due to missing values and two more, because they presented as significant mean-shift outliers based on their studentized residuals in the linear model (Bonferroni-adjusted p < 0.05). We also performed additional post hoc linear regression models in ROIs including sex as a factor, where male and female adolescents showed contrasting directions of association to test whether there was a significant dissociation between males and females in these ROIs relative to their individual M2D:4D ratio. That is, we tested whether the regression slopes differed significantly between male and female adolescents in a given ROI. We corrected for multiple comparisons across the number of tested ROIs using the false discovery rate (FDR, [65]). Assumptions for all analyses were tested and met.
Results
Sample characteristics and validation hypotheses
Of 75 recruited participants (48.0% female, mean age 15.11 ± 1.00 years), 61 complete datasets (54.1% female, mean age 15.15 ± 1.00 years) were accessible for the present project. Male adolescents differed from female adolescents with significantly lower M2D:4D and R2D:4D, but not L2D:4D (Table 1). Unexpectedly, we also found lower M2D:4D, R2D:4D, and L2D:4D in the participants aged 16 years compared to those aged 14 years (M (SD) [16 years] vs. M (SD) [14 years], t (df), p; M2D:4D, 0.960 (0.020) vs. 0.977 (0.024), – 3.072 (59), 0.003; R2D:4D, 0.960 (0.024) vs. 0.974 (0.026), – 2.173 (59), 0.034; L2D:4D, 0.959 (0.023) vs. 0.980 (0.026), – 3.317 (59), 0.002). Moreover, female adolescents had generally lower volumes in all ROIs than male adolescents, all ts > 2.14, all ps < 0.04, with an exception in right IFGorb, where the sexes showed comparable grey matter volumes, meanmales = 1.55, meanfemales = 1.48, t(55) = 1.12, p = 0.27.
Sex-dependent association between 2D:4D and frontal brain volumes
Male adolescents
After correction for multiple hypothesis testing, higher M2D:4D was significantly associated with larger grey matter volumes in right ACC (r-ACC; Fig. 1A). The volumes in left and right mOrG were marginally related to M2D:4D. No further significant associations regarding the other ROIs emerged (Table 2; for covariate contribution to model fits see Supplementary Material 1). The association between M2D:4D and r-ACC volume remained significant after adjustment for AUDIT scores (F(4,23) = 3.19, R2adj = 0.25, p < 0.05, β = 0.44, p < 0.05; see Supplementary Table S1). In separate analyses of R2D:4D and L2D:4D, the observed associations were also present for R2D:4D, but not for L2D:4D (see Supplementary Tables S2 and S3).
The figures show associations between the mean of right-hand and left-hand second-to-fourth digit length ratio (M2D:4D) and grey matter volumes (GMV) of the right anterior cingulate cortex (r-ACC) in male adolescents (A) and the orbital part of the left inferior frontal gyrus (l-IFGorb) in female adolescents (B). *p < 0.05. 95% confidence intervals
Female adolescents
After correction for multiple hypothesis testing, higher M2D:4D was significantly related to smaller grey matter volumes in left IFGorb (l-IFGorb; Fig. 1B). No other ROIs were significantly related to M2D:4D (Table 3; for covariate contribution to model fits see Supplementary Material 2). The association between M2D:4D and l-IFGorb remained significant after adjustment for AUDIT scores (F(4,25) = 21.39, R2adj = 0.74, p < 0.001, β = −0.50, p < 0.01, see Supplementary Table S4) and was present for both R2D:4D and L2D:4D (see Supplementary Tables S5 and S6).
Sex-divergent association between 2D:4D and frontal brain volumes
We computed post hoc linear regression models to compare the association between M2D:4D and gray matter volumes in the relevant ROIs for male and female adolescents. There were significant differences between males and females in the relationship between M2D:4D and r-ACC (F(1,55) = 5.37, p < 0.05, males B = 16.46 vs. females B = – 4.14, estimate = 20.6, SE = 8.89, t(55) = 2.32, p < 0.05; Fig. 2). This effect persisted after adjustment for AUDIT scores (F(1,53) = 4.08, p < 0.05, estimate = 18.0, SE = 8.92, t(53) = 2.02, p < 0.05) and was present in a separate analysis for R2D:4D, but not for L2D:4D (R2D:4D: F(1,55) = 12.17, p < 0.001, estimate = 27.00, SE = 7.74, t(55) = 3.49, p < 0.001; L2D:4D: F(1,55) = 0.85, p = 0.36, estimate = 7.76, SE = 8.40, t(55) = 0.92, p = 0.36). The sex difference in the association between M2D:4D and IFGorb volumes between male adolescents, B = -2.51, and female adolescents, B = – 17.72, did not reach statistical significance (F(1,55) = 2.94, p = 0.09).
The figure shows sex-separated associations between the mean of right-hand and left-hand second-to-fourth digit length ratio (M2D:4D) and grey matter volumes (GMV) of the right anterior cingulate cortex (r-ACC) (F(1,55) = 5.37, p < 0.05, male adolescents B = 16.46 vs. female adolescents B = – 4.14, estimate = 20.6, SE = 8.89, t(55) = 2.32, p < 0.05). 95% confidence intervals
Discussion
The prenatal exposure to sex hormones influences the development of the brain with effects that last into adulthood. However, there is a lack of knowledge on how prenatal androgenization shapes brain volumes in developmental sensitive periods. Especially during adolescence, frontal brain regions are important within the context of risky behavior and mental illness. The field is also subject to important sex differences. Hence, we aimed to provide novel evidence for a sex-specific role of prenatal androgenization in frontal brain control regions in an adolescent sample.
In sex-separated analyses, we found that higher prenatal androgen load (indicated by lower 2D:4D) is related to smaller r-ACC in male adolescents and larger l-IFGorb in female adolescents. In post hoc analysis, the ACC associations remained significant for R2D:4D, but not for L2D:4D. This finding is consistent with previous results suggesting that 2D:4D on the right hand might be superior than 2D:4D on the left hand to indicate prenatal androgen exposure [37].
