Stem cell-derived neurons from patients with familial forms of Parkinson’s may be used as a valuable model to screen and develop novel therapies for this disease, according to a study.
While most Parkinson’s cases are sporadic, approximately 10% of them are caused by mutations in the PARK1, LRRK2, PARK2 and PARK6 genes. PARK2 and PARK6 are known to be involved in stress responses and molecular equilibrium within mitochondria (considered the power generators of cells).
Despite knowing multiple possible causes for Parkinson’s, scientists have not yet developed effective therapeutic treatments. Research findings obtained from cellular and animal models do not always reflect what occurs in people with hereditary Parkinson’s disease, “due to different cellular contexts or vulnerability to disease-relevant mutations,” wrote Keio University researchers, who have developed a model using human induced pluripotent stem cell (iPSC) technology.
iPSCs are derived from either skin or blood cells of patients. These cells are then reprogrammed back into a stem cell-like state, which allows for the development of an unlimited source of almost any type of human cell needed. Because they’re derived from patients, the “novel daughter cells” will carry the same genetic defects as those found in the original cells.
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Using iPSCs, the team generated PARK2 patient-specific dopamine-producing neurons — those that are damaged in Parkinson’s — to model the disease in a laboratory setting.
The newly generated PARK2 mutant neurons were found to have high levels of oxidative stress, which causes cellular damage resulting from high levels of oxidant molecules. Oxidative stress is characterized by an imbalance between the production of free radicals and the ability of cells to detoxify them. These free radicals are harmful to the cells and are associated with a number of diseases, including Parkinson’s.
Because studies have shown reduced mitochondria activity in the brains of Parkinson’s patients, the Japanese researchers exposed PARK2 mutant neurons to rotenone, a pesticide known to inhibit the function of mitochondria. As expected, these neurons were more susceptible to rotenone-induced cell death than healthy neurons.
To understand whether this cellular model could be used for drug discovery and to repurpose existing medicines, scientists screened several compounds that had already been approved by the U.S. Food and Drug Administration.
Candidates were shortlisted based on their ability to protect dopaminergic nerve cells against rotenone-induced death.
Benidipine — a calcium channel blocker that stabilizes calcium levels in the cell by blocking its influx through specific channels, known as T-type calcium channel — reduced rotenone-induced cell death. Two similar compounds did not: nifedipine and isradipine, which use a different channel subtype. These findings suggest that “the calcium channel subtype is important for neuroprotective effects against PARK2-(dopaminergic) neurons,” the researchers wrote.
In addition, benipidine rescued the compromised growth of neuronal projections — called neurites — in these PARK2 mutant neurons. These projections lead to the development of either axons or dendrites, which nerve cells use to transmit chemical signals and communicate.
To further validate benidipine’s effect, scientists examined the compound’s effect on neurons generated from patients with a different form of familial Parkinson’s — a mutation in the PARK6 gene.
As in PARK2 models, PARK6 nerve cells had reduced neuronal projections and elevated levels of oxidant molecules, compared with control dopamine-producing neurons. Rotenone treatment further increased oxidant molecule levels and cellular death in PARK6 neurons. The researchers found benipidine prevented rotenone-induced death in these neurons in a concentration-dependent manner.
They concluded that PARK2 and PARK6 dopamine-producing neurons mirror several molecular characteristics of Parkinson’s disease and thus can be used to search for potential therapeutic targets for this neurodegenerative disorder.
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