ساختار مغز در ارتباط با علائم افسردگی افکار خودکار پیش بینی شده در افراد سالم

Previous behavioral studies have examined the correlation between personality and depression, and between negative automatic thoughts and depression, respectively. Little is known, however, about the relationships among these three factors. Even less is known about how variations in brain structure are related to negative automatic thoughts, which are thought to mediate the association between personality traits and depressive symptoms. A total of 298 healthy participants underwent magnetic resonance imaging and completed the following questionnaires: a Neuroticism scale, the Automatic Thoughts Questionnaire (ATQ), and the Self-Rating Depression Scale (SDS). We first investigated the relationships among the three questionnaires and found that the ATQ was a mediator between the Neuroticism scale and the SDS. Then, we investigated the neuroanatomical correlates of the ATQ in the participants using voxel-based morphometry. We found that the ATQ was significantly positively correlated with the gray matter volume of the parahippocampal gyrus (PHG). Structural Equation Modeling revealed that negative automatic thoughts mediated the relationship between the GMV of the parahippocampal gyrus and depression. Moreover, the interaction between parahippocampal gyrus volume and neuroticism predicted automatic thoughts. These findings highlight that negative automatic thoughts might be a good predictor of depression outcome.

Virtually, all individuals will experience feeling blue or sad at some time in their lives, and some people will undergo a clinical or biobehavioral syndrome called major depressive disorder (MDD) (Fava and Kendler, 2000). Both the transient mood disturbance and the clinical disorder are described as depression. As we know, depression is a heterogeneous disorder with a highly variable course and no established etiological mechanism (Belmaker and Agam, 2008). In the United States, 2%–5% of the general population is affected by severe forms of depression, and up to 20% suffer from milder forms (Nestler et al., 2002). Therefore, much research attention has focused on identifying the risk factors for depression in otherwise healthy individuals. Cognitive processes play a pivotal role in the phenomenology, treatment, maintenance, and remission of depression, Cognitive dysfunction arises, at least in part, as a consequence of maladaptive thinking styles and negative self-statements (Beck, 1987, Alloy, 1988 and Abramson et al., 1989). For example, according to Beck's cognitive theory of depression, both cognitive content and processes involving pervasive, systematically negative distortions lead to various components of the clinical syndrome of depression (Beck, 1963, Beck, 1964 and Beck, 1967). Negative automatic thoughts occur following a stressful event as the consequence of one's information-processing bias; meanwhile, thoughts about failure in response to stress, in turn, contribute to depressive symptoms (Beck, 1983). Thus, based on a general overview of Beck's cognitive theory of depression, Allen (2003) proposed that negative thoughts are central to depression. The “hopelessness theory” also proposes that negative inferences about the self (particularly ideas about failure and worthlessness) are associated with increased depression (Abramson et al., 1989). In summary, persons with depression believe they are worthless, the world is unfair, and the future is hopeless, which Beck identifies as the “negative cognitive triad” (Beck, 1976). It is also well established that personality is related to depression (Klein et al., 1993, Clark et al., 1994 and Watson and Clark, 1995). Personality traits can predict the onset of depressive symptoms (Block et al., 1991) and depressive episodes (Kendler et al., 1993a). Neuroticism is a highly heritable (40–50%) and stable personality trait that reflects stress sensitivity and emotional instability, and it shares up to 50% of the genetic risk for major depression (Kendler et al., 1993b and Joffe et al., 2009). Interestingly, previous research has found that a high degree of neuroticism may facilitate the emergence of negative cognition (Leucht et al., 1997). That is, higher levels of neuroticism have been found to be strongly associated with depression and are powerful predictors of the onset of depression (Hayward et al., 2013 and Yoon et al., 2013). In fact, neuroticism in early adolescence serves as a distal indicator of vulnerability for depression, conferring a risk of negative automatic thoughts (Kercher et al., 2009). That is to say, negative automatic thoughts