A Multi-Scale Computational Model of Levodopa-Induced Toxicity in Parkinson's Disease - Muddapu, Vignayanandam Ravindernath-Jayashree; Vijayakumar, Karthik; Ramakrishnan, Keerthiga; Chakravarthy, V. Srinivasa (Frontiers in Neuroscience, 2022)
Parkinson’s disease (PD) is caused by the progressive loss of dopaminergic cells in substantia nigra pars compacta (SNc). The root cause of this cell loss in PD is still not decisively elucidated. A recent line of thinking traces the cause of PD neurodegeneration to metabolic deficiency. Levodopa (L-DOPA), a precursor of dopamine, used as a symptom-relieving treatment for PD, leads to positive and negative outcomes. Several researchers suggested that L-DOPA might be harmful to SNc cells due to oxidative stress. The role of L-DOPA in the course of PD pathogenesis is still debatable. We hypothesize that energy deficiency can lead to L-DOPA-induced toxicity in two ways: by promoting dopamine-induced oxidative stress and by exacerbating excitotoxicity in SNc. We present a systems-level computational model of SNc-striatum, which will help us understand the mechanism behind neurodegeneration postulated above and provide insights for developing disease-modifying therapeutics. It was observed that SNc terminals are more vulnerable to energy deficiency than SNc somas. During L-DOPA therapy, it was observed that higher L-DOPA dosage results in increased loss of terminals in SNc. It was also observed that co-administration of L-DOPA and glutathione (antioxidant) evade L-DOPA-induced toxicity in SNc neurons. Our proposed model of SNc-striatum system is the first of its kind, where SNc neurons were modelled at biophysical level, and striatal neurons were modelled at spiking level. We show that our proposed model was able to capture L-DOPA-induced toxicity in SNc, caused by energy deficiency.