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
Schizophrenia risk from complex variation of complement component 4
Sekar, A., Bialas, A. R., de Rivera, H., Davis, A., Hammond, T. R., Kamitaki, N., Tooley, K., Presumey, J., Baum, M., Van Doren, V., et al. (2016) · Nature · doi:10.1038/nature16549 · Cited by 2,394
Genome-wide association study identifies five new schizophrenia loci
The Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (2011) · Nature Genetics · doi:10.1038/ng.940 · Cited by 1,919
Self-citationConserved role of intragenic DNA methylation in regulating alternative promoters
Maunakea, A. K., Nagarajan, R. P., Bilenky, M., Ballinger, T. J., D’Souza, C., Fouse, S. D., Johnson, B. E., Hong, C., Nielsen, C., Zhao, Y., et al. (2010) · Nature · doi:10.1038/nature09165 · Cited by 1,743
Fast and accurate genotype imputation in genome-wide association studies through pre-phasing
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R. (2012) · Nature Genetics · doi:10.1038/ng.2354 · Cited by 1,737
Matrix eQTL: ultra fast eQTL analysis via large matrix operations
Shabalin, A. A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts163 · Cited by 1,694
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
Genome-wide association analysis identifies 13 new risk loci for schizophrenia
Multicenter Genetic Studies of Schizophrenia Consortium, Ripke, S., Psychosis Endophenotypes International Consortium, Wellcome Trust Case Control Consortium 2, O'Dushlaine, C., Chambert, K., Moran, J. L., Kähler, A. K., Akterin, S., Bergen, S. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2742 · Cited by 1,496
Self-citationRare chromosomal deletions and duplications increase risk of schizophrenia
The International Schizophrenia Consortium (2008) · Nature · doi:10.1038/nature07239 · Cited by 1,475
Epigenome-wide association studies for common human diseases
Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3000 · Cited by 1,288
de Leon, J., & Diaz, F. J. (2005) · Schizophrenia Research · doi:10.1016/j.schres.2005.02.010 · Cited by 1,276
Panel Data Econometrics in R : The plm Package
Croissant, Y., & Millo, G. (2008) · Journal of Statistical Software · doi:10.18637/jss.v027.i02 · Cited by 1,243
Common variants on chromosome 6p22.1 are associated with schizophrenia
Shi, J., Levinson, D. F., Duan, J., Sanders, A. R., Zheng, Y., Pe’er, I., Dudbridge, F., Holmans, P., Whittemore, A. S., Mowry, B. J., et al. (2009) · Nature · doi:10.1038/nature08192 · Cited by 1,179
A data-driven approach to preprocessing Illumina 450K methylation array data
Pidsley, R., Y Wong, C. C., Volta, M., Lunnon, K., Mill, J., & Schalkwyk, L. C. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-293 · Cited by 1,143 · cited 2×
“Normalization of the DNA methylation data was performed used the dasen() function in the wateRmelon package [52].”
Self-citationIntegrated detection and population-genetic analysis of SNPs and copy number variation
McCarroll, S. A., Kuruvilla, F. G., Korn, J. M., Cawley, S., Nemesh, J., Wysoker, A., Shapero, M. H., de Bakker, P. I. W., Maller, J. B., Kirby, A., et al. (2008) · Nature Genetics · doi:10.1038/ng.238 · Cited by 936
Tobacco smoking leads to extensive genome-wide changes in DNA methylation
Zeilinger, S., Kühnel, B., Klopp, N., Baurecht, H., Kleinschmidt, A., Gieger, C., Weidinger, S., Lattka, E., Adamski, J., Peters, A., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063812 · Cited by 824
Korn, J. M., Kuruvilla, F. G., McCarroll, S. A., Wysoker, A., Nemesh, J., Cawley, S., Hubbell, E., Veitch, J., Collins, P. J., Darvishi, K., et al. (2008) · Nature Genetics · doi:10.1038/ng.237 · Cited by 783
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
Self-citationLinking disease associations with regulatory information in the human genomePreprint
Schaub, M. A., Boyle, A. P., Kundaje, A. B., Batzoglou, S., & Snyder, M. P. (2012) · Genome Research · doi:10.1101/gr.136127.111 · Cited by 723
Schedule for Affective Disorders and Schizophrenia
Endicott, J., & Spitzer, R. (2014) · PsycTESTS Dataset · doi:10.1037/t07870-000 · Cited by 678
minimac2: faster genotype imputation
Fuchsberger, C., Abecasis, G. R., & Hinds, D. A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu704 · Cited by 636
Analysing and interpreting DNA methylation data
Bock, C. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3273 · Cited by 600
From neuropathology to neurodevelopment
Weinberger, D. R. (1995) · The Lancet · doi:10.1016/s0140-6736(95)91386-6 · Cited by 558
