1 Sullivan, P. F. & Geschwind, D. H. Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders. Cell 177, 162-183, doi:10.1016/j.cell.2019.01.015 (2019).
2 Rapoport, J. L., Giedd, J. N. & Gogtay, N. Neurodevelopmental model of schizophrenia: update 2012. Mol Psychiatry 17, 1228-1238, doi:10.1038/mp.2012.23 (2012).
3 McGuffin, P., Farmer, A. E., Gottesman, I. I., Murray, R. M., Reveley, A. M. Twin concordance for operationally defined schizophrenia. Confirmation of familiality and heritability. Arch Gen Psychiatry 41, 541-545 (1984).
4 Sullivan, P. F., Kendler, K. S. & Neale, M. C. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry 60, 1187-1192, doi:10.1001/archpsyc.60.12.1187 (2003).
5 Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421-427, doi:10.1038/nature13595 (2014).
6 Pardinas, A. F. et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat Genet 50, 381-389, doi:10.1038/s41588-018-0059-2 (2018).
7 The Schizophrenia Working Group of the Psychiatric Genomics Consortium. Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia. Preprint at https://doi.org/10.1101/2020.09.12.20192922 (2020).
8 Bacanu, S. A. et al. Functional SNPs are enriched for schizophrenia association signals. Mol Psychiatry 19, 276-277, doi:10.1038/mp.2013.33 (2014).
9 Jaffe, A. E. et al. Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis. Nat Neurosci 21, 1117-1125, doi:10.1038/s41593-018-0197-y (2018).
10 Wang, D. F. et al. Comprehensive functional genomic resource and integrative model for the human brain. Science 362, doi:10.1126/science.aat8464 (2018).
11 Fullard, J. F. et al. An atlas of chromatin accessibility in the adult human brain. Genome Res 28, 1243-1252, doi:10.1101/gr.232488.117 (2018).
12 Bryois, J. et al. Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun 9, 3121, doi:10.1038/s41467-018-05379-y (2018).
13 Won, H. et al. Chromosome conformation elucidates regulatory relationships in developing human brain. Nature 538, 523-527, doi:10.1038/nature19847 (2016).
14 Huo, Y., Li, S., Liu, J., Li, X. & Luo, X. J. Functional genomics reveal gene regulatory mechanisms underlying schizophrenia risk. Nat Commun 10, 670, doi:10.1038/s41467-019-08666-4 (2019).
15 Radhakrishnan, R., Kaser, M. & Guloksuz, S. The Link Between the Immune System, Environment, and Psychosis. Schizophrenia Bull 43, 693-697, doi:10.1093/schbul/sbx057 (2017).
16 Karlic, R., Chung, H. R., Lasserre, J., Vlahovicek, K. & Vingron, M. Histone modification levels are predictive for gene expression. P Natl Acad Sci USA 107, 2926-2931, doi:10.1073/pnas.0909344107 (2010).
17 Kilpinen, H. et al. Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription. Science 342, 744-747, doi:10.1126/science.1242463 (2013).
18 Wong, E. S. et al. Interplay of cis and trans mechanisms driving transcription factor binding and gene expression evolution. Nat Commun 8, 1092, doi:10.1038/s41467-017-01037-x (2017).
19 McVicker, G. et al. Identification of Genetic Variants That Affect Histone Modifications in Human Cells. Science 342, 747-749, doi:10.1126/science.1242429 (2013).
20 Gusev, A. et al. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nature Genetics 50, 538-548, doi:10.1038/s41588-018-0092-1 (2018).
21 Delaneau, O. et al. Chromatin three-dimensional interactions mediate genetic effects on gene expression. Science 364, doi:10.1126/science.aat8266 (2019).
22 Fulton, D. L., Denarier, E., Friedman, H. C., Wasserman, W. W. & Peterson, A. C. Towards resolving the transcription factor network controlling myelin gene expression. Nucleic Acids Res 39, 7974-7991, doi:10.1093/nar/gkr326 (2011).
23 Nakajima, K. et al. Molecular Motor KIF5A Is Essential for GABA(A) Receptor Transport, and KIF5A Deletion Causes Epilepsy. Neuron 76, 945-961, doi:10.1016/j.neuron.2012.10.012 (2012).
24 Miczan, V. et al. NECAB1 and NECAB2 are Prevalent Calcium-Binding Proteins of CB1/CCK-Positive GABAergic Interneurons. Cereb Cortex 31, 1786-1806, doi:10.1093/cercor/bhaa326 (2021).
25 Zhao, S. F., Li, F. W., Leak, R. K., Jun, C. & Hu, X. M. Regulation of neuroinflannmation through programed death-1/programed death ligand signaling in neurological disorders. Front Cell Neurosci 8, doi:10.3389/fncel.2014.00271 (2014).
26 Fromer, M. et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci 19, 1442-1453, doi:10.1038/nn.4399 (2016).
27 Reay, W. R. & Cairns, M. J. The role of the retinoids in schizophrenia: genomic and clinical perspectives. Mol Psychiatr 25, 706-718, doi:10.1038/s41380-019-0566-2 (2020).
