Cortical Volumetric Correlates of Childhood Trauma, Anxiety, and Impulsivity in Bipolar Disorder

Song, Hyehyun; Chon, Myong-Wuk; Ryu, Vin; Yu, Rina; Lee, Dong-Kyun; Lee, Hyeongrae; Lee, Wonhye; Lee, Jung Hyun; Park, Dong Yeon

doi:10.30773/pi.2019.0305

Cited by 11 publications

(4 citation statements)

References 66 publications

(131 reference statements)

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“…Specifically, BD patients with CAs were compared with other patients without a history of CAs (Janiri et al ., 2017) or with HC (Janiri et al ., 2019) or divided into two groups according to specific genetic vulnerabilities (Aas et al ., 2013, 2014). Other structural studies investigating the possible GM correlates of CAs in BD patients showed volume reductions in the thalamus (Duarte et al ., 2016; Poletti et al ., 2016), alterations in the amygdala (Souza-Queiroz et al ., 2016; Janiri et al ., 2017) and in several frontal regions including the pre-frontal, orbito-frontal, para-central cortices and the middle-frontal gyrus (Duarte et al ., 2016; Poletti et al ., 2016; Song et al ., 2020; Begemann et al ., 2021). As shown in Table 1, these alterations seem to indicate that BD patients with a history of CAs are characterised by volume reductions in all these regions when compared with HC or similar group without a history of CAs.…”

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confidence: 99%

Childhood adversities and bipolar disorder: a neuroimaging focus

Zovetti

Perlini

Brambilla

2022

Epidemiol Psychiatr Sci

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Early-life adverse events or childhood adversities (CAs) are stressors and harmful experiences severely impacting on a child's wellbeing and development. Examples of CAs include parental neglect, emotional and physical abuse and bullying. Even though the prevalence of CAs and their psychological effects in both healthy and psychiatric populations is established, only a paucity of studies have investigated the neurobiological firms associated with CAs in bipolar disorder (BD). In particular, the exact neural mechanisms and trajectories of biopsychosocial models integrating both environmental and genetic effects are still debated. Considering the potential impact of CAs on BD, including its clinical manifestations, we reviewed existing literature discussing the association between CAs and brain alterations in BD patients. Results showed that CAs are associated with volume alterations of several grey matter regions including the hippocampus, thalamus, amygdala and frontal cortex. A handful of studies suggest the presence of alterations in the corpus callosum and the pre-fronto-limbic connectivity at rest. Alterations in these regions of the brain of patients with BD are possibly due to the effect of stress produced by CAs, being hippocampus part of the hypothalamus–pituitary–adrenal axis and thalamus together with amygdala filtering sensory information and regulating emotional responses. However, results are mixed possibly due to the heterogeneity of methods and study design. Future neuroimaging studies disentangling between different types of CAs or differentiating between BD sub-types are needed in order to understand the link between CAs and BD.

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confidence: 99%

Childhood adversities and bipolar disorder: a neuroimaging focus

Zovetti

Perlini

Brambilla

2022

Epidemiol Psychiatr Sci

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“…Indeed, recent studies on the impact of anxiety symptoms in bipolar disorder demonstrated unfavorable outcomes or a worse prognosis (Lorenzo-Luaces et al, 2018;Spoorthy et al, 2019;Kim et al, 2021). For instance, a significant association between anxiety symptoms and gray matter volume deficits in the left middle frontal lobe was presented, which implies neural evidence of the anxiety symptoms in BD (Song et al, 2020). Furthermore, there were predictors whose associations with cognitive domains are minimal, such as age of onset, depression severity, past mood disorder history, and impulsiveness.…”

Section: Discussionmentioning

confidence: 95%

Cognitive profiles in bipolar I disorder and associated risk factors: Using Wechsler adult intelligence scale—IV

Park²,

Shin

et al. 2022

Front. Psychol.

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BackgroundDespite the growing evidence of cognitive impairments in bipolar disorder (BD), little work has evaluated cognitive performances utilizing the latest version of the Wechsler Intelligence Scale-IV (WAIS-IV), which is one of the most widely used neurocognitive assessments in clinical settings. Furthermore, clinical characteristics or demographic features that negatively affect the cognitive functioning of BD were not systematically compared or evaluated. Accordingly, the present study aimed to examine the cognitive profile of bipolar I disorder (BD-I) patients and associated risk factors.MethodsParticipants included 45 patients, diagnosed with BD-I, current or most recent episode manic, and matching 46 healthy controls (HC). Cognitive performance was evaluated via WAIS-IV, and clinical characteristics of the BD-I group were examined via multiple self- and clinician-report questionnaires.ResultsMultivariate analysis of covariance (MANCOVA) results indicated that the BD-I group demonstrated significantly poorer performance compared to the HC group in subtests and indexes that reflect working memory and processing speed abilities. Redundancy analysis revealed that overall symptom severity, manic symptom severity, and anxiety were significant predictors of cognitive performance in BD-I, while age of onset, past mood disorder history, depression severity, and impulsiveness showed comparatively smaller predictive values.ConclusionThe current study suggests cognitive deterioration in the cognitive proficiency area while generalized ability, including verbal comprehension and most of the perceptual reasoning skills, remain intact in BD-I. The identified risk factors of cognitive performance provide specific clinical recommendations for intervention and clinical decision-making.

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“…When controlling for TIV, significant relationships appear that were not previously significant and those that were already present when TIV was not taken into account are maintained. Previous studies have also found differences in the statistical power of the relationships between personality traits and GMV depending on the control variables used [ 74 , 77 , 78 ]. The point that when not controlling for TIV our results show a reduction in the number of structures that are related to personality traits may be due to the fact that these relationships appear but cannot be observed because they are masked by a TIV that is not being taken into account.…”

Section: Discussionmentioning

confidence: 99%

Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers

Mas-Cuesta

Baltruschat

Cândido

et al. 2022

Behavioural Neurology

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Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.

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Cortical Volumetric Correlates of Childhood Trauma, Anxiety, and Impulsivity in Bipolar Disorder

Cited by 11 publications

References 66 publications

Childhood adversities and bipolar disorder: a neuroimaging focus

Childhood adversities and bipolar disorder: a neuroimaging focus

Cognitive profiles in bipolar I disorder and associated risk factors: Using Wechsler adult intelligence scale—IV

Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers

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