Multiscale and multimodal brain network changes causing Parkinson’s dementia
Award Number
225263/Z/22/ZAward Type
Career Development AwardsStatus / Stage
ActiveDates
1 June 2023 -31 May 2031
Duration (calculated)
07 years 11 monthsFunder(s)
Wellcome TrustFunding Amount
£4,109,069.00Funder/Grant study page
Wellcome TrustContracted Centre
University College LondonPrincipal Investigator
Dr Rimona WeilPI Contact
patrick.kagyah1@nhs.netWHO Catergories
Understanding risk factorsUnderstanding Underlying Disease
Disease Type
Parkinson's DementiaCPEC Review Info
Reference ID | 284 |
---|---|
Researcher | Reside Team |
Published | 12/06/2023 |
Data
Award Number | 225263/Z/22/Z |
---|---|
Status / Stage | Active |
Start Date | 20230601 |
End Date | 20310531 |
Duration (calculated) | 07 years 11 months |
Funder/Grant study page | Wellcome Trust |
Contracted Centre | University 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.