Resolving Heterogeneity in Posttraumatic Stress Disorder Using Individualized Structural Covariance Network Analysis

The heterogeneity of posttraumatic stress disorder (PTSD) is an obstacle to both understanding and therapy, and this has prompted a search for internally homogeneous neuroradiological subgroups within the broad clinical diagnosis. We set out to do this using the individual differential structural covariance network (IDSCN). We constructed cortical thickness-based IDSCN using T1-weighted images of 89 individuals with PTSD (mean age 42.8 years, 60 female) and 89 demographically matched trauma-exposed non-PTSD (TENP) controls (mean age 43.1 years, 63 female). The IDSCN metric quantifies how the structural covariance edges in a patient differ from those in the controls. We examined the structural diversity of PTSD and variation among subtypes using a hierarchical clustering analysis. PTSD patients exhibited notable diversity in distinct structural covariance edges but mainly affecting three networks: default mode, ventral attention, and sensorimotor. These changes predicted individual PTSD symptom severity. We identified two neuroanatomical subtypes: the one with higher PTSD symptom severity showed lower structural covariance edges in the frontal cortex and between frontal, parietal, and occipital cortex-regions that are functionally implicated in selective attention, response selection, and learning tasks. Thus, deviations in structural covariance in large-scale networks are common in PTSD but fall into two subtypes. This work sheds light on the neurobiological mechanisms underlying the clinical heterogeneity and may aid in personalized diagnosis and therapeutic interventions.