The fornix provides multiple biomarkers to characterize circuit disruption in a mouse model of Alzheimer’s disease.
Open accessAbstract
Multivariate biomarkers are needed for detecting Alzheimer's disease (AD), understanding its etiology, and quantifying the effect of therapies. Mouse models provide opportunities to study characteristics of AD in well-controlled environments that can help facilitate development of early interventions. The CVN-AD mouse model replicates multiple AD hallmark pathologies, and we identified multivariate biomarkers characterizing a brain circuit disruption predictive of cognitive decline. In vivo and ex vivo magnetic resonance imaging (MRI) revealed that CVN-AD mice replicate the hippocampal atrophy (6%), characteristic of humans with AD, and also present changes in subcortical areas. The largest effect was in the fornix (23% smaller), which connects the septum, hippocampus, and hypothalamus. In characterizing the fornix with diffusion tensor imaging, fractional anisotropy was most sensitive (20% reduction), followed by radial (15%) and axial diffusivity (2%), in detecting pathological changes. These findings were strengthened by optical microscopy and ultrastructural analyses. Ultrastructual analysis provided estimates of axonal density, diameters, and myelination-through the g-ratio, defined as the ratio between the axonal diameter, and the diameter of the axon plus the myelin sheath. The fornix had reduced axonal density (47% fewer), axonal degeneration (13% larger axons), and abnormal myelination (1.5% smaller g-ratios). CD68 staining showed that white matter pathology could be secondary to neuronal degeneration, or due to direct microglial attack. In conclusion, these findings strengthen the hypothesis that the fornix plays a role in AD, and can be used as a disease biomarker and as a target for therapy.
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Fornix can be used as a disease biomarker for pharmacological therapeutics.
“and can be used as a disease biomarker for pharmacological therapeutics (Badea et al., 2016).”
From Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging (2022) · cites this paper as Badea et al., 2016
Compared to other white matter bundles, fornix may play an important role in AD pathology.
“Compared to other white matter bundles, fornix may play an important role in AD pathology”
From Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging (2022) · cites this paper as Badea et al., 2016
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NIH Image to ImageJ: 25 years of image analysis
Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012) · Nature Methods · doi:10.1038/nmeth.2089 · Cited by 64,638 · see citing works
The mouse brain in stereotaxic coordinates
Konsman, J. (2003) · Psychoneuroendocrinology · doi:10.1016/s0306-4530(03)00088-x · Cited by 16,796 · see citing works
The Mouse Brain in Stereotaxic Coordinates
Paxinos, G. (2001) · Cited by 12,859 · see citing works
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155 · see citing works
N4ITK: Improved N3 Bias Correction
Tustison, N. J., Avants, B., Cook, P. A., Zheng, Y., Egan, A., Yushkevich, P. A., & Gee, J. C. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2010.2046908 · Cited by 6,119 · see citing works
Avants, B., Epstein, C. L., Grossman, M., & Gee, J. C. (2007) · Medical Image Analysis · doi:10.1016/j.media.2007.06.004 · Cited by 5,618 · see citing works
Thresholding of statistical maps in functional neuroimaging using the false discovery rate
Genovese, C. R., Lazar, N. A., & Nichols, T. (2002) · NeuroImage · doi:10.1006/nimg.2001.1037 · Cited by 4,923 · see citing works
Inflammation and Alzheimer’s disease
Akiyama, H. (2000) · Neurobiology of Aging · doi:10.1016/s0197-4580(00)00124-x · Cited by 4,514 · see citing works
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 · see citing works
Clinical and biomarker changes in dominantly inherited Alzheimer's disease
Bateman, R. J., Xiong, C., Benzinger, T. L. S., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1202753 · Cited by 3,814 · see citing works
Synapse Loss and Microglial Activation Precede Tangles in a P301S Tauopathy Mouse Model
