The DOI matches its Crossref record; 34 of the 35 references it cites were found in a registry or an index.
Gene expression correlates of neurofibrillary tangles in Alzheimer's disease
Open accessAbstract
Neurofibrillary tangles (NFT) constitute one of the cardinal histopathological features of Alzheimer's disease (AD). To explore in vivo molecular processes involved in the development of NFTs, we compared gene expression profiles of NFT-bearing entorhinal cortex neurons from 19 AD patients, adjacent non-NFT-bearing entorhinal cortex neurons from the same patients, and non-NFT-bearing entorhinal cortex neurons from 14 non-demented, histopathologically normal controls (ND). Of the differentially expressed genes, 225 showed progressively increased expression (AD NFT neurons > AD non-NFT neurons > ND non-NFT neurons) or progressively decreased expression (AD NFT neurons < AD non-NFT neurons < ND non-NFT neurons), raising the possibility that they may be related to the early stages of NFT formation. Immunohistochemical studies confirmed that many of the implicated proteins are dysregulated and preferentially localized to NFTs, including apolipoprotein J, interleukin-1 receptor-associated kinase 1, tissue inhibitor of metalloproteinase 3, and casein kinase 2, beta. Functional validation studies are underway to determine which candidate genes may be causally related to NFT neuropathology, thus providing therapeutic targets for the treatment of AD.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“This dataset was later re‐analyzed to show that neurons with high levels of tau were enriched for signatures of DNA damage and senescence (Dunckley et al, 2006; Musi et al, 2018).”
From Mechanisms of DNA damage-mediated neurotoxicity in neurodegenerative disease (2022) · cites this paper as Dunckley et al, 2006
Citations
Cites
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
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Randomization and Monte Carlo Methods in Biology.
Foutz, R. V., & Manly, B. F. J. (1992) · Journal of the American Statistical Association · doi:10.2307/2290299 · Cited by 1,627
Ebneth, A., Godemann, R., Stamer, K., Illenberger, S., Trinczek, B., Mandelkow, E.-M., & Mandelkow, E. (1998) · The Journal of Cell Biology · doi:10.1083/jcb.143.3.777 · Cited by 820
Oddo, S., Billings, L., Kesslak, J. P., Cribbs, D. H., & LaFerla, F. M. (2004) · Neuron · doi:10.1016/j.neuron.2004.07.003 · Cited by 780
Inhibition of neurite polarity by tau antisense oligonucleotides in primary cerebellar neurons
Cáceres, A., & Kosik, K. S. (1990) · Nature · doi:10.1038/343461a0 · Cited by 656
Li, Y., Liu, L., Barger, S. W., & Griffin, W. S. T. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-05-01605.2003 · Cited by 563
The calpain family and human disease
Huang, Y., & Wang, K. (2001) · Trends in Molecular Medicine · doi:10.1016/s1471-4914(01)02049-4 · Cited by 480
DeMattos, R. B., O'dell, M. A., Parsadanian, M., Taylor, J. W., Harmony, J. A. K., Bales, K. R., Paul, S. M., Aronow, B. J., & Holtzman, D. M. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.162228299 · Cited by 359
Backstrom, J. R., Lim, G. P., Cullen, M. J., & Tökés, Z. A. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-24-07910.1996 · Cited by 331 · cited 1×
“Further, matrix metalloproteinase 9, which is a target of TIMP inhibition, has been reported to be upregulated in plasma of AD patients [23] and has been implicated in the degradation of toxic β-amyloid species [2].”
