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Waveform-based prediction of AD-related pathology for patient diagnostics (WAVEAD)

Project description

Early Alzheimer’s brain waves as predictive tools

Alzheimer’s disease (AD) begins long before symptoms appear. This makes early detection crucial. Funded by the ERC, the WAVEAD project leverages a unique opportunity: living brain biopsies from patients with idiopathic normal pressure hydrocephalus, some of whom show early AD-related pathology. By studying how AD affects neuronal circuits, WAVEAD examines changes in synaptic strengthening and network function using multielectrode arrays. Machine-learning classifiers can already predict patient pathology from these waveforms. The project now investigates whether glutamatergic and cholinergic signalling patterns, combined with non-invasive transcranial magnetic stimulation and electroencephalogram recordings, can similarly indicate disease status in clinical settings. Success could lead to personalised therapies and early diagnostic tools.

Objective

Due to the early AD-related pathology present in a subpopulation of idiopathic normal pressure hydrocephalus (iNPH) patients, the brains of the iNPH patients offer a unique window to evaluate events taking place during the course of AD pathology progression. Here we take advantage of our continuous access to living brain biopsies from iNPH patients and related clinical data to assess, how AD pathology affects the neuronal circuit operational properties in human brain. During the ERC consolidator project, we have discovered that pre-existing AD-related pathology alters neuronal circuit operational properties, and importantly, impairs the ablity of the network to elicit synaptic strenthening, as evaluated using stimulation protocols on multielectrode arrays (MEA). Interestingly, a supervised machine-learning -based classifier was able to classify and predict the patient pathological status using the synaptic plasticity -induced waveforms. Here we now investigate the whether the waveforms related to glutamatergic signaling and cholinergic signaling have similar predictive value of the patient pathological status and possible clinical diagnosis and whether these readouts obtained from the ex vivo biopsies are correlated in the clinical settings using transcranial magnetic stimulations (TMS) and EEG recordings. Moreover, we probe whether the recorded TMS and EEG waveforms have the same predictive capacity in clinical settings. If succesful, these waveforms could facilitate personalized therapy or serve as a diagnostic tool for detection of early AD and thus have a significant commercialization potential.

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HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

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(opens in new window) ERC-2025-POC

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Host institution

ITA-SUOMEN YLIOPISTO
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Address
YLIOPISTONRANTA 8
70211 KUOPIO
Finland

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Activity type
Higher or Secondary Education Establishments
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Total cost

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Beneficiaries (1)

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