The functioning of the ACC is associated with impulse control, and behavioral inhibition has been associated with right-lateralized prefrontal networks [64]. Thus, the observed association between lower 2D:4D and smaller r-ACC in male adolescents per se and vs. female adolescents might indicate that prenatal hyperandrogenization reduces the capacity of behavioral control in males, but not in females. However, it is important to note that the investigated sample consisted of healthy adolescents without known deficits in behavioral control. We also did not directly assess behavioral control in this study, which should be a focus of future research. The ACC and related behavioral control are relevant for addictive behaviors, attention-deficit/hyperactivity disorder, and suicide. Adolescents with less top-down regulation capacity may be more vulnerable to develop substance use disorders [31]. In young alcohol-naive adolescents, those with a high risk for alcohol use disorder due to a positive family history show less inhibitory frontal activation than those with a negative family history [66]. Mashhoon et al. [67] found lower cortical thickness in the right middle ACC of alcohol binge drinkers vs. light drinkers. Moreover, the ACC is involved in processing of negative emotions [68], and coping with depressive symptoms is a frequent goal for alcohol use in individuals with alcohol use disorder [69]. Reduced volumes of the ACC are also involved in deficits of impulse control and cognition of patients with attention-deficit/hyperactivity disorder [70]. Furthermore, lower 2D:4D (with the here identified link to frontal brain volumes) has been related to addictions [14, 45, 71, 72], attention-deficit/hyperactivity disorder [13], overactive [8] and externalizing symptoms [56], aggression [4,5,6], and suicide [17, 57, 73] in males, but not in females. Altogether, these different pieces of evidence might indicate that in males prenatal androgenization organizes frontal brain control regions with lasting reduced behavioral control capacity. Consequently, this might increase the risk to develop mental illnesses, which are more prevalent in males than females particularly regarding addictive disorders (for a review highlighting the complexity of sex differences in substance use disorder see [74]) and attention-deficit/hyperactivity disorder. However, this model certainly needs validation in future studies. In particular, evidence on underlying causality from for example animal models and experimental modulations is needed. It will also be important to investigate whether the here observed associations between 2D:4D and frontal brain volumes are relevant to mental health in later life. Moreover, 2D:4D is related to sociability [7]. Hence, future studies should consider interactions with social and sociocultural aspects. It will be interesting to determine how prenatal androgenization interacts with other biopsychosocial factors (e.g., peer group pressure or self-efficacy expectancy) to associate with behavioral outcomes. In addition, future research should investigate mechanisms that transfer the prenatal influences into adolescence. Epigenetics might be of special interest, as its patterns have been associated with sex hormone activities [75, 76].
Previous research identified alcohol use and misuse as one of the main risk behaviors in relation to 2D:4D [14, 16] and even light-to-moderate alcohol consumption associates negatively with brain volume [77]. Thus, we analyzed whether AUDIT scores affect the here observed associations between 2D:4D and frontal brain structure. The findings remained significant after adjusting the statistical models for the AUDIT scores. Thus, it is unlikely that the observed smaller r-ACC volumes in male adolescents with higher prenatal androgenization is a consequence of alcohol use, but rather might represent a risk factor. The low AUDIT scores in our cohort of underage participants show that most participants did not use alcohol in a hazardous or harmful manner [78], which further supports this assumption.
This study also established in female adolescents an association between higher 2D:4D (indicative of lower prenatal androgenization) and smaller l-IFGorb volumes, a frontal brain region involved in emotion processing [79]. Smaller IFGorb volumes have been found in predominantly female samples of depression [80, 81] and bulimia nervosa [82], and higher 2D:4D has been associated with a higher risk and more severe symptoms of depression [18, 19] (but see also [83]) and bulimia [20, 21] in females. Together with the results observed here, this might indicate that lower prenatal androgen load entails lower l-IFGorb volumes in females with an increased risk for later depressive and eating disorders. However, this assumption needs again further validation in future studies.
The results may have important preventive implications. In combination with additional markers, 2D:4D might evolve as an illness predictor (e.g., the difference between alcohol-dependent patients and controls is of moderate effect size [14]) and thus help to identify individuals who are in particular need for targeted prevention programs. Moreover, human and animal research demonstrated that maternal smoking behavior, alcohol use, and higher stress during pregnancy are related to lower 2D:4D in the offspring [84,85,86]. Also, early life stress appears to affect neurochemistry within frontal brain areas in a sex-dependent manner [87]. A prospective, controlled, and investigator-blinded study is currently being conducted to test whether the reductions of cigarette smoking, consumption of alcohol, and stress in pregnant women influence 2D:4D in the offspring [88]. Based on the results of our work here, it will be interesting to test whether the aforementioned behavioral intervention during pregnancy is also able to modulate volumes of frontal brain control regions in adolescents with preventive effects. Again, it will be important to study how prenatal androgenization interacts with environmental factors to influence brain structure and function as well as behavior and mental illnesses.