Yoshiyama, Y., Higuchi, M., Zhang, B., Huang, S.-M., Iwata, N., Saido, T. C., Maeda, J., Suhara, T., Trojanowski, J. Q., & Lee, V. M.-Y. (2007) · Neuron · doi:10.1016/j.neuron.2007.01.010 · Cited by 2,208 · see citing works
A three-dimensional statistical analysis for CBF activation studies in human brain
Worsley, K. J., Evans, A. C., Marrett, S., & Neelin, P. (1992) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.1992.127 · Cited by 2,036 · see citing works
Assessing the significance of focal activations using their spatial extent
Friston, K. J., Worsley, K. J., Frackowiak, R. S. J., Mazziotta, J. C., & Evans, A. C. (1994) · Human Brain Mapping · doi:10.1002/hbm.460010306 · Cited by 1,907 · see citing works
Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease
Minoshima, S., Giordani, B., Berent, S., Frey, K. A., Foster, N. L., & Kuhl, D. E. (1997) · Annals of Neurology · doi:10.1002/ana.410420114 · Cited by 1,802 · see citing works
Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment
Jack, C. R., Petersen, R. C., Xu, Y. C., O’Brien, P. C., Smith, G. E., Ivnik, R. J., Boeve, B. F., Waring, S. C., Tangalos, E. G., & Kokmen, E. (1999) · Neurology · doi:10.1212/wnl.52.7.1397 · Cited by 1,404 · see citing works
Occurrence of neuropathological changes and dementia of Alzheimer’s disease in Down’s syndrome
Wisniewski, K. E., Wisniewski, H. M., & Wen, G. Y. (1985) · Annals of Neurology · doi:10.1002/ana.410170310 · Cited by 1,159 · see citing works
Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease
Jack, C. R., Petersen, R. C., Xu, Y. C., Waring, S. C., O'Brien, P. C., Tangalos, E. G., Smith, G. E., Ivnik, R. J., & Kokmen, E. (1997) · Neurology · doi:10.1212/wnl.49.3.786 · Cited by 1,128 · see citing works
A white matter disorder in dementia of the Alzheimer type: A pathoanatomical study
Brun, A., & Englund, E. (1986) · Annals of Neurology · doi:10.1002/ana.410190306 · Cited by 1,014 · see citing works
Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease
Bartzokis, G. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2003.03.001 · Cited by 968 · see citing works
Increased hippocampal activation in mild cognitive impairment compared to normal aging and AD
Dickerson, B. C., Salat, D. H., Greve, D. N., Chua, E. F., Rand-Giovannetti, E., Rentz, D. M., Bertram, L., Mullin, K., Tanzi, R. E., Blacker, D., et al. (2005) · Neurology · doi:10.1212/01.wnl.0000171450.97464.49 · Cited by 910 · see citing works
Staging of Alzheimer-Related Cortical Destruction
Braak, H., Braak, E., & Bohl, J. (2008) · European Neurology · doi:10.1159/000116984 · Cited by 836 · cited 2× · see citing works
“The hallmarks of AD include cognitive deficits, amyloid plaques, neurofibrillary tangles, and neuronal loss (Braak et al., 1993).”
The Insight ToolKit image registration framework
Avants, B. B., Tustison, N. J., Stauffer, M., Song, G., Wu, B., & Gee, J. C. (2014) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2014.00044 · Cited by 658 · see citing works
Bozzali, M. (2002) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.72.6.742 · Cited by 568 · see citing works
Weinberg, J., Misukonis, M., Shami, P., Mason, S. N., Sauls, D., Dittman, W. A., Wood, E., Smith, G., McDonald, B., & Bachus, K. (1995) · Blood · doi:10.1182/blood.v86.3.1184.1184 · Cited by 435 · see citing works
White Matter Structural Integrity in Healthy Aging Adults and Patients With Alzheimer Disease
Bartzokis, G., Cummings, J. L., Sultzer, D. L., Henderson, V. W., Nuechterlein, K. H., & Mintz, J. (2003) · Archives of Neurology · doi:10.1001/archneur.60.3.393 · Cited by 415 · see citing works
The cholinergic system in Alzheimer's disease
Kása, P., Rakonczay, Z., & Gulya, K. (1997) · Progress in Neurobiology · doi:10.1016/s0301-0082(97)00028-2 · Cited by 410 · see citing works
Ramprasad, M. P., Terpstra, V., Kondratenko, N., Quehenberger, O., & Steinberg, D. H. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.25.14833 · Cited by 382 · see citing works
Davis, J., Xu, F., Deane, R., Romanov, G., Previti, M. L., Zeigler, K., Zlokovic, B. V., & Van Nostrand, W. E. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m312946200 · Cited by 373 · see citing works