may play such an important role in this model that they fully mediate the effect of neuroticism on later depression. The above-reviewed findings, however, are based on behavioral studies of adolescents, and little is known about possible structural brain correlates of this important mediator in adults or the contribution of the brain to behavioral performance. The development of neuroimaging techniques during the past two decades has promoted a focus on alterations of the limbic system in mood disorders. Subtle changes in the hippocampus are associated with the pathophysiology of depression (Bremner et al., 2000, Videbech and Ravnkilde, 2004 and Cole et al., 2011). The parahippocampal gyrus and the hippocampus, structures that are strongly connected, constitute a considerable portion of the limbic system. The hippocampus traditionally has been associated with learning and memory processes (Bunsey and Eichenbaum, 1993 and Aguirre et al., 1996), especially emotionally salient memories (Engelien et al., 2000 and Burgess et al., 2001). Moreover, a growing body of evidence suggests that inter-individual variability in a wide range of human behaviors can be predicted from the structure of gray matter volume (GMV) measured with magnetic resonance imaging (MRI) (Kanai and Rees, 2011). Until now, however, the relationship between individual differences in negative automatic thoughts as mediators in this behavioral model and brain structure has been little studied. A study by Joffe et al. (2009) found that Val66Met carriers, compared with non-carriers, of brain-derived neurotrophic factor (BDNF) showed higher neuroticism, which, in turn, was associated with lower total GMV of the hippocampus and with depression. Moreover, compared with healthy controls or MDD patients, high-risk individuals who have first-degree family members with depression have been found to have a reduction in parahippocampal/hippocampal volume (de Geus et al., 2007, Baaré et al., 2010, Chen et al., 2010, Amico et al., 2011 and Carballedo et al., 2012), or greater GMV in the bilateral hippocampus (Romanczuk-Seiferth et al., 2014). In summary, we hypothesize that premorbid variations in brain structure may be important for the early detection and prevention of the disease in healthy volunteers (Forness et al., 2000). By analogy, individuals at high risk for psychosis can be distinguished from healthy controls, specifically on the basis of working memory performance (Smith et al., 2006 and Pflueger et al., 2007). For example, Ladouceur et al. (2008) reported that individuals with increased volume of the parahippocampal/hippocampal region have a high risk of developing bipolar disorder. Moreover, previous studies have shown correlations between depression severity and hippocampal volume (Vakili et al., 2000 and Saylam et al., 2006), although other studies have not replicated the correlation (Vythilingam et al., 2002, Frodl et al., 2004 and Frodl et al., 2006). Meta-analyses of depression research (Videbech and Ravnkilde, 2004, Campbell et al., 2004a, Campbell et al., 2004b, Lorenzetti et al., 2009 and Cole et al., 2011) have identified reduction in parahippocampal/hippocampal structure as the most replicated finding and a potential diagnostic neuro-biomarker for depression; however, more persistent forms of MDD, medication effects and gender tend to have an impact on hippocampal volume so that it is difficult to draw firm conclusions about the specificity of its relationship to the onset of depression. Therefore, drawing upon findings from neuroimaging studies with psychiatric samples, we proposed that individual differences in negative thoughts about oneself (i.e., the important mediator in this model) would be associated with parahippocampal/hippocampal volume in a healthy sample.

In conclusion, (1) our investigation of the relationship of personality, cognition, and depression found that automatic thoughts mediated the relationship between neuroticism and depression; (2) further exploration found that the automatic thoughts were positively correlated with individual differences in the volume of the parahippocampal gyrus; (3) negative automatic thoughts significantly mediated the relationship between the GMV of the parahippocampal gyrus and depression; (4) the interaction between parahippocampal gyrus volume and neuroticism could predict automatic thoughts. These findings indicated that negative automatic thoughts might be a good predictor for depression outcome. Further studies are needed to investigate the longitudinal relationships among automatic thoughts, personality traits, depressive disorders, and brain structure.