Hyman, S. E. Can neuroscience be integrated into the DSM-V? Nat. Rev. Neurosci. 8, 725–732 (2007).

Article 
PubMed 

Google Scholar
 

Grotzinger, A. D. et al. Genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic and molecular genetic levels of analysis. Nat. Genet. 54, 548–559 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Brainstorm, C. et al. Analysis of shared heritability in common disorders of the brain. Science 360, eaap8757 (2018).

Article 

Google Scholar
 

Mallard, T. T. et al. Multivariate GWAS of psychiatric disorders and their cardinal symptoms reveal two dimensions of cross-cutting genetic liabilities. Cell Genom. 2, 100140 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Smoller, J. W. et al. Psychiatric genetics and the structure of psychopathology. Mol. Psychiatry 24, 409–420 (2019).

Article 
PubMed 

Google Scholar
 

Romero, C. et al. Exploring the genetic overlap between twelve psychiatric disorders. Nat. Genet. 54, 1795–1802 (2022).

Article 
PubMed 

Google Scholar
 

Thompson, P. M. et al. ENIGMA and global neuroscience: a decade of large-scale studies of the brain in health and disease across more than 40 countries. Transl. Psychiatry 10, 100 (2020).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Thompson, P. M. et al. The enhancing neuroimaging genetics through meta-analysis consortium: 10 years of global collaborations in human brain mapping. Hum. Brain Mapp. 43, 15–22 (2022).

Article 
PubMed 

Google Scholar
 

Hoogman, M. et al. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: the ENIGMA adventure. Hum. Brain Mapp. 43, 37–55 (2022).

Article 
PubMed 

Google Scholar
 

Ching, C. R. et al. What we learn about bipolar disorder from large‐scale neuroimaging: findings and future directions from the ENIGMA Bipolar Disorder Working Group. Hum. Brain Mapp. 43, 56–82 (2022).

Article 
PubMed 

Google Scholar
 

Bas-Hoogendam, J. M. et al. ENIGMA-anxiety working group: rationale for and organization of large-scale neuroimaging studies of anxiety disorders. Hum. Brain Mapp. 43, 83–112 (2022).

Article 
PubMed 

Google Scholar
 

Schmaal, L. et al. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Mol. Psychiatry 22, 900–909 (2017).

Article 
PubMed 

Google Scholar
 

Wang, X. et al. Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis. Mol. Psychiatry 26, 4331–4343 (2021).

Article 
PubMed 

Google Scholar
 

van Erp, T. G. M. et al. Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium. Biol. Psychiatry 84, 644–654 (2018).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Moran, M. E., Hulshoff Pol, H. & Gogtay, N. A family affair: brain abnormalities in siblings of patients with schizophrenia. Brain 136, 3215–3226 (2013).

Article 
PubMed 
PubMed Central 

Google Scholar
 

McDonald, C. et al. Regional brain morphometry in patients with schizophrenia or bipolar disorder and their unaffected relatives. Am. J. Psychiatry 163, 478–487 (2006).

Article 
PubMed 

Google Scholar
 

Carballedo, A. et al. Early life adversity is associated with brain changes in subjects at family risk for depression. World J. Biol. Psychiatry 13, 569–578 (2012).

Article 
PubMed 

Google Scholar
 

Stauffer, E.-M. et al. Grey and white matter microstructure is associated with polygenic risk for schizophrenia. Mol. Psychiatry 26, 7709–7718 (2021).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Maglanoc, L. A. et al. Brain connectome mapping of complex human traits and their polygenic architecture using machine learning. Biol. Psychiatry 87, 717–726 (2020).

Article 
PubMed 

Google Scholar
 

Kirschner, M. et al. Schizophrenia polygenic risk during typical development reflects multiscale cortical organization. Biol. Psychiatry Glob. Open Sci. 3, 1083–1093 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Zhao, B. et al. Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits. Nat. Genet. 51, 1637–1644 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Grasby, K. L. et al. The genetic architecture of the human cerebral cortex. Science 367, eaay6690 (2020).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Warrier, V. et al. Genetic insights into human cortical organization and development through genome-wide analyses of 2,347 neuroimaging phenotypes. Nat. Genet. 55, 1483–1493 (2023).

