Identification of psychological features and development of an assessment tool for event-related psychological distress after experiencing non-traumatic stressful events.

Stressful events in daily life that are non-traumatic (e.g., family-, school-, work-, interpersonal-, and health-related problems) frequently cause various mood disturbances. For some people, being exposed to non-traumatic but stressful events could trigger the onset and relapse of mood disorders. Furthermore, non-traumatic stressful events also cause event-related psychological distress (ERPD), similar to that of post-traumatic stress disorder (PTSD; i.e., intense intrusive imagery or memory recall, avoidance, and hyperarousal) in the general population and individuals with mood disorders. However, previous ERPD studies only showed that people with ERPD display PTSD-like symptoms after non-traumatic experiences; they failed to get to the crux of the matter by only utilizing trauma- or PTSD-related assessment tools. We thus aimed to identify the psychological phenomena and features of ERPD after individuals experienced non-traumatic stressful events, and to develop and validate an appropriate ERPD assessment tool. First, we conducted a qualitative study to obtain the psychological features through interviews with 22 individuals (mean age = 41.50 years old, SD = 12.24) with major depressive disorder or bipolar disorder. Second, in the quantitative component, we implemented a web-based survey with 747 participants of the general population (mean age = 41.96 years old, SD = 12.64) by using ERPD-related questionnaires created based on the qualitative study; then, we examined the reliability and validity of the ERPD assessment tool. Results yielded that the psychological features of ERPD comprised four factors: feelings of revenge, rumination, self-denial, and mental paralysis. These were utilized in the developed 24-item measure of ERPD-a novel self-report assessment tool. For various professionals involved in mental healthcare, this tool can be used to clarify and assess psychological phenomena in people with ERPD.

Transition and Dynamic Reconfiguration of Whole-Brain Network in Major Depressive Disorder.

Major depressive disorder (MDD) has been characterized by abnormal brain activity and interactions across the whole-brain functional networks. However, the underlying alteration of brain dynamics remains unclear. Here, we aim to investigate in detail the temporal dynamics of brain activity for MDD, and to characterize the spatiotemporal specificity of whole-brain networks and transitions across them. We developed a hidden Markov model (HMM) analysis for resting-state functional magnetic resonance imaging (fMRI) from two independent cohorts with MDD. In particular, one cohort included 127 MDD patients and 117 gender- and age-matched healthy controls, and the other included 44 MDD patients and 33 controls. We identified brain states characterized by the engagement of distinct functional networks that recurred over time and assessed the dynamical configuration of whole-brain networks and the patterns of activation of states that characterized the MDD groups. Furthermore, we analyzed the community structure of transitions across states to investigate the specificity and abnormality of transitions for MDD. Based on our identification of 12 HMM states, we found that the temporal reconfiguration of states in MDD was associated with the high-order cognition network (DMN), subcortical network (SUB), and sensory and motor networks (SMN). Further, we found that the specific module of transitions was closely related to MDD, which were characterized by two HMM states with opposite activations in DMN, SMN, and subcortical areas. Notably, our results provide novel insights into the dynamical circuit configuration of whole-brain networks for MDD and suggest that brain dynamics should remain a prime target for further MDD research.

Comparison of Baseline Characteristics between Community-based and Hospital-based Suicidal Ideators and Its Implications for Tailoring Strategies for Suicide Prevention: Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior.

In this cross-sectional study, we aimed to identify distinguishing factors between populations with suicidal ideation recruited from hospitals and communities to make an efficient allocation of limited anti-suicidal resources according to group differences. We analyzed the baseline data from 120 individuals in a community-based cohort (CC) and 137 individuals in a hospital-based cohort (HC) with suicidal ideation obtained from the Korean Cohort for the Model Predicting a Suicide and Suicide-related Behavior (K-COMPASS) study. First, their sociodemographic factors, histories of medical and psychiatric illnesses, and suicidal behaviors were compared. Second, diagnosis by the Korean version of the Mini International Neuropsychiatric Interview, scores of psychometric scales were used to assess differences in clinical severity between the groups. The results revealed that the HC had more severe clinical features: more psychiatric diagnosis including current and recurrent major depressive episodes (odds ratio [OR], 4.054; P < 0.001 and OR, 11.432; P < 0.001, respectively), current suicide risk (OR, 4.817; P < 0.001), past manic episodes (OR, 9.500; P < 0.001), past hypomanic episodes (OR, 4.108; P = 0.008), current alcohol abuse (OR, 3.566; P = 0.020), and current mood disorder with psychotic features (OR, 20.342; P < 0.001) besides significantly higher scores in depression, anxiety, alcohol problems, impulsivity, and stress. By comparison, old age, single households, and low socioeconomic status were significantly associated with the CC. These findings indicate the necessity of more clinically oriented support for hospital visitors and more socioeconomic aid for community-dwellers with suicidality.

