1. Bethlehem, R. A. I. et al. Brain charts for the human lifespan. Nature 604, 525–533 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. 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 

  3. Gilmore, J. H., Knickmeyer, R. C. & Gao, W. Imaging structural and functional brain development in early childhood. Nat. Rev. Neurosci. 19, 123–137 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Paus, T., Keshavan, M. & Giedd, J. N. Why do many psychiatric disorders emerge during adolescence? Nat. Rev. Neurosci. 9, 947–957 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Elliott, L. T. et al. Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature 562, 210–216 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Stein, J. L. et al. Identification of common variants associated with human hippocampal and intracranial volumes. Nat. Genet. 44, 552–561 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Zhao, B. et al. Common genetic variation influencing human white matter microstructure. Science 372, eabf3736 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Makowski, C. et al. Discovery of genomic loci of the human cerebral cortex using genetically informed brain atlases. Science 375, 522–528 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jansen, P. R. et al. Genome-wide meta-analysis of brain volume identifies genomic loci and genes shared with intelligence. Nat. Commun. 11, 5606 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Smith, S. M. et al. An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank. Nat. Neurosci. 24, 737–745 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Naqvi, S. et al. Shared heritability of human face and brain shape. Nat. Genet. 53, 830–839 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Jayaraman, D., Bae, B.-I. & Walsh, C. A. The genetics of primary microcephaly. Annu. Rev. Genomics Hum. Genet. 19, 177–200 (2018).

    Article  CAS  PubMed  Google Scholar 

  14. Li, M. et al. Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science 362, eaat7615 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Casey, B. J. et al. The Adolescent Brain Cognitive Development (ABCD) study: imaging acquisition across 21 sites. Dev. Cogn. Neurosci. 32, 43–54 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Hedman, A. M., van Haren, N. E. M., Schnack, H. G., Kahn, R. S. & Hulshoff Pol, H. E. Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies. Hum. Brain Mapp. 33, 1987–2002 (2012).

    Article  PubMed  Google Scholar 

  20. Brouwer, R. M. et al. Genetic variants associated with longitudinal changes in brain structure across the lifespan. Nat. Neurosci. 25, 421–432 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. 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  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sodini, S. M., Kemper, K. E., Wray, N. R. & Trzaskowski, M. Comparison of genotypic and phenotypic correlations: Cheverud’s conjecture in humans. Genetics 209, 941–948 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Grotzinger, A. D. et al. Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits. Nat. Hum. Behav. 3, 513–525 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Sanderson, E. et al. Mendelian randomization. Nat. Rev. Methods Primers 2, 6 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Rakic, P. Specification of cerebral cortical areas. Science 241, 170–176 (1988).

    Article  CAS  PubMed  Google Scholar 

  27. Ronan, L. et al. Differential tangential expansion as a mechanism for cortical gyrification. Cereb. Cortex 24, 2219–2228 (2014).

    Article  PubMed  Google Scholar 

  28. Garcia, K. E., Kroenke, C. D. & Bayly, P. V. Mechanics of cortical folding: stress, growth and stability. Philos. Trans. R. Soc. Lond. B Biol. Sci. 373, 20170321 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Richman, D. P., Stewart, R. M., Hutchinson, J. W. & Caviness, V. S. Jr. Mechanical model of brain convolutional development. Science 189, 18–21 (1975).

    Article  CAS  PubMed  Google Scholar 

  30. Tallinen, T., Chung, J. Y., Biggins, J. S. & Mahadevan, L. Gyrification from constrained cortical expansion. Proc. Natl Acad. Sci. USA 111, 12667–12672 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Reillo, I., de Juan Romero, C., García-Cabezas, M. Á. & Borrell, V. A role for intermediate radial glia in the tangential expansion of the mammalian cerebral cortex. Cereb. Cortex 21, 1674–1694 (2011).

    Article  PubMed  Google Scholar 

  32. Kriegstein, A., Noctor, S. & Martínez-Cerdeño, V. Patterns of neural stem and progenitor cell division may underlie evolutionary cortical expansion. Nat. Rev. Neurosci. 7, 883–890 (2006).

