Back

Bradykinesia and postural instability in a model of prodromal Synucleinopathy with alpha-Synuclein aggregation in the gigantocellular nuclei.

Theologidis, V.; Ferreira, S. A.; Jensen, N. M.; Gomes Moreira, D.; Ahlgreen, O. A.; Hansen, M. W.; Rosenberg, E. D.; Richner, M.; Faress, I.; Gram, H.; Jensen, P. H.; Borghammer, P.; Nyengaard, J. R.; Romero-Ramos, M.; Vaegter, C. B.; van de Berg, W. D. J.; Van Den Berge, N.; Jan, A.

2024-09-09 neuroscience
10.1101/2024.09.05.610956 bioRxiv
Show abstract

-Synuclein (aSyn) accumulation within the extra-nigral neuronal populations in brainstem, including the gigantocellular nuclei (GRN/Gi) of reticular formation, is a recognized feature during the prodromal phase of Parkinson disease (PD). Accordingly, there is a burgeoning interest in animal model development for understanding the pathological significance of extra-nigral synucleinopathy, in relation to motor and/or non-motor symptomatology in PD. Here, we report an experimental paradigm for the induction of aSyn aggregation in brainstem, with stereotaxic delivery of pre-formed fibrillar (PFF) aSyn in the pontine GRN of transgenic mice expressing the mutant human Ala53Thr aSyn (M83 line). Our data show that PFF aSyn-induced aggregate pathology in GRN leads to progressive decline in spontaneous locomotion and an early phenotype of postural instability. This early phase of bradykinesia was followed by a moribund stage, characterized by worsening motor performance and impaired survival with substantial aSyn aggregation in several brain regions beyond the GRN. Collectively, our observations suggest an experimental framework for studying the pathological significance of aSyn aggregation in GRN in relation to features of movement disability in PD. With further refinements, we anticipate that this model holds promise as a test-bed for translational research in PD and related disorders.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.