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Molecular and functional signatures in a novel Alzheimer’s disease mouse model assessed by quantitative proteomics
Open accessAbstract
Alzheimer’s disease (AD), the most common neurodegenerative disorder, is characterized by the deposition of extracellular amyloid plaques and intracellular neurofibrillary tangles. To understand the pathological mechanisms underlying AD, developing animal models that completely encompass the main features of AD pathologies is indispensable. Although mouse models that display pathological hallmarks of AD (amyloid plaques, neurofibrillary tangles, or both) have been developed and investigated, a systematic approach for understanding the molecular characteristics of AD mouse models is lacking. To elucidate the mechanisms underlying the contribution of amyloid beta (Aβ) and tau in AD pathogenesis, we herein generated a novel animal model of AD, namely the AD-like pathology with amyloid and neurofibrillary tangles (ADLP APT ) mice. The ADLP APT mice carry three human transgenes, including amyloid precursor protein, presenilin-1, and tau, with six mutations. To characterize the molecular and functional signatures of AD in ADLP APT mice, we analyzed the hippocampal proteome and performed comparisons with individual-pathology transgenic mice (i.e., amyloid or neurofibrillary tangles) and wild-type mice using quantitative proteomics with 10-plex tandem mass tag. The ADLP APT mice exhibited accelerated neurofibrillary tangle formation in addition to amyloid plaques, neuronal loss in the CA1 area, and memory deficit at an early age. In addition, our proteomic analysis identified nearly 10,000 protein groups, which enabled the identification of hundreds of differentially expressed proteins (DEPs) in ADLP APT mice. Bioinformatics analysis of DEPs revealed that ADLP APT mice experienced age-dependent active immune responses and synaptic dysfunctions. Our study is the first to compare and describe the proteomic characteristics in amyloid and neurofibrillary tangle pathologies using isobaric label-based quantitative proteomics. Furthermore, we analyzed the hippocampal proteome of the newly developed ADLP APT model mice to investigate how both Aβ and tau pathologies regulate the hippocampal proteome. Because the ADLP APT mouse model recapitulates the main features of AD pathogenesis, the proteomic data derived from its hippocampus has significant utility as a novel resource for the research on the Aβ-tau axis and pathophysiological changes in vivo.
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“The ADLPAPT mice carry six human mutations affecting amyloid precursor protein, presenilin-1, and tau protein, and develop an AD-like pathology with amyloid and neurofibrillary tangles (167).”
From The gut-brain axis: how microbiota and host inflammasome influence brain physiology and pathology (2020) · cites this paper as [167]
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“The ADLPAPT mice carry six human mutations affecting amyloid precursor protein, presenilin-1, and tau protein, and develop an AD-like pathology with amyloid and neurofibrillary tangles (167).”
From The gut-brain axis: how microbiota and host inflammasome influence brain physiology and pathology (2020) · cites this paper as [167]
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
STRING v10: protein–protein interaction networks, integrated over the tree of life
Szklarczyk, D., Franceschini, A., Wyder, S., Forslund, K., Heller, D., Huerta-Cepas, J., Simonovic, M., Roth, A., Santos, A., Tsafou, K. P., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1003 · Cited by 10,436
Amyloid oligomers exacerbate tau pathology in a mouse model of tauopathy
Selenica, M.-L. B., Brownlow, M., Jimenez, J. P., Lee, D. C., Pena, G., Dickey, C. A., Gordon, M. N., & Morgan, D. (2013) · Neurodegenerative Diseases · doi:10.1159/000337230 · Cited by 10,359
The Perseus computational platform for comprehensive analysis of (prote)omics data
Tyanova, S., Temu, T., Sinitcyn, P., Carlson, A., Hein, M. Y., Geiger, T., Mann, M., & Cox, J. (2016) · Nature Methods · doi:10.1038/nmeth.3901 · Cited by 8,803
Universal sample preparation method for proteome analysis
Wiśniewski, J. R., Zougman, A., Nagaraj, N., & Mann, M. (2009) · Nature Methods · doi:10.1038/nmeth.1322 · Cited by 8,352
Causal analysis approaches in Ingenuity Pathway Analysis
Krämer, A., Green, J., Pollard, J., & Tugendreich, S. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt703 · Cited by 5,724
Triple-Transgenic Model of Alzheimer’s Disease with Plaques and Tangles
Oddo, S., Caccamo, A., Shepherd, J. D., Murphy, M. P., Golde, T. E., Kayed, R., Metherate, R., Mattson, M. P., Akbari, Y., & LaFerla, F. M. (2003) · Neuron · doi:10.1016/s0896-6273(03)00434-3 · Cited by 4,126
Research works printed but not linked: 1
- Han D, Moon S, Kim Y, Kim J, Jin J, Kim Y. In-depth proteomic analysis of mouse microglia using a combination of FASP and StageTip-based, high pH, reversed-phase fractionation. Proteomics. 2013;13:2984–8.