The focus on adolescence as an important developmental period of the frontal brain control areas, the sex-balanced cohort, and the sex-separated analytical approach are important strengths of our study. Moreover, all included participants were right-handed, which is important as some data indicate associations between 2D:4D and hand preference [47, 60]. The limitations of this study include criticism regarding the validity and reliability of 2D:4D [89,90,91]. Most studies assume that 2D:4D is a marker for the prenatal androgen milieu [90]. However, there is evidence suggesting that estrogens are also involved in the development of 2D:4D. 2D:4D increased after prenatal estradiol treatment in male mice, and it decreased after prenatal estrogen receptor antagonism (fulvestrant) in female mice [49]. Here, we were able to replicate the expected sex differences [37] with lower 2D:4D in male than in female adolescents. Future research should also consider ethnicity/population [41, 92], sexual orientation [93], gender identity [94], and hand preference [47, 60] as potential confounders in 2D:4D research. As expected from the literature [37], we further observed stronger effects on the right hand than on the left hand. In line with previous work using the same method [94,95,96,97], the inter-rater agreement for 2D:4D can be interpreted as excellent with inter-rater correlation coefficients greater than 0.950. The here analyzed 2D:4D values are based on hand scans, a method which is more time consuming, but also more precise than using a caliper [98]. We found lower 2D:4D in participants aged 16 years than in those aged 14 years, which was rather unexpected. Previous work established increases in 2D:4D between 20 and 40 months of age (based on hand scans) [44] and from age 1 to age 17 (radiographically determined) [42]. However, serial 2D:4D analysis in the latter study found high reliability for 2D:4D as a trait marker [42]. In rodent experiments, the increase of prenatal testosterone entailed a delayed onset of puberty [99]. Thus, future studies should investigate whether pubertal status influences the observed lower 2D:4D in adolescents aged 16 years than in those aged 14 years. Moreover, we dichotomized the sample into females and males according to the biological sex. Future studies are requested to consider here neglected aspects of the gender concept such as self-defined gender identity and gender expression concerning for example appearance and behavior associated with social norms [100]. The most important limitation is that this study used a cross-sectional design, which does not allow for drawing causal conclusions. Our results suggest that AUDIT scores do not significantly influence the sex-specific associations between 2D:4D and frontal brain volumes. However, future studies should also investigate the effects of other drugs such as cannabis. It is very tempting to infer behavioral consequences from the observed associations between 2D:4D and brain structure. However, brain structure cannot simply be transferred into brain function. To better understand the direct effects of prenatal androgenization on ongoing brain development and behavioral consequences, a longitudinal design and animal experiments will be needed.
Conclusion
As far as we know, this is the first study to identify that smaller 2D:4D (indicative of higher prenatal androgen load) associates with lower r-ACC volumes in male adolescents and larger l-IFGorb volumes in female adolescents. The results may indicate that the prenatal androgen load affects the development of the frontal brain in a sex- and region-specific and also sex-diverging manner. These brain areas are known to influence behavioral control and they are involved in risk-taking, emotionality, substance use, and depression.
Data availability
The data that support the findings of this study are available from the authors on reasonable request.
References
Phoenix CH, Goy RW, Gerall AA, Young WC (1959) Organizing action of prenatally administered testosterone propionate on the tissues mediating mating behavior in the female guinea pig. Endocrinology 65:369–382. https://doi.org/10.1016/j.yhbeh.2009.01.004
Brown ECZ, Steadman CJ, Lee TM, Padmanabhan V, Lehman MN, Coolen LM (2015) Sex differences and effects of prenatal exposure to excess testosterone on ventral tegmental area dopamine neurons in adult sheep. Eur J Neurosci 41:1157–1166. https://doi.org/10.1111/ejn.12871
Huber SE, Zoicas I, Reichel M, Mühle C, Büttner C, Ekici AB, Eulenburg V, Lenz B, Kornhuber J, Müller CP (2018) Prenatal androgen receptor activation determines adult alcohol and water drinking in a sex-specific way. Addict Biol 23:904–920. https://doi.org/10.1111/adb.12540
Hönekopp J, Watson S (2011) Meta-analysis of the relationship between digit-ratio 2D:4D and aggression. Pers Individ Dif 51:381–386. https://doi.org/10.1016/j.paid.2010.05.003
Kuepper Y, Hennig J (2007) Behavioral aggression is associated with the 2D:4D ratio in men but not in women. J Individ Dif 28:64–72. https://doi.org/10.1027/1614-0001.28.2.64
Butovskaya M, Burkova V, Karelin D, Filatova V (2019) The association between 2D:4D ratio and aggression in children and adolescents: Cross-cultural and gender differences. Early Hum Dev 137:104823. https://doi.org/10.1016/j.earlhumdev.2019.07.006