Effects of Antenatal Maternal Depressive Symptoms and Socio-Economic Status on Neonatal Brain Development are Modulated by Genetic Risk.

This study included 168 and 85 mother-infant dyads from Asian and United States of America cohorts to examine whether a genomic profile risk score for major depressive disorder (GPRSMDD) moderates the association between antenatal maternal depressive symptoms (or socio-economic status, SES) and fetal neurodevelopment, and to identify candidate biological processes underlying such association. Both cohorts showed a significant interaction between antenatal maternal depressive symptoms and infant GPRSMDD on the right amygdala volume. The Asian cohort also showed such interaction on the right hippocampal volume and shape, thickness of the orbitofrontal and ventromedial prefrontal cortex. Likewise, a significant interaction between SES and infant GPRSMDD was on the right amygdala and hippocampal volumes and shapes. After controlling for each other, the interaction effect of antenatal maternal depressive symptoms and GPRSMDD was mainly shown on the right amygdala, while the interaction effect of SES and GPRSMDD was mainly shown on the right hippocampus. Bioinformatic analyses suggested neurotransmitter/neurotrophic signaling, SNAp REceptor complex, and glutamate receptor activity as common biological processes underlying the influence of antenatal maternal depressive symptoms on fetal cortico-limbic development. These findings suggest gene-environment interdependence in the fetal development of brain regions implicated in cognitive-emotional function. Candidate biological mechanisms involve a range of brain region-specific signaling pathways that converge on common processes of synaptic development.

Assessment of abnormal brain structures and networks in major depressive disorder using morphometric and connectome analyses.

BACKGROUND: It is hypothesized that the phenomenology of major depressive disorder (MDD) is subserved by disturbances in the structure and function of brain circuits; however, findings of structural abnormalities using MRI have been inconsistent. Generalized q-sampling imaging (GQI) methodology provides an opportunity to assess the functional integrity of white matter tracts in implicated circuits. METHODS: The study population was comprised of 16 outpatients with MDD (mean age 44.81±2.2 years) and 30 age- and gender-matched healthy controls (mean age 45.03±1.88 years). We excluded participants with any other primary mental disorder, substance use disorder, or any neurological illnesses. We used T1-weighted 3D MRI with voxel-based morphometry (VBM) and vertex-wise shape analysis, and GQI with voxel-based statistical analysis (VBA), graph theoretical analysis (GTA) and network-based statistical (NBS) analysis to evaluate brain structure and connectivity abnormalities in MDD compared to healthy controls correlates with clinical measures of depressive symptom severity, Hamilton Depression Rating Scale 17-item (HAMD) and Hospital Anxiety and Depression Scale (HADS). RESULTS: Using VBM and vertex-wise shape analyses, we found significant volumetric decreases in the hippocampus and amygdala among subjects with MDD (p<0.001). Using GQI, we found decreases in diffusion anisotropy in the superior longitudinal fasciculus and increases in diffusion probability distribution in the frontal lobe among subjects with MDD (p<0.01). In GTA and NBS analyses, we found several disruptions in connectivity among subjects with MDD, particularly in the frontal lobes (p<0.05). In addition, structural alterations were correlated with depressive symptom severity (p<0.01). LIMITATIONS: Small sample size; the cross-sectional design did not allow us to observe treatment effects in the MDD participants. CONCLUSIONS: Our results provide further evidence indicating that MDD may be conceptualized as a brain disorder with abnormal circuit structure and connectivity.

Treatment decisions based on scalar and functional baseline covariates.

The amount and complexity of patient-level data being collected in randomized-controlled trials offer both opportunities and challenges for developing personalized rules for assigning treatment for a given disease or ailment. For example, trials examining treatments for major depressive disorder are not only collecting typical baseline data such as age, gender, or scores on various tests, but also data that measure the structure and function of the brain such as images from magnetic resonance imaging (MRI), functional MRI (fMRI), or electroencephalography (EEG). These latter types of data have an inherent structure and may be considered as functional data. We propose an approach that uses baseline covariates, both scalars and functions, to aid in the selection of an optimal treatment. In addition to providing information on which treatment should be selected for a new patient, the estimated regime has the potential to provide insight into the relationship between treatment response and the set of baseline covariates. Our approach can be viewed as an extension of "advantage learning" to include both scalar and functional covariates. We describe our method and how to implement it using existing software. Empirical performance of our method is evaluated with simulated data in a variety of settings and also applied to data arising from a study of patients with major depressive disorder from whom baseline scalar covariates as well as functional data from EEG are available.

