The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
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.
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
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
“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.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
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
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 .”
InfluentialSelf-citation
Flagged first, then by citations
Cited by
Sorted by citations
Items 901–975 of 975
Zhao, S., Yang, Q., & Gao, C. (2025) · Revista de investigaci�n Cl�nica · doi:10.24875/ric.24000246
The Aging Epigenome: Integrative Analyses Reveal Functional Overlap with Alzheimer’s DiseasePreprint
Zhang, W., Lukacsovich, D., Young, J., Gomez, L., Schmidt, M., Kunkle, B. W., Chen, X., Martin, E., & Wang, L. (2025) · medRxiv · doi:10.1101/2025.06.08.25329218
“These data were generated from two large clinical cohorts, the Framingham Heart Study (Exam 9) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI ).”
InfluentialDeciphering the Interplay: DNA Methylation Dynamics in Aging and Neurodegenerative Diseases
Lee, Y., & Lee, S.-M. (2025) · RNA technologies · doi:10.1007/978-3-031-91072-2_2
Ye, P., Kong, W., & Wang, S. (2025) · Current Bioinformatics · doi:10.2174/0115748936367139250801163310
The Search for Answers: Causes, Risk Factors, and Current Research in Neurodegenerative Disorders
Kajrolkar, A. (2025) · Premier Journal of Neuroscience · doi:10.70389/pjn.100013
Porras, L. M., Rodríguez‐Lausell, I., Iglesias‐Maldonado, G., Tuliao, E. V. F., Martínez, G., Leveque, C., Tobon, J., Eloy, R., Belangero, S. I., Bulik, C. M., et al. (2025) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.33063
Natural Compounds as Epigenetic Modulators to Treat Neurodegenerative Disorders
Rumman, M., & Khan, M. V. (2025) · Springer eBooks · doi:10.1007/978-981-95-0125-0_8
Gut microbiota and mental issues in humans
Singh, J., Mistry, C. R., Sharma, A., Baiju, A., Kumar, B., Maji, A., Sharma, M., Singh, A., Prasad, V., Lalbiaktluangi, C., et al. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-29932-2.00013-x
Lokmer, A., Troudet, R., Bacq‐Daian, D., Boland, A., Barau, C., the OPTiMiSE study group, Deleuze, J., Leboyer, M., & Jamain, S. (2025) · Translational Psychiatry · doi:10.1038/s41398-025-03561-7
Yu, D., Germann, J., Murtaza, G., Hajdarovic, K. H., Babcock, K. R., Dehkordi, S. K., Jackson, A. C., Delalle, I., Orr, M. E., Zare, H., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.08.681270 · Cited by 1
Aged brain multi-omic integration captures immunometabolic and sex variationPreprint
Whalley, J. P., Hunsberger, H. C., Bennett, D., Lamar, M., Peterson, D. A., & Stutzmann, G. E. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.10.681695
Self-citationSherman, E., Qiu, K., Roberts, R., Shichman, L., Li, S., Sun, H., Ide, L., Tucker, A., Lee, S., Gniadzik, W., et al. (2025) · SSRN Electronic Journal · doi:10.1101/2025.10.17.683162 · Cited by 1
Xiao, B., Zeng, Y., Klein, K., Granato, B., Blanchette, M., Shao, X., & Greenwood, C. M. T. (2025) · Scientific Reports · doi:10.1038/s41598-025-22004-3
Yamamoto, R., Fu, T., Huang, E., Fraser, A., Mohammad, N., Xiao, X. G., & Zaitlen, N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.14.688520
Gao, X., Jiang, P., Liu, L., Huang, Y., Tan, H., Guo, W., Xie, H., Xing, P., Wang, Q., Peng, S., et al. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.120788
A Functional Approach to Testing Overall Effect of Interaction Between DNA Methylation and SNPs
Gansou, Y., Oualkacha, K., Cremona, M. A., & Lakhal‐Chaieb, L. (2026) · Statistics in Medicine · doi:10.1002/sim.70364
Huang, J., Bai, L., Cui, B., Wu, L., Wang, L., An, Z., Ruan, S., Yu, Y., Zhang, X., & Chen, J. (2020) · Figshare · doi:10.6084/m9.figshare.12097371
