The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Harnessing Genetic Complexity to Enhance Translatability of Alzheimer’s Disease Mouse Models: A Path toward Precision Medicine
Open accessAbstract
An individual's genetic makeup plays a large role in determining susceptibility to Alzheimer's disease (AD) but has largely been ignored in preclinical studies. To test the hypothesis that incorporating genetic diversity into mouse models of AD would improve translational potential, we combined a well-established mouse model of AD with a genetically diverse reference panel to generate mice that harbor identical high-risk human mutations but differ across the remainder of their genome. We first show that genetic variation profoundly modifies the impact of human AD mutations on both cognitive and pathological phenotypes. We then validate this complex AD model by demonstrating high degrees of genetic, transcriptomic, and phenotypic overlap with human AD. Overall, work here both introduces a novel AD mouse population as an innovative and reproducible resource for the study of mechanisms underlying AD and provides evidence that preclinical models incorporating genetic diversity may better translate to human disease.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“One source of differences may be that most studies have used only the C57BL/6J strain10, known to be relatively resistant to the transgenes effects.”
From Magnetic resonance microscopy maps widespread effects of Alzheimer’s disease on brain structures and behavior in mice (2026) · cites this paper as [10]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“On a positive note, the use of diverse AD-BXD F1 models10 avoids the risk of idiosyncratic effects caused by studying mutations and other transgenes on a single genetic background.”
From Magnetic resonance microscopy maps widespread effects of Alzheimer’s disease on brain structures and behavior in mice (2026) · cites this paper as [10]
The cited source says what the claim attributes to it.
In the citing paper
“The protocol used matches that previously used in the AD-BXD F1s10 83.”
From Magnetic resonance microscopy maps widespread effects of Alzheimer’s disease on brain structures and behavior in mice (2026) · cites this paper as [10]
In the citing paper
“a PRS derived from human LOAD GWAS [96] showed significant association with cognitive outcomes across genetically diverse AD mice at 14 months of age [288]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [288]
In the citing paper
“efforts to expand existing AD mouse models through the inclusion of genetic diversity [288, 289] have resulted in resources that show a more significant overlap with human AD transcriptional profiles than models on a single genetic background [288]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [288]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
Alzheimer's disease: the amyloid cascade hypothesis
Hardy, J. A., & Higgins, G. A. (1992) · Science · doi:10.1126/science.1566067 · Cited by 7,484
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Oakley, H., Cole, S. L., Logan, S., Maus, E., Shao, P., Craft, J., Guillozet-Bongaarts, A., Ohno, M., Disterhoft, J., Van Eldik, L., et al. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1202-06.2006 · Cited by 3,530 · cited 8×
“This panel, which we term the AD-BXDs, combines two well-established resources: (1) the 5XFAD transgenic line on an otherwise fully inbred C57BL/6J (B6) background that recapitulates various aspects of the human disease, including amyloid-b42 accumulation, cognitive deficits, and neuron loss (Oakley et al., 2006) and…”
InfluentialComplement and microglia mediate early synapse loss in Alzheimer mouse models
Hong, S., Beja-Glasser, V. F., Nfonoyim, B. M., Frouin, A., Li, S., Ramakrishnan, S., Merry, K. M., Shi, Q., Rosenthal, A., Barres, B. A., et al. (2016) · Science · doi:10.1126/science.aad8373 · Cited by 3,343
