Electrophysiological Signature of Mild Cognitive Impairment and Its Relationship with Parkinson's Disease: a High-density EEG Investigation

Overview

The study aims to investigate neural correlate of Mild Cognitive Impairment (MCI) in Parkinson's disease (PD) and to identify a link between functional impairment (in both cognitive and motor domains) and electrophysiological cortical sing of MCI in PD. A sample of 42 subjects will be divide into three subgroup: healthy control, PD with MCI (PD-MCI) and PD without MCI (PD-ctrl). Those subjects will undergo a specific neuropsychological evaluation and, to measure the electro-cortical activity, high-density electroencephalography (hdEEG) will be record during both resting state and cognitive tasks. Furthermore, hdEEG data will be combine with structural magnetic resonance to obtain information about network connectivity.

Detailed description

Parkinson's disease (PD) is a neurodegenerative disorder, characterized by a degeneration of dopaminergic neurons at the level of the pars compacta of the substantia nigra, which results in impaired control of the nigrostriatal pathway. This degeneration is manifested by both motor and non-motor symptoms such bradykinesia, tremor, rigidity, and cognitive disorders. Particularly, patients with PD might be affected by Mild Cognitive Impairment (MCI), dementia, and related behavioral disorders including apathy and depressive syndromes. However, while motor disturbances are more evident, it is difficult to evaluate the onset of cognitive symptoms, especially in the prodromal phases of the disease. Indeed, it seems that the onset of cognitive deficits in PD occurs in a high prevalence in the earlier stages of the disease. PD patients can often be associated with MCI, a preclinical condition characterized by the presence of deficits in memory and executive functions as well as, to a lesser extent, in language- and visuospatial- related functions.

Dual-syndrome hypothesis posit the existence of two subtypes of MCI one fronto-striatal, characterised by executive and attentional deficits, and a posterior cortical one, characterised by deficits in memory visuo-spatial and language deficits. Recent studies described alterations in brain rhythm, measured with high-density EEG (HDEEG) in terms of frequency domain analysis, at the level of fronto-striatal regions only in patients with the fronto-striatal subtype. Moreover, fMRI studies have shown that the presence of MCI in PD causes a reduction in activity at the level of the cognitive cortico-striatal loop, which includes the caudate nucleus (CN) and prefrontal cortex (PFC).

Although the use of neurophysiological and neuroimaging techniques have substantially grown, the available data highlight the lack of detailed descriptions of functional connectivity in relation whit the onset and extent of the cognitive deficit itself. Therefore, the aim of the present study is to characterise MCI in PD from a neurophysiological and clinical point of view. First, all patients undergo a neuropsychological assessment to identify PD patients with MCI (PD-MCI) and those without MCI (PD-nMCI). Then, to investigate the functional connectivity of cortical areas underpinning cognitive decline, HDEEG will be record, during both resting state and cognitive tasks. Furthermore, for each participant will be collect MRI (Magnetic resonance imaging), to combine structural data with electrodes position over the scalp. This would allow obtaining a realistic model of the head for source analysis.

Identification of alterations in functional connectivity between specific cortical areas in MCI-PD patients, and a possible direct relationship between these and clinical impairment, could lead to improve therapeutic interventions and prevent cognitive disorders in PD patients.

Interventions

• Diagnostic test Hd-EEG
  Subjects undergo a clinical and neuropsychological assesment, then a Hd-EEG both during resting state and execution of tasks, and structural Magnetic Resonance Imaging

Primary outcome measures

• Power Spectrum Density Analysis profile for hdEEG resting state data [Time frame: at baseline]
• Power Spectrum Density Analysis profile for hdEEG during cognitive task data [Time frame: at baseline]
• Functional connectivity - seed based analysis for hdEEG resting state data [Time frame: at baseline]
• Functional connectivity - seed based analysis for hdEEG during cognitive task data [Time frame: at baseline]

Secondary outcome measures (3)

• Performances at neuropsychological evaluation [Time frame: at baseline]
• Fraility assessment [Time frame: at baseline]
• Accuracy during cognitive task [Time frame: at baseline]

