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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Recent single-cell studies of human AD revealed links between DNA damage and epigenome erosion during disease progression.
“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]
These works estimated damage burden by measuring chimeric gene fusions arising from DSBs.
“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]
The rs10792832-flanking OCR peak identified in iMG is present in brain microglia but not in other brain cell types.
“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]
These severely affected donors had lower transcription and reduced chromatin accessibility that may correspond to senescent states or global epigenome dysregulation that is indicative of cell identity loss.
“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]
The accompanying manuscript by Xiong et al. describes widespread changes in cell-type specific chromatin accessibility within excitatory neurons in human AD samples, termed epigenome erosion.
“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]
The observed loss of TAD definition and loop intensities 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 manuscript.
“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]
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Yang, J.-H., Griffin, P. T., Vera, D. L., Apostolides, J. K., Hayano, M., Meer, M. V., Salfati, E. L., Su, Q., Munding, E. M., Blanchette, M., et al. (2019) · doi:10.1101/808642 · Cited by 38 · see citing works
Effect of central JAZF1 on glucose production is regulated by the PI3K‐Akt‐AMPK pathway
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Epigenetic Erosion in Adult Stem Cells: Drivers and Passengers of Aging
Kosan, C., Heidel, F. H., Godmann, M., & Bierhoff, H. (2018) · Cells · doi:10.3390/cells7120237 · Cited by 27 · see citing works
ZBED1/DREF: A transcription factor that regulates cell proliferation (Review)
Jin, Y., Li, R., Zhang, Z., Ren, J., Song, X., & Zhang, G. (2020) · Oncology Letters · doi:10.3892/ol.2020.11997 · Cited by 26 · see citing works
DeepLINK: Deep learning inference using knockoffs with applications to genomics
Zhu, Z., Fan, Y., Kong, Y., Lv, J., & Sun, F. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2104683118 · Cited by 23 · see citing works
Is CpG Density the Link between Epigenetic Aging and Lifespan?
Bertucci, E. M., & Parrott, B. B. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.06.003 · Cited by 22 · see citing works
Knockoff boosted tree for model-free variable selection
Jiang, T., Li, Y., & Motsinger‐Reif, A. A. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa770 · Cited by 17 · see citing works
CoCoA-diff: counterfactual inference for single-cell gene expression analysis
Park, Y., & Kellis, M. (2021) · Genome biology · doi:10.1186/s13059-021-02438-4 · Cited by 17 · see citing works
Kousi, M., Boix, C., Park, Y. P., Mathys, H., Sledzieski, S., Peng, Z., Bennett, D. A., Tsai, L.-H., & Kellis, M. (2022) · doi:10.1101/2022.04.21.489103 · Cited by 7 · see citing works
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Human microglial state dynamics in Alzheimer’s disease progression
Sun, N., Victor, M. B., Park, Y. P., Xiong, X., Scannail, A. N., Leary, N., Prosper, S., Viswanathan, S., Luna, X., Boix, C. A., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.037 · Cited by 462 · see citing works
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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
Zheng, Q., & Wang, X. (2024) · Protein & Cell · doi:10.1093/procel/pwae026 · Cited by 454 · see citing works
Integrated multimodal cell atlas of Alzheimer’s disease
Gabitto, M. I., Travaglini, K. J., Rachleff, V. M., Kaplan, E. S., Long, B., Ariza, J., Ding, Y., Mahoney, J. T., Dee, N., Goldy, J., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01774-5 · Cited by 397 · see citing works
Cellular and pathological functions of tau
Bravo, C. P., Naguib, S. A., & Gan, L. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00753-9 · Cited by 245 · see citing works
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 · see citing works
“87 Interestingly, erosion of epigenetic information, TAD insulation, and cell identity was recently reported in a mouse model with inducible DNA damage (ICE mouse model) accompanied by brain aging and cognitive decline.”
BackgroundSelf-citationRen, F., Wei, J., Chen, Q., Hu, M., Yu, L., Mi, J., Zhou, X., Qin, D., Wu, J., & Wu, A. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.07.030 · Cited by 97 · see citing works
Yang, X., Mann, K. K., Wu, H., & Ding, J. (2024) · Genome biology · doi:10.1186/s13059-024-03338-z · Cited by 90 · see citing works
Therapeutic targeting of senescent cells in the CNS
Rießland, M., Ximerakis, M., Jarjour, A. A., Zhang, B., & Orr, M. E. (2024) · Nature Reviews Drug Discovery · doi:10.1038/s41573-024-01033-z · Cited by 74 · see citing works
Single-cell multiplex chromatin and RNA interactions in ageing human brain
Wen, X., Luo, Z., Zhao, W., Calandrelli, R., Nguyen, T. C., Wan, X., Richard, J. L. C., & Zhong, S. (2024) · Nature · doi:10.1038/s41586-024-07239-w · Cited by 65 · see citing works
“These data are reminiscent of a recent report on the association of global epigenome dysregulation and Alzheimer’s disease 44 .”
