A review on the relationship between testosterone and life-course persistent antisocial behavior

Psychiatry Research 200 (2012) 984–1010

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Review article

A review on the relationship between testosterone and life-course persistent antisocial behavior Baris- O. Yildirim a,n, Jan J.L Derksen b,1 a b

Department of Clinical Psychology, De Kluyskamp 1002, 6545 JD Nijmegen, The Netherlands Department of Clinical Psychology, Room: A.07.04B, Radboud University Nijmegen, Montessorilaan 3, 6525 HR Nijmegen, The Netherlands

a r t i c l e i n f o

a b s t r a c t

Article history: Received 16 October 2011 Received in revised form 18 July 2012 Accepted 28 July 2012

Life-course persistent antisocial behavior is 10 to 14 times more prevalent in males and it has been suggested that testosterone levels could account for this gender bias. Preliminary studies with measures of fetal testosterone find inconsistent associations with antisocial behavior, especially studies that use the 2D:4D ratio as a proxy for fetal testosterone. However, circulating testosterone consistently shows positive associations with antisocial behaviors throughout childhood, adolescence, and adulthood, particularly in males. It is suggested that high fetal/circulating testosterone interactively influence the maturation and functionality of mesolimbic dopaminergic circuitry, right orbitofrontal cortex, and cortico-subcortical connectivity, resulting in a strong reward motivation, low social sensitivity, and dampened regulation of strong motivational/emotional processes. The link between these testosterone induced endophenotypes and actual display of antisocial behavior is strongly modulated by different social (e.g., social rejection, low SES) and genetic (e.g., MAOA, 5HTT) risk factors that can disturb socio-, psycho-, and biological development and interact with testosterone in shaping behavior. When these additional risk factors are present, the testosterone induced endophenotypes may increase the risk for a chronic antisocial lifestyle. However, behavioral endophenotypes induced by testosterone can also predispose towards socially adaptive traits such as a strong achievement motivation, leadership, fair bargaining behaviors, and social assertiveness. These adaptive traits are more likely to emerge when the high testosterone individual has positive social experiences that promote prosocial behaviors such as strong and secure attachments with his caregivers, affiliation with prosocial peers, and sufficient socioeconomic resources. A theoretical model is presented, various hypotheses are examined, and future venues for research are discussed. & 2012 Elsevier Ireland Ltd. All rights reserved.

Keywords: Testosterone Antisocial Delinquent Criminal Impulsivity Reward-sensitivity Fronto-limbic cross-talk

Contents 1. 2. 3.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 985 A note on testosterone (T) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 985 Is T associated with antisocial behavior? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 986 3.1. Predictors/indicators of severity and chronicity of antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 986 3.2. Fetal T and antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 987 3.2.1. The second-to-fourth finger ratio (2D:4D) and antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 987 3.2.2. Other indicators of heightened fetal T exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 987 3.3. Circulating T and antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 989 3.3.1. T and antisocial behavior in children (mean age 3–12) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 989 3.3.2. T and antisocial behavior in adolescents (mean age 12–20) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 993 3.3.3. T and antisocial behavior in adults (mean age 20–40) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 994 3.4. Summary and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995 3.4.1. Fetal T and antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995 3.4.2. Circulating T and antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995 3.4.3. Gender-differences in etiological pathways to psychopathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995

Corresponding author. Tel.: þ31646118681. E-mail addresses: [email protected] (B.O. Yildirim), [email protected] (J.J. Derksen). 1 Tel.: þ31 24 36 12666.

0165-1781/$ - see front matter & 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2012.07.044

B.O. Yildirim, J.J.L Derksen / Psychiatry Research 200 (2012) 984–1010

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T and behavioral traits related to antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 996 4.1. T and impulsivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 996 4.2. T and empathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 997 T and neurobiological endophenotypes related to antisocial behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 998 5.1. T and reward reactivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 998 5.2. T and orbitofrontal maturation and responsivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 998 5.3. T and cortico-subcortical cross-talk. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 999 Biological factors that modulate the T- behavior relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 999 6.1. HPA-axis functioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 999 6.2. Serotonin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1000 Social experiences that modulate the T-antisocial behavior relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1001 7.1. Socio-biological effects of child abuse and neglect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1001 7.2. Socio-psychological effects of child abuse and peer rejection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1001 7.3. Sociological effects of deviant peer group affiliation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1002 7.4. Biological and psychological correlates of socioeconomic status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1002 Theoretical model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1002 Future perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1003 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1004

1. Introduction Life-course persistent antisocial behavior is 10 to 14 times more likely to develop in males than females (Moffit et al., 2001; Moffit, 2003, 2006; Eme, 2009). Because of this strong gender ratio in chronic antisocial behavior, it is asserted that male gonadal hormones such as testosterone (abbreviated as T), may play a role in its etiology (Van Honk and Schutter, 2006; Eme, 2009; Terburg et al., 2009). Different studies have demonstrated that conduct disorder (CD) in childhood and a diagnosis of antisocial personality disorder (APD) or psychopathy in adulthood are related to higher T levels (e.g., Virkkunen and Linnoila, 1993; ˚ ¨ et al., 1999; Chance et al., 2000; Stalenheim et al., 1998; Aromaki ¨ Aromaki et al., 2002; Glenn et al., 2011). Furthermore, other measures of antisocial behavior such as externalizing behavior in childhood, first offence before adolescence, delinquency in adolescence, and being an adult inmate, have also been associated with heightened T levels (e.g., Kreuz and Rose, 1972; Mattson et al., 1980; Dabbs et al., 1987, 1991; Virkkunen and Linnoila, 1993; Dabbs et al., 1995; Banks and Dabbs, 1996; Maras et al., 2003a; 2003b; Van Bokhoven et al., 2006). Despite the wealth of research into the relationship between T and antisocial behavior, there are no reviews that set up scientifically grounded hypotheses and construct the needed theories and models. The first goal of this paper is to determine if heightened T is consistently associated with antisocial behaviors throughout the life-span. We will try to answer this question through review and critical evaluation of studies that examine the relationship between fetal/circulating T and different indicators (e.g., CD and APD) and predictors (e.g., parole board decisions, externalizing behavior) of antisocial behavior. The second goal is trying to clarify how underlying behavioral or neurobiological processes induced by T could provide explanations on how T may increase the risk for antisocial behavior. Following this discussion on T, we will also examine different genetic and social factors that could modulate the relationship between T and antisocial behavior. After reviewing the literature and discussing the findings we will follow with the introduction of a new model to summarize the findings and commence new theories. We will conclude with potential future venues for research. The search for literature included the following databases; PubMed, Elsevier Sciencedirect, OvidSP, JSTOR, Sage, and Wiley Interscience. The following primary keywords were used; (fetal-) testosterone, second-to-fourth finger ratio (2D:4D), androgen, gender differences, HPA-axis, MAOA gene, social experiences.

These primary keywords were coupled to the following secondary keywords; antisocial, delinquency, criminal, impulsivity, empathy, prefrontal cortex, limbic system, dopamine, serotonin, corticosubcortical cross-talk, reward-sensitivity.

2. A note on testosterone (T) T is predominantly a male gonadal hormone that affects behavior and brain functioning differently dependent on the time of exposure (Phoenix et al., 1959). This phenomenon is called the organizational–activational hypothesis and asserts that gender- and individual-specific behavioral and neural responses to surges of T throughout the lifespan can significantly be programmed through the organizing effect of fetal T levels on maturation of the underlying neural circuitry (organization of the specific T-behavior response). Higher levels of fetal T exposure lead to sensitized and more ‘‘masculinized’’ behavioral responses to T throughout life (Phoenix et al., 1959; Arnold and Breedlove, 1985). Regarding organizational effects, different measures are used to determine T exposure in utero. Amniotic fluid assessment, which is a direct and valid measure of fetal T (Van de Beek et al., 2004), have not been conducted with regard to antisocial behaviors. The dominant measure as a proxy for fetal T that has been related to antisocial behavior is the second-to-fourth digit ratio (2D:4D). The validity of the 2D:4D measure as a proxy of fetal T has been confirmed in both rodents (Zheng and Cohn, 2011) as well as humans (Lutchmaya et al., 2004; McIntyre, 2006), indicating that lower ratios are associated with higher levels of fetal T exposure. Additionally, congenital hyperplasia, a condition that results in heightened levels of fetal T, has also been related to ¨ kten et al., 2002) but this lower 2D:4D ratios (Brown et al., 2002; O result has been less consistent (Buck et al., 2003). Furthermore, as is hypothesized by the organizational–activational theory of T, it has been demonstrated that the 2D:4D ratio modulates the effect of circulating T on behavioral measures such as cognitive empathy (Van Honk et al., 2011a). Nonetheless, further research is still needed to replicate and validate these preliminary findings and determine the exact strength of the relationship between 2D:4D ratios and actual fetal T exposure (see McIntyre, 2006 for a critical discussion). For example, gender-differences in 2D:4D ratios in newborns are smaller than in adults, become more pronounced during the first years of life, and show significant associations with postnatal levels of T (Knickmeyer et al., 2011).

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Other indirect forms of measuring the potential effect of fetal T on behavior are through studies with individuals naturally exposed to higher levels of fetal T. First off, women with the genetic disorder Congenital Adrenal Hyperplasia (CAH), are exposed to abnormally high levels of fetal androgens because of an enzyme defect. In males, CAH is less valid as an indicator of heightened fetal T exposure since uncontrolled adrenal androgen secretion can result in increased neural feedback and inhibition of testicular T production (via the aromatization of T into estrogens) which may lead to secondary hypogonadotrophic hypogonadism (Brown-Grant et al., 1975; Mathews et al., 2009). Since females do not produce testicular T, the high levels of fetal androgen exposure cannot be counterbalanced and result in masculinization of brain and behavior (Brown-Grant et al., 1975; Mathews et al., 2009). Other psychological effects of the disorder are also more pronounced in males. CAH is often discovered at a later age in males compared to females because of the absence of clear physical deformities (Hines and Kaufman, 1994). Males with CAH are therefore less preventively treated from birth and thus more often hospitalized for salt-losing crises at early ages (Hines and Kaufman, 1994). These traumatic hospitalizations show an inverse relationship with levels of aggressivity and rough-andtumble play demonstrating a significant effect of the illness on personality development, especially in males (Hines and Kaufman, 1994). Therefore, we will exclusively concentrate on findings in women with CAH. A second natural experiment to investigate the effects of fetal T is by examining the effects of fetal hormone transfer in opposite-sex twins. Female animals that codevelop next to a male twin, have been found to show increased levels of masculine behaviors (Ryan and Vandenbergh, 2002) and this is likely to be true in humans as well (Tapp et al., 2011). This may be explained when considering that T synthesized by a developing male fetus can diffuse across amniotic membranes thereby affecting neighboring fetuses and affecting the organizational maturation of their brains (i.e., masculinization of specific aspects of behavior, cognition, and morphology) (Ryan and Vandenbergh, 2002). In addition, T can also diffuse between fetuses through the mothers’ bloodstream (Meulenberg and Hofman, 1991). In this sense, females from an opposite-sex twin dyad are exposed to higher levels of fetal T than same-sex female twins and the differences in behavior between both groups could also inform on the effect of fetal T on behavior. Unfortunately, the literature regarding natural experiments of fetal T and antisocial behavior is very limited and can be regarded as preliminary. Activational effects are assessed through levels of circulating T which are measured through a variety of techniques. Most common methods of T measurement are through collecting saliva or blood samples and assessing circulating T levels via enzyme- or radio immunoassay procedures (EIA and RIA, respectively). Other procedures are measuring T levels through urine and in CSF fluid although the great majority of studies reviewed in this paper use either blood draws or saliva. Salivary assessments provide a direct measure of the unbound T because the larger protein bound T molecules do not readily pass through the saliva glands (Vining and McGinley, 1984). In contrast, in blood samples, a high percentage of T in the human body is bound by proteins such as sex hormone binding globulin (SHBG) and albumin that may affect its direct influence on neurobiology or behavior. Therefore, T in blood can be measured as ’’total’’ (i.e., the percentage which is protein bound) or ’’free’’ (i.e., unbound). However, SHBG levels vary strongly with age, substance abuse, and with bodily fat levels, whereas free-T is less affected by these parameters (e.g., Vermeulen et al., 1996; Allen et al., 2002). This is relevant because the relationship between total-T and behavior can be strongly modulated by SHBG levels. For example, Aluja and Garcia (2007) found that SHBG levels were higher in aggressive subjects

compared to controls and strongly modulated the relationship between total-T and aggressiveness. When SHBG levels were controlled for, the positive correlation between T and aggression ¨ became non-significant. In addition, Stalenheim et al. (1998) also reported that total-T and SHBG were higher in subjects with antisocial personality disorder compared to controls but found no difference with regard to free-T. Aluja and Garcia (2007) suggest that not T levels but liver damage caused by an unhealthy lifestyle (e.g., substance abuse, obesity) and leading to higher levels of SHBG may be related to aggression and anger thereby confounding the relationship between T and behavior in antisocial samples. Nevertheless, since we also review studies of total-T in children and adolescents when SHBG is unlikely to be altered by liver damage, substance abuse, or age, these studies may provide more direct representations of the total-T behavior relationship.

3. Is T associated with antisocial behavior? In the following section, we will focus on the association between fetal/circulating T and antisocial behaviors throughout the life-span. We will examine the following research questions; Do antisocial individuals have higher levels of fetal T exposure/ circulating T? How strong are the effect sizes? Does the strength of the relationship between fetal/circulating T and antisocial behavior vary at different life phases (childhood, adolescence, and adulthood)? Because biological transitions can impact on the relationship between T and biology/behavior, we have chosen to divide the discussion into the following age groupings; childhood and transition into adolescence (ages between 3 and 12), adolescence (ages between 12 and 20), and adulthood (age of 20 and up). These age groupings are justified by consistent empirical evidence that the pubertal surge of T and the crystallization (i.e., final maturation) of gender-specific physical anatomy and behavior (i.e., strong activational effects) begin at about 12 years of age and peak at age 16, reaching adult values (Sato et al., 2008). The transition into adulthood is set at the age of 20 since the maturation of prefrontal cortices is nearly complete at about 20 years of age with only small increases in this maturation between 20 and 25 years of age (Giedd, 2004; Toga et al., 2006).

