Association of a reproducible epigenetic risk profile for schizophrenia with brain methylation and function
Open accessAbstract
Importance: Schizophrenia is a severe mental disorder in which epigenetic mechanisms may contribute to illness risk. Epigenetic profiles can be derived from blood cells, but to our knowledge, it is unknown whether these predict established brain alterations associated with schizophrenia. Objective: To identify an epigenetic signature (quantified as polymethylation score [PMS]) of schizophrenia using machine learning applied to genome-wide blood DNA-methylation data; evaluate whether differences in blood-derived PMS are mirrored in data from postmortem brain samples; test whether the PMS is associated with alterations of dorsolateral prefrontal cortex hippocampal (DLPFC-HC) connectivity during working memory in healthy controls (HC); explore the association between interactions between polygenic and epigenetic risk with DLPFC-HC connectivity; and test the specificity of the signature compared with other serious psychiatric disorders. Design, Setting, and Participants: In this case-control study conducted from 2008 to 2018 in sites in Germany, the United Kingdom, the United States, and Australia, blood DNA-methylation data from 2230 whole-blood samples from 6 independent cohorts comprising HC (1238 [55.5%]) and participants with schizophrenia (803 [36.0%]), bipolar disorder (39 [1.7%]), major depressive disorder 35 [1.6%]), and autism (27 [1.2%]), and first-degree relatives of all patient groups (88 [3.9%]) were analyzed. DNA-methylation data were further explored from 244 postmortem DLPFC samples from 136 HC and 108 patients with schizophrenia. Neuroimaging and genome-wide association data were available for 393 HC. The latter data was used to calculate a polygenic risk score (PRS) for schizophrenia. The data were analyzed in 2019. Main Outcomes and Measures: The accuracy of schizophrenia control classification based on machine learning using epigenetic data; association of schizophrenia PMS scores with DLPFC-HC connectivity; and association of the interaction between PRS and PMS with DLPFC-HC connectivity. Results: This study included 7488 participants (4395 men [58.7%]), of whom 3158 (2230 men [70.6%]) received a diagnosis of schizophrenia. The PMS signature was associated with schizophrenia across 3 independent data sets (area under the curve [AUC] from 0.69 to 0.78; P value from 0.049 to 1.24 × 10-7) and data from postmortem DLPFC samples (AUC = 0.63; P = 1.42 × 10-4), but not with major depressive disorder (AUC = 0.51; P = .16), autism (AUC = 0.53; P = .66), or bipolar disorder (AUC = 0.58; P = .21). Pathways contributing most to the classification included synaptic processes. Healthy controls with schizophrenia-like PMS showed significantly altered DLPFC-HC connectivity (validation methylation/magnetic resonance imaging, t < -3.81; P for familywise error, <.04; validation magnetic resonance imaging, t < -3.54; P for familywise error, <.02), mirroring the lack of functional decoupling in schizophrenia. There was no significant association of the interaction between PMS and PRS with DLPFC-HC connectivity (P > .19). Conclusions and Relevance: We identified a reproducible blood DNA-methylation signature specific for schizophrenia that was correlated with altered functional DLPFC-HC coupling during working memory and mapped to methylation differences found in DLPFC postmortem samples. This indicates a possible epigenetic contribution to a schizophrenia intermediate phenotype and suggests that PMS could be of interest to be studied in the context of multimodal biomarkers for disease stratification and treatment personalization.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Individually the DNA methylation differences may be too small to have strong predictive power as a biomarker, but together they may have utility as a molecular classifier.
“While individually they may be too small to have a strong predictive power as a biomarker, together they may have utility as a molecular classifier (Chen et al., 2020).”
From DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia (2021) · cites this paper as Chen et al., 2020
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
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 · see citing works
Implications of Normal Brain Development for the Pathogenesis of Schizophrenia
Weinberger, D. R. (1987) · Archives of General Psychiatry · doi:10.1001/archpsyc.1987.01800190080012 · Cited by 3,724 · see citing works
Schizophrenia as a Complex Trait: Evidence From a Meta-analysis of Twin Studies
Sullivan, P. F., Kendler, K. S., & Neale, M. C. (2003) · Archives of General Psychiatry · doi:10.1001/archpsyc.60.12.1187 · Cited by 2,356 · see citing works
Schizophrenia genes, gene expression, and neuropathology: on the matter of their convergence
Harrison, P. J., & Weinberger, D. R. (2005) · Molecular Psychiatry · doi:10.1038/sj.mp.4001558 · Cited by 2,020 · see citing works
The environment and schizophrenia
van Os, J., Kenis, G., & Rutten, B. P. F. (2010) · Nature · doi:10.1038/nature09563 · Cited by 1,572 · see citing works
Modelling schizophrenia using human induced pluripotent stem cells
Brennand, K. J., Simone, A., Jou, J., Gelboin-Burkhart, C., Tran, N., Sangar, S., Li, Y., Mu, Y., Chen, G., Yu, D., et al. (2011) · Nature · doi:10.1038/nature09915 · Cited by 1,375 · see citing works
Epigenomic Profiling Reveals DNA-Methylation Changes Associated with Major Psychosis
Mill, J., Tang, T., Kaminsky, Z., Khare, T., Yazdanpanah, S., Bouchard, L., Jia, P., Assadzadeh, A., Flanagan, J., Schumacher, A., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.01.008 · Cited by 773 · see citing works
Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
The Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium (2015) · Nature Neuroscience · doi:10.1038/nn.3922 · Cited by 755 · see citing works
Childhood poverty, chronic stress, and adult working memory
Evans, G. W., & Schamberg, M. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811910106 · Cited by 724 · see citing works
van Os, J., Rutten, B. P., & Poulton, R. (2008) · Schizophrenia Bulletin · doi:10.1093/schbul/sbn117 · Cited by 713 · see citing works
The environment and susceptibility to schizophrenia
Brown, A. S. (2011) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2010.09.003 · Cited by 664 · see citing works
To Model a Psychiatric Disorder in Animals Schizophrenia As a Reality Test
Lipska, B. K. (2000) · Neuropsychopharmacology · doi:10.1016/s0893-133x(00)00137-8 · Cited by 650 · see citing works
Meyer-Lindenberg, A. S., Olsen, R. K., Kohn, P. D., Brown, T., Egan, M. F., Weinberger, D. R., & Berman, K. F. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.4.379 · Cited by 574 · see citing works
Self-citationGene Ontology Annotations and Resources
The Gene Ontology Consortium (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1050 · Cited by 555 · see citing works
Synaptic dysregulation in a human iPS cell model of mental disorders
Wen, Z., Nguyen, H. N., Guo, Z., Lalli, M. A., Wang, X., Su, Y., Kim, N.-S., Yoon, K.-J., Shin, J., Zhang, C., et al. (2014) · Nature · doi:10.1038/nature13716 · Cited by 549 · see citing works
Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex
Jaffe, A. E., Gao, Y., Deep-Soboslay, A., Tao, R., Hyde, T. M., Weinberger, D. R., & Kleinman, J. E. (2016) · Nature Neuroscience · doi:10.1038/nn.4181 · Cited by 511 · see citing works
Genetic insights into the neurodevelopmental origins of schizophrenia
Birnbaum, R., & Weinberger, D. R. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2017.125 · Cited by 493 · see citing works
Braun, P. R., Han, S., Hing, B., Nagahama, Y., Gaul, L. N., Heinzman, J. T., Grossbach, A. J., Close, L., Dlouhy, B. J., Howard, M. A., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0376-y · Cited by 467 · see citing works
The Genetic Epidemiology of Schizophrenia in a Finnish Twin Cohort
Cannon, T. D., Kaprio, J. A., Lönnqvist, J. K., HUTTUNEN, M. O., & Koskenvuo, M. J. (1998) · Archives of General Psychiatry · doi:10.1001/archpsyc.55.1.67 · Cited by 456 · see citing works
Hannon, E., Lunnon, K., Schalkwyk, L., & Mill, J. (2015) · Epigenetics · doi:10.1080/15592294.2015.1100786 · Cited by 455 · see citing works
Neural Mechanisms of a Genome-Wide Supported Psychosis Variant
