Analysis Of Molecular Networks In The Cerebellum In Chronic Schizophrenia: Modulation By Early Postnatal Life Stressors In Murine Models

2021 
Despite the growing importance of the cortico-cerebellar-thalamo-cortical circuit in schizophrenia, limited information is available regarding altered molecular networks in cerebellum. To identify altered protein networks, we conducted proteomic analysis of grey matter of postmortem cerebellar cortex in chronic schizophrenia subjects (n=12) and healthy individuals (n=14) followed by an extensive bioinformatic analysis. Two double-hit postnatal stress murine models for SZ were used to validate the most robust candidates. The models were maternal deprivation combined with an additional stressor: social isolation or chronic restraint stress. We found that the individual proteomic profile allowed the segregation of most schizophrenia cases from healthy individuals. We found 250 proteins with altered levels. This group was enriched in proteins related to mental disorders, mitochondrial disease, stress, and a number of biological functions including energy, immune response, axonal cytoskeletal organization and vesicle-mediated transport. Network analysis identified three modules: energy metabolism, neutrophil degranulation and a mixed module of mainly axonal-related functions. We analysed the most robust candidates in the networks in two double-hit stress murine models. METTL7A from the degranulation pathway was reduced in both models, while NDUFB9 from the energy network and CLASP1 from the axonal module decreased in only one model. This work provides evidence for altered energy, immune and axonal-related networks in the cerebellum in schizophrenia, suggesting that the accumulation of molecular errors, some by an early postnatal stress exposure, could lead to a failure in the normal cerebellar functions, impairing synaptic response and the defence mechanisms of this region against external harmful injuries in schizophrenia.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    82
    References
    0
    Citations
    NaN
    KQI
    []