Multilevel assessment of the neurobiological threat system in depressed adolescents: interplay between the limbic system and hypothalamic-pituitary-adrenal axis.

Integrative, multilevel approaches investigating neurobiological systems relevant to threat detection promise to advance understanding of the pathophysiology of major depressive disorder (MDD). In this study we considered key neuronal and hormonal systems in adolescents with MDD and healthy controls (HC). The goals of this study were to identify group differences and to examine the association of neuronal and hormonal systems. MDD and HC adolescents (N = 79) aged 12-19 years were enrolled. Key brain measures included amygdala volume and amygdala activation to an emotion face-viewing task. Key hormone measures included cortisol levels during a social stress task and during the brain scan. MDD and HC adolescents showed group differences on amygdala functioning and patterns of cortisol levels. Amygdala activation in response to emotional stimuli was positively associated with cortisol responses. In addition, amygdala volume was correlated with cortisol responses, but the pattern differed in depressed versus healthy adolescents, most notably for unmedicated MDD adolescents. The findings highlight the value of using multilevel assessment strategies to enhance understanding of pathophysiology of adolescent MDD, particularly regarding how closely related biological threat systems function together while undergoing significant developmental shifts.

Amplitude of low-frequency oscillations in first-episode, treatment-naive patients with major depressive disorder: a resting-state functional MRI study.

BACKGROUND: Resting-state fMRI is a novel approach to measure spontaneous brain activity in patients with major depressive disorder (MDD). Although most resting-state fMRI studies have focused on the examination of temporal correlations between low-frequency oscillations (LFOs), few studies have explored the amplitude of these LFOs in MDD. In this study, we applied the approaches of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF to examine the amplitude of LFOs in MDD. METHODOLOGY/PRINCIPAL FINDINGS: A total of 36 subjects, 18 first-episode, treatment-naive patients with MDD matched with 18 healthy controls (HCs) completed the fMRI scans. Compared with HCs, MDD patients showed increased ALFF in the right fusiform gyrus and the right anterior and posterior lobes of the cerebellum but decreased ALFF in the left inferior temporal gyrus, bilateral inferior parietal lobule, and right lingual gyrus. The fALFF in patients was significantly increased in the right precentral gyrus, right inferior temporal gyrus, bilateral fusiform gyrus, and bilateral anterior and posterior lobes of the cerebellum but was decreased in the left dorsolateral prefrontal cortex, bilateral medial orbitofrontal cortex, bilateral middle temporal gyrus, left inferior temporal gyrus, and right inferior parietal lobule. After taking gray matter (GM) volume as a covariate, the results still remained. CONCLUSIONS/SIGNIFICANCE: These findings indicate that MDD patients have altered LFO amplitude in a number of regions distributed over the frontal, temporal, parietal, and occipital cortices and the cerebellum. These aberrant regions may be related to the disturbances of multiple emotion- and cognition-related networks observed in MDD and the apparent heterogeneity in depressive symptom domains. Such brain functional alteration of MDD may contribute to further understanding of MDD-related network imbalances demonstrated in previous fMRI studies.

Systematic review of the neural basis of social cognition in patients with mood disorders.

BACKGROUND: This review integrates neuroimaging studies of 2 domains of social cognition--emotion comprehension and theory of mind (ToM)--in patients with major depressive disorder and bipolar disorder. The influence of key clinical and method variables on patterns of neural activation during social cognitive processing is also examined. METHODS: Studies were identified using PsycINFO and PubMed (January 1967 to May 2011). The search terms were "fMRI," "emotion comprehension," "emotion perception," "affect comprehension," "affect perception," "facial expression," "prosody," "theory of mind," "mentalizing" and "empathy" in combination with "major depressive disorder," "bipolar disorder," "major depression," "unipolar depression," "clinical depression" and "mania." RESULTS: Taken together, neuroimaging studies of social cognition in patients with mood disorders reveal enhanced activation in limbic and emotion-related structures and attenuated activity within frontal regions associated with emotion regulation and higher cognitive functions. These results reveal an overall lack of inhibition by higher-order cognitive structures on limbic and emotion-related structures during social cognitive processing in patients with mood disorders. Critically, key variables, including illness burden, symptom severity, comorbidity, medication status and cognitive load may moderate this pattern of neural activation. LIMITATIONS: Studies that did not include control tasks or a comparator group were included in this review. CONCLUSION: Further work is needed to examine the contribution of key moderator variables and to further elucidate the neural networks underlying altered social cognition in patients with mood disorders. The neural networks under lying higher-order social cognitive processes, including empathy, remain unexplored in patients with mood disorders.

