This review reveals how AI-driven transcriptomic analysis identifies therapeutic targets in Huntington's disease, suggesting new treatment pathways.
Huntington’s disease (HD) is an autosomal dominant neurodegenerative disorder characterized by progressive motor dysfunction, psychiatric disturbances, and cognitive decline. The pathophysiology of HD centers on a polyglutamine expansion in the huntingtin protein, which triggers widespread transcriptional dysregulation, impaired proteostasis, mitochondrial dysfunction, and excitotoxic neuronal loss—most prominently within the striatum and cortex. Despite decades of research, disease-modifying therapies remain elusive. This review synthesizes how the emerging integration of translational bioinformatics, spotlighting artificial intelligence-driven transcriptomic analyses, has identified transcriptional signatures correlating with disease progression and therapeutic response. These integrative approaches hold promise for accelerating the bench-to-bedside translation of HD therapeutics, positioning AI-powered discovery as a frontier for overcoming the complexity of neurodegeneration.
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Araldi et al. (2025) studied this question.
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