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

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.