# From synapse to system: mechanistic pathways of neural signaling dysfunction in psychiatric disorders

## TL;DR

This paper explores how disruptions in neural signaling at multiple levels contribute to psychiatric disorders and how integrating various scientific methods can lead to better precision treatments.

## Contribution

The paper introduces a framework connecting molecular and systems-level neural signaling disruptions in psychiatric disorders using genomics, connectomics, and AI.

## Key findings

- Receptor dysregulation and intracellular pathway changes lead to network dysconnectivity in psychiatric disorders.
- Genetic variations in genes like CACNA1C and DISC1 contribute to network vulnerability and clinical heterogeneity.
- Integrated methods using AI and connectomics help identify individualized signaling fingerprints for precision psychiatry.

## Abstract

Psychiatric disorders are increasingly viewed as network-level brain diseases resulting from disruptions in neural signaling across various hierarchies, including molecular, synaptic, circuit, and systems levels. Evidence indicates that receptor dysregulation, abnormal intracellular pathways, and changes in ion channel activity lead to widespread network dysconnectivity, resulting in cognitive, emotional, and behavioral deficits. This review integrates advancements in genomics, transcriptomics, connectomics, and computational modeling to establish a framework for understanding signaling abnormalities in major psychiatric disorders. Further, this study investigates essential molecular and cellular processes such as synaptic plasticity, receptor-mediated communication, intracellular signaling cascades, and neuroimmune interactions, and connects these to disturbances in oscillatory dynamics, circuit architecture, and overall brain network organization. Additionally, neuroimaging and graph-theoretic studies consistently demonstrate an excitation–inhibition imbalance, atypical synaptic pruning, impaired oscillatory synchrony, and maladaptive connectivity within networks, including the default mode, salience, and fronto-limbic systems, across schizophrenia, depression, bipolar disorder, anxiety, and autism spectrum disorders. Moreover, genetic and epigenetic variations in signaling genes, such as CACNA1C, GRIN2B, and DISC1, along with developmental and environmental factors, contribute to network vulnerability and clinical heterogeneity. Emerging artificial intelligence and multimodal integration methods facilitate the identification of individualized “signaling fingerprints,” which connect molecular perturbations to systems-level dysfunction. This research enhances precision psychiatry and guides targeted interventions based on neuromodulation, molecular mechanisms, and biomarkers.

Multilevel disturbances in neuropsychiatric diseases encompass molecular, synaptic, and cellular levels, resulting in circuit-level dysconnectivity and modified whole-brain connectomes. Impaired neurotransmission, abnormal synaptic signaling, and impaired neural communication lead to functional network imbalance. Further, integrated methodologies that merge genomes, connectomics, and AI modeling with targeted neuromodulation, molecular treatments, and biomarker methods seek to connect molecular dysfunctions with a systems-level comprehension and inform precision interventions in neuropsychiatric disorders.Diagram illustrating brain research from molecular, synaptic, and cellular dysfunctions to neural circuit interactions, connectome mapping, and integrated approaches including genomics, connectomics, artificial intelligence modeling, neuromodulation, molecular therapies, and biomarker strategies.

Multilevel disturbances in neuropsychiatric diseases encompass molecular, synaptic, and cellular levels, resulting in circuit-level dysconnectivity and modified whole-brain connectomes. Impaired neurotransmission, abnormal synaptic signaling, and impaired neural communication lead to functional network imbalance. Further, integrated methodologies that merge genomes, connectomics, and AI modeling with targeted neuromodulation, molecular treatments, and biomarker methods seek to connect molecular dysfunctions with a systems-level comprehension and inform precision interventions in neuropsychiatric disorders.