Background
Cited by
Sorted by citations
Liang, W. S., Reiman, E. M., Valla, J., Dunckley, T., Beach, T. G., Grover, A., Niedzielko, T. L., Schneider, L. E., Mastroeni, D., Caselli, R., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709259105 · Cited by 585
Self-citationTau protein aggregation is associated with cellular senescence in the brain
Musi, N., Valentine, J. M., Sickora, K. R., Baeuerle, E., Thompson, C. S., Shen, Q., & Orr, M. E. (2018) · Aging Cell · doi:10.1111/acel.12840 · Cited by 595
Arizona Study of Aging and Neurodegenerative Disorders and Brain and Body Donation Program
Beach, T. G., Adler, C. H., Sue, L. I., Serrano, G., Shill, H. A., Walker, D. G., Lue, L., Roher, A. E., Dugger, B. N., Maarouf, C., et al. (2015) · Neuropathology · doi:10.1111/neup.12189 · Cited by 460
Self-citationEpigenetic changes in Alzheimer's disease: Decrements in DNA methylation
Mastroeni, D., Grover, A., Delvaux, E., Whiteside, C. M., Coleman, P. D., & Rogers, J. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.12.005 · Cited by 401
Self-citationClusterin in Alzheimer’s Disease: Mechanisms, Genetics, and Lessons From Other Pathologies
Foster, E. M., Dangla-Valls, A., Lovestone, S., Ribe, E. M., & Buckley, N. J. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00164 · Cited by 381
Liang, W. S., Dunckley, T., Beach, T. G., Grover, A., Mastroeni, D., Ramsey, K., Caselli, R. J., Kukull, W. A., McKeel, D., Morris, J. C., et al. (2008) · Physiological Genomics · doi:10.1152/physiolgenomics.00242.2007 · Cited by 309
Self-citationXu, M., Zhang, D., Luo, R., Wu, Y., Zhou, H., Kong, L., Bi, R., & Yao, Y. (2017) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2017.08.012 · Cited by 296
Alzheimer disease, the two-hit hypothesis: An update
Zhu, X., Lee, H., Perry, G. L., & Smith, M. A. (2006) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2006.10.014 · Cited by 299
Genes and pathways underlying regional and cell type changes in Alzheimer’s disease
Miller, J. A., Woltjer, R. L., Goodenbour, J. M., Horvath, S., & Geschwind, D. H. (2013) · Genome Medicine · doi:10.1186/gm452 · Cited by 275
Molecular signatures underlying neurofibrillary tangle susceptibility in Alzheimer’s disease
Otero-Garcia, M., Mahajani, S. U., Wakhloo, D., Tang, W., Xue, Y.-Q., Morabito, S., Pan, J., Oberhauser, J., Madira, A. E., Shakouri, T., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.06.021 · Cited by 262
Sodium Channel β Subunits: Emerging Targets in Channelopathies
O’Malley, H. A., & Isom, L. L. (2015) · Annual Review of Physiology · doi:10.1146/annurev-physiol-021014-071846 · Cited by 247
Gene expression profiling in human neurodegenerative disease
Cooper‐Knock, J., Kirby, J., Ferraiuolo, L., Heath, P. R., Rattray, M., & Shaw, P. J. (2012) · Nature Reviews Neurology · doi:10.1038/nrneurol.2012.156 · Cited by 229
Stranahan, A. M., & Mattson, M. P. (2010) · Neural Plasticity · doi:10.1155/2010/108190 · Cited by 198
“In contrast, tangle-bearing neurons in layer II of the AD entorhinal cortex show increased expression of apolipoprotein-J and tissue inhibitor of metalloproteinase3, relative to non-tanglebearing neurons [36].”
BackgroundEpigenetic changes in the progression of Alzheimer's disease
Bradley‐Whitman, M. A., & Lovell, M. A. (2013) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2013.08.005 · Cited by 198
Selective Neuronal Vulnerability in Alzheimer’s Disease: A Network-Based Analysis
Roussarie, J.-P., Yao, V., Rodriguez-Rodriguez, P., Oughtred, R., Rust, J., Plautz, Z., Kasturia, S., Albornoz, C., Wang, W., Schmidt, E. F., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.06.010 · Cited by 180
Profiling senescent cells in human brains reveals neurons with CDKN2D/p19 and tau neuropathology