Esslinger, C., Walter, H., Kirsch, P., Erk, S., Schnell, K., Arnold, C., Haddad, L., Mier, D., Opitz von Boberfeld, C., Raab, K., et al. (2009) · Science · doi:10.1126/science.1167768 · Cited by 400 · see citing works
Self-citationEpigenetic influences on brain development and plasticity
Fagiolini, M., Jensen, C. L., & Champagne, F. A. (2009) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2009.05.009 · Cited by 362 · see citing works
Hannon, E., Dempster, E., Viana, J., Burrage, J., Smith, A. R., Macdonald, R., St Clair, D., Mustard, C., Breen, G., Therman, S., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-1041-x · Cited by 349 · see citing works
From maps to mechanisms through neuroimaging of schizophrenia
Meyer‐Lindenberg, A. (2010) · Nature · doi:10.1038/nature09569 · Cited by 314 · see citing works
Self-citationThe role of DNA methylation in stress-related psychiatric disorders
Klengel, T., Pape, J., Binder, E. B., & Mehta, D. (2014) · Neuropharmacology · doi:10.1016/j.neuropharm.2014.01.013 · Cited by 309 · see citing works
Exercise training and DNA methylation in humans
Voisin, S. A. C., Eynon, N., Yan, X., & Bishop, D. J. (2014) · Acta Physiologica · doi:10.1111/apha.12414 · Cited by 291 · see citing works
Walton, E., Hass, J., Liu, J., Roffman, J. L., Bernardoni, F., Roessner, V., Kirsch, M., Schackert, G., Calhoun, V., & Ehrlich, S. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbv074 · Cited by 286 · see citing works
Osimo, E. F., Beck, K., Marques, T. R., & Howes, O. D. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0041-5 · Cited by 264 · see citing works
BECon: a tool for interpreting DNA methylation findings from blood in the context of brain
Edgar, R. D., Jones, M. J., Meaney, M. J., Turecki, G., & Kobor, M. S. (2017) · Translational Psychiatry · doi:10.1038/tp.2017.171 · Cited by 261 · see citing works
Aberg, K. A., McClay, J. L., Nerella, S., Clark, S., Kumar, G., Chen, W., Khachane, A. N., Xie, L., Hudson, A., Gao, G., et al. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.3730 · Cited by 248 · see citing works
Bergen, S. E., O'Dushlaine, C. T., Ripke, S., Lee, P. H., Ruderfer, D. M., Akterin, S., Moran, J. L., Chambert, K. D., Handsaker, R. E., Backlund, L., et al. (2012) · Molecular Psychiatry · doi:10.1038/mp.2012.73 · Cited by 239 · see citing works
Alcohol metabolism and epigenetics changes
Zakhari, S. (2013) · Alcohol research · doi:10.35946/arcr.v35.1.02 · Cited by 211 · see citing works
Dietary and Lifestyle Factors of DNA Methylation
Lim, U., & Song, M. (2012) · Methods in molecular biology · doi:10.1007/978-1-61779-612-8_23 · Cited by 206 · see citing works
Ursini, G., Bollati, V., Fazio, L., Porcelli, A., Iacovelli, L., Catalani, A., Sinibaldi, L., Gelao, B., Romano, R., Rampino, A., et al. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.6631-10.2011 · Cited by 188 · see citing works
Altered Cortical Network Dynamics
Rasetti, R. (2011) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2011.103 · Cited by 169 · see citing works
Methylomic profiling of human brain tissue supports a neurodevelopmental origin for schizophrenia
Pidsley, R., Viana, J., Hannon, E., Spiers, H., Troakes, C., Al-Saraj, S., Mechawar, N., Turecki, G., Schalkwyk, L. C., Bray, N. J., et al. (2014) · Genome biology · doi:10.1186/s13059-014-0483-2 · Cited by 157 · see citing works
Phillips, K. G., Bartsch, U., McCarthy, A. P., Edgar, D. M., Tricklebank, M. D., Wafford, K. A., & Jones, M. W. (2012) · Neuron · doi:10.1016/j.neuron.2012.09.016 · Cited by 124 · see citing works
Early Cognitive Experience Prevents Adult Deficits in a Neurodevelopmental Schizophrenia Model
Lee, H., Dvorak, D., Kao, H.-Y., Duffy, Á. M., Scharfman, H. E., & Fenton, A. A. (2012) · Neuron · doi:10.1016/j.neuron.2012.06.016 · Cited by 122 · see citing works
DNA methylation regulates neuronal glutamatergic synaptic scaling
Meadows, J. P., Guzman-Karlsson, M. C., Phillips, S., Holleman, C., Posey, J. L., Day, J. J., Hablitz, J. J., & Sweatt, J. D. (2015) · Science Signaling · doi:10.1126/scisignal.aab0715 · Cited by 111 · see citing works
DNA methylation in schizophrenia: progress and challenges of epigenetic studies
Nishioka, M., Bundo, M., Kasai, K., & Iwamoto, K. (2012) · Genome Medicine · doi:10.1186/gm397 · Cited by 90 · see citing works
DNA methylation in peripheral tissue of schizophrenia and bipolar disorder: a systematic review