The molecular pathology of Alzheimer's disease
Selkoe, D. J. (1991) · Neuron · doi:10.1016/0896-6273(91)90052-2 · Cited by 2,708
Zerbino, D. R., Achuthan, P., Akanni, W., Amode, M. R., Barrell, D., Bhai, J., Billis, K., Cummins, C., Gall, A., Girón, C. G., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1098 · Cited by 2,605
Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease
Zhang, B., Gaiteri, C., Bodea, L.-G., Wang, Z., McElwee, J., Podtelezhnikov, A. A., Zhang, C., Xie, T., Tran, L., Dobrin, R., et al. (2013) · Cell · doi:10.1016/j.cell.2013.03.030 · Cited by 1,657
Cited by
Sorted by citations
Type I interferon response drives neuroinflammation and synapse loss in Alzheimer disease
Roy, E. R., Wang, B., Wan, Y.-W., Chiu, G., Cole, A., Yin, Z., Propson, N. E., Xu, Y., Jankowsky, J. L., Liu, Z., et al. (2020) · Journal of Clinical Investigation · doi:10.1172/jci133737 · Cited by 563
Adult Hippocampal Neurogenesis in Aging and Alzheimer's Disease
Babcock, K. R., Page, J. S., Fallon, J. R., & Webb, A. E. (2021) · Stem Cell Reports · doi:10.1016/j.stemcr.2021.01.019 · Cited by 330
Wan, Y.-W., Al-Ouran, R., Mangleburg, C. G., Perumal, T. M., Lee, T. V., Allison, K., Swarup, V., Funk, C. C., Gaiteri, C., Allen, M., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107908 · Cited by 295
Li, J., Pan, L., Pembroke, W. G., Rexach, J. E., Godoy, M. I., Condro, M. C., Alvarado, A. G., Harteni, M., Chen, Y., Stiles, L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24232-3 · Cited by 196
Updates on mouse models of Alzheimer’s disease
Zhong, M. Z., Peng, T., Duarte, M. L., Wang, M., & Cai, D. (2024) · Molecular Neurodegeneration · doi:10.1186/s13024-024-00712-0 · Cited by 189
A platform for experimental precision medicine: The extended BXD mouse family
Ashbrook, D. G., Arends, D., Prins, P., Mulligan, M. K., Roy, S., Williams, E. G., Lutz, C. M., Valenzuela, A., Bohl, C. J., Ingels, J. F., et al. (2021) · Cell Systems · doi:10.1016/j.cels.2020.12.002 · Cited by 171
Gene-by-environment interactions in Alzheimer’s disease and Parkinson’s disease
Dunn, A. R., O’Connell, K. M. S., & Kaczorowski, C. C. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.06.018 · Cited by 160
A unifying hypothesis for Alzheimer's disease: from plaques to neurodegeneration
Edwards, F. A. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2019.03.003 · Cited by 140
Canine Cognitive Dysfunction and Alzheimer’s Disease – Two Facets of the Same Disease?
Mihevc, S. P., & Majdič, G. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00604 · Cited by 152
Genetic architecture of Alzheimer's disease
Neuner, S. M., TCW, J., & Goate, A. M. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.104976 · Cited by 126
“In addition, efforts to expand existing AD mouse models through the inclusion of genetic diversity (Neuner et al., 2019; Onos et al., 2019) have resulted in resources that show a more sig-”
BackgroundInfluentialMullane, K., & Williams, M. J. (2020) · Biochemical Pharmacology · doi:10.1016/j.bcp.2020.113945 · Cited by 109
Model organism development and evaluation for late‐onset Alzheimer's disease: MODEL‐AD
Oblak, A. L., Forner, S., Territo, P. R., Sasner, M., Carter, G. W., Howell, G. R., Rizzo, S. J. S., Logsdon, B. A., Mangravite, L. M., Mortazavi, A., et al. (2020) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12110 · Cited by 107
Moving beyond amyloid and tau to capture the biological heterogeneity of Alzheimer’s disease
Young‐Pearse, T. L., Lee, H., Hsieh, Y., Chou, V., & Selkoe, D. J. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.03.005 · Cited by 104
Enhancing face validity of mouse models of Alzheimer’s disease with natural genetic variation
Onos, K. D., Uyar, A., Keezer, K. J., Jackson, H. M., Preuss, C., Acklin, C. J., O’Rourke, R., Buchanan, R., Cossette, T. L., Sukoff Rizzo, S. J., et al. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008155 · Cited by 93
Glia: victims or villains of the aging brain?