Dehkordi, S. K., Walker, J., Sah, E., Bennett, E., Atrian, F., Frost, B., Woost, B., Bennett, R. E., Orr, T. C., Zhou, Y., et al. (2021) · Nature Aging · doi:10.1038/s43587-021-00142-3 · Cited by 169
Wes, P. D., Holtman, I. R., Boddeke, E. W. G. M., Möller, T., & Eggen, B. J. L. (2016) · Glia · doi:10.1002/glia.22866 · Cited by 167
Johnson, S. C., Schmitz, T. W., Trivedi, M. A., Ries, M. L., Torgerson, B. M., Carlsson, C. M., Asthana, S., Hermann, B. P., & Sager, M. A. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.0959-06.2006 · Cited by 154
Rahman, M. R., Islam, T., Zaman, T., Shahjaman, M., Karim, M. R., Huq, F., Quinn, J. M. W., Holsinger, R. M. D., Gov, E., & Moni, M. A. (2020) · Genomics · doi:10.1016/j.ygeno.2019.07.018 · Cited by 136
Mechanisms of DNA damage-mediated neurotoxicity in neurodegenerative disease
Welch, G., & Tsai, L. (2022) · The EMBO Reports · doi:10.15252/embr.202154217 · Cited by 129
Kamal, M. S., Northcote, A., Chowdhury, L., Dey, N., Crespo, R. A. G., & Herrera‐Viedma, E. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3107056 · Cited by 131
Ray, M., Ruan, J., & Zhang, W. (2008) · Genome Biology · doi:10.1186/gb-2008-9-10-r148 · Cited by 119
Rahman, M. R., Islam, T., Turanlı, B., Zaman, T., Faruquee, H. M., Rahman, M. M., Mollah, M. N. H., Nanda, R. K., Arğa, K. Y., Göv, E., et al. (2018) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2018.12.011 · Cited by 118
Evidence for an association between KIBRA and late-onset Alzheimer's disease
Corneveaux, J. J., Liang, W. S., Reiman, E. M., Webster, J., Myers, A., Zismann, V., Joshipura, K. D., Pearson, J. V., Hu‐Lince, D., Craig, D. W., et al. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.07.014 · Cited by 112
Self-citationRivera, S., García-González, L., Khrestchatisky, M., & Baranger, K. (2019) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-019-03178-2 · Cited by 111
Voltage-Gated Sodium Channel β Subunits and Their Related Diseases
Bouza, A. A., & Isom, L. L. (2017) · Handbook of experimental pharmacology · doi:10.1007/164_2017_48 · Cited by 111
Genetics, Transcriptomics, and Proteomics of Alzheimers Disease
Papassotiropoulos, A., Fountoulakis, M., Dunckley, T. L., Stephan, D. A., & Reiman, E. M. (2006) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v67n0418 · Cited by 105
Self-citationCholinotrophic Molecular Substrates of Mild Cognitive Impairment in the Elderly
Mufson, E. J., Counts, S., Fahnestock, M. L., & Ginsberg, S. D. (2007) · Current Alzheimer Research · doi:10.2174/156720507781788855 · Cited by 100
Analysis of microRNA and Gene Expression Profiles in Alzheimer’s Disease: A Meta-Analysis Approach
Moradifard, S., Hoseinbeyki, M., Ganji, S. M., & Minuchehr, Z. (2018) · Scientific Reports · doi:10.1038/s41598-018-20959-0 · Cited by 106
Signal Transduction Cascades Associated with Oxidative Stress in Alzheimer's Disease
Petersen, R. B., Nunomura, A., Lee, H., Casadesús, G., Perry, G. L., Smith, M. A., & Zhu, X. (2007) · Journal of Alzheimer s Disease · doi:10.3233/jad-2007-11202 · Cited by 101
Antonell, A., Lladó, A., Altirriba, J., Botta‐Orfila, T., Balasa, M., Fernández, M., Ferrer, I., Sánchez‐Valle, R., & Molinuevo, J. L. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.12.026 · Cited by 101
Concerted Perturbation Observed in a Hub Network in Alzheimer’s Disease
Liang, D., Han, G., Feng, X., Sun, J., Duan, Y., & Lei, H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040498 · Cited by 93
Ma, X., Liu, L., & Meng, J. (2017) · Neuroscience Letters · doi:10.1016/j.neulet.2017.09.043 · Cited by 91
Retractedc‐Jun phosphorylation in Alzheimer disease
Thakur, A., Wang, X., Siedlak, S. L., Perry, G. L., Smith, M. A., & Zhu, X. (2007) · Journal of Neuroscience Research · doi:10.1002/jnr.21298 · Cited by 80
