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Functional Connectomics and Disease Progression in Drug-Naïve Parkinson's Disease Patients.
De Micco, Rosa; Agosta, Federica; Basaia, Silvia; Siciliano, Mattia; Cividini, Camilla; Tedeschi, Gioacchino; Filippi, Massimo; Tessitore, Alessandro.
Afiliación
  • De Micco R; Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
  • Agosta F; MRI Research Center, University of Campania "Luigi Vanvitelli", Naples, Italy.
  • Basaia S; Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
  • Siciliano M; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
  • Cividini C; Vita-Salute San Raffaele University, Milan, Italy.
  • Tedeschi G; Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
  • Filippi M; Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
  • Tessitore A; Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy.
Mov Disord ; 36(7): 1603-1616, 2021 07.
Article en En | MEDLINE | ID: mdl-33639029
ABSTRACT

BACKGROUND:

Functional brain connectivity alterations may be detectable even before the occurrence of brain atrophy, indicating their potential as early markers of pathological processes.

OBJECTIVE:

We aimed to determine the whole-brain network topologic organization of the functional connectome in a large cohort of drug-naïve Parkinson's disease (PD) patients using resting-state functional magnetic resonance imaging and to explore whether baseline connectivity changes may predict clinical progression.

METHODS:

One hundred and forty-seven drug-naïve, cognitively unimpaired PD patients were enrolled in the study at baseline and compared to 38 age- and gender-matched controls. Non-hierarchical cluster analysis using motor and non-motor data was applied to stratify PD patients into two subtypes 77 early/mild and 70 early/severe. Graph theory analysis and connectomics were used to assess global and local topological network properties and regional functional connectivity at baseline. Stepwise multivariate regression analysis investigated whether baseline functional imaging data were predictors of clinical progression over 2 years.

RESULTS:

At baseline, widespread functional connectivity abnormalities were detected in the basal ganglia, sensorimotor, frontal, and occipital networks in PD patients compared to controls. Decreased regional functional connectivity involving mostly striato-frontal, temporal, occipital, and limbic connections differentiated early/mild from early/severe PD patients. Connectivity changes were found to be independent predictors of cognitive progression at 2-year follow-up.

CONCLUSIONS:

Our findings revealed that functional reorganization of the brain connectome occurs early in PD and underlies crucial involvement of striatal projections. Connectomic measures may be helpful to identify a specific PD patient subtype, characterized by severe motor and non-motor clinical burden as well as widespread functional connectivity abnormalities. © 2021 International Parkinson and Movement Disorder Society.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Preparaciones Farmacéuticas / Conectoma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mov Disord Asunto de la revista: NEUROLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Preparaciones Farmacéuticas / Conectoma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mov Disord Asunto de la revista: NEUROLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Italia