    Article  CAS  PubMed  Google Scholar 

  33. De Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Sey, N. Y. A. et al. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nat. Neurosci. 23, 583–593 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Akbarian, S. et al. The PsychENCODE project. Nat. Neurosci. 18, 1707–1712 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Eze, U. C., Bhaduri, A., Haeussler, M., Nowakowski, T. J. & Kriegstein, A. R. Single-cell atlas of early human brain development highlights heterogeneity of human neuroepithelial cells and early radial glia. Nat. Neurosci. 24, 584–594 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Polioudakis, D. et al. A single-cell transcriptomic atlas of human neocortical development during mid-gestation. Neuron 103, 785–801 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Ziffra, R. S. et al. Single-cell epigenomics reveals mechanisms of human cortical development. Nature 598, 205–213 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Florio, M. & Huttner, W. B. Neural progenitors, neurogenesis and the evolution of the neocortex. Development 141, 2182–2194 (2014).

    Article  CAS  PubMed  Google Scholar 

  40. Geschwind, D. H. & Rakic, P. Cortical evolution: judge the brain by its cover. Neuron 80, 633–647 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Gertz, C. C., Lui, J. H., LaMonica, B. E., Wang, X. & Kriegstein, A. R. Diverse behaviors of outer radial glia in developing ferret and human cortex. J. Neurosci. 34, 2559–2570 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Nott, A. et al. Brain cell type-specific enhancer-promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Fukutomi, H. et al. Neurite imaging reveals microstructural variations in human cerebral cortical gray matter. Neuroimage 182, 488–499 (2018).

    Article  PubMed  Google Scholar 

  44. Zeng, J. et al. Widespread signatures of natural selection across human complex traits and functional genomic categories. Nat. Commun. 12, 1164 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Fu, J. M. et al. Rare coding variation provides insight into the genetic architecture and phenotypic context of autism. Nat. Genet. 54, 1320–1331 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Prevalence and architecture of de novo mutations in developmental disorders. Nature. 542, 433–438 (2017).

  48. Niemi, M. E. K. et al. Common genetic variants contribute to risk of rare severe neurodevelopmental disorders. Nature 562, 268–271 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. SPARK Consortium. SPARK: a US cohort of 50,000 families to accelerate autism research. Neuron 97, 488–493 (2018).

    Article  Google Scholar 

  50. Weissbrod, O. et al. Functionally informed fine-mapping and polygenic localization of complex trait heritability. Nat. Genet. 52, 1355–1363 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Kabeche, L., Nguyen, H. D., Buisson, R. & Zou, L. A mitosis-specific and R loop-driven ATR pathway promotes faithful chromosome segregation. Science 359, 108–114 (2018).

    Article  CAS  PubMed  Google Scholar 

  52. Kaczmarczyk, A. & Sullivan, K. F. CENP-W plays a role in maintaining bipolar spindle structure. PLoS ONE 9, e106464 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Koolen, D. A. et al. The Koolen-de Vries syndrome: a phenotypic comparison of patients with a 17q21.31 microdeletion versus a KANSL1 sequence variant. Eur. J. Hum. Genet. 24, 652–659, (2016).

    Article  CAS  PubMed  Google Scholar 

  54. Zhou, X. et al. Cellular and molecular properties of neural progenitors in the developing mammalian hypothalamus. Nat. Commun. 11, 4063 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Kuwayama, N. et al. A role for Hmga2 in the early-stage transition of neural stem-progenitor cell properties during mouse neocortical development. Preprint at bioRxiv https://doi.org/10.1101/2020.05.14.086330 (2021).

  56. De Crescenzo, A. et al. A splicing mutation of the HMGA2 gene is associated with Silver–Russell syndrome phenotype. J. Hum. Genet. 60, 287–293 (2015).

    Article  PubMed  Google Scholar 

  57. Chenn, A. & Walsh, C. A. Regulation of cerebral cortical size by control of cell cycle exit in neural precursors. Science 297, 365–369 (2002).

    Article  CAS  PubMed  Google Scholar 

  58. Xiang, Y.-Y. et al. Versican G3 domain regulates neurite growth and synaptic transmission of hippocampal neurons by activation of epidermal growth factor receptor. J. Biol. Chem. 281, 19358–19368 (2006).