Cerebrovascular Senescence Is Associated With Tau Pathology in Alzheimer's Disease
Bryant, A. G., Hu, M., Carlyle, B. C., Arnold, S. E., Frosch, M. P., Das, S., Hyman, B. T., & Bennett, R. E. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.575953 · Cited by 79
Transcriptomics in Alzheimer’s Disease: Aspects and Challenges
Bagyinszky, E., Giau, V. V., & An, S. A. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21103517 · Cited by 75
MAPT Isoforms: Differential Transcriptional Profiles Related to 3R and 4R Splice Variants
Chen, S., Townsend, K. P., Goldberg, T. E., Davies, P., & Conejero‐Goldberg, C. (2011) · Journal of Alzheimer s Disease · doi:10.3233/jad-2010-101155 · Cited by 81
Genetic study of multimodal imaging Alzheimer’s disease progression score implicates novel loci
Scelsi, M. A., Khan, R. R., Lorenzi, M., Christopher, L., Greicius, M. D., Schott, J. M., Ourselin, S., & Altmann, A. (2018) · Brain · doi:10.1093/brain/awy141 · Cited by 73
Prasad, H., & Rao, R. (2015) · Journal of Biological Chemistry · doi:10.1074/jbc.m114.602219 · Cited by 76
CFH Variants Affect Structural and Functional Brain Changes and Genetic Risk of Alzheimer’s Disease
Initiative, A. D. N., Zhang, D., Li, J., Wu, H., Cui, Y. J., Bi, R., Zhou, H., Wang, H.-Z., Zhang, C., Wang, D., et al. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.232 · Cited by 73
Talwar, P., Sinha, J., Grover, S., Rawat, C., Kushwaha, S. S., Agarwal, R., Taneja, V., & Kukreti, R. (2015) · Molecular Neurobiology · doi:10.1007/s12035-015-9390-0 · Cited by 71
Sutherland, G. T., Janitz, M., & Kril, J. J. (2010) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2010.07157.x · Cited by 67
Gene expression reveals overlap between normal aging and Alzheimer's disease genes
Avramopoulos, D., Szymanski, M., Wang, R., & Bassett, S. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.019 · Cited by 67
Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale
Ruffini, N., Klingenberg, S., Schweiger, S., & Gerber, S. (2020) · Cells · doi:10.3390/cells9122642 · Cited by 67
Genes associated with the progression of neurofibrillary tangles in Alzheimer’s disease
Miyashita, A., Hatsuta, H., Kikuchi, M., Nakaya, A., Saito, Y., Tsukie, T., Hara, N., Ogishima, S., Kitamura, N., Akazawa, K., et al. (2014) · Translational Psychiatry · doi:10.1038/tp.2014.35 · Cited by 65
Postmortem Delay Has Minimal Effect on Brain RNA Integrity
Ervin, J. F., Heinzen, E. L., Cronin, K. D., Goldstein, D. B., Szymanski, M. H., Burke, J. R., Welsh-Bohmer, K. A., & Hulette, C. M. (2007) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e31815c196a · Cited by 63
Self-citationA computational framework for the prioritization of disease-gene candidates
Browne, F., Wang, H., & Zheng, H. (2015) · BMC Genomics · doi:10.1186/1471-2164-16-s9-s2 · Cited by 61
Walker, J. M., Kazempour Dehkordi, S., Fracassi, A., Vanschoiack, A., Pavenko, A., Taglialatela, G., Woltjer, R., Richardson, T. E., Zare, H., & Orr, M. E. (2022) · Acta Neuropathologica Communications · doi:10.1186/s40478-022-01324-9 · Cited by 59
INTERSECTINg Pathways in Cell Biology
O’Bryan, J. P. (2010) · Science Signaling · doi:10.1126/scisignal.3152re10 · Cited by 65
Conejero‐Goldberg, C., Hyde, T. M., Chen, S., Dreses‐Werringloer, U., Herman, M. M., Kleinman, J. E., Davies, P., & Goldberg, T. E. (2010) · Molecular Psychiatry · doi:10.1038/mp.2010.57 · Cited by 56
Do Epigenetic Pathways Initiate Late Onset Alzheimer Disease (LOAD): Towards a New Paradigm
Bihaqi, S. W., Schumacher, A., Maloney, B., Lahiri, D. K., & Zawia, N. H. (2012) · Current Alzheimer Research · doi:10.2174/156720512800617982 · Cited by 52
Sun, J., Feng, X., Liang, D., Duan, Y., & Lei, H. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-111313 · Cited by 51