Two-dimensional assessment of cytoarchitecture in the superior temporal white matter in schizophrenia, major depressive disorder and bipolar disorder.

Evidence from brain imaging studies indicates that white matter volume, density and fractional anisotropy may be altered in individuals with schizophrenia and bipolar disorder. However, the molecular correlates of these deficits remain unknown. In this study we performed a cytoarchitectural assessment of the white matter adjacent to the planum temporale (PT), an auditory association region located within the superior temporal gyrus, in subjects with schizophrenia, bipolar disorder, major depressive disorder and controls (15 subjects per group). Using two-dimensional measures, we recorded the cell density, distribution and size of all neurons and glial nuclei within this region. Glial density was lower in the schizophrenia group, relative to the control group. Neuronal density, neuronal size, and glial nuclear size did not differ between groups. No significant differences in neuronal clustering were observed in the patient groups. Further studies are required to examine whether the observed decrease in glial density within the superior temporal white matter in schizophrenia reflects a deficit in any individual glial cell population.

Anterior cingulate volumes in never-treated patients with major depressive disorder.

The anterior cingulate cortex (ACC) is implicated in the cognitive and affective abnormalities observed in mood disorders. Bilateral ACC volume reductions have been reported in patients with major depressive disorder (MDD) when compared to healthy controls. We compared regional brain volumes in the subgenual prefrontal cortex (SGPFC; Brodmann area (BA) 24(sg)), subcallosal gyrus (BA25), and paracingulate gyrus (BA32) in 65 patients receiving a first course of treatment for MDD and 93 healthy control subjects. Patients with more than three episodes of untreated MDD had smaller subcallosal gyrus volumes than healthy controls, while those with three or fewer past untreated episodes did not differ from controls. We also found preliminary evidence that medication-exposed patients had smaller SGPFC volumes than patients with no exposure to medication and healthy controls. There was no evidence that these effects related to mood state, duration of untreated illness, or to patient age. No differences were apparent in paracingulate gyrus volumes between patients and controls. These findings confirm the presence of ACC volume reductions in untreated patients with MDD and suggest that illness burden and short-term medication exposure mediate this change.

[Neuropsychological assessment of the prefrontal cortex in major depressive disorder]. / A prefrontális cortex neuropszichológiai vizsgálata major depresszív zavarban.

The pathology of the prefrontal cortex (PFC) may play an important role in the development of the symptoms of major depressive disorder. In this study, the authors used the Wisconsin Card Sorting Test (WCST) and the Iowa Gambling Test (IGT) to investigate PFC functions in depression. The WCST investigates cognitive set-shifting abilities, whereas the IGT is sensitive for the cumulative effect of reward and punishment on decision-making. Participants were 20 patients with DSM-IV major depressive disorder and 20 age-, gender-, and education-matched healthy control subjects. The depressed patients showed significant impairment in both tests, but the WCST and IGT scores did not correlate. There was no significant correlation between the test results and the severity of depressive and anxiety symptoms. Our results suggest a global impairment of the PFC in depression, which includes the dorsolateral and ventromedial regions.

Two-dimensional assessment of cytoarchitecture in the anterior cingulate cortex in major depressive disorder, bipolar disorder, and schizophrenia: evidence for decreased neuronal somal size and increased neuronal density.

BACKGROUND: Abnormalities of cortical neuronal organization and reductions in neuronal somal size have been reported in schizophrenia. The purpose of this investigation was to assess patterns of neuronal and glial distribution in the anterior cingulate cortex (ACC) in major depressive disorder (MDD), schizophrenia, bipolar disorder (BPD), and normal control subjects (15 subjects per group). METHODS: Estimates for neuronal somal and glial nuclear size and density were obtained. We employed two-dimensional morphometric analysis to examine the location of neurons and glia in a 1000-microm-wide strip of cortex. RESULTS: A decreased clustering of neurons was seen in BPD (p =.001). No other group differences were observed in the clustering of neurons, glia, or of neurons about glia. Neuronal somal size was reduced in layer 5 in schizophrenia (18%, p =.001), BPD (16%, p <.001), and MDD (9%, p =.01). Neuronal density was increased in layer 6 in BPD (63%, p =.004) and schizophrenia (61%, p =.006) and in layer 5 in MDD (24%, p =.018) and schizophrenia (33%, p =.003). CONCLUSIONS: The results of this study indicate that reduced neuronal somal size and increased neuronal density in cortical layers 5 and 6 of the ACC may be key features of schizophrenia, MDD, and BPD.