Abstract

DYT1 or DYT-TOR1A dystonia is early-onset generalized dystonia caused by a trinucleotide deletion of GAG in the TOR1A or DYT1 gene leads to the loss of a glutamic acid residue in the resulting torsinA protein. A mouse model with overt dystonia is of unique importance to better understand the DYT1 pathophysiology and evaluate preclinical drug efficacy. DYT1 dystonia is likely a network disorder involving multiple brain regions, particularly the basal ganglia. Tor1a conditional knockout in the striatum or cerebral cortex leads to motor deficits, suggesting the importance of corticostriatal connection in the pathogenesis of dystonia. Indeed, corticostriatal long-term depression impairment has been demonstrated in multiple targeted DYT1 mouse models. Pappas and colleagues developed a conditional knockout line (Dlx-CKO) that inactivated Tor1a in the forebrain and surprisingly displayed overt dystonia. We set out to validate whether conditional knockout affecting both cortex and striatum would lead to overt dystonia and whether machine learning-based video behavioral analysis could be used to facilitate high throughput preclinical drug screening. We generated Dlx-CKO mice and found no overt dystonia or motor deficits at 4 months. At 8 months, retesting revealed motor deficits in rotarod, beam walking, grip strength, and hyperactivity in the open field; however, no overt dystonia was visually discernible or through the machine learning-based video analysis. Consistent with other targeted DYT1 mouse models, we observed age-dependent deficits in the beam walking test, which is likely a better motor behavioral test for preclinical drug testing but more labor-intensive when overt dystonia is absent.

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