Amyloid-β toxicity modulates tau phosphorylation through the PAX6 signalling pathway
Zhang, Y., Zhang, Y., Aman, Y., Ng, C. T., Chau, W. H., Zhang, Z., Yue, M., Böhm, C., Jia, Y., Li, S., et al. (2021) · Brain · doi:10.1093/brain/awab134 · Cited by 47
Wang, L., Chen, X., He, D.-D., Li, Y., & Fu, J. X. (2016) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2016.11.143 · Cited by 48
Emerging Roles for Intersectin (ITSN) in Regulating Signaling and Disease Pathways
Hunter, M. P., Russo, A., & O’Bryan, J. P. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms14047829 · Cited by 47
The Diverse Roles of TIMP-3: Insights into Degenerative Diseases of the Senescent Retina and Brain
Dewing, J. M., Carare, R. O., Lotery, A. J., & Ratnayaka, J. A. (2019) · Cells · doi:10.3390/cells9010039 · Cited by 46
Intersectin scaffold proteins and their role in cell signaling and endocytosis
Herrero-Garcia, E., & O’Bryan, J. P. (2016) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2016.10.005 · Cited by 45
AlzBase: An Integrative Database for Gene Dysregulation in Alzheimer’s Disease
Bai, Z., Han, G., Xie, B., Wang, J., Song, F., Peng, X., & Lei, H. (2016) · Molecular Neurobiology · doi:10.1007/s12035-014-9011-3 · Cited by 44
Neuronal gene expression profiling: uncovering the molecular biology of neurodegenerative disease
Mufson, E. J., Counts, S., Che, S., & Ginsberg, S. D. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)58010-0 · Cited by 40
Zhang, D., Fan, Y., Wang, D., Bi, R., Zhang, C., Fang, Y., & Yao, Y. (2015) · Molecular Neurobiology · doi:10.1007/s12035-015-9353-5 · Cited by 41
Linking Brain Imaging and Genomics in the Study of Alzheimer's Disease and Aging
Reiman, E. M. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1379.011 · Cited by 39
Self-citationDissecting gene expression at the blood-brain barrier
Huntley, M. A., Bien‐Ly, N., Daneman, R., & Watts, R. J. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00355 · Cited by 41
Tiernan, C. T., Ginsberg, S. D., Guillozet-Bongaarts, A. L., Ward, S., He, B., Kanaan, N. M., Mufson, E. J., Binder, L. I., & Counts, S. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.02.031 · Cited by 38
Intersectin 1 contributes to phenotypes in vivo
Hunter, M. P., Nelson, M., Kurzer, M., Wang, X., Kryscio, R. J., Head, E., Pinna, G., & O’Bryan, J. P. (2011) · Neuroreport · doi:10.1097/wnr.0b013e32834ae348 · Cited by 35
Rahman, M. R., Islam, T., Shahjaman, M., Zaman, T., Faruquee, H. M., Jamal, M. A. H. M., Huq, F., Quinn, J. M. W., & Moni, M. A. (2019) · Medicina · doi:10.3390/medicina55050191 · Cited by 35
Hoerndli, F. J., Pelech, S., Papassotiropoulos, A., & Götz, J. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05618.x · Cited by 34
Translational gene mapping of cognitive decline
Wilmot, B., McWeeney, S. K., Nixon, R. R., Montine, T. J., Laut, J., Harrington, C. A., Kaye, J. A., & Kramer, P. L. (2006) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2006.11.008 · Cited by 35
Chowdhury, U. N., Ahmad, S., Islam, M. B., Huq, F., Quinn, J. M. W., & Moni, M. A. (2020) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2020.100309 · Cited by 34
Vavougios, G. D., Nday, C. M., Pelidou, S., Gourgoulianis, K. I., Stamoulis, G. I., Doskas, T. K., & Zarogiannis, S. G. (2021) · Brain Behavior & Immunity - Health · doi:10.1016/j.bbih.2021.100243 · Cited by 33
Chong, M. S., Goh, L. K., Lim, W. S., Chan, M., Tay, L. B. G., Chen, G., Feng, L., Ng, T. P., Tan, C. H., & Lee, T.-S. W. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-121621 · Cited by 32
Liu, L., Wu, Q. J., Zhong, W., Chen, Y., Zhang, W., Ren, H., Sun, L., & Sun, J. (2020) · Medical Science Monitor · doi:10.12659/msm.919249 · Cited by 30
