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Epigenomic dissection of Alzheimer’s disease pinpoints causal variants and reveals epigenome erosion
Open accessAbstract
Recent work has identified dozens of non-coding loci for Alzheimer's disease (AD) risk, but their mechanisms and AD transcriptional regulatory circuitry are poorly understood. Here, we profile epigenomic and transcriptomic landscapes of 850,000 nuclei from prefrontal cortexes of 92 individuals with and without AD to build a map of the brain regulome, including epigenomic profiles, transcriptional regulators, co-accessibility modules, and peak-to-gene links in a cell-type-specific manner. We develop methods for multimodal integration and detecting regulatory modules using peak-to-gene linking. We show AD risk loci are enriched in microglial enhancers and for specific TFs including SPI1, ELF2, and RUNX1. We detect 9,628 cell-type-specific ATAC-QTL loci, which we integrate alongside peak-to-gene links to prioritize AD variant regulatory circuits. We report differential accessibility of regulatory modules in late AD in glia and in early AD in neurons. Strikingly, late-stage AD brains show global epigenome dysregulation indicative of epigenome erosion and cell identity loss.
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In the citing paper
“Recent single-cell studies of human AD revealed the links between DNA damage and epigenome erosion during disease progression77,78.”
From Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerability (2025) · cites this paper as [78]
In the citing paper
“These work estimated damage burden by measuring chimeric gene fusions arose from DSBs.”
From Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerability (2025) · cites this paper as [78]
In the citing paper
“Note the rs10792832-flanking peak (highlighted in the vertical yellow box) identified in our iMG is only present in brain microglia but not in other cell types.”
From PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia (2025) · cites this paper as [24]
In the citing paper
“These severely affected donors had lower transcription and reduced chromatin accessibility that may correspond to senescent states97, or global epigenome dysregulation that is indicative of cell identity loss98.”
From Integrated multimodal cell atlas of Alzheimer’s disease (2024) · cites this paper as [98]
In the citing paper
“the accompanying manuscript by Xiong et al. describes widespread changes in cell-type specific chromatin accessibility within excitatory neurons in human AD samples which they term “epigenome erosion””
From Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration (2023) · cites this paper as [89]
In the citing paper
“This is strikingly similar to epigenome erosion, particularly in excitatory neurons and oligodendrocytes, characterized by the loss of cell-type specific chromatin accessibility profile reported in the companion manuscript89.”
From Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration (2023) · cites this paper as [89]
Citations
Cites
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Integrated analysis of multimodal single-cell data
Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zagar, M., et al. (2020) · doi:10.1101/2020.10.12.335331 · Cited by 15,508
Fast, sensitive and accurate integration of single-cell data with Harmony
Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.-R., & Raychaudhuri, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0619-0 · Cited by 10,488
SCANPY: large-scale single-cell gene expression data analysis
Wolf, F. A., Angerer, P., & Theis, F. J. (2018) · Genome Biology · doi:10.1186/s13059-017-1382-0 · Cited by 8,881
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
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
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
Querfurth, H. W., & LaFerla, F. M. (2010) · New England Journal of Medicine · doi:10.1056/nejmra0909142 · Cited by 4,569
GREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502
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
AKT/PKB Signaling: Navigating the Network
Manning, B. D., & Toker, A. (2017) · Cell · doi:10.1016/j.cell.2017.04.001 · Cited by 3,772