Teroganova, N., Girshkin, L., Suter, C. M., & Green, M. J. (2016) · BMC Genetics · doi:10.1186/s12863-016-0332-2 · Cited by 86 · see citing works
Lenzenweger, M. F. (2013) · Depression and Anxiety · doi:10.1002/da.22042 · Cited by 84 · see citing works
Vargas, T., Lam, P. H., Azis, M., Osborne, K. J., Lieberman, A. J., & Mittal, V. A. (2018) · Schizophrenia Bulletin · doi:10.1093/schbul/sby150 · Cited by 75 · see citing works
Walton, E., Liu, J.-Y., Hass, J., White, T., Scholz, M., Roessner, V., Gollub, R., Calhoun, V., & Ehrlich, S. (2014) · Epigenetics · doi:10.4161/epi.29223 · Cited by 66 · see citing works
Review: DNA methylation and alcohol use disorders: Progress and challenges
Zhang, H., & Gelernter, J. E. (2016) · American Journal on Addictions · doi:10.1111/ajad.12465 · Cited by 65 · see citing works
BDNF rs6265 methylation and genotype interact on risk for schizophrenia
Ursini, G., Cavalleri, T., Fazio, L., Angrisano, T., Iacovelli, L., Porcelli, A., Maddalena, G., Punzi, G., Mancini, M., Gelao, B., et al. (2016) · Epigenetics · doi:10.1080/15592294.2015.1117736 · Cited by 62 · see citing works
Bähner, F., Demanuele, C., Schweiger, J. I., Gerchen, M. F., Zamoscik, V., Ueltzhöffer, K. J., Hahn, T., Meyer, P., Flor, H., Durstewitz, D., et al. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.13 · Cited by 57 · see citing works
Self-citationAltered Functional Subnetwork During Emotional Face Processing
Cao, H., Bertolino, A., Walter, H., Schneider, M., Schäfer, A., Taurisano, P., Blasi, G., Haddad, L., Grimm, O., Otto, K., et al. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2016.0161 · Cited by 49 · see citing works
Self-citationWorking memory genetics in schizophrenia and related disorders: An RDoC perspective
Schwarz, E., Tost, H., & Meyer‐Lindenberg, A. (2015) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32353 · Cited by 44 · see citing works
Self-citationSchneider, M., Walter, H., Moessnang, C., Schäfer, A., Erk, S., Mohnke, S., Romund, L., Garbusow, M., Dixson, L., Heinz, A., et al. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx001 · Cited by 43 · see citing works
Self-citationErk, S., Mohnke, S., Ripke, S., Lett, T. A. P., Veer, I. M., Wackerhagen, C., Grimm, O., Romanczuk‐Seiferth, N., Degenhardt, F., Tost, H., et al. (2017) · Translational Psychiatry · doi:10.1038/tp.2016.272 · Cited by 38 · see citing works
Self-citationMiller, J. A., Scult, M. A., Drabant, E. M., Chen, Q., Weinberger, D. R., & Hariri, A. R. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx140 · Cited by 26 · see citing works
Geiger, L. S., Moessnang, C., Schäfer, A., Zang, Z., Zangl, M., Cao, H., van Raalten, T. R., Meyer‐Lindenberg, A., & Tost, H. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1679-0 · Cited by 24 · see citing works
Self-citationCecil, C. A. M., Walton, E., & Viding, E. M. (2015) · Current Addiction Reports · doi:10.1007/s40429-015-0072-9 · Cited by 22 · see citing works
Lewis, C. R., Henderson-Smith, A., Breitenstein, R. S., Sowards, H., Piras, I. S., Huentelman, M. J., Doane, L. D., & Lemery‐Chalfant, K. (2019) · Epigenetics · doi:10.1080/15592294.2019.1583032 · Cited by 22 · see citing works
(2012) · Methods in molecular biology · doi:10.1007/978-1-61779-612-8 · Cited by 6 · see citing works
Chen, J., & Schwarz, E. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1712.00336 · Cited by 5 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Candidate biomarkers in psychiatric disorders: state of the field
Abi‐Dargham, A., Moeller, S. J., Ali, F., DeLorenzo, C., Domschke, K., Horga, G., Jutla, A., Kotov, R., Paulus, M. P., Rubio, J. M., et al. (2023) · World Psychiatry · doi:10.1002/wps.21078 · Cited by 390 · see citing works
The potential of using blood circular RNA as liquid biopsy biomarker for human diseases
Wen, G., Zhou, T., & Gu, W. (2020) · Protein & Cell · doi:10.1007/s13238-020-00799-3 · Cited by 178 · see citing works
Hannon, E., Dempster, E. L., Mansell, G., Burrage, J., Bass, N., Bohlken, M. M., Corvin, A., Curtis, C. J., Dempster, D., Di Forti, M., et al. (2021) · eLife · doi:10.7554/elife.58430 · Cited by 132 · see citing works
“While individually they may be too small to have a strong predictive power as a biomarker, together they may have utility as a molecular classifier ( Chen et al., 2020 ).”