    Article  CAS  PubMed  Google Scholar 

  59. Dobyns, W. B. et al. MACF1 mutations encoding highly conserved zinc-binding residues of the GAR domain cause defects in neuronal migration and axon guidance. Am. J. Hum. Genet. 103, 1009–1021 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. 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  CAS  PubMed  PubMed Central  Google Scholar 

  61. Chen, S. et al. A genome-wide mutational constraint map quantified from variation in 76,156 human genomes. Preperint at bioRxiv https://doi.org/10.1101/2022.03.20.485034 (2022).

  62. Demange, P. A. et al. Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction. Nat. Genet. 53, 35–44 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Bhaduri, A. et al. An atlas of cortical arealization identifies dynamic molecular signatures. Nature 598, 200–204 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Yeo, B. T. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165 (2011).

    Article  PubMed  Google Scholar 

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

    Article  PubMed  Google Scholar 

  66. 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 

  67. 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 

  68. Rubenstein, J. L. & Rakic, P. Genetic control of cortical development. Cereb. Cortex 9, 521–523 (1999).

    Article  CAS  PubMed  Google Scholar 

  69. Cox, S. R. et al. Ageing and brain white matter structure in 3,513 UK Biobank participants. Nat. Commun. 7, 13629 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Sexton, C. E. et al. Accelerated changes in white matter microstructure during aging: a longitudinal diffusion tensor imaging study. J. Neurosci. 34, 15425–15436 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Pletikos, M. et al. Temporal specification and bilaterality of human neocortical topographic gene expression. Neuron 81, 321–332 (2014).

    Article  CAS  PubMed  Google Scholar 

  72. Zhu, Y. et al. Spatiotemporal transcriptomic divergence across human and macaque brain development. Science 362, eaat8077 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Yoon, B., Shim, Y.-S., Lee, K.-S., Shon, Y.-M. & Yang, D.-W. Region-specific changes of cerebral white matter during normal aging: a diffusion-tensor analysis. Arch. Gerontol. Geriatr. 47, 129–138 (2008).

    Article  PubMed  Google Scholar 

  74. Shi, Y. et al. Diffusion tensor imaging-based characterization of brain neurodevelopment in primates. Cereb. Cortex 23, 36–48 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Coalson, T. S., Van Essen, D. C. & Glasser, M. F. The impact of traditional neuroimaging methods on the spatial localization of cortical areas. Proc. Natl Acad. Sci. USA 115, E6356–E6365 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Kharabian Masouleh, S. et al. Influence of processing pipeline on cortical thickness measurement. Cereb. Cortex 30, 5014–5027 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Alfaro-Almagro, F. et al. Confound modelling in UK Biobank brain imaging. NeuroImage 224, 117002 (2021).

    Article  PubMed  Google Scholar 

  78. Barch, D. M. et al. Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: rationale and description. Dev. Cogn. Neurosci. 32, 55–66 (2018).

    Article  PubMed  Google Scholar 

  79. Fischl, B. et al. Automatically parcellating the human cerebral cortex. Cereb. Cortex 14, 11–22 (2004).

    Article  PubMed  Google Scholar 

  80. Van Essen, D. C., Glasser, M. F., Dierker, D. L., Harwell, J. & Coalson, T. Parcellations and hemispheric asymmetries of human cerebral cortex analyzed on surface-based atlases. Cereb. Cortex 22, 2241–2262 (2012).

    Article  PubMed  Google Scholar 

  81. Rosen, A. F. G. et al. Quantitative assessment of structural image quality. Neuroimage 169, 407–418 (2018).

    Article  PubMed  Google Scholar 

  82. Alfaro-Almagro, F. et al. Image processing and quality control for the first 10,000 brain imaging datasets from UK Biobank. Neuroimage 166, 400–424 (2018).

    Article  PubMed  Google Scholar 

  83. Hagler, D. J. Jr et al. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study. Neuroimage 202, 116091 (2019).

    Article  CAS  PubMed  Google Scholar 

  84. Daducci, A. et al. Accelerated microstructure imaging via convex optimization (AMICO) from diffusion MRI data. Neuroimage 105, 32–44 (2015).