Buchholz VN, Mühle C, Cohort Study on Substance Use Risk Factors, Kornhuber J, Lenz B (2019) Lower digit ratio (2D:4D) indicative of excess prenatal androgen is associated with increased sociability and greater social capital. Front Behav Neurosci 13:246. https://doi.org/10.3389/fnbeh.2019.00246
Körner LM, Pause BM, Meinlschmidt G, Tegethoff M, Fröhlich S, Kozlowski P, Rivet N, Jamey C, Reix N, Kintz P, Raul JS, Heil M (2019) Prenatal testosterone exposure is associated with delay of gratification and attention problems/overactive behavior in 3-year-old boys. Psychoneuroendocrinology 104:49–54. https://doi.org/10.1016/j.psyneuen.2019.02.014
Rodríguez-Ramos A, Moriana JA, García-Torres F, Ruiz-Rubio M (2021) Emotional stability is related to 2D:4D and social desirability in women: possible implications on subjective well-being and psychopathology. PLoS ONE 16:e0248368. https://doi.org/10.1371/journal.pone.0248368
Lombardo MV, Ashwin E, Auyeung B, Chakrabarti B, Taylor K, Hackett G, Bullmore ET, Baron-Cohen S (2012) Fetal testosterone influences sexually dimorphic gray matter in the human brain. J Neurosci 32:674–680. https://doi.org/10.1523/JNEUROSCI.4389-11.2012
Lombardo MV, Ashwin E, Auyeung B, Chakrabarti B, Lai MC, Taylor K, Hackett G, Bullmore ET, Baron-Cohen S (2012) Fetal programming effects of testosterone on the reward system and behavioral approach tendencies in humans. Biol Psychiatry 72:839–847. https://doi.org/10.1016/j.biopsych.2012.05.027
Webber TA, Soder HE, Potts GF, Bornovalova MA (2018) Preliminary evidence that digit length ratio (2D:4D) predicts neural response to delivery of motivational stimuli. Biol Psychol 132:91–95. https://doi.org/10.1016/j.biopsycho.2017.11.008
Fusar-Poli L, Rodolico A, Sturiale S, Carotenuto B, Natale A, Arillotta D, Siafis S, Signorelli MS, Aguglia E (2021) Second-to-fourth digit ratio (2D:4D) in psychiatric disorders: a systematic review of case-control studies. Clin Psychopharmacol Neurosci 19:26–45. https://doi.org/10.9758/cpn.2021.19.1.26
Siegmann EM, Bouna-Pyrrou P, Lenz B, Kornhuber J (2019) Digit ratio (2D:4D) in relation to substance and computer use: a meta-analysis. J Neural Transm (Vienna) 126:623–636. https://doi.org/10.1007/s00702-019-02002-2
Lenz B, Eichler A, Buchholz VN, Konsortium I-M, Fasching PA, Kornhuber J (2021) Prenatal androgen influence on addictive behaviour in adolescence. SUCHT 67:315–322. https://doi.org/10.1024/0939-5911/a000736
Lenz B, Müller CP, Stoessel C, Sperling W, Biermann T, Hillemacher T, Bleich S, Kornhuber J (2012) Sex hormone activity in alcohol addiction: integrating organizational and activational effects. Prog Neurobiol 96:136–163. https://doi.org/10.1016/j.pneurobio.2011.11.001
Lenz B, Röther M, Bouna-Pyrrou P, Mühle C, Tektas OY, Kornhuber J (2019) The androgen model of suicide completion. Prog Neurobiol 172:84–103. https://doi.org/10.1016/j.pneurobio.2018.06.003
Aliabadi S, Zendehboodi Z (2021) Association of digit ratio with depression and hopelessness in females. Int J Basic Sci Med 6:100–104. https://doi.org/10.34172/ijbsm.2021.18
Smedley KD, McKain KJ, McKain DN (2014) 2D:4D digit ratio predicts depression severity for females but not for males. Pers Individ Dif 70:136–139. https://doi.org/10.1016/j.paid.2014.06.039
Quinton SJ, Smith AR, Joiner T (2011) The 2 to 4 digit ratio (2D:4D) and eating disorder diagnosis in women. Pers Individ Dif 51:402–405. https://doi.org/10.1016/j.paid.2010.07.024
Oinonen KA, Bird JL (2012) Age at menarche and digit ratio (2D:4D): relationships with body dissatisfaction, drive for thinness, and bulimia symptoms in women. Body Image 9:302–306. https://doi.org/10.1016/j.bodyim.2011.12.003
Mikhail ME, Culbert KM, Sisk CL, Klump KL (2019) Gonadal hormone contributions to individual differences in eating disorder risk. Curr Opin Psychiatry 32:484–490. https://doi.org/10.1097/YCO.0000000000000543
Chini M, Hanganu-Opatz IL (2021) Prefrontal cortex development in health and disease: lessons from rodents and humans. Trends Neurosci 44:227–240. https://doi.org/10.1016/j.tins.2020.10.017
Luciana M, Collins PF (2022) Neuroplasticity, the prefrontal cortex, and psychopathology-related deviations in cognitive control. Annu Rev Clin Psychol 18:443–469. https://doi.org/10.1146/annurev-clinpsy-081219-111203
Firouzabadi FD, Ramezanpour S, Firouzabadi MD, Yousem IJ, Puts NAJ, Yousem DM (2022) Neuroimaging in attention-deficit/hyperactivity disorder: recent advances. AJR Am J Roentgenol 218:321–332. https://doi.org/10.2214/AJR.21.26316
Lengvenyte A, Conejero I, Courtet P, Olie E (2021) Biological bases of suicidal behaviours: A narrative review. Eur J Neurosci 53:330–351. https://doi.org/10.1111/ejn.14635
Hare BD, Duman RS (2020) Prefrontal cortex circuits in depression and anxiety: contribution of discrete neuronal populations and target regions. Mol Psychiatry 25:2742–2758. https://doi.org/10.1038/s41380-020-0685-9
Val-Laillet D, Aarts E, Weber B, Ferrari M, Quaresima V, Stoeckel LE, Alonso-Alonso M, Audette M, Malbert CH, Stice E (2015) Neuroimaging and neuromodulation approaches to study eating behavior and prevent and treat eating disorders and obesity. Neuroimage Clin 8:1–31. https://doi.org/10.1016/j.nicl.2015.03.016