The DNA Methylation in Neurological Diseases
Younesian, S., Yousefi, A., Momeny, M., Ghaffari, S. H., & Bashash, D. (2022) · Cells · doi:10.3390/cells11213439 · Cited by 128 · see citing works
Tornero-Costa, R., Martínez-Millana, A., Muscat, N. A., Lazëri, L., Traver, V., & Novillo-Ortiz, D. (2023) · JMIR Mental Health · doi:10.2196/42045 · Cited by 118 · see citing works
Flack, N., Colwell, M., Drown, C., & Faulk, C. D. (2021) · Clinical Epigenetics · doi:10.1186/s13148-020-00993-4 · Cited by 72 · see citing works
Cecil, C. A. M., & Nigg, J. T. (2022) · Molecular Diagnosis & Therapy · doi:10.1007/s40291-022-00609-y · Cited by 71 · see citing works
Molecular mechanisms of psychiatric diseases
Blokhin, I. O., Khorkova, O., Saveanu, R. V., & Wahlestedt, C. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.105136 · Cited by 58 · see citing works
Colombo, F., Calesella, F., Mazza, M. G., Melloni, E. M. T., Morelli, M. J., Scotti, G. M., Benedetti, F., Bollettini, I., & Vai, B. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104552 · Cited by 52 · see citing works
Cognitive impairment in psychiatric diseases: Biomarkers of diagnosis, treatment, and prevention
Wang, Y., Meng, W., Liu, Z., An, Q., & Hu, X. (2022) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2022.1046692 · Cited by 49 · see citing works
Large-scale brain functional network abnormalities in social anxiety disorder
Zhang, X., Yang, X., Wu, B., Pan, N., He, M., Wang, S., Kemp, G. J., & Gong, Q. (2022) · Psychological Medicine · doi:10.1017/s0033291722003439 · Cited by 48 · see citing works
Guo, L., Su, Y., Zhang, Y., Yu, H., Lu, Z., Li, W., Yang, Y., Xiao, X., Yan, H., Lu, T., et al. (2023) · Military Medical Research · doi:10.1186/s40779-023-00459-7 · Cited by 39 · see citing works
Epigenetics applied to child and adolescent mental health: Progress, challenges and opportunities
Cecil, C. A. M., Neumann, A., & Walton, E. (2022) · JCPP Advances · doi:10.1002/jcv2.12133 · Cited by 33 · see citing works
A machine learning case–control classifier for schizophrenia based on DNA methylation in blood
Gunasekara, C., Hannon, E. J., MacKay, H., Coarfa, C., McQuillin, A., Clair, D. S., Mill, J. S., & Waterland, R. A. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01496-3 · Cited by 32 · see citing works
Cecula, P., Yu, J., Dawoodbhoy, F. M., Delaney, J., Tan, J. S., Peacock, I., & Cox, B. M. (2021) · Heliyon · doi:10.1016/j.heliyon.2021.e06626 · Cited by 32 · see citing works
A comparison of the genes and genesets identified by GWAS and EWAS of fifteen complex traits
Battram, T., Gaunt, T., Relton, C., Timpson, N., & Hemani, G. (2022) · Nature Communications · doi:10.1038/s41467-022-35037-3 · Cited by 6 · see citing works
Conole, E. L. S., Vaher, K., Blesa, M., Sullivan, G., Stevenson, A. J., Hall, J., Murphy, L., Thrippleton, M. J., Quigley, A. J., Bastin, M. E., et al. (2023) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2023.03.011 · Cited by 25 · see citing works
Lessons Learned From Parsing Genetic Risk for Schizophrenia Into Biological Pathways
Pergola, G., Penzel, N., Sportelli, L., & Bertolino, A. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.10.009 · Cited by 24 · see citing works
Machine Learning and Non-Affective Psychosis: Identification, Differential Diagnosis, and Treatment
Ferrara, M., Franchini, G., Funaro, M. C., Cutroni, M., Valier, B., Toffanin, T., Palagini, L., Zerbinati, L., Folesani, F., Murri, M. B., et al. (2022) · Current Psychiatry Reports · doi:10.1007/s11920-022-01399-0 · Cited by 21 · see citing works
Environmental epigenetics: new horizons in redefining biological and health outcomes
Faraji, J., & Metz, G. A. S. (2026) · Environment International · doi:10.1016/j.envint.2026.110072 · Cited by 21 · see citing works