3.1. Predictors/indicators of severity and chronicity of antisocial behavior Childhood and adolescent behavior disorders which have been consistently linked to antisocial behavior are the disruptive behavioral disorders (DBD) such as oppositional defiant disorder (ODD) and conduct disorder (CD) (Taylor et al., 1996; Simonoff et al., 2004; Burke et al., 2010; Pardini and Fite, 2010). Children and adolescents diagnosed with either ODD or CD are also at an increased risk of developing antisocial personality disorder (APD) later in life (Simonoff et al., 2004; Pardini et al., 2006; Gelhorn et al., 2007). Attention Deficit Hyperactivity Disorder (ADHD) has also been related to antisocial personality development but this association is less strong and is found mainly with the combined type of ADHD (Hyperactivity/Impulsivity) (Fergusson and Horwood, 1995; Taylor et al., 1996; McKay and Halperin, 2001; Murphy et al., 2002). Furthermore, children with callous-unemotional traits (CU), whether or not comorbid with CD, also have a greatly increased risk for a life long pattern of antisocial behavior and callous violence (Gretton et al., 2004; Pardini et al., 2006; Pardini and Fite, 2010). Additionally, we have also included studies conducted with community samples of children and adolescents that use parent-, teacher-, and self-report measures

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of delinquency and conduct problems. These measures encompass the Child Behavior Checklist (CBCL) ‘delinquency’ and ‘externalizing’ subscales, Risky Behavior Scale (RSB) ‘delinquency’ subscale, Youth Self-Report (YSR) ‘delinquency’ subscale, Social Potency/norm-Violating Behavior (SPNVB), Strength and Difficulties questionnaire (SDQ) ‘conduct problems’ subscale, and also other Questionnaires and (semi-)structured interviews designed ad hoc to measure delinquent behaviors. In adulthood, a valid and reliable tool to assess chronic antisocial behavior is the lifestyle/antisocial factor of the Psychopathy Checklist- Revised (PCL-R). The lifestyle/antisocial factor is frequently used in experimental, forensic, and clinical settings to determine recidivism risk, is strongly related to an antisocial and impulsive lifestyle, and is a somewhat similar but more comprehensive account of antisocial behaviors than those listed under APD in the DSM-IV (Verona et al., 2001; Hare, 2003). Furthermore, two personality disorders in particular, namely APD and borderline personality disorder (BPD), are associated and predictive of antisocial behavior throughout the lifespan (Tiihonen et al., 1993; De Barros and De Pa´dua Serafim, 2008). In addition to psychiatric conditions associated with antisocial behavior throughout life, we have also included studies from prison populations that assess criminal history, number of offences, parole board decisions, age at first conviction, and antisocial conduct within prison. These studies can provide more detailed and fine-tuned within-group comparisons between individuals with more or less severe antisocial behavior. In this review we have excluded studies that focus exclusively on the relationship between T and aggression. Different recent reviews and meta-analyses have already addressed the relationship between fetal/circulating T and aggression in humans (see Archer, 1991, 2006; Book et al., 2001; Carre´ et al., 2011; ¨ Honekopp and Watson, 2011; Yildirim and Derksen, 2012). Therefore, discussing this specific relationship would provide no new insights. However, since aggression is a strong indicator of antisocial behavior, the results and conclusions of these papers are used to aid in the construction of hypotheses and theoretical models that describe the probable causal mechanisms underlying the association between T and antisocial behavior. Regarding the included studies, we reviewed only measures that assessed the general level of antisocial behaviors or attitudes (e.g., socialization, social detachment, conduct problems, delinquency, being an inmate, criminality) rather than aggression specifically (e.g., reactive/instrumental aggression, hostility). We have identified 11 studies that assessed fetal T and antisocial behaviors, and 38 studies that assessed circulating T. The study design, descriptive statistics, and results of these studies are briefly summarized in Table 1 (fetal T and antisocial behavior) and Table 2 (circulating T and antisocial behavior). 3.2. Fetal T and antisocial behavior 3.2.1. The second-to-fourth finger ratio (2D:4D) and antisocial behavior Associations between 2D:4D and antisocial behaviors in children are highly inconsistent. In the youngest sample to date (children aged 2–5), Williams et al. (2003) studied the 2D:4D ratio as a correlate of conduct problems assessed through the Strength and Difficulties Questionnaire (SDQ) and found no association between both. However, Fink et al. (2007) conducted two independent studies in older samples and found significant results but with interactions of age and gender. In children aged 5 to 7, the 2D:4D ratio was found to be negatively associated with conduct problems assessed with the SDQ only in boys (r ¼  0.483, p o0.01). Remarkably, in a second study conducted with an older sample (ages 6–11) only girls showed a negative

987

correlation between 2D:4D and conduct problems (r ¼ 0.341, po0.01). The differences between these studies is that the younger samples (i.e. Williams et al., 2003 and study 1 of Fink et al., 2007) were assessed with the SDQ and the older sample with the Child Behavior Checklist (CBCL). Since the two measures are highly correlated in their ability to detect conduct problems (Goodman and Scott, 1999), it is unlikely that this difference caused the varying results. Further studies in children also find contrasting results. De Bruin et al. (2006) found that children with ADHD/ODD (mean age 9) had lower 2D:4D ratios compared to healthy controls (d¼0.39, p o0.05), while McFadden et al. (2005) reported no differences in 2D:4D ratios between children with ADHD-combined type (mean age 9.6) compared to healthy controls. However, McFadden studied children with exclusively ADHD-combined whereas De Bruin included children with ADHD and comorbid ODD in their sample which could have increased the variance in antisocial scores and thus increased the power of detecting differences. In sum, studies in children regarding 2D:4D ratios and antisocial behaviors report highly inconsistent results and it is at this point difficult to reconcile or explain these differences by comparing study designs. In adolescents, the results show consistent negative associations but again with interactions of gender. The first study by Stevenson et al. (2007) examined the correlation between 2D:4D ratios with ADHD/ODD symptoms assessed by the Wender Utah Rating Scale (WURS) but the results are difficult to interpret since their sample consisted of college students between the ages of 18 and 47 without specifying a mean age. Given that they studied a college sample and used adolescent measures of antisocial behavior (i.e., ADHD/ODD) we include this study in the adolescent section. In this study, a small negative correlation was found between 2D:4D and ADHD/ODD in both left (r ¼  0.230, po0.05) and right hand (r ¼ 0.199, p o0.05) but only in females. A second study by Martel et al. (2008) found that adolescent boys with ADHD-combined type had lower 2D:4D ratios compared to healthy controls (F(3.144)¼ 2.78, p o0.05) and ODD symptoms assessed with the Schedule for Affective Disorders and Schizophrenia (KSADS-E) were also negatively correlated with 2D:4D ratios (r ¼ 0.19, p o0.05). Although it was also found that CD symptoms showed a small negative correlation with 2D:4D ratios (r ¼  0.11), this association did not reach significance. In adults, the association between 2D:4D and antisocial behaviors is scarcely studied. Only one study assessed the association between 2D:4D and psychopathic traits in college students (mean age of 27) measured with the Self-Report Psychopathy Scale (SRP-II) and found that total psychopathy scores were positively correlated with right hand 2D:4D but only in females (r ¼0.45, p o0.05) (Blanchard and Lyons, 2010). In contrast, criminal tendency and antisocial behaviors were strongly and positively correlated with left hand 2D:4D but only in males (r ¼0.71, po0.05) which is a surprising finding. This result thus indicates that lower fetal T is moderately associated with higher psychopathy scores in females and strongly correlates with higher levels of antisocial behavior in males. It is unclear at this point how this finding may be reconciled with the existing literature on T and antisocial behavior.

3.2.2. Other indicators of heightened fetal T exposure Influences of fetal T exposure has also been examined through women with CAH. For example, Nielssen et al. (2011) described an interesting case study of a 21-year-old female with CAH who had committed premeditated homicide during non-adherence to her pharmacological treatment. The court accepted that she had diminished responsibility for her actions because of the heightened exposure to T. However, earlier studies reported

988

Table 1 Summary of studies on the relationship between fetal T and antisocial behavior. Subjects

Age group (M7 SD)

Fetal T measure

Dependent variables related to antisocial behavior

Study design

Relevant findings

Williams et al. (2003)

108M-CI 88F-CI

2–5

2D:4D

1 ¼Strength and Difficulties Questionnaire (SDQ) subscale of ‘conduct problems’

CS

Fink et al. (2007) (study 1)

25M-CI

5–7

2D:4D

1 ¼Strength and Difficulties Questionnaire (SDQ) subscale of ‘conduct problems’

CS

6-11

2D:4D

1 ¼Child Behavior Checklist (CBCL) subscale of ‘externalizing behavior’

CS

- Conduct problems and right 2D:4D (Partial regression coefficient b): In boys¼Ns. In girls ¼ Ns. - Conduct problems and left 2D:4D (Partial regression coefficient b): In boys¼Ns. In girls; Ns. - Conduct problems and right 2D:4D (Spearman’s rho): Whole sample¼  0.332** , In boys ¼  0.483** , In girls ¼  0.250 - Conduct problems and left 2D:4D (Spearman’s rho): Whole sample¼  0.337** , In boys ¼  0.457** , In girls ¼  0.196 - Externalizing and right 2D:4D (Pearson’s r): Whole sample¼  0.341** , In boys¼  0.027 , In girls ¼  0.601**

Fink et al. (2007) (Study 2)

De Bruin et al. (2006)

33F-CI

29M-CI 27F-CI

– Externalizing and left 2D:4D (Pearson’s r): Whole sample¼  0.360** , In boys¼  0.294 , In girls ¼  0.407*

67M-DBD

9.087 1.91

2D:4D

1 ¼DBD symptoms (ADHD/ODD) assessed by Diagnostic Schedule for Children IV (DISC-IV)

BS

– 2D:4D in children with ADHD/ODD (A) vs. healthy controls (B): Left hand ¼Ns., Right hand ¼ A oB*, d ¼0.39

96M-HC McFadden et al. 14M-DBD (2005) 17M-HC Martel et al. 72M-DBD (2008) 41F-DBD 77M-HC 60F-HC Blanchard and 30M-CS Lyons (2010) 24F-CS

9.087 1.82 9.67 1.9

2D:4D

1 ¼ADHD-combined type assessed by the DSM-IV-Tr

BS

- 2D:4D in children with ADHD-Combined type (A) vs. healthy controls (B): Left hand ¼Ns., Right hand¼ Ns.

10.677 2.41 14.25 72.32

2D:4D

1 ¼Parent and Teacher Behavior Assessment System for Children (ADHD-combined symptoms) 2 ¼DBD symptoms assessed by Schedule for Affective Disorders and Schizophrenia for School-Age children (KSADS-E) 1 ¼Self-Report Psychopathy Scale (SRP-II)

BS & CS – 2D:4D in children with ADHD (A) vs. healthy controls (B): In boys¼A o B, F(3,144) ¼2.78*, In girls ¼ Ns. - DBD symptoms as assessed by KSADS-E and 2D:4D (Pearson’s r): ODD symptoms¼  0.19**, CD symptoms¼  0.11 CS - Psychopathy scores and left hand 2D:4D (Pearson’s r): Whole sample¼  0.01 , In males ¼0.02 , In females ¼ 0.20 – Psychopathy scores and right hand 2D:4D (Pearson’s r): Whole sample¼ 0.10 , In males ¼ 0.07 , In females ¼0.45* – Psychopathy scores and average 2D:4D (Pearson’s r): Whole sample¼ 0.05 , In males ¼ 0.06 , In females ¼0.32 – Criminal tendency scores and left hand 2D:4D (Pearson’s r): Whole sample¼  0.08 , In males ¼0.71* , In females ¼  0.24 – Criminal tendency scores and right hand 2D:4D (Pearson’s r): Whole sample¼  0.13 , In males ¼  0.15 , In females ¼0.05 - Criminal tendency scores and average 2D:4D (Pearson’s r): Whole sample¼  0.08 , In males ¼0.02 , In females ¼  0.13 CS – WURS and left hand 2D:4D (Pearson’s r): In males ¼ 0.060, In females ¼  0.230** – WURS and right hand 2D:4D (Pearson’s r): In males ¼0.064 , In females ¼  0.199* BS – Dominance in CAH (A) vs. healthy controls (B): In males ¼ A o B** d ¼  0.84, In females ¼Ns.

15.017 1.89 Mean whole sample¼ 27.2

2D:4D

Stevenson et al. 61M-CS 161F-CS (2007)

18–47

2D:4D

1 ¼DBD symptoms (ADHD/ODD) assessed by the Wender Utah Rating Scale (WURS)

Mathews et al. (2009)

29M-CAH 40F-CAH

20.277 8.43 19.57 7.3

CAH

1 ¼Factors E (Dominance) and I (Tender-mindedness) from the 16PF

30M-HC 29F-HC

187 6.81 19.26 75.95

22F-CAH 22F-HC

22.7 22.7

Helleday et al. (1993)

– Tender-mindedness in CAH (A) vs. healthy controls (B): In males ¼ A 4B* d¼ 0.52, In females ¼ A o B** d ¼  1.16

CAH

1 ¼Karolinska Scales of Personality ‘‘socialization’’, ‘‘social desirability’’ and ‘‘social detachment’’ scales

BS

– Socialization and social desirability in CAH (A) vs. healthy controls (B): Socialization ¼ Ns. Social desirability ¼Ns. – Social detachment in CAH (A) vs. healthy controls (B): A 4B*** d ¼ 1.59

B.O. Yildirim, J.J.L Derksen / Psychiatry Research 200 (2012) 984–1010

Study

989

inconclusive and inconsistent findings between CAH and aggression (e.g., Money and Schwartz, 1976; Berenbaum and Resnick, 1997; Pasterski et al., 2007). Nonetheless, females with CAH consistently display lower levels of prosociality compared to healthy controls. Helleday et al. (1993) examined whether adult women with CAH differed from healthy women on the Karolinska Scales of Personality (KSP). They found that women with CAH scored higher on the subscale ‘‘social detachment’’ (p o0.001, d¼1.59) which indicates higher levels of coldness in social interactions and lower levels of empathy and attachment towards other people. In subsequent studies, these results were supported and it was found that women with CAH also show higher levels of dominance (po0.01, d ¼0.84) and lower levels of tender-mindedness (p o0.01, d ¼  1.16). These preliminary results indicate that women with CAH may be more dominant, less attached, and less empathetic, implying an important role of heightened fetal T in these behaviors. The last method regarding fetal T assessment and antisocial behavior comes from twin-studies that have examined the level of antisocial behavior in females from an opposite-sex twin dyad compared to same-sex female twins. Tuvblad et al. (2005) found that children (aged around 9) from a opposite-sex twin dyad showed higher levels of antisocial behaviors (i.e., CBCL ‘‘delinquency’’ subscale) than girls from monozygotic twin-dyads but not girls from a same-sex dizogytic twin dyad. The same was found in adolescents (aged around 13), with opposite-sex adolescent girls showing higher levels of antisocial behavior than monozygotic female twins but not same-sex dizogytic female twins. Nonetheless, the authors did not provide separate scores for the boys and the girls from the opposite-sex twin dyad and thus the findings could apply mainly to the difference between the boys in the opposite-sex twin dyad and the same-sex female twins. Meier et al. (2011) did provide separate scores for both the males and females in a opposite-sex twin dyad and found in a large community sample (N ¼6383) that adult females from an opposite-sex twin dyad showed significantly higher levels of antisocial behaviors in childhood (M7SD; 0.4871.02), than same-sex dizogytic females twins (0.39 70.88, po0.05, d¼0.09) and monozygotic female twins (0.39 70.89, po0.01, d¼0.09). Similarly, opposite-sex females also showed higher levels of antisocial behaviors in adulthood (0.54 71.01) compared to same-sex dizogytic females twins (0.39 70.79, p o0.01, d ¼0.1) and monozygotic female twins (0.45 70.88, po0.001, d ¼0.17). These preliminary results demonstrate that females exposed to higher levels of fetal T may indeed show increased levels of antisocial behaviors but these results must be regarded as preliminary.

nnn

nn

p o 0.05. p o0.01. po 0.001.

3.3. Circulating T and antisocial behavior

n

Meier et al. (2011)

Column ‘‘Subjects’’: M ¼male, F ¼ female, HC ¼healthy controls, CI ¼community individuals, CS¼ college students, DBD ¼disruptive behavioral disorders, CAH ¼congenital adrenal hyperplasia, OST ¼opposite-sex twins, SST ¼same-sex twins, MZT¼ monozygotic twins, DZT ¼ Dizogytic twins. Column ‘‘Study design’’: CS¼ correlational study, BS ¼between subjects comparisons. Column ‘‘Relevant Findings’’; ODD¼ oppositional defiant disorder, CD ¼conduct disorder, ADHD ¼Attention Deficit Hyperactivity Disorder. Ns ¼ Not significant.