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
Price, E. M., Cotton, A. M., Lam, L. L. C., Farré, P., Emberly, E. G., Brown, C. J., Robinson, W. P., & Kobor, M. S. (2013) · Epigenetics & Chromatin · doi:10.1186/1756-8935-6-4 · Cited by 494
Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P -values
Pedersen, B. S., Schwartz, D. A., Yang, I. V., & Kechris, K. J. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts545 · Cited by 485
400: A Method for Combining Non-Independent, One-Sided Tests of Significance
Brown, M. B. (1975) · Biometrics · doi:10.2307/2529826 · Cited by 473
Dempster, E. L., Pidsley, R., Schalkwyk, L. C., Owens, S., Georgiades, A., Kane, F., Kalidindi, S., Picchioni, M., Kravariti, E., Toulopoulou, T., et al. (2011) · Human Molecular Genetics · doi:10.1093/hmg/ddr416 · Cited by 460
Self-citationMatrix eQTL: Ultra fast eQTL analysis via large matrix operationsPreprint
Shabalin, A. A. (2011) · arXiv (Cornell University) · doi:10.17615/g28n-r219 · Cited by 452
Wagner, J. R., Busche, S., Ge, B., Kwan, T., Pastinen, T., & Blanchette, M. (2014) · Genome biology · doi:10.1186/gb-2014-15-2-r37 · Cited by 446
From promises to practical strategies in epigenetic epidemiology
Mill, J. S., & Heijmans, B. T. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3405 · Cited by 356
Self-citationMethylation QTLs in the developing brain and their enrichment in schizophrenia risk loci
Hannon, E. J., Spiers, H., Viana, J. F., Pidsley, R., Burrage, J., Murphy, T. M., Troakes, C., Turecki, G., O’Donovan, M. C., Schalkwyk, L. C., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4182 · Cited by 350
Self-citationMcClave, A. K., McKnight-Eily, L. R., Davis, S. P., & Dube, S. R. (2010) · American Journal of Public Health · doi:10.2105/ajph.2009.188136 · Cited by 339
Tsaprouni, L. G., Yang, T.-P., Bell, J., Dick, K. J., Kanoni, S., Nisbet, J., Viñuela, A., Grundberg, E., Nelson, C. P., Meduri, E., et al. (2014) · Epigenetics · doi:10.4161/15592294.2014.969637 · Cited by 319
Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients
Wockner, L. F., Noble, E. P., Lawford, B. R., Young, R. M., Morris, C. P., Whitehall, V., & Voisey, J. (2014) · Translational Psychiatry · doi:10.1038/tp.2013.111 · Cited by 315
Differences in smoking associated DNA methylation patterns in south asians and europeans
Elliott, H. R., Tillin, T., McArdle, W. L., Ho, K., Duggirala, A., Frayling, T. M., Davey Smith, G., Hughes, A. D., Chaturvedi, N., & Relton, C. L. (2014) · Clinical Epigenetics · doi:10.1186/1868-7083-6-4 · Cited by 282
Association Between Prenatal Exposure to Bacterial Infection and Risk of Schizophrenia
Sørensen, H. J., Mortensen, E. L., Reinisch, J. M., & Mednick, S. A. (2008) · Schizophrenia Bulletin · doi:10.1093/schbul/sbn121 · Cited by 261
Relton, C. L., & Davey Smith, G. (2010) · PLoS Medicine · doi:10.1371/journal.pmed.1000356 · Cited by 254
Koestler, D. C., Christensen, B. C., Karagas, M. R., Marsit, C. J., Langevin, S. M., Kelsey, K. T., Wiencke, J. K., & Houseman, E. A. (2013) · Epigenetics · doi:10.4161/epi.25430 · Cited by 251
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
Self-citationSlieker, R. C., Bos, S. D., Goeman, J. J., Bovée, J. V. M. G., Talens, R. P., van der Breggen, R., Suchiman, H. E. D., Lameijer, E.-W., Putter, H., van den Akker, E. B., et al. (2013) · Epigenetics & Chromatin · doi:10.1186/1756-8935-6-26 · Cited by 234
Arion, D., Corradi, J. P., Tang, S., Datta, D., Boothe, F., He, A., Cacace, A. M., Zaczek, R., Albright, C. F., Tseng, G., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.171 · Cited by 177
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
Self-citationUsing high-density DNA methylation arrays to profile copy number alterations
Feber, A., Guilhamon, P., Lechner, M., Fenton, T. R., Wilson, G. A., Thirlwell, C., Morris, T. J., Flanagan, A. M., Teschendorff, A. E., Kelly, J. D., et al. (2014) · Genome biology · doi:10.1186/gb-2014-15-2-r30 · Cited by 150
de Leon, J., Becona, E., Gurpegui, M., Gonzalez-Pinto, A., & Diaz, F. J. (2002) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v63n0911 · Cited by 144 · cited 3×
“Across the full sample, DNA methylation-derived smoking scores were significantly higher in patients with schizophrenia compared to controls (Mann – Whitney P = 1.51 × 10 − 41 ; Additional file 1: Figure S3), consistent with epidemiological data [25 – 27] and the results of our initial EWAS.”