Gillispie, G. J., Sah, E., Krishnamurthy, S., Ahmidouch, M. Y., Zhang, B., & Orr, M. E. (2021) · Life · doi:10.3390/life11020153 · Cited by 31
HYPK coordinates degradation of polyneddylated proteins by autophagy
Ghosh, D. K., & Ranjan, A. (2021) · Autophagy · doi:10.1080/15548627.2021.1997053 · Cited by 31
Selective neuronal vulnerability in Alzheimer’s disease: a network-based analysisPreprint
Roussarie, J.-P., Yao, V., Plautz, Z., Kasturia, S. E., Albornoz, C. A., Schmidt, E. F., Brichta, L., Barnea-Cramer, A. O., Heintz, N., Hof, P. R., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/499897 · Cited by 31
Alshamlan, H., Omar, S., Aljurayyad, R., & Alabduljabbar, R. (2023) · Diagnostics · doi:10.3390/diagnostics13101771 · Cited by 33
A Computational Framework for Genome-wide Characterization of the Human Disease Landscape
Lee, Y.-S., Krishnan, A., Oughtred, R., Rust, J., Chang, C., Ryu, J., Kristensen, V. N., Dolinski, K. J., Theesfeld, C. L., & Troyanskaya, O. G. (2019) · Cell Systems · doi:10.1016/j.cels.2018.12.010 · Cited by 28
Giannos, P., Prokopidis, K., Raleigh, S. M., Kelaiditi, E., & Hill, M. W. (2022) · Scientific Reports · doi:10.1038/s41598-022-15578-9 · Cited by 28
Lee, T.-S. W., Goh, L. K., Chong, M. S., Chua, S. M., Chen, G. B., Feng, L., Lim, W. S., Chan, M., Ng, T. P., & Krishnan, K. (2012) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2012.03.006 · Cited by 27
Martínez-Ballesteros, M., García-Heredia, J. M., Nepomuceno-Chamorro, I. A., & Riquelme, J. C. (2016) · Information Fusion · doi:10.1016/j.inffus.2016.11.005 · Cited by 24
Zhou, Y., Xu, Z., Yu, Y., Cao, J., Qiao, Y., Qiao, H., & Suo, G. (2019) · Molecular Omics · doi:10.1039/c9mo00129h · Cited by 26
Clusterin is a Potential Therapeutic Target in Alzheimer’s Disease
Palihati, N., Tang, Y., Yin, Y., Yu, D., Liu, G., Quan, Z., Ni, J., Yan, Y., & Qing, H. (2023) · Molecular Neurobiology · doi:10.1007/s12035-023-03801-1 · Cited by 25
The Prevalence of Alzheimer's Disease in China: A Systematic Review and Meta-analysis.
Li, K., Wei, S., Liu, Z., Li, H., Lin, J., Tan, S., Mai, Y., Peng, W., Mai, H., Hou, Q., et al. (2018) · Europe PMC (PubMed Central) · Cited by 24
Focusing on cellular biomarkers: The endo-lysosomal pathway in Down syndrome
Botté, A., & Potier, M. (2019) · Progress in brain research · doi:10.1016/bs.pbr.2019.10.002 · Cited by 22
Metabolic regulation of aging and age-related disease
Hamrick, M. W., & Stranahan, A. M. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101175 · Cited by 27
Is Seladin-1 Really a Selective Alzheimer's Disease Indicator?
Sharpe, L. J., Wong, J., Garner, B., Halliday, G. M., & Brown, A. J. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-111955 · Cited by 24
Identification of common molecular biomarker signatures in blood and brain of Alzheimer’s diseasePreprint
Rahman, M. R., Islam, T., Shahjaman, M., Quinn, J. M. W., Holsinger, R. M. D., & Moni, M. A. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/482828 · Cited by 24
Chandrasekaran, S., & Bonchev, D. (2016) · PLoS ONE · doi:10.1371/journal.pone.0144052 · Cited by 24
Kong, W., Mou, X., Zhang, N., Zeng, W., Li, S., & Yang, Y. (2015) · BioMed Research International · doi:10.1155/2015/394260 · Cited by 23
Wruck, W., Schröter, F., & Adjaye, J. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-150733 · Cited by 23
A Selection of Important Genes and Their Correlated Behavior in Alzheimer’s Disease
Cruz-Rivera, Y. E., Pérez‐Morales, J., Santiago, Y. M., Gonzalez, V., Morales, L., Cabrera‐Ríos, M., & Isaza, C. E. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-170799 · Cited by 22
RETRACTED ARTICLE: Exploring the Role of CLU in the Pathogenesis of Alzheimer’s Disease
