Progression of Parkinson's disease: a longitudinal MRI study of functional brain connectome in a large cohort of patients

Objective: To investigate functional neural pathway organization and changes over-time in patients with Parkinson’s disease (PD) using advanced network-based techniques. Background: Graph theoretical analyses and network science are powerful tools to study functional organization of the brain. Design/Methods: 146 PD patients performed clinical and cognitive evaluations and resting-state functional MRI at baseline and every year for 4 years. Hierarchical cluster analysis identified two PD subtypes: 86 “early” and 60 “mild-to-severe” patients. Within the “early” subtype, two clinical groups were identified: “early-motor-predominant” and “early-diffuse”, the latter having greater cognitive deficits and more frequent non-motor manifestations. 60 age- and sex-matched controls performed baseline assessments. Graph analysis and connectomics assessed global and local topological network properties and regional functional connectivity (FC) at baseline and changes over-time. Results: “Early” PD patients showed a relatively preserved global functional architecture at baseline and over-time. At baseline, “mild-to-severe” patients showed altered functional topological properties of the sensorimotor and parietal areas relative to controls. Longitudinal analysis showed a progressive deterioration of global functional topological features in “mild-to-severe” patients, with a specific involvement of the sensorimotor, frontal, parietal and temporal regions. At baseline, a widespread pattern of decreased FC involving the basal ganglia, sensorimotor, frontal, parietal and temporal networks was found in “mild-to-severe” and “early-diffuse” patients relative to controls and in “mild-to-severe” relative to “early-motor-predominant” cases. When FC changes over-time were compared between subtypes, five distinct patterns of progression were identified: 1) different trend of change between subtypes (increase vs decrease); 2 & 3) similar trend of change (increase or decrease), with or without FC difference between the groups; 4) different but stable FC values over time in the two subtypes; 5) stable FC with no difference between groups. Conclusions: Graph analysis and connectomics might represent a powerful approach to understand the pathophysiological process associated with PD progression. Disclosure: Dr. Filippi has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen Idec, Merck-Serono, Novartis, Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in an editorial capacity for Journal of Neurology. Dr. Filippi has received research support from Biogen Idec, Merck-Serono, Novartis, Teva Pharmaceutical Industries, Roche. Dr. Basaia has nothing to disclose. Dr. Zahedmanesh has nothing to disclose. Dr. Stojkovic has nothing to disclose. Dr. Stankovic has nothing to disclose. Dr. pica has nothing to disclose. Dr. Petrovic has nothing to disclose. Dr. Stefanova has nothing to disclose. Dr. Kostic has received personal compensation in an editorial capacity for Novartis Pharmaceuticals and Boehriner Ingelheim. Dr. Kostic has received research support from Valeant, Stada, Novartis Pharmaceuticals, and Boehriner Ingelheim. Dr. Agosta has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with EXCEMED– Excellence in Medical Education.