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Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci
Open accessAbstract
We used a collection of 708 prospectively collected autopsied brains to assess the methylation state of the brain's DNA in relation to Alzheimer's disease (AD). We found that the level of methylation at 71 of the 415,848 interrogated CpGs was significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validated 11 of the differentially methylated regions in an independent set of 117 subjects. Furthermore, we functionally validated these CpG associations and identified the nearby genes whose RNA expression was altered in AD: ANK1, CDH23, DIP2A, RHBDF2, RPL13, SERPINF1 and SERPINF2. Our analyses suggest that these DNA methylation changes may have a role in the onset of AD given that we observed them in presymptomatic subjects and that six of the validated genes connect to a known AD susceptibility gene network.
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“Alterations of DNA methylation levels have been shown to be involved in many diseases, including AD [19–24].”
From Distinct sex-specific DNA methylation differences in Alzheimer’s disease (2022) · cites this paper as [19]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“DNA methylation is an important epigenetic modification that regulates gene transcription and is known to be involved in AD”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [18]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Consistent with previous studies [18, 19, 86, 87], we observed the majority of these sex-specific differences were hyper-methylated in samples with AD neuropathology, for which methylation levels increased as the AD Braak stage increased”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [18]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
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“dysregulated DNAm has been observed as an early feature of AD neuropathology in the brain [19]”
From Distinct sex-specific DNA methylation differences in Alzheimer’s disease (2022) · cites this paper as [19]
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“Importantly, alterations of DNA methylation levels have also been implicated in multiple neurological disorders including AD [18–22]”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [18]
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“Notably, none of the 14 CpGs detected in our interaction analysis was identified in previous large-scale DNA methylation studies [18–22]”
From Sex-specific DNA methylation differences in Alzheimer’s disease pathology (2021) · cites this paper as [18]
In the citing paper
“These reference epigenomes, combined with other genomics data, have provided functional and causal insights about several human disease (De Jager et al., 2014; Farh et al., 2015; Yao, Tak, Berman, & Farnham, 2014).”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as De Jager et al., 2014
In the citing paper
“The most significant GWAS SNP was also a significant eQTL with the same direction of effect as in CMC for FURIN (rs4702: P = 1 × 10−6), CLCN3 (rs10520163: P = 9 × 10−6), and SNAP91 (rs3798869: P = 3 × 10−4); TSNARE1 (rs4129585: P = 0.057) and CNTN4 (rs17194490: P = 0.07) also had alleles in the same direction of effect as in CMC but did not reach significance.”
From Gene expression elucidates functional impact of polygenic risk for schizophrenia (2016) · cites this paper as [26]
In the citing paper
“and two independent genome-wide studies recently identified a differentially methylated region in the ANK1 gene as associated with the burden of AD pathology [198, 199].”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [199]
In the citing paper
“A different study found altered methylation in the BIN1 locus at cg22883290 in relation to neuritic amyloid plaques and a pathologic diagnosis of AD, and this altered methylation pattern was independent of the effect of the rs744373 susceptibility variant [14].”
From BIN1 protein isoforms are differentially expressed in astrocytes, neurons, and microglia: neuronal and astrocyte BIN1 are implicated in tau pathology (2020) · cites this paper as [14]
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Citations
Cites
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155
Self-citationMeta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Self-citationHarold, D., Abraham, R., Hollingworth, P., Sims, R., Gerrish, A., Hamshere, M. L., Pahwa, J. S., Moskvina, V., Dowzell, K., Williams, A., et al. (2009) · Nature Genetics · doi:10.1038/ng.440 · Cited by 3,326
Self-citationChromHMM: automating chromatin-state discovery and characterization
Ernst, J., & Kellis, M. (2012) · Nature Methods · doi:10.1038/nmeth.1906 · Cited by 2,457
Self-citationGenome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease
the European Alzheimer's Disease Initiative Investigators, Lambert, J.-C., Heath, S., Even, G., Campion, D., Sleegers, K., Hiltunen, M., Combarros, O., Zelenika, D., Bullido, M. J., et al. (2009) · Nature Genetics · doi:10.1038/ng.439 · Cited by 2,234
Du, P., Zhang, X., Huang, C.-C., Jafari, N., Kibbe, W. A., Hou, L., & Lin, S. M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-587 · Cited by 2,136 · cited 2×
“We then performed a refinement step similar to that used in “ iSVA” 52 where for each independent component i ( 1 = i =k ) we created a sub-matrix of the beta values populated only by methylation probes that were significantly associated with component i .”