Peper JS, Koolschijn PC, Crone EA (2013) Development of risk taking: contributions from adolescent testosterone and the orbito-frontal cortex. J Cogn Neurosci 25:2141–2150. https://doi.org/10.1162/jocn_a_00445
Giedd JN (2004) Structural magnetic resonance imaging of the adolescent brain. Ann N Y Acad Sci 1021:77–85. https://doi.org/10.1196/annals.1308.009
Casey BJ, Jones RM (2010) Neurobiology of the adolescent brain and behavior: implications for substance use disorders. J Am Acad Child Adolesc Psychiatry 49:1189–1201. https://doi.org/10.1016/j.jaac.2010.08.017
Nawi AM, Ismail R, Ibrahim F, Hassan MR, Manaf MRA, Amit N, Ibrahim N, Shafurdin NS (2021) Risk and protective factors of drug abuse among adolescents: a systematic review. BMC Public Health 21:2088. https://doi.org/10.1186/s12889-021-11906-2
Pollak Y, Dekkers TJ, Shoham R, Huizenga HM (2019) Risk-taking behavior in attention deficit/hyperactivity disorder (ADHD): a review of potential underlying mechanisms and of interventions. Curr Psychiatry Rep 21:33. https://doi.org/10.1007/s11920-019-1019-y
Fornaro M, Ventriglio A, De Pasquale C, Pistorio ML, De Berardis D, Cattaneo CI, Favaretto E, Martinotti G, Tomasetti C, Elassy M, D’Angelo E, Mungo S, Del Debbio A, Romano A, Ciampa G, Colicchio S (2013) Sensation seeking in major depressive patients: relationship to sub-threshold bipolarity and cyclothymic temperament. J Affect Disord 148:375–383. https://doi.org/10.1016/j.jad.2013.01.002
McGorry PD, Purcell R, Goldstone S, Amminger GP (2011) Age of onset and timing of treatment for mental and substance use disorders: implications for preventive intervention strategies and models of care. Curr Opin Psychiatry 24:301–306. https://doi.org/10.1097/YCO.0b013e3283477a09
Manning J, Kilduff L, Cook C, Crewther B, Fink B (2014) Digit ratio (2D:4D): a biomarker for prenatal sex steroids and adult sex steroids in challenge situations. Front Endocrinol (Lausanne) 5:9. https://doi.org/10.3389/fendo.2014.00009
Hönekopp J, Watson S (2010) Meta-analysis of digit ratio 2D:4D shows greater sex difference in the right hand. Am J Hum Biol 22:619–630. https://doi.org/10.1002/ajhb.21054
Lutchmaya S, Baron-Cohen S, Raggatt P, Knickmeyer R, Manning JT (2004) 2nd to 4th digit ratios, fetal testosterone and estradiol. Early Hum Dev 77:23–28. https://doi.org/10.1016/j.earlhumdev.2003.12.002
Ventura T, Gomes MC, Pita A, Neto MT, Taylor A (2013) Digit ratio (2D:4D) in newborns: influences of prenatal testosterone and maternal environment. Early Hum Dev 89:107–112. https://doi.org/10.1016/j.earlhumdev.2012.08.009
Malas MA, Dogan S, Evcil EH, Desdicioglu K (2006) Fetal development of the hand, digits and digit ratio (2D:4D). Early Hum Dev 82:469–475. https://doi.org/10.1016/j.earlhumdev.2005.12.002
Butovskaya M, Burkova V, Apalkova Y, Dronova D, Rostovtseva V, Karelin D, Mkrtchyan R, Negasheva M, Batsevich V (2021) Sex, population origin, age and average digit length as predictors of digit ratio in three large world populations. Sci Rep 11:8157. https://doi.org/10.1038/s41598-021-87394-6
McIntyre MH, Ellison PT, Lieberman DE, Demerath E, Towne B (2005) The development of sex differences in digital formula from infancy in the Fels Longitudinal Study. Proc Biol Sci 272:1473–1479. https://doi.org/10.1098/rspb.2005.3100
Galis F, Ten Broek CMA, Van Dongen S, Wijnaendts LCD (2010) Sexual dimorphism in the prenatal digit ratio (2D:4D). Arch Sex Behav 39:57–62. https://doi.org/10.1007/s10508-009-9485-7
Körner LM, Schaper ML, Pause BM, Heil M (2020) Parent-reports of sex-typed play preference in preschool children: relationships to 2D:4D digit ratio and older siblings’ sex. Arch Sex Behav 49:2715–2724. https://doi.org/10.1007/s10508-020-01662-6
Lenz B, Bouna-Pyrrou P, Mühle C, Kornhuber J (2018) Low digit ratio (2D:4D) and late pubertal onset indicate prenatal hyperandrogenziation in alcohol binge drinking. Prog Neuropsychopharmacol Biol Psychiatry 86:370–378. https://doi.org/10.1016/j.pnpbp.2018.02.012
Hönekopp J, Bartholdt L, Beier L, Liebert A (2007) Second to fourth digit length ratio (2D:4D) and adult sex hormone levels: new data and a meta-analytic review. Psychoneuroendocrinology 32:313–321. https://doi.org/10.1016/j.psyneuen.2007.01.007
Richards G, Medland SE, Beaton AA (2021) Digit ratio (2D:4D) and handedness: A meta-analysis of the available literature. Laterality 26:421–484. https://doi.org/10.1080/1357650X.2020.1862141
Talarovičová A, Kršková L, Blažeková J (2009) Testosterone enhancement during pregnancy influences the 2D:4D ratio and open field motor activity of rat siblings in adulthood. Horm Behav 55:235–239. https://doi.org/10.1016/j.yhbeh.2008.10.010
Zheng Z, Cohn MJ (2011) Developmental basis of sexually dimorphic digit ratios. Proc Natl Acad Sci U S A 108:16289–16294. https://doi.org/10.1073/pnas.1108312108
Huber SE, Lenz B, Kornhuber J, Müller CP (2017) Prenatal androgen-receptor activity has organizational morphological effects in mice. PLoS ONE 12:e0188752. https://doi.org/10.1371/journal.pone.0188752
