Large-Scale Structural Network Change Correlates With Clinical Response to rTMS in Depression

SOURCE: Neuropsychopharmacology. 47(5):1096-1105, 2022 Apr.

AUTHORS: Nestor SM; Mir-Moghtadaei A; Vila-Rodriguez F; Giacobbe P; Daskalakis ZJ; Blumberger DM; Downar J

ABSTRACT: Response to repetitive transcranial magnetic stimulation (rTMS) among
individuals with major depressive disorder (MDD) varies widely. The neural mechanisms underlying rTMS are thought to involve changes in large-scale networks. Whether structural network integrity and plasticity are associated with response to rTMS therapy is unclear. Structural MRIs were acquired from a series of 70 adult healthy controls and 268 persons with MDD who participated in two arms of a large randomized, non-inferiority trial, THREE-D, comparing intermittent theta-burst stimulation to high-frequency rTMS of the left dorsolateral prefrontal cortex (DLPFC). Patients were grouped according to percentage improvement on the 17-item Hamilton Depression Rating Score at treatment completion. For the entire
sample and then for each treatment arm, multivariate analyses were used to characterize structural covariance networks (SCN) from cortical gray matter thickness, volume, and surface area maps from T1-weighted MRI. The association between SCNs and clinical improvement was assessed. For both study arms, cortical thickness and volume SCNs distinguished healthy controls from MDD (p = 0.005); however, post-hoc analyses did not reveal a significant association between pre-treatment SCN expression and clinical improvement. We also isolated an anticorrelated SCN between the left DLPFC rTMS target site and the subgenual anterior cingulate cortex across cortical measures (p = 0.0004). Post-treatment change in cortical thickness SCN architecture was associated with clinical improvement in treatment responders (p = 0.001), but not in non-responders. Structural network changes may underpin clinical response to rTMS, and SCNs are
useful for understanding the pathophysiology of depression and neural mechanisms of plasticity and response to circuit-based treatments.