Villain, N., Desgranges, B., Viader, F., de la Sayette, V., Mezenge, F., Landeau, B., Baron, J.-C., Eustache, F., & Chetelat, G. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.1392-08.2008 · Cited by 366 · see citing works
Microglial Activation Resulting from CD40-CD40L Interaction After β-Amyloid Stimulation
Tan, J., Town, T., Paris, D., Mori, T., Suo, Z., Crawford, F., Mattson, M. P., Flavell, R. A., & MULLAN, M. J. (1999) · Science · doi:10.1126/science.286.5448.2352 · Cited by 352 · see citing works
Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD
de Leon, M. J., Bobinski, M., Convit, A. J., Wolf, O. T., & Insausti, R. (2001) · Neurology · doi:10.1212/wnl.56.6.820 · Cited by 351 · see citing works
Neuroimaging markers for the prediction and early diagnosis of Alzheimer's disease dementia
Ewers, M., Sperling, R. A., Klunk, W. E., Weiner, M. W., & Hampel, H. J. (2011) · Trends in Neurosciences · doi:10.1016/j.tins.2011.05.005 · Cited by 345 · see citing works
Zhou, Y., Dougherty, J. H., Hübner, K. F., Bai, B., Cannon, R. L., & Hutson, R. K. (2008) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2008.04.006 · Cited by 340 · see citing works
Patterns of gliosis in alzheimer's disease and aging cerebrum
Beach, T. G., Walker, R., & McGeer, E. G. (1989) · Glia · doi:10.1002/glia.440020605 · Cited by 337 · see citing works
Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD
Xu, Y., Jack, C. R., O’Brien, P. C., Kokmen, E., Smith, G. E., Ivnik, R. J., Boeve, B. F., Tangalos, R. G., & Petersen, R. C. (2000) · Neurology · doi:10.1212/wnl.54.9.1760 · Cited by 335 · see citing works
A Three-dimensional MRI Atlas of the Mouse Brain with Estimates of the Average and Variability
Kovačević, N., Henderson, J., Chan, E. T., Lifshitz, N., Bishop, J. E., Evans, A. C., Henkelman, R. M., & Chen, X. J. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh165 · Cited by 328 · see citing works
Ringman, J. M., O'Neill, J., Geschwind, D., Medina, L., Apostolova, L. G., Rodriguez, Y., Schaffer, B., Varpetian, A., Tseng, B., Ortiz, F., et al. (2007) · Brain · doi:10.1093/brain/awm102 · Cited by 290 · see citing works
di Penta, A., Moreno, B., Reix, S., Fernández-Díez, B., Villanueva, M., Errea, O., Escala, N., Vandenbroeck, K., Comella, J. X., & Villoslada, P. (2013) · PLoS ONE · doi:10.1371/journal.pone.0054722 · Cited by 255 · see citing works
Waxholm Space: An image-based reference for coordinating mouse brain research
Johnson, G. A., Badea, A., Brandenburg, J., Cofer, G. P., Fubara, B. N., Liu, S., & Nissanov, J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.067 · Cited by 253 · see citing works
Self-citationJack, C. R., Wiste, H. J., Weigand, S. D., Knopman, D. S., Mielke, M. M., Vemuri, P., Lowe, V. J., Senjem, M. L., Gunter, J. L., Reyes, D. A., et al. (2015) · Brain · doi:10.1093/brain/awv283 · Cited by 252 · see citing works
Morphologic Phenotyping with MR Microscopy: The Visible Mouse
Johnson, G. A., Cofer, G. P., Gewalt, S. L., & Hedlund, L. W. (2002) · Radiology · doi:10.1148/radiol.2223010531 · Cited by 250 · see citing works
Self-citationWhite matter tract integrity in aging and Alzheimer's disease
Damoiseaux, J. S., Smith, S. M., Witter, M. P., Sanz‐Arigita, E., Barkhof, F., Scheltens, P., Stam, C. J., Zarei, M., & Rombouts, S. A. R. B. (2008) · Human Brain Mapping · doi:10.1002/hbm.20563 · Cited by 249 · see citing works
Insausti, R., & Amaral, D. G. (2004) · Elsevier eBooks · doi:10.1016/b978-012547626-3/50024-7 · Cited by 246 · see citing works
Ihara, M., Polvikoski, T. M., Hall, R., Slade, J. Y., Perry, R. H., Oakley, A. E., Englund, E. M., O'Brien, J. T., Ince, P. G., & Kalaria, R. N. (2010) · Acta Neuropathologica · doi:10.1007/s00401-009-0635-8 · Cited by 242 · see citing works
Jankowsky, J. L., Slunt, H. H., Gonzales, V., Savonenko, A. V., Wen, J. C., Jenkins, N. A., Copeland, N. G., Younkin, L. H., Lester, H. A., Younkin, S. G., et al. (2005) · PLoS Medicine · doi:10.1371/journal.pmed.0020355 · Cited by 237 · see citing works
Sperling, R. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1379.009 · Cited by 236 · see citing works
Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer’s disease.
