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Methylomic profiling of human brain tissue supports a neurodevelopmental origin for schizophrenia
Open accessAbstract
BACKGROUND: Schizophrenia is a severe neuropsychiatric disorder that is hypothesized to result from disturbances ine arly brain development. There is mounting evidence to support a role for developmentally regulated epigenetic variation in the molecular etiology of the disorder. Here, we describe a systematic study of schizophrenia-associated methylomic variation in the adult brain and its relationship to changes in DNA methylation across human fetal brain development. RESULTS: We profile methylomic variation in matched prefrontal cortex and cerebellum brain tissue from schizophrenia patients and controls, identifying disease-associated differential DNA methylation at multiple loci,particularly in the prefrontal cortex, and confirming these differences in an independent set of adult brain samples.Our data reveal discrete modules of co-methylated loci associated with schizophrenia that are enriched for genes involved in neurodevelopmental processes and include loci implicated by genetic studies of the disorder. Methylomic data from human fetal cortex samples, spanning 23 to 184 days post-conception, indicates that schizophrenia-associated differentially methylated positions are significantly enriched for loci at which DNA methylation is dynamically altered during human fetal brain development. CONCLUSIONS: Our data support the hypothesis that schizophrenia has an important early neurodevelopmental component, and suggest that epigenetic mechanisms may mediate these effects.
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![Figure 2 Schizophrenia-associated gene co-methylation modules in the prefrontal cortex. (A) Heatmap representing correlations between module eigenvalues (ME) and clinical/demographic variables. Each row represents a specific module, indicated by an arbitrary module color labeled on the y-axis. Dark red indicates strong positive correlation, dark green indicates strong negative correlation, and white indicates no correlation, as indicated in color scale bar. P-values are given in parentheses. The black (P = 0.0004) and pink (P = 0.002) WGCNA modules are most significantly associated with schizophrenia in the PFC. (B) Module membership in both modules is strongly correlated with probe significance with disease (black module: r = 0.39, P <1e-200; pink module: r = 0.22, P = 2.4e-49). (C) Ingenuity Pathway Analysis of genes associated with CpG sites in the black module reveals a highly significant enrichment of disease pathways related to schizophrenia and other neuropsychiatric disease. (D) Co-methylation networks between the top 1% of loci in the black and pink modules ranked by their module membership, where thicker lines indicate more connected genes. Black edges represent co-methylation between probes in the black module and pink edges represent co-methylation in the pink module; thicker and deeper colored edges indicate stronger correlations between probes. Interestingly, the two modules are connected by SHANK2, which encodes a molecular scaffold protein that plays a role in synaptogenesis. Furthermore, several of the genes are associated with schizophrenia in recent collaborative genome-wide association studies (GWAS) [27]. GWAS significance for SNPs in the vicinity of each locus is depicted by color.](/paper-figures/f0073f8400ad403eacf99cb582db4903/methylomic-profiling-of-human-brain-tissue-supports-a-neurodevelopmental-origin-figure-2.jpg)

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“Further, EWAS studies have identified differential DNAm in HTR2A (Numata, Ye, Herman, & Lipska, 2014), HTR5A and HTR1E (Nishioka et al., 2013; Pidsley et al., 2014) genes in those with psychosis.”
From Can epigenetics shine a light on the biological pathways underlying major mental disorders? (2022) · cites this paper as Pidsley et al., 2014
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Cites
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
Identifying biological themes within lists of genes with EASE
Hosack, D. A., Dennis, G., Sherman, B. T., Lane, H. C., & Lempicki, R. A. (2003) · Genome biology · doi:10.1186/gb-2003-4-10-r70 · Cited by 1,961
Chen, Y. A., Lemire, M., Choufani, S., Butcher, D. T., Grafodatskaya, D., Zanke, B. W., Gallinger, S., Hudson, T. J., & Weksberg, R. (2013) · Epigenetics · doi:10.4161/epi.23470 · Cited by 1,547
Rare chromosomal deletions and duplications increase risk of schizophrenia