van Calker, D., & Serchov, T. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.03.019 · Cited by 19 · see citing works
Özçelik, F., Dündar, M. S., Yildirim, A. B., HENEHAN, G. T. M., Vicente, O., Sánchez-Alcázar, J. A., Gökçe, N., Yildirim, D. T., Bingol, N. N., Plaseska‐Karanfilska, D., et al. (2024) · Functional & Integrative Genomics · doi:10.1007/s10142-024-01417-9 · Cited by 21 · see citing works
Lian, K., Li, Y., Yang, W. H., Ye, J., Liu, H., Wang, T., Yang, G., Cheng, Y., & Xu, X. (2024) · IBRO Neuroscience Reports · doi:10.1016/j.ibneur.2024.01.007 · Cited by 16 · see citing works
Jameei, H., Rakesh, D., Zalesky, A., Cairns, M. J., Reay, W. R., Wray, N. R., & Biase, M. A. D. (2023) · Schizophrenia Bulletin · doi:10.1093/schbul/sbad087 · Cited by 15 · see citing works
Zhang, X., Lai, H., Li, Q., Yang, X., Pan, N., He, M., Kemp, G. J., Wang, S., & Gong, Q. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad231 · Cited by 15 · see citing works
Multimodal Associations of FKBP5 Methylation with Emotion-Regulatory Brain Circuits.
Kremer, T. L., Chen, J., Buhl, A., Berhe, O., Bilek, E., Geiger-Primo, L. S., Ma, R., Moessnang, C., Reichert, M., Reinhard, I., et al. (2024) · Biological Psychiatry · doi:10.1016/j.biopsych.2024.03.003 · Cited by 15 · see citing works
Self-citationAssociations of age, sex, sexual abuse, and genotype with monoamine oxidase a gene methylation
Checknita, D., Tiihonen, J., Hodgins, S., & Nilsson, K. W. (2021) · Journal of Neural Transmission · doi:10.1007/s00702-021-02403-2 · Cited by 14 · see citing works
Pan, L., Zhu, J., Wang, S., Zhuang, H., Zhang, S., Huang, Z., Cai, F., Song, Z., Liu, Y., Liu, W., et al. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105829 · Cited by 14 · see citing works
Self-citationKikuchi, M., Nakazawa, T., Kinoshita, M., Yamamori, H., Yasuda, Y., Fujimoto, M., Hashimoto, R., & Numata, S. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.734606 · Cited by 14 · see citing works
van Houtum, L. A. E. M., Baaré, W. F. C., Beckmann, C. F., Castro‐Fornieles, J., Cecil, C. A. M., Dittrich, J., Ebdrup, B. H., Fegert, J. M., Havdahl, A., Hillegers, M. H. J., et al. (2024) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-024-02423-9 · Cited by 12 · see citing works
Yang, H., Sun, W., Li, J., & Zhang, X. (2025) · Annals of General Psychiatry · doi:10.1186/s12991-025-00557-x · Cited by 16 · see citing works
Karaglani, M., Agorastos, A., Παναγοπούλου, Μ., Parlapani, E., Athanasis, P., Bitsios, P., Tzitzikou, K., Θεοδοσίου, Θ., Iliopoulos, I., Bozikas, V., et al. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02946-4 · Cited by 11 · see citing works
Ni, P., Zhou, C., Liang, S., Jiang, Y., Liu, D., Shao, Z., Noh, H., Zhao, L., Yang, T., Zhang, C., et al. (2023) · Advanced Science · doi:10.1002/advs.202300455 · Cited by 10 · see citing works
BioM2: biologically informed multi-stage machine learning for phenotype prediction using omics data
Zhang, S., Li, P., Wang, S., Zhu, J., Huang, Z., Cai, F., Freidel, S., Ling, F., Schwarz, E., & Chen, J. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae384 · Cited by 11 · see citing works
Self-citationBartolomeo, M. D., Čerňanová, A., Petrušová, V., Martino, S. D., Hodosy, J., Drago, F., Micale, V., & D’Addario, C. (2024) · Pharmacological Research · doi:10.1016/j.phrs.2024.107343 · Cited by 9 · see citing works
Luo, M., Walton, E., Neumann, A., Thio, C. H. L., Felix, J. F., van IJzendoorn, M. H., Pappa, I., & Cecil, C. A. M. (2023) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13866 · Cited by 9 · see citing works
Hao, M., Qin, Y., Li, Y., Tang, Y., Ma, Z., Tan, J., Li, J., Wang, F., & Gong, X. (2023) · Psychiatry Research · doi:10.1016/j.psychres.2023.115605 · Cited by 9 · see citing works
