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Updated: Feb 28, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Mapping spatially organized molecular and genetic signatures of schizophrenia across multiple scales in human
Sang Ho Kwon1,2,3, Boyi Guo4,5, Cindy Fang4
1Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Abstract:
The dorsolateral prefrontal cortex (dlPFC) controls many cognitive and emotional processes that are disrupted in schizophrenia (SCZ). However, the spatial location of molecular changes associated with SCZ within the dlPFC remains poorly characterized. dlPFC cell types are spatially organized across six layers into microcircuits that mediate dlPFC function. While SCZ has been linked to regionally-defined cell types, spatially-resolved transcriptomics (SRT) can more directly map molecular associations of disease. We integrated protein detection for perineuronal nets, neurons and vasculature with SRT to investigate how gene expression varies across different cellular microenvironments in the human dlPFC from neurotypical control (n=31) and SCZ (n=32) brain donors. We mapped transcriptional alterations in synaptic, neuroimmune and metabolic pathways to neuropil and glia-enriched domains including the white matter. Integrative analyses linked laminar alterations predominantly to non-neuronal populations, and in situ profiling further resolved these changes at cellular resolution, indicating intracellular transcriptional changes that may underpin SCZ-associated alterations. By mapping SCZ-associated ligand-receptor pairs, we curated altered patterns of cell-cell communication that may coordinate local signaling dynamics across specialized tissue microenvironments. Finally, analyses that integrate SCZ genetic risk further highlight the significance of neuron-glia interactions, suggesting that neuronal genetic liability may signal through non-neuronal alterations across cortical domains. This multimodal atlas provides a spatial-anatomical framework for linking genetic risk to transcriptional phenotypes in the human cortex, delineating SCZ-associated gene expression landscapes across layers, single cells, and microenvironments. The data is available as a browsable PsychENCODE resource to support broad utilization that can inform mechanistic studies investigating SCZ pathology and risk.
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