Computational modeling and preclinical evaluation support targeting somatic instability for Huntington’s disease treatment

Genetic modifiers of Huntington’s disease (HD) disease onset and progression implicate somatic instability (SI) of the expanded CAG repeat as a key pathogenic driver, with MSH3 emerging as a therapeutic target. Here, we generated a computational model that uses HD patient data to infer therapeutic effects of reducing SI and in parallel designed an artificial miRNA to lower MSH3 mRNA (miMSH3) after delivery with AAV-DB-3, a previously described medium spiny neuron (MSN)-targeting AAV capsid variant. AAV-DB-3.miMSH3 achieved 48–94% MSH3 mRNA reduction in MSNs of nonhuman primates (NHPs), which when applied to predictive modeling predicts 50–120 % slowing of HD progression as measured by change from baseline in the composite Unified Huntington Disease Rating Scale. Additionally, AAV-DB-3.miMSH3 reduced SI reduction by up to 46% in HdhQ111 mice. Cumulatively, the preclinical experimental data and the computational model support the translational potential of AAV-DB-3.miMSH3 as a disease-modifying therapy for HD. A one-time gene therapy targeting MSH3 reduced the expansion of HD-causing DNA repeats in preclinical studies. Patient-based modeling predicts this approach could delay symptom onset by years and meaningfully slow Huntington’s disease progression.