Abstract
Genome wide association studies of schizophrenia reveal a complex polygenic risk architecture comprised of hundreds of risk variants; most are common in the population, non-coding, and act by genetically regulating the expression of one or more gene targets (“eGenes”). It remains unclear how the myriad genetic variants that are predicted to confer individually small effects combine to yield substantial clinical impacts in aggregate. Here, we demonstrate that convergence (i.e., the shared downstream transcriptomic changes with a common direction of effect), resulting from one-at-a-time perturbation of schizophrenia eGenes, influences the outcome when eGenes are manipulated in combination. In total, we apply pooled and arrayed CRISPR approaches to target 21 schizophrenia eGenes in human induced pluripotent stem cell-derived glutamatergic neurons, finding that functionally similar eGenes yield stronger and more specific convergent effects. Points of convergence constrain additive relationships between polygenic risk loci: consistent with a liability threshold model, combinatorial perturbations of these same schizophrenia eGenes reveal that pathway-level convergence predicts when observed effects will fail to sum to levels predicted by an additive model. Targeting points of convergence as novel therapeutic targets may prove more efficacious than individually reversing the effects of multiple risk loci.
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Data availability
All source donor hiPSCs have already been deposited at the Rutgers University Cell and DNA Repository (study 160; http://www.nimhstemcells.org/). All vectors are available at https://www.addgene.org/Kristen_Brennand/. Bulk and single-cell RNA sequencing data are available at the Gene Expression Omnibus under accession code GSE200774. Processed data can be accessed through Synapse under Synapse accession code syn27819129 [https://www.synapse.org/Synapse:syn27819129/wiki/623524]. For the pooled and arrayed CRISPR analyses, all raw FASTQ Count files and corresponding processed data are available on the Gene Expression Omnibus under GEO accession code GSE200774). Average expression count matrices and metadata following quality control and normalization of ECCITE-seq data, as well as results of differential gene expression analysis and Target Network Reconstruction of Bayesian Bi-clustering are available on Synapse accession code syn27819129 [https://www.synapse.org/Synapse:syn27819129/wiki/623524. All corresponding code was uploaded to Synapse under accession code syn27819129 [https://www.synapse.org/Synapse:syn27819129/wiki/623524]). DEGs, GSEA tables, synergy sub-categories, and synergy sub-category over-representation analysis for arrayed screen RNA-seq data; individual scRNA-seq perturbation DEGs and pathway enrichments from pooled experiments; reconstructed convergent networks and convergent network enrichment results (FUMA, ClusterProfiler, ORA of common/rare/variants) from arrayed and pooled screens; and CMAP drug prioritization queries and GSEA for 10 targets and each individual perturbation signature used in CMAP query are available in Supplementary Data Files 1–4.
Code availability
Code used for the convergence and additivity analyses presented in this manuscript can be accessed through Synapse under Synapse accession code syn27819129 [https://www.synapse.org/Synapse:syn27819129/wiki/623524].
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Acknowledgements
Special thanks to Michael Talkowski and Douglas Ruderfer for countless discussions on convergence, and to Naomi Wray for thoughtful insights and contextualizations of our analyses on non-additive effects.
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SCZ eGene lists were prioritized by E.S., L.M.H., W.Z., G.V. and P.R., together with K.J.B. Epigenome data provided by K.G., S.A. and P.R. iGLUT transcriptomic and phenotypic studies were conducted by P.J.M.D., with assistance by E.C. Synergy analysis was conceptualized by N.S. and applied by P.J.M.D.; convergent analyses were conceptualized by K.G.R-T. and applied by C.S. Transcriptomic imputation was conducted by J.J. and L.M.H.; pathway-specific PRS by J.G.G. and P.O. The ECCITE-seq pipeline was adapted to hiPSC-neurons by A.L., supported by P.J.M.D., J.F.F., A.Y., S.C and B.Z. ECCITE-seq iGLUT neuron studies were conducted by A.L. and P.J.M.D. 10x analyses were conducted by J.F.F., and preliminary ECCITE-seq quality control was conducted by M.W. Convergent analyses were conceptualized by K.J.B. and L.H., developed and conducted entirely by K.G.R-T. The paper was written by P.J.M.D., K.G.R-T., L.H., and K.J.B., with input from all authors. The following pairs of authors contributed equally to this manuscript: P.J.M.D. and K.G.R-T; C.S. and A.L.; J.J. and J.G.G. This work was supported by F31MH130122 (K.G.R-T.), R01MH109897 (K.J.B., P.R.), R56MH101454 (K.J.B., E.S., L.M.H.), R01MH123155 (K.J.B.) and R01ES033630 (L.M.H., K.J.B.), R01MH124839 (L.M.H.), R01MH118278 (L.M.H.), R01MH106056 (K.J.B and S.A.), U01DA047880 (K.J.B and S.A), R01DA048279 (K.J.B and S.A), T35DK104689-07 (E.C.), K08MH122911 (G.V.). R01MH125246 (P.R.), U01MH116442 (P.R.), R01MH109677 (P.R.), I01BX002395 (P.R.), and by the State of Connecticut, Department of Mental Health and Addiction Services. This publication does not express the views of the Department of Mental Health and Addiction Services or the State of Connecticut.
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E.S. is today an employee at Regeneron. K.J.B. is on the advisory board of Cell Stem Cell and a scientific advisor to Rumi Scientific Inc. and Neuro Pharmaka Inc. The remaining authors declare that they have no competing interests.
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Michael Deans, P., Retallick-Townsley, K.G., Li, A. et al. Functional implications of polygenic risk for schizophrenia in human neurons. Nat Commun (2026). https://doi.org/10.1038/s41467-025-67959-z
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DOI: https://doi.org/10.1038/s41467-025-67959-z
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