Structural and Functional Brain Patterns of Non-Motor Syndromes in Parkinson’s Disease

Abstract

Parkinson’s disease (PD) is a common, progressive and multisystem neurodegenerative disorder characterized by motor and non-motor symptoms. Advanced magnetic resonance imaging, positron emission tomography, and functional magnetic resonance imaging can render the view toward understanding the neural basis of these non-motor syndromes, as they help to understand the underlying pathophysiological abnormalities. This review provides an up-to-date description of structural and functional brain alterations in patients with PD with cognitive deficits, visual hallucinations, fatigue, impulsive behavior disorders, sleep disorders, and pain.

Distinct large-scale networks are associated with motor and nonmotor symptoms in Parkinson’s disease

“…Importantly, two hubs of this network, namely the temporal pole and posterior cingulate cortex, are affected in semantic dementia (Acosta-Cabronero et al, 2011) and Alzheimer's disease (Buckner et al, 2008), respectively, implying that the dysregulation of this network may also be a harbinger of cognitive decline. This is supported by a parietotemporal pattern of atrophy that has been associated with worse cognitive performance in nondemented PD subjects (Uribe et al, 2016;2018), as well as correlation between cognitive impairment in PD and reduced functional connectivity in the default mode network, and frontoparietal and temporal regions (Wolters et al, 2019).…”

“…Functional MRI (fMRI) studies have shown abnormal functional connectivity patterns within and between the nodes of major networks including the sensorimotor, default mode, salience, and executive-attention networks in PD (for a meta-analysis see Tahmasian et al, 2017). A number of MRI studies have also investigated more specifically the neuroanatomical correlates of motor and nonmotor features of PD (for reviews, see Wen et al, 2016;Yousaf et al, 2017;Prell 2018;Valli et al, 2019).…”

Whole Exome Sequencing Study of Parkinson Disease and Related Endophenotypes in the Italian Population

“…Indeed, in spite of the relatively small sample size sequenced and of the availability of exome (rather than whole genome) data, which represent the main limitations of the present study, we exploited the wealth of neurological scales assessed to carry out an exome-wide association study of motor and non-motor PD endophenotypes. Moreover, we tested associations of the scales available-namely UPDRS, MoCA and NMS-with PRSs known to influence subcortical volumes, which have long been considered as neuroimaging correlates of PD and neurodegeneration (32)(33)(34)(35). To our knowledge, this study represents the first attempt to test genetic associations with neurological scales in PD at the exome-wide level.…”

“…We used exome-wide genetic data to build Polygenic Risk Scores (PRSs) influencing brain subcortical volumes, which were trained using summary statistics of a previous large independent GWAS (N max = 30,717) (55). This analysis was motivated by previous literature reporting both structural and functional alterations of several subcortical structures in PD (32)(33)(34)(35), for which these are often considered useful neuroimaging correlates. First we computed standardized best-fit polygenic scores through PRSice-2 (56), over varying association significance thresholds in the training GWAS (ranging from 5 × 10 −8 to 1), for nucleus accumbens, caudate, putamen, pallidum, amygdala, hippocampus and thalamus volume.…”

“…However, PRS analyses of Parkinson neuroimaging correlates were never reported. Overall, no NGS study so far focused on identifying genetic variants associated with PD endophenotypes, and there is a paucity of genomic studies doing so, in particular with motor, cognitive and non-motor scales, as well as with neuroimaging traits related to PD risk and symptoms, like subcortical volumes (32)(33)(34)(35).…”