Cited by 161Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsCancer-related cognitive impairment studies

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Brain structural alterations before mild cognitive impairment

Smith, C. D., Chebrolu, H., Wekstein, D. R., Schmitt, F. A., Jicha, G. A., Cooper, G., Markesbery, W. R.·2007·Neurology

DOI 10.1212/01.wnl.0000259542.54830.34

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Abstract

OBJECTIVE: To determine whether alterations of brain structure in normal aged individuals precede the development of mild cognitive impairment (MCI) or Alzheimer disease (AD). BACKGROUND: Persons with MCI and AD demonstrate cortical volume losses vs asymptomatic aged individuals, particularly in the hippocampus, amygdala, and entorhinal cortex. It is unknown whether these losses or other volumetric changes are present, and to what degree, in cognitively normal individuals before the clinical diagnosis of MCI. METHODS: Structural MRI was performed on a cross-section of 136 longitudinally examined normal aged subjects. All subjects were cognitively normal at the time of their scan, but 23 later developed MCI, and 9 of these 23 went on to an AD diagnosis. Extracted volumes from voxel-based morphometric analysis were combined with clinical data to compare the 23 subjects who eventually developed MCI to 113 subjects who remained cognitively normal over an average follow-up of 5.4 years. RESULTS: Initially normal subjects who eventually developed MCI demonstrated decreased gray matter volumes in the anteromedial temporal lobes bilaterally and left angular gyrus while still cognitively normal. CONCLUSION: Structural brain changes in anatomic areas involved in higher cognitive processes precede clinical signs and symptoms in longitudinally followed normal subjects destined to develop mild cognitive impairment.

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Clinical diagnosis of Alzheimer's disease: Report of the NINCDS‐ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Mild Cognitive Impairment: Clinical Characterization and Outcome
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999) · Archives of Neurology · doi:10.1001/archneur.56.3.303 · Cited by 8,980
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
Mild cognitive impairment – Beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment.
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L. ‐., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., et al. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01380.x · Cited by 4,946
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
A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0786 · Cited by 4,561
Frequency of Stages of Alzheimer-Related Lesions in Different Age Categories
Braak, H., & Braak, E. (1997) · Neurobiology of Aging · doi:10.1016/s0197-4580(97)00056-0 · Cited by 1,656
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
Preclinical Evidence of Alzheimer's Disease in Persons Homozygous for the ε4 Allele for Apolipoprotein E
Reiman, E. M., Caselli, R. J., Yun, L. S., Chen, K., Bandy, D., Minoshima, S., Thibodeau, S. N., & Osborne, D. (1996) · New England Journal of Medicine · doi:10.1056/nejm199603213341202 · Cited by 1,366
Voxel-Based Morphometry of the Human Brain: Methods and Applications
Mechelli, A., Price, C. J., Friston, K. J., & Ashburner, J. (2005) · Current Medical Imaging Formerly Current Medical Imaging Reviews · doi:10.2174/1573405054038726 · Cited by 894

Show all 49 references

Research works printed but not linked: 4

Petersen RC. Clinical subtypes of Alzheimer's disease. Dement Geriatr Cogn Disord 1998;9 Suppl 3:16–24.
Morris JC. Mild cognitive impairment and preclinical Alzheimer's disease. Geriatrics 2005;Suppl:9–14.
Menzel HJ, Kladetzky RG, Assmann G. Apolipoprotein E polymorphism and coronary artery disease. Arteriosclerosis 1983;3:310–315.
Braak H, Braak E. Alzheimer's disease starts in early adulthood. Neurobiol Aging 1998;19:S78.

