Multimodal MRI data fusion reveals distinct structural, functional and neurochemical correlates of depression in patients with Parkinson's disease.

Depression in Parkinson's disease (PD) involves complex structural, functional and multiple neurotransmitter systems alterations. So far, the precise interplay between structural and functional brain alterations and their underlying neurotransmitter processes remains largely unexplored. The advent of parallel independent component analysis (pICA) and the JuSpace toolbox provide a possible clue to elucidate their interrelationships and underlying mechanisms. In this study, we employed pICA to examine co-varying components interaction between gray matter volume (GMV) and fractional amplitude of low-frequency fluctuations (fALFF) in a cohort of 142 PD patients, comprising 53 PD patients with depression (PDD) and 89 PD patients without depression (PDND). Furthermore, we examined the spatial correlations between the GMV/fALFF components identified by pICA and neurotransmitter system maps using the JuSpace toolbox. Our analysis revealed significant negative correlations between one fMRI component (fALFF_IC6, frontoparietal, temporal and cerebellar regions) and two sMRI components (GMV_IC1 and GMV_IC4, basal ganglia, thalamocortical circuits, cerebellum and sensorimotor networks), which was significantly different between PDD and PDND group. Meanwhile, we found that alterations in both fALFF and GMV were widely associated with multiple neurotransmitter systems, primarily the dopaminergic and serotonergic systems. Notably, the severity of depression in PD was significantly correlated with these two distinct structural networks, independent of disease duration, motor symptoms and cognitive performance. These findings suggest the PD related depression-specific interrelationships between intrinsic network activity and GMV, potentially elucidating the multimodal neural circuitry and potential neurotransmitter patterns underlying depression in PD.