Mielke, M. M., Kozauer, N. A., Chan, K. C. G., George, M., Toroney, J., Zerrate, M., Bandeen-Roche, K., Wang, M.-C., vanZijl, P., & Pekar, J. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.054 · Cited by 225 · see citing works
Morphometric analysis of the C57BL/6J mouse brain
Badea, A., Ali-Sharief, A., & Johnson, G. A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.05.046 · Cited by 211 · see citing works
Self-citationMiao, J., Xu, F., Davis, J., Otte‐Höller, I., Verbeek, M. M., & Nostrand, W. E. V. (2005) · American Journal Of Pathology · doi:10.1016/s0002-9440(10)62993-8 · Cited by 198 · see citing works
Neuronal Hypertrophy in Asymptomatic Alzheimer Disease
Iacono, D., O'Brien, R., Resnick, S. M., Zonderman, A. B., Pletnikova, O., Rudow, G., An, Y., West, M. J., Crain, B., & Troncoso, J. C. (2008) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e3181772794 · Cited by 188 · see citing works
Wilcock, D. M., Lewis, M. R., Nostrand, W. E. V., Davis, J., Previti, M. L., Gharkholonarehe, N., Vitek, M. P., & Colton, C. A. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.5066-07.2008 · Cited by 187 · see citing works
Self-citationArginine Deprivation and Immune Suppression in a Mouse Model of Alzheimer's Disease
Kan, M. J., Lee, J. E., Wilson, J. G., Everhart, A. L., Brown, C. M., Hoofnagle, A. N., Jansen, M., Vitek, M. P., Gunn, M. D., & Colton, C. A. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4668-14.2015 · Cited by 174 · see citing works
Self-citationSong, S.-K., Kim, J. H., Lin, S.-J., Brendza, R. P., & Holtzman, D. M. (2004) · Neurobiology of Disease · doi:10.1016/j.nbd.2003.12.003 · Cited by 170 · see citing works
Kantarci, K., Weigand, S. D., Przybelski, S. A., Shiung, M. M., Whitwell, J. L., Negash, S., Knopman, D. S., Boeve, B. F., O’Brien, P. C., Petersen, R. C., et al. (2009) · Neurology · doi:10.1212/wnl.0b013e3181a2e864 · Cited by 155 · see citing works
Lau, J. C., Lerch, J. P., Sled, J. G., Henkelman, R. M., Evans, A. C., & Bedell, B. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.04.252 · Cited by 151 · see citing works
Frodl, T., & Amico, F. (2013) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2012.12.013 · Cited by 147 · see citing works
Increased Cortical Thickness and Caudate Volume Precede Atrophy in PSEN1 Mutation Carriers
Fortea, J., Sala‐Llonch, R., David Bartrés-faz, A., Bosch, B., Lladó, A., Bargalló, N., Molinuevo, J. L., & Sánchez‐Valle, R. (2010) · Journal of Alzheimer s Disease · doi:10.3233/jad-2010-100678 · Cited by 146 · see citing works
Ottnad, E., Parthasarathy, S., Sambrano, G. R., Ramprasad, M. P., Quehenberger, O., Kondratenko, N., Green, S., & Steinberg, D. H. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.5.1391 · Cited by 144 · see citing works
Accelerating drug discovery for Alzheimer's disease: best practices for preclinical animal studies
Shineman, D. W., Basi, G. S., Bizon, J. L., Colton, C. A., Greenberg, B., Hollister, B. A., Lincecum, J. M., Leblanc, G. G., Lee, L. H., Luo, F. R., et al. (2011) · Alzheimer s Research & Therapy · doi:10.1186/alzrt90 · Cited by 136 · see citing works
Self-citationPer, A., Morris, R., David, A., Tim, B., & O'Keefe, J. M. (2006) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195100273.003.0001 · Cited by 135 · see citing works
Functional Duality of Astrocytes in Myelination
Nash, B., Thomson, C. E., Linington, C., Arthur, A. T., McClure, J., McBride, M., & Barnett, S. C. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1449-11.2011 · Cited by 129 · see citing works
Structural imaging biomarkers of Alzheimer's disease: predicting disease progression
Eskildsen, S. F., Pierrick Coupé, A., Fonov, V., Pruessner, J. C., & Collins, D. L. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.04.034 · Cited by 129 · see citing works
Colton, C. A., Vitek, M. P., Wink, D. A., Xu, Q., Cantillana, V., Previti, M. L., Van Nostrand, W. E., Weinberg, J. B., & Dawson, H. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601075103 · Cited by 128 · see citing works
Self-citationDouet, V., & Chang, L. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00343 · Cited by 122 · see citing works
High-throughput morphologic phenotyping of the mouse brain with magnetic resonance histology