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Rutsch, A., Kantsjö, J. B., & Ronchi, F. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.604179 · Cited by 821
Kim, M.-S., Kim, Y., Choi, H., Kim, W., Park, S., Lee, D., Kim, D. K., Kim, H. J., Choi, H., Hyun, D.-W., et al. (2020) · Gut · doi:10.1136/gutjnl-2018-317431 · Cited by 614
Fang, J., Zhang, P., Zhou, Y., Chiang, C.-W., Tan, J., Hou, Y., Stauffer, S., Li, L., Pieper, A. A., Cummings, J., et al. (2021) · Nature Aging · doi:10.1038/s43587-021-00138-z · Cited by 206
Fang, J., Zhang, P., Wang, Q., Chiang, C.-W., Zhou, Y., Hou, Y., Xu, J., Chen, R., Zhang, B., Lewis, S. J., et al. (2022) · Alzheimer's Research & Therapy · doi:10.1186/s13195-021-00951-z · Cited by 140
Transgenic Mouse Models of Alzheimer’s Disease: An Integrative Analysis
Sanchez-Varo, R. M., Mejias‐Ortega, M., Fernandez-Valenzuela, J. J., Nuñez‐Diaz, C., Cáceres-Palomo, L., Vegas‐Gomez, L., Sánchez‐Mejías, E., Trujillo‐Estrada, L., García‐León, J. A., Moreno‐González, I., et al. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23105404 · Cited by 136
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Choi, H., Kim, H. J., Yang, J., Chae, S., Lee, W., Chung, S., Kim, J., Choi, H., Song, H., Lee, C. K., et al. (2019) · Aging Cell · doi:10.1111/acel.13081 · Cited by 124
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You, L., Yang, C., Du, Y., Wang, W., Sun, M., Liu, J., Ma, B., Pang, L., Zeng, Y., Zhang, Z., et al. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.01067 · Cited by 119
Xu, J., Mao, C., Hou, Y., Luo, Y., Binder, J. L., Zhou, Y., Bekris, L. M., Shin, J., Hu, M., Wang, F., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111717 · Cited by 115
Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing
Fang, J., Pieper, A. A., Nussinov, R., Lee, G., Bekris, L. M., Leverenz, J. B., Cummings, J. L., & Cheng, F. (2020) · Medicinal Research Reviews · doi:10.1002/med.21709 · Cited by 96
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Jung, E. S., Suh, K., Han, J., Kim, H., Kang, H., Choi, W., & Mook‐Jung, I. (2022) · Aging Cell · doi:10.1111/acel.13623 · Cited by 97
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Zheng, Q., Li, G., Wang, S., Zhou, Y., Liu, K., Gao, Y., Zhou, Y., Zheng, L., Zhu, L., Deng, Q., et al. (2021) · Science Advances · doi:10.1126/sciadv.abe1340 · Cited by 85
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Tang, B. L. (2020) · Toxics · doi:10.3390/toxics8020021 · Cited by 84
Rayaprolu, S., Gao, T., Xiao, H., Ramesha, S., Weinstock, L. D., Shah, J., Duong, D. M., Dammer, E. B., Webster, J. A., Lah, J. J., et al. (2019) · doi:10.1101/802694 · Cited by 71
Mendonça, C. F., Kuras, M., Nogueira, F. C. S., Plá, I., Hortobágyi, T., Csiba, L., Palkovits, M., Renner, É., Döme, P., Marko‐Varga, G., et al. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104509 · Cited by 69
Lei, W., Cheng, Y., Liu, X., Gao, J., Zhu, Z., Ding, W., Xu, X., Li, Y., Ling, Z., Jiang, R., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1582119 · Cited by 68
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Nguyen, V. T. T., & Endres, K. (2022) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2022.114418 · Cited by 52
Song, H., Chen, M., Chen, C., Cui, J., Johnson, C. E., Cheng, J. J., Wang, X., Swerdlow, R. H., DePalma, R. G., Xia, W., et al. (2018) · Journal of Neurotrauma · doi:10.1089/neu.2018.6114 · Cited by 47
Gupta, R., Min, C. W., Kim, Y., & Kim, S. T. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20174135 · Cited by 38
Castro-Ochoa, K. F., Guerrero-Fonseca, I. M., & Schnoor, M. (2018) · Journal of Leukocyte Biology · doi:10.1002/jlb.mr0618-212r · Cited by 35
Concepts and strategies of soybean seed proteomics using the shotgun proteomics approach
Min, C. W., Gupta, R., Agrawal, G. K., Rakwal, R., & Kim, S. T. (2019) · Expert Review of Proteomics · doi:10.1080/14789450.2019.1654860 · Cited by 31
Xue-ju, Z., Liu, W., Cao, Y. W., & Tan, W. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00255 · Cited by 33
