The DOI matches its Crossref record; 65 of the 66 references it cites were found in a registry or an index.
An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation
Open accessAbstract
BACKGROUND: Schizophrenia is a highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. RESULTS: We performed a multi-stage epigenome-wide association study, quantifying genome-wide patterns of DNA methylation in a total of 1714 individuals from three independent sample cohorts. We have identified multiple differentially methylated positions and regions consistently associated with schizophrenia across the three cohorts; these effects are independent of important confounders such as smoking. We also show that epigenetic variation at multiple loci across the genome contributes to the polygenic nature of schizophrenia. Finally, we show how DNA methylation quantitative trait loci in combination with Bayesian co-localization analyses can be used to annotate extended genomic regions nominated by studies of schizophrenia, and to identify potential regulatory variation causally involved in disease. CONCLUSIONS: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological approach that can be used to inform epigenome-wide association study analyses of other complex traits and diseases. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with etiological variation, and of using DNA methylation quantitative trait loci to refine the functional and regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation.
Overview
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
Figures
![Fig. 1 It is critical to control for smoking in an epigenome-wide association study (EWAS) of schizophrenia. Manhattan plots comparing association P-values (y-axis, −log10 scale) against genomic location (x-axis) for (a) an EWAS of schizophrenia case–control status without inclusion of a smoking covariate, (b) a published EWAS of tobacco smoking (never versus current) [22], and (c) an EWAS of schizophrenia case–control status including a DNA methylation-derived smoking score as a covariate. There is considerable overlap between the associated loci in panels a and b (e.g., on chromosomes 2, 5, 6, and 19), implying that the elevated rate and intensity of smoking in patients with schizophrenia [25–27] is a severe confounder in this analysis. In contrast, there is no overlap in the associated loci shown in panels b and c, suggesting that the derived smoking score effectively removes these false positives](/paper-figures/3dd11689a1dc4123ae5e238aeb3f5cac/an-integrated-genetic-epigenetic-analysis-of-schizophrenia-evidence-for-co-figure-1.jpg)
![Fig. 2 Replication of schizophrenia-associated DNA methylation differences identified in the phase 1 analysis in two independent cohorts. Shown are scatterplots demonstrating the concordance in effect size [schizophrenia-associated DNA methylation difference (%)] between the phase 1 (case–control) cohort (n = 675) (x-axis) and either the (a) phase 2 (case–control) cohort (n = 847) or (b) phase 3 (n = 96 monozygotic twin pairs) cohort for probes associated with schizophrenia at both the experiment-wide (P < 1 × 10−7; red circles) and discovery (P < 5 × 10−5; blue triangles) P-value thresholds. Many of these individual DNA methylation sites are significantly associated with schizophrenia in the replication cohorts (Table 1 and Additional file 2: Table S3). Meta-analyses across the three independent cohorts identified many additional sites significantly associated with schizophrenia at P < 1 × 10−7. (c) A forest plot of the top ranked probe from the meta-analysis (cg02488934), with the effect size and standard error (SE) from each individual cohort and the pooled effect from the meta-analysis. CI confidence interval](/paper-figures/edeb5a4d619a42fb802fffb311cac580/an-integrated-genetic-epigenetic-analysis-of-schizophrenia-evidence-for-co-figure-2.jpg)
![Fig. 4 Evidence for schizophrenia-associated differential DNA methylation within genome-wide association study (GWAS)-nominated genomic regions. A Manhattan plot of an example genomic region (chr10:104423800-105165583) identified in the recent GWAS of schizophrenia [2] illustrates the location (x-axis) of genetic variants and Illumina 450 K probes against their significance with schizophrenia (y-axis; −log10 P value). Gene locations (exons and introns) are depicted above the Manhattan plot. Red diamonds depict GWAS results, green circles depict results from our phase 1 schizophrenia EWAS, and blue triangles depict results from our schizophrenia polygenic risk score EWAS](/paper-figures/5bcbaff9cfcd4123820d9b5aa5ef1dd7/an-integrated-genetic-epigenetic-analysis-of-schizophrenia-evidence-for-co-figure-4.jpg)
Verification
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“An EWAS by Montano et al. (Montano et al. 2016) found differences in DNAm in genes involved in T-cell development in the blood of SCZ patients (ZC3H12D, TCF3, and IKZF4); other EWAS have also reported an enrichment in the immune system pathway by differently methylated genes”
From Can epigenetics shine a light on the biological pathways underlying major mental disorders? (2022) · cites this paper as Hannon et al., 2016
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The confounding effect of smoking is clearly evidenced in an EWAS study on peripheral blood of SCZ patients (Hannon et al., 2016).”