lumi : a pipeline for processing Illumina microarray
Du, P., Kibbe, W. A., & Lin, S. M. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn224 · Cited by 2,028
Initiative, T. A. D. N., Hollingworth, P., CHARGE consortium, EADI1 consortium, Harold, D., Sims, R., Gerrish, A., Lambert, J.-C., Carrasquillo, M. M., Abraham, R., et al. (2011) · Nature Genetics · doi:10.1038/ng.803 · Cited by 1,997
Naj, A. C., Jun, G., Beecham, G. W., Wang, L.-S., Vardarajan, B. N., Buros, J., Gallins, P. J., Buxbaum, J. D., Jarvik, G. P., Crane, P. K., et al. (2011) · Nature Genetics · doi:10.1038/ng.801 · Cited by 1,901 · cited 1×
“…in the BIN1 locus (beta=4.44, p=9.00×10 −8 ) and cg02308560 in the ABCA7 locus (beta=3.62, p=2.45×10 −12 ) 19-22 . cg22883290, is located 5 kb from the 5’ end of the BIN1 gene and 92 kb from the index SNP, rs744373, that best captures the genetic association to AD in this region ( Figure 2c ) 19 .”
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Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
Self-citationAging and aging-related diseases: from molecular mechanisms to interventions and treatments
Guo, J., Huang, X., Dou, L., Yan, M., Shen, T., Tang, W., & Li, J. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01251-0 · Cited by 1,976
Editing DNA Methylation in the Mammalian Genome
Liu, X. S., Wu, H., Ji, X., Stelzer, Y., Wu, X., Czauderna, S., Shu, J., Dadon, D., Young, R. A., & Jaenisch, R. (2016) · Cell · doi:10.1016/j.cell.2016.08.056 · Cited by 1,224
“Importantly, these maps have allowed for the identification of differentially methylated regions (DMRs) at base pair resolution during different stages of normal development as well as disease (De Jager et al., 2014; Landau et al., 2014).”
Religious Orders Study and Rush Memory and Aging Project
Bennett, D. A., Buchman, A. S., Boyle, P. A., Barnes, L. L., Wilson, R. S., & Schneider, J. A. (2018) · Journal of Alzheimer's Disease · doi:10.3233/jad-179939 · Cited by 1,260
Self-citationAgeing, neurodegeneration and brain rejuvenation
Wyss-Coray, T. (2016) · Nature · doi:10.1038/nature20411 · Cited by 1,147
ARUK Consortium, Sims, R., GERAD/PERADES, C., van der Lee, S. J., Naj, A. C., Bellenguez, C., Badarinarayan, N., Jakobsdottir, J., Kunkle, B. W., Boland, A., et al. (2017) · Nature Genetics · doi:10.1038/ng.3916 · Cited by 1,012
Self-citationGene expression elucidates functional impact of polygenic risk for schizophrenia
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., Ruderfer, D. M., Oh, E. C., Topol, A., Shah, H. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4399 · Cited by 1,091
“First, we replicated these eQTL in the Religious Orders 258 Study and Memory and Aging Project (ROS/MAP) (38), with unpublished human DLPFC RNA 259 sequencing data (n=461).”
MethodSelf-citationMolecular and cellular mechanisms underlying the pathogenesis of Alzheimer’s disease
Guo, T., Zhang, D., Zeng, Y., Huang, T. Y., Xu, H., & Zhao, Y. (2020) · Molecular Neurodegeneration · doi:10.1186/s13024-020-00391-7 · Cited by 994
Chromatin-state discovery and genome annotation with ChromHMM
Ernst, J., & Kellis, M. (2017) · Nature Protocols · doi:10.1038/nprot.2017.124 · Cited by 905
Self-citationBrain cell type–specific enhancer–promoter interactome maps and disease - risk association
Nott, A., Holtman, I. R., Coufal, N. G., Schlachetzki, J. C. M., Yu, M., Hu, R., Han, C. Z., Pena, M., Xiao, J., Wu, Y., et al. (2019) · Science · doi:10.1126/science.aay0793 · Cited by 699
An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease
Horvath, S., Gurven, M., Levine, M. E., Trumble, B. C., Kaplan, H. S., Allayee, H., Ritz, B. R., Chen, B. H., Lu, A. T.-H., Rickabaugh, T. M., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1030-0 · Cited by 749
“Additional details on the DNA methylation data can be found in [81].”
BackgroundA multi-omic atlas of the human frontal cortex for aging and Alzheimer’s disease research
De Jager, P. L., Ma, Y., McCabe, C., Xu, J., Vardarajan, B. N., Felsky, D., Klein, H.-U., White, C. C., Peters, M. A., Lodgson, B., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.142 · Cited by 598
Self-citationThe 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
Molecular genetics of early-onset Alzheimer’s disease revisited
Cacace, R., Sleegers, K., & Van Broeckhoven, C. (2016) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.01.012 · Cited by 617
“[136] De Jager PL, Srivastava G, Lunnon K, Burgess J, Schalkwyk LC, Yu L, et al.”
Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer's disease
Lunnon, K., Smith, R., Hannon, E., De Jager, P. L., Srivastava, G., Volta, M., Troakes, C., Al-Sarraj, S., Burrage, J., Macdonald, R., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3782 · Cited by 574
Self-citationThe road to restoring neural circuits for the treatment of Alzheimer's disease
Canter, R. G., Penney, J., & Tsai, L.-H. (2016) · Nature · doi:10.1038/nature20412 · Cited by 565
Jühling, F., Kretzmer, H., Bernhart, S. H., Otto, C., Stadler, P. F., & Hoffmann, S. (2015) · Genome Research · doi:10.1101/gr.196394.115 · Cited by 509
“Differences in DNA methylation levels have also been connected to many different diseases like diabetes (Nilsson et al. 2014) or Alzheimer’s disease (De Jager et al. 2014).”
BackgroundBrain Cell Type Specific Gene Expression and Co-expression Network Architectures
McKenzie, A. T., Wang, M., Hauberg, M. E., Fullard, J. F., Kozlenkov, A., Keenan, A., Hurd, Y. L., Dracheva, S., Casaccia, P., Roussos, P., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-27293-5 · Cited by 481
Ferroptosis and Its Role in Diverse Brain Diseases
Weiland, A., Wang, Y., Wu, W., Lan, X., Han, X., Li, Q., & Wang, J. (2018) · Molecular Neurobiology · doi:10.1007/s12035-018-1403-3 · Cited by 473
Sun, Y. V., & Hu, Y.-J. (2016) · Advances in Genetics · doi:10.1016/bs.adgen.2015.11.004 · Cited by 459
“These reference epigenomes, combined with other genomics data, have provided functional and causal insights about several human disease (De Jager et al., 2014; Farh et al., 2015; Yao, Tak, Berman, & Farnham, 2014).”
BackgroundHannon, E., Lunnon, K., Schalkwyk, L., & Mill, J. (2015) · Epigenetics · doi:10.1080/15592294.2015.1100786 · Cited by 455
“Platforms such as the Illumina Infinium HumanMethylation450 BeadChip (450K) have enabled the economical, high-throughput profiling of methylomic variation across large numbers of samples and epigenome-wide association studies (EWAS), which aim to identify DNA methylation differences associated with environmental expos…”
MethodSelf-citationLevine, M. E., Lu, A. T., Bennett, D. A., & Horvath, S. (2015) · Aging · doi:10.18632/aging.100864 · Cited by 455
“Additional details on the DNA methylation data can be found in [9].”
BackgroundSelf-citationAn xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome
Ng, B., White, C. C., Klein, H.-U., Sieberts, S. K., McCabe, C., Patrick, E., Xu, J., Yu, L., Gaiteri, C., Bennett, D. A., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4632 · Cited by 452
Self-citationZhu, X., Chen, Z., Shen, W., Huang, G., Sedivy, J. M., Wang, H., & Ju, Z. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00646-9 · Cited by 425
Epigenetic mechanisms in neurogenesis
Yao, B., Christian, K. M., He, C., Jin, P., Ming, G., & Song, H. (2016) · Nature reviews. Neuroscience · doi:10.1038/nrn.2016.70 · Cited by 406
The epigenetics of aging and neurodegeneration
Lardenoije, R., Iatrou, A., Kenis, G., Kompotis, K., Steinbusch, H. W. M., Mastroeni, D., Coleman, P., Lemere, C. A., Hof, P. R., van den Hove, D. L. A., et al. (2015) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2015.05.002 · Cited by 381
“More specifically, a differential cortex-specific hypermethylated region of ankyrin 1 (ANK1) was found to be associated with the early stages as well as the progression of AD neuropathology (De Jager et al., 2014; Lunnon et al., 2014).”
BackgroundNativio, R., Lan, Y., Donahue, G., Sidoli, S., Berson, A., Srinivasan, A. R., Shcherbakova, O., Amlie-Wolf, A., Nie, J., Cui, X., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0696-0 · Cited by 380
Biological aging processes underlying cognitive decline and neurodegenerative disease
Gonzales, M. M., Garbarino, V. R., Pollet, E., Palavicini, J. P., Kellogg, D. L., Kraig, E., & Orr, M. E. (2022) · Journal of Clinical Investigation · doi:10.1172/jci158453 · Cited by 426
“Genes implicated in AD, including those coding for APP, MAPT, BDNF, ABCA7, ANK1, BIB1, SORL1, and SIRT1, show differential methylation between individuals with AD and controls (116, 117).”
BackgroundGenetics of Parkinson's disease
Lill, C. M. (2016) · Molecular and Cellular Probes · doi:10.1016/j.mcp.2016.11.001 · Cited by 387
“not been implicated in AD by genetic association studies before (142,143).”
BackgroundThe emerging field of epigenetics in neurodegeneration and neuroprotection
Hwang, J.-Y., Aromolaran, K. A., & Zukin, R. S. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2017.46 · Cited by 353
Tau Activates Transposable Elements in Alzheimer’s Disease
Guo, C., Jeong, H.-H., Hsieh, Y.-C., Klein, H.-U., Bennett, D. A., De Jager, P. L., Liu, Z., & Shulman, J. M. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.05.004 · Cited by 315
“In both human brains and animal models, AD pathologic changes have been associated with epigenomic remodeling and transcriptional dysregulation (Frost et al., 2014; Gjoneska et al., 2015; De Jager et al., 2014).”