Liu, Z., Zhang, S., James, B. T., Galani, K., Mangan, R. J., Fass, S. B., Liang, C., Wagle, M. M., Boix, C. A., Tanigawa, Y., et al. (2025) · Cell · doi:10.1016/j.cell.2025.06.031 · Cited by 65 · see citing works
Levites, Y., Dammer, E. B., Ran, Y., Tsering, W., Duong, D. M., Abreha, M. H., Gadhavi, J. D., Lolo, K., Trejo‐Lopez, J. A., Phillips, J., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101669 · Cited by 57 · see citing works
PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia
Kozlova, A., Zhang, S., Sudwarts, A., Zhang, H., Smirnou, S., Byeon, S. K., Thapa, C., Sun, X., Stephenson, K., Zhao, X., et al. (2025) · Nature · doi:10.1038/s41586-025-09486-x · Cited by 53 · see citing works
“Except for our iMG, data of all other cell types are from a snATAC-seq study 24 and reanalysed by using 10x Genomics Cell Ranger ARC 2.0.2.”
InfluentialCross-disorder and disease-specific pathways in dementia revealed by single-cell genomics
Rexach, J. E., Cheng, Y., Chen, L., Polioudakis, D., Lin, L., Mitri, V., Elkins, A., Han, X., Yamakawa, M., Yin, A., et al. (2024) · Cell · doi:10.1016/j.cell.2024.08.019 · Cited by 56 · see citing works
Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data
Xu, J., Lu, C., Jin, S., Meng, Y., Fu, X., Zeng, X., Nussinov, R., & Cheng, F. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf138 · Cited by 48 · see citing works
“A previous study have demonstrated that SPI1 and RUNX1 binding sites exhibit higher enrichment with known AD genetic loci from genome-wide association study [ 34 ].”
InfluentialThe night’s watch: Exploring how sleep protects against neurodegeneration
Parhizkar, S., & Holtzman, D. M. (2025) · Neuron · doi:10.1016/j.neuron.2025.02.004 · Cited by 51 · see citing works
Gene networks and systems biology in Alzheimer's disease: Insights from multi‐omics approaches
Rahimzadeh, N., Srinivasan, S. S., Zhang, J., & Swarup, V. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13790 · Cited by 36 · see citing works
Wang, G., Zhao, J., Lin, Y., Liu, T., Zhao, Y., & Zhao, H. (2025) · Nature Communications · doi:10.1038/s41467-025-60333-z · Cited by 29 · see citing works
“Integrating different single-cell modalities that measure brain cells is crucial for revealing intricate cell type-speci fi c regulatory networks and pathways, as well as studying disease mechanisms such as the Alzheimer ’ s disease in the brain 10 .”
Human brain vascular multi-omics elucidates disease-risk associations
Reid, M. M., Menon, S., Liu, H., Zhou, H., Hu, Z., Frerich, S., Ding, B., Oveisgharan, S., Zhang, Z., Nelson, S., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.07.001 · Cited by 33 · see citing works
Khan, A. F., & Iturria‐Medina, Y. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-03073-w · Cited by 28 · see citing works
“As genomics progresses from bulk tissue to single-cell/nucleus sequencing and spatial transcriptomics [228, 229], and larger omics datasets such as the Seattle Alzhiemer ’ s Disease Brain Cell Atlas (SEA-AD) become available [230], there is an increasing opportunity to integrate molecular…”
BackgroundCacabelos, R., Martínez-Iglesias, O. A., Cacabelos, N., Carrera, I., Corzo, L., & Naidoo, V. (2024) · Life · doi:10.3390/life14121555 · Cited by 27 · see citing works
Hudson, H. R., Sun, X., & Orr, M. E. (2025) · Neurotherapeutics · doi:10.1016/j.neurot.2024.e00519 · Cited by 26 · see citing works
“While a comprehensive evaluation for senescence susceptibility of all neuronal cell types has not been explored, one consistent fi nding across the early reports has been that excitatory neurons may be particularly vulnerable to neurescence [37,39,43,52].”
Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer’s disease
Vilkaite, G., Vogel, J. W., & Mattsson, N. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101735 · Cited by 25 · see citing works
Wen, J., Yang, Z., Nasrallah, I. M., Cui, Y., Erus, G., Srinivasan, D., Abdulkadir, A., Mamourian, E., Skampardoni, I., Hwang, G., et al. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-03121-5 · Cited by 30 · see citing works
Ghatak, S., Diedrich, J. K., Talantova, M. V., Bhadra, N., Scott, H. R., Sharma, M., Albertolle, M. E., Schork, N. J., Yates, J. R., & Lipton, S. A. (2024) · Advanced Science · doi:10.1002/advs.202400545 · Cited by 22 · see citing works
Accelerated epigenetic aging in Huntington’s disease involves polycomb repressive complex 1
Brulé, B., Alcalá‐Vida, R., Penaud, N., Scuto, J., Mounier, C., Séguin, J., Khodaverdian, S. V., Cosquer, B., Birmelé, É., Gras, S. L., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56722-z · Cited by 22 · see citing works
Murphy, K. B., Hu, D., Wolfs, L., Rohde, S. K., Fauró, G. L., Geric, I., Mancuso, R., De Strooper, B., & Marzi, S. J. (2025) · Nature Communications · doi:10.1038/s41467-025-60099-4 · Cited by 25 · see citing works
Microglia networks within the tapestry of alzheimer’s disease through spatial transcriptomics
Zhou, Y. F., & Glass, C. K. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00897-y · Cited by 20 · see citing works
“Multiple studies have now begun to apply single-cell and spatial genomics to identify cellular vulnerabilities and molecular changes in human brains with AD [18, 20, 21, 23, 76, 86, 93, 125– 131].”
Mehta, P., & Shende, P. K. (2023) · Journal of Drug Delivery Science and Technology · doi:10.1016/j.jddst.2023.105205 · Cited by 18 · see citing works
Genetic risk for neurodegenerative conditions is linked to disease-specific microglial pathways
Askarova, A., Yaa, R. M., Marzi, S. J., & Nott, A. (2025) · PLoS Genetics · doi:10.1371/journal.pgen.1011407 · Cited by 18 · see citing works
“These findings corroborate observations that AD GWAS variants are enriched at microglia enhancers compared to microglia promoters defined using histone modifications [40,56].”
Varshney, A., Manickam, N., Orchard, P., Tovar, A., Ventresca, C., Zhang, Z., Feng, F., Mears, J., Erdos, M. R., Narisu, N., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.15.571696 · Cited by 18 · see citing works
Zhou, B., Li, J., Wu, A., Wang, X., Cheng, L., Yang, G., Gao, D., & Zhu, C. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2025.1587986 · Cited by 17 · see citing works
Zheng, Z., Qiao, X., Yin, J., Kong, J., Han, W., Qin, J., Meng, F., Tian, G., & Feng, X. (2024) · International Journal of Molecular Medicine · doi:10.3892/ijmm.2024.5479 · Cited by 17 · see citing works
“In the complex pathology of ALI/ARDS, finding novel diagnostic markers is key (183). compared to using one of these technologies alone, integrating transcriptomic and epigenomic analyses provides deeper insight into disease pathogenesis and potential thera‑ peutic targets (184,185).”
Epigenetics in Neurodegenerative Diseases
van Zundert, B., & Montecino, M. A. (2025) · Sub-cellular biochemistry/Subcellular biochemistry · doi:10.1007/978-3-031-75980-2_3 · Cited by 18 · see citing works
Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerability
Bai, D., Cao, Z., Attada, N., Song, J., & Zhu, C. (2025) · Nature Methods · doi:10.1038/s41592-025-02632-3 · Cited by 16 · see citing works
Zou, F., Liu, Y., Luo, Y., & Xu, T. (2025) · Science Advances · doi:10.1126/sciadv.adw1732 · Cited by 16 · see citing works
Introducing the Role of Genotoxicity in Neurodegenerative Diseases and Neuropsychiatric Disorders
Kisby, G. E., Wilson, D. M., & Spencer, P. S. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25137221 · Cited by 16 · see citing works
“Transcriptome and epigenome data from single-cell studies of AD brain tissue have revealed that DNA damage and DNA repair increase substantially as the disease progresses [49,53]).”