The International Schizophrenia Consortium (2008) · Nature · doi:10.1038/nature07239 · Cited by 1,475
A polygenic burden of rare disruptive mutations in schizophrenia
Purcell, S. M., Moran, J. L., Fromer, M., Ruderfer, D., Solovieff, N., Roussos, P., O’Dushlaine, C., Chambert, K., Bergen, S. E., Kähler, A., et al. (2014) · Nature · doi:10.1038/nature12975 · Cited by 1,385
DNA methylation profiling of human chromosomes 6, 20 and 22
Eckhardt, F., Lewin, J., Cortese, R., Rakyan, V. K., Attwood, J., Burger, M., Burton, J. H., Cox, T. V., Davies, R., Down, T. A., et al. (2006) · Nature Genetics · doi:10.1038/ng1909 · Cited by 1,378
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Nie, F., Zhang, M.-R., Shang, S.-S., Zhang, Q.-X., Zhang, R., Chen, P., & Ma, J. (2020) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.110081 · Cited by 11
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Yan, Q., Forno, E., Celedon, J. C., & Chen, W. (2021) · Epigenetics · doi:10.1080/15592294.2021.1900026 · Cited by 11
Postberg, J., Schubert, M. T., Nin, V., Wagner, L., & Piefke, M. (2024) · Neurogenetics · doi:10.1007/s10048-024-00771-x · Cited by 9
Common epigenetic variation in a European population of mentally healthy young adults
Milnik, A., Vogler, C., Demougin, P., Egli, T., Freytag, V., Hartmann, F., Heck, A., Peter, F., Spalek, K., Steták, A., et al. (2016) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2016.08.012 · Cited by 9
Epigenetic regulation of fetal brain development in pig
Strawn, M., & Behura, S. K. (2022) · Gene · doi:10.1016/j.gene.2022.146823 · Cited by 8
Epigenetic studies of schizophrenia: current status and future directions
Migdalska‐Richards, A., & Mill, J. S. (2019) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.12.003 · Cited by 9
DNA Methylation Differences in Cortical Grey and White Matter in Schizophrenia
van Berlekom, A. B., Notman, N., Sneeboer, M. A. M., Snijders, G. J. L., Houtepen, L. C., Nispeling, D. M., He, Y., Dracheva, S. M., Hol, E. M., Kahn, R. S., et al. (2021) · Epigenomics · doi:10.2217/epi-2021-0077 · Cited by 9
Almodóvar-Payá, C., Guardiola-Ripoll, M., Giralt‐López, M., Gallego, C., Salgado‐Pineda, P., Miret, S., Salvador, R. M., Muñoz, M. J. Z., Lázaro, L., Guerrero‐Pedraza, A., et al. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23137456 · Cited by 9
Properties of the epigenetic clock and age accelerationPreprint
Khoury, L. Y. E., Gorrie-Stone, T. J., Smart, M., Hughes, A., Bao, Y., Andrayas, A., Burrage, J., Hannon, E. J., Meena Kumari, B., Mill, J. S., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/363143 · Cited by 8
Алфимова, М. В., Kondratyev, N. V., Golov, A. K., & Голимбет, В. Е. (2020) · Scientific Reports · doi:10.1038/s41598-020-61671-2 · Cited by 6
Hannon, E. J., Chand, A. N., Evans, M. D., Wong, C. C. Y., Grubb, M. S., & Mill, J. S. (2015) · Neuroepigenetics · doi:10.1016/j.nepig.2015.06.001 · Cited by 6
Epigenetic analysis of human postmortem brain tissue
Islam, S. A., Lussier, A. A., & Kobor, M. S. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63639-3.00017-7 · Cited by 6
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Piao, Y. H., Cui, Y., Rami, F. Z., Li, L., Karamikheirabad, M., Kang, S. H., Kim, S., Kim, J., Lee, B. J., & Chung, Y. (2022) · Clinical Psychopharmacology and Neuroscience · doi:10.9758/cpn.2022.20.3.462 · Cited by 5
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Suetake, I., Watanebe, M., Takeshita, K., Takahashi, S., & Carlton, P. M. (2017) · Cancer drug discovery and develogment/Cancer drug discovery and development · doi:10.1007/978-3-319-59786-7_2 · Cited by 5
Rizzardi, L. F., Hickey, P. F., DiBlasi, V. R., Tryggvadóttir, R., Callahan, C. M., Idrizi, A., Hansen, K. D., & Feinberg, A. P. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/120386 · Cited by 5
Regulation of the brain-placental axis, and its relevance to the health and disease of the offspring
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Mancino, S., Seneviratne, J., Mupo, A., Krueger, F., Oxley, D., Krueger, F., & Oxley, D. (2024) · doi:10.59368/agingbio.20240030 · Cited by 7
Kondratiev, N., Alfimova, M., & Golimbet, V. (2017) · Zhurnal Nevrologii i Psikhiatrii imeni S.S. Korsakova · doi:10.17116/jnevro20171178172-75 · Cited by 3
Hannon, E. J., Dempster, E. L., Chioza, B. A., Davies, J. P., Blake, G. E. T., Burrage, J., Policicchio, S. S. S., Franklin, A., Walker, E., Bamford, R. A., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.23.545974 · Cited by 3
Stability of Genomic Imprinting and X-Chromosome Inactivation in the Aging BrainPreprint