Self-citationDNA Methylation Biomarkers in Aging and Age-Related Diseases
Salameh, Y., Bejaoui, Y., & Hajj, N. E. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00171 · Cited by 322
“After the introduction of methylation arrays, a large study on >700 autopsied brain samples revealed methylation and expression changes in ANK1, CDH23, DIP2A, RHBDF2, RPL13, SERPINF1, and SERPINF2 (De Jager et al., 2014).”
BackgroundThe complexity of Alzheimer’s disease: an evolving puzzle
Ferrari, C., & Sorbi, S. (2021) · Physiological Reviews · doi:10.1152/physrev.00015.2020 · Cited by 343
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
“cancer [2–4], autoimmune disorders [5–7], psychiatric illnesses [8, 9], neurodevelopmental disorders [10, 11] and dementia [12, 13].”
BackgroundSelf-citationShou, Y., Huang, Y., Zhu, X., Liu, C., Hu, Y., & Wang, H. (2019) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2019.02.086 · Cited by 310
Aging and Alzheimer's disease: comparison and associations from molecular to system level
Xia, X., Jiang, Q., McDermott, J., & Han, J. J. (2018) · Aging Cell · doi:10.1111/acel.12802 · Cited by 301
Monoaminergic neuropathology in Alzheimer’s disease
Šimić, G., Leko, M. B., Wray, S., Harrington, C. R., Delalle, I., Milošević, N. J., Bažadona, D., Buée, L., de Silva, R., Giovanni, G. D., et al. (2016) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2016.04.001 · Cited by 297
Molecular Pathogenesis of the Tauopathies
Götz, J., Halliday, G., & Nisbet, R. M. (2019) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-012418-012936 · Cited by 276
Yu, L., Chibnik, L. B., Srivastava, G. P., Pochet, N., Yang, J., Xu, J., Kozubek, J., Obholzer, N., Leurgans, S. E., Schneider, J. A., et al. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2014.3049 · Cited by 290
Self-citationKlein, H., Aubin, C., Gjoneska, E., Sullivan, S. E., Kaskow, B. J., Tang, A. Y., Smith, R. V., Xu, J., Pfenning, A. R., Bernstein, B., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0291-1 · Cited by 283
“For example, a recent study characterized the redistribution of histone 4 lysine 16 acetylation (H4K16ac) in the temporal cortex of 12 AD subjects compared to controls 4 , but, so far, large AD-related epigenome-wide association studies of the human cortex have been limited to DNA methylation 5,6 .”
InfluentialSelf-citationLi, P., Marshall, L., Oh, G., Jakubowski, J. L., Groot, D., He, Y., Wang, T., Petronis, A., & Labrie, V. (2019) · Nature Communications · doi:10.1038/s41467-019-10101-7 · Cited by 234
The Ageing Brain: Molecular and Cellular Basis of Neurodegeneration
Azam, S., Haque, M. E., Balakrishnan, R., Kim, I., & Choi, D. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.683459 · Cited by 273
Application of Metabolomics in Alzheimer’s Disease
Wilkins, J. M., & Trushina, E. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2017.00719 · Cited by 268
Alzheimer’s Disease: From Firing Instability to Homeostasis Network Collapse
Frère, S. G. A., & Slutsky, I. (2018) · Neuron · doi:10.1016/j.neuron.2017.11.028 · Cited by 242
Marzi, S. J., Leung, S. K., Ribarska, T., Hannon, E., Smith, A. R., Pishva, E., Poschmann, J., Moore, K., Troakes, C., Al-Sarraj, S., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0253-7 · Cited by 232
Self-citationUntangling Genetic Risk for Alzheimer’s Disease
Pimenova, A. A., Raj, T., & Goate, A. M. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.05.014 · Cited by 223
“AD-related methylation changes have been detected near known GWAS genes ABCA7 and BIN1 and novel genes ANK1, RHBDF2, CDH23 and RPL13 (48, 49).”
BackgroundSelf-citationGasparoni, G., Bultmann, S., Lutsik, P., Kraus, T. F. J., Sordon, S., Vlcek, J., Dietinger, V., Steinmaurer, M., Haider, M., Mulholland, C. B., et al. (2018) · Epigenetics & Chromatin · doi:10.1186/s13072-018-0211-3 · Cited by 229
“Therefore, if not noted otherwise we worked with nominal p values as done in other recent EWAS [27, 82].”