Min, C. W., Hyeon, H., Gupta, R., Park, J., Cheon, Y. E., Lee, G., Jang, J. W., Ryu, H. W., Lee, B. W., Park, S. U., et al. (2020) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.0c00986 · Cited by 31
Shin, D., Park, J., Han, D., Moon, J. H., Ryu, H. S., & Kim, Y. (2020) · Clinical Proteomics · doi:10.1186/s12014-020-09280-z · Cited by 25
Min, C. W., Park, J., Bae, J., Agrawal, G. K., Rakwal, R., Kim, Y., Yang, P., Kim, S. T., & Gupta, R. (2020) · Cells · doi:10.3390/cells9061517 · Cited by 25
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Qin, T., Prins, S., Groeneveld, G. J., van Westen, G. J. P., de Vries, H. E., Wong, Y. C., Bischoff, L. J. M., & de Lange, E. C. M. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21093158 · Cited by 24
Gut Microbiota as a Hidden Player in the Pathogenesis of Alzheimer’s Disease
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Pauls, E., Bayod, S., Mateo, L., Alcalde, V., Juan-Blanco, T., Sánchez‐Soto, M., Saido, T. C., Saito, T., Berenguer, A., Attolini, C. S., et al. (2021) · Genome Medicine · doi:10.1186/s13073-021-00983-y · Cited by 23
Oh, H., Min, U.-G., Jang, H.-J., Kim, N., Lim, J., Chalita, M., & Chun, J. (2022) · The Journal of Microbiology · doi:10.1007/s12275-022-1526-0 · Cited by 22
Min, C. W., Jang, J. W., Lee, G., Gupta, R., Yoon, J., Park, H. J., Cho, H. S., Park, S. R., Kwon, S., Cho, L., et al. (2022) · Journal of Proteomics · doi:10.1016/j.jprot.2022.104687 · Cited by 20
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MacDonald, M. L., Favo, D., Garver, M. E., Sun, Z., Arion, D., Ding, Y., Yates, N. A., Sweet, R. A., & Lewis, D. A. (2018) · Neuropsychopharmacology · doi:10.1038/s41386-018-0260-0 · Cited by 20
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Chung, S., Yang, J., Kim, H. J., Hwang, E. M., Lee, W., Suh, K. Y., Choi, H., & Mook‐Jung, I. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102075 · Cited by 17
Wu, D., Yu, N., Gao, Y., Xiong, R., Liu, L., Lei, H., Jin, S., Liu, J., Liu, Y., Xie, J., et al. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00614-7 · Cited by 17
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Bisogno, T., Lauritano, A., & Piscitelli, F. (2021) · Life · doi:10.3390/life11090934 · Cited by 16
Zhao, T., Zeng, J., Zhang, R., Fan, W., Guan, Q., Wang, H., Pu, L., Jiang, Y., Yang, H., Wang, X., et al. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00885 · Cited by 15
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Wang, G., Shen, X., Song, X., Wang, N., Wo, X., & Gao, Y. (2023) · NeuroToxicology · doi:10.1016/j.neuro.2022.12.011 · Cited by 14
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Hippocampal complement C3 might contribute to cognitive impairment induced by anesthesia and surgery
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Nguyen, T. V., Gupta, R., Annas, D., Yoon, J., Kim, Y., Lee, G., Jang, J. W., Park, K. H., Rakwal, R., Jung, K., et al. (2021) · Frontiers in Plant Science · doi:10.3389/fpls.2021.723369 · Cited by 9
Xia, P., Chen, J., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · BMC Neurology · doi:10.1186/s12883-022-02724-z · Cited by 8
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Luo, R., Kang, Y., Ma, H., Zhang, Z., Hölscher, C., Li, H., & Zhang, Z. (2025) · International Immunopharmacology · doi:10.1016/j.intimp.2025.114612 · Cited by 7
Radford‐Smith, D. E., Oke, K., Costa, C. F. F. A., & Anthony, D. C. (2025) · Brain Behavior & Immunity - Health · doi:10.1016/j.bbih.2025.101013 · Cited by 8
Park, J., Lee, S. H., Shin, D., Kim, Y., Kim, Y. S., Seong, M. Y., Lee, J. J., Seo, H. G., Cho, W., Ro, Y. S., et al. (2023) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00544 · Cited by 6
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Shibato, J., Takenoya, F., Yamashita, M., Gupta, R., Min, C. W., Kim, S. T., Kimura, A., Takasaki, I., Hori, M., Shioda, S., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24044169 · Cited by 6
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Shibato, J., Takenoya, F., Kimura, A., Min, C. W., Yamashita, M., Gupta, R., Kim, S. T., Rakwal, R., & Shioda, S. (2023) · Molecules · doi:10.3390/molecules28041565 · Cited by 4