Flores-Aguilar, L., Iulita, M. F., Orciani, C., Tanna, N., Yang, J., Bennett, D. A., & Cuello, A. C. (2021) · Figshare · doi:10.6084/m9.figshare.14908162
Self-citationRydbirk, R., Folke, J., Busato, F., Roché, E., Chauhan, A. S., Løkkegaard, A., Hejl, A.-M., Bode, M., Blaabjerg, M., Møller, M. L., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11960322
Yu, F., Xu, C., HongWen, D., & Shen, H. (2020) · Figshare · doi:10.6084/m9.figshare.13316615
Flores-Aguilar, L., Iulita, M. F., Orciani, C., Tanna, N., Yang, J., Bennett, D. A., & Cuello, A. C. (2021) · Figshare · doi:10.6084/m9.figshare.14908153
Self-citationAdditional file 1 of Sex-specific DNA methylation differences in Alzheimer’s disease pathology
Zhang, L., Young, J. I., Gomez, L., Silva, T. C., Schmidt, M. A., Cai, J., Chen, X., Martin, E. R., & Wang, L. (2021) · Figshare · doi:10.6084/m9.figshare.14490461
Chen, Q., Aguirre, L., Liang, G., Zhao, H., Dong, T., Borrego, F., de Rojas, I., Hu, Q., Reyes, C., Su, L.-Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26944074
Walker, R. M., Vaher, K., Bermingham, M. L., Morris, S. W., Bretherick, A. D., Zeng, Y., Rawlik, K., Amador, C., Campbell, A., Haley, C. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.13521105
Gamache, J., Gingerich, D. C., Shwab, E. K., Barrera, J., Garrett, M. E., Hume, C., Crawford, G. E., Ashley‐Koch, A. E., & Chiba‐Falek, O. (2024) · Figshare · doi:10.6084/m9.figshare.26622151
Flores-Aguilar, L., Iulita, M. F., Orciani, C., Tanna, N., Yang, J., Bennett, D. A., & Cuello, A. C. (2021) · Figshare · doi:10.6084/m9.figshare.14908147
Self-citationHuang, J., Bai, L., Cui, B., Wu, L., Wang, L., An, Z., Ruan, S., Yu, Y., Zhang, X., & Chen, J. (2020) · Figshare · doi:10.6084/m9.figshare.12097362
Additional file 1 of Distinct sex-specific DNA methylation differences in Alzheimer’s disease
C. Silva, T., Zhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Varma, A., Chen, X. S., Martin, E. R., & Wang, L. (2022) · Figshare · doi:10.6084/m9.figshare.21129953
Li, Q. S., Vasanthakumar, A., Davis, J. W., Idler, K. B., Nho, K. T., Waring, J. F., & Saykin, A. J. (2021) · Figshare · doi:10.6084/m9.figshare.16821479
Chen, Q., Aguirre, L., Liang, G., Zhao, H., Dong, T., Borrego, F., de Rojas, I., Hu, Q., Reyes, C., Su, L.-Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26944077
Vasanthakumar, A., Davis, J. W., Idler, K. B., Waring, J. F., Asque, E., Riley-Gillis, B. M., Grosskurth, S., Srivastava, G. P., Kim, S., Nho, K. T., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12487052
Self-citationWang, Q., Chen, Y., Readhead, B., Chen, K., Su, Y., Reiman, E. M., & Dudley, J. T. (2020) · Figshare · doi:10.6084/m9.figshare.13357550
Mei, H., Simino, J. M., Li, L., Jiang, F., Bis, J. C., Davies, G., Hill, W. D., Xia, C., Gudnason, V. G., Yang, Q., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25036297
Self-citationWalker, R. M., Vaher, K., Bermingham, M. L., Morris, S. W., Bretherick, A. D., Zeng, Y., Rawlik, K., Amador, C., Campbell, A., Haley, C. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.13521102
Li, C., Shangguan, Y., Zhu, P., Dai, W., Tang, D., Ou, M., & Dai, Y. (2021) · Figshare · doi:10.6084/m9.figshare.16880267
Rydbirk, R., Folke, J., Busato, F., Roché, E., Chauhan, A. S., Løkkegaard, A., Hejl, A.-M., Bode, M., Blaabjerg, M., Møller, M. L., et al. (2020) · Figshare · doi:10.6084/m9.figshare.11960316
Chen, Q., Aguirre, L., Liang, G., Zhao, H., Dong, T., Borrego, F., de Rojas, I., Hu, Q., Reyes, C., Su, L.-Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26944071
Flores-Aguilar, L., Iulita, M. F., Orciani, C., Tanna, N., Yang, J., Bennett, D. A., & Cuello, A. C. (2021) · Figshare · doi:10.6084/m9.figshare.14908144
Self-citationLi, Q. S., Sun, Y., & Wang, T. (2020) · Figshare · doi:10.6084/m9.figshare.13107633
Vellame, D. S., Castanho, I., Dahir, A., Mill, J. S., & Hannon, E. J. (2021) · Figshare · doi:10.6084/m9.figshare.14782453