Mancino, S., Seneviratne, J. A., Mupo, A., Krueger, F., Oxley, D., Eckersley-Maslin, M. A., & da Rocha, S. T. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.29.560184 · Cited by 3
Policicchio, S. S. S., Dempster, E. L., & Murphy, T. M. (2018) · OBM Genetics · doi:10.21926/obm.genet.1804039 · Cited by 2
Epigenetics of Psychiatric Disorders
Kundaković, M. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-803239-8.00019-3 · Cited by 3
Alrofaidi, A., Alghamdi, R. S., Alharbi, M. G., Algothmi, K. M., Farsi, R. M., Alburae, N. A., Ganash, M., Basingab, F. S., Azhari, S. A., Alkhatabi, H. A., et al. (2021) · Journal of Pharmaceutical Research International · doi:10.9734/jpri/2021/v33i33b31794 · Cited by 2
Garg, P., Joshi, R. S., Watson, C. T., & Sharp, A. J. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/189704 · Cited by 2
Hu, M., Xia, Y., Zong, X., Sweeney, J. A., Bishop, J. R., Liao, Y., Giase, G. M., Li, B., Rubin, L. H., Wang, Y., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.31.018283 · Cited by 2
DNA co-methylation has a stable structure and is related to specific aspects of genome regulationPreprint
Watkins, S., Suderman, M. J., Hemani, G., Burrows, K., Lawlor, D. A., West, J., Willan, K., Timpson, N. J., Min, J. L., & Gaunt, T. R. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.16.484648 · Cited by 3
Translational medicine in psychiatry: challenges and imaging biomarkers
Meyer‐Lindenberg, A., Tost, H., & Schwarz, E. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-820493-1.00004-0 · Cited by 1
DNA Methyltransferases and Schizophrenia: Current Status
Maroju, P. A., & Mohan, K. N. (2021) · IntechOpen eBooks · doi:10.5772/intechopen.98567 · Cited by 1
Almodóvar-Payá, C., París-Gómez, I., Latorre-Guardia, M., Guardiola-Ripoll, M., Catalán, R., Arias, B., Penadés, R., & Fatjó‐Vilas, M. (2024) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2024.111175 · Cited by 1
Chromatin modification and remodeling in schizophrenia
Duan, J. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813796-3.00014-6 · Cited by 1
Hu, X., Li, M., Wang, L., Li, X., Wu, F., & Wang, J. (2019) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm47256.2019.8983308 · Cited by 1
Epigenetics in mental and neurodegenerative disorders
Iatrou (2018) · Research Publications (Maastricht University) · doi:10.26481/dis.20180712ai · Cited by 1
Hannon, E. J., Dempster, E. L., Mansell, G., Burrage, J., Bass, N. J., Bohlken, M. M., Corvin, A. P., Curtis, C. J. C., Dempster, D. W., Forta, M. D., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.05.026211 · Cited by 1
The biology of schizophrenia as a neurodevelopmental disorder
van Berlekom, A. B. (2022) · Utrecht University Repository (Utrecht University) · doi:10.33540/1269 · Cited by 1
Aas, M., Blokland, G. A. M., Chawner, S. J. R. A., Choi, S. W., Estrada, J., Forsingdal, A., Friedrich, M. U., Ganesham, S., Hall, L. S., Haslinger, D., et al. (2015) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000112
355 Fetal Growth is Associated with Altered Expression of Imprinted Genes in the Placenta
Piyasena, C., Khulan, B., Menon, G. N., & Drake, A. J. (2012) · Archives of Disease in Childhood · doi:10.1136/archdischild-2012-302724.0355
Mukamel, E. A., & Lister, R. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-801596-4.00005-8
沼田, 周., 木下, 誠., & 大森, 哲. (2015) · 日本生物学的精神医学会誌 = Japanese journal of biological psychiatry · doi:10.11249/jsbpjjpp.26.1_7
Dynamics of reaching imago stage by F1 animals after terahertz irradiation of parental Drosophila
Weisman, N. Y., & Fedorov, V. I. (2017) · Russian Journal of Developmental Biology · doi:10.1134/s1062360417020084
Weisman, N. Y., & Golubovsky, M. D. (2017) · Biology Bulletin Reviews · doi:10.1134/s2079086417050073
Functional analysis of evolutionary human methylated regions in schizophrenia patientsPreprint
Banerjee, N., Polushina, T. V., Stavrum, A.-K., Steen, V. M., & Hellard, S. L. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/540294
Circadian Hallmarks of the Aging Epigenome
Ebrahimi, S. B. (2017) · TSpace (University of Toronto)
Big Data and Its Emerging Role in Precision Medicine and Therapeutic Response
Epsi, N. J., Panja, S., & Mitrofanova, A. (2020) · Royal Society of Chemistry eBooks · doi:10.1039/9781788019958-00088
Effect of CpG Sites on Transcription Factor in Promoter of ‘RASA3’ Gene
Algothmi, K. M., Kalboneh, H., Alrofaidi, A., Alharbi, M. G., Farsi, R. M., Alburae, N. A., Ganash, M., Alhebshi, A. M., Basingab, F. S., Azhari, S. A., et al. (2021) · International Journal of Pharmaceutical and Phytopharmacological Research · doi:10.51847/80ckl5vnec
