An Increase of the Character Function of Self-Directedness Is Centrally Involved in Symptom Reduction during Remission from Major Depression

Background. Studies with the Temperament and Character Inventory (TCI) in depressive disorders have shown changes (Δ) of the character of Self-Directedness (SD) and the temperament of Harm Avoidance (HA). The central question of this study is which of these two changes is most proximally related to the production of depressive symptoms. Methods. The start and endpoint data from a two-year followup of 58 depressed patients were reanalyzed. We used the ΔHA and ΔSD scores as well as the Δ scores on three dimensions of psychopathology, called Emotional Dysregulation (ED), Retardation (RET), and Anxiety (ANX). The presence of the main relation between personality and psychopathology was tested in all patients and in four subcategories. The data were analyzed by MANCOVA and Structural Equation Modelling (SEM). Results. ΔHA and ΔSD correlated negatively, and only ΔSD was related (negatively) to ΔED. This pattern was found in all subcategories. SEM showed ΔHA and ΔSD had an ambiguous causal interrelationship, while ΔSD, ΔRET, and ΔANX had unidirectional effects on ΔED. Conclusion. The results correspond with a central pathogenetic role for a state-related deficit at the character level in depression. This may have important consequences for investigations of endophenotypes and clinical treatment

A Network View on Psychiatric Disorders: Network Clusters of Symptoms as Elementary Syndromes of Psychopathology

<div><p>Introduction</p><p>The vast number of psychopathological syndromes that can be observed in clinical practice can be described in terms of a limited number of elementary syndromes that are differentially expressed. Previous attempts to identify elementary syndromes have shown limitations that have slowed progress in the taxonomy of psychiatric disorders.</p><p>Aim</p><p>To examine the ability of network community detection (NCD) to identify elementary syndromes of psychopathology and move beyond the limitations of current classification methods in psychiatry.</p><p>Methods</p><p>192 patients with unselected mental disorders were tested on the Comprehensive Psychopathological Rating Scale (CPRS). Principal component analysis (PCA) was performed on the bootstrapped correlation matrix of symptom scores to extract the principal component structure (PCS). An undirected and weighted network graph was constructed from the same matrix. Network community structure (NCS) was optimized using a previously published technique.</p><p>Results</p><p>In the optimal network structure, network clusters showed a 89% match with principal components of psychopathology. Some 6 network clusters were found, including "DEPRESSION", "MANIA", “ANXIETY”, "PSYCHOSIS", "RETARDATION", and "BEHAVIORAL DISORGANIZATION". Network metrics were used to quantify the continuities between the elementary syndromes.</p><p>Conclusion</p><p>We present the first comprehensive network graph of psychopathology that is free from the biases of previous classifications: a ‘Psychopathology Web’. Clusters within this network represent elementary syndromes that are connected via a limited number of bridge symptoms. Many problems of previous classifications can be overcome by using a network approach to psychopathology.</p></div

Network metrics of individual symptoms of the Psychopathology Web.

<p>Item: item of the CPRS. Cluster: name of the network cluster to which the symptom belongs (one of 6 network clusters identified in the CPRS dataset). Bridge or core: specifies whether the symptom is a bridge symptom or a core symptom. Ext. clust.: number of external clusters that the (bridge) symptom connects with. Ln_w_D: logtransformed and weighted degree. Ln_w_BS: logtransformed and weighted betweenness centrality. Ln_w_CS: logtransformed and weighted closeness centrality.</p><p>Network metrics of individual symptoms of the Psychopathology Web.</p

Table showing the quantitative results of the cluster-to-component matching procedure.

<p>Table shows the network community structures (NCS) that were most similar to the confirmatory 5, 6, 7, 8, 9, and 10 principal component structure (PCS) of the CPRS dataset. Component structure: the component structure that was matched against the candidate network community structures obtained from the incremental pruning procedure (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112734#s2" target="_blank">Materials and Methods</a>). Principal Component: the number of the principal component from this component structure. % mismatch per cluster: the percentage of items in a network cluster of the most similar NCS that did not match the item content of its corresponding principal component. % overall mismatch: the percentage of items in the entire NCS that did not match its corresponding PCS. ABS(r): the absolute value of the correlation coefficient at which the optimal match with a NCS was found. p: the corresponding p value. Nrnodes: number of nodes left in the NCS at this threshold (some nodes dropped off the network due to incremental pruning, see text).</p><p>Table showing the quantitative results of the cluster-to-component matching procedure.</p

The Psychopathology Web.

