INTRODUCTION Chromosomal conformations, topologically associated chromatin domains (TADs) assembling in nested fashion across hundreds of kilobases, and other “three-dimensional genome” (3DG) structures bypass the linear genome on a kilo- or megabase scale and play an important role in transcriptional regulation. Most of the genetic variants associated with risk for schizophrenia (SZ) are common and could be located in enhancers, repressors, and other regulatory elements that influence gene expression; however, the role of the brain’s 3DG for SZ genetic risk architecture, including developmental and cell type–specific regulation, remains poorly understood. RATIONALE We monitored changes in 3DG after isogenic differentiation of human induced pluripotent stem cell–derived neural progenitor cells (NPCs) into neurons or astrocyte-like glial cells on a genome-wide scale using Hi-C. With this in vitro model of brain development, we mapped cell type–specific chromosomal conformations associated with SZ risk loci and defined a risk-associated expanded genome space. RESULTS Neural differentiation was associated with genome-wide 3DG remodeling, including pruning and de novo formations of chromosomal loopings. The NPC-to-neuron transition was defined by the pruning of loops involving regulators of cell proliferation, morphogenesis, and neurogenesis, which is consistent with a departure from a precursor stage toward postmitotic neuronal identity. Loops lost during NPC-to-glia transition included many genes associated with neuron-specific functions, which is consistent with non-neuronal lineage commitment. However, neurons together with NPCs, as compared with glia, harbored a much larger number of chromosomal interactions anchored in common variant sequences associated with SZ risk. Because spatial 3DG proximity of genes is an indicator for potential coregulation, we tested whether the neural cell type–specific SZ-related “chromosomal connectome” showed evidence of coordinated transcriptional regulation and proteomic interaction of the participating genes. To this end, we generated lists of genes anchored in cell type–specific SZ risk-associated interactions. Thus, for the NPC-specific interactions, we counted 386 genes, including 146 within the risk loci and another 240 genes positioned elsewhere in the linear genome but connected via intrachromosomal contacts to risk locus sequences. Similarly, for the neuron-specific interactions, we identified 385 genes: 158 within risk loci and 227 outside of risk loci. Last, for glia-specific interactions, we identified 201 genes: 88 within and 113 outside of risk loci. We labeled the genes located outside of schizophrenia risk loci as “risk locus–connect,” which we define as a collection of genes identified only through Hi-C interaction data, expanding—depending on cell type—by 50 to 150% the current network of known genes overlapping risk sequences that is informed only by genome-wide association studies. This disease-related chromosomal connectome was associated with “clusters” of coordinated gene expression and protein interactions, with at least one cluster strongly enriched for regulators of neuronal connectivity and synaptic plasticity and another cluster for chromatin-associated proteins, including transcriptional regulators. CONCLUSION Our study shows that neural differentiation is associated with highly cell type–specific 3DG remodeling. This process is paralleled by an expansion of 3DG space associated with SZ risk. Specifically, developmentally regulated chromosomal conformation changes at SZ-relevant sequences disproportionally occurred in neurons, highlighting the existence of cell type–specific disease risk vulnerabilities in spatial genome organization. 3DG remodeling across neuronal differentiation with parallel expansion of SZ risk space. (Left) Chromatin conformation assays reveal pruning of short-range loops in neurons along with widening of TADs upon differentiation from NPCs. (Right) Cell type–specific chromatin interactions, functionally validated with CRISPR assays, expand the network of known risk-associated genes (blue circle), which show evidence for coregulation at the transcriptomic and proteomic levels.