Resolving heterogeneity in obsessive-compulsive disorder through individualized differential structural covariance...

Area of Science:

• Neuroimaging
• Neuroscience
• Psychiatry

Background:

• Obsessive-compulsive disorder (OCD) exhibits high heterogeneity, complicating traditional neuroimaging biomarker discovery for precise diagnosis and treatment.
• Subject-level analysis is needed to address individual differences in OCD.

Purpose of the Study:

• To develop an individualized approach to identify neuroimaging biomarkers for obsessive-compulsive disorder (OCD).
• To uncover subject-level altered structural covariance networks in OCD patients.
• To classify OCD patients into subtypes based on their unique neuroimaging patterns.

Main Methods:

• Individualized differential structural covariance network (IDSCN) analysis was employed.
• Structural covariance edges were compared between 100 OCD patients and 106 healthy controls (HCs).
• Patients were clustered into subtypes based on subject-level differential edges.

Main Results:

• Two distinct neuroanatomical subtypes of OCD were identified.
• Subtype 1 showed distributed altered edges; Subtype 2 exhibited decreased default mode and motor network connectivity.
• Altered edges in Subtype 1 predicted symptom severity, unlike in Subtype 2.

Conclusions:

• Individualized structural covariance analysis reveals distinct OCD subtypes.
• Shared altered connections within the subcortical-cerebellum network are common in OCD.
• These subtypes provide a foundation for precision diagnosis and treatment strategies in OCD.