Wigley, I. L. C. M., Mascheroni, E., Peruzzo, D., Giorda, R., Bonichini, S., & Montirosso, R. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.672786 · Cited by 9 · see citing works
Blostein, F., Fisher, J., Dou, J., Schneper, L. M., Ware, E. B., Notterman, D. A., Mitchell, C. M., & Bakulski, K. M. (2022) · Epigenetics · doi:10.1080/15592294.2022.2112815 · Cited by 7 · see citing works
Zhang, S., Shi, K., Lyu, N., Zhang, Y., Liang, G., Zhang, W., Wang, X., Wen, H., Wen, L., Ma, H., et al. (2023) · The World Journal of Biological Psychiatry · doi:10.1080/15622975.2023.2198595 · Cited by 7 · see citing works
Epigenetic Association Analyses and Risk Prediction of RLS
Harrer, P., Mirza‐Schreiber, N., Schmoll, V., Roeber, S., Stefani, A., Naher, S., Wagner, M., Gieger, C., Waldenberger, M., Peters, A., et al. (2023) · Movement Disorders · doi:10.1002/mds.29440 · Cited by 7 · see citing works
The Potential for Artificial Intelligence Applied to Epigenetics
Vinciguerra, M. (2023) · Mayo Clinic Proceedings Digital Health · doi:10.1016/j.mcpdig.2023.07.005 · Cited by 7 · see citing works
A review of disease risk prediction methods and applications in the omics era
Sun, C., Cheng, X., Xu, J., Chen, H., Tao, J., Dong, Y., Wei, S., Chen, R., Meng, X., Ma, Y., et al. (2024) · PROTEOMICS · doi:10.1002/pmic.202300359 · Cited by 7 · see citing works
Hirjak, D., Reininghaus, U., Braun, U., Sack, M., Tost, H., & Meyer‐Lindenberg, A. (2021) · Der Nervenarzt · doi:10.1007/s00115-021-01086-0 · Cited by 7 · see citing works
Self-citationWang, P., Zang, Z., Zhang, M., Cao, Y., Zhao, Z., Shan, Y., Ma, Q., & Lu, J. (2021) · Neural Plasticity · doi:10.1155/2021/7031178 · Cited by 6 · see citing works
Self-citationCoto-Vílchez, C., Martínez-Magaña, J. J., Mora-Villalobos, L., Valerio, D., Genis-Mendoza, A. D., Silverman, J. M., Nicolini, H., Raventós, H., & Chavarria-Soley, G. (2021) · CNS Spectrums · doi:10.1017/s109285292100105x · Cited by 5 · see citing works
Hyper-Coordinated DNA Methylation is Altered in Schizophrenia and Associated with Brain Function
Chen, J., Schwarz, K., Zang, Z., Braun, U., Harneit, A., Kremer, T. L., Ma, R., Schweiger, J. I., Moessnang, C., Geiger, L. S., et al. (2021) · Schizophrenia Bulletin Open · doi:10.1093/schizbullopen/sgab036 · Cited by 4 · see citing works
Self-citationGan, Y., Yue, W., Sun, J., Yang, D., Fang, C.-X., Zhou, Z., Yin, J.-J., & Zhou, H.-L. (2025) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s513992 · Cited by 2 · see citing works
Age of Onset, Brain Controllability, and Working Memory Performance in First-Episode Schizophrenia
Wang, F., Liu, Z., Yang, J., Cheng, P., Tan, W., Huang, D., Liu, X., Zhong, M., Yang, J., & Palaniyappan, L. K. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf156 · Cited by 2 · see citing works
Wang, B., Zhu, X., Chen, L., Liu, S., & Wang, C. (2025) · PLoS ONE · doi:10.1371/journal.pone.0337847 · Cited by 2 · see citing works
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 · see citing works
Self-citationDiscordant monozygotic twin studies of epigenetic mechanisms in mental health
van Dongen, J., Odintsova, V. V., & Boomsma, D. I. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-820951-6.00003-x · Cited by 1 · see citing works
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 · see citing works
5-Methylcytosine and 5-hydroxymethylcytosine in psychiatric epigenetics
Grayson, D. R., & Dunn, J. T. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823577-5.00033-7
A comparison of the genes and genesets identified by EWAS and GWAS of fourteen complex traitsPreprint
Battram, T., Gaunt, T. R., Relton, C., Timpson, N., & Hemani, G. (2022) · medRxiv · doi:10.1101/2022.03.25.22272928 · Cited by 18 · see citing works
