Neuronal secretome from bipolar patient-derived neurons alters network function and contains candidate biomarkers for diagnosis and lithium response
Alessia PietrantonioiD, Charles-Etienne CastonguayiD, Daniel L. RochefortiD, Camila Tiefensee RibeiroiD, Yumin LiuiD, Malak AbuzgayaiD, Isabella PietrantonioiD, Ziqi Yu, M Guadalupe AldaiD, Guy Armand RouleauiD, Austen J. MilnerwoodiD, Anouar KhayachiiD
Abstract
Delayed diagnosis and treatment are a major burden to patients with bipolar disorder. While lithium is the most effective treatment against mania, depressive episodes, and suicide, only 30% of patients respond to it fully. Currently there are no reliable methods to predict lithium responsiveness. To address these challenges, we aimed to identify potential diagnostic and treatment response biomarkers for BD, in addition furthering understanding of BD pathophysiology. Here, we leveraged human induced pluripotent stem cell (hiPSC) derived neurons from lithium responsive (LR), lithium non-responsive (LNR), and healthy age-matched controls (CTL). We found extracellular vesicle (EV) cargos from hiPSC-derived neurons are indicative of disease state and treatment-response. Unbiased proteomic and miRNA profiling identified 10 proteins and 13 miRNAs that were differentially expressed in BD EVs relative to CTL, as well as distinct molecular signatures separating LR ad LNR groups. These differences converged on pathways related to synaptic function, neurotrophic signalling, and cellular stress responses. Additionally, we found the BD neuronal secretome alters activity in non-BD neuronal networks. Chronic treatment of CTL cultures with BD neuron-conditioned media modified the proportion of active neurons and the frequency and amplitude of calcium transients in individual neurons. We demonstrate that neuronal EVs contain molecular signatures of disease state and treatment response in BD and identify the BD secretome as an active regulator of neuronal network homeostasis. This study provides novel insights into the pathophysiology of BD and candidate biomarkers for personalized BD diagnosis and treatment selection.
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