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Epigenetic regulation and chromatin remodeling in learning and memory
Kim, S., & Kaang, B. (2017) · Experimental & Molecular Medicine · doi:10.1038/emm.2016.140 · Cited by 217
The role of ABCA7 in Alzheimer’s disease: evidence from genomics, transcriptomics and methylomics
De Roeck, A., Van Broeckhoven, C., & Sleegers, K. (2019) · Acta Neuropathologica · doi:10.1007/s00401-019-01994-1 · Cited by 212
Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex
Shireby, G. L., Davies, J. P., Francis, P. T., Burrage, J., Walker, E., Neilson, G., Dahir, A., Thomas, A. J., Love, S., Smith, R. G., et al. (2020) · Brain · doi:10.1093/brain/awaa334 · Cited by 194
“…with publicly available datasets downloaded from the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) (Jaffe et al. , 2016; De Jager et al. , 2014; Lunnon et al. , 2014; Pidsley et al. , 2014; Smith et al. , 2018, 2019; Wong et al. , 2019) (Supplementary Tables 1 and 2).”
Self-citationWatson, C. T., Roussos, P., Garg, P., Ho, D. J., Azam, N., Katsel, P. L., Haroutunian, V., & Sharp, A. J. (2016) · Genome Medicine · doi:10.1186/s13073-015-0258-8 · Cited by 201
“Eight of the genes overlapped by these top 25 DMRs (LOC100507547, PPT2, PPT2-EGFL8, PRDM16, PRRT1, C10orf105, CDH23, and RNF39) were also among genes recently reported to be associated with the most significantly differentially methylated CpGs in one or more of three brain regions (entorhinal cortex, prefrontal cortex…”
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Bekdash, R. A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22031273 · Cited by 222
A Revised Sociogenomic Model of Personality Traits
Roberts, B. W. (2017) · Journal of Personality · doi:10.1111/jopy.12323 · Cited by 216
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Verheijen, J., & Sleegers, K. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.02.007 · Cited by 192
Targeting microglia for the treatment of Alzheimer’s Disease
Wes, P. D., Sayed, F. A., Bard, F., & Gan, L. (2016) · Glia · doi:10.1002/glia.22988 · Cited by 185
“Furthermore, many of these genes fall into the same protein interaction network, suggesting that they may be part of a common biological pathway (De Jager et al., 2014).”
BackgroundGraph Theory and Brain Connectivity in Alzheimer’s Disease
del'Etoile, J., & Adeli, H. (2017) · The Neuroscientist · doi:10.1177/1073858417702621 · Cited by 188
Smith, R. G., Hannon, E., De Jager, P. L., Chibnik, L., Lott, S. J., Condliffe, D., Smith, A. R., Haroutunian, V., Troakes, C., Al‐Sarraj, S., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.01.017 · Cited by 184
“Although one previous study had demonstrated differential methylation at a single CpG within the HOXA gene cluster [7] and another identified a DMR spanning seven CpG sites [6], this represents the first study to illustrate that hypermethylation in this region extends to 208 DMPs, spanning approximately 48.”
BackgroundMethodInfluentialSelf-citationWatson, C. T., Szutorisz, H., Garg, P., Martin, Q., Landry, J. A., Sharp, A. J., & Hurd, Y. L. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.155 · Cited by 185
Epigenetics of Alzheimer’s Disease
Perković, M. N., Paska, A. V., Konjevod, M., Kouter, K., Štrac, D. Š., Erjavec, G. N., & Pivac, N. (2021) · Biomolecules · doi:10.3390/biom11020195 · Cited by 192
Hodes, R. J., & Buckholtz, N. S. (2015) · Expert Opinion on Therapeutic Targets · doi:10.1517/14728222.2016.1135132 · Cited by 170
“The aim is to discover, select, and characterize novel therapeutic targets for AD and begin building predictive models.[4,5] A major goal is to shorten the time between discovery of potential”
BackgroundEpigenetic Alterations in Alzheimer’s Disease
Sanchez-Mut, J. V., & Gräff, J. (2015) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2015.00347 · Cited by 175
“WDR81 (SERPINF1 and SERPINF2) Increase Gene body (Upstream) BS-array NA (decrease and increase) Human Entorhinal, temporal, and prefrontal cortex De Jager et al., 2014 BS-array, bisulfite-modified DNA based arrays, MSRE-PCR, methylation-sensitive restriction enzyme-PCR, MeDIP, Methylated DNA…”
BackgroundMicroRNA-132 provides neuroprotection for tauopathies via multiple signaling pathways
El Fatimy, R., Li, S., Chen, Z., Mushannen, T., Gongala, S., Wei, Z., Balu, D. T., Rabinovsky, R., Cantlon, A., Elkhal, A., et al. (2018) · Acta Neuropathologica · doi:10.1007/s00401-018-1880-5 · Cited by 161
Smith, R. G., Pishva, E., Shireby, G. L., Smith, A. R., Roubroeks, J. A. Y., Hannon, E. J., Wheildon, G., Mastroeni, D., Gasparoni, G., Riemenschneider, M. J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23243-4 · Cited by 176
Self-citationWes, P. D., Holtman, I. R., Boddeke, E. W. G. M., Möller, T., & Eggen, B. J. L. (2016) · Glia · doi:10.1002/glia.22866 · Cited by 167
“With this in mind, two groups recently performed the first large-scale epigenomewide association studies (EWAS) in AD, focusing of the DNA methylation of CpG positions, which is known to influence gene expression (De Jager et al., 2014; Lunnon et al., 2014).”
