26 research outputs found
Neural correlates of anxious distress in depression:A neuroimaging study of reactivity to emotional faces and resting-state functional connectivity
Background: Comorbid anxiety disorders and anxious distress are highly prevalent in major depressive disorder (MDD). The presence of the DSM-5 anxious distress specifier (ADS) has been associated with worse treatment outcomes and chronic disease course. However, little is known about the neurobiological correlates of anxious distress in MDD. Methods: We probed the relation between the DSM-5 ADS and task-related reactivity to emotional faces, as well as resting-state functional connectivity patterns of intrinsic salience and basal ganglia networks in unmedicated MDD patients with (MDD/ADS+, N = 24) and without ADS (MDD/ADS−, N = 48) and healthy controls (HC, N = 59). Both categorical and dimensional measures of ADS were investigated. Results: MDD/ADS+ patients had higher left amygdala responses to emotional faces compared to MDD/ADS− patients (p =.015)—part of a larger striato-limbic cluster. MDD/ADS+ did not differ from MDD/ADS− or controls in resting-state functional connectivity of the salience or basal ganglia networks. Conclusions: Current findings suggest that amygdala and striato-limbic hyperactivity to emotional faces may be a neurobiological hallmark specific to MDD with anxious distress, relative to MDD without anxious distress. This may provide preliminary indications of the underlying mechanisms of anxious distress in depression, and underline the importance to account for heterogeneity in depression research
Distinguishing symptom dimensions of depression and anxiety: An integrative approach
AbstractBackgroundClark and Watson developed the tripartite model in which a symptom dimension of ‘negative affect’ covers common psychological distress that is typically seen in anxious and depressed patients. The ‘positive affect’ and ‘somatic arousal’ dimensions cover more specific symptoms. Although the model has met much support, it does not cover all relevant anxiety symptoms and its negative affect dimension is rather unspecific. Therefore, we aimed to extend the tripartite model in order to describe more specific symptom patterns with unidimensional measurement scales.Method1333 outpatients provided self report data. To develop an extended factor model, exploratory factor analysis (EFA) was conducted in one part of the data (n=578). Confirmatory factor analysis (CFA) was conducted in the second part (n=755), to assess model-fit and comparison with other models. Rasch analyses were done to investigate the unidimensionality of the factors.ResultsEFA resulted in a 6-factor model: feelings of worthlessness, fatigue, somatic arousal, anxious apprehension, phobic fear and tension. CFA in the second sample showed that a 6-factor model with a hierarchical common severity factor fits the data better than alternative 1- and 3-factor models. Rasch analyses showed that each of the factors and the total of factors can be regarded as unidimensional measurement scales.LimitationsThe model is based on a restricted symptom-pool: more dimensions are likely to exist.ConclusionThe extended tripartite model describes the clinical state of patients more specifically. This is relevant for both clinical practice and research
Working definitions, subjective and objective assessments and experimental paradigms in a study exploring social withdrawal in schizophrenia and Alzheimer's disease
Social withdrawal is one of the first and common signs of early social dysfunction in a number of important neuropsychiatric disorders, likely because of the enormous amount and complexity of brain processes required to initiate and maintain social relationships (Adolphs, 2009). The Psychiatric Ratings using Intermediate Stratified Markers (PRISM) project focusses on the shared and unique neurobiological basis of social withdrawal in schizophrenia, Alzheimer and depression. In this paper, we discuss the working definition of social withdrawal for this study and the selection of objective and subjective rating scales to assess social withdrawal chosen or adapted for this project. We also discuss the MRI and EEG paradigms selected to study the systems and neural circuitry thought to underlie social functioning and more particularly to be involved in social withdrawal in humans, such as the social perception and the social affiliation networks. A number of behavioral paradigms were selected to assess complementary aspects of social cognition. Also, a digital phenotyping method (a smartphone application) was chosen to obtain real-life data.This work was supported by the European Union Horizon 2020 Innovative Medicines Initiative 2 Joint Undertaking grant 115916 for the project ‘Psychiatric ratings using intermediate stratified markers
Structural brain correlates of childhood inhibited temperament: an ENIGMA-Anxiety Mega-analysis
NWORubicon 019.201SG.022Pathways through Adolescenc
Resting-State Functional Connectivity Characteristics of Resilience to Traumatic Stress in Dutch Police Officers
Background: Insights into the neurobiological basis of resilience can have important implications for the prevention and treatment of stress-related disorders, especially in populations that are subjected to high-stress environments. Evaluating large-scale resting-state networks (RSNs) can provide information regarding resilient specific brain function which may be useful in understanding resilience. This study aimed to explore functional connectivity patterns specific for (high) resilience in Dutch policemen after exposure to multiple work-related traumatic events. We investigated resting-state functional connectivity (RSFC) of the salience network (SN), limbic network, and the default-mode network (DMN). Methods: Resting-state functional MRI scans were obtained from trauma-exposed executive personnel of the Dutch police force and non-trauma-exposed recruits from the police academy. Participants were divided into three groups: a resilient group (n = 31; trauma exposure; no psychopathology), a vulnerable group (n = 32; trauma exposure, psychopathology), and a control group (n = 19; no trauma exposure, no psychopathology). RSFC of the three networks of interest was compared between these groups, using an independent component analysis and a dual regression approach. Results: We found decreased resilience-specific positive RSFC of the salience network with several prefrontal regions. The DMN and limbic network RFSC did not show resilience-specific patterns. Conclusion: This study shows a differential RSFC specific for resilient police officers. This differential RSFC may be related to a greater capacity for internal-focused thought and interoceptive awareness, allowing more effective higher-order responses to stress in highly resilient individuals