Panizzon, M. S. et al. Distinct genetic influences on cortical surface area and cortical thickness. Cereb. Cortex 19, 2728–2735 (2009).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Sullivan, P. F., Daly, M. J. & O’Donovan, M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat. Rev. Genet. 13, 537–551 (2012).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Chambers, J. C. et al. Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma. Nat. Genet. 43, 1131–1138 (2011).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Schizophrenia Psychiatric Genome-Wide Association Study, C. Genome-wide association study identifies five new schizophrenia loci. Nat. Genet. 43, 969–976 (2011).

Article 

Google Scholar
 

Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Dudbridge, F. Power and predictive accuracy of polygenic risk scores. PLoS Genet. 9, e1003348 (2013).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Choi, S. W., Mak, T. S. & O’Reilly, P. F. Tutorial: a guide to performing polygenic risk score analyses. Nat. Protoc. 15, 2759–2772 (2020).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Euesden, J., Lewis, C. M. & O’Reilly, P. F. PRSice: Polygenic Risk Score software. Bioinformatics 31, 1466–1468 (2015).

Article 
PubMed 

Google Scholar
 

Alnaes, D. et al. Brain heterogeneity in schizophrenia and its association with polygenic risk. JAMA Psychiatry 76, 739–748 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Doan, N. T. et al. Distinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disorders. Neuroimage Clin. 15, 719–731 (2017).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Andreassen, O. A. et al. Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors. Am. J. Hum. Genet. 92, 197–209 (2013).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Andreassen, O. A., Thompson, W. K. & Dale, A. M. Boosting the power of schizophrenia genetics by leveraging new statistical tools. Schizophr. Bull. 40, 13–17 (2014).

Article 
PubMed 

Google Scholar
 

Andreassen, O. A. et al. Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional false discovery rate. PLoS Genet. 9, e1003455 (2013).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Smeland, O. B. et al. Discovery of shared genomic loci using the conditional false discovery rate approach. Hum. Genet. 139, 85–94 (2020).

Article 
PubMed 

Google Scholar
 

Bahrami, S. et al. Shared genetic loci between body mass index and major psychiatric disorders: a genome-wide association study. JAMA Psychiatry 77, 503–512 (2020).

Article 
PubMed 

Google Scholar
 

Yokoyama, J. S. et al. Association between genetic traits for immune-mediated diseases and Alzheimer disease. JAMA Neurol. 73, 691–697 (2016).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Demontis, D. et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat. Genet. 51, 63–75 (2019).

Article 
PubMed 

Google Scholar
 

Zhou, H. et al. Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nat. Neurosci. 23, 809–818 (2020).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Otowa, T. et al. Meta-analysis of genome-wide association studies of anxiety disorders. Mol. Psychiatry 21, 1485 (2016).

Article 
PubMed 

Google Scholar
 

Grove, J. et al. Identification of common genetic risk variants for autism spectrum disorder. Nat. Genet. 51, 431–444 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Stahl, E. A. et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat. Genet. 51, 793–803 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Wray, N. R. et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat. Genet. 50, 668–681 (2018).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Stein, M. B. et al. Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program. Nat. Genet. 53, 174–184 (2021).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Trubetskoy, V. et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 604, 502–508 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Glasser, M. F. et al. A multi-modal parcellation of human cerebral cortex. Nature 536, 171–178 (2016).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Garcia-Marin, L. M. et al. Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries. Nat. Genet. 56, 2333–2344 (2024).

Article 
PubMed 

Google Scholar
 

Wilson, D. J. The harmonic mean p-value for combining dependent tests. Proc. Natl Acad. Sci. USA 116, 1195–1200 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8, 1826 (2017).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Burt, J. B. et al. Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography. Nat. Neurosci. 21, 1251–1259 (2018).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Garcia-Cabezas, M. A., Zikopoulos, B. & Barbas, H. The Structural Model: a theory linking connections, plasticity, pathology, development and evolution of the cerebral cortex. Brain Struct. Funct. 224, 985–1008 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Hilgetag, C. C., Beul, S. F., van Albada, S. J. & Goulas, A. An architectonic type principle integrates macroscopic cortico-cortical connections with intrinsic cortical circuits of the primate brain. Netw. Neurosci. 3, 905–923 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Sydnor, V. J. et al. Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology. Neuron 109, 2820–2846 (2021).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Hilgetag, C. C. & Goulas, A. ‘Hierarchy’ in the organization of brain networks. Philos. Trans. R. Soc. Lond. B 375, 20190319 (2020).

