Polderman TJC, Benyamin B, de Leeuw CA, Sullivan PF, van Bochoven A, Visscher PM, et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet. 2015;47:702–9.

Article  CAS  PubMed  Google Scholar 

Geschwind DH, Flint J. Genetics and genomics of psychiatric disease. Science. 2015;349:1489–94.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Schaid DJ, Chen W, Larson NB. From genome-wide associations to candidate causal variants by statistical fine-mapping. Nat Rev Genet. 2018;19:491–504.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gandal MJ, Leppa V, Won H, Parikshak NN, Geschwind DH. The road to precision psychiatry: translating genetics into disease mechanisms. Nat Neurosci. 2016;19:1397–407.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Nica AC, Dermitzakis ET. Expression quantitative trait loci: present and future. Philos Trans R Soc Lond B Biol Sci. 2013;368:20120362.

Article  PubMed  PubMed Central  Google Scholar 

de la Torre-Ubieta L, Stein JL, Won H, Opland CK, Liang D, Lu D, et al. The dynamic landscape of open chromatin during human cortical neurogenesis. Cell. 2018;172:289-304.e18.

Article  PubMed  PubMed Central  Google Scholar 

Cockerill PN. Structure and function of active chromatin and DNase I hypersensitive sites. FEBS J. 2011;278:2182–210.

Article  CAS  PubMed  Google Scholar 

Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005;15:1034–50.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lu M, Zhang Y, Yang F, Mai J, Gao Q, Xu X, et al. TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies. Nucleic Acids Res. 2023;51:D1179–87.

Article  CAS  PubMed  Google Scholar 

Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx BWJH, et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016;48:245–52.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gamazon ER, Wheeler HE, Shah KP, Mozaffari SV, Aquino-Michaels K, Carroll RJ, et al. A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. 2015;47:1091–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Barbeira AN, Dickinson SP, Bonazzola R, Zheng J, Wheeler HE, Torres JM, et al. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun. 2018;9:1825.

Article  PubMed  PubMed Central  Google Scholar 

Wainberg M, Sinnott-Armstrong N, Mancuso N, Barbeira AN, Knowles DA, Golan D, et al. Opportunities and challenges for transcriptome-wide association studies. Nat Genet. 2019;51:592–9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang J, Xie S, Gonzales S, Liu J, Wang X. A fast and powerful eQTL weighted method to detect genes associated with complex trait using GWAS summary data. Genet Epidemiol. 2020;44:550–63.

Article  PubMed  Google Scholar 

Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48:481–7.

Article  CAS  PubMed  Google Scholar 

Hauberg ME, Zhang W, Giambartolomei C, Franzén O, Morris DL, Vyse TJ, et al. Large-scale identification of common trait and disease variants affecting gene expression. Am J Hum Genet. 2017;100:885–94.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pavlides JMW, Zhu Z, Gratten J, McRae AF, Wray NR, Yang J. Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits. Genome Med. 2016;8:84.

Article  PubMed  PubMed Central  Google Scholar 

Li YI, van de Geijn B, Raj A, Knowles DA, Petti AA, Golan D, et al. RNA splicing is a primary link between genetic variation and disease. Science. 2016;352:600–4.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Walker RL, Ramaswami G, Hartl C, Mancuso N, Gandal MJ, de la Torre-Ubieta L, et al. Genetic control of expression and splicing in developing human brain informs disease mechanisms. Cell. 2019;179:750-771.e22.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Howard DM, Adams MJ, Clarke T-K, Hafferty JD, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–352.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wingo AP, Fan W, Duong DM, Gerasimov ES, Dammer EB, Liu Y, et al. Shared proteomic effects of cerebral atherosclerosis and Alzheimer’s disease on the human brain. Nat Neurosci. 2020;23:696–700.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ahuja N, Sharma AR, Baylin SB. Epigenetic therapeutics: a new weapon in the war against cancer. Annu Rev Med. 2016;67:73–89.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Horvath S, Zhang Y, Langfelder P, Kahn RS, Boks MPM, van Eijk K, et al. Aging effects on DNA methylation modules in human brain and blood tissue. Genome Biol. 2012;13:R97.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Klose RJ, Bird AP. Genomic DNA methylation: the mark and its mediators. Trends Biochem Sci. 2006;31:89–97.

Article  CAS  PubMed  Google Scholar 

Liu D, Wang Y, Jing H, Meng Q, Yang J. Mendelian randomization integrating GWAS and DNA methylation quantitative trait loci data identified novel pleiotropic DNA methylation loci for neuropathology of Alzheimer’s disease. Neurobiol Aging. 2021;97:18–27.

Article  CAS  PubMed  Google Scholar 

Yang C, Hu Y, Zhou B, Bao Y, Li Z, Gong C, et al. The role of m6A modification in physiology and disease. Cell Death Dis. 2020;11:960.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Roundtree IA, Evans ME, Pan T, He C. Dynamic RNA modifications in gene expression regulation. Cell. 2017;169:1187–200.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Frye M, Harada BT, Behm M, He C. RNA modifications modulate gene expression during development. Science. 2018;361:1346–9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang Z, Luo K, Zou Z, Qiu M, Tian J, Sieh L, et al. Genetic analyses support the contribution of mRNA N6-methyladenosine (m6A) modification to human disease heritability. Nat Genet. 2020;52:939–49.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:2535.

Article  Google Scholar 

Zhang W, Voloudakis G, Rajagopal VM, Readhead B, Dudley JT, Schadt EE, et al. Integrative transcriptome imputation reveals tissue-specific and shared biological mechanisms mediating susceptibility to complex traits. Nat Commun. 2019;10:3834.

Article  PubMed  PubMed Central  Google Scholar 

Barbeira AN, Pividori M, Zheng J, Wheeler HE, Nicolae DL, Im HK. Integrating predicted transcriptome from multiple tissues improves association detection. PLoS Genet. 2019;15: e1007889.

Article  PubMed  PubMed Central  Google Scholar 

Zhou D, Jiang Y, Zhong X, Cox NJ, Liu C, Gamazon ER. A unified framework for joint-tissue transcriptome-wide association and Mendelian randomization analysis. Nat Genet. 2020;52:1239–46.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hu Y, Li M, Lu Q, Weng H, Wang J, Zekavat SM, et al. A statistical framework for cross-tissue transcriptome-wide association analysis. Nat Genet. 2019;51:568–76.

Article  CAS  PubMed  PubMed Central