Single-cell transcriptomic analysis of Alzheimer’s disease
Mathys, H., Davila-Velderrain, J., Peng, Z., Gao, F., Mohammadi, S., Young, J. Z., Menon, M., He, L., Abdurrob, F., Jiang, X., et al. (2019) · Nature · doi:10.1038/s41586-019-1195-2 · Cited by 2,568
New insights into the genetic etiology of Alzheimer’s disease and related dementias
Bellenguez, C., Küçükali, F., Jansen, I. E., Kleineidam, L., Moreno-Grau, S., Amin, N., Naj, A. C., Campos-Martin, R., Grenier-Boley, B., Andrade, V., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01024-z · Cited by 2,498 · cited 1×
“Despite AD’s high heritability and tens of AD-GWAS-associated genetic loci, functional interpretation and finemapping of variants remains challenging, as many lie in the non-coding genome.(8,12,13) A common hypothesis for non-coding variants is that they disrupt cell-type-specific regulatory elements to affect gene ex…”
BackgroundChromHMM: automating chromatin-state discovery and characterization
Ernst, J., & Kellis, M. (2012) · Nature Methods · doi:10.1038/nmeth.1906 · Cited by 2,457
Staging of alzheimer's disease-related neurofibrillary changes
Braak, H., & Braak, E. (1995) · Neurobiology of Aging · doi:10.1016/0197-4580(95)00021-6 · Cited by 2,357
An integrated map of structural variation in 2,504 human genomes
Sudmant, P. H., Rausch, T., Gardner, E. J., Handsaker, R. E., Abyzov, A., Huddleston, J., Zhang, Y., Ye, K., Jun, G., Hsi-Yang Fritz, M., et al. (2015) · Nature · doi:10.1038/nature15394 · Cited by 2,354
The “independent components” of natural scenes are edge filters
Bell, A. J., & Sejnowski, T. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00121-1 · Cited by 2,201
Normalization of RNA-seq data using factor analysis of control genes or samples
Risso, D., Ngai, J., Speed, T. P., & Dudoit, S. (2014) · Nature Biotechnology · doi:10.1038/nbt.2931 · Cited by 2,052
JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles
Castro-Mondragon, J. A., Riudavets-Puig, R., Rauluseviciute, I., Berhanu Lemma, R., Turchi, L., Blanc-Mathieu, R., Lucas, J., Boddie, P., Khan, A., Manosalva Pérez, N., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1113 · Cited by 1,935
ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis
Granja, J. M., Corces, M. R., Pierce, S. E., Bagdatli, S. T., Choudhry, H., Chang, H. Y., & Greenleaf, W. J. (2021) · Nature Genetics · doi:10.1038/s41588-021-00790-6 · Cited by 1,392
TREM2 Maintains Microglial Metabolic Fitness in Alzheimer’s Disease
Ulland, T. K., Song, W. M., Huang, S. C.-C., Ulrich, J. D., Sergushichev, A., Beatty, W. L., Loboda, A. A., Zhou, Y., Cairns, N. J., Kambal, A., et al. (2017) · Cell · doi:10.1016/j.cell.2017.07.023 · Cited by 1,263
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-citationActivity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations
Fulco, C. P., Nasser, J., Jones, T. R., Munson, G., Bergman, D. T., Subramanian, V., Grossman, S. R., Anyoha, R., Doughty, B. R., Patwardhan, T. A., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0538-0 · Cited by 1,111
Natural history of mild cognitive impairment in older persons
Bennett, D. A., Wilson, R. S., Schneider, J. A., Evans, D. A., Beckett, L. A., Aggarwal, N. T., Barnes, L. L., Fox, J. H., & Bach, J. (2002) · Neurology · doi:10.1212/wnl.59.2.198 · Cited by 1,037
Grubman, A., Chew, G., Ouyang, J. F., Sun, G., Choo, X. Y., McLean, C., Simmons, R. K., Buckberry, S., Vargas-Landin, D. B., Poppe, D., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0539-4 · Cited by 956
Yeh, F. L., Wang, Y., Tom, I., Gonzalez, L. C., & Sheng, M. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.015 · Cited by 943
BBKNN: fast batch alignment of single cell transcriptomes
Polański, K., Young, M. D., Miao, Z., Meyer, K. B., Teichmann, S. A., & Park, J.-E. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz625 · Cited by 932
A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk
Yang, A. C., Vest, R. T., Kern, F., Lee, D. P., Agam, M., Maat, C. A., Losada, P. M., Chen, M. B., Schaum, N., Khoury, N., et al. (2022) · Nature · doi:10.1038/s41586-021-04369-3 · Cited by 797
Controlling the false discovery rate via knockoffs