Self-citationBarrera, J., Song, L., Gamache, J., Garrett, M. E., Safi, A., Yun, Y., Premasinghe, I., Sprague, D., Chipman, D., Li, J., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16435926
Additional file 1 of Alzheimer’s disease-related transcriptional sex differences in myeloid cells
Coales, I., Tsartsalis, S., Fancy, N. N., Weinert, M., Clode, D., Owen, D., & Matthews, P. (2022) · Figshare · doi:10.6084/m9.figshare.21285653
Gamache, J., Gingerich, D. C., Shwab, E. K., Barrera, J., Garrett, M. E., Hume, C., Crawford, G. E., Ashley‐Koch, A. E., & Chiba‐Falek, O. (2024) · Figshare · doi:10.6084/m9.figshare.26622154
Sommerer, Y., Dobričić, V. S., Schilling, M., Ohlei, O., Sabet, S. S., Wesse, T., Fuß, J., Franzenburg, S., Franke, A., Parkkinen, L., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22775893
Xu, H., Chien, J.-F., Kozlenkov, A., Vadukapuram, R., Li, J., Wei, Y., Dwork, A. J., Liu, C., Dracheva, S. M., & Mukamel, E. A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.18.706675 · Cited by 1
DNA Adenine Methylation Clock in Brain Aging and Alzheimer’s Disease ProgressionPreprint
Rahim, A., Zhan, X., Han, Q., O’Donnell, A., Jeong, A., Madugundu, G. S., Pujari, S. S., Kruk, M., Luo, X., Li, L., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.05.709867 · Cited by 1
“14 The neuropathological markers, such as neurotic plaques, diffuse plaques, and amyloid load, were associated with epigenetic age acceleration in the dorsolateral prefrontal cortex.”
Epigenetic reprogramming in traumatic brain injury
Lu, Z., & Sima, J. (2025) · Aging Research · doi:10.26599/agr.2025.9340067
Pathophysiological role of Pyk2 in the nervous system
de Pins, B. (2019) · theses.fr (ABES) · doi:10.70675/e9fd4e35z9e7ez42d4za65cz5d999e5b2d5e
Valverde, A. (2020) · theses.fr (ABES) · doi:10.70675/f1b70734zf4e3z4870z8fbdz950d831642a7
The role of the serum response factor in the pathogenesis of Huntington's disease
Awada, A. (2021) · theses.fr (ABES) · doi:10.70675/fabef4b5z9d78z440bz99f2z9be7d0814a03
Signatures épigénétiques de la maladie d'Alzheimer dans l'ADN libre circulant
Guemri, J. (2021) · theses.fr (ABES) · doi:10.70675/aa3cb199zc068z4b72zab7fz6deb0fe1de87
The Use of Localized Proteomics to Understand the Pathogenesis of Alzheimer's Disease
Pires, G. (2021) · theses.fr (ABES) · doi:10.70675/45826fd6zd2c8z4b3dz91e0za5080544cb17
Marmiroli, G., Candelora, F., Fiano, V., Richiardi, L., & Popovic, M. (2026) · Clinical Epigenetics · doi:10.1186/s13148-026-02124-x
The aging epigenome: integrative analyses reveal intersection with Alzheimer’s disease
Zhang, W., Lukacsovich, D., Young, J. I., Gomez, L., Schmidt, M. A., Kunkle, B. W., Chen, X., Martin, E. R., Wang, L., & Initiative, A. D. N. (2026) · GeroScience · doi:10.1007/s11357-026-02195-x
“Growing literature also links DNAm signatures to both incident dementia (including our study [8]) and early alterations in AD neuropathology [9].”
BIN1 (amphiphysin 2) in the pathogenesis of cognitive impairment
Shamakina, I. Y., Kokhan, V. S., Venkova, V. A., Баронец, В. Ю., Popov, S. S., & Anokhin, P. K. (2026) · S S Korsakov Journal of Neurology and Psychiatry · doi:10.17116/jnevro202612603145
Wan, M.-D., Liu, X., Wan, T., Liu, Y.-W., Jiang, Y.-L., Zou, J., Jiao, B., Liu, Q.-Q., Jin, L., Duan, R., et al. (2026) · Journal of Neuroinflammation · doi:10.1186/s12974-026-03854-8
Shared genetic architecture between Alzheimer’s disease and brain morphology
Wu, X., Shadrin, A. A., Blokland, G. A. M., Gülöksüz, S., Andreassen, O. A., Linden, D. E. J., & van der Meer, D. (2026) · Alzheimer s Research & Therapy · doi:10.1186/s13195-026-02105-5
“The absence of significant correlations is likely in part due to GWAS only capturing common SNP variation, not accounting for epigenetics and other complex, dynamic regulatory mechanisms, leading to ‘missing heritability’ [20].”