1 ¼Childhood conduct disorder (retrospective) 2 ¼Adult antisocial behavior OST vs. SST

BS

1 ¼Child Behavior Checklist (CBCL) subscale of ‘delinquency’ (Wave 1) 2 ¼Self-reported delinquency (Wave 2) Tuvblad et al. (2005)

421F-MZT

Wave 1: 8.77 0.47 364F-DZT Wave 2: 666F-OST 13.77 0.47 1,502F-MZT 37.66 72.3 1,183F-DZT 1,572F-OST

OST vs. SST

BS

– CBCL delinquency in female MZT (A1) and DZT (A2) versus OST (B): A1o B* d ¼ 0.16, A2¼ B – Self reported delinquency in female MZT (A1) and DZT (A2) versus OST (B): A1oB** d¼ 0.2, A2 ¼B – Childhood conduct disorder in female MZT (A1) and DZT (A2) versus female OST (B): A1o B** d¼ 0.09, A2o B* d¼ 0.09 – Adult antisocial behavior in female MZT (A1) and DZT (A2) versus female OST (B): A1oB** d ¼0.1, A2oB*** d ¼ 0.17

B.O. Yildirim, J.J.L Derksen / Psychiatry Research 200 (2012) 984–1010

3.3.1. T and antisocial behavior in children (mean age 3–12) In the late 1930s a little boy of 3 years was treated with T in a mistaken attempt to treat tumors on his larynx. After treatment, although the tumor did not shrink, the personality of the boy changed dramatically. He became hyper-sexualized and started to dominate other children on his ward and was increasingly aggressive and oppositional, so much that he became notorious for his actions. Remarkably, after stopping the T treatment the boy slowly returned to his former self, becoming gentle, thoughtful of others, and his hyper-sexuality waned (De Kruif, 1945). Later studies have found similar results in various age groupings when examining the relationship between T and disruptive/ antisocial behaviors in children. The study with the youngest population examined was conducted by Strong and Dabbs (2000) who studied the relationship between free-T and different parental ratings of behaviors associated with antisocial behavior

990

Table 2 Summary of studies on the relationship between circulating T and antisocial behavior. Study

Subjects

Age group (M 7SD)

T Dependent variables measure

Community samples with children and adolescents 22M-CI S (EIA) Strong and Dabbs 15F-CI (2000) 25 3–8

Tarter et al. (2009) Fang et al. (2009)

12 208M-CI 164M-CI 180F-CI

9-12 1st : 12–14 Bl (RIA) 2nd :16 12.6 70.72 Bl (RIA)

Study Relevant findings design

Parental rating of behavior on likert scale: 1 ¼Moodiness (difficult, oppositional, irritable) 2 ¼Attached (close, warm, cuddly) 3 ¼Sociable (happy, not difficult, team player)

CS

Correlations with Free-T at ages 3–8 (Pearson’s r): Moodiness ¼0.35n, Attached ¼  0.52nn, Sociable¼ -0.44nn – Correlations with Free-T at ages 9–12 (Pearson’s r): Moodiness ¼0.68n, Attached ¼ -0.52, Sociable¼ 0.18

1 ¼Social potency/Norm-violating behavior (SPNVB)

LTS (WS) CS

–Total-T at point 1 (age 12–14) predicted SPNVB at point 2 (age 16); b ¼0.14n

1 ¼Child Behavior Checklist (CBCL) ‘delinquency’ subscale

– CBCL Delinquency and Free-T (Pearson’s r): In boys ¼0.22nn, In girls ¼  0.15n

S (RIA)

Self-report likert scale: 1 ¼Risky Behavior Scale (RBS) (sensation-seeking, delinquent, and norm-violating behavior)

CS

– RBS and Free-T (Pearson’s r): In boys¼ 0.25nn, In girls ¼  0.07

Granger et al. 106M-CI (2003) 107F-CI

13.7 71.53

S (RIA)

1 ¼Child Behavior Checklist (CBCL), ‘delinquency’ subscale. 2 ¼Youth self-report (YSR), ‘delinquency’ subscale. 3 ¼Diagnostic Interview Schedule for Children based on DSMIV (DISC), ‘disruptive behavior disorders’ category.

CS

Maras et al. (2003a)

36M-CI 51F-CI

14.5 70.3

Bl (RIA)

1 ¼Child Behavior Checklist (CBCL) ‘externalizing’, ‘delinquency’ BS & subscales. CS

Dabbs et al. (1990) (study 3) Dabbs et al. (1990) (study 4)

57M-CS

–

S (RIA)

CS

53F-CS 63M–CS

–

S (RIA)

Questionnaires about 1 ¼School delinquency (grade and high school) 2 ¼Current delinquency (since high school) Questionnaires about 1 ¼School delinquency (grade and high school) 2 ¼Current delinquency (since high school)

– CBCL delinquency and Free-T (Pearson’s r): In boys ¼ 0.116 to 0.167, In girls ¼  0.069 to  0.211n (dependent on time of measurement) – YSR delinquency and Free-T (Pearson’s r): In boys¼0.149 to 0.217n , In girls ¼  0.005 to 0.120 – DISC disruptive behavior and Free-T (Pearson’s r): In boys¼ 0.151 to 0.245n, In girls ¼  0.051 to 0.079 – Free-T in High externalizing subjects (A) vs. Low externalizing subjects (B): In boys ¼ A 4B, F(1.34)¼ 4.62n, d ¼ 0.71, In girls ¼Ns. – Free-T in never (A) vs. episodic (B) vs. persistent (C) externalizing subjects: A oBn d ¼1.1, A o Cn d ¼ 1.38, B ¼ C – CBCL Delinquency and Free-T (rho): In whole sample¼ 0.361n – delinquency and Free-T (Pearson’s r): School delinquency ¼ 0.21, Current delinquency ¼0.32

CS

– Delinquency and Free-T (Pearson’s r): School delinquency ¼ 0.00, Current delinquency ¼  0.17

1 ¼Children with DBD vs. healthy controls 2 ¼Child Behavior Checklist (CBCL) ‘externalizing’, ‘delinquency’ subscales.

BS & CS

S (EIA)

1 ¼Children with DBD vs. healthy controls

BS

– Free-T in children with DBD (A) vs. healthy controls (B): At age 5–8 ¼ Ns. at age 9–11 ¼A 4Bn d ¼2.06 – CBCL Externalizing and Free-T (Pearson’s r): At age 5–8 ¼0.09, at age 9 –11 ¼ 0.56nn – CBCL Delinquency and Free-T (Pearson’s r): At age 5–8 ¼  0.02, at age 9–11 ¼ 0.47n – Free-T in children with DBD (A) vs. healthy controls (B): In boys ¼Ns. In girls ¼ Ns.

8–12 (M¼ 10.2) 8–11 (M¼ 9.6) 9–15

Bl (RIA)

1 ¼Children with CD vs. healthy controls 2 ¼Child Behavior Checklist (CBCL) ‘delinquency’ subscale

BS & CS

– Total-T in CD (A) vs. healthy controls (B):Ns. – CBCL Delinquency and T:Ns.

Bl (RIA)

CS

1st : 13 2nd :15

S (RIA)

1 ¼Severity of non-aggressive CD symptoms (stealing, lying, vandalism etc.) 1 ¼Delinquency: - 27-item delinquency scale (stealing, lying, vandalism, drug abuse, theft) at age 13 – Official criminal records at age 16 and 21 1 ¼Adolescents with CD vs. healthy controls

– Total-T levels and high (A) vs. low (B) antisocial CD symptoms: A 4B, Proportional odds ratio¼ 1.4nn – Free-T and delinquency: At age 13¼ Ns. At age 16 ¼ Mann-Whitney U test; Z ¼  2.14n At age 21¼ F(1,91) ¼11.11nn High Free-T throughout adolescence was strongly predictive of continuous antisocial behavior

800CI (E 50% M)

62F-CS

Disruptive behavioral disorders (ODD&CD) Chance et al. 25M-DBD 8.77 1.5 S (EIA) (2000) 20M-HC 8.67 1.3 Dorn et al. (2009)

Van Goozen et al. (1998) Rowe et al. (2004) Van Bokhoven et al. (2006) Pajer et al. (2006)

84M-DBD 27F-DBD

97 1.8

57M-HC 12F-HC 15M-CD

9.27 1.6

25M-HC 713M (CD þ HC) 96M-CD

47F-CD 36F-HC

3rd : 20 16.5 70.9 167 0.8

Bl (RIA)

LTS (WS)

BS

– T levels in girls with CD (A) vs. healthy controls (B): Total-T ¼ Ns. Free-T ¼Ns.

B.O. Yildirim, J.J.L Derksen / Psychiatry Research 200 (2012) 984–1010

6–18

Booth et al. (2003)

Psychopathic Traits Loney et al. 29 CD&CU (2006) 20 CU 27 CD 32 HC (E 50% M) Dolan et al. 60M-PI 27M-HC (2001)

12–18

S (RIA)

1 ¼Adolescents with CD and/or CU vs. healthy controls

BS

– Free-T in children with CD&CU (A) vs. with only CU (B) vs. with only CD (C) vs. healthy controls (D):Ns.

30.37 6.0 29.7 76.6

Bl (RIA)

1 ¼Special Hospital Assessment of Personality and Socialisation BS (SHAPS) and SCID-II to determine antisocial and psychopathic traits 1 ¼Structural Clinical Interview (SCID) of DSM III personality BS disorders 2 ¼Psychopathy Checklist-revised (PCL-R)

– Total-T levels in subjects with APD (A) vs. without APD (B): A 4 Bn d ¼ 0.67, Free-T ¼Ns. – Total-T levels in subject high on L/A facet (A) vs. subjects low on L/A facet (B): A 4Bn n d ¼0.71, Free-T¼ Ns.

– Total-T levels in SHAPS psychopaths (A) vs. healthy controls (B): A 4B p o0.10

61M-PI

18–56

Bl (RIA)

Glenn et al. (2011) Laxton (1998)

156M-CI 22F-CI 62M-PI

36.5 78.8

S (EIA)

1 ¼Psychopathy Checklist-revised (PCL-R)

BS

– Free-T in high L/A (A) subjects vs. low L/A (B) subjects: Ns.

377 12.1

S (RIA)

1 ¼Psychopathy Checklist-revised (PCL-R) 2 ¼Scoring of past antisocial behavior

CS

– Free-T and antisocial behavior (Pearson’s r): L/A traits ¼  0.03 Non-violent crimes total score ¼  0.17 Sexual crimes total score ¼0.14

Bl (RIA)

1 ¼Delinquent (inmates) vs. healthy controls

BS

S (RIA)

1 ¼Crime records 2 ¼Prison disciplinary reports

BS

– Total-T levels in delinquent (A) vs. healthy controls (B) Pubertal (Tanner) stage 3; A 4Bn Pubertal (Tanner) stage 4; A 4Bn Pubertal (Tanner) stage 5; Ns. – Prevalence ratios (A : B) in high (A) vs. normal (B) Free-T delinquents Committed violent crimes; A 4B, odds ratio ¼1.4n Violated prison rules; A 4B, odds ratio ¼ 1.3n – Free-T and level of severity of criminal history (Pearson’s r)In whole sample; r¼ .20n – Behavior in high (A) vs. low (B) total-T criminals: Parole board decisions ¼A 4 Bnn, Violated prison rules ¼ A 4Bnn

Delinquent and prison inmate samples Mattson et al. 40M-DQ 13.7–19.1 (1980) (M¼ 16) 58M-HC 14.8–17.4 (M¼ 16) Dabbs et al. 113M-DQ 17–18 (1991) 692M-PI

19.8 72.6

S (RIA)

1 ¼Crime records 2 ¼Parole board decisions (risk of recidivism) 3 ¼Prison disciplinary reports

CS

Dabbs et al. (1987)

89M-PI

18–23

S (RIA)

1 ¼Crime records 2 ¼Parole board decisions (risk of recidivism) 3 ¼Prison disciplinary reports

CS

Banks and Dabbs (1996)

16M-DQ 13F-DQ 15M-HC 21F-HC 84F-PI 15F-HC

25.4 74.3 22.6 75.3

S (RIA)

1 ¼Delinquents (not currently imprisoned) vs. healthy controls BS

17–66 (M¼ 28)

S (RIA)

1 ¼Criminal history 2 ¼Prison behavior 3 ¼Parole board decisions (risk of recidivism)

CS

21M-PI

19–32 (M¼ 28)

CPB

1 ¼Age of commission of past criminal offences

CS

– Free-T in prison inmates (A) vs. healthy controls (B):Ns. – Free-T and number of charges (Pearson’s r): In whole sample¼ 0.27n – Free-T level and rule breaking prison behavior (number of disciplinary rep.): in whole sample¼ Ns. – Free-T level and Parole board decisions (Pearson’s r): in whole sample¼ 0.34n – T and age at first conviction: For violent Crimes ¼  0.65nn, For non-violent crimes ¼Ns.

87 F-PI

17–60 (M¼ 33)

S (RIA)

1 ¼Rule breaking/dominant behavior in prison

CS

– Free-T and behavior (Pearson’s r): Rule breaking/dominant behavior in prison¼0.30n

BS & CS

– T levels in subjects with APD (A) vs. without APD (B): Total-T ¼ Ns. Free-T ¼Ns. – T levels in inmates with (A) vs. without (B) disciplinary reports: Total-T ¼ Ns. Free-T ¼Ns. – T levels in recidivist (A) vs. first time (B) criminals: Total-T ¼ A 4Bn d¼ 0.12, Free-T ¼Ns.

Dabbs et al. (1988)

Kreuz and Rose (1972) Dabbs and Hargrove (1997)

Antisocial and borderline personality disordered samples 86M-PI 27.7 75.7 Bl (RIA) 1 ¼Inmates with APD vs. healthy controls Aluja and 2 ¼Inmates with vs. without disciplinary reports Garcia (2007) 3 ¼First time vs. recidivist

– Free-T and severely violent (A) vs. lowly violent criminals (B): A 4Bn t(87) ¼ 2.5, d ¼ 0.53 – Free-T and severity of prison rule violations (Pearson’s r): Violent criminals ¼Ns. Non-violent criminals ¼0.50n – Free-T and severity of parole board decisions (Pearson’s r): Violent criminals ¼ Ns. Non-violent criminals ¼0.45nn – Free-T levels in delinquents (A) vs. healthy controls (B): A 4Bn F(1,61) ¼5.83

991

Dabbs et al. (1995)

B.O. Yildirim, J.J.L Derksen / Psychiatry Research 200 (2012) 984–1010

˚ Stalenheim et al. (1998)

992

Table 2 (continued ) Subjects

Age group (M 7SD)

T Dependent variables measure

Study Relevant findings design

Roepke et al. (2010)

31F-BPD 30 F-HC

297 6.7 287 4.3

Bl (RIA)

1 ¼Adults with BPD vs. healthy controls

BS

– T levels in BPD (A) vs. healthy controls (B): Total-T ¼ Higher in BPD but Ns. Free-T ¼A 4 Bn d ¼0.55

29.3 78

Bl (RIA)

BS

36.4 78 M ¼31

Bl (RIA)

1 ¼Adults with a PD (with antisocial behavior) vs. healthy controls 2 ¼Criminal records (recidivism) of the PD subjects 1 ¼Adults with APD vs. adults with APD and comorbid BPD 2 ¼Severe CD vs. moderate CD

– T levels in PD (A) vs. healthy controls (B): Total-T ¼ A 4Bn d ¼1.51 Free-T¼ A 4Bn d ¼1.36 – T levels in PD recidivists (A) vs. PD non-recidivists (B): Total-T ¼ A 4Bn d ¼0.79, Free-T ¼A 4Bn d ¼0.81 – Total-T levels in APD (A) vs. APD þ BPD (B) ¼Ns. – Total-T levels in severe CD (A) vs. moderate CD (B): A 4Bnn d ¼ 1.54