BackgroundMulti-omics and high-spatial-resolution omics: deciphering complexity in neurological disorders
Liu, X., Li, F., Czosnyka, M., Czosnyka, Z. H., Yu, H., Tong, X., Xing, Y., Li, H., Pu, K., Feng, K., et al. (2025) · GigaScience · doi:10.1093/gigascience/giaf137 · Cited by 16 · see citing works
“However, future studies should incorporate histone chromatin immunoprecipitation sequencing technology to enable more refined characterization of chromatin states [ 80 ].”
Ma, Y., Xia, Y., Karako, K., Song, P., Tang, W., & Hu, X. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-04997-0 · Cited by 13 · see citing works
“In the early stages of AD, local epigenomic changes predominate, while in the late stages, the entire epigenome becomes dysregulated, a phenomenon known as “epig-enomic erosion” [108–110].”
Sun, Y., Liu, S., Chen, L., Zhou, Z., Yin, X., Shi, Y., Li, H., Li, J., Lü, Y., Jiang, W., et al. (2025) · Science Advances · doi:10.1126/sciadv.adz9283 · Cited by 14 · see citing works
“To evaluate MLT’s therapeutic potential, we interrogated BMAL1/p300/SP1 expression profiles by integrating scRNA-seq ( 51 ) (patients with AD) and spatial transcriptomics (APP/PS1 mice) ( 52 ).”
The broken Alzheimer’s disease genome
Roque, C. G., Phatnani, H. P., & Hengst, U. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100555 · Cited by 13 · see citing works
The AD odyssey 2023: Tales of single cell
Luo, W., Qu, W., & Gan, L. (2023) · Cell · doi:10.1016/j.cell.2023.09.001 · Cited by 14 · see citing works
Cognitive resilience to Alzheimer's disease characterized by cell‐type abundance
O’Neill, N. K., Stein, T. D., Olayinka, O. A., Empawi, J. A., Hu, J., Tong, T., Zhang, X., & Farrer, L. A. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14187 · Cited by 13 · see citing works
Single cell variant to enhancer to gene map for coronary artery diseasePreprint
Amrute, J., Lee, P. C., Eres, I. E., Lee, C. J. M., Bredemeyer, A. L., Sheth, M. U., Yamawaki, T., Gurung, R., Anene-Nzelu, C. G., Qiu, W., et al. (2024) · medRxiv · doi:10.1101/2024.11.13.24317257 · Cited by 12 · see citing works
“Single cell caQTLs enable further identification of variants that may regulate chromatin accessibility in a cell-type specific manner 34,53 .”
Dong, M., Qian, Y., Geng, Y., Wang, R., Wang, Y., Cai, J., Wang, X., Huang, Y., Liu, Y., Liu, W., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251378007 · Cited by 12 · see citing works
Liu, A., Citu, C., Enduru, N., Chen, X., Tung, C.-H., Sinha, T., Sepulveda, S. E., Manuel, A. M., Gorski, D., Fernandes, B. S., et al. (2025) · Science Advances · doi:10.1126/sciadv.adw4917 · Cited by 14 · see citing works
“1B), we computed chromatin erosion scores using ChromHMM based on a previously described method ( 8 ).”
InfluentialYamakawa, M., & Rexach, J. E. (2024) · Biomedicines · doi:10.3390/biomedicines12020308 · Cited by 11 · see citing works
“…genes could be indicative of low-quality cells as conventionally interpreted; however, recent single-cell multiomic studies have shown the presence of transcription erosion in severely affected cases [27,73], which also aligns with the terminal differentiation of the enriched CD8 T cell population.”
BackgroundCocoş, R., & Popescu, B. O. (2024) · Human Genomics · doi:10.1186/s40246-024-00704-7 · Cited by 14 · see citing works
“…chromatin sequencing coupled with high-throughput sequencing (ATAC–seq) [249] while concurrently establishing a single-cell-resolution population-scale map of epigenomic alterations of multidimensional chromatin states [250], thereby enhancing the cell type-specific transcriptomic observations.”
Wen, J., Yang, Z., Nasrallah, I. M., Cui, Y., Erus, G., Srinivasan, D., Abdulkadir, A., Mamourian, E., Skampardoni, I., Hwang, G., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.16.508329 · Cited by 12 · see citing works
Zhang, J., Mao, Y., & Rao, J. (2024) · Journal of Orthopaedic Surgery and Research · doi:10.1186/s13018-024-04933-3 · Cited by 10 · see citing works
Mettl3 regulates the pathogenesis of Alzheimer’s disease via fine-tuning Lingo2
Zhao, X., Ma, C., Sun, Q., Huang, X., Qu, W., Chen, Y., Liu, Z., Bao, A., Sun, B., Yang, Y., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-02984-4 · Cited by 10 · see citing works
“Recent studies have suggested the important roles of m 6 A in the pathogenesis of AD [17 – 28], but the results are quite debated.”