28 O'Donovan, S. M. et al. Cell-subtype-specific changes in adenosine pathways in schizophrenia. Neuropsychopharmacology 43, 1667-1674, doi:10.1038/s41386-018-0028-6 (2018).
29 Kraft, R. et al. Phenotypes of Drosophila brain neurons in primary culture reveal a role for fascin in neurite shape and trajectory. J Neurosci 26, 8734-8747, doi:10.1523/Jneurosci.2106-06.2006 (2006).
30 Bell, S. et al. Mutations in ACTL6B Cause Neurodevelopmental Deficits and Epilepsy and Lead to Loss of Dendrites in Human Neurons. Am J Hum Genet 104, 815-834, doi:10.1016/j.ajhg.2019.03.022 (2019).
31 Deinhardt, K. et al. Neuronal Growth Cone Retraction Relies on Proneurotrophin Receptor Signaling Through Rac. Sci Signal 4, doi:10.1126/scisignal.2002060 (2011).
32 Nozumi, M., Nakatsu, F., Katoh, K. & Igarashi, M. Coordinated Movement of Vesicles and Actin Bundles during Nerve Growth Revealed by Superresolution Microscopy. Cell Rep 18, 2203-2216, doi:10.1016/j.celrep.2017.02.008 (2017).
33 Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans (vol 581, pg 434, 2020). Nature 590, E53-E53, doi:10.1038/s41586-020-03174-8 (2021).
34 Mendizabal, I. et al. Cell type-specific epigenetic links to schizophrenia risk in the brain. Genome Biology 20, doi:10.1186/s13059-019-1747-7 (2019).
35 Qu, L. et al. The Ras Superfamily of Small GTPases in Non-neoplastic Cerebral Diseases. Front Mol Neurosci 12, doi:10.3389/fnmol.2019.00121 (2019).
36 Bhambhvani, H. P., Mueller, T. M., Simmons, M. S. & Meador-Woodruff, J. H. Actin polymerization is reduced in the anterior cingulate cortex of elderly patients with schizophrenia. Transl Psychiat 7, doi:10.1038/s41398-017-0045-y (2017).
37 Yan, Z., Kim, E., Datta, D., Lewis, D. A. & Soderling, S. H. Synaptic Actin Dysregulation, a Convergent Mechanism of Mental Disorders? J Neurosci 36, 11411-11417, doi:10.1523/Jneurosci.2360-16.2016 (2016).
38 Costa, J. F., Dines, M. & Lamprecht, R. The Role of Rac GTPase in Dendritic Spine Morphogenesis and Memory. Front Synaptic Neuro 12, doi:10.3389/fnsyn.2020.00012 (2020).
39 Tessier, C. et al. Membrane lipidomics in schizophrenia patients: a correlational study with clinical and cognitive manifestations. Transl Psychiat 6, doi:10.1038/tp.2016.142 (2016).
40 Aguet, F. et al. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318-1330, doi:10.1126/science.aaz1776 (2020).
41 Dobbyn, A. et al. Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS. Am J Hum Genet 102, 1169-1184, doi:10.1016/j.ajhg.2018.04.011 (2018).
42 de la Torre-Ubieta, L. et al. The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis. Cell 172, 289-304, doi:10.1016/j.cell.2017.12.014 (2018).
43 Girdhar, K. et al. Cell-specific histone modification maps in the human frontal lobe link schizophrenia risk to the neuronal epigenome. Nature Neuroscience 21, 1126-1136, doi:10.1038/s41593-018-0187-0 (2018).
44 de Candia, T. R. et al. Additive Genetic Variation in Schizophrenia Risk Is Shared by Populations of African and European Descent. Am J Hum Genet 93, 463-470, doi:10.1016/j.ajhg.2013.07.007 (2013).
45 Bigdeli, T. B. et al. Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry. Mol Psychiatry 25, 2455-2467, doi:10.1038/s41380-019-0517-y (2020).
46 Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7, doi:10.1186/s13742-015-0047-8 (2015).
47 McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet 48, 1279-1283, doi:10.1038/ng.3643 (2016).
48 Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at arXiv:1303.3997v2 (2013).
49 Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21, doi:10.1093/bioinformatics/bts635 (2013).
50 Delaneau, O. et al. A complete tool set for molecular QTL discovery and analysis. Nat Commun 8, 15452, doi:10.1038/ncomms15452 (2017).
51 Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38, 576-589, doi:10.1016/j.molcel.2010.05.004 (2010).
52 Storey, J. D. & Tibshirani, R. Statistical significance for genomewide studies. Proc Natl Acad Sci U S A 100, 9440-9445, doi:10.1073/pnas.1530509100 (2003).
53 Nica, A. C. et al. Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations. Plos Genet 6, doi:10.1371/journal.pgen.1000895 (2010).
54 Ongen, H. et al. Estimating the causal tissues for complex traits and diseases. Nat Genet 49, 1676-1683, doi:10.1038/ng.3981 (2017).
55 Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15, 550, doi:10.1186/s13059-014-0550-8 (2014).
56 Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284-287, doi:10.1089/omi.2011.0118 (2012).
57 Scutari, M. Learning Bayesian Networks with the bnlearn R Package. J Stat Softw 35, 1-22, doi:DOI 10.18637/jss.v035.i03 (2010).