Johnson, G. A., Ali-Sharief, A., Badea, A., Brandenburg, J., Cofer, G. P., Fubara, B. N., Gewalt, S. L., Hedlund, L. W., & Upchurch, L. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.05.013 · Cited by 121 · see citing works
Self-citationSun, S.-W., Song, S.-K., Harms, M. P., Lin, S.-J., Holtzman, D. M., Merchant, K. M., & Kotyk, J. J. (2005) · Experimental Neurology · doi:10.1016/j.expneurol.2004.09.006 · Cited by 121 · see citing works
Copenhaver, B. R., Rabin, L. A., Saykin, A. J., Roth, R. M., Wishart, H. A., Flashman, L. A., Santulli, R. B., McHugh, T. L., & Mamourian, A. C. (2006) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2006.01.015 · Cited by 112 · see citing works
Calabrese, E., Badea, A., WATSON, C. R. R., & Johnson, G. A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.01.017 · Cited by 110 · see citing works
Self-citationVos, S. J. B., Gordon, B. A., Su, Y., Visser, P. J., Holtzman, D. M., Morris, J. C., Fagan, A. M., & Benzinger, T. L. S. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.03.025 · Cited by 98 · see citing works
In vivo imaging of tau pathology using multi-parametric quantitative MRI
Wells, J. A., O'Callaghan, J. M., Holmes, H. E., Powell, N. M., Johnson, R. A., Siow, B., Torrealdea, F., Ismail, O., Walker-Samuel, S., Golay, X., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.023 · Cited by 93 · see citing works
The Fornix in Mild Cognitive Impairment and Alzheimer’s Disease
Nowrangi, M. A., & Rosenberg, P. B. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2015.00001 · Cited by 87 · see citing works
Rémy, F., Vayssière, N., Saint‐Aubert, L., Barbeau, E. J., & Pariente, J. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.01.014 · Cited by 87 · see citing works
Barnett, S. C., & Linington, C. (2012) · The Neuroscientist · doi:10.1177/1073858412465655 · Cited by 83 · see citing works
Guo, Z., Shao, L., Zheng, L., Du, Q., Li, P., John, B., & Geller, D. A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1118118109 · Cited by 81 · see citing works
Memory binding and white matter integrity in familial Alzheimer’s disease
Parra, M. A., Saarimäki, H., Bastin, M. E., Londoño, A. C., Pettit, L., Lopera, F., Della Sala, S., & Abrahams, S. (2015) · Brain · doi:10.1093/brain/awv048 · Cited by 79 · see citing works
Alzheimer’s disease and the fornix
Oishi, K., & Lyketsos, C. G. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00241 · Cited by 72 · see citing works
Cai, S.-P., Huang, L.-Y., Zou, J., Jing, L., Zhai, B., Ji, G.-J., von Deneen, K. V., Ren, J., & Ren, A.-F. (2015) · PLoS ONE · doi:10.1371/journal.pone.0115573 · Cited by 68 · see citing works
Cavedo, E., Lista, S., Khachaturian, Z., Aisen, P., Amouyel, P., Herholz, K., Jack Jr, C. R., Sperling, R., Cummings, J., Blennow, K., et al. (2014) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2014.32 · Cited by 67 · see citing works
Yang, D., Xie, Z., Stephenson, D., Morton, D., Hicks, C. D., Brown, T. M., Sriram, R., O'Neill, S., Raunig, D., & Bocan, T. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.067 · Cited by 64 · see citing works
Capillary CAA and perivascular Aβ-deposition: Two distinct features of Alzheimer's disease pathology
Attems, J., Yamaguchi, H., Saido, T. C., & Thal, D. R. (2010) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2010.08.030 · Cited by 63 · cited 2× · see citing works
“…first around blood vessels and an apparent failure to clear Aβ from the brain, which is similar to humans with cerebral amyloid angiopathy (CAA) (Attems et al., 2010); 3) CVN-AD mice show AT8 antibody immunopositive hyperphosphorylated tau (Colton et al., 2014), and the subsequent tau…”
InfluentialProtective roles of nitric oxide and testosterone in endotoxemia: evidence from NOS-2-deficient mice
Laubach, V. E., Foley, P. L., Shockey, K. S., Tribble, C. G., & Kron, I. L. (1998) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.1998.275.6.h2211 · Cited by 56 · see citing works
Gispert, J. D., Rami, L., Sánchez‐Benavides, G., Falcón, C., Tucholka, A., Rojas, S., & Molinuevo, J. L. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.06.027 · Cited by 56 · see citing works