Richards G, Browne WV, Aydin E, Constantinescu M, Nave G, Kim MS, Watson SJ (2020) Digit ratio (2D:4D) and congenital adrenal hyperplasia (CAH): Systematic literature review and meta-analysis. Horm Behav 126:104867. https://doi.org/10.1016/j.yhbeh.2020.104867
Chang S, Skakkebæk A, Trolle C, Bojesen A, Hertz JM, Cohen A, Hougaard DM, Wallentin M, Pedersen AD, Østergaard JR, Gravholt CH (2015) Anthropometry in Klinefelter syndrome–multifactorial influences due to CAG length, testosterone treatment and possibly intrauterine hypogonadism. J Clin Endocrinol Metab 100:E508-517. https://doi.org/10.1210/jc.2014-2834
Manning JT, Kilduff LP, Trivers R (2013) Digit ratio (2D:4D) in Klinefelter’s syndrome. Andrology 1:94–99. https://doi.org/10.1111/j.2047-2927.2012.00013.x
van Hemmen J, Cohen-Kettenis PT, Steensma TD, Veltman DJ, Bakker J (2017) Do sex differences in CEOAEs and 2D:4D ratios reflect androgen exposure? A study in women with complete androgen insensitivity syndrome. Biol Sex Differ 8:11. https://doi.org/10.1186/s13293-017-0132-z
van Anders SM, Vernon PA, Wilbur CJ (2006) Finger-length ratios show evidence of prenatal hormone-transfer between opposite-sex twins. Horm Behav 49:315–319. https://doi.org/10.1016/j.yhbeh.2005.08.003
Eichler A, Heinrich H, Moll GH, Beckmann MW, Goecke TW, Fasching PA, Muschler MR, Bouna-Pyrrou P, Lenz B, Kornhuber J (2018) Digit ratio (2D:4D) and behavioral symptoms in primary-school aged boys. Early Hum Dev 119:1–7. https://doi.org/10.1016/j.earlhumdev.2018.02.012
Lenz B, Thiem D, Bouna-Pyrrou P, Mühle C, Stoessel C, Betz P, Kornhuber J (2016) Low digit ratio (2D:4D) in male suicide victims. J Neural Transm (Vienna) 123:1499–1503. https://doi.org/10.1007/s00702-016-1608-4
Kallai J, Csatho A, Kover F, Makany T, Nemes J, Horvath K, Kovacs N, Manning JT, Nadel L, Nagy F (2005) MRI-assessed volume of left and right hippocampi in females correlates with the relative length of the second and fourth fingers (the 2D:4D ratio). Psychiatry Res 140:199–210. https://doi.org/10.1016/j.pscychresns.2004.05.010
Prignitz M, Guldner S, Nees F, Konsortium I-M (2021) Adolescence alcohol use behaviours during the COVID-19 pandemic and the role of mindfulness. SUCHT 67:287–297. https://doi.org/10.1024/0939-5911/a000734
Manning JT, Peters M (2009) Digit ratio (2D:4D) and hand preference for writing in the BBC Internet Study. Laterality 14:528–540. https://doi.org/10.1080/13576500802637872
Babor TF, Grant M (1989) From clinical research to secondary prevention: International collaboration in the development of the alcohol disorders identification test (AUDIT). Alcohol Health Res World 13:371–374
Leiner D (2019) SoSci Survey (Version 3.2.32) [Computer software]. https://www.soscisurvey.de.
Badre D, Nee DE (2018) Frontal cortex and the hierarchical control of behavior. Trends Cogn Sci 22:170–188. https://doi.org/10.1016/j.tics.2017.11.005
Sebastian A, Jung P, Krause-Utz A, Lieb K, Schmahl C, Tüscher O (2014) Frontal dysfunctions of impulse control - a systematic review in borderline personality disorder and attention-deficit/hyperactivity disorder. Front Hum Neurosci 8:698. https://doi.org/10.3389/fnhum.2014.00698
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc B 57:289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Schweinsburg AD, Paulus MP, Barlett VC, Killeen LA, Caldwell LC, Pulido C, Brown SA, Tapert SF (2004) An FMRI study of response inhibition in youths with a family history of alcoholism. Ann N Y Acad Sci 1021:391–394. https://doi.org/10.1196/annals.1308.050
Mashhoon Y, Czerkawski C, Crowley DJ, Cohen-Gilbert JE, Sneider JT, Silveri MM (2014) Binge alcohol consumption in emerging adults: anterior cingulate cortical “thinness” is associated with alcohol use patterns. Alcohol Clin Exp Res 38:1955–1964. https://doi.org/10.1111/acer.12475
Hiser J, Koenigs M (2018) The multifaceted role of the ventromedial prefrontal cortex in emotion, decision making, social cognition, and psychopathology. Biol Psychiatry 83:638–647. https://doi.org/10.1016/j.biopsych.2017.10.030
Müller CP, Mühle C, Kornhuber J, Lenz B (2021) Sex-dependent alcohol instrumentalization goals in non-addicted alcohol consumers versus patients with alcohol use disorder: longitudinal change and outcome prediction. Alcohol Clin Exp Res 45:577–586. https://doi.org/10.1111/acer.14550
Vogt BA (2019) Cingulate impairments in ADHD: Comorbidities, connections, and treatment. Handb Clin Neurol 166:297–314. https://doi.org/10.1016/B978-0-444-64196-0.00016-9
Lenz B, Mühle C, Cohort Study on Substance Use Risk Factors, Kornhuber J (2020) Lower digit ratio (2D:4D) in alcohol dependence: Confirmation and exploratory analysis in a population-based study of young men. Addict Biol 25:e12815. https://doi.org/10.1111/adb.12815
Buchholz VN, Mühle C, Cohort Study on Substance Use Risk Factors, Kornhuber J, Lenz B (2021) Markers of prenatal androgen exposure correlate with online sexual compulsivity and erectile function in young men. Front Psychiatry 12:517411. https://doi.org/10.3389/fpsyt.2021.517411
Lenz B, Kornhuber J (2018) Cross-national gender variations of digit ratio (2D:4D) correlate with life expectancy, suicide rate, and other causes of death. J Neural Transm (Vienna) 125:239–246. https://doi.org/10.1007/s00702-017-1815-7