Recent Progress in Alzheimer’s Disease Research, Part 2: Genetics and Epidemiology
Robinson, M. J., Lee, B. Y., & Hane, F. T. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161149 · Cited by 179
“Epigenomic studies are revealing common sites of methylation that occur in AD, including at genomic sites ABCA7 and BIN1 regions (which have been identified previously in genomic studies and validated associations by measuring RNA expression of nearby genes, including: ANK1, CDH23, DP2A, RPL13, SERPINF1 and 2 [91].”
BackgroundAltered Expression of the m6A Methyltransferase METTL3 in Alzheimer’s Disease
Huang, H., Camats‐Perna, J., Medeiros, R., Anggono, V., & Widagdo, J. (2020) · eNeuro · doi:10.1523/eneuro.0125-20.2020 · Cited by 164
Epigenetics in Alzheimer’s Disease: Perspective of DNA Methylation
Qazi, T. J., Quan, Z., Mir, A., & Qing, H. (2018) · Molecular Neurobiology · doi:10.1007/s12035-016-0357-6 · Cited by 153
iRhoms 1 and 2 are essential upstream regulators of ADAM17-dependent EGFR signaling
Li, X., Maretzky, T., Weskamp, G., Monette, S., Qing, X., Issuree, P. D. A., Crawford, H. C., McIlwain, D. R., Mak, T. W., Salmon, J. E., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1505649112 · Cited by 162
“Therapeutically targeting iRhom2 in the brain could thus be beneficial for prevention or treatment of Alzheimer’s disease, particularly in patients with increased expression of iRhom2 (35).”
BackgroundHuman DNA methylomes of neurodegenerative diseases show common epigenomic patterns
Sanchez-Mut, J. V., Heyn, H., Vidal, E., Morán, S., Sayols, S., Delgado‐Morales, R., Schultz, M. D., Ansoleaga, B., Garcia‐Esparcia, P., Pons‐Espinal, M., et al. (2016) · Translational Psychiatry · doi:10.1038/tp.2015.214 · Cited by 160
Herbert, J., & Lucassen, P. J. (2016) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2015.12.001 · Cited by 150
“…pattern: results from different studies have been highly variable; some (often based on small numbers of subjects) report no differences between AD and controls, and analysis of positive findings is complicated by being limited to end-stage disease (De Jager et al., 2014; Van den Hove et al., 2014).”
ResultPlascencia‐Villa, G., Ponce, A., Collingwood, J. F., Arellano-Jiménez, M. J., Zhu, X., Rogers, J. T., Betancourt, I., José–Yacamán, M., & Perry, G. L. (2016) · Scientific Reports · doi:10.1038/srep24873 · Cited by 153
Epigenetics of dementia: understanding the disease as a transformation rather than a state
Maloney, B., & Lahiri, D. K. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(16)00065-x · Cited by 159
Seo, D. H., Pineda, S., Fang, J., Gozukara, Y. M., Yick, S., Bendavid, A., Lam, S. K. H., Murdock, A. T., Murphy, A. B., Han, Z., et al. (2017) · Nature Communications · doi:10.1038/ncomms14217 · Cited by 152
Advances in Porous Silicon–Based Nanomaterials for Diagnostic and Therapeutic Applications
Tieu, T., Alba, M., Elnathan, R., Cifuentes‐Rius, A., & Voelcker, N. H. (2018) · Advanced Therapeutics · doi:10.1002/adtp.201800095 · Cited by 150
Fabrício, D. D. M., Chagas, M. H. N., & Diniz, B. S. (2020) · Translational research · doi:10.1016/j.trsl.2020.01.002 · Cited by 153
The APOE Gene is Differentially Methylated in Alzheimer’s Disease
Foraker, J. E., Millard, S. P., Leong, L., Thomson, Z., Chen, S., Keene, C. D., Bekris, L. M., & Yu, C. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-143060 · Cited by 143
“Notably, other DNA methylation studies have not identified APOE to be differentially methylated in AD [22, 25].”
BackgroundDobbyn, A. L., Huckins, L. M., Boocock, J., Sloofman, L. G., Glicksberg, B. S., Giambartolomei, C., Hoffman, G. E., Perumal, T. M., Girdhar, K., Jiang, Y., et al. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.04.011 · Cited by 144
Self-citationDelgado‐Morales, R., Agís‐Balboa, R. C., Esteller, M., & Berdasco, M. (2017) · Clinical Epigenetics · doi:10.1186/s13148-017-0365-z · Cited by 147
“ANK1 DNA methylation Human WGBS, BS-array, pyrosequencing [121, 122]”
BackgroundMethodEditing the Epigenome: Reshaping the Genomic Landscape
Holtzman, L., & Gersbach, C. A. (2018) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-083117-021632 · Cited by 147
“For example, epigenetic aberrations are commonly observed in cancer (4), Parkinson’s disease (52), Alzheimer’s disease (39, 115), and diabetes (68).”
