Large animal models for Huntington's disease research.

Huntington's disease (HD) is a hereditary neurodegenerative disorder for which there is currently no effective treatment available. Consequently, the development of appropriate disease models is critical to thoroughly investigate disease progression. The genetic basis of HD involves the abnormal expansion of CAG repeats in the huntingtin ( HTT) gene, leading to the expansion of a polyglutamine repeat in the HTT protein. Mutant HTT carrying the expanded polyglutamine repeat undergoes misfolding and forms aggregates in the brain, which precipitate selective neuronal loss in specific brain regions. Animal models play an important role in elucidating the pathogenesis of neurodegenerative disorders such as HD and in identifying potential therapeutic targets. Due to the marked species differences between rodents and larger animals, substantial efforts have been directed toward establishing large animal models for HD research. These models are pivotal for advancing the discovery of novel therapeutic targets, enhancing effective drug delivery methods, and improving treatment outcomes. We have explored the advantages of utilizing large animal models, particularly pigs, in previous reviews. Since then, however, significant progress has been made in developing more sophisticated animal models that faithfully replicate the typical pathology of HD. In the current review, we provide a comprehensive overview of large animal models of HD, incorporating recent findings regarding the establishment of HD knock-in (KI) pigs and their genetic therapy. We also explore the utilization of large animal models in HD research, with a focus on sheep, non-human primates (NHPs), and pigs. Our objective is to provide valuable insights into the application of these large animal models for the investigation and treatment of neurodegenerative disorders.

Genetically-directed Sparse Neuronal Labeling in BAC Transgenic Mice through Mononucleotide Repeat Frameshift.

Mosaicism with Repeat Frameshift (MORF) allows a single Bacterial Artificial Chromosome (BAC) transgene to direct sparse labeling of genetically-defined neuronal populations in mice. The BAC transgene drives cell-type-specific transcription of an out-of-frame mononucleotide repeat that is placed between a translational start codon and a membrane-bound fluorescent protein lacking its start codon. The stochastic frameshift of the unstable repeat DNA in a subset of BAC-expressing neurons results in the in-frame translation of the reporter protein hence the sparse neuronal labeling. As a proof-of-concept, we generated D1-dopamine receptor (D1) BAC MORF mice that label about 1% striatal D1-expressing medium spiny neurons and allow visualization of their dendrites. These mice enable the study of D1-MSN dendrite development in wildtype mice, and its degeneration in a mouse model of Huntington's disease.

Metabolic profiling of presymptomatic Huntington's disease sheep reveals novel biomarkers.

The pronounced cachexia (unexplained wasting) seen in Huntington's disease (HD) patients suggests that metabolic dysregulation plays a role in HD pathogenesis, although evidence of metabolic abnormalities in HD patients is inconsistent. We performed metabolic profiling of plasma from presymptomatic HD transgenic and control sheep. Metabolites were quantified in sequential plasma samples taken over a 25 h period using a targeted LC/MS metabolomics approach. Significant changes with respect to genotype were observed in 89/130 identified metabolites, including sphingolipids, biogenic amines, amino acids and urea. Citrulline and arginine increased significantly in HD compared to control sheep. Ten other amino acids decreased in presymptomatic HD sheep, including branched chain amino acids (isoleucine, leucine and valine) that have been identified previously as potential biomarkers of HD. Significant increases in urea, arginine, citrulline, asymmetric and symmetric dimethylarginine, alongside decreases in sphingolipids, indicate that both the urea cycle and nitric oxide pathways are dysregulated at early stages in HD. Logistic prediction modelling identified a set of 8 biomarkers that can identify 80% of the presymptomatic HD sheep as transgenic, with 90% confidence. This level of sensitivity, using minimally invasive methods, offers novel opportunities for monitoring disease progression in HD patients.