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Multimodal PET/MRI and 31-Phosphorus magnetic resonance spectroscopy to mechanistically stratify sporadic Parkinson's disease

In plain English

AI plain-English summary

Parkinson’s disease patients have different underlying biological faults, and this project will use two brain-scanning techniques at once to sort them into groups based on how their brain cells produce energy. Currently, doctors cannot tell which Parkinson’s patient has a failing energy system inside their neurons—known as mitochondrial dysfunction—and which has a problem with how their brain uses sugar. This matters because a treatment that fixes one energy pathway may do nothing for the other. Without a way to see these differences in a living patient, clinical trials for new drugs mix together people who need different therapies, diluting any real effect. The researcher will combine two scanning methods: one that measures the brain’s energy currency (ATP) and another that tracks glucose consumption. If the scans reliably identify distinct bioenergetic subtypes, future trials could recruit only those patients whose specific energy fault matches the drug being tested. Skin biopsies taken from the same participants will later be turned into lab-grown neurons to confirm the scanning results and pinpoint the exact genetic or molecular cause. This is fundamental science aimed at building a diagnostic tool—not an immediate treatment—but it could reshape how Parkinson’s clinical trials are designed.

View original technical description
Parkinson’s disease (PD) is a common, relentlessly progressive, neurodegenerative movement disorder. Multiple pathogenic mechanisms are implicated. The lack of disease modifying treatments for PD is in part due to distinct different mechanisms leading to PD in individual patients. Mitochondrial dysfunction is one such mechanism, observed in sporadic PD brain tissue and implicated in almost all familial forms of PD. Tools to mechanistically stratify PD (e.g., mitochondrial dysfunction) will facilitate future precision medicine approaches. My previous work demonstrated that 31-Phosphorus magnetic resonance spectroscopy (31P-MRS) measures of in vivo bioenergetic dysfunction in the putamen of PD correlated with the deep phenotyping of mitochondria in peripheral tissue fibroblasts. However, 31P-MRS cannot interrogate major metabolic pathways such as glucose metabolism, a major contributor to brain bioenergetics and possibly also the bioenergetic heterogeneity in PD. This project will comprehensively assess the bioenergetic status of the PD brain by concurrently assessing oxidative phosphorylation using 31P-MRS and glucose metabolism using 18-Fluorodeoxyglucose (FDG)-positron emission tomography (PET) to identify specific bioenergetic phenotypes that may be amenable to targeted therapies towards the rescue of mitochondrial dysfunction or altered glucose homeostasis. Skin biopsies will be obtained from all participants to establish fibroblast cell lines for future reprogramming into i-neurons. This will put me in a strong position to obtain subsequent funding for work outside the scope of this grant, whereby the in vitro metabolic assessment of oxidative phosphorylation and glycolysis in patient derived i-neurons, will be used to validate the observed neurometabolic imaging phenotypes and identify their underlying causative pathogenic mechanism.

View the original record at the funder ↗

Researchers

Thomas Payne (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Systems Medicine of Mitochondrial Parkinson’s Disease
Does mitochondrial function correlate in brain tissue and peripheral tissue in patients with Parkinson’s disease and controls? (ATP correlation in PD)
Does mitochondrial function correlate in brain tissue and peripheral tissue in patients with Parkinson’s disease and controls?
Using neuroimaging data to map dysfunctional brain networks and predict symptom severity in Parkinson's disease progression.
Multiscale and multimodal brain network changes causing Parkinson’s dementia

Original classification

Starter Grant for Clinical Lecturers

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