BackgroundOmics sciences for systems biology in Alzheimer’s disease: State-of-the-art of the evidence
Hampel, H. J., Nisticò, R., Seyfried, N. T., Levey, A. I., Modeste, E. S., Lemercier, P., Baldacci, F., Toschi, N., Garaci, F., Perry, G. L., et al. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101346 · Cited by 147
Dissecting the clinical heterogeneity of early-onset Alzheimer’s disease
Sirkis, D. W., Bonham, L. W., Johnson, T. P., La Joie, R., & Yokoyama, J. S. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01531-9 · Cited by 151
“Given that methylation within SORL1, ABCA7, and other loci has been associated with AD risk [233, 234], the results suggest that epigenetic modifications (and genetic variation that affects such modifications) should be explored further for their contribution to EOAD risk.”
Conserved brain myelination networks are altered in Alzheimer’s and other neurodegenerative diseases
Allen, M., Wang, X., Burgess, J. D., Watzlawik, J., Serie, D. J., Younkin, C. S., Nguyen, T., Malphrus, K. G., Lincoln, S., Carrasquillo, M. M., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2017.09.012 · Cited by 143
“We also included cell specific gene levels as covariates to account for neuronal loss, gliosis and/or vascular tissue, as previously described[22].”
Self-citationGenetic–epigenetic interactions in cis: a major focus in the post-GWAS era
Do, C., Shearer, A., Suzuki, M., Terry, M. B., Gelernter, J. E., Greally, J. M., & Tycko, B. (2017) · Genome biology · doi:10.1186/s13059-017-1250-y · Cited by 145
Kaempferol: Paving the path for advanced treatments in aging-related diseases
Hussain, M. S., Altamimi, A. S. A., Afzal, M., Almalki, W. H., Kazmi, I. A., Alzarea, S. I., Gupta, G., Shahwan, M. J., Kukreti, N., Wong, L. S., et al. (2024) · Experimental Gerontology · doi:10.1016/j.exger.2024.112389 · Cited by 146
Cronin, P., McCarthy, M. J., Lim, A. S. P., Salmon, D. P., Galasko, D. R., Masliah, E., Jager, P. L. D., Bennett, D. A., & Desplats, P. (2016) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2016.10.003 · Cited by 143
“Although significant changes in methylation have been reported in AD brains [15] and altered circadian methylation rhythms have been noted in the human frontal cortex in the context of AD [14], the pathways that mediate circadian deregulation in AD are yet not fully elucidated, and nothing is known about epigenetic me…”
BackgroundSelf-citationCano, A., Sánchez-López, E., Ettcheto, M., López-Machado, A., Espina, M., Souto, E. B., Galindo, R., Camins, A., García, M. L., & Turowski, P. (2020) · Nanomedicine · doi:10.2217/nnm-2019-0443 · Cited by 144
Nagpal, S., Meng, X., Epstein, M. P., Tsoi, L. C., Patrick, M. T., Gibson, G. C., Jager, P. L. D., Bennett, D. A., Wingo, A. P., Wingo, T. S., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.05.018 · Cited by 134
Self-citationThe interaction between ageing and Alzheimer's disease: insights from the hallmarks of ageing
Liu, Y., Tan, Y., Zhang, Z., Yi, M., Zhu, L., & Peng, W. (2024) · Translational Neurodegeneration · doi:10.1186/s40035-024-00397-x · Cited by 156
Zhang, L., Silva, T. C., Young, J. I., Gomez, L., Schmidt, M. A., Hamilton-Nelson, K. L., Kunkle, B. W., Chen, X., Martin, E. R., & Wang, L. (2020) · Nature Communications · doi:10.1038/s41467-020-19791-w · Cited by 139
Birnbaum, J. H., Wanner, D., Gietl, A. F., Saake, A., Kündig, T. M., Hock, C., Nitsch, R. M., & Tackenberg, C. (2018) · Stem Cell Research · doi:10.1016/j.scr.2018.01.019 · Cited by 135
DNA Methyltransferases, DNA Methylation, and Age-Associated Cognitive Function
Cui, D., & Xu, X. Z. S. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19051315 · Cited by 139
Alzheimer’s disease-associated (hydroxy)methylomic changes in the brain and blood
Lardenoije, R., Roubroeks, J. A. Y., Pishva, E., Leber, M., Wagner, H., Iatrou, A., Smith, A. R., Smith, R. G., Eijssen, L., Kleineidam, L., et al. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0755-5 · Cited by 135
Self-citationRamanan, V. K., Risacher, S. L., Nho, K., Kim, S., Shen, L., McDonald, B. C., Yoder, K. K., Hutchins, G. D., West, J. D., Tallman, E. F., et al. (2015) · Brain · doi:10.1093/brain/awv231 · Cited by 133
Self-citationMicroglial Malfunction: The Third Rail in the Development of Alzheimer's Disease
Mhatre, S. D., Tsai, C. A., Rubin, A. J., James, M. L., & Andreasson, K. I. (2015) · Trends in Neurosciences · doi:10.1016/j.tins.2015.08.006 · Cited by 134
“In epigenome-wide association studies (EWAS) examining patterns of DNA methylation, the gene (ANK1) encoding ankyrin 1, a cytoskeletal protein known to be involved in inflammation, was found to be hypermethylated in AD patients [123,124].”
