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, metabotropic), their interacting scaffolding proteins (PSD-95, Homer1b/c), plasma membrane and vesicular glutamate transporters (EAAT1, EAAT2, VGluT1, VGluT2), enzymes involved either in glutamate-dependent GABA neurotransmitter synthesis (GAD65 and 67), or in post-synaptic NMDA receptor-mediated signaling (CAMKIIα) and the pre-synaptic marker Synapsin-1. Univariable analyses revealed that none of the investigated molecules was differently represented in the post-mortem DLPFC and hippocampus of schizophrenia patients, compared with controls. Nonetheless, multivariable hypothesis-driven analyses revealed that the presence of schizophrenia was significantly affected by variations in neuroactive amino acid levels and glutamate-related synaptic elements. Furthermore, a Machine Learning hypothesis-free unveiled other discriminative clusters of molecules, one in the DLPFC and another in the hippocampus. Overall, while confirming a key role of glutamatergic synapse in the molecular pathophysiology of schizophrenia, we reported molecular signatures encompassing elements of the glutamate synapse able to discriminate patients with schizophrenia and normal individuals.

• Authors: Arianna De Rosa, Andrea Fontana, Tommaso Nuzzo, Martina Garofalo, Anna Di Maio, Daniela Punzo, Massimiliano Copetti, Alessandro Bertolino, Francesco Errico, Antonio Rampino, Andrea de Bartolomeis, Alessandro Usiello
• Journal: Schizophrenia (Heidelberg, Germany) (Schizophrenia (Heidelb)) Vol. 8 Issue 1 Pg. 8 (02 25 2022) ISSN: 2754-6993 [Print] Germany
• PMID: 35217646 (Publication Type: Journal Article)
• Copyright: © 2022. The Author(s).