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Neurosci 2011;31:1652-63. DOI PubMed PMC
68. Zhang Z, Hofmann C, Casanova E, Schütz G, Lutz B. Generation of a conditional allele of the CBP gene in mouse. Genesis
2004;40:82-9. DOI PubMed
69. Morimoto Y, Ono S, Yoshida S, et al. A unique missense variant in the E1A-binding protein P400 gene is implicated in schizophrenia
by whole-exome sequencing and mutant mouse models. Transl Psychiatry 2021;11:132. DOI PubMed PMC
70. Ripke S, Walters JTR, O’Donovan MC. Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia.
medRxiv 2020. DOI
71. Lambert JC, Ibrahim-Verbaas CA, Harold D, et al; European Alzheimer's Disease Initiative (EADI); Genetic and Environmental Risk
in Alzheimer's Disease; Alzheimer's Disease Genetic Consortium; Cohorts for Heart and Aging Research in Genomic Epidemiology.
Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 2013;45:1452-8. DOI
PubMed PMC
72. Cai L, Wheeler E, Kerrison ND, et al. Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study. Sci Data
2020;7:393. DOI PubMed PMC
73. Shah S, Henry A, Roselli C, et al; Regeneron Genetics Center. Genome-wide association and Mendelian randomisation analysis
provide insights into the pathogenesis of heart failure. Nat Commun 2020;11:163. DOI PubMed PMC
74. Yengo L, Sidorenko J, Kemper KE, et al; GIANT Consortium. Meta-analysis of genome-wide association studies for height and body
mass index in ~700000 individuals of European ancestry. Hum Mol Genet 2018;27:3641-9. DOI PubMed PMC
75. Leslie R, O'Donnell CJ, Johnson AD. GRASP: analysis of genotype-phenotype results from 1390 genome-wide association studies
and corresponding open access database. Bioinformatics 2014;30:i185-94. DOI PubMed PMC
76. Lam M, Awasthi S, Watson HJ, et al. RICOPILI: rapid imputation for COnsortias PIpeLIne. Bioinformatics 2020;36:930-3. DOI
PubMed PMC
77. Singh T, Kurki MI, Curtis D, et al; Swedish Schizophrenia Study; INTERVAL Study; DDD Study; UK10 K Consortium. Rare loss-
of-function variants in SETD1A are associated with schizophrenia and developmental disorders. Nat Neurosci 2016;19:571-7. DOI
PubMed PMC
78. Satterstrom FK, Kosmicki JA, Wang J, et al; Autism Sequencing Consortium; iPSYCH-Broad Consortium. Large-scale exome
sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell 2020;180:568-84.e23.
DOI PubMed PMC
79. Hannon E, Dempster E, Viana J, et al. An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of
genetic associations and differential DNA methylation. Genome Biol 2016;17:176. DOI PubMed PMC
80. Aberg KA, McClay JL, Nerella S, et al. Methylome-wide association study of schizophrenia: identifying blood biomarker signatures
of environmental insults. JAMA Psychiatry 2014;71:255-64. DOI PubMed PMC
81. Chan RF, Shabalin AA, Montano C, et al. Independent methylome-wide association studies of schizophrenia detect consistent case-
control differences. Schizophr Bull 2020;46:319-27. DOI PubMed PMC
82. Aberg KA, Dean B, Shabalin AA, et al. Methylome-wide association findings for major depressive disorder overlap in blood and
brain and replicate in independent brain samples. Mol Psychiatry 2020;25:1344-54. DOI PubMed PMC
83. van Dongen J, Zilhão NR, Sugden K, et al; BIOS Consortium. Epigenome-wide Association Study of Attention-Deficit/Hyperactivity
Disorder Symptoms in Adults. Biol Psychiatry 2019;86:599-607. DOI PubMed PMC
84. Walton E, Pingault JB, Cecil CA, et al. Epigenetic profiling of ADHD symptoms trajectories: a prospective, methylome-wide study.
Mol Psychiatry 2017;22:250-6. DOI PubMed PMC
85. Hannon E, Schendel D, Ladd-Acosta C, et al; iPSYCH-Broad ASD Group. Elevated polygenic burden for autism is associated with
differential DNA methylation at birth. Genome Med 2018;10:19. DOI PubMed PMC
86. Spiers H, Hannon E, Schalkwyk LC, et al. Methylomic trajectories across human fetal brain development. Genome Res 2015;25:338-
52. DOI PubMed PMC
87. Miller JA, Ding SL, Sunkin SM, et al. Transcriptional landscape of the prenatal human brain. Nature 2014;508:199-206. DOI
PubMed PMC
88. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol
2015;11:e1004219. DOI PubMed PMC
89. Kulakovskiy IV, Vorontsov IE, Yevshin IS, et al. HOCOMOCO: towards a complete collection of transcription factor binding
models for human and mouse via large-scale ChIP-Seq analysis. Nucleic Acids Res 2018;46:D252-9. DOI PubMed PMC
90. Grant CE, Bailey TL, Noble WS. FIMO: scanning for occurrences of a given motif. Bioinformatics 2011;27:1017-8. DOI PubMed
PMC
91. Shen L, Sinai M. GeneOverlap: Test and visualize gene overlaps. R package version 1.2.0. 2013. Available from: http://shenlab-
sinai.github.io/shenlab-sinai/. [Last accessed on 7 Jun 2021].
92. Hoffman GE, Bendl J, Voloudakis G, et al. CommonMind Consortium provides transcriptomic and epigenomic data for
Schizophrenia and Bipolar Disorder. Sci Data 2019;6:180. DOI PubMed PMC
93. Gearing LJ, Cumming HE, Chapman R, et al. CiiiDER: A tool for predicting and analysing transcription factor binding sites. PLoS
One 2019;14:e0215495. DOI PubMed PMC
94. Metsalu T, Vilo J. ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and
heatmap. Nucleic Acids Res 2015;43:W566-70. DOI PubMed PMC
95. McKenzie AT, Wang M, Hauberg ME, et al. Brain cell type specific gene expression and co-expression network architectures. Sci
Rep 2018;8:8868. DOI PubMed PMC