Gene expression shapes the brain's functional connectome, yet it is unclear whether genes linked to the same disorder converge on shared networks. We introduce gene network mapping-a framework combining spatial transcriptomics with normative functional connectivity to identify networks associated with gene expression. By generating gene-network maps, we captured distributed connectivity patterns for individual genes. Aggregating these across genes implicated in the same disorder yielded disease-network maps that captured the cumulative genetic impact on brain networks. We validated these maps by comparing them to lesion-derived networks and testing whether modulation of these networks predicted outcomes in deep brain stimulation (DBS) cohorts. This framework offers a novel tool to study the molecular architecture of brain disorders and supports the network-informed diagnostics and therapeutics in precision medicine.