Functional Network Connectivity Deviation Is Associated With Transdiagnostic Symptomatology: Brain Connectivity Links to Transdiagnostic Symptoms

Abstract

Background

Large comorbidity and heterogeneity within psychiatric populations have prompted the use of transdiagnostic methods to account for this variability in brain-phenotype associations. Normative modeling offers a way to map individual deviations in brain functioning with respect to a large reference population. This study aims to explore brain-phenotype associations, using normative modeling to compute individual deviation scores of brain functioning, and relating them to different levels of psychopathology in a naturalistic patient sample.

Methods

We applied normative modeling to estimate individual deviations in brain functional connectivity in a naturalistic sample (N = 309) comprising both patients and healthy control participants. We examined the association between the resulting neural deviation scores and levels of psychopathology, including traditional diagnostic categories, transdiagnostic symptom profiles, and cognition measures using sparse canonical correlation analysis.

Results

We successfully estimated normative models using data from the MIND-Set (Measuring Integrated Novel Dimensions in Neurodevelopmental and Stress-Related Mental Disorders) study and found significantly more extreme deviation scores in the patient as compared with the control population. We found a significant association (R_c = 0.16, R² = 2.56%, p = .021) between neural deviation scores and transdiagnostic symptom profiles, aligning with 4 Research Domain Criteria (RDoC) domains: negative valence, cognition, arousal/inhibition, and social systems.

Conclusions

With the use of normative modeling, we were able to detect differences in functional brain connectivity in patients compared with control participants, even in a highly heterogeneous and comorbid patient sample. Additionally, transdiagnostic approaches, such as those embodied in the RDoC framework, are more accurate in uncovering shared neurobiological mechanisms compared with traditional diagnostic categories or cognitive measures.