Nakatsuka, N. J., Adler, D. I., Jiang, L., Hartman, A., Cheng, E., Klann, E., & Satija, R. (2025) · Nature Communications · doi:10.1038/s41467-025-62579-z · Cited by 16 · see citing works
“We found a slight decrease in reproducibility when only using the broader cell types (AUC= 0.76) as well as when using the more speci fi c cell types (AUC= 0.65), which could be due to loss of cell type identity in AD 51 , leading to worse cell mapping.”
InfluentialYaPing, Z., Ai, W., Zheng, J., Hu, X., & Zhang, L. (2024) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2024.1332845 · Cited by 10 · see citing works
“…revealed the global epigenomic information loss that occurs with H3K27ac histone modifications in patients with advanced AD; Runt-associated transcription factor 1, Spi-1 Proto-Oncogene and other transcription factors play an important role in the pathogenesis of microglia AD (Xiong et al., 2023).”
BackgroundSampson, M. M., Morgan, R. K., Sloan, S. A., & Bakulski, K. M. (2024) · Current Opinion in Toxicology · doi:10.1016/j.cotox.2024.100464 · Cited by 10 · see citing works
Chromatin accessibility provides a window into the genetic etiology of human brain disease
Bendl, J. M., Fullard, J. F., Girdhar, K., Dong, P., Kosoy, R., Zeng, B., Hoffman, G. E., & Roussos, P. (2025) · Trends in Genetics · doi:10.1016/j.tig.2025.01.001 · Cited by 9 · see citing works
Su, C., Lee, D., Jin, P., & Zhang, J. (2025) · Nature Communications · doi:10.1038/s41467-025-59306-z · Cited by 8 · see citing works
“1c shows that the computational costs vary signi fi cantly across methods, with SCENT taking 1.47 days, Signac taking 1.46 hours, and scMultiMap taking only 8.35 seconds.”
InfluentialKim, J. P., Cho, M., Kim, C., Lee, H., Jang, B., Jung, S., Kim, Y., Koh, I. G., Kim, S., Shin, D., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59949-y · Cited by 10 · see citing works
“For functional annotation, cell type-speci fi c regulatory elements from single-cell data obtained from postmortem AD brain samples 26,27 (available at https://personal. broadinstitute.org/bjames/AD_snATAC/ and https://compbio.mit. edu/microglia_states/) and AD-speci fi c epigenomic histone…”
InfluentialSingle-nucleus multi-omics identifies shared and distinct pathways in Pick’s and Alzheimer’s disease
Shi, Z., Das, S., Morabito, S., Stocksdale, J. T., Miyoshi, E., Srinivasan, S. S., Emerson, N., Shahin, A., Rahimzadeh, N., Cao, Z., et al. (2025) · Science Advances · doi:10.1126/sciadv.ads7973 · Cited by 8 · see citing works
Alzheimer's disease: from molecular pathways to therapies
Feng, J.-Q., Yang, L.-L., Ya-xi, L., & Yao, X. (2026) · Molecular Biomedicine · doi:10.1186/s43556-026-00443-2 · Cited by 9 · see citing works
“Analysis of the epigenomic and transcriptomic landscapes of 850,000 nuclei from the prefrontal cortex of 92 individuals with and without AD revealed widespread epi-genomic dysregulation in the brains of late-stage AD patients [242].”
Revolutionizing Alzheimer’s Detection: Immune-Related Gene Biomarkers as Non-Invasive Predictors
Abed, S., Ebrahimi, A., Fattahi, F., Khaniani, M. S., & Derakhshan, S. M. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-04970-x · Cited by 8 · see citing works
“While the influence of environmental factors on AD is undeniable, genetics has garnered increased interest recently due to the finding of many genetic and epigenetic anomalies associated with AD [5].”