Salas, I. H., Burgado, J., & Allen, N. J. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.105008 · Cited by 99
Mouse models of neurodegeneration: Know your question, know your mouse
Fisher, E., & Bannerman, D. M. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aaq1818 · Cited by 80
APOE4 confers transcriptomic and functional alterations to primary mouse microglia
Machlovi, S. I., Neuner, S. M., Hemmer, B. M., Khan, R., Liu, Y., Huang, M., Zhu, J. D., Castellano, J. M., Cai, D., Marcora, E., et al. (2022) · Neurobiology of Disease · doi:10.1016/j.nbd.2022.105615 · Cited by 73
Insulin Resistance in Peripheral Tissues and the Brain: A Tale of Two Sites
Rhea, E. M., Banks, W. A., & Raber, J. (2022) · Biomedicines · doi:10.3390/biomedicines10071582 · Cited by 76
Vitek, M. P., Araujo, J. A., Fossel, M., Greenberg, B. D., Howell, G. R., Rizzo, S. J. S., Seyfried, N. T., Tenner, A. J., Territo, P. R., Windisch, M., et al. (2020) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12114 · Cited by 103
Granzotto, A., Vissel, B., & Sensi, S. L. (2024) · eLife · doi:10.7554/elife.90633 · Cited by 71
Mouse Systems Genetics as a Prelude to Precision Medicine
Li, H., & Auwerx, J. H. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.01.004 · Cited by 72
Smit, T., Deshayes, N. A. C., Borchelt, D. R., Kamphuis, W., Middeldorp, J., & Hol, E. M. (2021) · Glia · doi:10.1002/glia.23981 · Cited by 71
Williams, G. H., Gatt, A. P., Clarke, E. E., Corcoran, J. P. T., Doherty, P., Chambers, D. J., & Ballard, C. G. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0555-x · Cited by 66
Translational approaches to understanding resilience to Alzheimer’s disease
Neuner, S. M., Telpoukhovskaia, M., Menon, V., O’Connell, K. M. S., Hohman, T. J., & Kaczorowski, C. C. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.02.005 · Cited by 68
“To specifically use GRPs (Box 3) to identify resilience factors, a new F1 mouse population was generated by introducing the well-established 5XFAD transgene into almost 30 BXD strains [56].”
BackgroundMethodInfluentialSelf-citationNackenoff, A. G., Hohman, T. J., Neuner, S. M., Akers, C. S., Weitzel, N. C., Shostak, A., Ferguson, S. M., Mobley, B., Bennett, D. A., Schneider, J. A., et al. (2021) · PLOS Genetics · doi:10.1371/journal.pgen.1009406 · Cited by 59
Cognitive Reserve in Model Systems for Mechanistic Discovery: The Importance of Longitudinal Studies
McQuail, J. A., Dunn, A. R., Stern, Y., Barnes, C. A., Kempermann, G., Rapp, P. R., Kaczorowski, C. C., & Foster, T. C. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.607685 · Cited by 67
O’Leary, T. P., & Brown, R. E. (2022) · Genes Brain & Behavior · doi:10.1111/gbb.12794 · Cited by 61
The APOEε3/ε4 Genotype Drives Distinct Gene Signatures in the Cortex of Young Mice
Foley, K. E., Hewes, A. A., Garceau, D. T., Kotredes, K. P., Carter, G. W., Sasner, M., & Howell, G. R. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.838436 · Cited by 62
Omics-based biomarkers discovery for Alzheimer's disease
Aerqin, Q., Wang, Z.-T., Wu, K., He, X., Dong, Q., & Yu, J. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04614-6 · Cited by 56
Landowski, M., & Rickman, C. B. (2021) · Journal of Ocular Pharmacology and Therapeutics · doi:10.1089/jop.2021.0067 · Cited by 48
Dunn, A. R., & Kaczorowski, C. C. (2019) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2019.107069 · Cited by 42
Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency
Tabbaa, M., Knoll, A., & Levitt, P. (2023) · Neuron · doi:10.1016/j.neuron.2023.01.009 · Cited by 45
Tadenev, A. L. D., & Burgess, R. W. (2019) · Mammalian Genome · doi:10.1007/s00335-019-09798-0 · Cited by 50
Logsdon, B. A., Perumal, T. M., Swarup, V., Wang, M., Funk, C. C., Gaiteri, C., Allen, M., Wang, X., Dammer, E. B., Srivastava, G. P., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/510420 · Cited by 46