Genome-wide quantification of the effects of DNA methylation on human gene regulation
Lea, A. J., Vockley, C. M., Johnston, R. A., Carpio, C. A. D., Barreiro, L. B., Reddy, T. E., & Tung, J. (2018) · eLife · doi:10.7554/elife.37513 · Cited by 138
Neuropathological and transcriptomic characteristics of the aged brain
Miller, J. A., Guillozet-Bongaarts, A., Gibbons, L. E., Postupna, N., Renz, A., Beller, A. E., Sunkin, S. M., Ng, L., Rose, S. E., Smith, K. A., et al. (2017) · eLife · doi:10.7554/elife.31126 · Cited by 134
Functions of ‘A disintegrin and metalloproteases (ADAMs)’ in the mammalian nervous system
Hsia, H., Tüshaus, J., Brummer, T., Zheng, Y., Scilabra, S. D., & Lichtenthaler, S. F. (2019) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-019-03173-7 · Cited by 148
Mechanisms and Disease Associations of Haplotype-Dependent Allele-Specific DNA Methylation
Do, C., Lang, C. F., Lin, J. P., Darbary, H. K., Krupska, I., Gaba, A., Petukhova, L., Vonsattel, J., GALLAGHER, M. P., Goland, R., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.03.027 · Cited by 130
Metadata
- Authors
- De Jager, P. L., Srivastava, G., Lunnon, K., Burgess, J., Schalkwyk, L. C., Yu, L., Eaton, M. L., Keenan, B. T., Ernst, J., McCabe, C., Tang, A., Raj, T., Replogle, J., Brodeur, W., Gabriel, S., Chai, H. S., Younkin, C., Younkin, S. G., Zou, F., Szyf, M., Epstein, C. B., Schneider, J. A., Bernstein, B. E., Meissner, A., Ertekin-Taner, N., Chibnik, L. B., Kellis, M., Mill, J., & Bennett, D. A.
- Affiliations
- Broad Institute (US)
- King's College London (GB)
- Mayo Clinic (US)
- Rush University Medical Center (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Bennett, David A
- ORCID
- Venue
- Nature Neuroscience
- Published
- 2014-08-17
- Volume
- 17
- Issue
- 9
- Pages
- 1156-1163
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC4292795
- OpenAlex
- W2074750860
- Cited by
- 956
- References
- 62
- Citations by year
- 2026: 49 · 2025: 77 · 2024: 74 · 2023: 69 · 2022: 82 · 2021: 94 · 2020: 93 · 2019: 94 · 2018: 93 · 2017: 71 · 2016: 84 · 2015: 59 · 2014: 17
- FWCI
- 31.73
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Open Access at Essex (University of Essex) (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion)
- Figshare (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Open Research Exeter (University of Exeter) (submittedVersion)
- Funders
- National Institute on Aging (R01AG017917, P30-AG 10161, K25AG041906, R01AG036039, R01‐AG17917, R01 AG15819, R01AG018023, R01AG036836, U01AG046152, R01-AG18023, AG036039, R01AG036042, R01AG015819, P30AG010161, RC2AG036547, R01AG032990, U01AG046139, RF1AG015819, RF1AG036042, P50AG016574)
- National Human Genome Research Institute (R01HG004037)
- National Institute of Neurological Disorders and Stroke (R01NS080820)
- National Institute of Environmental Health Sciences (U01ES017155)
- National Center for Research Resources (KL2RR024151)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- Alzheimer's disease, DNA methylation, ANK1, BIN1, RHBDF2, ABCA7, differentially methylated regions, gene expression, preclinical Alzheimer's disease, epigenome-wide association study
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Amyloidosis, Brain, Carrier Proteins, Female, Humans, Male, Middle Aged, Nuclear Proteins, Ankyrins, CpG Islands, DNA Methylation, Genetic Predisposition to Disease, Tumor Suppressor Proteins, Intracellular Signaling Peptides and Proteins, Adaptor Proteins, Signal Transducing, Genome-Wide Association Study, Protein Interaction Maps
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