Integrative Neurobiological Approaches to Assessment
Schwarz, E., Tost, H., & Meyer‐Lindenberg, A. (2023) · Springer eBooks · doi:10.1007/978-3-030-42825-9_116-1
Self-citationIntegrative Neurobiological Approaches to Assessment
Schwarz, E., Tost, H., & Meyer‐Lindenberg, A. (2024) · Springer eBooks · doi:10.1007/978-3-030-51366-5_116
Self-citationViana, J. H. D. F., Calife, K. B., Bergamo, F. M. D. A., Battirola, V. H., Ribeiro, F. M., de Freitas, G. D. A. T., Teófilo, R. N. F., & Dossena, C. (2024) · International Journal of Health Science · doi:10.22533/at.ed.15941002418111
Putri, S., Sansuwito, T. B., & Panduragan, S. L. (2024) · Journal of Health Sciences and Epidemiology · doi:10.62404/jhse.v2i3.59
Use of Artificial Intelligence in Epigenetic Studies for Diseases
Ganguly, A. (2025) · Journal of Applied Biochemistry & Laboratory Medicine · doi:10.5005/jablm-11031-0005
Epigenomic alterations in psychiatric disorders and glioblastoma
Šmon, J., Jovčevska, I., Paska, A. V., & Kouter, K. (2025) · Epigenomics · doi:10.1080/17501911.2025.2572960
Sosin, D. N., Khasanova, A. K., Illarionov, R. A., Popova, A. K., Mirzaev, K. B., Glotov, A. S., Mosolov, S. N., & Sychev, D. A. (2025) · Current Issues in Molecular Biology · doi:10.3390/cimb47121020
Guo, L.-K., Su, Y., Zhang, Y., Yu, H., Lu, Z., Li, W.-Q., Yang, Y.-F., Xiao, X., Yan, H., Lu, T.-L., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23290495
Guo, L.-K., Su, Y., Zhang, Y., Yu, H., Lu, Z., Li, W.-Q., Yang, Y.-F., Xiao, X., Yan, H., Lu, T.-L., et al. (2023) · Figshare · doi:10.6084/m9.figshare.23290498
Zhao, Y., Xi, Z., Zang, Z., Yang, Z., & Liu, J. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1705969
Self-citationOhi, K., Fujikane, D., Takai, K., Kuramitsu, A., Muto, Y., Sugiyama, S., & Shioiri, T. (2026) · Bipolar Disorders · doi:10.1111/bdi.70078
Balfour, D., Mittinty, M., Nguyen, D. P., & Cohen‐Woods, S. (2026) · European Neuropsychopharmacology · doi:10.64898/2026.02.17.26346504
MEIJER, M., & Kobor, M. S. (2026) · Handbook of clinical neurology · doi:10.1016/b978-0-443-19043-8.00001-3
- Authors
- Chen, J., Zang, Z., Braun, U., Schwarz, K., Harneit, A., Kremer, T., Ma, R., Schweiger, J., Moessnang, C., Geiger, L., Cao, H., Degenhardt, F., Nöthen, M. M., Tost, H., Meyer-Lindenberg, A., & Schwarz, E.
- Affiliations
- Heidelberg University (DE)
- University of Bonn (DE)
- Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Corresponding author
- Schwarz, Emanuel
- ORCID
- Venue
- JAMA Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 2020-06-01
- Volume
- 77
- Issue
- 6
- Pages
- 628
- ISSN
- 2168-622X (ISSN-L)
- PMC
- PMC7042900
- OpenAlex
- W3005902259
- Cited by
- 69
- References
- 57
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 11 · 2023: 15 · 2022: 11 · 2021: 15 · 2020: 3
- FWCI
- 3.57
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Psychiatry (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Deutsche Forschungsgemeinschaft
- Agence Nationale de la Recherche (ANR-18-PERM-0011)
- 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 › Genetics › Genetic Associations and Epidemiology
- Keywords
- schizophrenia, DNA methylation, polygenic risk score, dorsolateral prefrontal cortex, hippocampus, working memory, postmortem brain, bipolar disorder, major depressive disorder, autism spectrum disorder, mental illness, machine learning
- MeSH terms
- Machine Learning, Adult, Female, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Schizophrenia, Biomarkers, Case-Control Studies, Prefrontal Cortex, DNA Methylation, Epigenesis, Genetic, Genome-Wide Association Study, Neuroimaging
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