M ¼37

Bl (RIA)

1 ¼Severity of antisocial behavior (ASP index)

CS

– ASP index and T (Pearson’s r): Morning Total-T ¼ 0.50n, Afternoon Total-T ¼ Ns., Evening Total-T ¼0.47n Mean Total-T ¼ 0.36n – ASP index and Total-T (after removal of items related to aggression) (Pearson’s r): Morning Total-T ¼0.51nn – ASP index and Free-T (Pearson’s r): In the APD group ¼0.52n, In the control group ¼0.36nn

¨ anen ¨ Ras et al. 42M-PD (1999) 22M-HC 16M-APD Lindberg et al. (2003) ¨ 59M-APD Aromaki et al. (1999) 16M-HC ¨ Aromaki et al. (2002) Virkkunen and Linnoila (1993)

317 6.9

10M-APD 31M-HC

27–71 32.6 79.7

S (RIA)

1 ¼Severity of antisocial behavior (ASP index)

CS

58M-APD 27M-HC

–

CSF (RIA)

1 ¼Criminals with APD vs. healthy controls 2 ¼Karolinska Scales of Personality (KSP) ‘‘socialization’’ subscale

BS & CS

– Free-T in criminals (A) vs. healthy controls (B)Criminals without APD ¼ A 4Bn, Criminals with APD ¼A 4Bnn – KSP socialization and Free-T (Pearson’s r): In whole sample¼  0.41n

M ¼37

S (RIA)

1 ¼Diagnostic Interview Schedule for DSM-III

CS

– Free-T and DSM-III classifications (Pearson’s r): APD ¼ 0.18nnn

37.2 73

Bl (RIA)

1 ¼CD in childhood (retrospective) 2 ¼Adults with APD vs. healthy controls 3 ¼Military AWOL (misbehavior in military service)

BS

– Prevalence ratios (A : B) in high (A) vs. normal (B) total-T subjects: CD ¼1:1.4n (95% CI ¼1.1–1.8), APD ¼1:1.9n (95% CI ¼1.6–2.3), Military AWOL¼ 1:1.8n (95% CI¼ 1.3–2.3)

Dabbs (1992) 4462M-AV

387 2.5

Bl (RIA)

1 ¼Juvenile delinquency (CD symptoms) 2 ¼Adult antisocial behavior

CS

– Total-T and antisocial behavior (Pearson’s r): Childhood conduct disorders ¼0.11nnn, Adult antisocial behavior ¼ 0.18nnn

Mazur, (1995)

4179M-AV

33–42

Bl (RIA)

CS

Booth and Osgood (1993)

4400M-AV

30–44

Bl (RIA)

Structural interview about 1 ¼Juvenile delinquency (CD symptoms) 2 ¼Adult antisocial behavior 3 ¼Military misbehavior Structural interview about 1 ¼Juvenile delinquency (CD symptoms) 2 ¼Adult antisocial behavior

– Total-T and antisocial behavior in whites (N¼ 3654) (Pearson’s r): Childhood CD symptoms¼ 0.11nnn, Adult antisocial behavior ¼0.11nnn, Military misbehavior¼ 0.10nnn – Total-T and antisocial behavior in blacks (N ¼525)(Pearson’s r): Childhood CD symptoms¼ 0.16nn, Adult antisocial behavior ¼ 0.10nn, Military misbehavior¼ 0.22nnn – Total-T and antisocial behavior (Pearson’s r): Childhood conduct disorders ¼0.14nnn, Adult antisocial behavior ¼ 0.11nnn

Army Veterans Dabbs et al. 5236M-AV (1990) (study 5) 4462M-AV Dabbs and Morris (1990)

CS

Column ‘‘Subjects’’: M ¼ male, F ¼female, HC ¼ healthy controls, CI ¼community individuals, CS ¼ college student, BPD ¼ borderline personality disorder, APD ¼antisocial personality disorder, DBD ¼disruptive behavioral disorders, ODD¼ oppositional defiant disorder, CD ¼ conduct disorder, CU ¼callous-unemotional traits, DQ ¼delinquents, PIM ¼prison inmates, AV ¼army veterans. Column ‘‘T measure’’: S ¼ Saliva, Bl ¼Blood, CPB ¼competitive protein binding method, CSF ¼cerebrospinal fluid, EIA ¼enzyme immunoassay, RIA¼ radio immunoassay. Column ‘‘Study design’’: CS¼ correlational study, BS ¼ between subjects comparisons, WS ¼within subjects comparisons, LTS¼ longitudinal study. Column ‘‘Results’’: L/A ¼Lifestyle/ antisocial facet of psychopathy. Ns ¼ Not significant. p o 0.05. p o0.01. nnn po 0.001. n

nn

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Study

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(Moodiness, Attached, and Sociable) in children aged 3 to 11. As a whole group, higher free-T children were more moody, being more often upset, fussy, and waking up in a bad mood (r ¼0.35). They were also less attached, being less cuddly and close to their parents (r ¼ 0.45). However, only the younger group (ages 3–8) showed a negative association with sociability (r ¼ 0.44) that disappeared in the older group (ages 9–11). Whereas the older group showed a strong positive association with moodiness (r ¼0.68) that was not found in the younger group. In sum, children with high free-T levels are less attached in general, and become more social but also more oppositional and irritable when transitioning into adolescence (Strong and Dabbs, 2000). Also in psychiatric samples, results vary with the age studied. Chance et al. (2000) found that children with disruptive behavior disorders (DBD) showed higher free-T levels than healthy controls (HC) only at age 9–11 (with strong effect sizes d¼ 2.06) but not at younger ages of 5 to 8 years. In addition, they also found that in the sample as a whole (both DBD and HC) externalizing and delinquent behaviors were only positively related to free-T at older ages (9–11) (r ¼0.56 and 0.47, respectively) and not in younger ages (5–8) (r ¼0.09 and  0.02). This finding is in line with Strong and Dabbs (2000) who also reported an absent association between free-T and disruptive behaviors at younger ages but significant correlations at the ages 9 to 11. Therefore, free-T may be more strongly related to pathological externalizing behaviors and thus antisocial behaviors at the transition into puberty (ages 9 to 11) but not in younger children (ages 3 to 8). In contrast, two other studies, in children aged 7 to 12, did not find a significant difference in free- and total-T levels between healthy controls and children with DBD’s (mean age 9) (Dorn et al., 2009), or CD (mean age 10) (Van Goozen et al., 1998). Although Dorn et al. (2009) used only total-T measures, Van Goozen et al. (1998) who used free-T measures, also did not find a relationship with delinquency (measured with Child-Behavior Checklist; CBCL). However, Dorn et al. (2009), did not differentiate between younger and older children, thus the correlation may have been significant only in the older cohort (ages 9 to 12) but not in the younger children (ages 7 to 9). We identified four studies with large numbers of participants that have retrospectively assessed childhood CD symptoms and their relationship with total- and free-T in adulthood. For example, Dabbs and Morris (1990) found that in a large group of army veterans the presence of CD symptoms during childhood was 1.4 times more likely in high free-T subjects compared to low free-T subjects. In addition, other studies have also found significant positive correlations between retrospectively assessed CD symptoms in childhood and total-T levels in adulthood (r ¼between 0.11 and 0.14) (Dabbs, 1992; Booth and Osgood, 1993; Mazur, 1995). These four studies have studied a combined population of more that 17.000 individuals, who’s criminal records were made available and were interviewed about childhood delinquency and antisocial behavior. Lidberg et al. (2003) also found that retrospectively assessed severity of CD symptoms was associated with total-T levels in adulthood. Subjects with severe CD symptoms in childhood displayed higher levels of totalT as adults than subjects with moderate CD symptoms (d ¼1.54). Despite the high number of subjects that were studied, one must be wary that correlations of 0.11 to 0.14 are accurate reflections of the actual correlation between T levels and childhood CD symptoms. Only total-T levels were assessed which are more subject to change with age than free-T levels due to lifestyle factors (e.g., substance abuse, unhealthy diet, liver problems). Therefore, causality is unclear; antisocial behavior throughout life, which is strongly related to an unhealthy lifestyle, may in time also have increased total-T levels (Aluja and Garcia, 2007).

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It appears that both total- and free-T show small to moderate correlations with antisocial behaviors in childhood, especially in boys, and these associations become stronger over time. Younger children show less robust associations between T and antisocial behaviors and these associations become more defined and robust in older children who are in the transition into adolescence.

3.3.2. T and antisocial behavior in adolescents (mean age 12–20) Five different studies have examined the relationship between T and antisocial behavior in adolescents from the community. These studies have mostly used the ‘delinquency’ and ‘externalizing’ subscales of the CBCL to assess antisocial behaviors. Regarding the ‘externalizing‘ subscale of the CBCL, Maras et al. (2003a) found that a group of highly externalizing adolescent boys had higher levels of free-T than a group of low externalizing boys of the same ages (d¼0.71). They also noted that subjects who never showed externalizing behaviors were lower in free-T than subjects who episodically (d¼1.1) or persistently (d¼1.38) showed externalizing behavior. Regarding the ‘delinquency’ subscale of the CBCL, two out of three studies report positive associations with T. Fang et al. (2009) report a significant but small association between free-T and delinquency (r¼0.22), which is in line with the moderate association found by Maras and colleagues (Spearman’s r ¼ 0.361) (2003a). The only study that failed to find a significant positive relationship between CBCL delinquency and free-T was Granger et al., 2003. Nonetheless, Granger et al. (2003) reported a positive relationship between free-T and CBCL delinquency in boys (r¼0.167) but this association did not reach significance. Also, a small but significant negative association was found in girls (r¼  0.211). Other measures of delinquency and antisocial behavior, such as the Youth self-report (YSR) delinquency subscale and the Risky Behavior Scale (RBS), were also found to be positively related to free-T levels in adolescent boys (r¼ 0.217 and 0.25, respectively) but not in girls (Booth et al., 2003; Granger et al., 2003). A final longitudinal study in the community indicated that total-T levels at ages 12 to 14 predicted antisocial norm-violating behaviors at age 16 (b ¼0.14) (Tarter et al., 2009). These results consistently indicate that free-T levels in community adolescent boys have a small but significant association with externalizing and delinquent behavior (rE0.20) in different studies with different methods (between-subject designs, correlational analyses, and longitudinal studies). Regarding adolescents with psychiatric diagnoses, we have found five studies that have examined the relationship between DBD symptoms and T levels. The first study is actually a community sample study but the degree of DBD traits have also been identified with the Diagnostic Interview Schedule for Children based on DSM-IV (DISC), ‘disruptive behavior disorders’ category (Maras et al., 2003a). In this study it was found that DISC identified DBD symptoms were positively related to free-T levels in boys (r ¼0.245) but not in girls (r ¼0.120). Three other studies have examined the differences in T levels in adolescents diagnosed with DBD vs. healthy controls. Rowe and colleagues found that adolescent boys with severe non-aggressive CD symptoms (high levels of non-aggressive antisocial behavior) were 1.4 times more likely to exhibit elevated total-T levels than adolescents with moderate non-aggressive CD symptoms (Rowe et al., 2004). Furthermore, free-T levels in a group of 13-year-old boys with CD were significantly predictive of delinquency and criminal behavior at age 16 and at age 21 (Van Bokhoven et al., 2006). Only one study reported an absence of a significant difference in free-T levels between different groups of adolescent boys that differed in degree of CD or CU symptomatology and a group of healthy controls (CD, CU, CD & CU, and healthy controls) (Loney et al., 2006). Furthermore, as with other measures of delinquency and antisocial behavior, both total- and free-T seem to be unrelated to

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CD in females (Pajer et al., 2006). Therefore, in addition to community samples, psychiatrically diagnosed adolescent boys with DBD’s consistently display higher free-T levels compared to healthy controls. In prison samples, three different studies have examined the relationship between T, past crimes and prison behavior. Mattson et al. (1980) found that total-T levels were significantly higher in delinquent adolescent boys compared to healthy controls, especially in boys with lower levels of pubertal development (Tanner stage 3 and 4). Within the group of delinquents, those with higher levels of free-T were 1.4 times more likely to have committed serious crimes rather than petty crimes, and were 1.3 times more likely to disregard prison rules and misbehave in prison than delinquents with lower levels of free-T (Dabbs et al., 1991). Dabbs et al. (1995) confirmed the higher level of prison misconduct and recidivism risk in a group of high free-T vs. low free-T adolescent prison inmates. Furthermore, in the same study free-T also correlated significantly with severity of criminal history (r¼0.20) (Dabbs et al., 1995). These results indicate that T levels are higher in delinquents than normal controls and strongly correlate with the severity of criminal behavior within the group of delinquents. In sum, many of reviewed studies above indicate a small positive association between free-T and antisocial, delinquent, and criminal behaviors in adolescents from the community, psychiatric, and prison samples (r E0.20).

3.3.3. T and antisocial behavior in adults (mean age 20–40) The majority of studies into the role of T in antisocial behavior have been conducted with adults. First off, ten different studies have examined T levels in relation to personality disorders that are strongly associated with antisocial behavior. Total-T levels were higher in criminals with APD vs. healthy controls (Virkkunen and Linnoila, 1993), and correlated significantly with the severity of antisocial behavior in APD subjects (r ¼between ¨ et al., 1999, 2002). This correlation also 0.36 and 0.52) (Aromaki remained significant after removal of items related to aggression (r¼ 0.51), indicating an unique association with the non-aggres¨ sive antisocial behaviors of these individuals (Aromaki et al., ¨ 1999). Sjoberg et al. (2008) also found a moderate to strong effect of free-T on the risk for antisocial personality traits (b ¼0.67). Also in healthy control subjects, severity of antisocial behavior was ¨ et al., 2002). positively correlated with free-T (r ¼0.36) (Aromaki Roepke et al. (2010) found that free-T, but not total-T, were significantly higher in subjects with BPD compared to healthy controls (d ¼0.55). However, total-T levels did not differentiate between subjects with APD compared to subjects with APD and comorbid BPD (Lindberg et al., 2003), indicating that T likely correlates with the antisocial behavior and not the severity of the ¨ anen ¨ personality disorder. Furthermore, Ras et al. (1999) found that both total- and free-T levels were significantly higher in personality disordered (PD) subjects with high levels of antisocial behavior compared to healthy controls (d ¼1.51 and 1.36, respectively). Finally, both total- and free-T levels in recidivists with PD’s were also higher than in non-recidivists with PD’s (d¼0.79 and 0.81, respectively). In contrast to these studies, Aluja and Garcia (2007) have found no differences in T levels in inmates with or without APD. The main difference with the other studies is that Aluja and Garcia compared inmates with APD to inmates without APD rather than subjects with APD to healthy controls. It is arguable that inmates generally display high levels of antisocial behavior and to differentiate between them on the basis of APD may not prove to be good indicator of the severity of antisocial behavior. Accordingly, the same study did find significant results when the subjects were differentiated on the basis of recidivism rather than