Inflammation in Alzheimer’s disease: insights from immunotherapy
Schott, J. M., & Révész, T. (2013) · Brain · doi:10.1093/brain/awt231 · Cited by 50 · see citing works
Three-Dimensional Imaging of the Mouse Neurovasculature with Magnetic Resonance Microscopy
Pathak, A. P., Kim, E., Zhang, J., & Jones, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022643 · Cited by 50 · see citing works
Grandjean, J., Derungs, R., Kulic, L., Welt, T., Henkelman, M., Nitsch, R. M., & Rudin, M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.042 · Cited by 48 · see citing works
Badea, A., Johnson, G. A., & Jankowsky, J. L. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.070 · Cited by 47 · see citing works
Self-citationQin, Y.-Y., Li, M.-W., Zhang, S., Zhang, Y., Zhao, L.-Y., Lei, H., Oishi, K., & Zhu, W.-Z. (2013) · Neuroradiology · doi:10.1007/s00234-013-1195-0 · Cited by 42 · see citing works
Differential MRI patterns of brain atrophy in double or single transgenic mice for APP and/or SOD
Borg, J., & Chereul, E. (2008) · Journal of Neuroscience Research · doi:10.1002/jnr.21778 · Cited by 42 · see citing works
Epicentral Disruption of Structural Connectivity in Alzheimer's Disease
Mallio, C. A., Schmidt, R., de Reus, M. A., Vernieri, F., Quintiliani, L., Curcio, G., Beomonte Zobel, B., Quattrocchi, C. C., & van den Heuvel, M. P. (2015) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12397 · Cited by 39 · see citing works
Harms, M. P., Kotyk, J. J., & Merchant, K. M. (2006) · Experimental Neurology · doi:10.1016/j.expneurol.2006.01.002 · Cited by 38 · see citing works
Grand’Maison, M., Zehntner, S. P., Ho, M., Hébert, F., Wood, A., Carbonell, F., Zijdenbos, A. P., Hamel, É., & Bedell, B. J. (2013) · Neurobiology of Disease · doi:10.1016/j.nbd.2013.02.005 · Cited by 38 · see citing works
Hoos, M. D., Richardson, B. M., Foster, M. W., Everhart, A. L., Thompson, J. W., Moseley, M. A., & Colton, C. A. (2013) · Journal of Proteome Research · doi:10.1021/pr4005103 · Cited by 38 · see citing works
Self-citationmNos2Deletion and HumanNOS2Replacement in Alzheimer Disease Models
Colton, C. A., Wilson, J. G., Everhart, A. L., Wilcock, D. M., Puoliväli, J. T., Heikkinen, T., Oksman, J., Jääskeläinen, O., Lehtimäki, K. K., Laitinen, T., et al. (2014) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0000000000000094 · Cited by 37 · see citing works
Self-citationGupta, M., Kantor, M. A., Tung, C. E., Zhang, N., & Albers, G. W. (2015) · Frontiers in Neurology · doi:10.3389/fneur.2014.00291 · Cited by 35 · see citing works
Hoos, M. D., Vitek, M. P., Ridnour, L. A., Wilson, J. G., Jansen, M., Everhart, A. L., Wink, D. A., & Colton, C. A. (2014) · Molecular Neurodegeneration · doi:10.1186/1750-1326-9-50 · Cited by 35 · see citing works
Self-citationAnatomical and Functional Phenotyping of Mice Models of Alzheimer's Disease by MR Microscopy
Benveniste, H., Ma, Y., Dhawan, J., Gifford, A. J., Smith, S. D. B., Feinstein, I., Du, C., Grant, S. C., & Hof, P. R. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1379.006 · Cited by 34 · see citing works
Quantitative mouse brain phenotyping based on single and multispectral MR protocols
Badea, A., Gewalt, S. L., Avants, B., Cook, J. J. H., & Johnson, G. A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.07.021 · Cited by 31 · see citing works
Self-citationKerbler, G. M., Hamlin, A. S., Pannek, K., Kurniawan, N. D., Keller, M., Rose, S., & Coulson, E. J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.075 · Cited by 28 · see citing works
In vivo diffusion tensor imaging of amyloid‐β‐induced white matter damage in mice
Sun, S.-W., Liang, H.-F., Mei, J., Xu, D., & Shi, W.-X. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-130236 · Cited by 27 · see citing works
Development of MRI ‐based atlases of non‐human brains
Ullmann, J. F. P., Janke, A. L., Reutens, D. C., & WATSON, C. R. R. (2014) · The Journal of Comparative Neurology · doi:10.1002/cne.23678 · Cited by 26 · see citing works
Dumont, J. R., Amin, E., Wright, N. F., Dillingham, C. M., & Aggleton, J. P. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.10.016 · Cited by 26 · see citing works
Diffusion tensor magnetic resonance imaging of the brain in app transgenic mice: A cohort study.