InfluentialGuo, H., Fortune, M. D., Burren, O. S., Schofield, E. C., Todd, J. A., & Wallace, C. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv077 · Cited by 139
(2015) · Cited by 104
Genome-wide expression profiling of schizophrenia using a large combined cohort
Mistry, M., Gillis, J. A., & Pavlidis, P. (2012) · Molecular Psychiatry · doi:10.1038/mp.2011.172 · Cited by 92
A System-Level Transcriptomic Analysis of Schizophrenia Using Postmortem Brain Tissue Samples
Roussos, P., Katsel, P., Davis, K. L., Siever, L. J., & Haroutunian, V. (2012) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2012.704 · Cited by 92
Epigenetics in health and disease: heralding the EWAS era
Murphy, T. M., & Mill, J. S. (2014) · The Lancet · doi:10.1016/s0140-6736(14)60269-5 · Cited by 84
Self-citationNielsen, P. R., Laursen, T. M., & Mortensen, P. B. (2011) · Schizophrenia Bulletin · doi:10.1093/schbul/sbr149 · Cited by 74
Datta, S. R., McQuillin, A., Rizig, M., Blaveri, E., Thirumalai, S., Kalsi, G., Lawrence, J., Bass, N. J., Puri, V., Choudhury, K., et al. (2008) · Molecular Psychiatry · doi:10.1038/mp.2008.128 · Cited by 66
Self-citationvan Eijk, K. R., de Jong, S., Strengman, E., Buizer‐Voskamp, J. E., Kahn, R. S., Boks, M. P., Horvath, S., & Ophoff, R. A. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.245 · Cited by 64
Self-citationfcGENE: A Versatile Tool for Processing and Transforming SNP Datasets
Roshyara, N. R., & Scholz, M. R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097589 · Cited by 50
Aberrant DNA Methylation of Blood in Schizophrenia by Adjusting for Estimated Cellular Proportions
Kinoshita, M., Numata, S., Tajima, A., Ohi, K., Hashimoto, R., Shimodera, S., Imoto, I., Takeda, M., & Ohmori, T. (2014) · NeuroMolecular Medicine · doi:10.1007/s12017-014-8319-5 · Cited by 42
Refinement of schizophrenia GWAS loci using methylome-wide association data
Kumar, G., Clark, S. L., McClay, J. L., Shabalin, A. A., Adkins, D. E., Xie, L., Chan, R. F., Nerella, S., Kim, Y., Sullivan, P. F., et al. (2014) · Human Genetics · doi:10.1007/s00439-014-1494-5 · Cited by 17
Self-citation
Cited by
Sorted by citations
The Key Role of Epigenetics in Human Disease Prevention and Mitigation
Feinberg, A. P. (2018) · New England Journal of Medicine · doi:10.1056/nejmra1402513 · Cited by 638
van Rheenen, W., van der Spek, R. A. A., Bakker, M. K., van Vugt, J. J. F. A., Hop, P. J., Zwamborn, R. A. J., de Klein, N., Westra, H.-J., Bakker, O. B., Deelen, P., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00973-1 · Cited by 542
Self-citationFairchild, G. F., Hawes, D. J., Frick, P. J., Copeland, W., Odgers, C. L., Franke, B., Freitag, C. M., & Brito, S. A. D. (2019) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0095-y · Cited by 471
Guidance for DNA methylation studies: statistical insights from the Illumina EPIC array
Mansell, G., Gorrie-Stone, T. J., Bao, Y., Kumari, M., Schalkwyk, L. S., Mill, J., & Hannon, E. (2019) · BMC Genomics · doi:10.1186/s12864-019-5761-7 · Cited by 340
Self-citationA Bayesian framework for multiple trait colocalization from summary association statistics
Giambartolomei, C., Liu, J. Z., Zhang, W., Hauberg, M. E., Shi, H., Boocock, J., Pickrell, J., Jaffe, A. E., Paşaniuc, B., & Roussos, P. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty147 · Cited by 299
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