Barber, R. F., & Candès, E. J. (2015) · The Annals of Statistics · doi:10.1214/15-aos1337 · Cited by 756
Brain 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
Panning for Gold: ‘Model-X’ Knockoffs for High Dimensional Controlled Variable Selection
Candès, E. J., Fan, Y., Janson, L., & Lv, J. (2018) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12265 · Cited by 694
Single-nucleus chromatin accessibility and transcriptomic characterization of Alzheimer’s disease
Morabito, S., Miyoshi, E., Michael, N., Shahin, S., Martini, A. C., Head, E., Silva, J., Leavy, K., Perez-Rosendahl, M., & Swarup, V. (2021) · Nature Genetics · doi:10.1038/s41588-021-00894-z · Cited by 643
Multi-omics single-cell data integration and regulatory inference with graph-linked embedding
Cao, Z.-J., & Gao, G. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01284-4 · Cited by 616
Fast and efficient QTL mapper for thousands of molecular phenotypes
Ongen, H., Buil, A., Brown, A. A., Dermitzakis, E. T., & Delaneau, O. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv722 · Cited by 580
Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer's disease
Gjoneska, E., Pfenning, A. R., Mathys, H., Quon, G., Kundaje, A., Tsai, L.-H., & Kellis, M. (2015) · Nature · doi:10.1038/nature14252 · Cited by 576
Self-citationSingle-cell RNA-seq reveals cell type–specific molecular and genetic associations to lupus
Perez, R. K., Gordon, M. G., Subramaniam, M., Kim, M. C., Hartoularos, G. C., Targ, S., Sun, Y., Ogorodnikov, A., Bueno, R., Lu, A. C., et al. (2022) · Science · doi:10.1126/science.abf1970 · Cited by 535
Schwartzentruber, J., Cooper, S., Liu, J. Z., Barrio-Hernandez, I., Bello, E., Kumasaka, N., Young, A. M. H., Franklin, R. J. M., Johnson, T., Estrada, K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00776-w · Cited by 532
Bennett, D. A., Schneider, J. A., Wilson, R. S., Bienias, J. L., & Arnold, S. E. (2004) · Archives of Neurology · doi:10.1001/archneur.61.3.378 · Cited by 526
Self-citationMathys, H., Peng, Z., Boix, C. A., Victor, M. B., Leary, N., Babu, S., Abdelhady, G., Jiang, X., Ng, A. P., Ghafari, K., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.039 · Cited by 495
Self-citationMolecular characterization of selectively vulnerable neurons in Alzheimer’s disease
Leng, K., Li, E., Eser, R., Piergies, A., Sit, R., Tan, M., Neff, N., Li, S. H., Rodriguez, R. D., Suemoto, C. K., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-020-00764-7 · Cited by 485
STAT3 labels a subpopulation of reactive astrocytes required for brain metastasis
Priego, N., Zhu, L., Monteiro, C., Mulders, M., Wasilewski, D., Bindeman, W., Doglio, L., Martínez, L., Martínez-Saez, E., Ramón y Cajal, S., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0044-4 · Cited by 452
Akbarian, S., Liu, C., Knowles, J. A., Vaccarino, F. M., Farnham, P. J., Crawford, G. E., Jaffe, A. E., Pinto, D., Dracheva, S., Geschwind, D. H., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4156 · Cited by 451
GTEx Consortium, Gamazon, E. R., Segrè, A. V., van de Bunt, M., Wen, X., Xi, H. S., Hormozdiari, F., Ongen, H., Konkashbaev, A., Derks, E. M., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0154-4 · Cited by 412
TFBSTools: an R/bioconductor package for transcription factor binding site analysis
Tan, G., & Lenhard, B. (2016) · Bioinform. · doi:10.1093/bioinformatics/btw024 · Cited by 370
propeller: testing for differences in cell type proportions in single cell data
Phipson, B., Sim, C. B., Porrello, E. R., Hewitt, A. W., Powell, J. E., & Oshlack, A. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac582 · Cited by 362
Factors regulating microglia activation
Kierdorf, K., & Prinz, M. (2013) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2013.00044 · Cited by 360
Corces, M. R., Shcherbina, A., Kundu, S., Gloudemans, M. J., Frésard, L., Granja, J. M., Louie, B. H., Eulalio, T., Shams, S., Bagdatli, S. T., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00721-x · Cited by 358
Alzheimer’s disease: analyzing the missing heritability
Ridge, P. G., Mukherjee, S., Crane, P. K., Kauwe, J. S. K., & Alzheimer’s Disease Genetics Consortium (2013) · PLoS ONE · doi:10.1371/journal.pone.0079771 · Cited by 328
