College
Taneja College of Pharmacy
Mentor Information
Chuanhai Cao
Description
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid-β plaques and neurofibrillary tau tangles, leading to progressive cognitive decline and synaptic dysfunction. Because current disease-modifying therapies for AD are extremely limited, there is a pressing need to investigate compounds that may influence underlying disease-related cellular processes. This study investigated the dose- and time-dependent effects of Δ9-tetrahydrocannabinol (Δ9-THC), 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) to identify cannabinoid exposure conditions and to establish a framework for future AD research. N2a-APP cells, a mouse neuroblastoma cell line genetically modified to overproduce human amyloid precursor protein (APP) and serve as an in vitro AD model, were exposed to six concentrations (0.025, 0.05, 0.10, 0.20, 0.30, and 0.50 µM) for 24, 48, and 72 hours. Cellular metabolic activity was quantified using the MTT assay following blank correction and normalization to untreated controls. Computational analysis in Python was used to generate dose-response curves, compare compound-specific responses, and perform exploratory three-way analysis of variance (ANOVA). The three cannabinoids produced distinct concentration- and time-dependent effects on cellular metabolic activity, with significant effects of compound, concentration, exposure time, and multiple interaction terms. Among the compounds evaluated, 11-OH-THC generally produced greater reductions in cellular metabolic activity than Δ9-THC and THC-COOH across several experimental conditions. This suggests that individual cannabinoids and their metabolites elicit distinct biological responses in an AD cell model. This can help identify candidate exposure conditions for future studies, providing a foundation for the investigation of cannabinoid biology in AD while informing future therapeutic research.
Optimizing Cannabinoid Exposure in an In Vitro Alzheimer's Disease Model: A Dose- and Time-Dependent Analysis of Δ9-THC, 11-OH-THC, and THC-COOH
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid-β plaques and neurofibrillary tau tangles, leading to progressive cognitive decline and synaptic dysfunction. Because current disease-modifying therapies for AD are extremely limited, there is a pressing need to investigate compounds that may influence underlying disease-related cellular processes. This study investigated the dose- and time-dependent effects of Δ9-tetrahydrocannabinol (Δ9-THC), 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) to identify cannabinoid exposure conditions and to establish a framework for future AD research. N2a-APP cells, a mouse neuroblastoma cell line genetically modified to overproduce human amyloid precursor protein (APP) and serve as an in vitro AD model, were exposed to six concentrations (0.025, 0.05, 0.10, 0.20, 0.30, and 0.50 µM) for 24, 48, and 72 hours. Cellular metabolic activity was quantified using the MTT assay following blank correction and normalization to untreated controls. Computational analysis in Python was used to generate dose-response curves, compare compound-specific responses, and perform exploratory three-way analysis of variance (ANOVA). The three cannabinoids produced distinct concentration- and time-dependent effects on cellular metabolic activity, with significant effects of compound, concentration, exposure time, and multiple interaction terms. Among the compounds evaluated, 11-OH-THC generally produced greater reductions in cellular metabolic activity than Δ9-THC and THC-COOH across several experimental conditions. This suggests that individual cannabinoids and their metabolites elicit distinct biological responses in an AD cell model. This can help identify candidate exposure conditions for future studies, providing a foundation for the investigation of cannabinoid biology in AD while informing future therapeutic research.
