De Simone, Giuseppe (2026) Altered interactions between monoaminergic and glutamatergic neurotransmission in schizophrenia: insights from a bi-regional network analysis of postmortem tissues. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Altered interactions between monoaminergic and glutamatergic neurotransmission in schizophrenia: insights from a bi-regional network analysis of postmortem tissues
Autori:
Autore
Email
De Simone, Giuseppe
giuseppe.desimone2@unina.it
Data: Febbraio 2026
Numero di pagine: 85
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Neuroscienze e Scienze Riproduttive ed Odontostomatologiche
Dottorato: Neuroscienze
Ciclo di dottorato: 38
Coordinatore del Corso di dottorato:
nome
email
Taglialatela, Maurizio
[non definito]
Tutor:
nome
email
de Bartolomeis, Andrea
[non definito]
Data: Febbraio 2026
Numero di pagine: 85
Parole chiave: Schizophrenia Postsynaptic Density Dopamine
Settori scientifico-disciplinari del MIUR: Area 06 - Scienze mediche > MED/25 - Pschiatria
Informazioni aggiuntive: Appartengo al ciclo 38
Depositato il: 16 Feb 2026 10:52
Ultima modifica: 02 Set 2026 08:06
URI: https://www.fedoa.unina.it/id/eprint/16224

Abstract

Schizophrenia is a severe mental illness characterized by significant impairments in social and occupational functioning, whose neurobiology increasingly points to altered integration of glutamatergic and monoaminergic signaling across multiple spatial scales. This thesis investigates microscale dysconnectivity between glutamatergic and monoaminergic pathways in schizophrenia by applying an intersubject network analysis to postmortem dorsolateral prefrontal cortex (DLPFC) and hippocampal tissues from 20 patients with schizophrenia and 20 non-psychiatric controls. Concentrations of 38 molecular effectors, including amino acids, monoamines, glutamate receptors and transporters, synaptic proteins, and catabolic enzymes, were quantified using high-performance liquid chromatography and Western blotting at the Neuroscience Lab of CEINGE - Advanced Biotechnologies. Missing data were handled through multiple imputation by chained equations, and molecular networks were estimated using conditional mutual information combined with autoencoder-based dimensionality reduction to capture both linear and non-linear associations while mitigating high-dimensional bias. Group differences in global strength, node strength, and pairwise edge weights were assessed via permutation testing with cluster-based correction for multiple comparisons. Results revealed region- and hierarchy-specific patterns of molecular dysconnectivity in schizophrenia. Global connectivity was preserved in the DLPFC but significantly reduced in the hippocampus, where several nodes, including dopamine, GluA4, GLT-1, 5-HIAA, CaMKII, NR1, Synapsin I, and DOPAC, showed decreased degree in patients compared with controls. At the edge level, most alterations involved glutamatergic components across pre- and postsynaptic compartments, as well as cross-system interactions between monoamines and glutamatergic effectors, indicating disrupted integration of synaptic signaling across the cleft. Dopamine emerged as a central hub with reduced weighted degree in both regions, suggesting a network-level impairment of dopaminergic modulation of glutamatergic plasticity. Taken together, these findings extend the dysconnectivity hypothesis of schizophrenia to the molecular domain, showing that alterations in glutamate-monoamine interactions are reflected in reorganized synaptic networks within DLPFC and hippocampus. By leveraging an entropy- and autoencoder-based framework for network estimation, this work further provides a novel methodology for intersubject molecular network analysis.

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