Article 

Google Scholar
 

Mesulam, M. M. From sensation to cognition. Brain 121, 1013–1052 (1998).

Article 
PubMed 

Google Scholar
 

Di Biase, M. A. et al. Cell type-specific manifestations of cortical thickness heterogeneity in schizophrenia. Mol. Psychiatry 27, 2052–2060 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Kamburov, A., Stelzl, U., Lehrach, H. & Herwig, R. The ConsensusPathDB interaction database: 2013 update. Nucleic Acids Res. 41, D793–D800 (2013).

Article 
PubMed 

Google Scholar
 

Rivero, O. et al. Haploinsufficiency of the attention-deficit/hyperactivity disorder risk gene St3gal3 in mice causes alterations in cognition and expression of genes involved in myelination and sialylation. Front. Genet. 12, 688488 (2021).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Ford, T. J. L., Jeon, B. T., Lee, H. & Kim, W. Y. Dendritic spine and synapse pathology in chromatin modifier-associated autism spectrum disorders and intellectual disability. Front. Mol. Neurosci. 15, 1048713 (2022).

Article 
PubMed 

Google Scholar
 

Ferreira, M. A. et al. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat. Genet. 40, 1056–1058 (2008).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Yoon, S. et al. Usp9X controls ankyrin-repeat domain protein homeostasis during dendritic spine development. Neuron 105, 506–521 e507 (2020).

Article 
PubMed 

Google Scholar
 

Zhang, Y. et al. The emerging role of furin in neurodegenerative and neuropsychiatric diseases. Transl. Neurodegener. 11, 39 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Sudre, G. et al. Mapping the cortico-striatal transcriptome in attention deficit hyperactivity disorder. Mol. Psychiatry 28, 792–800 (2023).

Article 
PubMed 

Google Scholar
 

Gandal, M. J. et al. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362, eaat8127 (2018).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Jaffe, A. E. et al. Decoding shared versus divergent transcriptomic signatures across cortico-amygdala circuitry in PTSD and depressive disorders. Am. J. Psychiatry 179, 673–686 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Willis, C. et al. Gene expression differences associated with alcohol use disorder in human brain. Mol. Psychiatry https://doi.org/10.1038/s41380-024-02777-1 (2024).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Kaczkurkin, A. N. et al. Evidence for dissociable linkage of dimensions of psychopathology to brain structure in youths. Am J Psychiatry 176, 1000–1009 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Sha, Z., Wager, T. D., Mechelli, A. & He, Y. Common dysfunction of large-scale neurocognitive networks across psychiatric disorders. Biol. Psychiatry 85, 379–388 (2019).

Article 
PubMed 

Google Scholar
 

Barack, D. L. & Krakauer, J. W. Two views on the cognitive brain. Nat. Rev. Neurosci. 22, 359–371 (2021).

Article 
PubMed 

Google Scholar
 

Goodkind, M. et al. Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry 72, 305–315 (2015).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Bearden, C. E. & Freimer, N. B. Endophenotypes for psychiatric disorders: ready for primetime? Trends Genet. 22, 306–313 (2006).

Article 
PubMed 

Google Scholar
 

Ferland, R. J., Cherry, T. J., Preware, P. O., Morrisey, E. E. & Walsh, C. A. Characterization of Foxp2 and Foxp1 mRNA and protein in the developing and mature brain. J. Comp. Neurol. 460, 266–279 (2003).

Article 
PubMed 

Google Scholar
 

Lai, C. S., Gerrelli, D., Monaco, A. P., Fisher, S. E. & Copp, A. J. FOXP2 expression during brain development coincides with adult sites of pathology in a severe speech and language disorder. Brain 126, 2455–2462 (2003).

Article 
PubMed 

Google Scholar
 

den Hoed, J., Devaraju, K. & Fisher, S. E. Molecular networks of the FOXP2 transcription factor in the brain. EMBO Rep. 22, e52803 (2021).

Article 

Google Scholar
 

French, C. A. et al. Differential effects of Foxp2 disruption in distinct motor circuits. Mol. Psychiatry 24, 447–462 (2019).

Article 
PubMed 

Google Scholar
 

Vargha-Khadem, F., Gadian, D. G., Copp, A. & Mishkin, M. FOXP2 and the neuroanatomy of speech and language. Nat. Rev. Neurosci. 6, 131–138 (2005).

