Genetic studies of schizophrenia (SCZ) reveal a complex polygenic risk architecture comprised of hundreds of risk variants, the majority of which are common in the population at-large and confer only modest increases in disorder risk. Precisely how genetic variants with individually small predicted effects on gene expression combine to yield substantial clinical impacts in aggregate is unclear. Towards this, we previously reported that the combinatorial perturbation of four SCZ risk genes ("eGenes", whose expression is regulated by common variants) resulted in gene expression changes that were not predicted by individual perturbations, being most non-additive among genes associated with synaptic function and SCZ risk. Now, across fifteen SCZ eGenes, we demonstrate that non-additive effects are greatest within groups of functionally similar eGenes. Individual eGene perturbations reveal common downstream transcriptomic effects ("convergence"), while combinatorial eGene perturbations result in changes that are smaller than predicted by summing individual eGene effects ("sub-additive effects"). Unexpectedly, these convergent and sub-additive downstream transcriptomic effects overlap and constitute a large proportion of the genome-wide polygenic risk score, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. Single eGene perturbations likewise fail to predict the magnitude or directionality of cellular phenotypes resulting from combinatorial perturbations. Overall, our results indicate that polygenic risk cannot be extrapolated from experiments testing one risk gene at a time and must instead be empirically measured. By unravelling the interactions between complex risk variants, it may be possible to improve the clinical utility of polygenic risk scores through more powerful prediction of symptom onset, clinical trajectory, and treatment response, or to identify novel targets for therapeutic intervention.

Common variants associated with schizophrenia are concentrated in non-coding regulatory sequences, but their precise target genes are context-dependent and impacted by cell-type-specific three-dimensional spatial chromatin organization. Here, we map long-range chromosomal conformations in isogenic human dopaminergic, GABAergic, and glutamatergic neurons to track developmentally programmed shifts in the regulatory activity of schizophrenia risk loci. Massive repressive compartmentalization, concomitant with the emergence of hundreds of neuron-specific multi-valent chromatin architectural stripes, occurs during neuronal differentiation, with genes interconnected to genetic risk loci through these long-range chromatin structures differing in their biological roles from genes more proximal to sequences conferring heritable risk. Chemically induced CRISPR-guided chromosomal loop-engineering for the proximal risk gene SNAP91 and distal risk gene BHLHE22 profoundly alters synaptic development and functional activity. Our findings highlight the large-scale cell-type-specific reorganization of chromosomal conformations at schizophrenia risk loci during neurodevelopment and establish a causal link between risk-associated gene-regulatory loop structures and neuronal function.

NRXN1 undergoes extensive alternative splicing, and non-recurrent heterozygous deletions in NRXN1 are strongly associated with neuropsychiatric disorders. We establish that human induced pluripotent stem cell (hiPSC)-derived neurons well represent the diversity of NRXN1α alternative splicing observed in the human brain, cataloguing 123 high-confidence in-frame human NRXN1α isoforms. Patient-derived NRXN1+/- hiPSC-neurons show a greater than twofold reduction in half of the wild-type NRXN1α isoforms and express dozens of novel isoforms from the mutant allele. Reduced neuronal activity in patient-derived NRXN1+/- hiPSC-neurons is ameliorated by overexpression of individual control isoforms in a genotype-dependent manner, whereas individual mutant isoforms decrease neuronal activity levels in control hiPSC-neurons. In a genotype-dependent manner, the phenotypic impact of patient-specific NRXN1+/- mutations can occur through a reduction in wild-type NRXN1α isoform levels as well as the presence of mutant NRXN1α isoforms.

The mechanisms by which common risk variants of small effect interact to contribute to complex genetic disorders are unclear. Here, we apply a genetic approach, using isogenic human induced pluripotent stem cells, to evaluate the effects of schizophrenia (SZ)-associated common variants predicted to function as SZ expression quantitative trait loci (eQTLs). By integrating CRISPR-mediated gene editing, activation and repression technologies to study one putative SZ eQTL (FURIN rs4702) and four top-ranked SZ eQTL genes (FURIN, SNAP91, TSNARE1 and CLCN3), our platform resolves pre- and postsynaptic neuronal deficits, recapitulates genotype-dependent gene expression differences and identifies convergence downstream of SZ eQTL gene perturbations. Our observations highlight the cell-type-specific effects of common variants and demonstrate a synergistic effect between SZ eQTL genes that converges on synaptic function. We propose that the links between rare and common variants implicated in psychiatric disease risk constitute a potentially generalizable phenomenon occurring more widely in complex genetic disorders.

As genetic studies continue to identify risk loci that are significantly associated with risk for neuropsychiatric disease, a critical unanswered question is the extent to which diverse mutations--sometimes impacting the same gene-- will require tailored therapeutic strategies. Here we consider this in the context of rare neuropsychiatric disorder-associated copy number variants (2p16.3) resulting in heterozygous deletions in NRXN1, a pre-synaptic cell adhesion protein that serves as a critical synaptic organizer in the brain. Complex patterns of NRXN1 alternative splicing are fundamental to establishing diverse neurocircuitry, vary between the cell types of the brain, and are differentially impacted by unique (non-recurrent) deletions. We contrast the cell-type-specific impact of patient-specific mutations in NRXN1 using human induced pluripotent stem cells, finding that perturbations in NRXN1 splicing result in divergent cell-type-specific synaptic outcomes. Via distinct loss-of-function (LOF) and gain-of-function (GOF) mechanisms, NRXN1+/- deletions cause decreased synaptic activity in glutamatergic neurons, yet increased synaptic activity in GABAergic neurons. Stratification of patients by LOF and GOF mechanisms will facilitate individualized restoration of NRXN1 isoform repertoires; towards this, antisense oligonucleotides knockdown mutant isoform expression and alters synaptic transcriptional signatures, while treatment with β-estradiol rescues synaptic function in glutamatergic neurons. Given the increasing number of mutations predicted to engender both LOF and GOF mechanisms in brain disease, our findings add nuance to future considerations of precision medicine.

The power of human induced pluripotent stem cell (hiPSC)-based studies to resolve the smaller effects of common variants within the size of cohorts that can be realistically assembled remains uncertain. We identified and accounted for a variety of technical and biological sources of variation in a large case/control schizophrenia (SZ) hiPSC-derived cohort of neural progenitor cells and neurons. Reducing the stochastic effects of the differentiation process by correcting for cell type composition boosted the SZ signal and increased the concordance with post-mortem data sets. We predict a growing convergence between hiPSC and post-mortem studies as both approaches expand to larger cohort sizes. For studies of complex genetic disorders, to maximize the power of hiPSC cohorts currently feasible, in most cases and whenever possible, we recommend expanding the number of individuals even at the expense of the number of replicate hiPSC clones.