    Article  PubMed  Google Scholar 

  85. Schaer, M. et al. How to measure cortical folding from MR images: a step-by-step tutorial to compute local gyrification index. J. Vis. Exp. 2, e3417 (2012).

    Google Scholar 

  86. Knussmann, G. N. et al. Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images. Neuroimage Rep. 2, 100086 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Haddad, E. et al. Multisite test-retest reliability and compatibility of brain metrics derived from FreeSurfer versions 7.1, 6.0, and 5.3. Hum. Brain Mapp. 44, 1515–1532 (2023).

    Article  PubMed  Google Scholar 

  88. Hedges, E. P. et al. Reliability of structural MRI measurements: the effects of scan session, head tilt, inter-scan interval, acquisition sequence, FreeSurfer version and processing stream. Neuroimage 246, 118751 (2022).

    Article  CAS  PubMed  Google Scholar 

  89. Madan, C. R. & Kensinger, E. A. Test-retest reliability of brain morphology estimates. Brain Inform. 4, 107–121 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Duff, E. et al. Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: the COVID-CNS travelling heads study. PLoS ONE 17, e0273704 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. O’Donnell, L. J. & Westin, C.-F. An introduction to diffusion tensor image analysis. Neurosurg. Clin. N. Am. 22, 185–196 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  92. Zhang, H., Schneider, T., Wheeler-Kingshott, C. A. & Alexander, D. C. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 61, 1000–1016 (2012).

    Article  PubMed  Google Scholar 

  93. Tariq, M., Schneider, T., Alexander, D. C., Gandini Wheeler-Kingshott, C. A. & Zhang, H. Bingham–NODDI: mapping anisotropic orientation dispersion of neurites using diffusion MRI. Neuroimage 133, 207–223 (2016).

    Article  PubMed  Google Scholar 

  94. Andica, C. et al. Scan–rescan and inter-vendor reproducibility of neurite orientation dispersion and density imaging metrics. Neuroradiology 62, 483–494 (2020).

    Article  PubMed  Google Scholar 

  95. Kong, X.-Z. et al. Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium. Proc. Natl Acad. Sci. USA 115, E5154–E5163 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Kurth, F., Gaser, C. & Luders, E. A 12-step user guide for analyzing voxel-wise gray matter asymmetries in statistical parametric mapping (SPM). Nat. Protoc. 10, 293–304 (2015).

    Article  CAS  PubMed  Google Scholar 

  97. Leroy, F. et al. New human-specific brain landmark: the depth asymmetry of superior temporal sulcus. Proc. Natl Acad. Sci. USA 112, 1208–1213 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. 1000 Genomes Project Consortium. et al.A global reference for human genetic variation. Nature 526, 68–74 (2015).

    Article  Google Scholar 

  99. Gogarten, S. M. et al. Genetic association testing using the GENESIS R/bioconductor package. Bioinformatics 35, 5346–5348 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Manichaikul, A. et al. Robust relationship inference in genome-wide association studies. Bioinformatics 26, 2867–2873 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Jiang, L. et al. A resource-efficient tool for mixed model association analysis of large-scale data. Nat. Genet. 51, 1749–1755 (2019).

    Article  CAS  PubMed  Google Scholar 

  102. Day, F. R., Loh, P.-R., Scott, R. A., Ong, K. K. & Perry, J. R. B. A robust example of collider bias in a genetic association study. Am. J. Hum. Genet. 98, 392–393 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Hartwig, F. P., Tilling, K., Davey Smith, G., Lawlor, D. A. & Borges, M. C. Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations. Int. J. Epidemiol. 50, 1639–1650 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Zhu, Z. et al. Causal associations between risk factors and common diseases inferred from GWAS summary data. Nat. Commun. 9, 224 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Burgess, S. & Thompson, S. G. Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects. Am. J. Epidemiol. 181, 251–260 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  106. Grotzinger, A. D. et al. Multivariate genomic architecture of cortical thickness and surface area at multiple levels of analysis. Nat. Commun. 14, 946 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Loh, P.-R., Kichaev, G., Gazal, S., Schoech, A. P. & Price, A. L. Mixed-model association for biobank-scale datasets. Nat. Genet. 50, 906–908 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Zheng, J. et al. PhenoSpD: an integrated toolkit for phenotypic correlation estimation and multiple testing correction using GWAS summary statistics. Gigascience 7, giy090 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  110. Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Dahlke, J. A. & Wiernik, B. M. psychmeta: an R package for psychometric meta-analysis. Appl. Psychol. Meas. 43, 415–416 (2019).