From Can epigenetics shine a light on the biological pathways underlying major mental disorders? (2022) · cites this paper as Hannon et al., 2016
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
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
Self-citationDNA methylation age of human tissues and cell types
Horvath, S. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r115 · Cited by 7,075
Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., Charlson, F. J., Norman, R. E., Flaxman, A. D., Johns, N., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)61611-6 · Cited by 6,006
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
Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
DNA methylation arrays as surrogate measures of cell mixture distribution
Houseman, E. A., Accomando, W. P., Koestler, D. C., Christensen, B. C., Marsit, C. J., Nelson, H. H., Wiencke, J. K., & Kelsey, K. T. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-86 · Cited by 3,175
Mapping and analysis of chromatin state dynamics in nine human cell types
Ernst, J., Kheradpour, P., Mikkelsen, T. S., Shoresh, N., Ward, L. D., Epstein, C. B., Zhang, X., Wang, L., Issner, R., Coyne, M., et al. (2011) · Nature · doi:10.1038/nature09906 · Cited by 2,898
Cited by
Sorted by citations
Items 101–200 of 352
Engelmann, J., Zillich, L., Frank, J., Wagner, S., Cetin, M., Herzog, D. P., Müller, M. B., Tadic, A., Foo, J. C., Sirignano, L., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02032-7 · Cited by 29
Epigenetic age dysregulation in individuals with bipolar disorder and schizophrenia
Jeremian, R., Malinowski, A., Chaudhary, Z., Srivastava, A., Qian, J., Zai, C. C. H., Adanty, C., Fischer, C. E., Burhan, A. M., Kennedy, J. L., et al. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114689 · Cited by 32
Løkhammer, S., Stavrum, A.-K., Polushina, T. V., Aas, M., Ottesen, A. A., Andreassen, O. A., Melle, I. S., & Hellard, S. L. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-01936-8 · Cited by 31
An improved epigenetic counter to track mitotic age in normal and precancerous tissues
Zhu, T., Tong, H., Du, Z., Beck, S., & Teschendorff, A. E. (2024) · Nature Communications · doi:10.1038/s41467-024-48649-8 · Cited by 27
Luijk, R., Wu, H., Ward-Caviness, C. K., Hannon, E. J., Carnero‐Montoro, E., Min, J. L., Mandaviya, P. R., Müller‐Nurasyid, M., Mei, H., van der Maarel, S. M., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05714-3 · Cited by 28
Self-citationReddi, H. V., Wand, H., Funke, B., Zimmermann, M. T., Lebo, M. S., Qian, E., Shirts, B. H., Zou, Y. S., Zhang, B. M., Rose, N. C., et al. (2023) · Genetics in Medicine · doi:10.1016/j.gim.2023.100804 · Cited by 30
Venugopal, D., Shivakumar, V., Subbanna, M., Kalmady, S. V., Amaresha, A. C., Agarwal, S. M., Narayanaswamy, J. C., Banerjee, M., Debnath, M., & Venkatasubramanian, G. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.07.002 · Cited by 28
Methylation age acceleration does not predict mortality in schizophrenia
Kowalec, K., Hannon, E. J., Mansell, G., Burrage, J., Ori, A. P. S., Ophoff, R. A., Mill, J. S., & Sullivan, P. F. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0489-3 · Cited by 26
Self-citationNeuroepigenetics of Schizophrenia
Punzi, G., Bharadwaj, R. A., & Ursini, G. (2018) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2018.04.010 · Cited by 27
A comprehensive map of the aging blood methylome in humans
Seale, K., Teschendorff, A. E., Reiner, A. P., Voisin, S. A. C., & Eynon, N. (2024) · Genome biology · doi:10.1186/s13059-024-03381-w · Cited by 31
