Multiscale and multimodal brain network changes causing Parkinson’s dementia

Award Number
225263/Z/22/Z
Award Type
Career Development Awards
Status / Stage
Active
Dates
1 June 2023 -
31 May 2031
Duration (calculated)
07 years 11 months
Funder(s)
Wellcome Trust
Funding Amount
£4,109,069.00
Funder/Grant study page
Wellcome Trust
Contracted Centre
University College London
Principal Investigator
Dr Rimona Weil
PI Contact
patrick.kagyah1@nhs.net
WHO Catergories
Understanding risk factors
Understanding Underlying Disease
Disease Type
Parkinson's Dementia

CPEC Review Info
Reference ID284
ResearcherReside Team
Published12/06/2023

Data

Award Number225263/Z/22/Z
Status / StageActive
Start Date20230601
End Date20310531
Duration (calculated) 07 years 11 months
Funder/Grant study pageWellcome Trust
Contracted CentreUniversity College London
Funding Amount£4,109,069.00

Abstract

Dementia affects more than half of patients with Parkinson’s disease (PD) but the underlying mechanisms are not understood. I have previously shown that PD dementia is linked to changes in brain networks, but the causes of network dysfunction are not known. Specific gaps are: the link between network dysfunction and accumulation of pathological proteins such as alpha-synuclein, amyloid and tau; relative importance of feedback versus feedforward signaling within circuits; the role of neurotransmitters such as acetylcholine and noradrenaline on PD dementia; and the sequence of events leading to PD dementia.

In this proposal I will use advanced MRI combined with PET imaging, plasma markers and pharmacological manipulation to transform our understanding of PD dementia.

My goals are to:

Relate network changes in early PD dementia to underlying neural pathology using tau and amyloid PET and fluid biomarkers
Characterise changes in feedback and feedforward brain networks in early PD dementia using high-field MRI and magnetoencephalography
Understand the link between neurotransmitters and network changes in PD dementia through pharmacological manipulation
Determine the sequence of events leading to Parkinson’s dementia using computational modelling

This will shed light onto pathological mechanisms, provide targets for intervention and guide development of effective biomarkers for PD dementia.

Aims

In this proposal I will use advanced MRI combined with PET imaging, plasma markers and pharmacological manipulation to transform our understanding of PD dementia.