Nicolas C, Zlebnik NE, Farokhnia M, Leggio L, Ikemoto S, Shaham Y (2022) Sex differences in opioid and psychostimulant craving and relapse: A critical review. Pharmacol Rev 74:119–140. https://doi.org/10.1124/pharmrev.121.000367
Muschler MAN, Lenz B, Hillemacher T, Kraus C, Kornhuber J, Frieling H, Bleich S (2014) CAGn repeat of the androgen receptor is linked to proopiomelanocortin promoter methylation-relevance for craving of male alcohol-dependent patients? Psychopharmacology 231:2059–2066. https://doi.org/10.1007/s00213-013-3349-5
Kovács T, Szabó-Meleg E, Ábrahám IM (2020) Estradiol-induced epigenetically mediated mechanisms and regulation of gene expression. Int J Mol Sci. https://doi.org/10.3390/ijms21093177
Daviet R, Aydogan G, Jagannathan K, Spilka N, Koellinger PD, Kranzler HR, Nave G, Wetherill RR (2022) Associations between alcohol consumption and gray and white matter volumes in the UK Biobank. Nat Commun 13:1175. https://doi.org/10.1038/s41467-022-28735-5
Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M (1993) Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption–II. Addiction 88:791–804. https://doi.org/10.1111/j.1360-0443.1993.tb02093.x
Levens SM, Phelps EA (2010) Insula and orbital frontal cortex activity underlying emotion interference resolution in working memory. J Cogn Neurosci 22:2790–2803. https://doi.org/10.1162/jocn.2010.21428
Wang J, Liu P, Zhang A, Yang C, Liu S, Wang J, Xu Y, Sun N (2020) Specific gray matter volume changes of the brain in unipolar and bipolar depression. Front Hum Neurosci 14:592419. https://doi.org/10.3389/fnhum.2020.592419
Kandilarova S, Stoyanov D, Sirakov N, Maes M, Specht K (2019) Reduced grey matter volume in frontal and temporal areas in depression: contributions from voxel-based morphometry study. Acta neuropsychiatrica 31:252–257. https://doi.org/10.1017/neu.2019.20
Cyr M, Kopala-Sibley DC, Lee S, Chen C, Stefan M, Fontaine M, Terranova K, Berner LA, Marsh R (2017) Reduced inferior and orbital frontal thickness in adolescent bulimia nervosa persists over two-year follow-up. J Am Acad Child Adolesc Psychiatry 56(866–874):e867. https://doi.org/10.1016/j.jaac.2017.08.008
Lautenbacher LM, Neyse L (2020) Depression, neuroticism and 2D:4D ratio: evidence from a large, representative sample. Sci Rep 10:11136. https://doi.org/10.1038/s41598-020-67882-x
Lilley T, Laaksonen T, Huitu O, Helle S (2010) Maternal corticosterone but not testosterone level is associated with the ratio of second-to-fourth digit length (2D:4D) in field vole offspring (Microtus agrestis). Physiol Behav 99:433–437. https://doi.org/10.1016/j.physbeh.2009.11.015
Rizwan S, Manning JT, Brabin BJ (2007) Maternal smoking during pregnancy and possible effects of in utero testosterone: evidence from the 2D:4D finger length ratio. Early Hum Dev 83:87–90. https://doi.org/10.1016/j.earlhumdev.2006.05.005
Lenz B, Mühle C, Braun B, Weinland C, Bouna-Pyrrou P, Behrens J, Kubis S, Mikolaiczik K, Muschler M-R, Saigali S, Sibach M, Tanovska P, Huber SE, Hoppe U, Eichler A, Heinrich H, Moll GH, Engel A, Goecke TW, Beckmann MW, Fasching PA, Müller CP, Kornhuber J (2017) Prenatal and adult androgen activities in alcohol dependence. Acta Psychiatr Scand 136:96–107. https://doi.org/10.1111/acps.12725
Perry CJ, Campbell EJ, Drummond KD, Lum JS, Kim JH (2021) Sex differences in the neurochemistry of frontal cortex: Impact of early life stress. J Neurochem 157:963–981. https://doi.org/10.1111/jnc.15208
Lenz B, Eichler A, Schwenke E, Buchholz VN, Hartwig C, Moll GH, Reich K, Mühle C, Volz B, Titzmann A, Beckmann MW, Heinrich H, Kornhuber J, Fasching PA (2018) Mindfulness-based stress reduction in pregnancy: an app-based programme to improve the health of mothers and children (MINDFUL/PMI study). Geburtshilfe Frauenheilkd 78:1283–1291. https://doi.org/10.1055/a-0677-2630
Del Giudice M, Barrett ES, Belsky J, Hartman S, Martel MM, Sangenstedt S, Kuzawa CW (2018) Individual differences in developmental plasticity: a role for early androgens? Psychoneuroendocrinology 90:165–173. https://doi.org/10.1016/j.psyneuen.2018.02.025
Berenbaum SA, Bryk KK, Nowak N, Quigley CA, Moffat S (2009) Fingers as a marker of prenatal androgen exposure. Endocrinology 150:5119–5124. https://doi.org/10.1210/en.2009-0774
Richards G, Gomes M, Ventura T (2019) Testosterone measured from amniotic fluid and maternal plasma shows no significant association with directional asymmetry in newborn digit ratio (2D:4D). J Dev Orig Health Dis 10:362–367
Manning JT, Churchill AJG, Peters M (2007) The effects of sex, ethnicity, and sexual orientation on self-measured digit ratio (2D:4D). Arch Sex Behav 36:223–233. https://doi.org/10.1007/s10508-007-9171-6
Grimbos T, Dawood K, Burriss RP, Zucker KJ, Puts DA (2010) Sexual orientation and the second to fourth finger length ratio: a meta-analysis in men and women. Behav Neurosci 124:278–287. https://doi.org/10.1037/a0018764
Siegmann EM, Müller T, Dziadeck I, Mühle C, Lenz B, Kornhuber J (2020) Digit ratio (2D:4D) and transgender identity: new original data and a meta-analysis. Sci Rep 10:19326. https://doi.org/10.1038/s41598-020-72486-6