Intrinsic functional connectivity in families genetically enriched for social anxiety disorder – an endophenotype study
Background: Social anxiety disorder (SAD) is a serious psychiatric condition with a high prevalence, and a typical onset during childhood/adolescence. The condition runs in families, but it is largely unknown which neurobiological characteristics transfer this genetic vulnerability (‘endophenotypes’). Using data from the Leiden Family Lab study on SAD, including two generations of families genetically enriched for SAD, we investigated whether social anxiety (SA) co-segregated with changes in intrinsic functional connectivity (iFC), and examined heritability. Methods: Functional MRI data were acquired during resting-state in 109 individuals (56 males; mean age: 31·5, range 9·2-61·5 years). FSL's tool MELODIC was used to perform independent component analysis. Six networks of interest (default mode, dorsal attention, executive control, frontoparietal, limbic and salience) were identified at the group-level and used to generate subject-specific spatial maps. Voxel-wise regression models, with SA-level as predictor and voxel-wise iFC as candidate endophenotypes, were performed to investigate the association with SA, within masks of the networks of interest. Subsequently, heritability was estimated. Findings: SA co-segregated with iFC within the dorsal attention network (positive association in left middle frontal gyrus and right postcentral gyrus) and frontoparietal network (positive association within left middle temporal gyrus) (cluster-forming-threshold z>2·3, cluster-corrected extent-threshold p<0·05). Furthermore, iFC of multiple voxels within these clusters was at least moderately heritable. Interpretation: These findings provide initial evidence for increased iFC as candidate endophenotype of SAD, particularly within networks involved in attention. These changes might underlie attentional biases commonly present in SAD. Funding: Leiden University Research Profile ‘Health, Prevention and the Human Lifecycle’
PTSD symptom dynamics after the great east Japan earthquake : mapping the temporal structure using Dynamic Time Warping
Four-year course of quality of life and obsessive–compulsive disorder
Objective: Patients with obsessive compulsive disorder (OCD) have high disease burden. It is important to restore quality of life (QoL) in treatment, so that patients become able to live a fulfilling life. Little is known about the longitudinal course of QoL in patients with OCD, its association with remission from OCD, and about factors that contribute to an unfavourable course of QoL in remitting patients. Methods: Study on the 4-year course of QoL of patients with chronic (n = 144), intermittent (n = 22), and remitting OCD (n = 73) using longitudinal data of the Netherlands Obsessive Compulsive Disorder Association (NOCDA; complete data: n = 239; imputed data n = 382). The EuroQol five-dimensional questionnaire (EQ-5D) utility score was used to assess QoL. In patients with remitting OCD, we examined patient characteristics that contributed to an unfavourable course of QoL, including sociodemographics, OCD characteristics, psychiatric comorbidity, and personality traits. Results: Course of QoL was associated with course of OCD. QoL improved in those who remitted from OCD; however, even in these patients, QoL remained significantly below the population norms. The correlation between QoL and severity of OCD was only moderate: r = − 0.40 indicating that other factors besides OCD severity contribute to QoL. In remitters, more severe anxiety and depression symptoms were related to a lower QoL. Results were similar in complete and imputed data sets. Conclusions: Remission from OCD is associated with improvement of QoL, but comorbid anxiety and depression symptoms hamper the improvement of QoL. QoL could be improved by reducing OCD symptoms in patients with OCD and by treating comorbid anxiety and depression symptoms in remitting patients
PTSD Symptom dynamics after the great east japan earthquake: mapping the temporal structure using Dynamic Time Warping
Background: After the Great East Japan Earthquake [GEJE], approximately 70,000 Japan Ground Self Defense Force [JGSDF] personnel were deployed, risking Post-Traumatic Stress Disorder [PTSD]. The network approach to psychopathology suggests that symptoms may cause and exacerbate each other, resulting in the emergence and maintenance of disorders, including PTSD. It is therefore important to further explore the temporal interplay between symptoms. Most studies assessing the factor structure of the Impact of Event Scale-Revised [IES-R] have used cross-sectional designs. In this study, the structure of the IES-R was re-evaluated while incorporating the temporal interplay between symptoms. Methods: Using Dynamic Time Warping [DTW] the distances between PTSD symptoms on the IES-R were modelled in 1120 JGSDF personnel. Highly correlated symptoms were clustered at the group level using Distatis three-way principal component analyses of the distance matrices. The resulting clusters were compared to the original three subscales of the IES-R using a Confirmatory Factor Analysis (CFA). Results: The DTW analysis yielded four symptom clusters: Intrusion (five items), Hyperarousal (six items), Avoidance (six items), and Dissociation (five items). CFA yielded better fit estimates for this four-factor solution (RMSEA = 0.084, CFI = 0.918, TLI = 0.906), compared to the original three subscales of the IES-R (RMSEA = 0.103, CFI = 0.873, TLI = 0.858). Conclusions: DTW offers a new method of modelling the temporal relationships between symptoms. It yielded four IES-R symptom clusters, which may facilitate understanding of PTSD as a complex dynamic system