Machine Learning algorithm unveils glutamatergic alterations in the post-mortem schizophrenia brain.

ABSTRACT: Schizophrenia is a disorder of synaptic plasticity and aberrant connectivity in which a major dysfunction in glutamate synapse has been suggested. However, a multi-level approach tackling diverse clusters of interacting molecules of the glutamate signaling in schizophrenia is still lacking. We investigated in the post-mortem dorsolateral prefrontal cortex (DLPFC) and hippocampus of schizophrenia patients and non-psychiatric controls, the levels of neuroactive D- and L-amino acids (L-glutamate, D-serine, glycine, L-aspartate, D-aspartate) by HPLC. Moreover, by quantitative RT-PCR and western blotting we analyzed, respectively, the mRNA and protein levels of pre- and post-synaptic key molecules involved in the glutamatergic synapse functioning, including glutamate receptors (NMDA, AMPA, meta

SUBMITTER: De Rosa A 

PROVIDER: S-EPMC8881508 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature