Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n=35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (p adj =6.73x10-6). Novel reciprocal case-control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.

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Extrinsic signaling between diverse cell types is crucial to nervous system development. Ligand binding is a key driver of developmental processes, but it remains a significant challenge to disentangle how collections of these signals act cooperatively to affect changes in recipient cells. In the developing human brain, cortical progenitors transition from neurogenesis to gliogenesis in a stereotyped progression that is influenced by extrinsic ligands. Therefore, we sought to use the wealth of published genomic data in the developing human brain to identify and then test novel ligand combinations that act synergistically to drive gliogenesis. Using computational tools, we identified ligand-receptor pairs that are expressed at appropriate developmental stages, in relevant cell types, and whose activation is predicted to cooperatively stimulate complimentary astrocyte gene signatures. We then tested a group of five neuronally-secreted ligands and validated their synergistic contributions to astrocyte development within both human cortical organoids and primary fetal tissue. We confirm cooperative capabilities of these ligands far greater than their individual capacities and discovered that their combinatorial effects converge on AKT/mTOR signaling to drive transcriptomic and morphological features of astrocyte development. This platform provides a powerful agnostic framework to identify and test how extrinsic signals work in concert to drive developmental processes.