the presence of APD, with recidivists showing higher levels of ˚ total-T than non-recidivists (d ¼0.12). Stalenheim et al. (1998) also compared inmates with APD to inmates without APD and found a significant difference with the APD group having higher levels of total-T (d ¼0.67) but not free-T. The difference between ˚ the Stalenheim and the Aluja study is that both used different measures to assess APD in the prison population. Aluja and Garcia used a self-constructed measure, the Aluja Antisocial Personality Scale (AAPS), that has shown good sensitivity and specificity in identifying APD in prison populations, whereas Stalenheim and colleagues used the Structural Clinical Interview for DSM-III-R (SCID). Because of these differences in assessment it is complicated to pinpoint the factor underlying the different findings. However, in a large study (N ¼ 5,236) of army veterans, the diagnosis of APD derived from a structural interview was significantly related to free-T levels (r ¼0.18) (Dabbs et al., 1990). In short, the results in subjects from different samples are largely consistent and indicate that T levels are higher in antisocial subjects (APD and BPD) compared to healthy controls but also that within the group of antisocial subjects, T levels correlate with the severity of the antisocial behavior (ASP severity index, recidivism), also after removal of items relating to aggression. The second group who are at high risk to develop life-course persistent antisocial behavior are individuals with psychopathic traits, especially the lifestyle/antisocial (L/A) traits. Three studies have examined the relationship between T and the L/A traits. ˚ Stalenheim et al. (1998) found that inmates high in L/A traits had significantly higher total-T levels than inmates low in L/A traits (d¼0.71) but did not differ with respect to free-T levels. Furthermore, Dolan et al. (2001) also reported a trend towards higher levels of total-T in both psychopathic and antisocial prison inmates compared to healthy controls (F(2.81)¼2.49, P¼0.08). In contrast, two other studies have failed to find a difference in baseline free-T between low and high scorers on the L/A facet in both community (Glenn et al., 2011), and prison samples (Laxton, 1998). These results point out that mainly total-T and not free-T levels are associated with L/A traits indicating that part of this correlation may be explained by indirect biological effects such as liver damage through substance abuse or otherwise increased ¨ levels of SHBG (Stalenheim et al., 1998; Aluja and Garcia, 2007). The third group of studies are the prison inmate and delinquent samples. Free-T levels were found to be higher in delinquent adults (from the community) compared to controls (F(1.61)¼5.83, Po0.05) (Banks and Dabbs, 1996), and in violent criminals (imprisoned for robbery, rape, homicide) compared to non-violent criminals (imprisoned for drug possession, burglary, theft) (Dabbs et al., 1987). These results indicate that higher freeT levels are associated with increasingly violent and criminal acts such that criminals show higher levels than controls and violent criminals show higher levels than non-violent criminals. Furthermore, six different studies have examined the correlation between free-T levels in prison inmate samples and a variety of different predictors of antisocial behavior. Higher free-T was in some studies significantly related to increased rule-breaking behavior in prison (r ¼between 0.30 and 0.50) (Dabbs et al., 1987; Dabbs and Hargrove, 1997), whereas other studies report non-significant result between free-T and rule-breaking in prison (Dabbs et al., 1988; Aluja and Garcia, 2007). Higher free-T was also significantly positively associated with parole board decisions, indicating that individuals higher in free-T were rated by the parole board to be more dangerous and at more risk to recidivate, and therefore saw a greater need to contain them in prison as long as possible (Dabbs et al., 1987, 1988). Also, free-T levels were positively related to the number of charges in the criminal history (r ¼0.27) (Dabbs et al., 1988), and the age at first conviction for violent crimes (r ¼  0.65) (Kreuz and Rose, 1972).

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In sum, free-T levels are consistently higher in increasingly violent and antisocial populations (violent criminals4criminals 4healthy controls). Furthermore, in prison inmate populations, free-T levels are related to a variety of measures that are valid predictors of life-course persistent antisocial behavior (personality disorders, antisocial behavior index, risk to recidivate, rulebreaking in prison, number of charges, and age at first conviction) (r ¼between 0.30 and 0.70). The last population that has extensively been studied are the army veterans (AV). Army veterans are characterized by the same level of SES, education, and family background as healthy community individuals. Five different studies consisting of large groups of subjects (N ¼ ranging from 4179 to 5236) have examined this population and all have found small positive associations between T and antisocial behavior. First off, APD was found to be 1.9 times more likely to be diagnosed in a high free-T group of army veterans compared to a low free-T group (Dabbs and Morris, 1990). In accordance, Dabbs et al. (1990) also found a significant positive association between APD and free-T (r ¼0.18). These results demonstrate that among army veterans, those higher in T are more likely to be diagnosed as having APD than those low in free-T. In addition, different studies with veterans find a positive correlation between total-T and antisocial behaviors (r ¼ranging from 0.11 to 0.18) (Dabbs, 1992; Booth and Osgood, 1993; Mazur, 1995). Veterans higher in free-T were 1.8 times more likely to have misbehaved during military than those lower in free-T (Dabbs and Morris, 1990), and it was also found that total-T correlated positively with army misbehavior (r ¼0.10) and norm-breaking (r¼ 0.22) (Mazur, 1995). 3.4. Summary and discussion 3.4.1. Fetal T and antisocial behavior The hitherto studies into the relationship between fetal T, as measured by the 2D:4D ratio, and antisocial behaviors show highly inconsistent results. Studies in children find inconsistent results between 2D:4D and antisocial behavior to the point that it is complicated to identify the source of their differences. In adolescence, the results become somewhat more consistent and show a negative relationship between 2D:4D and antisocial behaviors (as expected) but these correlations are small and often insignificant. In adulthood only one preliminary study found a strong positive correlation with 2D:4D suggesting that it is actually lower fetal T that is associated with antisocial behaviors. In contrast, natural experiments regarding fetal T exposure find more consistently that higher fetal T exposure is related to increased antisocial behaviors and reduced prosociality. Specifically, CAH afflicted women primarily show lower levels of prosocial related traits such as tender-mindedness and higher levels of traits associated with antisocial behaviors such as dominance, aggression, and socio-emotional detachment. Furthermore, studies with same-sex versus opposite-sex twins confirm these results. Namely, females that are part of a oppositesex twin dyad show higher levels of antisocial behaviors than same-sex female twins especially during childhood and adulthood (agesE9 and 37). These results also attest for a potential link between fetal T and antisocial behaviors throughout life. Nonetheless, these conclusions are drawn from two studies with CAH women and two studies comparing twin-dyads and could thus be seen as preliminary. ¨ Honekopp and Watson (2011) recently confirmed in a large meta-analysis that a negative relationship exists between 2D:4D ratios and aggression albeit small, and this could also hold true for the association between 2D:4D and other antisocial behaviors. However, fetal T may not be related to antisocial behaviors directly but may indirectly increase the risk for antisocial

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behavior by sensitizing the T- behavior pathway and thus increasing the risk of high-T related psychopathology, especially when other risk factors are present (e.g., abuse). This could explain the contrasting results when studying fetal T without accounting for circulating T levels. For example, fetal T has been found to be related to lower social sensitivity in infants and toddlers and dampened empathetic capacities in children (e.g., Lutchmaya et al., 2002; Williams et al., 2003; Chapman et al., 2006; Knickmeyer et al., 2006). Moreover, it has been demonstrated that the 2D:4D ratio strongly modulates the effect of circulating T on empathetic capacities in young adults (Van Honk et al., 2011a). This modulating effect of fetal T on empathy and probably also antisocial behaviors is likely to be mediated through intersecting neurobiological endophenotypes which are organized by fetal T and can increase the risk for antisocial behaviors dependent on circulating T levels throughout life. Mediating endophenotypes may be related to fetal T induced programming of brain circuitry involved in reward (e.g., mesolimbic dopaminergic circuitry) and socio-emotional processing (e.g., right orbitofrontal cortex). We will elaborate on this hypothesis below in Section 5. 3.4.2. Circulating T and antisocial behavior Both free and total circulating T levels, have a small but positive correlation with antisocial behaviors throughout the lifespan and earlier reviews also reported a positive relationship between T and reactive/instrumental aggression specifically (Archer 1991; Book et al., 2001; Archer, 2006; Carre´ et al., 2011; Yildirim and Derksen, 2012). The correlations between circulating T and antisocial behavior are lowest in childhood (ages 3 to 8) (r E0.10), and increase during the transition into adolescence (ages 9 to 12). During adolescence, the association between T and different measures of antisocial behavior is small but higher than in childhood (r E0.20). Remarkably, the found associations between T and antisocial behaviors in adulthood show a greater variety between different samples (r E0.15 in community samples and r E0.45 in antisocial samples) than the associations in child and adolescent samples. Furthermore, these positive associations between T and antisocial behavior throughout all lifephases are particularly pronounced in males and not in females. Since males are naturally exposed to higher levels of fetal T, the T-antisocial behavior pathway could be modulated by fetal T exposure. A socio-psycho-biological explanation may explain the differing correlations between T and antisocial behavior during different lifephases. Critical psychological and biological development phases occur parallel to early childhood and adolescence. When these psychological and biological transitions are promoted by positive social experiences, positive mental models of the world and the healthy maturation of brain circuitry involved in impulse-control and empathy could inhibit biological influences over antisocial behavior during adulthood. Alternatively, when healthy biological maturation during these critical phases is thwarted by negative social experiences, the resulting disturbances in psychological and neurobiological functioning could augment the effect of biology on behavior and thus gradually increase the occurrence and severity of antisocial behaviors in biologically at-risk individuals. In Section 7, we will discuss the modulating effects of life phase-characteristic social experiences on the pathway from high T to antisocial behavior. 3.4.3. Gender-differences in etiological pathways to psychopathology Longitudinal studies of gender-differences in predictors of psychopathology might provide insight into the behavioral mechanisms underlying the relationship between high T and antisocial behavior.

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Cˆote´ et al. (2002) followed the development of a sample of 1.865 children over 6 years, from kindergarten to grade six and assessed the characteristic developmental trajectories (impulsivity, fearfulness, and helpfulness) towards potential future psychopathology. They found that boys were more likely than girls to follow a risk trajectory of high impulsiveness and low helpfulness (low empathy) towards future externalizing pathology, while girls were more likely to follow a trajectory marked by high fearfulness towards future internalizing disorders. Furthermore, different studies have found lower levels of impulsivity in girls as compared to boys, when studied as a predictor of crime (LaGrange and Silverman, 1999; Moffit et al., 2001), aggression (Campbell and Muncer, 2009), substance abuse (Stoltenberg et al., 2008), gambling behaviors (Stoltenberg et al., 2008), and adolescent sexual behavior (Hope and Chapple, 2005). Also, men tend to be less empathetic than women (Goldenfeld et al., 2005) and empathetic responding in men is strongly dependent on the individual perceived (Singer et al., 2006). Dampened empathy is also strongly and consistently related to antisocial behavior (e.g., Ellis, 1982; Lee and Prentice, 1988; De Kemp et al., 2007; Schaffer et al., 2009; Marshall and Marshall, 2011). Moreover, fetal and circulating levels of T have already been related to empathy (Yildirim and Derksen, 2012). In light of these results, we suggest that T could increase the risk for antisocial behavior by increasing impulsivity and/ or dampening empathy and this will be examined below. In Sections 4 and 5, we will, respectively examine the following questions; is T related to behavioral phenotypes of high impulsivity or dampened empathy? Through which neurobiological endophenotypes induced by T can these associations between T and behavior be explained?

4. T and behavioral traits related to antisocial behavior 4.1. T and impulsivity Impulsivity is generally defined as the inclination to initiate behavior without adequate forethought or insight into the consequences of this behavior. Current research demonstrates the differentiation of impulsivity into two components; impulsive action and impulsive decision making (see for detailed conceptualization Bechara et al., 2000; Winstanley et al., 2006). Impulsive action is the absence of higher order inhibitory control on behavioral tendencies leading to impaired response inhibition. In contrast, impulsive decision making is the tendency to act on short-term rewards, internal drives, or momentary emotions without proper cognitive insight into the long-term consequences. Beginning with correlational studies, Virkkunen et al. (1994a, 1994b) found that highly violent and impulsive offenders displayed higher levels of CSF T and lower levels of CSF 5HIAA than less violent and impulsive offenders. However, impulsivity was primarily related to low levels of CSF 5HIAA whereas T was related to high levels of aggression and interpersonal violence. In another study by Vikkunen and Linnoila (1993) CSF T concentration was also primarily associated with outward-directed aggressiveness and lack of socialization but not directly with impulsiveness in a group of alcoholic violent offenders. These results indicate that the relationship between T and impulsive violence may be mediated through its enhancing effect on aggression and its disturbing effect on socialization rather than increasing impulsivity, which is more directly related to low serotonin levels. Accordingly, T showed no association with impulsivity as measured by the Eysenck personality questionnaire (EPQ-II) in personality disordered men and pathological gamblers (Blanco et al., 2001; Coccaro et al., 2007), the Impulsiveness-Venturesomeness-Empathy (IVE) inventory in prison inmates (Dolan et al., 2001), the Barrat Impulsivity Scale (BIS) in two different samples of rapists (Giotakos

et al., 2003, 2005), the Impulsiveness Scale (IS) in a group of delinquent recidivists (Mattson et al., 1980), and the Minnesota Multiphasic Personality Inventory (MMPI) in pathological gamblers (Blanco et al., 2001). In prison inmates, T was related to less future planning (r¼ 0.210) on the BIS (Dolan et al., 2001), and higher avoidance of monotony (t¼ 1.85, Po0.05) (Mattson et al., 1980), living life more in the moment. However, T was unrelated to more relevant subscales on the BIS, such as motor-(impulsive action) and cognitive impulsivity (impulsive decision making) which are more strongly related to real-life impulsivity (Dolan et al., 2001). In ˚ contrast, Stalenheim et al. (1998) found a small but significant relationship between T and the impulsiveness subscale (r¼0.15) of the Karolinska Scales of Personality (KSP) in adult inmates. Some associational studies use behavioral tasks to assess the link between T and impulsivity. One study with a large group of participants (N¼154) found a significant association in both men and women between naturally varying T levels and risk taking on the Iowa Gambling Task (IGT) (Stanton et al., 2011). However, in contrast to the other studies reviewed above which are conducted with pathologically impulsive individuals, the participants in the Stanton study were college students. It has been supported in research that in low-impulsive individuals (such as college students), disadvantageous strategies on the IGT may not reflect impulsive decision making but rather deliberate risk-taking, which are two fundamentally different constructs (Steinberg et al., 2008; Upton et al., 2011). A second difference in the design of these studies may be related to the dependent measure used to assess impulsivity. Whereas the above studies used self-report personality measures, Stanton et al. (2011) used a behavioral task, which may also account for the found differences. Nevertheless, Takahashi et al. (2008) also used a behavioral task in a sample of college students and found a positive association between free-T and delay discounting in a group of male students (mean age 22), indicating that T might in fact be related to lower impulsive decision making. Therefore, high T may be related specifically with higher deliberate risk-taking rather than impulsive decision making. Regarding impulsive action on behavioral tasks, three different studies have examined the correlation with circulating T levels (Bjork et al., 2001; Fontani et al., 2004; Van Strien et al., 2009). Van Strien et al. (2009) measured the performance of a group of older men (mean age of 67) on the Eriksen flanker task (which measures the ability to suppress automatic behavioral tendencies) to assess the association between T levels and response inhibition. Higher levels of circulating T were positively related to the interference elicited by irrelevant incongruent flankers (r ¼0.24, P¼0.05). T was thus related to less inhibitory control over behavior resulting in heightened impulsive action. In a second experiment, T levels showed a significant positive association with commission errors in a the continuous performance task (r ¼0.55, Po0.01) (which has been related to impaired response inhibition) in 27 women aged between 32 and 55 (Bjork et al., 2001). In contrast, Fontani et al. (2004) reported a negative relationship between T and the number of errors in a go/no-go task (r ¼  0.294, P o0.01), indicating a better ability to suppress automatic responses. Their study was done with a greatly varied population, consisting of 35 males and 33 females between the ages of 18 and 77. Regarding these varying results it may be concluded that it is unclear at this point whether T influences impulsive action but it is likely that T does affect processes implicated in response inhibition. Another way to study the effect of T administration on impulsivity is through individuals that use/abuse T enhancing substances. Anabolic androgenic steroids (AAS) are stimulant drugs, often taken by athletes, which chemically boost T levels and hence improve muscle building and energy. Earlier correlative studies have suggested a positive relationship between AAS

