IPSC‐derived hindbrain spheroids to evaluate drug responses targeting neuropsychiatric symptoms in Alzheimer’s disease

Abstract

AbstractBackgroundAlzheimer’s disease (AD), a neurodegenerative disorder, is the most common cause of dementia. The gradual deterioration of brain function eventually leads to death. Almost all AD patients eventually suffer from neuropsychiatric symptoms (NPS; e.g., agitation, depression) whose emergence correlates with dysfunctional serotonergic systems. Our aim is to generate hindbrain spheroids containing serotonergic neurons using induced Pluripotent Stem Cells (iPSCs) from healthy volunteers or AD patients with and without NPS. The spheroids can be used to study AD, NPS, and to evaluate individual differences in disease progression, NPS development, and/or pharmacological treatment response.MethodHuman peripheral blood mononuclear cells from healthy volunteers (n = 3), an AD patient without NPS (n = 1), and AD patients with NPS (n = 2) were reprogrammed into iPSCs and subsequently differentiated into hindbrain spheroids. The presence of serotonergic neurons was confirmed by quantitative reverse transcription PCR, flow cytometry, immunocytochemistry, and detection of serotonin (5‐HT) secreted in the extracellular environment. To assess patient‐specific treatment effects, spheroids were treated with different concentrations of escitalopram oxalate, a medication widely prescribed for the treatment of NPS.ResultHindbrain spheroids containing serotonergic neurons were successfully generated and characterized from these 6 individual iPSC lines. Changes in 5‐HT levels before and after treatment with escitalopram were dose‐dependent and variable across patients.ConclusionIt is possible to generate hindbrain spheroids from human iPSCs to study inter‐patient variability using a precision medicine approach. Since hindbrain spheroids from different people respond differently to the application of escitalopram in vitro this may reveal subgroups of AD patients who may be more or less likely to benefit from the drug in vivo. We propose that this 3D platform might be effectively used for drug screening purposes to predict patients with NPS most likely to respond to treatment with escitalopram.