DNA Methylation is Predictive of Mortality in Current and Former Smokers
Morrow, J. D., Make, B. J., Regan, E. A., Han, M. K., Hersh, C. P., Tal‐Singer, R., Quackenbush, J. F., Choi, A. M. K., Silverman, E. K., & DeMeo, D. L. (2020) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201902-0439oc · Cited by 27
Pergola, G., Parihar, M., Sportelli, L., Bharadwaj, R. A., Borcuk, C., Radulescu, E., Bellantuono, L., Blasi, G., Chen, Q., Kleinman, J. E., et al. (2023) · Science Advances · doi:10.1126/sciadv.ade2812 · Cited by 26
Human disease genomics: from variants to biology
McCarthy, M. I., & MacArthur, D. G. (2017) · Genome biology · doi:10.1186/s13059-017-1160-z · Cited by 26
Spindola, L. M., Santoro, M. L., Pan, P. M., Ota, V. K., Xavier, G., Carvalho, C. M., Talarico, F., Sleiman, P., March, M., Pellegrino, R., et al. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0740-z · Cited by 25
Owolabi, M. O., Peprah, E. K., Xu, H., Akinyemi, R., Tiwari, H. K., Irvin, M. R., Wahab, K., Arnett, D. K., & Ovbiagele, B. I. (2017) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2017.09.021 · Cited by 26
Research Progress on the Correlation Between Epigenetics and Schizophrenia
Chen, Q., Li, D., Jin, W., Shi, Y., Li, Z., Ma, P., Sun, J., Chen, S., Li, P., & Lin, P. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.688727 · Cited by 26
Peripheral Blood-Based Gene Expression Studies in Schizophrenia: A Systematic Review
Wagh, V. V., Vyas, P., Agrawal, S., Pachpor, T. A., Paralikar, V. P., & Khare, S. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.736483 · Cited by 25
Brägelmann, J., & Bermejo, J. L. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby068 · Cited by 23
Hu, B., Cha, J., Fullerton, J. M., Hesam-Shariati, S., Nakamura, K., Nürnberger, J. I., & Anand, A. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-01892-3 · Cited by 22
Alameda, L., Liu, Z., Sham, P. C., Aas, M., Trotta, G., Rodríguez, V., Forti, M. D., Stilo, S. A., Kandaswamy, R., Arango, C., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02044-9 · Cited by 24
Self-citationWalton, E., Relton, C. L., & Caramaschi, D. (2019) · Genes · doi:10.3390/genes10030193 · Cited by 20
He, Y., de Witte, L. D., Houtepen, L. C., Nispeling, D. M., Xu, Z., Yu, Q., Yu, Y., Hol, E. M., Kahn, R. S., & Boks, M. P. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0680-7 · Cited by 23
Self-citationScreening for rare epigenetic variations in autism and schizophrenia
Garg, P., & Sharp, A. J. (2019) · Human Mutation · doi:10.1002/humu.23740 · Cited by 20
Kiltschewskij, D. J., Reay, W. R., Geaghan, M. P., Atkins, J., Xavier, A., Zhang, X., Watkeys, O. J., Carr, V. J., Scott, R. J., Green, M. J., et al. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.07.010 · Cited by 22
Karpiński, P., Samochowiec, J., Frydecka, D., Sasiadek, M. M., & Misiak, B. (2018) · Schizophrenia Research · doi:10.1016/j.schres.2018.04.026 · Cited by 22
Twin studies of brain structure and cognition in schizophrenia
Besteher, B., Brambilla, P., & Nenadić, I. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.12.021 · Cited by 23
Chan, R. F., Shabalin, A. A., Montaño, C., Hannon, E. J., Hultman, C. M., Fallin, M. D., Feinberg, A. P., Mill, J. S., van den Oord, E. J. C. G., & Åberg, K. A. (2019) · Schizophrenia Bulletin · doi:10.1093/schbul/sbz056 · Cited by 22
Self-citationEpigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity
Nikpay, M., Ravati, S., Dent, R., & McPherson, R. (2021) · Nutrients · doi:10.3390/nu13061984 · Cited by 22