Functional omics for disease modelling and target identification in neurodegenerative drug discovery
Singh, S. A., Nirenjen, S., Sridevi, S., Afreen, N., Prajapati, B. G., Rushendran, R., Vellapandian, C., & Begum, R. F. (2026) · Advances in protein chemistry and structural biology · doi:10.1016/bs.apcsb.2026.02.008
Astrocyte epigenetics in development, aging, and neurodegeneration: a DNA methylation perspective
Bhaskar, U., & Carless, M. A. (2026) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2026.1876219
Talotta, R., & Rapisarda, F. (2026) · IntechOpen eBooks · doi:10.5772/intechopen.1016888
Frank, L. E., Flack, N., Faulk, C. D., Block, A. J., Bartz, J. C., & Larsen, P. A. (2026) · Prion · doi:10.1080/19336896.2026.2710965
“Disruption of these mechanisms has been linked to various diseases, including many cancers and diseases caused by environmental exposures ( e.g. , air pollution, heavy metals) [13–15].”
Activity-dependent DNA methylation and demethylation: epigenetic regulators of learning and memory
Li, Z., Xu, Z., Li, X., Ren, H., Zhang, Y., Sun, Z., Xu, H., Zeng, F., Liu, Z., Chen, J., et al. (2026) · Neurobiology of Disease · doi:10.1016/j.nbd.2026.107596
BIN1 (Amphiphysin 2) in the Pathogenesis of Cognitive Impairment
Shamakina, I. Y., Kokhan, V. S., Venkova, V. A., Баронец, В. Ю., Popov, S. S., & Anokhin, P. K. (2026) · Neuroscience and Behavioral Physiology · doi:10.1007/s11055-026-02059-z
“Indeed, analysis of DNA methylation patterns in the brains of AD patients revealed altered BIN1 methylation by the early stages of the disease [46–48].”
Bioactive Compounds as Putative Molecules of Neuroplasticity: An Epigenetic Perspective
Zhao, F., Bordoni, L., Mao, Y., Cao, J., Gong, F., Hou, W., Li, T., Gabbianelli, R., & Li, K. (2026) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.6c08366
Neuroepigenetics of the Environmental Exposome
Avendaño-Arango, E., Salom-Palacio, I., Castillo-Támara, E. E., & Palacio-Villalba, B. (2026) · The Neurologist · doi:10.1097/nrl.0000000000000694
Proteomic Signatures of Noise‐Induced Hearing Loss in the Mouse Cochlea
Batissoco, A. C., Coutinho, D., Ferreira‐Scatone, A. C., Cavassana, S. D., Oiticica, J., Lezirovitz, K., & Bento, R. F. (2026) · Cell Biology International · doi:10.1002/cbin.70218
“ANK1 dysregulation has been associated with Alzheimer's disease neuropathology (De Jager et al. 2014; Lunnon et al. 2014), EHD3 participates in vesicular pathways linked to amyloid processing (Buggia‐Prévot et al. 2013), and MAP2 is involved in microtubule organization and dendritic stability in…”
Giuliani, M. E., Fortunato, C., Fumarola, S., Pazmay, G. V. B., Giuliani, A., Marcozzi, S., Bigossi, G., Lai, G., Alimi, S. S., Perini, D., et al. (2026) · Experimental Gerontology · doi:10.1016/j.exger.2026.113348
Yaman, Ü., Gustavsson, E. K., Lee, J., Ugolini, H., Macpherson, H. L., Mumford, P., Wiseman, F. K., Hardy, J., & Salih, D. A. M. (2026) · STAR Protocols · doi:10.1016/j.xpro.2026.104827
Use of chromatin changes as biomarkers
Hlady, R. A., & Robertson, K. D. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-19001-8.00027-1
Miao, G., Gao, C., Yu, L., Yang, J., Li, Y., Grodstein, F., Schneider, J. A., Barnes Lisa, L., Jager, P. L. D., Yao, B., et al. (2026) · Nature Aging · doi:10.1038/s43587-026-01243-7
Self-citationHONG, Y., Ming, G.-L., & SONG, H. (2026) · Handbook of clinical neurology · doi:10.1016/b978-0-443-19043-8.00002-5
Epigenetic mechanisms in brain development and in neurodegeneration
MA, Y., CHEN, K. W., & JAGER, P. D. (2026) · Handbook of clinical neurology · doi:10.1016/b978-0-443-19043-8.00030-x
Cerebrospinal fluid cell-free DNA methylation captures disease-specific biology in tauopathies
Tian, H., Zhang, J., Zuo, H., Liu, Y., Kim, I.-D., & 桂雅星 (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877261500498
Roadmap Epigenomics Enhancer-Gene links
Ernst, J. (2017) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.12042964
Self-citation
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
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