Tektas OY, Kapsner L, Lemmer M, Bouna-Pyrrou P, Lewczuk P, Lenz B, Kornhuber J (2019) Digit ratio (2D:4D) and academic success as measured by achievement in the academic degree “Habilitation.” PLoS ONE 14:e0212167. https://doi.org/10.1371/journal.pone.0212167
Kornhuber J, Erhard G, Lenz B, Kraus T, Sperling W, Bayerlein K, Biermann T, Stoessel C (2011) Low digit ratio 2D:4D in alcohol dependent patients. PLoS ONE 6:e19332. https://doi.org/10.1371/journal.pone.0019332
Kornhuber J, Zenses EM, Lenz B, Stoessel C, Bouna-Pyrrou P, Rehbein F, Kliem S, Mößle T (2013) Low 2D:4D values are associated with video game addiction. PLoS ONE 8:e79539. https://doi.org/10.1371/journal.pone.0079539
Kemper CJ, Schwerdtfeger A (2009) Comparing indirect methods of digit ratio (2D:4D) measurement. Am J Hum Biol 21:188–191. https://doi.org/10.1002/ajhb.20843
Dela Cruz C, Pereira OCM (2012) Prenatal testosterone supplementation alters puberty onset, aggressive behavior, and partner preference in adult male rats. J Physiol Sci 62:123–131. https://doi.org/10.1007/s12576-011-0190-7
Lindqvist A, Gustafsson Sendén M, Renström EA (2021) What is gender, anyway: a review of the options for operationalising gender. Psychol Sex 12:332–344. https://doi.org/10.1080/19419899.2020.1729844
Heinz A, Kiefer F, Smolka MN, Endrass T, Beste C, Beck A, Liu S, Genauck A, Romund L, Banaschewski T, Bermpohl F, Deserno L, Dolan RJ, Durstewitz D, Ebner-Priemer U, Flor H, Hansson AC, Heim C, Hermann D, Kiebel S, Kirsch P, Kirschbaum C, Koppe G, Marxen M, Meyer-Lindenberg A, Nagel WE, Noori HR, Pilhatsch M, Priller J, Rietschel M, Romanczuk-Seiferth N, Schlagenhauf F, Sommer WH, Stallkamp J, Strohle A, Stock AK, Winterer G, Winter C, Walter H, Witt S, Vollstadt-Klein S, Rapp MA, Tost H, Spanagel R (2020) Addiction Research Consortium: Losing and regaining control over drug intake (ReCoDe)-From trajectories to mechanisms and interventions. Addict Biol 25:e12866. https://doi.org/10.1111/adb.12866
Acknowledgements
We thank Alexander Stellrecht, B.Sc., and Berkan Akin for technical assistance with 2D:4D and Michaela Ruttorf for support with MRI data preprocessing.
Funding
Open Access funding enabled and organized by Projekt DEAL. With the public-funded research project IMAC-Mind: Improving Mental Health and Reducing Addiction in Childhood and Adolescence through Mindfulness: Mechanisms, Prevention and Treatment (2017–2022 01GL1745B (subproject TP2)), the Federal Ministry of Education and Research contributes to improving the prevention and treatment of children and adolescents with substance use disorders and associated mental disorders. Project coordination was realized by the German Center of Addiction Research in Childhood and Adolescence at the University Medical Center Hamburg-Eppendorf. The consortium comprises seven projects in Germany. Principal Investigators are Rainer Thomasius (Coordinator, University Medical Center Hamburg-Eppendorf), Tobias Banaschewski, Herta Flor (Central Institute of Mental Health, Mannheim), Frauke Nees (Central Institute of Mental Health, Mannheim, and University Medical Center Schleswig Holstein, Kiel University), Johannes Kornhuber (Friedrich-Alexander-Universität Erlangen-Nürnberg), Michael Klein (Catholic University of Applied Sciences, Cologne), Olaf Reis (University Medicine of Rostock), Tanja Legenbauer (Ruhr-University Bochum), and Antonia Zapf (University Medical Center Hamburg-Eppendorf). Further members of the consortium are Nicolas Arnaud, Christiane Baldus, Anne Daubmann, Amra Hot, Sabrina Kunze, Kathrin Simon-Kutscher, Anna-Lena Schulz, Michael Supplieth (University Medical Center Hamburg-Eppendorf), Karina Abenova, Karl Gottfried, Stella Guldner, Sabina Millenet, Maren Prignitz (Central Institute of Mental Health, Mannheim), Bernd Lenz, Peter Fasching, Matthias Beckmann, Verena Nadine Buchholz, Eva-Maria Siegmann, Anna Eichler, Jenny Gerlach, Christiane Mühle, Adriana Titzmann (Friedrich-Alexander-Universität Erlangen-Nürnberg), Lina-Sophia Falkenberg, Daria Kunst (Catholic University of Applied Sciences, Cologne), Lucie Waedel, Katrin Bogumil (University Medicine of Rostock), Martin Holtmann, Regina Herdering, Carina Maria Huhn, Lea Kretschmar, and Laura Mokros (Ruhr-University Bochum). For more information, please visit our homepage www.IMAC-Mind.de. The project was also funded in part by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 402170461 – TRR265 [101]. The funders had no role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript.
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Conceived and designed the experiments: BL, SGe, SGu, MP, FN. Performed the experiments: MP, SGu. Data Preprocessing: RBJ (2D:4D), SGu (MRI). Analyzed the data: BL, SGu, MP. Wrote the paper: BL, SGe, SGu, MP, FN. Commented on the manuscript and provided intellectual input: RBJ, AE, VNB, PAF, JK, TB, HF.
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Lenz, B., Gerhardt, S., Boroumand-Jazi, R. et al. Sex-specific association between prenatal androgenization (second-to-fourth digit length ratio) and frontal brain volumes in adolescents. Eur Arch Psychiatry Clin Neurosci 273, 1243–1254 (2023). https://doi.org/10.1007/s00406-022-01515-4
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DOI: https://doi.org/10.1007/s00406-022-01515-4