Poster abstracts
Poster number 98 submitted by Tuhin Roy
Age-dependent Kv channel compensation governs tremor emergence in the olivo-cerebellar circuit
Tuhin Roy (Interdisciplinary Biophysics Graduate Program, The Ohio State University, Columbus, OH 43210, USA), Yujia Hu (Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America), Bing Ye (Department of Cell and Developmental Biology, Medical School, University of Michigan, Ann Arbor, Michigan, United States of America), Chen Gu
Abstract:
Voltage-gated potassium (Kv) channels are key determinants of action potential firing in neurons, particularly within the olivo-cerebellar circuit that governs motor coordination. Dysfunction of this circuit has been strongly implicated in tremor disorders, including essential tremor and spinocerebellar ataxia. A specific Kv channel is expressed in Purkinje cells and deep cerebellar nuclei neurons and plays a central role in regulating their action potential firing patterns. However, its role in tremor onset and progression remains unclear. Here, we investigate age-dependent mechanisms of the dysfunction of this channel using three mouse models: parvalbumin (PV)-specific conditional knockout, global knockout, and the dominant-negative knockin mouse lines. Tremor phenotypes were quantified using AI-based video analysis (LabGym). Preliminary data show that young global knockout mice exhibit little to no tremor, whereas older knockout mice display increased tremor episodes; in contrast, knockin mice show early tremor onset, while PV-specific conditional knockouts remain tremor-free across the ages examined. These findings support a model in which early compensation by co-expressed other channel subunits preserves circuit stability, but age-dependent failure of this compensation leads to impaired high-frequency firing and tremor emergence. This work identifies the dysfunction of a potassium channel as a potential mechanism underlying age-dependent tremor progression.
Keywords: Tremor, Potassium channel, LABGYM AI analysis