Functional discrimination of CSF from Alzheimer’s patients in a brain on chip platform - Louise Miny; Jessica Rontard; Ahmad Allouche; Nicolas Violle; Louise Dubuisson; Aurélie Batut; Alexandre Ponomarenko; Rania Talbi; Hélène Gautier; Benoît G. C. Maisonneuve; Serge Roux; Florian Larramendy; et al. (Scientific Reports)
Abstract Neurodegenerative diseases, including Alzheimer’s disease (AD), present significant diagnostic challenges due to overlapping symptoms and the invasive, time-consuming, and costly nature of current diagnostic methods. While AD remains the only neurodegenerative disorder for which biomarkers in cerebrospinal fluid (CSF), such as amyloid beta peptide (Aβ), are available for clinical diagnosis, similar tools are lacking for other neurodegenerative conditions. This diagnostic gap hinders timely and accurate differential diagnoses, limiting patient access to appropriate clinical trials and therapeutic interventions. In this study, we developed a compartmentalized microfluidic platform to facilitate differential diagnosis of neurodegenerative diseases by providing an initial screening tool to guide patients toward targeted clinical pathways. Using CSF samples from AD patients with confirmed diagnoses, we showed a proof of concept to distinguish between non neurodegenerative (NN) and Alzheimer’s samples. Human glutamatergic neurons derived from induced pluripotent stem cells (iPSCs) were exposed to synthetic Aβ oligomers (AβO) and patient CSF to assess their effects on neuronal network activity. Neuronal responses were recorded via microelectrode array (MEA) before and after treatments, with tetrodotoxin (TTX) serving as a control for validating modulation of the neuronal network. Our findings demonstrated that key electrophysiological metrics extracted from MEA recordings can tend to differentiate AD from non-neurodegenerative CSF samples. This standardized platform not only provides a robust approach for AD biomarker validation but also offers a foundation for broader differential diagnosis of neurodegenerative diseases. By enabling more accurate patient stratification, this tool could have the potential to direct patients toward appropriate clinical trials, enabling the diagnosis of a broader range of neurodegenerative diseases. This approach has the potential to expand the patient population included in research and accelerate the development of new therapeutic strategies.