آناتومی سطحی قشر مغز در کودکان مبتلا به اختلال اضطراب فراگیر

Background It is established that pediatric patients with generalized anxiety disorder (GAD) exhibit functional abnormalities and altered gray matter volumes in neural structures that subserve emotional processing, yet there are no data regarding the surface anatomy of the cerebral cortex in youth with GAD. Methods Using an automated surface-based approach (FreeSurfer), cortical thickness was assessed node-by-node over the entire cerebral cortex in adolescents with GAD and no co-occurring major depressive disorder (n = 13) and healthy subjects (n = 19). Results Compared with healthy adolescents, youth with GAD exhibited increased cortical thickness in the right inferolateral and ventromedial prefrontal cortex (i.e., inferior frontal gyrus), the left inferior and middle temporal cortex as well as the right lateral occipital cortex. No relationships were observed between cortical thickness and the severity of anxiety symptoms in the significant regions that were identified in the vertex-wise analysis. Conclusions These findings suggest that, in adolescents with GAD, abnormalities in cortical thickness are present in an ensemble of regions responsible for fear learning, fear extinction, reflective functioning (e.g., mentalization), and regulation of the amygdala.

Anxiety disorders are among the most common psychiatric conditions affecting children and adolescents (Beesdo, Pine, Lieb, & Wittchen, 2010) and are associated with an increased risk of suicidality (Foley et al., 2006 and Jacobson et al., 2008), and also increase the likelihood of other mood and anxiety disorders later in life (Beesdo-Baum, Pine, Lieb, & Wittchen, 2012). Of the anxiety disorders, generalized anxiety disorder (GAD) is among the most prevalent (Beesdo et al., 2010) in the pediatric population. However, only recently has the neuroanatomy of GAD been systematically evaluated. Functional neuroimaging studies of pediatric patients with GAD suggest dysfunction within the anterior limbic network, a collection of subcortical and cortical structures involved in the modulation and expression of complex affective states (Beesdo et al., 2009, McClure et al., 2007, Monk et al., 2006, Monk et al., 2008, Strawn et al., 2012a and Strawn et al., in press). Specifically, this research suggests hyperactivation of amygdala (Beesdo et al., 2009 and Monk et al., 2008) as well as ventrolateral prefrontal cortex (Beesdo et al., 2009, Guyer et al., 2008, McClure et al., 2007 and Strawn et al., 2012b) and ventromedial prefrontal cortex (Strawn, Bitter, et al., 2012) in addition to altered functional connectivity among these structures (McClure et al., 2007 and Strawn et al., 2012b). In parallel, neurostructural studies of the circuits that subserve emotional processing have identified abnormalities in structures within (De Bellis et al., 2000, De Bellis et al., 2002, Milham et al., 2005 and Mueller et al., 2013) and beyond the anterior limbic network (Strawn, Wehry, et al., 2013). For example, the superior temporal gyrus (STG), a region which is dense with afferent projections from the amygdala, was shown to have increased gray and white matter volumes in adolescents with anxiety disorders (De Bellis et al., 2002). Additionally, the amygdala, in some studies exhibits increased gray matter volumes (De Bellis et al., 2000 and Milham et al., 2005), while conflicting studies suggest reduced gray matter volumes (Mueller et al., 2013) in adolescents with GAD compared to healthy controls. Other areas in which gray matter volumes have been shown to be increased in youth with anxiety disorders include the right insula (Mueller et al., 2013) as well as the right precuneus, right precentral gyrus and orbitofrontal cortex (Strawn, Wehry, et al., 2013). Additionally, the right anterior hippocampus (Mueller et al., 2013), left orbitofrontal cortex, and posterior cingulate cortex (Strawn, Wehry, et al., 2013) have been shown to exhibit decreased gray matter volumes in anxious youth compared to healthy controls. Importantly, these voxel-based morphometry studies and “tracing” studies may reflect multiple changes in gray matter density, as well as cortical surface area and cortical folding, so interpretation can be problematic (Hutton, Draganski, Ashburner, & Weiskopf, 2009). Additionally, voxel-based morphometry measurements are highly dependent on the degree of smoothing (Jones, Symms, Cercignani, & Howard, 2005) as well as the templates which are used for normalization (Bookstein, 2001). As a solution to the inherent limitations of these voxel-based morphometry and “tracing” techniques that measure volume rather than thickness, surface-based cortical morphology analyses have been recently employed to evaluate cortical structure and may provide improved signal-to-noise ratios compared with voxel-based morphometry ( Kuhn, Schubert, & Galliant, 2010). However, it should be emphasized that these cortical thickness measures only permit evaluation of the cortical surface and thus do not allow analysis of “non-cortical” (e.g., subcortical) structures such as the amygdala, hippocampus, etc. Nonetheless, given that patterns of cortical thickness are regionally specific and determined early in development ( Fischl and Dale, 2000 and Rosas et al., 2002), an understanding of cortical thickness in pediatric patients with GAD could be helpful in understanding the neurostructural basis for the neurofunctional abnormalities observed in pediatric patients with GAD (for review see Strawn, Wehry, et al., 2012). In this study, we sought to examine differences in cortical thickness in youth with GAD and age- and sex-matched healthy control subjects and hypothesized that differences in cortical thickness would be observed in the ventromedial and ventrolateral prefrontal cortex consistent with functional abnormalities.

The cortical thickness findings described herein may relate to an array of factors, including neuronal density (la Fougère et al., 2011), microglial density (Peters & Sethares, 2002) or even vascular factors (Cardenas et al., 2012) and may also relate to learning and the frequency of specific cognitive functions which have been shown to influence thickness of subservient regions (Draganski et al., 2004 and Draganski et al., 2006). Thus, the regions in which we observed increased cortical thickness in this sample of adolescents with GAD may implicate dysfunction of early neurodevelopmental events such as abnormal migration of neurons within the cortex or decreased development-associated pruning of neurons within the cortical mantle. Finally, given that learning may influence cortical thickness, we cannot exclude the possibility—which is consistent with cognitive models of anxiety—that “fear learning” has alters cortical organization in these regions.