Cognitive rejuvenation through partial reprogramming of engram cells
Berdugo‐Vega, G., Sierra, C., Astori, S., Calati, V., Orsat, J., Scoglio, M. J., Sandi, C., & Gräff, J. (2026) · Neuron · doi:10.1016/j.neuron.2025.11.028 · Cited by 8 · see citing works
Melnik, M., Miyoshi, E., Ma, R., Corrada, M. M., Kawas, C. H., Bohannan, R. C., Caraway, C. A., Miller, C. A., Hinman, J. D., John, V., et al. (2024) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2024.110137 · Cited by 8 · see citing works
GWAS highlights the neuronal contribution to multiple sclerosis susceptibilityPreprint
Zeng, L., Khan, A., Lama, T. D., Chitnis, T., Weiner, H. L., Wang, G. T., Fujita, M., Zipp, F., Taga, M. F., Kiryluk, K., et al. (2024) · medRxiv · doi:10.1101/2024.12.04.24318500 · Cited by 9 · see citing works
“Reviewing reference epigenomic profiles ( 70 ), we found that most of our top prioritized variants ( Figure 5 and Supplementary Table S7 ) are not located in segments of open chromatin in the cell types implicated by the eQTL analyses.”
Functional insight into East Asian–specific genetic risk loci for Alzheimer's disease
Cho, M., Chaudhuri, S., Liu, S., Park, T., Huang, Y.-N., Rosewood, T. J., Bice, P. J., Saykin, A. J., Won, H., & Nho, K. T. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14553 · Cited by 6 · see citing works
Du, J., & An, Z. (2025) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2025.578650 · Cited by 7 · see citing works
Single Cell Sequencing Technology and Its Application in Alzheimer’s Disease
Han, Y., Huang, C., Pan, Y., & Gu, X. (2024) · Journal of Alzheimer s Disease · doi:10.3233/jad-230861 · Cited by 7 · see citing works
GoFCards: an integrated database and analytic platform for gain of function variants in humans
Zhao, W., Tao, Y., Xiong, J., Liu, L., Wang, Z., Shao, C., Shang, L., Hu, Y., Xu, Y., Su, Y., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1079 · Cited by 7 · see citing works
Holtman, I. R., Glass, C. K., & Nott, A. (2024) · Advances in neurobiology · doi:10.1007/978-3-031-55529-9_29 · Cited by 6 · see citing works
Coleman, P. D., Delvaux, E., Kordower, J. H., Boehringer, A. V., & Huseby, C. J. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14555 · Cited by 6 · see citing works
“The relationship between the epigenome and gene expression in AD received added evidence in the recent data from Xiong et al., 41 which showed a close correspondence between chromatin accessibility and geneexpression.”
Zhang, R., Guo, S., Zhou, J., Lin, X., Wang, Y., Wang, Y., Li, M., Zhao, K., Bao, W., Shui, K., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-04367-4 · Cited by 6 · see citing works
“The coordination between chromatin structure and transcription plays a crucial role in gene regulation, influencing processes from embryonic development to the progression of disease 7,8 .”
fSuSiE enables fine-mapping of QTLs from genome-scale molecular profilesPreprint
Denault, W. R. P., Sun, H. H., Carbonetto, P. S., Liu, A., Jager, P. L. D., Bennett, D., Wang, G. T., & Stephens, M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.17.670732 · Cited by 6 · see citing works
Salminen, A. (2026) · Neurochemistry International · doi:10.1016/j.neuint.2026.106115 · Cited by 5 · see citing works
Zeng, L., Khan, A., Fitzgerald, K. C., Lama, T., Chen, J., Li, R., Harroud, A., Compston, A., Sawcer, S. J., Kermode, A. G., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02731-7 · Cited by 5 · see citing works
“Review of reference epigenomic profiles 66 showed that many prioritized variants (Fig.”
The role of astrocytes in Alzheimer’s disease: a bibliometric analysis
An, X., He, J., Bi, B., Wu, G., Xu, J., Yu, W., & Ren, Z. (2024) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2024.1481748 · Cited by 5 · see citing works
The China Brain Multi-omics Atlas Project (CBMAP)
Zhou, D., Zhou, Y., Sun, Z., Ji, F., Zhang, D., Wang, Q., Ruan, Y., Wang, Y., Zhu, Y., Sun, X., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03250-3 · Cited by 6 · see citing works
“…has analyzed the genomes, epigenomes, transcriptomes, and proteomes of hundreds of human brain tissue samples, primarily from individuals of European ancestry, thereby creating a multi-omics atlas mainly focused on understanding the etiology of Alzheimer ’ s disease (AD) [10, 11, 13, 16 – 18].”