Longitudinal investigation of DNA methylation changes preceding adolescent psychotic experiences
Roberts, S., Suderman, M. J., Zammit, S., Watkins, S., Hannon, E. J., Mill, J. S., Relton, C. L., Arseneault, L., Wong, C. C. Y., & Fisher, H. L. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0407-8 · Cited by 27
Self-citationEffect of metformin on the epigenetic age of peripheral blood in patients with diabetes mellitus
Li, M., Bao, L., Zhu, P., & Wang, S. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.955835 · Cited by 21
Campos-Martín, R., Bey, K., Elsner, B., Reuter, B., Klawohn, J., Philipsen, A., Kathmann, N., Wagner, M., & Ramı́rez, A. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02219-4 · Cited by 21
Delphin, N., Aust, C. E., Griffiths, L. R., & Fernandez, F. (2024) · Genes · doi:10.3390/genes15030272 · Cited by 24
Altered DNA Methylation of the Alu Y Subfamily in Schizophrenia and Bipolar Disorder
Li, S., Zong, L., Hou, Y., Zhang, W., Zhou, L., Yang, Q., Wang, L., Jiang, W., Li, Q., Huang, X., et al. (2019) · Epigenomics · doi:10.2217/epi-2018-0139 · Cited by 22
Hop, P. J., Zwamborn, R. A. J., Hannon, E. J., Dekker, A. M., van Eijk, K. R., Walker, E., Iacoangeli, A., Jones, A. R., Shatunov, A., Khleifat, A. A., et al. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa105 · Cited by 21
Self-citationAn OMIC Biomarker Detection Algorithm TriVote and its Application in Methylomic Biomarker Detection
Xu, C., Liu, J., Yang, W., Shu, Y., Wei, Z., Zheng, W., Feng, X., & Zhou, F. (2018) · Epigenomics · doi:10.2217/epi-2017-0097 · Cited by 20
Methylation risk scores for childhood aeroallergen sensitization: Results from the LISA birth cohort
Kilanowski, A., Chen, J.-Y., Everson, T., Thiering, E., Wilson, R., Gladish, N., Waldenberger, M., Zhang, H.-M., Celedón, J., Burchard, E., et al. (2021) · Allergy. European Journal of Allergy and Clinical Immunology · doi:10.1111/all.15315 · Cited by 17
Lu, A. K.-M., Lin, J., Tseng, H., Wang, X., Jang, F.-L., Chen, P.-S., Huang, C. J., Hsieh, S., & Lin, S.-H. (2022) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2022.11.008 · Cited by 20
Cortical cellular diversity and development in schizophrenia
Price, A. J., Jaffe, A. E., & Weinberger, D. R. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0775-8 · Cited by 23
Cataloging Recent Advances in Epigenetic Alterations in Major Mental Disorders and Autism
Abdolmaleky, H. M., Zhou, J., & Thiagalingam, S. (2021) · Epigenomics · doi:10.2217/epi-2021-0074 · Cited by 20
Kalyakulina, A., Yusipov, I., Bacalini, M. G., Franceschi, C., Vedunova, M. V., & Ivanchenko, M. (2022) · GigaScience · doi:10.1093/gigascience/giac097 · Cited by 19
Doherty, T., Dempster, E. L., Hannon, E. J., Mill, J. S., Poulton, R., Corcoran, D. L., Sugden, K., Williams, B., Caspi, A., Moffitt, T. E., et al. (2023) · BMC Bioinformatics · doi:10.1186/s12859-023-05282-4 · Cited by 19
Self-citationOri, A. P. S., Loohuis, L. M. O., Guintivano, J., Hannon, E. J., Dempster, E. L., Clair, D. S., Bass, N. J., McQuillin, A., Mill, J. S., Sullivan, P. F., et al. (2024) · Clinical Epigenetics · doi:10.1186/s13148-024-01660-8 · Cited by 26
Self-citationMa, Y., Li, J., Xu, Y., Wang, Y., Yao, Y., Liu, Q., Wang, M., Zhao, X., Fan, R., Chen, J., et al. (2020) · Aging · doi:10.18632/aging.102735 · Cited by 17
Altered hypothalamic DNA methylation and stress-induced hyperactivity following early life stress
