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Cited by 154Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsCancer-related cognitive impairment studies

Serial MRI and CSF biomarkers in normal aging, MCI, and AD

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Vemuri, P., Wiste, H.J., Weigand, S.D., Knopman, D.S., Trojanowski, J.Q., Shaw, L.M., Bernstein, M.A., Aisen, P.S. +3 more·2010·Neurology
DOI 10.1212/wnl.0b013e3181e7ca82PMC PMC2905929
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Abstract

OBJECTIVE: To compare the annual change in MRI and CSF biomarkers in cognitively normal (CN), amnestic mild cognitive impairment (aMCI), and Alzheimer disease (AD). Comparisons were based on intergroup discrimination, correlation with concurrent cognitive/functional changes, relationships to APOE genotype, and sample sizes for clinical trials. METHODS: We used data from the Alzheimer's Disease Neuroimaging Initiative study consisting of CN, aMCI, and AD cohorts with both baseline and 12-month follow-up CSF and MRI. The annual change in CSF (total-tau [t-tau], Abeta(1-42)) and MRI (change in ventricular volume) was obtained in 312 subjects (92 CN, 149 aMCI, 71 AD). RESULTS: There was no significant average annual change in either CSF biomarker in any clinical group except t-tau in CN; moreover, the annual change did not differ by clinical group in pairwise comparisons. In contrast, annual increase in ventricular volume increased in the following order, AD > aMCI > CN, and differences were significant between all clinical groups in pairwise comparisons. Ventricular volume increase correlated with concurrent worsening on cognitive/functional indices in aMCI and AD whereas evidence of a similar correlation with change in CSF measures was unclear. The annual changes in MRI differed by APOE epsilon4 status overall and among aMCI while annual changes in CSF biomarkers did not. Estimated sample sizes for clinical trials are notably less for MRI than the CSF or clinical measures. CONCLUSIONS: Unlike the CSF biomarkers evaluated, changes in serial structural MRI are correlated with concurrent change on general cognitive and functional indices in impaired subjects, track with clinical disease stage, and are influenced by APOE genotype.

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  • A number of studies have suggested that CSF markers in combination with neuroimaging and neuropsychological tools add to the accuracy of AD diagnosis.

    “A number of studies have suggested that CSF markers in combination with neuroimaging and neuropsychological tools add to the accuracy of AD diagnosis (Richard et al., 2013; Schuff et al., 2009; Vemuri et al., 2010).”

    From T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease (2015) · cites this paper as Vemuri et al., 2010

    The discussion (pp. 143–151; passage does not identify a specific page) says MRI and CSF biomarkers are both needed to characterize different aspects of AD pathology, and the Methods describes cognitive assessments alongside both biomarkers. But the paper does not show that combining these tools improves the accuracy of AD diagnosis; its reported discrimination analyses assess changes in the biomarkers separately. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 34