Uddin, M. S., Kabir, M. T., Begum, M. M., Islam, M. S., Behl, T., & Ashraf, G. M. (2020) · Neurotoxicity Research · doi:10.1007/s12640-020-00271-4 · Cited by 22
RetractedBisht, I., Ambasta, R. K., & Kumar, P. (2020) · Neuropeptides · doi:10.1016/j.npep.2020.102078 · Cited by 20
Sree, G. N. S. H., Rajalekshmi, S. G., & Burri, R. R. (2021) · Journal of Molecular Neuroscience · doi:10.1007/s12031-021-01919-2 · Cited by 19
Sex-specific associations of matrix metalloproteinases in Alzheimer’s disease
Aksnes, M., Edwin, T. H., Saltvedt, I. T., Eldholm, R. S., Chaudhry, F. A., Halaas, N. B., Myrstad, M., Watne, L. O., & Knapskog, A. (2023) · Biology of Sex Differences · doi:10.1186/s13293-023-00514-x · Cited by 20
Hippocampal DHCR24 down regulation in a rat model of streptozotocin-induced cognitive decline
Hosseinzadeh, S., Zahmatkesh, M., Heidari, M., Hassanzadeh, G., Karimian, M., Sarrafnejad, A., & Zarrindast, M. (2014) · Neuroscience Letters · doi:10.1016/j.neulet.2014.12.039 · Cited by 20
Rahman, M. R., Islam, T., Zaman, T., Shahjaman, M., Karim, M. R., Huq, F., Quinn, J. M. W., Holsinger, R. M. D., & Moni, M. A. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/481879 · Cited by 19
Hu, J., Wang, X., Kong, W., & Jiang, Q. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.839622 · Cited by 18
Matrix metalloproteinases are associated with brain atrophy in cognitively unimpaired individuals.
Aksnes, M., Capogna, E., Vidal-Piñeiro, D., Chaudhry, F., Myrstad, M., Idland, A., Halaas, N., Dakhil, S., Blennow, K., Zetterberg, H., et al. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.05.012 · Cited by 16
Minding the Gap: Exploring Neuroinflammatory and Microglial Sex Differences in Alzheimer’s Disease
Reed-Geaghan, E. G., & Keller-Norrell, P. R. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242417377 · Cited by 19
Stein-O’Brien, G., Palaganas, R. G., Meyer, E. M., Redding‐Ochoa, J., Pletniková, O., Guo, H., Bell, W. R., Troncoso, J. C., Huganir, R. L., & Morris, M. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115422 · Cited by 18
Metadata
- Authors
- Dunckley, T., Beach, T. G., Ramsey, K. E., Grover, A., Mastroeni, D., Walker, D. G., LaFleur, B. J., Coon, K. D., Brown, K. M., Caselli, R., Kukull, W., Higdon, R., McKeel, D., Morris, J. C., Hulette, C., Schmechel, D., Reiman, E. M., Rogers, J., & Stephan, D. A.
- Affiliations
- Translational Genomics Research Institute (US)
- Vanderbilt University (US)
- Mayo Clinic (US)
- National Alzheimer's Coordinating Center (US)
- Duke University (US)
- Corresponding author
- Stephan, Dietrich A.
- ORCID
- Venue
- Neurobiology of Aging
- Publisher
- Elsevier BV
- Published
- 2006-10
- Volume
- 27
- Issue
- 10
- Pages
- 1359-1371
- ISSN
- 0197-4580 (ISSN-L)
- PMC
- PMC2259291
- OpenAlex
- W2005889734
- Cited by
- 177
- References
- 35
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 8 · 2023: 14 · 2022: 11 · 2021: 10 · 2020: 15 · 2019: 10 · 2018: 10 · 2017: 5 · 2016: 9 · 2015: 12 · 2014: 10 · 2013: 9 · 2012: 9
- FWCI
- 3.60
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neurobiology of Aging (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (1k01ag024079-01a2)
- National Institute on Aging (P30-AG-19610, AG05 128, R01AG023193, 1-RO1-AG023193, U01AG016976, K01-AG-024079, P50AG005128, P 50 AG05681, P50AG005681, P30AG019610, P01 AG0 3991, P01AG003991)
- 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
- neurofibrillary tangles, Alzheimer's disease, gene expression profiling, differentially expressed genes, clusterin, TIMP-3, casein kinase 2, therapeutic target
- MeSH terms
- Aged, 80 and over, Female, Humans, Male, Nerve Tissue Proteins, Gene Expression, Neurofibrillary Tangles, Entorhinal Cortex, Gene Expression Profiling
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