Fitzgerald, E., Sinton, M. C., Wernig-Zorc, S., Morton, N. M., Holmes, M. C., Boardman, J. P., & Drake, A. J. (2021) · Epigenetics & Chromatin · doi:10.1186/s13072-021-00405-8 · Cited by 19
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. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114789 · Cited by 19
Sportelli, L., Eisenberg, D. P., Passiatore, R., D’Ambrosio, E., Antonucci, L. A., Bettina, J. S., Chen, Q., Goldman, A. L., Gregory, M. D., Griffiths, K., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47456-5 · Cited by 19
Schizophrenia is associated with altered DNA methylation variance
Kiltschewskij, D. J., Reay, W. R., & Cairns, M. J. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02749-5 · Cited by 19
DNA-methylation of the dopamin receptor 2 gene is altered during alcohol withdrawal
Hillemacher, T., Rhein, M., Burkert, A., Heberlein, A., Wilhelm, J., Glahn, A., Muschler, M. A. N., Kahl, K. G., Kornhuber, J., Bleich, S., et al. (2019) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2019.09.002 · Cited by 18
Lapato, D. M., Roberson‐Nay, R., Kirkpatrick, R. M., Webb, B. T., York, T. P., & Kinser, P. A. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0769-z · Cited by 21
Gedik, H., Nguyen, T. H., Peterson, R. E., Chatzinakos, C., Riley, B. P., Vladimirov, V. I., & Bacanu, S. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1191264 · Cited by 16
Yu, H., Cheng, W., Zhang, X., Wang, X., & Yue, W. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0605-3 · Cited by 18
Genome-Wide Analysis of DNA Methylation in 106 Schizophrenia Family Trios in Han Chinese
Shen, L., Lv, X., Huang, H., Li, M., Huai, C., Wu, X., Wu, H., Ma, J., Chen, L., Wang, T., et al. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103609 · Cited by 18
Yoshino, Y., Ozaki, Y., Yamazaki, K., Sao, T., Mori, Y., Ochi, S., Iga, J., & Ueno, S. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00275 · Cited by 16
Traversing the epigenetic landscape: DNA methylation from retina to brain in development and disease
Xu, C., Fu, X., Qin, H., & Yao, K. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1499719 · Cited by 17
Marttila, S., Tamminen, H., Rajić, S., Mishra, P. P., Lehtimäki, T. J., Raitakari, O. T., Kähönen, M. A. P., Kananen, L., Jylhävä, J., Hägg, S., et al. (2022) · Epigenomics · doi:10.2217/epi-2022-0228 · Cited by 16
Endophenotypes, Epigenetics, Polygenicity and More: Irv Gottesman’s Dynamic Legacy
BRAFF, D. L., & Tamminga, C. A. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbw157 · Cited by 17
The schizophrenia and bipolar twin study in Sweden (STAR)
Johansson, V., Hultman, C. M., Kizling, I., Martinsson, L., Borg, J., Hedman, A. M., & Cannon, T. D. (2018) · Schizophrenia Research · doi:10.1016/j.schres.2018.08.001 · Cited by 17
Self-citationKundu, K., Mann, A., Tardáguila, M., Watt, S. B., Ponstingl, H., Vasquez, L. J., Morrell, N. W., Stegle, O., Pastinen, T., Sawcer, S. J., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.15.907436 · Cited by 17
Applicability of epigenetic age models to next-generation methylation arrays
Garma, L. D., & Quintela-Fandiño, M. (2024) · Genome Medicine · doi:10.1186/s13073-024-01387-4 · Cited by 16
Derivation of poly-methylomic profile scores for schizophrenia
Watkeys, O. J., Cohen‐Woods, S., Quidé, Y., Cairns, M. J., Overs, B. J., Fullerton, J. M., & Green, M. J. (2020) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.109925 · Cited by 16
Chiba, H., Kakuta, Y., Kinouchi, Y., Kawai, Y., Watanabe, K., Nagao, M., Naito, T., Onodera, M., Moroi, R., Kuroha, M., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0194036 · Cited by 19