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and different forms of impulsive behavior, including severe violence (Pope and Katz, 1988, 1990, 1994). This has been confirmed by Galligani et al. (1996) who reported a positive relationship between AAS abuse and impulsiveness on the Karolinka Scales of Personality. Other studies have reported that impulsivity is even more profound when combining AAS with other substances that can also lower impulse control (such as GABAergic drugs) (Kindlundh et al., 1999). The above research with AAS indicate that men who abuse these compounds are more likely to be impulsive. However, most studies examine men who already abuse AAS which clouds validity. It may well be that men who are more impulsive and risk-taking are also more inclined to abuse AAS, which is in accordance with the findings that high impulsiveness is related to stimulant substance abuse (Moeller et al., 2001). Therefore, one should be wary of the causality between AAS abuse and impulsivity. Regarding experimental designs (i.e., T administration and impulsivity in the laboratory), Goudriaan et al. (2010) observed no significant influence on IGT performance after one week of Letrozole treatment in men (which boosts T levels). However, Van Honk et al. (2004) report riskier, more disadvantageous decision making after a single administration of T to a group of healthy women ranging from 20 to 25 years of age. Nevertheless, it has been argued that risky decision making on the IGT by lowimpulsive individuals may reflect deliberate risk-taking in order to obtain rewards, rather than true impulsivity (Upton et al., 2011), again indicating that T may in fact increase risk-taking rather than impulsivity, which may be related to a T-induced focus on rewards (Van Honk et al., 2004). In sum, T has not been consistently linked to impulsivity and it is therefore unlikely that high T directly results in antisocial behavior through reduced control of short-sighted motivations and behavioral activations. However, T is likely to be related to higher risk taking and may have an effect on neurobiological processes implicated in impulsivity. In light of these conclusions we suggest that T increases the risk for reactive, aggressive, and reward driven impulsivity when impulse-control is compromised because of other risk factors. Other biological variables such as serotonin and cortisol, and social processes such as parent-child and social experiences are likely to strengthen the T-antisocial behavior relationship by compromising impulse-control. These modulating factors are discussed below in Sections 6 and 7. 4.2. T and empathy Preston and de Waal (2002) argue that empathetic responding may be processed via two pathways; the subcortical route is fast and reflexive and encompasses the basic emotional resonation with the distress of others (e.g., sub-cortical reactivity to facial expressions), whereas the cortical route is slower and strongly based on self- and other awareness and the capacity to take other people’s point of view (e.g., cortical appraisal of the significance of other’s distress). The first route is mainly determined by automatic and unconscious processes that are largely inherited and less affected by the environment (emotional empathy), whereas the second route is an effortful process that needs to be learned through socio-emotional experiences which communicate and promote self/other-awareness (social cognition/ cognitive empathy) (Eisenberg and Eggum, 2009). A recent review has already discussed the effect of T on empathy in depth and readers are therefore directed to this paper for a more comprehensive understanding of the role of T in empathy (Yildirim and Derksen, 2012). Higher fetal T exposure measured through amniotic fluid appear to be negatively related to eye-contact in 12-month-olds (Lutchmaya et al., 2002), and to the child version of the Empathy Quotient in 4 to 8 year olds

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(Chapman et al., 2006; Knickmeyer et al., 2006). Also, higher fetal T as indicated by a lower 2D:4D ratio has also been related to lower social cognition in girls between 2 to 5 years (Williams et al., 2003), lower cognitive empathy in women aged 20 to 25 (Van Honk et al., 2011a), and lower emotional empathy in women aged 18–49 years (Kempe and Heffernan, 2011). However, these results with regard to 2D:4D have been inconsistent and different studies have found no associations with social cognition in boys aged 2 to 5 (Williams et al., 2003), and cognitive empathy in men aged 18 to 49 years (Blanchard and Lyons, 2010; Kempe and Heffernan, 2011). Nonetheless, since amniotic fluid studies have greater construct validity than 2D:4D ratios and consistently find a negative association between fetal T exposure and social sensitivity/empathy in childhood we suggest that a small negative correlation likely exists. Regarding circulating T levels, in children of 5-years-old, affiliation (only in girls) and prosociality (only in boys) were found to be negatively related to salivary T (Azurmendi et al., 2006). Furthermore, research with university students also indicated an inverse relationship between prosocial behavior/personality and levels of T measured through saliva in both sexes (Harris et al., 1996). Finally, in older adult women, T showed a small negative relationship with kindness, having a caring attitude, and being helpful (Baucom et al., 1985). Regarding causal relationships between T and empathy, T administration in women from 19 to 31 years of age, was found to reduce facial mimicry when seeing dynamic facial expressions of happy and angry faces (Hermans et al., 2006). Furthermore, T administration to men was found to reduce generosity in the ultimatum game which is a measure of empathy (Zak et al., 2009; Zak, 2011), but this result has not been found in women (Eisenegger et al., 2009; Zethraeus et al., 2009). Moreover, it has even been found that T administration increases fair-bargaining behaviors in middle aged women demonstrating that T can have varying behavioral associations that can be both prosocial and antisocial (Eisenegger et al., 2009). Although these studies may not be directly comparable since Zethraeus used long-term administration of T whereas Eisenegger and Zak measured the effects of a single dose of T, they do imply widely varying behavioral associations of T (both prosocial and antisocial responses). Furthermore, both Eisenegger who used a single administration of T and Zethraeus who used long-term administration found associations in women that are normally not found in males (e.g., increased prosociality). Thus, preliminary reports indicate that women show differential responses compared to men irrespective of the duration of T administration (single vs. long-term). It is therefore tempting to speculate that these differences were found not only because of the length of administration but mainly because of gender differences in the response to T administration. This gender-difference in ultimatum game responses may be explained by the recent finding that the link between T and empathy is strongly dependent on fetal T exposure (Van Honk et al., 2011a). Nevertheless, future studies should delineate how T is exactly related to social behaviors in different settings (e.g., fair vs unfair players), in men versus women, and in response to single versus long-term administration. In reaction to these results, the hypothesis put forward by scientists in the field is that high levels of T in utero and high circulating T levels throughout the lifespan can dampen both emotional and cognitive empathy (e.g., Baron-Cohen, 2002; Van Honk and Schutter, 2006; Yildirim and Derksen, 2012). This effect of T on empathy may be explained by its effect on neurobiological substrates of empathetic responding such as the right orbitofrontal cortex. We will discuss this modulation below.

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5. T and neurobiological endophenotypes related to antisocial behavior 5.1. T and reward reactivity Gender differences have been found in psychological components of reward-sensitivity with males generally scoring higher than females. For example, males show higher sensitivity to rewards as measured by the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) in a sample of 584 Taiwanese college students (RayLi et al., 2007), in 1.563 Spanish undergraduates (Torrubia et al., 2001), and in a sample of 360 French adolescents and young-adults (Lardi et al., 2008). Other arguments to suspect that T is associated with reward processing include the increased reward-sensitivity during adolescence, which has also been attributed to the heightened expression of gonadal hormones such as T during this period (Dahl, 2001; Sato et al., 2008; Van Leijenhorst et al., 2009; Kuhn et al., 2010). In experimental research it has been indicated that T has strong rewarding properties on the brain and that this effect is mainly due to the activating effect of T on the mesolimbic dopaminergic circuitry. Hermans et al. (2010) designed a counterbalanced placebo-controlled crossover design in which 12 healthy female participants (mean age ¼20.4) were administered 0.5mg T sublingually and their ventral striatal response to a monetary incentive was assessed through blood-oxygenation level-dependent fMRI (BOLD-fMRI). Furthermore, intrinsic appetitive motivation of participants was also assessed through the Behavioral Activation System (BAS) scores. A single dose of T administration significantly increased mesolimbic BOLD responses during anticipation of the monetary incentive (reward-anticipation) (peak T¼5.89, Po0.005 after volume corrections) (Hermans et al., 2010), which is indicative of increased mesolimbic dopaminergic release (Schott et al., 2008). Interestingly, this effect was stronger in participants with a lower intrinsic appetitive motivation (peak T¼7.26, Po0.001 after volume correction), suggesting that individuals with low reward-sensitivity might be more sensitive to the rewarding effects of a single administration of T, probably because of its enhancing effect on reward-sensitivity. This result is interpreted as T shifting the balance from punishment- to reward processing thereby increasing risk taking to obtain shortterm rewards (Van Honk et al., 2004). The finding of Hermans and colleagues also help to explain the increased risk taking to obtain monetary rewards on the IGT after administration of T (Van Honk et al., 2004; Stanton et al., 2011) further supporting the hypothesis that high T is more likely to be related to risk-taking in order to obtain desirable rewards than to impulsivity that arises out of an inability to control behavior or foresee adverse consequences. In rodents, administration of T creates conditioned placepreferences that can be inhibited by dopaminergic antagonists, suggesting that the heightened place-preference due to T is partly modulated through its effects on dopaminergic processes (Alexander et al., 1994; Caldarone et al., 1996; Packard et al., 1998; Arnedo et al., 2000; Schroeder and Packard, 2000). These positive hedonic effects of T have been found to be mediated by actions of its metabolites, especially 3a-androstanediol, in the nucleus accumbens (Rosellini et al., 2001; Frye et al., 2002). Chronic exposure to T has shown to alter sensitivity to DA by increasing DA metabolism in the cerebral cortex (Kurling et al., 2005). For example, anabolic androgenic steroid (AAS) treatment also increased the binding potential of the dopamine transporter (DAT), indicating a higher clearing of dopamine from the synaptic cleft (Kindlundh et al., 2002). Increased DAT binding is suggested to reflect efforts of the brain to compensate for the higher release of dopamine due to AAS use, indicating the robust effect of T on dopaminergic functioning (Kindlundh et al., 2002). Finally,

infusion of T into the nucleus accumbens has strong rewarding properties in rodents, which can also be blocked with dopaminergic D1 antagonists (Packard et al., 1997, 1998) and long-term T treatment down-regulated D2 autoreceptor density in the nucleus accumbens (Kindlundh et al., 2001, 2003), indicating that T increases D1-receptor and decreases D2-receptor sensitivity in brain structures closely associated with reward processing. In sum, in both humans as well as in rodents, T has been found to increase mesolimbic dopaminergic reactivity demonstrated by an increased neural reactivity to reward and decreased D2receptor mediated inhibitory control of that activity. We therefore propose that T increases motivational responses to rewards. How might increased neural reactivity to rewards and higher reward-sensitivity influence antisocial behavior? First off, higher reward-sensitivity, due to a higher reactivity of mesolimbic dopaminergic circuitry and decreased auto-inhibitory D2 receptor densities in neocortex and limbic structures have been found to predispose towards favoring short-term small rewards over more delayed but greater rewards (low delay discounting) and thus predisposes towards risk-taking and impulsive decision making, likely resulting in increased impulsivity and antisocial behavior when other risk factors are also present (e.g., orbitofrontal disturbance) (Kheramin et al., 2002; Viggiano et al., 2002; Acheson et al., 2006; Bezzina et al., 2007; Dalley et al., 2007; Bezzina et al., 2008; Davis et al., 2008; Steeves et al., 2009; Buckholtz et al., 2010; Waraczynski et al., 2010). Second, a hyper-focus on concrete and short-term rewarding outcomes may compromise adaptive consideration of long-term aversive consequences. Failing to take into account aversive long-term consequences beforehand because one is hyper-focused on directly rewarding behavior may lead to a dominant focus on rewards during decision making and thus hedonistic behaviors (Bechara et al., 2000). Thirdly, because of hypersensitivity to rewards there may be less flexibility in ongoing behavior when peripherally warned of potential punishments and dangers (response modulation), when the rewarding stimulus actually ceases to be rewarding, and/or is accompanied by different aversive consequences that would normally neutralize the rewarding property (response reversal) (Newman et al., 2005; Goodnight et al., 2006; Wallace and Newman, 2008; Wallace et al., 2009; Baskin-Sommers et al., 2010). 5.2. T and orbitofrontal maturation and responsivity Both organizational and activational effects could have effects on the maturation and functionality of important cortical structures involved in socio-emotional processes. The right orbitofrontal cortex has been implicated in socio-emotional modulation during motivational decision making but also more directly in empathetic responsivity and social sensitivity (Damasio et al., 1990; Grattan et al., 1994; Eslinger, 1998) and thus strongly modulates impulsivity, emotion regulation, and empathy. Empirical studies have found that males consistently show lower right orbitofrontal gray matter volumes (Xu et al., 2000; Welborn et al., 2009; Raine et al., 2012; Lombardo et al., 2012), and reduced functionality of this structure during emotional decision making (Lee et al., 2009). Raine et al. (2012), found that lower orbitofrontal gray matter volumes in males explained 77.3% of the gender-difference in antisocial personality/behaviors. Moreover, this reduction was not a function of psychiatric comorbidity, psychosocial risk factors, head injury, or trauma exposure, indicating that sexual differentiation may partly underlie the found differences in the right orbitofrontal cortex gray volumes, and thus, antisocial behavior (Raine et al., 2012). Indeed, fetal T exposure as measured through amniocentesis at 13–20 weeks of gestation (i.e., a timeframe that is hypothesized to be critical in human sexual differentiation; Hines, 2004) was found to negatively predict right orbitofrontal gray volumes (t¼5.69, po0.001) and this effect

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accounted partially for the observed gender-differences of this structure in the same study (rpartial ¼0.49, p¼0.006) (Lombardo et al., 2012). Activational effects of T may then exacerbate these differences and increase the risk for antisocial behaviors. For example, circulating T levels have been found to be negatively correlated with bilateral orbitofrontal cortex responsivity to social cues during decision making, which was directly related to higher levels of aggressive reactions (Mehta and Beer, 2009). Also in double-blind placebo controlled studies, T administration dampened orbitofrontal reactivity to social cues of distress (i.e., fearful facial expressions) (Van Wingen et al., 2009, 2010), indicating lower social sensitivity. Both antisocial behavior and empathy may thus be mediated through the effects of T on the maturation and functionality of the orbitofrontal cortex. These preliminary results indicate that fetal T may inhibit the maturation of the right orbitofrontal cortex and circulating T may subsequently dampen its responsivity to social cues resulting in lower empathy and higher aggressive behaviors, processes that increase the risk for chronic antisocial behavior. This observation is in line with the organization-activational theory of gonadal hormones (Phoenix et al., 1959), and the extreme male brain theory of autism which states that high levels of fetal T may lead to dampened maturation of brain structures involved in socioemotional processing (Baron-Cohen, 2002). 5.3. T and cortico-subcortical cross-talk The prefrontal cortices and the limbic system bi-directionally affect each others influence over behavior. This bi-directional flow of information (i.e., cross-talk) has been asserted to be a prerequisite for the normal human capacity to regulate emotions and compare the emotional consequences of different motivational actions plans and higher levels of cross-talk have been related to behavioral inhibition (Knyazev and Slobodskaya, 2003; Van Honk and Schutter, 2006; Van Peer et al., 2008). When this flow of information is disturbed, capacity of the prefrontal cortex to regulate emotional influences on behavior is likely reduced, and alternatively, capacity of the limbic system to modulate motivational and goal-driven action plans is also likely to be limited (Van Honk and Schutter, 2006). These processes can increase the risk for both reactive as well as instrumental aggression, respectively (Yildirim and Derksen, 2012). It is further suggested that the degree and quality of corticosubcortical cross-talk can be studied by examining the bandwidth of frequencies in which these structures oscillate when stimulated and observe how these frequencies are interrelated. It has been known that neural stimulation of the subcortical circuitry evokes delta/theta activity (4–8 Hz) (slow wave), whereas the cortical mantle of many primates oscillate in the 8–12 Hz (alpha) and 13–30 Hz (beta) frequencies (fast wave) (Gray, 1982; Knyazev and Slobodskaya, 2003). When EEG recordings are observed, the delta/theta frequencies (slow wave) and the alpha frequency (fast wave) are negatively correlated, implying that higher subcortical reactivity is associated with reduced prefrontal control (Robinson, 1999; Schutter et al., 2006). In response to such findings, it has been theorized that the degree of coupling between these slow and fast wave frequencies predicts prefrontal control over subcortical processes and thus the capacity to regulate emotional activations and control behavior that would normally be triggered by the emotional reaction or motivational activation (Knyazev and Slobodskaya, 2003). In response to EEG findings of an increase in slow wave frequencies, and a decoupling of EEG slow and fast-waves after T administration, it is hypothesized that T down-regulates cortico-subcortical interactions of information-flow (Schutter and Van Honk, 2004). Sleep-research studies have also indicated that higher levels of T