Newman, M., Hin, N., Pederson, S., & Lardelli, M. T. (2019) · Molecular Brain · doi:10.1186/s13041-019-0467-y · Cited by 44
Raikwar, S. P., Kikkeri, N. S., Sakuru, R. C., Saeed, D., Zahoor, H., Premkumar, K., Mentor, S., Thangavel, R., Dubova, I., Ahmed, M. E., et al. (2019) · Journal of Neuroimmune Pharmacology · doi:10.1007/s11481-019-09849-y · Cited by 48
Uses for humanised mouse models in precision medicine for neurodegenerative disease
Nair, R., Corrochano, S., Gasco, S., Tibbit, C., Thompson, D., Maduro, C., Ali, Z., Fratta, P., Acevedo‐Arozena, A., Cunningham, T. J., et al. (2019) · Mammalian Genome · doi:10.1007/s00335-019-09807-2 · Cited by 43
Large artery stiffness and brain health: insights from animal models
Winder, N. R., Reeve, E. H., & Walker, A. E. (2020) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00696.2020 · Cited by 42
Advances in mouse genetics for the study of human disease
Brown, S. D. M. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab153 · Cited by 44
The expanded BXD family of mice: A cohort for experimental systems genetics and precision medicinePreprint
Ashbrook, D. G., Arends, D., Prins, P., Mulligan, M. K., Roy, S., Williams, E. G., Lutz, C. M., Valenzuela, A., Bohl, C. J., Ingels, J. F., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/672097 · Cited by 43
Sasmita, A. O., Ong, E. C., Nazarenko, T., Mao, S., Komarek, L., Thalmann, M., Hantakova, V., Spieth, L., Berghoff, S. A., Barr, H. J., et al. (2025) · Neuron · doi:10.1016/j.neuron.2024.12.025 · Cited by 42
“15 Based on our findings, we recommend breeding and maintaining 5xFAD mice by inheriting the transgene through only one germ line—for example, paternally—when a more rapid plaque deposition is desired.”
Colon-Perez, L. M., Ibanez, K. R., Suarez, M., Torroella, K., Acuna, K., Ofori, E., Levites, Y., Vaillancourt, D. E., Golde, T. E., Chakrabarty, P., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116138 · Cited by 41
Amaral, D. G., Anderson, G. M., Bailey, A. J., Bernier, R., Bishop, S. L., Blatt, G. J., Canal‐Bedia, R., Charman, T., Dawson, G., de Vries, P. J., et al. (2019) · Autism Research · doi:10.1002/aur.2101 · Cited by 40
Genetic Variants Associated With Resilience in Human and Animal Studies
Cahill, S., Chandola, T., & Hager, R. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.840120 · Cited by 52
Evolving therapeutic interventions for the management and treatment of Alzheimer’s disease
Ahmad, F., Karan, A., Sharma, R., Sharma, N. S., Sundar, V., Jayaraj, R. L., Mukherjee, S., & DeCoster, M. A. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102229 · Cited by 40
Arnold, S. E., Hyman, B. T., Betensky, R. A., & Dodge, H. H. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14063 · Cited by 37
Doldur-Balli, F., Imamura, T., Veatch, O. J., Gong, N. N., Lim, D. C., Hart, M. P., Abel, T. G., Kayser, M. S., Brodkin, E. S., & Pack, A. I. (2022) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2022.101595 · Cited by 46
McKee, C., Hoffos, M., Vecchiarelli, H. A., & Tremblay, M. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1125982 · Cited by 38
Vasunilashorn, S. M., Lunardi, N., Newman, J. C., Crosby, G. J., Acker, L., Abel, T. G., Bhatnagar, S., Cunningham, C. M., de Cabo, R., Dugan, L. L., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.12941 · Cited by 39
Millan, M. J., Dekeyne, A., Gobert, A., Brocco, M., la Cour, C. M., Ortuno, J., Watson, D. J., & Fone, K. C. F. (2020) · Neuropharmacology · doi:10.1016/j.neuropharm.2020.108099 · Cited by 38
Artificial intelligence for neurodegenerative experimental models
Marzi, S. J., Schilder, B. M., Nott, A., Frigerio, C. S., Willaime‐Morawek, S., Bucholc, M., Hanger, D. P., James, C. R., Lewis, P. A., Lourida, I., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13479 · Cited by 35