Алфимова, М. В., Kondratyev, N. V., Golov, A. K., & Голимбет, В. Е. (2018) · Molecular Biology · doi:10.1134/s0026893318050023 · Cited by 16
Altered DNA methylation associated with a translocation linked to major mental illness
McCartney, D. L., Walker, R. M., Morris, S. W., Anderson, S. M., Duff, B. J., Marioni, R. E., Millar, J. K., McCarthy, S., Ryan, N., Lawrie, S. M., et al. (2018) · Schizophrenia · doi:10.1038/s41537-018-0047-7 · Cited by 16
Beyond the maternal epigenetic legacy
Champagne, F. A. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0157-6 · Cited by 16
van Gastel, J., Hendrickx, J. O., Leysen, H., Martin, B., Veenker, L., Beuning, S., Coppens, V., Morrens, M., & Maudsley, S. R. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9554-7_39 · Cited by 16
Sun, Y., Liao, Y., Zhang, Y., Lü, Z., Ma, Y., Kang, Z., Feng, X., Zhao, G., Sun, J., Zhu, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-57066-4 · Cited by 17
Dall’Aglio, L., Rijlaarsdam, J., Mulder, R. H., Neumann, A., Felix, J. F., Kok, R., Bakermans‐Kranenburg, M. J., van IJzendoorn, M. H., Tiemeier, H. W., & Cecil, C. A. M. (2020) · Psychological Medicine · doi:10.1017/s0033291720004353 · Cited by 18
Liu, Y., Qu, H., Chang, X., Tian, L., Glessner, J., Abou‐Sleiman, P. M., & Hakonarson, H. H. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.797329 · Cited by 16
Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits
Freytag, V., Vukojević, V., Wagner-Thelen, H., Milnik, A., Vogler, C., Leber, M., Weinhold, L., Böhmer, A. C., Riedel-Heller, S. G., Maier, W., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-017-0070-x · Cited by 14
Schizophrenia: a classic battle ground of nature versus nurture debate
Clair, D. S., & Lang, B. (2021) · 中国科学通报：英文版 · doi:10.1016/j.scib.2021.01.032 · Cited by 20
Methylome analysis of ALS patients and presymptomatic mutation carriers in blood cells
Ruf, W. P., Hannon, E. J., Freischmidt, A., Grozdanov, V., Brenner, D., Müller, K., Knehr, A., Günther, K., Dorst, J., Ammerpohl, O., et al. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2022.04.003 · Cited by 14
Self-citationEpigenetic research of cognitive deficit in schizophrenia: some methodological considerations
Лежейко, Т. В., & Алфимова, М. В. (2017) · S S Korsakov Journal of Neurology and Psychiatry · doi:10.17116/jnevro201711710176-80 · Cited by 14
Paul, K. C., Kusters, C., Furlong, M., Zhang, K., Yu, Y., Folle, A. D., Rosario, I. D., Keener, A. M., Bronstein, J. M., Sinsheimer, J. S., et al. (2022) · Brain Behavior & Immunity - Health · doi:10.1016/j.bbih.2022.100530 · Cited by 14
Rijlaarsdam, J., Cosín‐Tomás, M., Schellhas, L., Abrishamcar, S., Malmberg, A., Neumann, A., Felix, J. F., Sunyer, J., Gützkow, K. B., Gražulevičienė, R., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01871-6 · Cited by 16
Negative Evidence for a Functional Role of Neuronal DNMT3a in Persistent Pain
Saunders, J., Hore, Z. L., Gentry, C., McMahon, S. B., & Denk, F. (2018) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2018.00332 · Cited by 13
Integrative Genomic–Epigenomic Analysis of Clozapine-Treated Patients with Refractory Psychosis
Mayén-Lobo, Y. G., Martínez‐Magaña, J. J., Pérez-Aldana, B. E., Ortega‐Vázquez, A., Mendoza, A. D. G., de Montellano, D. J. D., Soto‐Reyes, E., Nicolini, H., López, M., & Monroy‐Jaramillo, N. (2021) · Pharmaceuticals · doi:10.3390/ph14020118 · Cited by 14
