Translating the Transcriptome: A Connectomics Approach for Gene-Network Mapping and Clinical Application.

Area of Science:

• Neuroscience
• Genetics
• Computational Biology

Background:

• Gene expression influences brain functional connectivity, but shared genetic networks in disorders remain unclear.
• Understanding the molecular basis of brain disorders is crucial for developing targeted therapies.

Purpose of the Study:

• To develop a framework, gene network mapping, to identify brain networks associated with gene expression.
• To create disease-network maps that represent the cumulative genetic impact on brain circuitry.
• To validate these maps using independent datasets and assess their clinical relevance.

Main Methods:

• Combined spatial transcriptomics with normative functional connectivity data.
• Generated gene-network maps for individual genes and aggregated them into disease-network maps.
• Validated maps against lesion data and deep brain stimulation (DBS) outcomes.

Main Results:

• Gene network mapping successfully identified distributed connectivity patterns for individual genes.
• Disease-network maps captured the cumulative genetic influence on brain networks.
• Network modulation predicted outcomes in deep brain stimulation cohorts, validating the maps.

Conclusions:

• Gene network mapping provides a novel tool to explore the molecular architecture of brain disorders.
• This framework supports network-informed diagnostics and therapeutics in precision medicine.
• The study highlights the convergence of genes on shared brain networks in the context of disease.