Intranasal Dantrolene as a Disease-Modifying Drug in Alzheimer 5XFAD Mice
Shi, Y., Zhang, L., Gao, X., Zhang, J., Abou, M. B., Liang, G., Meng, Q., Hepner, A., Eckenhoff, M. F., & Wei, H. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200227 · Cited by 32
Genetic Factors Mediate the Impact of Chronic Stress and Subsequent Response to Novel Acute Stress
Terenina, E. E., Cavigelli, S. A., Mormède, P., Zhao, W., Parks, C., Lu, L., Jones, B. C., & Mulligan, M. K. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00438 · Cited by 31
Zhukov, O., He, C., Soylu-Kucharz, R., Cai, C., Lauritzen, A. D., Aldana, B. I., Björkqvist, M., Lauritzen, M., & Kucharz, K. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1089005 · Cited by 30
Mouse Genetic Reference Populations: Cellular Platforms for Integrative Systems Genetics
Swanzey, E., O’Connor, C., & Reinholdt, L. G. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.09.007 · Cited by 34
Magnetic Resonance Imaging in Animal Models of Alzheimer’s Disease Amyloidosis
Ni, R. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222312768 · Cited by 34
Reynolds, T., Johnson, E. C., Huggett, S. B., Bubier, J. A., Palmer, R. H. C., Arpana Agrawal, A., Baker, E. J., & Chesler, E. J. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00795-5 · Cited by 32
An Overview of Astrocyte Responses in Genetically Induced Alzheimer’s Disease Mouse Models
Spanos, F., & Liddelow, S. A. (2020) · Cells · doi:10.3390/cells9112415 · Cited by 32
Neuner, S. M., Heuer, S. E., Zhang, J., Philip, V. M., & Kaczorowski, C. C. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00035 · Cited by 29
Wang, Y., Liang, G., Liang, S., Mund, R., Shi, Y., & Wei, H. (2020) · Anesthesiology · doi:10.1097/aln.0000000000003224 · Cited by 30
Heuer, S. E., Neuner, S. M., Hadad, N., O’Connell, K. M. S., Williams, R. W., Philip, V. M., Gaiteri, C., & Kaczorowski, C. C. (2020) · Learning & Memory · doi:10.1101/lm.051839.120 · Cited by 26
Animal and Cellular Models of Alzheimer’s Disease: Progress, Promise, and Future Approaches
Trujillo‐Estrada, L., Sánchez‐Mejías, E., Sanchez-Varo, R. M., García‐León, J. A., Nuñez‐Diaz, C., Dávila, J. C., Vitórica, J., LaFerla, F. M., Moreno‐González, I., Gutiérrez, A., et al. (2021) · The Neuroscientist · doi:10.1177/10738584211001753 · Cited by 30
Characterization of Apathy-Like Behaviors in the 5xFAD Mouse Model of Alzheimer's Disease
Keszycki, R. M., Rodríguez, G., Dunn, J. T., Locci, A., Orellana, H., Haupfear, I., Dominguez, S., Fisher, D. W., & Dong, H. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.02.012 · Cited by 31
Recent advances in understanding the genetics of sleep
Jan, M., O’Hara, B. F., & Franken, P. (2020) · F1000Research · doi:10.12688/f1000research.22028.1 · Cited by 27
Cellular Biology of Tau Diversity and Pathogenic Conformers
Kang, S., Eskandari‐Sedighi, G., Hromádková, L., Safar, J., & Westaway, D. A. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.590199 · Cited by 29
Genç, Ö., An, J., Fetter, R. D., Kulik, Y. D., Zunino, G., Sanders, S., & Davis, G. W. (2020) · eLife · doi:10.7554/elife.55775 · Cited by 28
Hendrickx, J. O., Martinet, W., Dam, D. V., & Meyer, G. R. Y. D. (2021) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2021.651215 · Cited by 28
O’Connell, K. M. S., Ouellette, A. R., Neuner, S. M., Dunn, A. R., & Kaczorowski, C. C. (2019) · Genes Brain & Behavior · doi:10.1111/gbb.12603 · Cited by 23
Establishment of multi-stage intravenous self-administration paradigms in mice
Slosky, L. M., Pires, A., Bai, Y., Clark, N. B., Hauser, E. R., Gross, J., Porkka, F., Zhou, Y., Chen, X., Pogorelov, V. M., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-24740-2 · Cited by 25