  1. sation and holds stock options in Saladax Biomedical. Dr. Bernstein serves as an Associate Editor of Medical Physics and on the editorial board of Magnetic Resonance in Medicine; may accrue revenue on patents re: Under-sampled 3D MRI using a shells k-space sampling trajectory, Mo- tion correction of magnetic resonance images, MRI RF power monitor, and Method of performing magnetic resonance angiography using two- dimensional imaging and de-rated gradients; receives royalties from the publication of Handbook of MRI Pulse Sequences (Elsevier's Academic Press, 2004), Thinking About Equations: A Practical Guide for Develop- ing Mathematical Intuition in the Physical Sciences and Engineering (John Wiley and Sons, 2009); and receives research support from Pfizer Inc and from the NIH (NIA AG24904-01 [Co-I]).
  2. and from the State of California; and holds stock in Synarc and Elan Corporation. Dr. Petersen serves on scientific advisory boards for Elan Corporation, Wyeth, and GE Healthcare; receives royalties from the pub- lication of Mild Cognitive Impairment (Oxford University Press, 2003);
  3. Blennow K, Wallin A, Agren H, Spenger C, Siegfried J, Vanmechelen E. Tau protein in cerebrospinal fluid: a bio- chemical marker for axonal degeneration in Alzheimer dis- ease? Mol Chem Neuropathol 1995;26:231-245.
  4. Bobinski M, de Leon MJ, Wegiel J, et al. The histological validation of post mortem magnetic resonance imaging- determined hippocampal volume in Alzheimer's disease. Neuroscience 2000;95:721-725.
  5. Dubois B, Feldman HH, Jacova C, et al. Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 2007;6:734 - 746.
  6. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state": a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189 - 198.
  7. Hughes CP, Berg L, Danziger WL, Coben LA, Martin RL. A new clinical scale for the staging of dementia. Br J Psy- chiatry 1982;140:566 -572.
  8. Rosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer's disease. Am J Psychiatry 1984;141:1356 - 1364.
  9. Freeborough PA, Fox NC. The boundary shift integral: an accurate and robust measure of cerebral volume changes from registered repeat MRI. IEEE Trans Med Imaging 1997;16:623-629.
  10. Fagan AM, Head D, Shah AR, et al. Decreased cerebrospi- nal fluid Abeta(42) correlates with brain atrophy in cogni- tively normal elderly. Ann Neurol 2009;65:176 -183.
  11. Ingelsson M, Fukumoto H, Newell KL, et al. Early Abeta accumulation and progressive synaptic loss, gliosis, and tangle formation in AD brain. Neurology 2004;62:925- 931.
  12. Jack CR Jr, Lowe VJ, Weigand SD, et al. Serial PIB and MRI in normal, mild cognitive impairment and Alzhei- mer's disease: implications for sequence of pathological events in Alzheimer's disease. Brain 2009;132:1355-1365.
  13. Mormino EC, Kluth JT, Madison CM, et al. Episodic memory loss is related to hippocampal-mediated ␤-amyloid deposition in elderly subjects. Brain 2008;132: 1310 -1323.
  14. Fagan AM, Mintun MA, Mach RH, et al. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol 2006;59:512-519.
  15. Wahlund LO, Blennow K. Cerebrospinal fluid biomarkers for disease stage and intensity in cognitively impaired pa- tients. Neurosci Lett 2003;339:99 -102.
  16. Andersson C, Blennow K, Almkvist O, et al. Increasing CSF phospho-tau levels during cognitive decline and pro- gression to dementia. Neurobiol Aging 2008;29:1466 - 1473.
  17. Engler H, Forsberg A, Almkvist O, et al. Two-year follow-up of amyloid deposition in patients with Alzhei- mer's disease. Brain 2006;129:2856 -2866.
  18. Vemuri P, Wiste HJ, Weigand SD, et al. MRI and CSF biomarkers in normal, MCI, and AD subjects: diagnostic discrimination and cognitive correlations. Neurology 2009;73:287-293.
  19. Mitchell TW, Mufson EJ, Schneider JA, et al. Parahip- pocampal tau pathology in healthy aging, mild cognitive impairment, and early Alzheimer's disease. Ann Neurol 2002;51:182-189.
  20. Sunderland T, Wolozin B, Galasko D, et al. Longitudinal stability of CSF tau levels in Alzheimer patients. Biol Psy- chiatry 1999;46:750 -755.
  21. Gosche KM, Mortimer JA, Smith CD, Markesbery WR, Snowdon DA. Hippocampal volume as an index of Alzhei- mer neuropathology: findings from the Nun Study. Neu- rology 2002;58:1476 -1482.
  22. Jack CR Jr, Dickson DW, Parisi JE, et al. Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology 2002;58:750 - 757.
  23. Fox NC, Schott JM. Imaging cerebral atrophy: normal ageing to Alzheimer's disease. Lancet 2004;363:392-394.
  24. Scahill RI, Schott JM, Stevens JM, Rossor MN, Fox NC. Mapping the evolution of regional atrophy in Alzheimer's disease: unbiased analysis of fluid-registered serial MRI. Proc Natl Acad Sci USA 2002;99:4703-4707.
  25. de Leon MJ, Convit A, George AE, et al. In vivo structural studies of the hippocampus in normal aging and in incipi- ent Alzheimer's disease. Ann NY Acad Sci 1996;777:1-13.
  26. Nestor SM, Rupsingh R, Borrie M, et al. Ventricular enlarge- ment as a possible measure of Alzheimer's disease progression validated using the Alzheimer's disease neuroimaging initia- tive database. Brain 2008;131:2443-2454.
  27. Evans MC, Barnes J, Nielsen C, et al. Volume changes in Alzheimer's disease and mild cognitive impairment: cogni- tive associations. Eur Radiol 2010;20:674 -682.
  28. van de Pol LA, van der Flier WM, Korf ES, Fox NC, Barkhof F, Scheltens P. Baseline predictors of rates of hip- pocampal atrophy in mild cognitive impairment. Neurol- ogy 2007;69:1491-1497.
  29. Stoub TR, Bulgakova M, Leurgans S, et al. MRI predictors of risk of incident Alzheimer disease: a longitudinal study. Neurology 2005;64:1520 -1524.
  30. Jack CR Jr, Slomkowski M, Gracon S, et al. MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD. Neurology 2003;60:253-260.
  31. Schott JM, Frost C, Whitwell JL, et al. Combining short interval MRI in Alzheimer's disease: implications for ther- apeutic trials. J Neurol 2006;253:1147-1153.
  32. Fox NC, Cousens S, Scahill R, Harvey RJ, Rossor MN. Using serial registered brain magnetic resonance imaging to measure disease progression in Alzheimer disease: power calculations and estimates of sample size to detect treat- ment effects. Arch Neurol 2000;57:339 -344.
  33. Hua X, Leow AD, Lee S, et al. 3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impair- ment using tensor-based morphometry. Neuroimage 2008;41:19 -34.
  34. Jack CR Jr, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer's patholog- ical cascade. Lancet Neurol 2010;9:119 -128.

Cited by

Sorted by citations

Authors
Vemuri, P., Wiste, H. J., Weigand, S. D., Knopman, D. S., Trojanowski, J. Q., Shaw, L. M., Bernstein, M. A., Aisen, P. S., Weiner, M., Petersen, R. C., & Jack, C. R.
Affiliations
Mayo Clinic (US)
ORCID
Venue
Neurology
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2010-07-13
Volume
75
Issue
2
Pages
143-151
ISSN
  • 0028-3878 (ISSN-L)
  • 1526-632X
DOI
10.1212/wnl.0b013e3181e7ca82
PMC
PMC2905929
OpenAlex
W2112691652
Cited by
154
References
8
Citations by year
2025: 5 · 2024: 2 · 2023: 3 · 2022: 1 · 2021: 6 · 2020: 8 · 2019: 3 · 2018: 5 · 2017: 10 · 2016: 9 · 2015: 9 · 2014: 18 · 2013: 13 · 2012: 23
FWCI
16.40
Type
journal article
Language
en
Open access
Locations
  • Neurology (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Foundation for the National Institutes of Health (C06 RR018898)
  • Alzheimer's Association
  • Richard and Susan Smith Family Foundation
  • Bristol-Myers Squibb
  • Eli Lilly and Company
  • Pfizer
  • AstraZeneca
  • GlaxoSmithKline
  • