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    • The brain should also be

    2018-10-25

    The arginase inhibitors should also be expected to underlie differential susceptibility inasmuch as it is intrinsically and reciprocally interconnected with genotypic to phenotypic systems already empirically demonstrated to manifest susceptibility. Activation of the anterior cingulate cortex (ACC), for example, has been associated with genotypic variations in DRD2 (Pecina et al., 2013) and MAOA (Eisenberger et al., 2007), high skin conductance reactivity (Nagai et al., 2010), and negative emotionality/neuroticism (Haas et al., 2007). All of these are well-established susceptibility markers in contexts of social and affective processing. With the brain as the primary determinant of behavior, it stands to reason that it arbitrates and integrates between these different levels of analysis, which may demonstrate the operation of susceptibility in different domains of functioning and combine in cumulative and/or multiplicative ways. Expanding the range of neurobiological susceptibility factors examined would ultimately be useful for deriving comprehensive, multi-modal profiles regarding which adolescents are likely to experience which outcomes, to the benefit of predictive accuracy and prevention and intervention efforts. Even within a given level of analysis, established susceptibility factors may act on different underlying neurobiological circuits, resulting in a variety of neurobiological pathways through which susceptibility manifests to impact behavior (Hariri, 2009; Moore and Depue, in press). For example, the DRD2 and DRD4 genes encode types of dopamine receptors that are richly distributed in the striatum and other brain regions and that associate these regions with individual differences in attention and reward-sensitivity (Padmanabhan and Luna, 2014; Wise, 2004) and responses to aversive stimuli (Horvitz, 2000). As another example, the 158Met allele of the COMT gene is linked to increased working memory capacity and efficient prefrontal information processing (Tan et al., 2007). Because numerous complex, interactive pathways contribute to neural processing and, through the brain, to behavior, the brain may provide especially effective summary measures of susceptibility. With increasingly advanced methodologies, such as imaging genetics, this can be taken a step further by quantifying linkages from genotype to brain to outcome Indeed, any given reactivity pattern may encompass “many specific gene-environment-outcome pathways (or be characterized by domain specificity, where different individuals are susceptible for different reasons to different environmental influences for different outcomes)” (Moore and Depue, in press, p. 2). Finally, structural and functional brain indices may be sufficiently stable within and across developmental periods (Caceres et al., 2009; Fair et al., 2012; Forbes et al., 2009; Hariri, 2009; Johnstone et al., 2005; Manuck et al., 2007; Miller et al., 2002, 2009; Wu et al., 2014; Zuo et al., 2010) to warrant treatment as susceptibility factors. The test-retest reliability of fMRI measures is critical to establish in longitudinal developmental work to be able to separate what is stable vs. changing about neural response, such as due to development vs. noise. In adults, high test-retest reliability (e.g., intraclass correlation coefficients (ICCs)>.70) of amygdala response to emotional faces was found across multiple sessions conducted over days (Gee et al., 2015) and months (Johnstone et al., 2005), suggesting that individual differences in certain types of neural response are stable in adults (but see Sauder et al., 2013, for an example of poorer reliability in amygdala reactivity that is affected by stimulus type). Even more imperative for our framework is establishing the reliability of fMRI measures in adolescent samples. Test-retest reliability of the amygdala\'s response to aversive stimuli over three measurement occasions across six months showed low reliability (ICC<.40) in a sample of adolescents (N=22; ages 12–19 years) (van den Bulk et al., 2013). Nevertheless, Koolschijn et al. (2011) observed that, in contrast to children (N=10), adolescents (N=12) and adults (N=10) showed fair (ICCs=.41–.59) to good (ICCs=.60–.74) reliabilities for activations in a variety of brain regions (e.g., precuneus, ACC, insula, inferior and superior parietal cortices, angular gyrus) during a rule-switch task separated by ∼3.5 years. These values are comparable to the stability of other susceptibility factors (e.g., physiological measures; Cohen and Hamrick, 2003; Cohen et al., 2000), suggesting that brain indices may be sufficiently reliable to join the collection of established susceptibility markers.