Lee, M. J., Wang, C., Carroll, M. J., Brubaker, D. K., Hyman, B. T., & Lauffenburger, D. A. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.727784 · Cited by 19
Animal Models of Psychosis in Alzheimer Disease
Krivinko, J. M., Koppel, J. L., Savonenko, A. V., & Sweet, R. A. (2019) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2019.05.009 · Cited by 19
Ni, R. (2021) · Pharmaceuticals · doi:10.3390/ph14111179 · Cited by 18
Genetic diversity promotes resilience in a mouse model of Alzheimer's disease
Soni, N., Hohsfield, L. A., Tran, K. M., Kawauchi, S., Walker, A., Javonillo, D. I., Phan, J., Matheos, D. P., Cunha, C. D., Uyar, A., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13753 · Cited by 17
Multi-omic and multi-species meta-analyses of nicotine consumption
Palmer, R. H. C., Benca‐Bachman, C. E., Huggett, S. B., Bubier, J. A., McGeary, J. E., Ramgiri, N., Srijeyanthan, J., Yang, J., Visscher, P. M., Yang, J., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01231-y · Cited by 17
Smith, S. A., & Hopp, S. C. (2023) · Aging Brain · doi:10.1016/j.nbas.2023.100078 · Cited by 18
Dysregulated ac4C modification of mRNA in a mouse model of early-stage Alzheimer’s disease
Ji, H., Zhou, H.-Q., Qie, J., Lu, W.-M., Gao, H., & Wu, D. (2025) · Cell & Bioscience · doi:10.1186/s13578-025-01389-8 · Cited by 17
Ali, M., Huarte, O. U., Heurtaux, T., Garcia, P., Rodriguez, B. P., Grzyb, K., Halder, R., Skupin, A., Buttini, M., & Glaab, E. (2022) · Molecular Neurobiology · doi:10.1007/s12035-022-02985-2 · Cited by 27
Promoting validation and cross-phylogenetic integration in model organism research
Cheng, K. C., Burdine, R. D., Dickinson, M. E., Ekker, S. C., Lin, A. Y., Lloyd, K. C. K., Lutz, C. M., MacRae, C. A., Morrison, J. H., O’Connor, D. H., et al. (2022) · Disease Models & Mechanisms · doi:10.1242/dmm.049600 · Cited by 16
Davies, G. F., Gorman, R., McGlacken, R., & Peres, S. (2021) · Laboratory Animals · doi:10.1177/0023677221993157 · Cited by 16
Pursuit of precision medicine: Systems biology approaches in Alzheimer's disease mouse models
Gurdon, B., & Kaczorowski, C. C. (2021) · Neurobiology of Disease · doi:10.1016/j.nbd.2021.105558 · Cited by 16
Cunningham, A. M., Santos, T. L., Gutzeit, V. A., Hamilton, H. C., Hen, R., & Donaldson, Z. R. (2019) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.8b00638 · Cited by 16
The abiding relevance of mouse models of rare mutations to psychiatric neuroscience and therapeutics
Gogos, J. A., Crabtree, G. W., & Diamantopoulou, A. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.03.018 · Cited by 15
Animal models of Alzheimer’s disease embrace diversity
Neff, E. P. (2019) · Lab Animal · doi:10.1038/s41684-019-0377-8 · Cited by 17
Strategies to dissect microglia-synaptic interactions during aging and in Alzheimer's disease
Heuer, S. E., Bloss, E. B., & Howell, G. R. (2024) · Neuropharmacology · doi:10.1016/j.neuropharm.2024.109987 · Cited by 16
Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
Gurdon, B., Yates, S. C., Csucs, G., Groeneboom, N. E., Hadad, N., Telpoukhovskaia, M., Ouellette, A., Ouellette, T., O’Connell, K. M. S., Singh, S., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-06242-1 · Cited by 15
Self-citationDeng, T., Li, J., Liu, J., Xu, F., Liu, X., Mi, J., Bergquist, J., Wang, H. H., Yang, C., Lu, L., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.745668 · Cited by 16
Genetic Background Matters: Population-Based Studies in Model Organisms for Translational Research
Olguín, V., Durán, A., Heras, M. L., Rubilar, J. C., Cubillos, F. A., Olguı́n, P., & Klein, A. D. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23147570 · Cited by 14
Williams, T., Bathe, T., Vo, Q., Sacilotto, P., McFarland, K. N., Ruiz, A. J., Hery, G. P., Sullivan, P. M., Borchelt, D., Prokop, S., et al. (2023) · Acta Neuropathologica Communications · doi:10.1186/s40478-023-01581-2 · Cited by 16
