Sleep and circadian rhythm disturbance has been widely observed in neurological disorders although the mechanistic basis for this association remains unknown. In order to understand this association further, a combination of rest/activity and molecular profiling was carried out on mouse models of Parkinson’s Disease (PD), Lysosomal Storage Disorders (LSDs) and schizophrenia. Data from rest/activity behavioural screening of new BAC (Bacterial Artificial Chromosome) transgenic PD models displayed scotophase hyperactivity and decreased fragmentation patterns. Interestingly, rest/activity profiles of LSD models displayed possible core clock defects under constant conditions (Hexb<sup>-/-</sup>) and potential re-entrainment deficits following a 6hr phase advance (Npc1<sup>-/-</sup>). Together these data suggest new associations between disruptions in rest/activity cycles and neurodegeneration. The blind-drunk (Bdr) mutant is a mouse model of synaptosomal-associated protein (Snap)-25 exocytotic disruption that displays schizophrenic endophenotypes and phase advanced rest/activity cycles. Despite identification of phase advanced expression of signalling neuropeptides (e.g. arginine vasopressin) in the Bdr suprachiasmatic nucleus (SCN), the underlying mechanisms regulating circadian disruption in this model remain elusive; therefore, label-free shotgun proteomics was carried out over 24 hours to elucidate potential post-transcriptional pathways. A number of novel circadian patterns of protein expression were identified including myristoylated alanine-rich C-kinase substrate (MARCKS) which exhibited a robust phase advanced expression profile. This study has identified novel SCN post-transcriptional mechanisms that may link schizoaffective disorder biomarkers to dysfunctional rest/activity cycles.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:618411 |
| Date | January 2013 |
| Creators | Livieratos, Achilleas |
| Contributors | Davies, Kay Elizabeth |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:a03f34d5-285d-464b-b676-21b493db7f56 |
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