    Article  PubMed  Google Scholar 

  112. Foley, C. N. et al. A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits. Nat. Commun. 12, 764 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Berisa, T. & Pickrell, J. K. Approximately independent linkage disequilibrium blocks in human populations. Bioinformatics 32, 283–285 (2016).

    Article  CAS  PubMed  Google Scholar 

  114. Bowden, J., Smith, G. D., Haycock, P. C. & Burgess, S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet. Epidemiol. 40, 304–314 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  115. Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44, 512–525 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  116. Verbanck, M., Chen, C.-Y., Neale, B. & Do, R. Publisher correction: detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat. Genet. 50, 1196 (2018).

    Article  CAS  PubMed  Google Scholar 

  117. Morrison, J., Knoblauch, N., Marcus, J. H., Stephens, M. & He, X. Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics. Nat. Genet. 52, 740–747 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Hemani, G., Tilling, K. & Smith, G. D. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 13, e1007081 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  119. Hemani, G. et al. The MR-base platform supports systematic causal inference across the human phenome. eLife 7, e34408 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  120. Burgess, S. Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome. Int. J. Epidemiol. 43, 922–929 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  121. Bryois, J. et al. Genetic identification of cell types underlying brain complex traits yields novel insights into the etiology of Parkinson’s disease. Nat. Genet 52, 482–493 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Won, H. et al. Chromosome conformation elucidates regulatory relationships in developing human brain. Nature 538, 523–527 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  123. Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Ge, T., Chen, C.-Y., Ni, Y., Feng, Y.-C. A. & Smoller, J. W. Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat. Commun. 10, 1776 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  126. Warrier, V. et al. Gene–environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach. Lancet Psychiatry 8, 373–386 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  127. Warrier, V. et al. Genetic correlates of phenotypic heterogeneity in autism. Nat. Genet. 54, 1293–1304 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Wright, C. F. et al. Optimising diagnostic yield in highly penetrant genomic disease. N. Engl. J. Med. 388, 1559–1571 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Wang, G., Sarkar, A., Carbonetto, P. & Stephens, M. A simple new approach to variable selection in regression, with application to genetic fine mapping. J. R. Stat. Soc. Series B Stat. Methodol. 82, 1273–1300 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  130. Hu, B. et al. Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders. Nat. Commun. 12, 3968 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. McLaren, W. et al. The ensembl variant effect predictor. Genome Biol. 17, 122 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  132. Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).

    Article  CAS  PubMed  Google Scholar 

  133. O’Brien, H. E. et al. Expression quantitative trait loci in the developing human brain and their enrichment in neuropsychiatric disorders. Genome Biol. 19, 194 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  134. Yang, J., Qi, T., Wu, Y., Zhang, F. & Zeng, J. Genetic control of RNA splicing and its distinctive role in complex trait variation. Nat. Genet. 54, 1355–1363 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  135. Qi, T. et al. Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nat. Commun. 9, 2282 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  136. Bethlehem, R. A. I. & Romero-Garcia, R. ucam-department-of-psychiatry/UKB: V1. Zenodo. https://doi.org/10.5281/zenodo.8051797 (2023).

  137. Bethlehem, R. A. I. & Romero-Garcia, R. ucam-department-of-psychiatry/ABCD: V1. Zenodo. https://doi.org/10.5281/zenodo.8051799 (2023).

  138. Warrier, V. vwarrier/ABCD_geneticQC: v1. Zenodo. https://doi.org/10.5281/zenodo.8050609 (2023).

  139. Warrier, V. vwarrier/Imaging_genetics_analyses: v1. Zenodo. https://doi.org/10.5281/zenodo.8050589 (2023).