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correlated directly with increased levels of slow wave activity during sleep (Lindberg et al., 2003). fMRI studies support these hypotheses; T enhances the responsiveness of the amygdala to fearful or angry faces (Van Honk et al., 2001, 2005; Derntl et al., 2009; Hermans et al., 2008; Van Wingen et al., 2009, 2010) but decreases orbitofrontal reactivity to the same social cues (Mehta and Beer, 2009; Van Wingen et al., 2010). In response to these fMRI results, Van Wingen et al. (2010) assert that T ‘‘rapidly reduced functional coupling of the amygdala with the orbitofrontal cortex, and enhanced amygdala coupling with the thalamus. This suggests that testosterone may reduce the regulatory control over the amygdala, or that testosterone shifts amygdala output away from the orbitofrontal cortex towards the thalamus’’ (pp. 105, abstract). These processes are directly related to heightened social threat reactivity and reduced control of that reactivity (Van Honk and Schutter, 2006, 2007a), and can result in reactive aggression (Mehta and Beer, 2009). Another example illustrating diminished appraisal of social stimuli is the finding that T disturbs conscious recognition of the affective facial emotion of anger (Van Honk and Schutter, 2007a), while it increases limbic reactivity when confronted with an angry face (Van Honk et al., 2001, 2005). T may also decrease subcortical control over motivational processes. T has been found to increase utilitarian decision making when confronted with a moral dilemma (Carney and Mason, 2010) and it is posited that reduced limbic control of prefrontally mediated decision making processes increases the risk of premeditated antisocial behaviors (Van Honk and Schutter, 2006; Yildirim and Derksen, 2012). Accordingly, different studies and a recent review have also implicated heightened T in instrumental and goal-driven antisocial behaviors (Dabbs et al., 1995, 2001; Andreu et al., 2006; Yildirim and Derksen, 2012). In addition, high T has been found to increase risk taking to obtain rewards, indicating a shift from punishment processing to reward processing and thus a more instrumental way of decision making that is less dependent on emotional consequences and more focused on obtaining rewards (Van Honk et al., 2004; Stanton et al., 2011). Summarizing, Carney and Mason (2010) conclude that high T individuals ‘‘are able – and perhaps likely- to approach decision making in a manner that is divorced from negative affect and disproportionally focus on outcome’’ (pp. 670). In short, it could be that T induced decreases of cortico-subcortical coupling of information flow may result in decreased cortical control over dysregulated emotional processes and therefore in less cortically modulated expressions of strong emotions (reactive antisocial), but also in decreased limbic modulation of goal-driven motivations and thus in less emotionally modulated decision-making processes (instrumental antisocial) (Yildirim and Derksen, 2012). HPA-axis or serotonergic responsivity may partly influence which type of antisocial behavior is more likely in a high T individual and this modulation is discussed in the following section.

6. Biological factors that modulate the T- behavior relationship 6.1. HPA-axis functioning Different researchers have consistently asserted and supported that an important biological modulator of the T-antisocial behavior pathway is HPA-axis functioning (both baseline activity and phasic responsivity to stressors and threats) (Dabbs et al., 1991; Van Honk and Schutter, 2006; Terburg et al., 2009; Glenn et al., 2011). Regarding basal levels, a study of 4462 male US military veterans, higher behavioral inhibition was associated with higher basal cortisol levels, whereas higher behavioral activation was associated with higher T levels, indicating that the balance (ratio) between T and cortisol may modulate approach-withdrawal behavior (Windle,

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1994). Many researchers have also suggested that T and cortisol jointly regulate threat processing (Van Honk and Schutter, 2006), dominance (Mehta and Josephs, 2010), and physical aggression (Dabbs et al., 1991). Low basal cortisol levels have been consistently found in antisocial samples and relate with increased aggression ¨ (e.g., Fairchild et al., 2008; Hawes et al., 2009; Bohnke et al., 2010). Nevertheless, in a large meta-analysis, Hawes et al. (2009) conclude that both low and high basal HPA-axis activity is related to antisocial behaviors but that in children with high activity, environmental risk factors play a more direct and important role in the etiology of that behavior. Low basal cortisol may thus increase the behavioral activating effects of high levels of T and conversely high basal cortisol can inhibit these motivational tendencies. Therefore, antisocial individuals characterized by impulsivity, reactive aggression, and behavioral disinhibition may be more likely to exhibit low basal cortisol levels. Other studies have found differences in HPA-axis reactivity to direct stressors in different antisocial populations. For example, Glenn et al. (2011) found that basal cortisol levels were the same for both psychopathic and non-psychopathic individuals and that it was specifically an attenuated HPA-axis reactivity to stress which differentiated these two groups. Furthermore, high HPAaxis reactivity has also been found to relate to reactive aggression ¨ and impulsivity, especially in females (Bohnke et al., 2010). Interestingly, The intensity of HPA-axis reactivity to stressors is determined primarily by genetic factors and less by social experiences, whereas the latency of the HPA-axis to return to baseline functioning is affected by cortical structures (i.e., hippocampus and prefrontal cortex) and is strongly determined by both ¨ genotype and social experiences (Liu et al., 1997; Wust et al., 2004). Therefore, low HPA-axis responsivity to direct stressors and threats coupled with high T may characterize those with a particularly strong genetic foundation for antisocial behavior (Hawes et al., 2009) such as observed in psychopathy (Viding et al., 2005; 2008; Glenn et al., 2011), contributing to instrumentally aggressive and goal-driven antisocial psychopathology often observed in these individuals (but see Van Honk and Schutter, 2006; Terburg et al., 2009; Yildirim and Derksen, 2012 for a detailed discussion of this process). In contrast, high T interacting with high HPA-axis reactivity may particularly define those with a strong genetic foundation towards frustration and irritability and may increase the risk for reactive aggressive and impulse-driven antisocial psychopathology such as observed in antisocial and borderline personality disordered individuals (e.g., Marsman et al., 2008; Hawes et al., 2009; Kuepper et al., 2010; Roepke et al., 2010). Since both high and low cortisol reactivity may contribute to antisocial behaviors we will refer to this as HPA-axis deregulation rather than HPA-axis hypo- or hyperreactivity.

6.2. Serotonin Serotonergic mechanisms have been consistently implicated in impulsivity (Krakowski, 2003; Homberg, 2012). Highly impulsive and reactive aggressive offenders display both heightened T as well as dampened serotonergic responsivity (Virkkunenet al., 1993, 1994a, 1994b; Dolan et al., 2001). The link between T and antisocial behavior may thus be strongly dependent on dysfunctional serotonergic functioning in specific pathways such as the orbitofrontal cortex (Siever et al., 1999; Soloff et al., 2000, 2003; Meyer-Lindenberg et al., 2006; Liening and Josephs, 2010). In accordance, when serotonergic functioning is dampened, high T individuals have been found to be more likely to act out in impulsive and antisocial ways (Higley et al., 1996; Birger et al., 2003; Kuepper et al., 2010). For example, it was found that the interaction between low serotonin/high T predicted impulsivity in reactive aggressive responding more accurately than

either factor alone (Kuepper et al., 2010). These interacting influences of T and monoamines on impulsive behavior are replicated in nonhuman primates. Higley et al. (1996) found in a group of adolescent primates, that individuals with low levels of cerebrospinal fluid 5-HIAA levels (major metabolite of serotonin), exhibited high levels of impulsivity indicated by a increased amount of long leaps from tree to tree compared to more safe and shorter leaps (long leap ratio). However this ratio was synergistically increased if the individual also exhibited high T levels (low 5HIAA¼0.09, low 5HIAA  T¼0.40). Regarding genetic risk-factors influencing impulsivity, a functional VNTR polymorphism in the promoter of the monoamine oxidase A (MAOA) leading to a lower number of tandem repeats and associated with less profound MAOA activity (abbreviated as MAOA-L) may be such a genetic marker (MeyerLindenberg et al., 2006). For example, men with MAOA-L showed a significantly dampened CNS serotonergic reactivity to a fenfluramine challenge (Manuck et al., 2000), and reduced serotonergic activation of prefrontal structures (Passamonti et al., 2006). Reduced serotonergic responsiveness has been associated with reduced orbitofrontal activity patterns (Siever et al., 1999; Soloff et al., 2000), and aggression and impulsivity in males and females (Siever et al., 1999; Soloff et al., 2000, 2003; Carver et al., 2008). Accordingly, MAOA-L has been found to interact with high circulating T in the prediction of antisocial personality traits ¨ (Sjoberg et al., 2008). Liening and Josephs (2010) argue that genetic variation in MAOA genotypes is likely to modulate the extent to which T influences behavior with MAOA-L decreasing control over T-induced motivational/emotional activations. Since both MAOA-L and high T have been related to hyperreactivity of limbic structures to social threat combined with reduced orbitofrontal regulatory activity (Meyer-Lindenberg et al., 2006), MAOA-L genotype status and the presence of high T may be related primarily to reactive aggressive and impulse-driven antisocial behaviors as observed in antisocial and borderline personality disorder (Buckholtz and Meyer-Lindenberg, 2008). Interestingly, the core characteristics of psychopathy associated with instrumentally aggressive and goal-driven antisocial behaviors have been found to be positively correlated with serotonergic responsivity (Dolan and Anderson, 2003). A potential genetic risk marker for this type of antisocial behavior and which interacts with T, is the gene encoding for the serotonin transporter (5HTTLPR). The difference in the three different polymorphisms (s/s, s/l, l/l) of 5HTTLPR is related to variations in serotonergic functionality, with male l-homozygotes having a higher serotonergic responsivity independent of social experiences (Reist et al., 2001; Manuck et al., 2004). Furthermore, higher transcriptional activity associated with the l-allele is strongly related to an attenuated emotional responsivity to social and threatening stimuli with remarkable parallels to observations in psychopathic individuals (i.e., low amygdalar and HPA-axis responsiveness, impaired fear-conditioning, low autonomic arousal) (Glenn, 2011). This is also supported by studies who reported that lhomozygosity was found at higher rate in psychopathic individuals (Sadeh et al., 2010; Herman et al., 2011) but this finding has not been consistent (Fowler et al., 2009). Furthermore, l-homozygosity is also related to utilitarian decision making indicating instrumental decision-making processes (Koenigs et al., in press). Research has demonstrated that 5HTTLPR polymorphisms strongly interact with gonadal hormones, such as T, in HPA-axis reactivity to threat (Evans et al., in press; Josephs et al., 2012). Carriers of the s-allele display significantly higher cortisol reactivity to the social threat and stress compared to l-homozygotes. However, the difference in genotype status and cortisol reactivity becomes substantially stronger when T levels are included as a covariate. Participants with at least one s-allele show a positive correlation between T levels and cortisol reactivity, whereas in l-homozygotes T levels and cortisol

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reactivity to the same social stressor are negatively related (Evans et al., in press; Josephs et al., 2012). Comparing values in the high T individuals, s-homozygotes and l-homozygotes differed significantly in cortisol reactivity (t(19)¼2.21, p¼0.04, effect size r¼0.45) (Josephs et al., 2012). After reviewing different findings, Liening and Josephs (2010) posit the hypothesis that threat reactivity is only significantly reduced under the condition of both high T combined with l-homozygosity of 5HTTLPR. Since high circulating T combined with low cortisol reactivity has been associated with psychopathy (Glenn et al., 2011), l-homozygosity of 5HTTLPR combined with high T could be a strong biological risk factor for instrumentally aggressive and goal-driven antisocial behavior as observed in psychopathy (Glenn, 2011; Josephs et al., 2012).

7. Social experiences that modulate the T-antisocial behavior relationship 7.1. Socio-biological effects of child abuse and neglect Children who are abused or neglected and develop insecure attachment relationships (i.e., particularly avoidant attachment) with their parents or caretakers, display lower levels of impulse control and empathetic capacity, and have a higher risk for becoming antisocial, delinquent, and psychopathic than securely attached children (e.g., Bowlby, 1944; Greenberg et al., 1993; Van Ijzendoorn, 1997; Speltz et al., 1999; Aguilar et al., 2000). In the three studies that controlled for the security of the parent-child attachment relationship, the association between T and antisocial behavior in community samples became non-significant, indicating that the attachment relationship may serve as a strong protective modulator of the T-antisocial behavior link (Booth et al., 2003; Fang et al., 2009; Updegraff et al., 2006). This experience-dependent relationship between T and antisocial behavior may be partly explained through socio-biological processes interacting with fetal/circulating T. Biological maturation of cortical structures which are implicated in socio-emotional behavior is not complete at birth and is therefore strongly dependent on environmental factors, especially social experiences (Shore, 2001). Early relational trauma such as abuse and neglect have been suggested to disturb the healthy maturation of important structures implicated in empathy and impulse-control (i.e., ventromedial prefrontal structures) (Shore, 2001). Accordingly, children who are chronically abused or neglected show impaired functional reactivity of the orbitofrontal cortex in childhood (Chugani et al., 2001), and reduced gray matter volumes of this structure in adolescence and adulthood (Hanson et al., 2010; Thomaes et al., 2010; Edmiston et al., 2011). The destructive effects of relational trauma on maturation of orbitofrontal structures might interact with the T induced alterations in maturation and functionality of this structure (Mehta and Beer, 2009; Van Wingen et al., 2009, 2010; Lombardo et al., 2012). We therefore suggest that high levels of fetal/circulating T combined with negative social experiences is more likely to result in serious empathetic and impulse-control deficits than either factor alone. Another way that the early attachment relationship may have an impact on the T-behavior link is through the effect of these social experiences on maturation of neurochemical and endocrinological pathways implicated in human prosocial behaviors. Serotonergic and HPA-axis functioning have been discussed as biological modulators of the T-behavior pathway and the maturation and functionality of both systems is strongly influenced by early attachment experiences (Fontenot et al., 1995; Tafet et al., 2001; Shively et al., 2003; Gunnar and Vazquez, 2006). Moreover, reduced orbitofrontal functionality may be partly explained by the destructive effects of negative social experiences on

