Cross-diagnostic cognitive heterogeneity in body dysmorphic disorder and obsessive-compulsive disorder

Subtypes of cognitive impairment in cerebellar disease identified by cross-diagnostic cluster-analysis: results from a German multicenter study

BACKGROUND

Cognitive and neuropsychiatric impairment, known as cerebellar cognitive affective syndrome (CCAS), may be present in cerebellar disorders. This study identified distinct CCAS subtypes in cerebellar patients using cluster analysis.

METHODS

The German CCAS-Scale (G-CCAS-S), a brief screening test for CCAS, was assessed in 205 cerebellar patients and 200 healthy controls. K-means cluster analysis was applied to G-CCAS-S data to identify cognitive clusters in patients. Demographic and clinical variables were used to characterize the clusters. Multiple linear regression quantified their relative contribution to cognitive performance. The ability of the G-CCAS-S to correctly distinguish between patients and controls was compared across the clusters.

RESULTS

Two clusters explained the variance of cognitive performance in patients' best. Cluster 1 (30%) exhibited severe impairment. Cluster 2 (70%) displayed milder dysfunction and overlapped substantially with that of healthy controls. Cluster 1 patients were on average older, less educated, showed more severe ataxia and more extracerebellar involvement than cluster 2 patients. The cluster assignment predicted cognitive performance even after adjusting for all other covariates. The G-CCAS-S demonstrated good discriminative ability for cluster 1, but not for cluster 2.

CONCLUSIONS

The variance of cognitive impairment in cerebellar disorders is best explained by one severely affected and one mildly affected cluster. Cognitive performance is not only predicted by demographic/clinical characteristics, but also by cluster assignment itself. This indicates that factors that have not been captured in this study likely have effects on cognitive cerebellar functions. Moreover, the CCAS-S appears to have a relative weakness in identifying patients with only mild cognitive deficits.

STUDY REGISTRATION

The study has prospectively been registered at the German Clinical Study Register ( https://www.drks.de ; DRKS-ID: DRKS00016854).

A systematic review of visual processing in body dysmorphic disorder (BDD)

To understand the visual preponderance of perceived flaws in appearance in body dysmorphic disorder (BDD), the study of visual processing has been growing. Studies have focused on facial and other basic visual stimuli. The current literature does not provide evidence of consistent behavioural patterns, lacking an overarching body of work describing visual processing in BDD. This systematic review aims to characterise behavioural outcomes of visual processing anomalies and/or deficits in BDD. Articles were collected through online databases MEDLINE and PubMed, and were included if they comprised a clinical BDD group, and were published after 1990. Results indicate that individuals with BDD demonstrate deficits in emotional face processing, a possible overreliance on detail processing, aberrant eye-scanning behaviours, and a tendency to overvalue attractiveness. While findings consistently signal towards visual deficits in BDD, there is lack of clarity as to the type. This inconsistency may be attributed to heterogeneity within BDD samples and differences in experimental design (i.e., stimuli, tasks, conditions). There are difficulties distinguishing between BDD-associated deficits and those associated with OCD or eating disorders. A coherent framework, including sample characterisation and task design will seek to generate clear and consistent behavioural patterns to guide future treatments.

Mechanisms of cognitive behavioral therapy vs. supportive psychotherapy in body dysmorphic disorder: An exploratory mediation analysis

Body dysmorphic disorder (BDD) is common, severe, and often chronic. Cognitive behavioral therapy (CBT) is the first-line psychosocial treatment for BDD, with well-established efficacy. However, some patients do not improve with CBT, and little is known about how CBT confers its effects. Neurocognitive processes have been implicated in the etiology and maintenance of BDD and are targeted by CBT-BDD treatment components. Yet, the malleability of these factors in BDD, and their potential role in mediating symptom improvement, are not well understood. Understanding how treatment works could help optimize treatment outcomes. In this secondary data analysis of a randomized clinical trial of CBT vs. supportive psychotherapy (SPT) in BDD (n = 120), we examined whether treatment-related changes in detail processing (Rey-Osterrieth Complex Figure test), maladaptive appearance beliefs (Appearance Schemas Inventory-Revised), and emotion recognition (Emotion Recognition Task) mediated treatment outcome. All constructs improved over time and were associated with symptom improvement. CBT was associated with greater improvements in maladaptive beliefs than SPT. None of the variables examined mediated symptom improvement. Findings suggest that with successful treatment, individuals with BDD demonstrate reduced neurocognitive deficits (detail processing, emotion recognition, maladaptive beliefs) and that CBT is more likely than SPT to improve maladaptive appearance beliefs. More work is needed to understand mechanisms of change and thus maximize treatment outcomes.

Neurocognitive Artificial Neural Network Models Are Superior to Linear Models at Accounting for Dimensional Psychopathology

In recent years, there has been debate about the optimal conceptualisation of psychopathology. Structural models of psychopathology have been developed to counter issues, including comorbidity and poor diagnostic stability prevalent within the traditional nosological approach. Regardless of the conceptualisation of psychological dysfunction, deficits in neurocognitive abilities have been claimed to be an aetiological feature of psychopathology. Explorations of the association between neurocognition and psychopathology have typically taken a linear approach, overlooking the potential interactive dynamics of neurocognitive abilities. Previously, we proposed a multidimensional hypothesis, where within-person interactions between neurocognitive domains are fundamental to understanding the role of neurocognition within psychopathology. In this study, we used previously collected psychopathology data for 400 participants on psychopathological symptoms, substance use, and performance on eight neurocognitive tasks and compared the predictive accuracy of linear models to artificial neural network models. The artificial neural network models were significantly more accurate than the traditional linear models at predicting actual (a) lower-level and (b) high-level dimensional psychopathology. These results provide support for the multidimensional hypothesis: that the study of non-linear interactions and compensatory neurocognitive profiles are integral to understanding the functional associations between neurocognition and of psychopathology.