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Bastos, P. A. D., Ferreira, R. M., Manadas, B. J., Moreira, P. I., & Vitorino, R. M. P. (2017) · Critical Reviews in Clinical Laboratory Sciences · doi:10.1080/10408363.2017.1299682 · Cited by 40
Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early Alzheimer’s disease
Xie, L., Das, S. R., Wisse, L. E. M., Ittyerah, R., de Florès, R., Shaw, L. M. J., Yushkevich, P. A., Wolk, D. A., & Initiative, A. D. N. (2023) · Alzheimer s Research & Therapy · doi:10.1186/s13195-023-01210-z · Cited by 50
Alzheimer’s disease in late-life dementia: A minor toxic consequence of devastating cerebrovascular dysfunction
Henry–Feugeas, M.-C. (2007) · Medical Hypotheses · doi:10.1016/j.mehy.2007.07.027 · Cited by 38
Staging Neurodegenerative Disorders: Structural, Regional, Biomarker, and Functional Progressions
Archer, T., Kostrzewa, R. M., Beninger, R. J., & Palomo, T. (2011) · Neurotoxicity Research · doi:10.1007/s12640-010-9190-2 · Cited by 34
Molecular targets and therapeutic interventions for iron induced neurodegeneration
Bagwe‐Parab, S., & Kaur, G. (2019) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2019.12.011 · Cited by 33
MRI of the ‘Alzheimer syndrome’
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Promising Genetic Biomarkers of Preclinical Alzheimer's Disease: The Influence ofAPOEandTOMM40on Brain Integrity
Ferencz, B., Karlsson, S., & Kalpouzos, G. (2012) · International Journal of Alzheimer s Disease · doi:10.1155/2012/421452 · Cited by 35
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Gold, B. T., Jiang, Y., Jicha, G. A., & Smith, C. D. (2010) · Human Brain Mapping · doi:10.1002/hbm.20932 · Cited by 27
Self-citation
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Mild cognitive impairment and on to dementia
Knopman, D. S. (2010) · Neurology · doi:10.1212/wnl.0b013e3181d5dc61 · Cited by 21
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Cognitive changes in mild cognitive impairment patients with impaired visual recognition memory.
Anna, F. D., Félician, O., Barbeau, E. J., Mancini, J., Didic, M., & Ceccaldi, M. P. (2013) · Neuropsychology · doi:10.1037/neu0000032 · Cited by 20
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Azevedo, T., Bethlehem, R. A. I., Whiteside, D. J., Swaddiwudhipong, N., Rowe, J. B., Lió, P., Rittman, T., Initiative, T. A. D. N., Silbert, L. C., Lind, B., et al. (2023) · Communications Medicine · doi:10.1038/s43856-023-00313-w · Cited by 17
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Pachter, D., Kaplan, A., Tsaban, G., Zelicha, H., Meir, A. Y., Rinott, E., Levakov, G., Salti, M., Yovell, Y., Hühn, S., et al. (2024) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2024.09.013 · Cited by 16
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Cooley, S., Paul, R. H., Fennema‐Notestine, C., Morgan, E. E., Vaida, F., Deng, Q., Chen, J. A., Letendre, S. L., Ellis, R. J., Clifford, D. B., et al. (2016) · Journal of NeuroVirology · doi:10.1007/s13365-016-0434-7 · Cited by 16

Authors: Smith, C. D., Chebrolu, H., Wekstein, D. R., Schmitt, F. A., Jicha, G. A., Cooper, G., & Markesbery, W. R.
Affiliations: From the Departments of Neurology (C.D.S., H.C., F.A.S., G.A.J., W.R.M.), Anatomy and Neurobiology (C.D.S., W.R.M.), Pathology (W.R.M.), Behavioral Science (F.A.S.), Psychiatry (F.A.S.), and Psychology (F.A.S.), Magnetic Resonance Imaging and Spectroscopy Center (C.D.S., H.C.), and Alzheimer's Disease Center and Sanders-Brown Center on Aging (C.D.S., D.R.W., F.A.S., G.A.J., G.C., W.R.M.), University of Kentucky College of Medicine, Lexington.
ORCID: Smith, C. D.
Schmitt, F. A.
Jicha, G. A.
Cooper, G.
Venue: Neurology
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2007-04-17
Volume: 68
Issue: 16
Pages: 1268-1273
ISSN: 0028-3878 (ISSN-L)
1526-632X
DOI: 10.1212/01.wnl.0000259542.54830.34
OpenAlex: W2020623898
Cited by: 161
References: 49
Citations by year: 2026: 4 · 2025: 8 · 2024: 7 · 2023: 7 · 2022: 5 · 2021: 4 · 2020: 7 · 2019: 8 · 2018: 5 · 2017: 2 · 2016: 7 · 2015: 7 · 2014: 7 · 2013: 13 · 2012: 14
FWCI: 7.87
Type: journal article
Language: en
Open access: closed
Locations: Neurology (publishedVersion)
PubMed (publishedVersion)
Funders: University of Kentucky
National Institute on Aging (P30AG028383)
National Institute of Neurological Disorders and Stroke (5R01 NS-36660, R01NS036660)
National Center for Research Resources (5M01RR02602, M01RR002602)
Topics: Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
Health Sciences › Medicine › Oncology › Cancer-related cognitive impairment studies
Keywords: mild cognitive impairment, Alzheimer's disease, brain structural changes, gray matter loss, angular gyrus, hippocampus, amygdala, entorhinal cortex, normal aging, prodromal Alzheimer's disease, voxel-based morphometry
MeSH terms: Aged, Aged, 80 and over, Aging, Alzheimer Disease, Brain, Cognition, Cognition Disorders, Cross-Sectional Studies, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Neural Pathways, Parietal Lobe, Predictive Value of Tests, Temporal Lobe, Disease Progression

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Brain structural alterations before mild cognitive impairment

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