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serotonergic neurochemistry (e.g., Siever et al., 1999; Soloff et al., 2000; Shore, 2001; Passamonti et al., 2008). Preliminary reports indicate that parenting styles and parent-child relationship are related to the responsivity of the serotonergic circuitry throughout childhood (Pine et al., 1996; Crowell et al., 2008). Furthermore, high levels of social stress arising out of neglect and abuse during the first years of life may lastingly deregulate the set-point and activity of the HPA-axis throughout life (Wismer Fries et al., 2008; Bruce et al., 2009; Van der Vegt et al., 2009; Diamond and Fagundes, 2010; Quevedo et al., 2012). Oxytocin is another important hormone that acts as a neurotransmitter, is strongly impacted by early social experiences, and modulates both brain maturation and social functioning later in life. Oxytocin is related to attachment motivation, growth-promotion of the prefrontal cortex (in particular the medial frontal cortex), and the development of social sensitivity, empathy, trust, ¨ and human connectedness (Carter, 1998; Uvnas-Moberg, 2003). Different studies with rodents indicate that the production of oxytocin and its receptors in the medial frontal cortex, and therefore its lifelong effects on social behavior, may be especially vulnerable to postnatal experiences (Champagne et al., 2001; Francis et al., 2002). In humans, there have been associational studies finding that oxytocinergic responsivity to social cues is associated with early caregiving conditions (Wismer Fries et al., 2005), and adult attachment styles (Strathearn et al., 2009). Moreover, the development of oxytocinergic pathways strongly interacts with gonadal hormones. For example, gender specific levels of steroids, such as T and estrogen, alter the sensitivity and innervation of oxytocin and its receptors (De Vries et al., 1986; Johnson et al., 1991; Johnson, 1992). Oxytocinergic mechanisms are amplified by female sex-specific hormones such as estrogen (up-regulation of receptor sensitivity) (Rhodes et al., 1981; Johnson et al., 1991; Johnson, 1992; Grazzini et al., 1998), and are dampened by T (down-regulation of receptor sensitivity) (Johnson et al., 1991; Francis et al., 2002). Therefore, a double hit downregulation of oxytocinergic responsivity because of high levels of fetal/circulating T combined with insensitive attachments early in life is likely to have a synergistic negative effect on social functioning. In this sense, males may be more vulnerable to negative social experiences in the development of empathy and interpersonal connectedness. For example, Singer et al. (2006) reported that men showed empathy-related activation in painrelated brain structures (fronto-insular and anterior cingulate cortices) only toward fair players of an economic game, whereas women showed increased empathy-related responses towards both fair and unfair players, indicating that affective empathy in men is more strongly modulated by social experiences. 7.2. Socio-psychological effects of child abuse and peer rejection Children who are deficient in impulse control or empathy due to early relational trauma’s, insecure attachment patterns, and other negative social experiences, often display higher levels of aggression and impulsivity than children without these risk factors (Lahey et al., 2003). Consequently, impulsive and aggressive children/adolescents are more likely to be rejected by peers (Dodge, 2003; Chapple et al., 2005; Briscoe-Smith and Hinshaw, 2006), bullied by peers (Shea and Wiener, 2003; Kokkinos and Panayiotou, 2004; Holmberg and Hjern, 2008; Cook et al., 2010), victimized in different settings (Kokkinos and Panayiotou, 2004; Turner et al., 2010), rejected by teachers, expelled from school, and are more likely to be abused by parents (Gottfredson and Hirschi, 1990; Briscoe-Smith and Hinshaw, 2006). In a sense these youngsters are more likely to be rejected by their community at large because of their aberrant social behavior (Shea and Wiener, 2003).

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During childhood children develop ‘‘multidimensional, stable and unique patterns of processing social stimuli, which form the working component of personality’’ (pp. 225, Dodge, 2003) and strongly determine social adjustment (Crick and Dodge, 1994). Abuse by caregivers and repeated rejections and victimization by peers during this critical period can result in biased social information processing patterns centred around a hostile and rejecting worldview (Dodge et al., 2001, 2003). These individuals develop social hypersensitivity to threatening and rejecting cues and react fiercely to these perceived provocations (Crick and Dodge, 1994; Dodge et al., 2003). With advancing age, social information processing patterns become self-perpetuating thereby evolving in stable traits and personality patterns (Dodge and Price, 1994; Dodge, 2003). Somewhat similarly, T has been implicated in hypersensitivity to social threat and a increased tendency to react with aggression and dominance to perceived injustices and slights (Archer, 2006; Van Honk and Schutter, 2007b; Bos et al., 2012; Yildirim and Derksen, 2012). T enhances the responsiveness of the amygdala to social threat (Van Honk et al., 2001, 2005; Van Wingen et al., 2010) and decreases orbitofrontal reactivity to and conscious recognition of the same social cues, which is directly related to reactive aggression (Van Honk and Schutter, 2007a; Mehta and Beer, 2009; Van Wingen et al., 2010). Second, the neuropeptide vasopressin is released when the environment is perceived as being unsafe, threatening, and challenging (Kvetnansky et al., 1989, 1990), and is associated with increased power-motivation (dominance) and intermale offensive aggression in response to social threat (Compaan et al., 1991; Delville et al., 1996; Sewards and Sewards, 2003). Because T augments vasopressinergic activity in limbic areas (Rasri et al., 2008), hostile attributional biases may be more likely to result in dominant and aggressive reactions in high T individuals. Therefore, high T individuals may be more likely to develop hostile attributional biases because of higher sensitivity to social threat and more likely to generate maladaptive and aggressive responses. For example, southern Americans were more quick to perceive slight and respond aggressively than northern Americans which was directly related to stronger increases in both cortisol and T in response to the perceived slights (Nisbett and Cohen, 1996). Furthermore, boys demonstrate stronger hostile attributional biases, more aggressive responsegeneration patterns, and greater confidence in aggressing and its consequences (Coie and Dodge, 1998). However, direct links between T and hostile attributional biases have not been studied.

7.3. Sociological effects of deviant peer group affiliation Sociologically, T is related to the motivation of achieving and maintaining a high social status with the specific strategy (prosocial vs. antisocial) being dependent on social reinforcement of behaviors that grant the desired social status (Eisenegger et al., 2009; Van Honk et al., 2011b). The aforementioned psychological processes which stem from mental models of the world as harsh and hostile can bias attention away from prosocial behaviors and towards more antisocial means to achieve and protect the status quo, whereas in environments where it is in one’s best interest to help others, T may induce fair bargaining behaviors to protect the status quo (Dabbs and Dabbs, 2000; Eisenegger et al., 2009; Van Honk et al., 2011b). Furthermore, repeated rejections by peers, authority figures (i.e., teachers), and abuse by parents is predictive of rebellion towards conventional social norms and values, and involvement and affiliation with other deviant peers (Dishion et al., 1991; Agnew and Brezina, 1997; Simons et al., 2001; Lochman et al., 2010) who reinforce shared activities such as aggressive and delinquent acts through mutual respect (Burgess and Akers, 1966; Patterson et al., 2000; Lochman et al., 2010).

Interestingly, Rowe et al. (2004) have found that T is related to antisocial behaviors only in boys with deviant peers, whereas it is related to leadership in boys with non-deviant peers, supporting the hypothesis that high T is associated with socially valued characteristics in prosocial environments. 7.4. Biological and psychological correlates of socioeconomic status Socioeconomic influences can also modulate the T-behavior pathway. Research has supported that T mainly relates to delinquency and antisocial behavior in the lower socioeconomic classes, whereas it shows no associations with antisocial behavior in the higher socioeconomic classes (Dabbs and Morris, 1990; Mazur, 1995; Arom¨aki et al., 1999). It has been suggested and supported that T is more strongly related to competitive achievement motivation and social dominance in the higher socio-economic classes (Dabbs and Morris, 1990). For example, T has been positively associated with socially desirable traits such as social dominance (Ehrenkranz et al., 1974; Christiansen and Knussmann, 1987; Lindman et al., 1987; Booth et al., 1989), leadership qualities (Rowe et al., 2004), fair bargaining behaviors (Eisenegger et al., 2009), social assertiveness (Lindman et al., 1987), and competitiveness (Booth et al., 1989), behaviors that are more likely to be observed in high T individuals from the higher socioeconomic classes. First off, socioeconomic variables can strongly impact on psychological processes. For example, different studies have found that lower socioeconomic status was related to a higher incidence of hostile attributional biases in children (Weiss et al., 1992; Schultz and Shaw, 2003). As an explanation, the authors assert that the higher levels of subjective stress and lower levels of support and resources experienced by parents in lower socioeconomic statuses can increase harsh or impatient caregiving thereby increasing the risk for hostility and anger in offspring (Schultz and Shaw, 2003). For example, socioeconomic status predicted maternal depression, which was directly related to biased social information-processing patterns and conduct problems in children (Schultz and Shaw, 2003). Second, socioeconomic status might also impact on the T-behavior pathway partly through biological consequences. First off, chronic social stress resulting from living in disadvantaged socioeconomic circumstances may deregulate the HPA-axis. For example, acute social stress, -challenge, and -competition has profound influences on the HPA-axis (Suay et al., 1999; Kudielka et al., 2007a, 2007b). Living in lower socio-economic statuses has been associated with deregulated post-waking HPA-axis activity in infancy (12–20 months old) (Saridjan et al., 2010), childhood (6–10 years old) (Lupien et al., 2000, 2001), adulthood (mean age of 37) (Cohen et al., 2006), and mid life (aged 45) (Li et al., 2007). Second, individuals in lower socioeconomic classes show a less pronounced prolactin response to a d-fenfluramine challenge indicating lower serotonergic responsivity (Matthews et al., 2000; Manuck et al., 2004). Finally, cumulative adversity and stressful life events more often experienced by individuals in the lower socioeconomic classes can alter orbitofrontal functionality (Ansell et al., 2012).

8. Theoretical model We have summarized the main findings of this review into a theoretical model which can serve as a template to generate new hypotheses that can be tested in future empirical research (see Fig. 1). The numbers within parentheses at the beginning of a sentence stand for the numbered circles in the model. In this model, T is depicted as interacting with other social and biological risk factors in the etiology of antisocial behavior. (1) High levels of fetal T prime the brain to react to circulating T later in life

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Fig. 1. Bio-socio-psychological model of the etiology of life course persistent antisocial behavior. The arrows originating from different input variables and leading into the numbered circles represent the input of these different moderating factors and the arrows originating from these circles signify the hypothesized outcome. Thicker lines represent stronger relationships. Since we do not yet know how the different factors are causally related and what the exact mechanisms may be that drive these interactions, these interactions are represented by empty white circles with only a number rather than the mechanism of action, which represents our lack of knowledge about these precise interactions.

with dampened orbitofrontal responsivity, reduced cortico-subcortical cross-talk, and increased mesolimbic dopaminergic reactivity to rewards. These neurobiological endophenotypes may then predispose towards dampened social sensitivity, reduced regulation of strong emotional and motivational activations, and heightened risk-taking. (2) However, other biological and socio-psychological factors strongly modulate the T-behavior pathway and may even determine whether this ‘‘hormonal profile’’ results in prosocial or antisocial behaviors. Concerning socio-biological development, insecure attachment relationships with caregivers and social rejection by peers (negative social experiences) may lead to chronically high levels of dysfunctional social stress (i.e., social distress4social eustress). High levels of prolonged social stress can result in; HPA-axis deregulation thereby modulating approach-withdrawal behaviors, oxytocinergic deregulation thereby impacting on basic social sensitivity, and serotonergic deregulation thereby decreasing healthy impulsecontrol. In addition, imbalances in neurochemical pathways brought about by high levels of chronic social stress can disturb healthy maturation of the prefrontal cortices, in particular during critical development phases such as the first three years of life. (3) However, serotonergic, HPA-axis, and oxytocinergic deregulations are likely to be the result of an interaction between these social risk factors and specific genetic predispositions (e.g., MAOA, 5HTT). (4) Concerning socio-psychological development, the link between T and antisocial behavior may also be mediated by social information-processing patterns that arise from accumulated social experiences. First off, when raised by abusive/neglectful caregivers, rejected by peers and teachers, and living in impoverished low SES environments, children may develop social information-processing patterns biased towards social threat hypersensitivity and a strong fight/flight response. We have argued that high T individuals are more likely to develop these hostile attributional biases because of the increased social threat sensitivity and more likely to react on them with a ‘‘fight’’ response such as aggressive dominance. Second, rejected youth are also at a greater risk to affiliate with deviant peers who reinforce shared activities such as delinquent and aggressive acts. Since T is strongly associated with achieving and maintaining a high social status, these youngsters learn to gain this status by perpetuating aggressive/ delinquent acts and maintain it through aggressive dominance. In short, individuals who have in addition to high T levels, also other biological and social risk factors, are at greatest risk for developing life-course persistent antisocial behavior and have more severe

antisocial behaviors during adolescence (hence the thick lines representing solid associations). (5) In addition, antisocial behaviors during the life-span are also likely to alienate others, cause further rejection and victimization, and lead to lead to many legal and social problems, thereby creating a vicious circle. (5) However, children with high T levels but who have had a healthy and enjoyable socio-emotional development (i.e., positive social experiences) and have no constitutional predisposition towards neurochemical dysfunctioning, have the lowest risk of developing life-course persistent antisocial behavior. These individuals may have difficulties in impulse-control during the identity forming years in adolescence, especially when not properly supervised by caregivers, but these behaviors are likely to wane in adulthood. (7) Low genetic load towards antisocial behavior coupled with balanced social stress (i.e., eustress 4distress) caused by positive social experiences may help to regulate serotonergic and HPA-axis functioning throughout life and serve as a strong protective factor against antisocial behavior. (8) Positive social experiences may also serve as a protective factor against antisocial behavior through protective psychological processes such as secure and trustworthy mental models of the world. Moreover, since T has been implicated in social functioning in general with other factors modulating its pathway to either antisocial or prosocial behavior, these positive social experiences in high T individuals can lead to desirable social characteristics such as leadership qualities, competitive achievement motivation, fair bargaining behaviors, and social assertiveness.

9. Future perspectives It is beyond the scope of this paper to describe detailed research designs but we will shortly introduce the different problems that need to be solved in order to better understand the interaction between T and behavior. First off, we want to know how fetal and circulating T co-influence neurobiology and ultimately behavior. Although we do find consistent associations between both fetal and circulating T and different behavioral traits, research regarding the underlying mechanisms is scarce. For example, we do know that T increases aggressive responding during certain circumstances and in certain environments, but we do not yet know which neurobiological events drive most of these

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associations. Of interest are T interactions with neuropeptide functioning (oxytocinergic and vasopressinergic circuitry), monoaminergic circuitry (norepinephrine, serotonin and dopamine), and endocrinological functioning (HPA-axis, estrogen, progesterone, SHBG) in the prediction of antisocial behavior and impulsivity. Additionally, important to know are T-induced changes in the reactivity and functionality of brain regions that are involved in behavior and emotions such as the different parts of the limbic system and ventromedial prefrontal cortex during decision making, response inhibition, aversive experience, fear-conditioning, and executive functioning. Studies like those of Mehta and Beer (2009), Van Wingen et al. (2010), and Van Honk et al. (2011a) are highly important to better understand how fetal and circulating T co-influence biology and behavior. Regarding psychological factors it would be useful to know whether T shows any interactions with social information processing, attachment, or peer-group affiliation in the prediction of antisocial behavior. Second, can socio-emotional experiences induce long-lasting changes in T levels? It is paramount to know whether different positive and negative social experiences, beyond winning and losing in competition, can induce both short-term and long lasting changes in circulating T levels? Longitudinal research in children that have been abused or have experienced trauma to see how the hormonal levels of these children are affected in the long-term. Another interesting approach is to measure how rejection, social discrimination, and living in low SES can influence T levels or the T-behavior relationship. These study designs would shed more light on the strength of influence T has on behavior and in how far it directly influences behavior or is being influenced itself by environmental, social, and psychological influences. Another question relevant in this context is whether there are personality differences in children that have different endocrinological reactions to the same sort of experiences. Some children may react with long-lasting increases in T levels (in reaction to feeling challenged) and externalizing pathology, while other children faced with the same experiences may react with a decrease in T-levels (in reaction to the feeling of being victimized and helpless) and internalizing pathology. In sum, different steps can be taken to improve our understanding of the stability of T effects throughout life, the reciprocity of T with social and psychological events, and our understanding of how T may interact with other biological and social processes to result in specific behavioral patterns.

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