Article 
PubMed 

Google Scholar
 

Chand, G. B. et al. Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning. Brain 143, 1027–1038 (2020).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Haruvi-Lamdan, N., Horesh, D. & Golan, O. PTSD and autism spectrum disorder: co-morbidity, gaps in research, and potential shared mechanisms. Psychol. Trauma 10, 290–299 (2018).

Article 
PubMed 

Google Scholar
 

Van Rooij, D. et al. Cortical and subcortical brain morphometry differences between patients with autism spectrum disorder and healthy individuals across the lifespan: results from the ENIGMA ASD Working Group. Am. J. Psychiatry 175, 359–369 (2018).

Article 
PubMed 

Google Scholar
 

Sha, Z. et al. The genetic architecture of structural left-right asymmetry of the human brain. Nat. Hum. Behav. 5, 1226–1239 (2021).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Attwaters, M. Connecting noncoding variants to human traits. Nat. Rev. Genet. 24, 489 (2023).

Article 
PubMed 

Google Scholar
 

Ramasamy, A. et al. Genetic variability in the regulation of gene expression in ten regions of the human brain. Nat. Neurosci. 17, 1418–1428 (2014).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Consortium, G. T. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).

Article 

Google Scholar
 

Nelson, C. E., Hersh, B. M. & Carroll, S. B. The regulatory content of intergenic DNA shapes genome architecture. Genome Biol. 5, R25 (2004).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Gandal, M. J. et al. Broad transcriptomic dysregulation occurs across the cerebral cortex in ASD. Nature 611, 532–539 (2022).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Fusar-Poli, P. et al. Transdiagnostic psychiatry: a systematic review. World Psychiatry 18, 192–207 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Plana-Ripoll, O. et al. Exploring comorbidity within mental disorders among a Danish national population. JAMA Psychiatry 76, 259–270 (2019).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Merikangas, K. R. et al. Lifetime prevalence of mental disorders in U.S. adolescents: results from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A). J. Am. Acad. Child Adolesc. Psychiatry 49, 980–989 (2010).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Aschard, H., Vilhjálmsson, B. J., Joshi, A. D., Price, A. L. & Kraft, P. Adjusting for heritable covariates can bias effect estimates in genome-wide association studies. Am. J. Hum. Genet. 96, 329–339 (2015).

Article 
PubMed 
PubMed Central 

Google Scholar
 

International Obsessive Compulsive Disorder Foundation Genetics Collaborative & OCD Collaborative Genetics Association Studies. Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis. Mol. Psychiatry 23, 1181–1188 (2018).

1000 Genomes Project Consortium A global reference for human genetic variation. Nature 526, 68–74 (2015).

Article 

Google Scholar
 

Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).

Article 

Google Scholar
 

Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Wang, D. et al. Comprehensive functional genomic resource and integrative model for the human brain. Science 362, eaat8464 (2018).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Fromer, M. et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat. Neurosci. 19, 1442–1453 (2016).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Giusti-Rodríguez, P. et al. Using three-dimensional regulatory chromatin interactions from adult and fetal cortex to interpret genetic results for psychiatric disorders and cognitive traits. Preprint at bioRxiv https://doi.org/10.1101/406330 (2018).

Schmitt, A. D. et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 17, 2042–2059 (2016).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Roadmap Epigenomics Consortiumet al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

Article 
PubMed Central 

Google Scholar
 

Glasser, M. F. & Van Essen, D. C. Mapping human cortical areas in vivo based on myelin content as revealed by T1- and T2-weighted MRI. J. Neurosci. 31, 11597–11616 (2011).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Vasa, F. et al. Adolescent tuning of association cortex in human structural brain networks. Cereb. Cortex 28, 281–294 (2018).

Article 
PubMed 

Google Scholar
 

Alexander-Bloch, A. F. et al. On testing for spatial correspondence between maps of human brain structure and function. Neuroimage 178, 540–551 (2018).

Article 
PubMed 

Google Scholar
 

Alexander-Bloch, A., Raznahan, A., Bullmore, E. & Giedd, J. The convergence of maturational change and structural covariance in human cortical networks. J. Neurosci. 33, 2889–2899 (2013).

Article 
PubMed 
PubMed Central 

Google Scholar
 

Koskinen, M. K. & Hovatta, I. Genetic insights into the neurobiology of anxiety. Trends Neurosci. 46, 318–331 (2023).

Article 
PubMed 

Google Scholar