Müller, H.-P., Kassubek, J., Vernikouskaya, I., Ludolph, A. C., Stiller, D., & Rasche, V. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067630 · Cited by 22 · see citing works
Statistical Voxel-Based Methods and [18F]FDG PET Brain Imaging: Frontiers for the Diagnosis of AD
Gallivanone, F., Rosa, P. A. D., & Castiglioni, I. (2016) · Current Alzheimer Research · doi:10.2174/1567205013666151116142039 · Cited by 19 · see citing works
Altered brain development in an early-onset murine model of Alzheimer's disease
Allemang-Grand, R., Scholz, J., Ellegood, J., Cahill, L. S., Laliberté, C. L., Fraser, P. E., Josselyn, S. A., Sled, J. G., & Lerch, J. P. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.08.032 · Cited by 15 · see citing works
Lyketsos, C. G., Holroyd, K., Fosdick, L., Smith, G. S., Leoutsakos, J., Munro, C. A., Oh, E. S., Drake, K. E., Rosenberg, P., Anderson, W. S., et al. (2015) · Open Access Journal of Clinical Trials · doi:10.2147/oajct.s81542 · Cited by 14 · see citing works
Magnetic Resonance Imaging-Based Mouse Brain Atlas and Its Applications
Aggarwal, M., Zhang, J., & Mori, S. (2010) · Methods in molecular biology · doi:10.1007/978-1-61737-992-5_12 · Cited by 12 · see citing works
Holroyd, K. B., Fosdick, L., Smith, G. S., Leoutsakos, J. M., Munro, C. A., Oh, E. S., Drake, K. E., Rosenberg, P. B., Anderson, W. S., Salloway, S., et al. (2015) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 8 · see citing works
Kärkkäinen, E., Lahtinen, H.-M., Närväinen, J., Gröhn, O. H. J., & Tanila, H. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150059 · Cited by 7 · see citing works
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1 of the 109 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- Fox JGA The Mouse in Biomedical Research [electronic resource]: History, Wild Mice, and Genetics. Elsevier Jan 2007 Ipswich 2007 New York Ebsco Publishing [Distributor]
- Jack CR Jr Petersen RC Xu YC O’Brien PC Smith GE Ivnik RJ Boeve BF Waring SC Tangalos EG Kokmen E Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment Neurology 1999 52 1397 1403 10227624 PMC2730146
- Jack CR Jr Petersen RC Xu YC Waring SC O’Brien PC Tangalos EG Smith GE Ivnik RJ Kokmen E Medial temporal atrophy on MRI in normal aging and very mild Alzheimer’s disease Neurology 1997 49 786 794 9305341 PMC2730601
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Lifespan Changes of the Human Brain In Alzheimer’s Disease
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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 · see citing works
Anderson, R. J., Cook, J. J. H., Delpratt, N. A., Nouls, J. C., Gu, B., McNamara, J. O., Avants, B., Johnson, G. A., & Badea, A. (2018) · Neuroinformatics · doi:10.1007/s12021-018-9410-0 · Cited by 52 · see citing works
Self-citationBinette, A. P., Theaud, G., Rheault, F., Roy, M., Collins, D. L., Levin, J., Mori, H., Lee, J. H., Farlow, M. R., Schofield, P. R., et al. (2021) · eLife · doi:10.7554/elife.62929 · Cited by 57 · see citing works
A White Matter Connection of Schizophrenia and Alzheimer’s Disease
Kochunov, P. V., Zavaliangos‐Petropulu, A., Jahanshad, N., Thompson, P. M., Ryan, M. C., Chiappelli, J., Chen, S., Du, X. M., Hatch, K. S., Adhikari, B. M., et al. (2020) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaa078 · Cited by 55 · see citing works
Ji, F., Pasternak, O., Ng, K. K., Chong, J. S. X., Liu, S., Zhang, L., Shim, H. Y., Loke, Y. M., Tan, B. Y., Venketasubramanian, N., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-41363-2 · Cited by 44 · see citing works
Badea, A., Wu, W., Shuff, J., Wang, M. S., Anderson, R. J., Qi, Y. P., Johnson, G. A., Wilson, J. G., Koudoro, S., Garyfallidis, E., et al. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00072 · Cited by 36 · see citing works
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Infection and inflammation: New perspectives on Alzheimer's disease
Whitson, H. E., Colton, C. A., Khoury, J. B. E., Gate, D., Goate, A., Heneka, M. T., Kaddurah‐Daouk, R., Klein, R. S., Shinohara, M. L., Sisodia, S. S., et al. (2022) · Brain Behavior & Immunity - Health · doi:10.1016/j.bbih.2022.100462 · Cited by 33 · see citing works
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Jullienne, A., Trinh, M. V., & Obenaus, A. (2022) · Biomedicines · doi:10.3390/biomedicines10020305 · Cited by 32 · see citing works
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 33 · see citing works
On the Usage of Brain Atlases in Neuroimaging Research
Hess, A., Hinz, R., Keliris, G. A., & Boehm-Sturm, P. (2018) · Molecular Imaging and Biology · doi:10.1007/s11307-018-1259-y · Cited by 30 · see citing works
Gozdas, E., Fingerhut, H., Chromik, L. C., O'Hara, R. M., Reiss, A. L., & Hosseini, S. M. H. (2020) · Scientific Reports · doi:10.1038/s41598-020-66796-y · Cited by 27 · see citing works