Zeb1 links epithelial-mesenchymal transition and cellular senescence
Liu, Y., El‐Naggar, S., Darling, D. S., Higashi, Y., & Dean, D. C. (2008) · Development · doi:10.1242/dev.007047 · Cited by 312
A 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
UCSC Cell Browser: visualize your single-cell data
Speir, M. L., Bhaduri, A., Markov, N. S., Moreno, P. A., Nowakowski, T. J., Papatheodorou, I., Pollen, A. A., Raney, B. J., Seninge, L., Kent, W. J., et al. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab503 · Cited by 281
Infectious Complications of Open Type III Tibial Fractures among Combat Casualties
Johnson, E. N., Burns, T. C., Hayda, R. A., Hospenthal, D. R., & Murray, C. K. (2007) · Clinical Infectious Diseases · doi:10.1086/520029 · Cited by 275
Wu, L., Sun, T., Kobayashi, K., Gao, P., & Griffin, J. D. (2002) · Molecular and Cellular Biology · doi:10.1128/mcb.22.21.7688-7700.2002 · Cited by 266
Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients
Mertens, J., Herdy, J. R., Traxler, L., Schafer, S. T., Schlachetzki, J. C. M., Böhnke, L., Reid, D. A., Lee, H., Zangwill, D., Fernandes, D. P., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.04.004 · Cited by 240
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
Somatic genomic changes in single Alzheimer’s disease neurons
Miller, M. B., Huang, A. Y., Kim, J., Zhou, Z., Kirkham, S. L., Maury, E. A., Ziegenfuss, J. S., Reed, H. C., Neil, J. E., Rento, L., et al. (2022) · Nature · doi:10.1038/s41586-022-04640-1 · Cited by 223
Reed, B. D., Charos, A. E., Szekely, A. M., Weissman, S. M., & Snyder, M. P. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000133 · Cited by 214
Novikova, G., Kapoor, M., TCW, J., Abud, E. M., Efthymiou, A. G., Chen, S. X., Cheng, H., Fullard, J. F., Bendl, J., Liu, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21823-y · Cited by 214
Temporal course and pathologic basis of unawareness of memory loss in dementia
Wilson, R. S., Boyle, P. A., Yu, L., Barnes, L. L., Sytsma, J., Buchman, A. S., Bennett, D. A., & Schneider, J. A. (2015) · Neurology · doi:10.1212/wnl.0000000000001935 · Cited by 195
Genetic determinants of co-accessible chromatin regions in activated T cells across humans
Gate, R. E., Cheng, C. S., Aiden, A. P., Siba, A., Tabaka, M., Lituiev, D., Machol, I., Gordon, M. G., Subramaniam, M., Shamim, M., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0156-2 · Cited by 181
He, L., Davila-Velderrain, J., Sumida, T. S., Hafler, D. A., Kellis, M., & Kulminski, A. M. (2021) · Communications Biology · doi:10.1038/s42003-021-02146-6 · Cited by 181
Self-citationGenetics of the human microglia regulome refines Alzheimer’s disease risk loci
Kosoy, R., Fullard, J. F., Zeng, B., Bendl, J., Dong, P., Rahman, S., Kleopoulos, S. P., Shao, Z., Girdhar, K., Humphrey, J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01149-1 · Cited by 168
Self-citationThe missing link between genetic association and regulatory function
Connally, N. J., Nazeen, S., Lee, D., Shi, H., Stamatoyannopoulos, J. A., Chun, S., Cotsapas, C. J., Cassa, C. A., & Sunyaev, S. R. (2022) · eLife · doi:10.7554/elife.74970 · Cited by 153
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Xiong, X., Hou, L., Park, Y., Molinié, B., Ardlie, K., Aguet, F., Gregory, R. I., & Kellis, M. (2021) · Nature Genetics · doi:10.1038/s41588-021-00890-3 · Cited by 149
Dileep, V., Boix, C. A., Mathys, H., Marco, A., Welch, G. M., Meharena, H. S., Loon, A., Jeloka, R., Peng, Z., Bennett, D. A., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.038 · Cited by 130
Self-citationBIN1 is a key regulator of proinflammatory and neurodegeneration-related activation in microglia
Sudwarts, A., Ramesha, S., Gao, T., Ponnusamy, M., Wang, S., Hansen, M. T., Kozlova, A., Bitarafan, S., Kumar, P., Beaulieu‐Abdelahad, D., et al. (2022) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00535-x · Cited by 110
Large-scale chromatin reorganization reactivates placenta-specific genes that drive cellular aging
Liu, Z., Ji, Q., Ren, J., Yan, P., Wu, Z., Wang, S., Sun, L., Wang, Z., Li, J., Sun, G., et al. (2022) · Developmental Cell · doi:10.1016/j.devcel.2022.05.004 · Cited by 109