Geroprotective interventions in the 3xTg mouse model of Alzheimer’s disease
Sonsalla, M. M., & Lamming, D. W. (2023) · GeroScience · doi:10.1007/s11357-023-00782-w · Cited by 17
Telpoukhovskaia, M. A., Hadad, N., Gurdon, B., Dai, Y., Ouellette, A. R., Neuner, S. M., Dunn, A. R., Willcox, J. A. L., Wu, Y., Dumitrescu, L. C., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.12.487877 · Cited by 13
Villani, F., Sasani, T. A., Maksimov, M., Gunturkun, M. H., Ma, N., Ren, Y.-Y., Rothschild, D., Chen, H., Lu, L., Dumont, B. L., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.21.489063 · Cited by 15
Fingolimod mitigates synaptic deficits and psychosis‐like behavior in APP/PSEN1 mice
Krivinko, J. M., Erickson, S. L., MacDonald, M. L., Garver, M. E., & Sweet, R. A. (2022) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12324 · Cited by 12
Kim, Y., Cho, M., Jang, C. H., Lee, J., Kim, J., Oh, J., & Lim, J. (2024) · Foods · doi:10.3390/foods13050682 · Cited by 12
Cai, J., Xie, D., Kong, F., Zhai, Z., Zhu, Z., Zhao, Y., Xu, Y., & Sun, T. (2024) · Journal of Alzheimer s Disease · doi:10.3233/jad-231249 · Cited by 13
Chaperone-mediated autophagy as a modulator of aging and longevity
Endicott, S. J. (2024) · Frontiers in Aging · doi:10.3389/fragi.2024.1509400 · Cited by 16
Ouellette, A. R., Hadad, N., Deighan, A. G., Robinson, L. L., O’Connell, K. M. S., Freund, A., Churchill, G. A., & Kaczorowski, C. C. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2022.07.004 · Cited by 12
McGinley, L. M., Chen, K. S., Mason, S. N., Rigan, D. M., Kwentus, J. F., Hayes, J. M., Glass, E., Reynolds, E. L., Murphy, G. G., & Feldman, E. L. (2022) · Clinical and Translational Medicine · doi:10.1002/ctm2.1046 · Cited by 13
Heuer, S. E., Keezer, K. J., Hewes, A. A., Onos, K. D., Graham, K., Howell, G. R., & Bloss, E. B. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13440 · Cited by 11
Gammie, S. C., Messing, A., Hill, M. A., Kelm‐Nelson, C. A., & Hagemann, T. L. (2024) · PLoS ONE · doi:10.1371/journal.pone.0291995 · Cited by 11
Tau propagation is dependent on the genetic background of mouse strains
Dujardin, S., Fernandes, A., Bannon, R., Commins, C., De Los Santos, M., Kamath, T. V., Hayashi, M., & Hyman, B. T. (2022) · Brain Communications · doi:10.1093/braincomms/fcac048 · Cited by 11
Metadata
- Authors
- Neuner, S. M., Heuer, S. E., Huentelman, M. J., O’Connell, K. M. S., & Kaczorowski, C. C.
- Affiliations
- University of Tennessee Health Science Center (US)
- Tufts University (US)
- Translational Genomics Research Institute (US)
- Jackson Laboratory (US)
- Corresponding author
- Kaczorowski, Catherine C.
- ORCID
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 101
- Issue
- 3
- Pages
- 399-411.e5
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC6886697
- OpenAlex
- W2908182575
- Cited by
- 202
- References
- 51
- Citations by year
- 2026: 12 · 2025: 14 · 2024: 27 · 2023: 31 · 2022: 31 · 2021: 27 · 2020: 30 · 2019: 30
- FWCI
- 14.91
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Funders
- NIA (R01AG057914)
- BrightFocus Foundation (A2016397S)
- National Institute on Aging (R01AG054180, F31AG050357, R01AG059778)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK102918)
- Evnin family
- University of Tennessee Health Science Center Neuroscience Institute
- Translational Genomics Research Institute
- 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, mouse model, genetic diversity, translational research, precision medicine, cognitive phenotypes, amyloid pathology, transcriptomics, genetic susceptibility
- MeSH terms
- Alzheimer Disease, Animals, Disease Models, Animal, Female, Genotype, Male, Mice, Inbred C57BL, Species Specificity, Mice, Translational Research, Biomedical, Precision Medicine
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