Magnetic resonance imaging of mouse brain networks plasticity following motor learning
Badea, A., Ng, K., Anderson, R. J., Zhang, J., Miller, M. I., & O’Brien, R. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216596 · Cited by 26 · see citing works
Self-citationFalangola, M. F., Nie, X., Ward, R., Dhiman, S., Voltin, J., Nietert, P. J., & Jensen, J. H. (2021) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2021.06.022 · Cited by 25 · see citing works
Contrasting Metabolic Insufficiency in Aging and Dementia
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Synaptic Pruning in Alzheimer’s Disease: Role of the Complement System
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Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice
Falangola, M. F., Nie, X., Ward, R., McKinnon, E. T., Dhiman, S., Nietert, P. J., Helpern, J. A., & Jensen, J. H. (2020) · NMR in Biomedicine · doi:10.1002/nbm.4346 · Cited by 22 · see citing works
Anderson, R. J., Long, C. M., Calabrese, E., Robertson, S. H., Johnson, G. A., Cofer, G. P., O’Brien, R., & Badea, A. (2020) · Frontiers in Physics · doi:10.3389/fphy.2020.00088 · Cited by 22 · see citing works
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Connectome-derived diffusion characteristics of the fornix in Alzheimer's disease
Perea, R. D., Rabin, J. S., Fujiyoshi, M. G., Neal, T. E., Smith, E. E., Dijk, K. R. A. V., & Hedden, T. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.04.029 · Cited by 20 · see citing works
Wang, C., Song, L., Zhang, R., & Gao, F. (2018) · European Radiology Experimental · doi:10.1186/s41747-018-0057-2 · Cited by 16 · see citing works
Marchi, N. A., Daneault, V., André, C., Martineau‐Dussault, M., Baril, A., Thompson, C., Montplaisir, J. Y., Gilbert, D., Lorrain, D., Boré, A., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13833 · Cited by 16 · see citing works
Ou, Y.-N., Ge, Y.-J., Wu, B.-S., Zhang, Y., Jiang, Y.-C., Kuo, K., Yang, L., Tan, L., Feng, J.-F., Cheng, W., et al. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02475-6 · Cited by 16 · see citing works
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Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging
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“Compared to other white matter bundles, fornix may play an important role in AD pathology and can be used as a disease biomarker for pharmacological therapeutics (Badea et al., 2016).”
BackgroundMicrocephaly with altered cortical layering in GIT1 deficiency revealed by quantitative neuroimaging
Badea, A., Schmalzigaug, R., Kim, W., Bonner, P. E., Ahmed, U., Johnson, G. A., Cofer, G. P., Foster, M., Anderson, R. J., Badea, C. T., et al. (2020) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2020.09.023 · Cited by 9 · see citing works
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MRI analysis of brain connectivity in a mouse model of Alzheimer’s disease
Degiorgis, L. (2019) · theses.fr (ABES) · doi:10.70675/5334d86bz9cc5z451cz865fzcf91895a5400 · Cited by 1 · see citing works
An HPC Pipeline with Validation Framework for Small Animal Multivariate Brain Analysis (SAMBA).Preprint
Anderson, R. J., Cook, J. J. H., Delpratt, N. A., Nouls, J. C., Gu, B., McNamara, J. O., Avants, B., Johnson, G. A., & Badea, A. (2017) · arXiv (Cornell University)
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Self-citationBhattrai, A., Raikes, A. C., & Brinton, R. D. (2026) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70325
- Authors
- Badea, A., Kane, L., Anderson, R. J., Qi, Y., Foster, M., Cofer, G. P., Medvitz, N., Buckley, A. F., Badea, A. K., Wetsel, W. C., & Colton, C. A.
- Affiliations
- Duke University (US)
- Duke Medical Center (US)
- Corresponding author
- Badea, Alexandra
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 142
- Pages
- 498-511
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC5159324
- OpenAlex
- W2507413010
- Cited by
- 39
- References
- 109
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 5 · 2020: 7 · 2019: 7 · 2018: 5 · 2017: 1
- FWCI
- 3.49
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (P41 EB015897, 1S10OD010683-01, R01 AG045422, K01 AG041211)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neurological Disease Mechanisms and Treatments
- Keywords
- Alzheimer's disease, fornix, hippocampal atrophy, white matter pathology, fractional anisotropy, g-ratio, axonal degeneration, myelination, microglial activation, cognitive decline, diffusion tensor imaging
- MeSH terms
- Alzheimer Disease, Animals, Atrophy, Disease Models, Animal, Hippocampus, Mice, Transgenic, Microscopy, Electron, Biomarkers, Fornix, Brain, Mice, Diffusion Tensor Imaging, White Matter
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.
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