Beyond the Dopaminergic System: Lessons Learned from levodopa Resistant Symptoms in Parkinson's Disease

Validation of the Italian version of the Parkinson's Disease- Cognitive Functional Rating Scale

A key distinguishing factor between mild cognitive impairment (MCI) and dementia in Parkinson's disease (PD) lies in the notable decrease in functioning due to cognitive impairment. The Parkinson's Disease-Cognitive Functional Rating Scale (PD-CRFS) was developed to assess functional limitations caused by cognitive impairment, while reducing the influence of motor impairment. The aim of this multicenter study was to (i) validate the Italian version of the PD-CFRS in PD, (ii) determine optimal cut-off scores for detecting MCI and dementia in PD, (iii) compare its performances with the most established functional assessment tool (IADL). Six hundred and sixty nine PD participants were recruited from 4 Italian Movement Disorders centers (Venice, Milan, Gravedona, and Salerno). They underwent Level-II cognitive evaluation, which resulted in 282 PD-NC, 310 PD-MCI, and 77 PDD. The PD-CFRS's psychometric and clinimetric properties, applicability, and responsiveness were analyzed. The PD-CFRS showed high acceptability. Floor and ceiling effects were acceptable. It also displayed strong internal consistency (Cronbach's α = 0.738), and test-retest reliability (ICC = .854). The PD-CFRS demonstrated higher coefficient of variation to detect dysfunction in PD-MCI patients in comparison to the IADL scale (PD-CFRS 96% vs IADL 22.5%). Convergent validity with the IADL was r = - 0.638 and - 0.527 in males and females, respectively. PD-CFRS total score negatively correlated with global cognition (MoCA corrected score r = - 0.61; p < 0.001). A cut-off score > 6.5 identified PDD with a sensitivity of 90% and specificity of 88% (AUC = .959). A cut-off value of > 1 detected PD-MCI with a sensitivity of 68% and specificity of 69% (AUC = .695). The Italian version of the PD-CFRS demonstrated to be an easy, valid and reliable tool that properly captures functional impairment due to cognitive decline in PD. It also proved to be particularly effective in the advanced stages of PD, and would be a useful support for the diagnosis of PD-MCI and PDD.

Brain Dynamics Complexity as a Signature of Cognitive Decline in Parkinson's Disease

BACKGROUND

Higuchi's fractal dimension (FD) captures brain dynamics complexity and may be a promising method to analyze resting-state functional magnetic resonance imaging (fMRI) data and detect the neuronal interaction complexity underlying Parkinson's disease (PD) cognitive decline.

OBJECTIVES

The aim was to compare FD with a more established index of spontaneous neural activity, the fractional amplitude of low-frequency fluctuations (fALFF), and identify through machine learning (ML) models which method could best distinguish across PD-cognitive states, ranging from normal cognition (PD-NC), mild cognitive impairment (PD-MCI) to dementia (PDD). Finally, the aim was to explore correlations between fALFF and FD with clinical and cognitive PD features.

METHODS

Among 118 PD patients age-, sex-, and education matched with 35 healthy controls, 52 were classified with PD-NC, 46 with PD-MCI, and 20 with PDD based on an extensive cognitive and clinical evaluation. fALFF and FD metrics were computed on rs-fMRI data and used to train ML models.

RESULTS

FD outperformed fALFF metrics in differentiating between PD-cognitive states, reaching an overall accuracy of 78% (vs. 62%). PD showed increased neuronal dynamics complexity within the sensorimotor network, central executive network (CEN), and default mode network (DMN), paralleled by a reduction in spontaneous neuronal activity within the CEN and DMN, whose increased complexity was strongly linked to the presence of dementia. Further, we found that some DMN critical hubs correlated with worse cognitive performance and disease severity.

CONCLUSIONS

Our study indicates that PD-cognitive decline is characterized by an altered spontaneous neuronal activity and increased temporal complexity, involving the CEN and DMN, possibly reflecting an increased segregation of these networks. Therefore, we propose FD as a prognostic biomarker of PD-cognitive decline. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The pharmacological management of the behavioral aspects of Parkinson's disease: an update

INTRODUCTION

Behavioural symptoms are common manifestations of Parkinson's disease and include depression, anxiety, impulse control disorders, hallucinations, psychosis, and cognitive dysfunction. They remain inadequately addressed in many patients despite their relevance for quality of life and disability. This applies also to impulse control disorders where the most common approach in recent literature is to refrain from using dopamine agonists without consideration about their potential benefit on motor complications.

AREAS COVERED

We conducted a narrative review searching for articles on behavioral symptoms in Parkinson disease and selected those which included involved neurotransmitters such as dopamine, noradrenaline, serotonin, acetylcholine. We specifically focused our search on open-label and randomized double-blind studies and biomarkers which could best characterize these clinical manifestations.

EXPERT OPINION

Management of Parkinson disease behavioural manifestations lacks clear guidelines and standardized protocols beside general suggestions of dose adjustments in dopamine replacement therapy and use of antidepressants or antipsychotic drugs with little consideration of patients' age, sex, comorbidities, and motor status. We suggest a pragmatic approach which includes education of affected patients and caring people, dealing with complex cases by experienced multidisciplinary teams, use of cognitive behavioural therapy, and psychological counselling to complement drug treatment.