npj Schizophrenia (Feb 2022)

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

  • 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

DOI
https://doi.org/10.1038/s41537-022-00231-1
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 16

Abstract

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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.