Brain Derived Neurotrophic Factor (BDNF) Gene in Peripheral Blood Cells of Stable Schizophrenia
Zaifah, A. P. D. N. K., Tokhi, E., Rahim, N. E. H. A., Talib, N. A., & Noor, H. M. (2022) · IIUM Medical Journal Malaysia · doi:10.31436/imjm.v21i1.1840
Höffler, K. D., Stavrum, A.-K., O'Connell, K., Weibell, M., Djurovic, S., Andreassen, O. A., Melle, I. S., Hellard, S. L., & Spíndola, L. (2022) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2022.07.288
Regulation of fetal brain development in short versus long lived mice
Islam, M. (2022) · MOspace Institutional Repository (University of Missouri) · doi:10.32469/10355/94012
Biological mechanisms underlying susceptibility to traumatic stress
An, N. (2024) · Research Publications (Maastricht University) · doi:10.26481/dis.20240116an
Giant Platelets as Potential Biomarker for Autism Spectrum Disorder
Sanyour, A., & Alhazmi, S. (2024) · European journal of applied sciences · doi:10.14738/aivp.121.16177
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471409
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Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471430
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471412
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471451
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471418
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Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471442
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471457
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471433
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471454
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471424
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471445
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Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471427
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471415
Almodóvar-Payá, C., Moreno, M., Guardiola-Ripoll, M., Latorre-Guardia, M., Morentín, B., Garcia‐Ruiz, B., Pomarol‐Clotet, E., Callado, L. F., Gallego, C., & Fatjó‐Vilas, M. (2024) · medRxiv · doi:10.1101/2024.10.29.24315982
Hannon, E. J., Dempster, E. L., Davies, J. P., Chioza, B. A., Blake, G. E. T., Burrage, J., Policicchio, S. S. S., Franklin, A., Walker, E., Bamford, R. A., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26672745
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K. E., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471439
Rizzardi, L. F., Hickey, P. F., Idrizi, A., Tryggvadóttir, R., Callahan, C. M., Stephens, K. E., Taverna, S. D., Zhang, H., Ramazanoglu, S., Hansen, K. D., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14471436
Hannon, E. J., Dempster, E. L., Davies, J. P., Chioza, B. A., Blake, G. E. T., Burrage, J., Policicchio, S. S. S., Franklin, A., Walker, E., Bamford, R. A., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26672742
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Metadata
- Authors
- Pidsley, R., Viana, J., Hannon, E., Spiers, H., Troakes, C., Al-Saraj, S., Mechawar, N., Turecki, G., Schalkwyk, L. C., Bray, N. J., & Mill, J.
- Affiliations
- Garvan Institute of Medical Research (AU)
- University of Exeter (GB)
- King's College London (GB)
- Douglas Mental Health University Institute (CA)
- University of Essex (GB)
- Corresponding author
- Mill, Jonathan
- ORCID
- Venue
- Genome biology
- Published
- 2014-10-28
- Volume
- 15
- Issue
- 10
- Pages
- 483-483
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC4262979
- OpenAlex
- W1980511338
- Cited by
- 157
- References
- 40
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 11 · 2023: 6 · 2022: 10 · 2021: 15 · 2020: 11 · 2019: 15 · 2018: 15 · 2017: 25 · 2016: 24 · 2015: 18 · 2014: 2
- FWCI
- 9.42
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- Open Access at Essex (University of Essex) (acceptedVersion)
- Figshare (submittedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (G0700089, GR082557)
- National Institutes of Health
- Medical Research Council (MC_PC_15004, MR/K013807/1, K013807)
- National Institute on Aging (R01AG036039, AG036039)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- schizophrenia, DNA methylation, epigenetics, brain development, prefrontal cortex, cerebellum, fetal brain development, differentially methylated positions
- MeSH terms
- Brain, Cerebellum, Humans, Schizophrenia, Prefrontal Cortex, DNA Methylation, Epigenesis, Genetic, Fetal Development
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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