RNAi Targeting of Kv3 Channels in Basal Ganglia Disease

DESCRIPTION (provided by applicant): Parkinson's disease (PD) is a neurodegenerative disorder characterized by impairment of motor function. It affects about 1 in 1000 adults, rising exponentially after the age of fifty. At present there is no treatment for PD shown to definitively attenuate disease progression. Even temporal correction of symptoms extending the period of physical mobility is considered valuable. We suggest to test a new strategy to relieve motor symptoms of the Parkinson's disease. The abnormal correlated rhythmic activity in the globus pallidus (GP) and subthalamic nucleus (STN) are believed to underlie bradykinesia and tremor of PD patients. A specific set of membrane conductances in GP and STN neurons enable such activity. Recent work by our group has shown that high frequency burst discharge in GP and STN neurons is dependent upon their expression of a combination of voltage-dependent Kv3 K+ channel subunits. These neurons form heteromeric channels containing Kv3.1 and Kv3.4 subunits. These heteromeric channels are very efficient at repolarizing spikes - keeping them very brief - and then deactivating after the spike to allow the next spike to occur quickly. Eliminating the Kv3.4 subunit from these channels diminishes the repolarizing efficiency of the channels, resulting in lower maximal discharge rates. Thus our goal is to test the hypothesis that the suppression of Kv3.4 subunit in GP/STN neurons will dramatically reduce pathological, high frequency burst discharge leading to symptomatic relief in PD models and patients. Kv3.4 is an excellent target for gene therapy approaches since its expression is highly specific for fast spiking neurons and the firing of non-targeted neurons in GP/STN surrounding areas should not be affected. We propose to use lentivirus vector to deliver small interfering RNA (siRNA) designed to trigger the degradation of Kv3.4 mRNA in GP and STN neurons. The proposed specific aims will allow development of the techno