Single-cell sequencing: accurate disease detection
Wang, X., Li, N., Wang, W., & Liu, B. (2025) · Clinical & Translational Oncology · doi:10.1007/s12094-025-04007-8 · Cited by 6 · see citing works
“On September 28, 2023, the team of Professor Li Huei Tsai of Massachusetts Institute of Technology published three research papers related to AD in the journal Cell, analyzing the pathogenesis of AD from multiple perspectives from the cellular, genetic and mechanism levels [72–74].”
Single‐cell digital twins identify drug targets and repurposable medicine in Alzheimer’s disease
Ren, Y., Hu, M., Li, Y. E., Pieper, A. A., Cummings, J. L., & Cheng, F. (2025) · Alzheimer s & Dementia · doi:10.1002/alz70859_102982 · Cited by 4 · see citing works
ACSS2 upregulation enhances neuronal resilience to aging and tau-associated neurodegeneration
Pourshafie, N., Alexander, D. C., Xu, H. W., Yang, K., Donahue, G., Lei, X., Zhang, S., Shcherbakova, O., Hogan, C., Gilbert, M., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2503834122 · Cited by 3 · see citing works
Lee, C.-Y., Hwang, A., McRiley, D., Lee, J., Thibodeau, G., Duman, C. H., Zhang, X., Škarica, M., Coudriet, J. M., Xu, S., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-68351-1 · Cited by 4 · see citing works
Impacts of host genetics on gut microbiome composition in Alzheimer’s disease
Liu, J., Cao, J., Jia, L., Gan, Z., Zhao, X., Yang, A., Lai, S., Chen, F., Yang, Y. T., & Zhao, X.-M. (2026) · Microbiome · doi:10.1186/s40168-026-02342-8 · Cited by 4 · see citing works
“To investigate the differential expression patterns of the ES-Ana-associated genes in AD brains, we leveraged a recently published snRNA-seq dataset of prefrontal cortex samples from 15 late-stage AD and 48 non-AD individuals [100].”
Dysfunction of the neurovascular unit as a temporal driver in Alzheimer’s pathogenesis
Wang, L., Han, L., & Liu, S. (2026) · Translational Neurodegeneration · doi:10.1186/s40035-026-00548-2 · Cited by 5 · see citing works
“Microglia play a key role in the onset and progression of AD [79, 80].”
Liu, W., Wu, S.-A., Zhang, B.-X., Guo, S., Li, L., Sun, W., Xiong, X., Nan, J., Wu, J., Zeng, L., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02299-9 · Cited by 4 · see citing works
Ramamurthy, E., Agarwal, S., Toong, N., Sestili, H. H., Kaplow, I. M., Chen, Z., Phan, B. N., & Pfenning, A. R. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012356 · Cited by 4 · see citing works
The chromatin conformation landscape of Alzheimer’s diseasePreprint
Nativio, R., Lan, Y., Donahue, G. D., Shcherbakova, O., Barnett, N., Titus, K., Chandrashekar, H., Phillips‐Cremins, J. E., Bonini, N. M., & Berger, S. L. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.09.588722 · Cited by 4 · see citing works
“To understand the changes that may occur to the genome with disease, our work 8,9 and others 10–13 has focused on epigenetic status of the brain in Alzheimer’s.”
BackgroundNakatsuka, N. J., Adler, D. I., Jiang, L., Hartman, A., Cheng, E., Klann, E., & Satija, R. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.15.618577 · Cited by 4 · see citing works
Early microglial priming in Alzheimer’s disease revealed by ME-seqPreprint
Zhu, B., Ghosh, A., Wang, Z., Liao, Z., Appiah, M. G., Li, J., Zhang, M., Tullio, F. D., Kurowski, A., Fullard, J. F., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.30.702946 · Cited by 4 · see citing works
“Sai Ma sai.ma2@mssm.edu; Nan Yang nan.yang1@mssm.edu; Ka Lung Cheung kalung.cheung@mssm.edu Lead contact: Sai Ma sai.ma2@mssm.edu Graphic abstract”
Xiao, H., Wang, J., & Wan, S. (2024) · doi:10.1101/2024.09.25.614862 · Cited by 6 · see citing works
Siano, G., Varisco, M., Terrigno, M., Wang, C., Scarlatti, A., Iannone, V., Groth, M., Galas, M., Hoozemans, J. J. M., Cellerino, A., et al. (2025) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1459573 · Cited by 3 · see citing works
“92 (Zerbino et al., 2018)) with Tophat v2.”