Ohi, K., Shimada, M., Soda, M., Nishizawa, D., Fujikane, D., Takai, K., Kuramitsu, A., Muto, Y., Sugiyama, S., Hasegawa, J., et al. (2024) · BMJ Mental Health · doi:10.1136/bmjment-2023-300936 · Cited by 16
Epigenetic clocks and inflammaging: pitfalls caused by ignoring cell-type heterogeneity
Guo, X., & Teschendorff, A. E. (2025) · GeroScience · doi:10.1007/s11357-025-01677-8 · Cited by 12
Kondratyev, N. V., Golov, A. K., Алфимова, М. В., Лежейко, Т. В., & Голимбет, В. Е. (2018) · Clinical Epigenetics · doi:10.1186/s13148-018-0565-1 · Cited by 13
Hidden hypotheses in ‘hypothesis-free’ genome-wide epigenetic associations
Barker, E. D., Roberts, S., & Walton, E. (2018) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2018.07.009 · Cited by 14
Li, Y., Wang, K., Zhang, P., Huang, J., An, H., Wang, N., Yang, F. D., Wang, Z., Tan, S., Chen, S., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-35718-4 · Cited by 14
Network modules linking expression and methylation in prefrontal cortex of schizophrenia
Lin, D., Chen, J., Duan, K., Perrone‐Bizzozero, N. I., Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Calhoun, V. D., & Liu, J. (2020) · Epigenetics · doi:10.1080/15592294.2020.1827718 · Cited by 13
Алфимова, М. В., Кондратьев, Н. В., Golov, A. K., & Голимбет, В. Е. (2018) · Molecular Biology · doi:10.1134/s0026898418050026 · Cited by 13
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
Buck, J. M., Yu, L., Knopik, V. S., & Stitzel, J. A. (2021) · Biology of Reproduction · doi:10.1093/biolre/ioab138 · Cited by 11
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
Aslibekyan, S. W., Almasy, L. A., Province, M. A., Absher, D., & Arnett, D. K. (2018) · BMC Proceedings · doi:10.1186/s12919-018-0114-0 · Cited by 11
Study investigating executive function in schizophrenia patients and their unaffected siblings
Xu, F., & Xian, Z. (2023) · PLoS ONE · doi:10.1371/journal.pone.0285034 · Cited by 10
Cabrera‐Mendoza, B., Martínez‐Magaña, J. J., Mendoza, A. D. G., Sarmiento, E., Ruíz-Ramos, D., Tovilla‐Zárate, C. A., González‐Castro, T. B., Juárez‐Rojop, I. E., la Cruz, D. D. G.-D., López‐Armenta, M., et al. (2020) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2020.01.008 · Cited by 11
Complete deconvolution of DNA methylation signals from complex tissues: a geometric approach
Zhang, W., Wu, H., & Li, Z. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa930 · Cited by 11
Lokmer, A., Goud, A. C., Troudet, R., Bacq‐Daian, D., Boland, A., Latapie, V., Deleuze, J., Rajkumar, R. P., Shewade, D. G., Bélivier, F., et al. (2023) · Epigenomics · doi:10.2217/epi-2023-0017 · Cited by 10
Villar, J. D., Stavrum, A.-K., Spíndola, L., Torsvik, A., Bjella, T. D., Steen, N. E., Djurovic, S., Andreassen, O. A., Steen, V. M., & Hellard, S. L. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02507-1 · Cited by 11
Ariff, A., Melton, P. E., Brennecke, S. P., & Moses, E. K. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00227 · Cited by 12
Thompson, M. J., Chen, Z. J., Rahmani, E., & Halperin, E. (2019) · Genome biology · doi:10.1186/s13059-019-1743-y · Cited by 11
Finding associations in a heterogeneous setting: statistical test for aberration enrichment
Mezlini, A. M., Das, S., & Goldenberg, A. (2021) · Genome Medicine · doi:10.1186/s13073-021-00864-4 · Cited by 10
Gassó, P., Rodríguez, N., Martínez-Pinteño, A., Mezquida, G., Ribeiro, M., González‐Peñas, J., Zorrilla, E. P., Martínez-Sadurní, L., Rodríguez–Jiménez, R., Corripio, I., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01645-8 · Cited by 11
Genetic and epigenetic analysis of schizophrenia in blood—a no-brainer?