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Xu, J., Hou, Y., Zhou, Y., Hu, M., & Cheng, F. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.20.465087 · Cited by 4
Choi, H., Hong, S. B., Kim, Y., Joung, H., Choi, Y., Cha, J., Park, J. Y., Lee, Y.-S., Choi, H., Han, J. W., et al. (2026) · Journal of Neuroinflammation · doi:10.1186/s12974-026-03796-1 · Cited by 3
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Jung, E. S., & Mook‐Jung, I. (2024) · Springer eBooks · doi:10.1007/978-981-97-0130-8_24 · Cited by 1
Xia, P., Chen, J., Bai, X., Li, M., Wang, L., & Lu, Z. (2021) · Research Square · doi:10.21203/rs.3.rs-997410/v1 · Cited by 1
Immunopharmacology of Alzheimer’s disease
Nissar, K., Firdous, P., Ali, S., & Hussain, A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-90053-9.00014-2
Protective mechanism of gold nanoparticles on human neural stem cells injured by β-amyloid proteinPreprint
Wang, G., Shen, X., Song, X., Wang, N., Wo, X., & Gao, Y. (2022) · Research Square · doi:10.21203/rs.3.rs-1453537/v1
Xia, P., Chen, J., Bai, X., Li, M., Wang, L., & Lu, Z. (2021) · Research Square · doi:10.21203/rs.3.rs-997410/v2
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Beraldo, I. J. S., Rodrigues, M. P., Polanczyk, R. S., Verano‐Braga, T., & Lopes‐Aguiar, C. (2024) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-50624-6_7
Xia, P., Chen, J. W., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19933005
Xia, P., Chen, J. W., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932978
Xia, P., Chen, J. W., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19933002
Xia, P., Chen, J. W., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932999
Xia, P., Chen, J. W., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932993
Xia, P., Chen, J. W., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932996
Wu, D., Yu, N., Gao, Y., Xiong, R., Liu, L., Lei, H., Jin, S., Liu, J., Liu, Y., Xie, J., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22637926
Xia, P., Chen, J., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932990
Pauls, E., Bayod, S., Mateo, L., Alcalde, V., Juan-Blanco, T., Sánchez‐Soto, M., Saido, T. C., Saito, T., Berrenguer-Llergo, A., Attolini, C. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16880438
Wu, D., Yu, N., Gao, Y., Xiong, R., Liu, L., Lei, H., Jin, S., Liu, J., Liu, Y., Xie, J., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22637923
Xia, P., Chen, J., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932984
Wu, D., Yu, N., Gao, Y., Xiong, R., Liu, L., Lei, H., Jin, S., Liu, J., Liu, Y., Xie, J., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22637920
Xia, P., Chen, J., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932981
Xia, P., Chen, J., Bai, X., Li, M., Wang, L., & Lu, Z. (2022) · Figshare · doi:10.6084/m9.figshare.19932987
Metadata
- Authors
- Kim, D. K., Park, J., Han, D., Yang, J., Kim, A., Woo, J., Kim, Y., & Mook-Jung, I.
- Affiliations
- Seoul National University (KR)
- Corresponding author
- Kim, Youngsoo
- Venue
- Molecular Neurodegeneration
- Published
- 2018-01-16
- Volume
- 13
- Issue
- 1
- Pages
- 2-2
- ISSN
- 1750-1326 (ISSN-L)
- PMC
- PMC5771139
- OpenAlex
- W2782632913
- Cited by
- 95
- References
- 78
- Citations by year
- 2026: 2 · 2025: 11 · 2024: 11 · 2023: 10 · 2022: 19 · 2021: 14 · 2020: 16 · 2019: 9 · 2018: 3
- FWCI
- 7.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Molecular Neurodegeneration (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Research Foundation of Korea (2011-0030738, 2017M3C9A5031597, 2011-0030740, 2015R1A2A1A05001794, 2014M3C7A1046047, 2015M3C7A1028790)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, amyloid plaques, neurofibrillary tangles, amyloid-beta, tau protein, hippocampal proteome, differentially expressed proteins, synaptic dysfunction, neuroinflammation, memory impairment, transgenic mouse model
- MeSH terms
- Alzheimer Disease, Animals, Disease Models, Animal, Hippocampus, Humans, Mice, Transgenic, Mutation, Amyloid beta-Protein Precursor, tau Proteins, Transgenes, Proteomics, Mice, Presenilin-1
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