Bone-Derived Factors: Regulating Brain and Treating Alzheimer’s Disease
Guan, Q., Cao, Y., Zou, J., & Zhang, L. (2025) · Biology · doi:10.3390/biology14091112 · Cited by 3 · see citing works
“AD risk loci are significantly enriched in microglial enhancer regions (e.g., binding pockets of SPI1, ELF2, and RUNX1), with late-stage AD exhibiting epigenomic erosion that leads to loss of cellular identity [247].”
Age‐Associated Transcriptomic and Epigenetic Alterations in Mouse Hippocampus
Bilgic, M., Obata, R., Panfil, V., Zhu, Z., Saeki, M., Gotoh, Y., & Kishi, Y. (2025) · Aging Cell · doi:10.1111/acel.70233 · Cited by 5 · see citing works
“Many studies identified the specific molecular state of microglia, immune residents in the brain, in normal aging and in AD conditions in mice and humans (Li et al. 2023; Xiong et al. 2023; Sun et al. 2023; Lopes et al. 2022).”
Katbe, A., Hanna, R., Flamier, A., Serhani, D., Hamam, R., Barabino, A., Tavares, E. S., Héon, E., & Bernier, G. (2025) · Development · doi:10.1242/dev.204910 · Cited by 3 · see citing works
Egervári, G., Alexander, D. C., Huang, H., Donahue, G., Hogan, C., Mendoza, M. R., Xu, H. W., Lee, V., Garcia, B. A., Bonini, N. M., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.70998 · Cited by 3 · see citing works
FAM134B-mediated ER-phagy degrades APP and suppresses Alzheimer’s disease pathology
Zhang, Y., Sun, J., Cai, Y., Xu, Z., Li, X., Wei, W., Liu, P., Sun, Q., Wang, Z.-H., & Cui, Y. (2026) · The EMBO Journal · doi:10.1038/s44318-026-00818-9 · Cited by 3 · see citing works
“For ATAC-seq enrichment analysis of cortical tissue from AD cases in the Synapse database (dataset syn52293424 (Xiong et al, 2023)), data were processed using the Seurat, SingleCellExperiment, and GenomicRanges R packages.”
Omics-driven strategies for identifying biomarkers in Alzheimer’s disease
Khan, Y., Rekha, A., Ballal, S., Maharana, L., Maqbool, M., Goyal, K., Mishra, R., Uniyal, P., Alam, P., Aljarba, T. M., et al. (2026) · Metabolic Brain Disease · doi:10.1007/s11011-026-01873-1 · Cited by 3 · see citing works
“The late AD human brains exhibited widespread epigenomic mis-regulation with erosion of enhancers and loss of cell identity (Xiong et al. 2023).”
Li, M., Su, Y., Gao, Y.-B., & Tian, W. (2024) · Briefings Bioinform. · doi:10.1093/bib/bbae422 · Cited by 4 · see citing works
Genetic architecture of postpartum psychosis: from common to rare genetic variation
Jung, S., Caballero, M., Kępińska, A. P., Smout, S., Munk‐Olsen, T., Robakis, T. K., Bergink, V., & Mahjani, B. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03637-w · Cited by 3 · see citing works
The impact of genetic variability on Alzheimer’s therapies: obstacles for pharmacogenetic progress
Cacabelos, R., Martínez-Iglesias, O. A., Cacabelos, N., Carrera, J., Rodríguez, D., & Naidoo, V. (2025) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1080/17425255.2024.2433626 · Cited by 4 · see citing works
Single-cell multiplex chromatin and RNA interactions in aging human brainPreprint
Wen, X., Luo, Z., Zhao, W., Calandrelli, R., Nguyen, T. C., Wan, X., Richard, J. L. C., & Zhong, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.28.546457 · Cited by 3 · see citing works
“These data are reminiscent of the recent report on the association of a global epigenome dysregulation and AD 43 .”
Zhao, Z., Liu, A., Citu, C., Enduru, N., Chen, X., Manuel, A. M., Sinha, T., Gorski, D., Fernandes, B. S., Yu, M., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4622123/v1 · Cited by 3 · see citing works
Liu, Q., Zeng, W., Hongtu Zhu, B., Li, L., Wong, W. H., & Initiative, A. D. N. (2024) · medRxiv · doi:10.1101/2024.10.03.24314824 · Cited by 3 · see citing works
- 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 · 2022: 1
- 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
- Health Sciences › Medicine › Physiology › 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
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