Florian J. Raabe, David Popovic, Clara Vetter, Laura E. Fischer, Genc Hasanaj, Berkhan Karslı, Tim Schäfer, Valeria Almeida, Alessia Atella, Miriam Gagliardi, Emanuel Boudriot, Vladislav Yakimov, Lucia Trastulla, Tengjia Jiang, Clara Weyer, Lukas Roell, Joanna Moussiopoulou, Lenka Krčmář, Sabrina Galinski, I. Papazova, Oliver Pogarell, Alkomiet Hasan, E Schulte, Andrea Schmitt, Nikolaos Koutsouleris, Anna Levina, Elias Wagner, Moritz J. Rossner, Sergi Papiol, Peter Falkai, D. Keeser, Michael J. Ziller, CDP Working Group, Stephanie Behrens, Emanuel Boudriot, Man-Hsin Chang, Valéria de Almeida, Sylvia de Jonge, Fanny Dengl, Lina Dürrwald, Peter Falkai, Laura E. Fischer, Nadja Gabellini, Vanessa Gabriel, Sabrina Galinski, Thomas Geyer, Katharina Hanken, Alkomiet Hasan, Genc Hasanaj, Alexandra Hisch, Georgios Ioannou, Marcus Ising, Iris Jäger, Tengjia Jiang, Marcel S. Kallweit, Temmuz Karali, Susanne Karch, Berkhan Karslı, D. Keeser, Christoph Kern, Nicole Klimas, Maxim Korman, Nikolaos Koutsouleris, Lenka Krčmář, Verena Meisinger, Julian Melcher, Matin Mortazavi, Joanna Moussiopoulou, Karin Neumeier, Frank Padberg, Boris Papazov, I. Papazova, Sergi Papiol, Pauline Pingen, Oliver Pogarell, Siegfried G. Priglinger, Florian J. Raabe, Lukas Roell, Moritz J. Rossner, Philipp G. Sämann, Andrea Schmitt, Susanne Schmölz, E Schulte, Enrico Schulz, Benedikt Schworm, Sophie Seeburger, Elias Wagner, Sven P. Wichert, Vladislav Yakimov, Peter Zill, Michael J. Ziller
Importance: While growing evidence implicates synaptic dysfunction as a key pathophysiological mechanism in cognitive impairments in schizophrenia (SCZ), it remains unknown how individual alterations in synaptic connectivity translate into corresponding neural circuit dysfunction and cognitive deficits. Objective: To test whether genetically driven variability in excitatory neurons' transcriptome and synapse density in patient-derived neurons in vitro explain individual changes in cortical morphology, electrophysiology, and cognitive impairments in vivo. Design, Setting, and Participants: This multimodal case-control study integrated deep clinical phenotyping (magnetic resonance imaging, electroencephalography, and cognitive assessments) across 2 independent cohorts with schizophrenia and healthy controls (N = 461) with donor-matched induced pluripotent stem cell (iPSC)-derived neurons (n = 80). Machine learning, transcriptome imputation, and reverse dynamic causal modeling were applied to link cellular and systems-level phenotypes. Data were collected between September 16, 2014, and November 10, 2023, and analyzed from January 2022 to January 2026. Main Outcomes and Measures: The primary outcome was associations between cellular phenotypes (gene expression, synapse density) and individual-level brain structure, electrophysiology, and cognition. Results: This multiscale translational framework was implemented in 461 individuals with SCZ and healthy controls across 2 independent cohorts. In both cohorts (cohort 1 [C1]: mean [SD] age: 35.1 [11.6] years; 46 female participants [31.1%]; cohort 2 [C2]: mean [SD] age, 36.9 [11.7] years; 140 female participants [44.57%]), cognitive impairments in SCZ were associated with specific gray matter volume reductions across multiple brain regions, in particular the right dorsolateral prefrontal cortex, as well as disturbed electrophysiological activity in the gamma band. Importantly, the individual-level differences in the genetically driven neuronal gene expression patterns and synapse density in vitro predicted the macro-scale alterations of brain structural (C1: r = 0.39; 95% CI, 0.21-0.55; P < .001; iPSC: r = 0.31; 95% CI, -0.07 to 0.60; P = .049; C2: r = 0.23; 95% CI, 0.07-0.37; P = .003), electrophysiological (theta: r = 0.19; 95% CI, 0.04-0.32; P = .05; gamma1: r = 0.17; 95% CI, 0.028-0.31; P = .005; gamma2: r = 0.22; 95% CI, 0.07-0.35; P < .001), and cognitive (C1: r = 0.76; 95% CI, 0.66-0.83; P < .001; iPSC: r = 0.77; 95% CI, 0.57-0.89; P < .001; C2: r = 0.17; 95% CI, 0.02-0.32; P = .02) phenotypes in vivo, providing a mechanistic link from synapse deficits to cognitive impairments in SCZ. Conclusions and Relevance: These findings establish a patient-specific link between genetically driven alterations in gene expression, synaptic dysfunction, and large-scale brain and cognitive phenotypes in SCZ. This multiscale framework provides a foundation for mechanism-based stratification and precision target identification for cognitive impairment.