Altered Brain Wiring in Parkinson's Disease: A Structural Connectome-Based Analysis

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Abstract

Parkinson's disease (PD) is a neurodegenerative disorder that predominantly affects the motor system. Diffusion magnetic resonance imaging (MRI) has demonstrated deficits in anisotropy as well as increased diffusivity in the sub-cortical structures, primarily in the substantia nigra in PD. However, the clinical spectrum of PD is not limited to motor symptoms; rather, it encompasses several nonmotor symptoms such as depression, psychosis, olfactory dysfunction, and cognitive impairment. These nonmotor symptoms underscore PD as a complex neurological disorder arising from dysfunction of several network components. Therefore, to decipher the underlying neuropathology, it is crucial to employ novel network-based methods that can elucidate associations between specific network changes. This study aimed at assessing the large-scale structural network changes in PD. Structural connectomes were computed by using probabilistic fiber tracking on diffusion MRI between 86 regions of interest. Graph theoretic analysis on the connectome was carried out at several levels of granularity: global, local (nodal), lobar, and edge wise. Our findings demonstrate lower network clustering capability, overall lower neural connectivity, and significantly reduced nodal influence of the hippocampus in PD. In addition, extensive patterns of reduced connectivity were observed within and between the temporal, parietal, and occipital areas. In summary, our findings corroborate widespread structural disconnectivity that can be potentially linked to the nonmotor symptoms in PD.

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