Specific patterns of endogenous functional connectivity are associated with harm avoidance in OCD.

BACKGROUND

Individuals with OCD show persistent-avoidance behaviors, often in the absence of actual threat. Quality-of-life costs and heterogeneity support the need for novel brain-behavior intervention targets. Informed by mechanistic and anatomic studies of persistent-avoidance in rodents and non-human primates, our goal was to test whether connections within a hypothesized persistent-avoidance related network predicted OCD-related harm-avoidance (HA), a trait measure of persistent-avoidance. We hypothesized that 1)HA, not OCD diagnosis, would be associated with altered endogenous connectivity in at least one connection in the network; 2)HA-specific findings would be robust to comorbid symptoms; and 3)reliable findings would replicate in an holdout testing subsample.

METHODS

Using resting-state fcMRI, cross-validated elastic-net for feature selection and Poisson generalized linear models, we tested which connections significantly predicted HA in our training subsample(n=73;71.8% Female;nHC=36,nOCD=37); robustness to comorbidities; and replicability in a testing subsample(n=30;56.7% Female;nHC=15,nOCD=15).

RESULTS

Stronger inverse connectivity between right dorsal anterior cingulate and right basolateral-amygdala (R_dACC-R_BLA) and stronger positive connectivity between right ventral anterior insula and left ventral-striatum (R_vaIns-L_VS) were associated with greater HA across groups. Network connections did not discriminate OCD diagnosis or predict HA-correlated traits, suggesting sensitivity to trait HA. The dACC-BLA relationship was robust to controlling for comorbidities and medication in individuals with OCD and was also predictive of HA in our testing subsample.

CONCLUSION

Stronger inverse dACC-BLA connectivity was robustly and reliably associated with HA across groups and in OCD. Results support the relevance of a cross-species persistent-avoidance-related network to OCD, with implications for precision-based approaches and treatment.

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.