Transdiagnostic phenotypes of compulsive behavior and associations with psychological, cognitive, and neurobiological affective processing

Linden Parkes,Chao Suo,Rebecca Segrave,Samuel R Chamberlain,Lauren Den Ouden,Jeggan Tiego,Karyn Richardson,Lucy Albertella,Lisa-Marie Greenwood,Rico S C Lee,Murat Yücel,Leonardo F Fontenelle

doi:10.1038/s41398-021-01773-1

Abstract

Compulsivity is a poorly understood transdiagnostic construct thought to underlie multiple disorders, including obsessive-compulsive disorder, addictions, and binge eating. Our current understanding of the causes of compulsive behavior remains primarily based on investigations into specific diagnostic categories or findings relying on one or two laboratory measures to explain complex phenotypic variance. This proof-of-concept study drew on a heterogeneous sample of community-based individuals (N = 45; 18–45 years; 25 female) exhibiting compulsive behavioral patterns in alcohol use, eating, cleaning, checking, or symmetry. Data-driven statistical modeling of multidimensional markers was utilized to identify homogeneous subtypes that were independent of traditional clinical phenomenology. Markers were based on well-defined measures of affective processing and included psychological assessment of compulsivity, behavioral avoidance, and stress, neurocognitive assessment of reward vs. punishment learning, and biological assessment of the cortisol awakening response. The neurobiological validity of the subtypes was assessed using functional magnetic resonance imaging. Statistical modeling identified three stable, distinct subtypes of compulsivity and affective processing, which we labeled “Compulsive Non-Avoidant”, “Compulsive Reactive” and “Compulsive Stressed”. They differed meaningfully on validation measures of mood, intolerance of uncertainty, and urgency. Most importantly, subtypes captured neurobiological variance on amygdala-based resting-state functional connectivity, suggesting they were valid representations of underlying neurobiology and highlighting the relevance of emotion-related brain networks in compulsive behavior. Although independent larger samples are needed to confirm the stability of subtypes, these data offer an integrated understanding of how different systems may interact in compulsive behavior and provide new considerations for guiding tailored intervention decisions.

Highlights

Traditional classification systems, such as the Diagnostic and Statistical Manual (DSM) and International Classification of Diseases (ICD), remain the primary means for classifying psychopathology
Comprising a range of traditional labels, subtypes identified were independent of behavioral domains and were instead based on the current understanding of shared intermediate affective processes underpinning compulsivity
Each subtype included all types of behavior demonstrating transdiagnostic expression and exhibited unique profiles across psychological, cognitive, and neurobiological indicators

Summary

Introduction

Traditional classification systems, such as the Diagnostic and Statistical Manual (DSM) and International Classification of Diseases (ICD), remain the primary means for classifying psychopathology. There is mounting evidence that diagnostic categories do not capture the natural organization of psychopathology symptoms, impeding identification of underlying neurobiological substrates [1,2,3,4,5]. This has led to calls for empirically-based approaches to study psychiatric nosology that will foster the neuroscientific discovery of pathogenic mechanisms across multiple levels of analysis [i.e., symptom, cognitive, neurobiological, [6,7,8,9]]. Previous work has shown that intermediate phenotypes track variation in clinical symptoms across multiple disorders [3], and can be mapped onto

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Conclusion