Eligibility criteria

Inclusion criteria

• Upper score >24 MMSE or >15.5 Moca
• If taking medications, taking stable doses for at least 4 weeks prior to the inclusion visit - of anticholinesterase drugs (donepezil, memantine, rivastigmine, ...) or antidepressants (SSRIs, tricyclics, SNARI, ...) or Levodopa.
• Having signed the informed consent

Exclusion criteria

• Subjects with severe dementia ( MMSE < 24 )
• Lower score <15.5 Moca
• Subjects on antipsychotic treatment for less than 3 months
• Subjects with uncontrolled comorbidities
• Subjects with metal prostheses or dentures and in general conditions for which MRI examinations are prevented.
• Subjects with an inability to walk independently.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Cohort

Study locations

Italy · 1 center

• IRCCS San Camillo S.R.L — Lido

Publications

• Nagano-Saito A, Habak C, Mejia-Constain B, Degroot C, Monetta L, Jubault T, Bedetti C, Lafontaine AL, Chouinard S, Soland V, Ptito A, Strafella AP, Monchi O. Effect of mild cognitive impairment on the patterns of neural activity in early Parkinson's disease. Neurobiol Aging. 2014 Jan;35(1):223-31. doi: 10.1016/j.neurobiolaging.2013.06.025. Epub 2013 Aug 7. PMID 23932879
• Betrouni N, Devignes Q, Bayot M, Derambure P, Defebvre L, Leentjens AF, Delval A, Dujardin K. The frontostriatal subtype of mild cognitive impairment in Parkinson's disease, but not the posterior cortical one, is associated with specific EEG alterations. Cortex. 2022 Aug;153:166-177. doi: 10.1016/j.cortex.2022.04.015. Epub 2022 May 11. PMID 35667287
• Monchi O, Petrides M, Doyon J, Postuma RB, Worsley K, Dagher A. Neural bases of set-shifting deficits in Parkinson's disease. J Neurosci. 2004 Jan 21;24(3):702-10. doi: 10.1523/JNEUROSCI.4860-03.2004. PMID 14736856
• Samogin J, Marino M, Porcaro C, Wenderoth N, Dupont P, Swinnen SP, Mantini D. Frequency-dependent functional connectivity in resting state networks. Hum Brain Mapp. 2020 Dec 15;41(18):5187-5198. doi: 10.1002/hbm.25184. Epub 2020 Aug 25. PMID 32840936
• Cai M, Dang G, Su X, Zhu L, Shi X, Che S, Lan X, Luo X, Guo Y. Identifying Mild Cognitive Impairment in Parkinson's Disease With Electroencephalogram Functional Connectivity. Front Aging Neurosci. 2021 Jul 1;13:701499. doi: 10.3389/fnagi.2021.701499. eCollection 2021. PMID 34276350
• Cera N, Esposito R, Cieri F, Tartaro A. Altered Cingulate Cortex Functional Connectivity in Normal Aging and Mild Cognitive Impairment. Front Neurosci. 2019 Sep 13;13:857. doi: 10.3389/fnins.2019.00857. eCollection 2019. PMID 31572106
• Gorges M, Muller HP, Lule D; LANDSCAPE Consortium; Pinkhardt EH, Ludolph AC, Kassubek J. To rise and to fall: functional connectivity in cognitively normal and cognitively impaired patients with Parkinson's disease. Neurobiol Aging. 2015 Apr;36(4):1727-1735. doi: 10.1016/j.neurobiolaging.2014.12.026. Epub 2014 Dec 31. PMID 25623332
• Litvan I, Goldman JG, Troster AI, Schmand BA, Weintraub D, Petersen RC, Mollenhauer B, Adler CH, Marder K, Williams-Gray CH, Aarsland D, Kulisevsky J, Rodriguez-Oroz MC, Burn DJ, Barker RA, Emre M. Diagnostic criteria for mild cognitive impairment in Parkinson's disease: Movement Disorder Society Task Force guidelines. Mov Disord. 2012 Mar;27(3):349-56. doi: 10.1002/mds.24893. Epub 2012 Jan 24. PMID 22275317

Identifiers

NCT: NCT06640673 · 2023.06

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