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Oliveira, T. G., & Paolo, G. D. (2010) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2010.04.004 · Cited by 99
Miura, Y., Tam, T., Ido, A., Morinaga, T., Miki, T., Hashimoto, T., & Tamaoki, T. (1995) · Journal of Biological Chemistry · doi:10.1074/jbc.270.45.26840 · Cited by 91
Zhang, Y., Amaral, M. L., Zhu, C., Grieco, S. F., Hou, X., Lin, L., Buchanan, J., Tong, L., Preissl, S., Xu, X., et al. (2022) · Cell Research · doi:10.1038/s41422-022-00719-6 · Cited by 89
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Wilson, R. S., Barral, S., Lee, J. H., Leurgans, S. E., Foroud, T., Sweet, R. A., Graff-Radford, N., Bird, T. D., Mayeux, R. P., & Bennett, D. A. (2011) · Journal of Alzheimer s Disease · doi:10.3233/jad-2010-101515 · Cited by 86
Limited overlap of eQTLs and GWAS hits due to systematic differences in discoveryPreprint
Mostafavi, H., Spence, J. P., Naqvi, S., & Pritchard, J. K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.07.491045 · Cited by 86
Dedifferentiation and neuronal repression define familial Alzheimer’s disease
Caldwell, A. B., Liu, Q., Schroth, G. P., Galasko, D. R., Yuan, S. H., Wagner, S. L., & Subramaniam, S. (2020) · Science Advances · doi:10.1126/sciadv.aba5933 · Cited by 69
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Bendl, J., Hauberg, M. E., Girdhar, K., Im, E., Vicari, J. M., Rahman, S., Fernando, M. B., Townsley, K. G., Dong, P., Misir, R., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01166-7 · Cited by 65
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Zhou, M., Xu, X., Wang, H., Yang, G., Yang, M., Zhao, X., Guo, H., Song, J., Zheng, H., Zhu, Z., et al. (2020) · The FASEB Journal · doi:10.1096/fj.201901836rr · Cited by 33
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Human microglial state dynamics in Alzheimer’s disease progression
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“Especially in excitatory neurons, the cohesin complex expression was also correlated with the expression of many chromatin regulators, warranting the examination of changes to the chromatin landscape in AD (see Dileep et al. 48 and Xiong et al. 49 in this issue).”
BackgroundSelf-citationAlzheimer’s disease: insights into pathology, molecular mechanisms, and therapy
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Integrated multimodal cell atlas of Alzheimer’s disease
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Cellular and pathological functions of tau
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Metadata
- Authors
- Xiong, X., James, B. T., Boix, C. A., Park, Y. P., Galani, K., Victor, M. B., Sun, N., Hou, L., Ho, L.-L., Mantero, J., Scannail, A. N., Dileep, V., Dong, W., Mathys, H., Bennett, D. A., Tsai, L.-H., & Kellis, M.
- Affiliations
- MIT Computer Science and Artificial Intelligence Laboratory (US)
- Broad Institute (US)
- Massachusetts Institute of Technology (US)
- University of California San Diego (US)
- University of Pittsburgh (US)
- Rush University Medical Center (US)
- Corresponding author
- Tsai, Li-Huei
- Kellis, Manolis
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2023-09
- Volume
- 186
- Issue
- 20
- Pages
- 4422-4437.e21
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC10782612
- OpenAlex
- W4387142583
- Cited by
- 205
- References
- 86
- Citations by year
- 2026: 70 · 2025: 72 · 2024: 51 · 2023: 11
- FWCI
- 36.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion, other-oa)
- Funders
- Cure Alzheimer's Fund
- National Institutes of Health (AG062377, P30AG10161, NS110453, U01AG46152, AG058002, MH119509, R01AG57473, U01AG61356, AG054012, NS127187, R01AG17917, P30AG72975, AG062335, NS115064, HG008155, MH109978, DA053631, R01AG15819, AG067151, AG074003, AG081017, AG077227, NS129032)
- Russian Science Foundation
- National Science Foundation (1745302)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- Alzheimer's disease, prefrontal cortex, PU.1, RUNX1, chromatin accessibility, glial cells, neurons
- MeSH terms
- Epigenome, Alzheimer Disease, Brain, Gene Expression Regulation, Humans, 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.
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