<p>Network graph of the correlational relationships between 55 items (symptoms) of the CPRS, which form a 6-cluster structure. Node  =  CPRS item (symptom), link  =  significant correlation. The threshold for the significance of network links has been optimized using the procedure described above. Red links: positive correlations. Blue links: negative correlations. The thickness of the links reflects the strength of their corresponding correlation coefficient (weight). It01 etc: item number of the CPRS. Nodes are positioned according to the Hagel-Koren Fast Multiscale layout algorithm. The color of the nodes shows their network cluster membership. Yellow: ANXIETY, Light Blue: DEPRESSION. Orange: MANIA, Green: PSYCHOSIS, Grey: RETARDATION, Brown: BEHAVIORAL DISORGANIZATION. NCD and PCA differ with respect to the placement of items 03, 04, 25, 27, and 28. These mismatches occur at the boundaries between the DEPRESSION cluster and the PSYCHOSIS cluster, and between the DEPRESSION cluster and the ANXIETY cluster and can be interpreted as ‘border disputes’ between NCD and PCA. Spheres: bridge symptoms. Closed diamonds: core symptoms. Node size denotes betweenness centrality score of the node (a measure of its involvement in connecting the various parts of the Psychopathology Web through shortest paths). Smaller and larger loops can be observed that run within and between the various network clusters. See text for further details.</p

Scree-plot (A) and pruning plot (B) of the CPRS dataset.

<p>A. Scree-plot of the exploratory principal component analysis of the CPRS dataset, suggesting a 10-component structure. Defining a cut-off for the total number of components to extract was complicated by the lack of a clear bend in the plot. Hence, 5 additional alternative component structures were matched to the total array of possible network community structures of the dataset, to allow identification of an optimal solution. B. Incremental pruning plot of network community structure analyses showing the number of clusters in the Psychopathology Web as a function of the correlation coefficient that defines the threshold for significance of the links in the network. Neighborless nodes (isolates) are removed from the calculation and do not count as clusters.</p

Results of optimizing the network community structure of the CPRS dataset with respect to its principal component structure.

<p>Results of the NCS-to-PCS matching procedure for 6 different components structures of the CPRS dataset. X-axis shows the correlation coefficient r as a threshold for significance of a link in the network graph (as r increases to the right, more links are pruned from the network). Y-axis shows dissimilarity (mismatch) scores. Dark blue: 5-PCS, dark red: 6-PCS, green: 7-PCS, purple: 8-PCS, turquoise: 9-PCS, orange: 10-PCS. Mismatch scores collapse at r = 0.27 (p = 1.67E-04), indicating an optimal threshold for the Psychopathology Web and a corresponding six-cluster solution. For details, see text and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112734#pone-0112734-t001" target="_blank">Tables 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112734#pone-0112734-t002" target="_blank">2</a>.</p

Table comparing the component memberships and network cluster memberships of items of the CPRS for the optimal 6-network cluster structure and corresponding 6-component structure.

<p>It01 etc: item 1 of the CPRS. Left: matching template of the 6-component structure consisting of 55 nodes. Items were assigned to a single component using a forced-choice filter based on the highest component loadings. Right: the 6-cluster network structure showing an optimal match with the matching template. 1 =  member of this component or cluster, blank  =  not a member. Items that dropped off the network during the incremental pruning procedure or that were discarded from further analyses (it35 and it55, no scores) are shown in [brackets]. Items that were allocated differently by PCA and NCD are shown in <b>bold.</b> See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112734#pone-0112734-g003" target="_blank">Figure 3</a>.</p><p>Table comparing the component memberships and network cluster memberships of items of the CPRS for the optimal 6-network cluster structure and corresponding 6-component structure.</p