Our findings revealed a functional disruption of the DMN in cognitively unimpaired patients with PD, in the absence of significant structural differences between patients and controls. We hypothesize that a dysfunction of the DMN connectivity may have a role in the development of cognitive decline in PD.

The Montreal Cognitive Assessment (MoCA) is a rapid screening battery, also including subtests to assess frontal functions such as set-shifting, abstraction and cognitive flexibility. MoCA seems to be useful to identify non-amnestic mild cognitive impairment (MCI) and subcortical dementia; it has high sensitivity and specificity in distinguishing MCI from mild Alzheimer's Disease. Previous studies revealed that certain items of MoCA may be culturally biased and highlighted the need for population-based norms for the MoCA. The aim of present study was to collect normative values in a sample of Italian healthy subjects. Four hundred and fifteen Italian healthy subjects (252 women and 163 men) of different ages (age range 21-95 years) and educational level (from primary to university) underwent MoCA and Mini Mental State Examination (MMSE). Multiple linear regression analysis revealed that age and education significantly influenced performance on MoCA. No significant effect of gender was found. From the derived linear equation, a correction grid for MoCA raw scores was built. Inferential cut-off score, estimated using a non-parametric technique, is 15.5 and equivalent scores were computed. Correlation analysis showed a significant but weak correlation between MoCA adjusted scores with MMSE adjusted scores (r = 0.43, p < 0.001). The present study provided normative data for the MoCA in an Italian population useful for both clinical and research purposes.

No abstract

BackgroundThe variability in the clinical phenotype of Parkinson’s disease seems to suggest the existence of several subtypes of the disease. To test this hypothesis we performed a cluster analysis using data assessing both motor and non-motor symptoms in a large cohort of newly diagnosed untreated PD patients.MethodsWe collected data on demographic, motor, and the whole complex of non-motor symptoms from 100 consecutive newly diagnosed untreated outpatients. Statistical cluster analysis allowed the identification of different subgroups, which have been subsequently explored.ResultsThe data driven approach identified four distinct groups of patients, we have labeled: 1) Benign Pure Motor; 2) Benign mixed Motor-Non-Motor; 3) Non-Motor Dominant; and 4) Motor Dominant.ConclusionOur results confirmed the existence of different subgroups of early PD patients. Cluster analysis revealed the presence of distinct subtypes of patients profiled according to the relevance of both motor and non-motor symptoms. Identification of such subtypes may have important implications for generating pathogenetic hypotheses and therapeutic strategies.