Jaffe, A. E., & Kleinman, J. E. (2016) · Genome Medicine · doi:10.1186/s13073-016-0354-4 · Cited by 10
Genome-wide search identified DNA methylation sites that regulate the metabolome
Nikpay, M. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1093882 · Cited by 9
Bartolomeo, 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
van den Oord, E. J. C. G., Xie, L. Y., Zhao, M., Campbell, T. L., Turecki, G., Kähler, A. K., Dean, B., Mors, O. N., Hultman, C. M., Staunstrup, N. H., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02080-5 · Cited by 9
Self-citation
Metadata
- Authors
- Hannon, E., Dempster, E., Viana, J., Burrage, J., Smith, A. R., Macdonald, R., St Clair, D., Mustard, C., Breen, G., Therman, S., Kaprio, J., Toulopoulou, T., Pol, H. E. H., Bohlken, M. M., Kahn, R. S., Nenadic, I., Hultman, C. M., Murray, R. M., Collier, D. A., Bass, N., Gurling, H., McQuillin, A., Schalkwyk, L., & Mill, J.
- Affiliations
- University of Exeter (GB)
- University of the Highlands and Islands (GB)
- King's College London (GB)
- Finnish Institute for Health and Welfare (FI)
- University of Helsinki (FI)
- University of Hong Kong (HK)
- University Medical Center Utrecht (NL)
- Karolinska Institutet (SE)
- University College London (GB)
- University of Essex (GB)
- Corresponding author
- Mill, Jonathan
- ORCID
- Venue
- Genome Biology
- Published
- 2016-08-30
- Volume
- 17
- Issue
- 1
- Pages
- 176-176
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC5004279
- OpenAlex
- W2510420694
- Cited by
- 349
- References
- 66
- Citations by year
- 2026: 8 · 2025: 29 · 2024: 39 · 2023: 32 · 2022: 40 · 2021: 54 · 2020: 39 · 2019: 37 · 2018: 45 · 2017: 21 · 2016: 3
- FWCI
- 18.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Open Access at Essex (University of Essex) (acceptedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Aberdeen University Research Archive (Aberdeen University) (submittedVersion)
- Työväentutkimus Vuosikirja (submittedVersion, other-oa)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Funders
- Medical Research Council (MR/K013807/1)
- National Institutes of Health (R01 AG036039, R01 MH52857)
- Suomen Akatemia (213506, 129680, 265240, 263278)
- Karolinska Institutet (ALF 20090183, ALF 20100305)
- 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, epigenome-wide association study, differentially methylated regions, DNA methylation quantitative trait loci, polygenic risk score, genetic risk variants, gene expression regulation
- MeSH terms
- Bayes Theorem, Humans, Phenotype, Schizophrenia, Twins, Monozygotic, CpG Islands, DNA Methylation, Multifactorial Inheritance, Quantitative Trait Loci, Genome-Wide Association Study, Epigenomics
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
