Depression patient-derived cortical neurons reveal potential biomarkers for antidepressant response

Abstract

Introduction Major depressive disorder is highly prevalent worldwide and has been affecting an increasing number of people each year. Current first line antidepressants show merely 37% remission, and physicians are forced to use a trial-and-error approach when choosing a single antidepressant out of dozens of available medications. Objectives We sought to identify a method of testing that would provide patient-specific information on whether a patient will respond to a medication using in vitro modeling. Methods Patient-derived lymphoblastoid cell lines from the STAR*D study were used to rapidly generate cortical neurons and screen them for bupropion effects, for which the donor patients showed remission or non-remission. Results We provide evidence for biomarkers specific for bupropion response, including synaptic connectivity and morphology changes as well as specific gene expression alterations. Conclusions These biomarkers support the concept of personalized antidepressant treatment based on in vitro platforms and could be utilized as predictors to patient response in the clinic. Disclosure This work was funded by Genetika+ Ltd, Jerusalem, Israel. YA, DK, EN, DL and TCS are employees of Genetika+ Ltd and received salary and/or stock options for the submitted work.

Keywords

• Depression
• personalized medicine
• biomarkers
• disease models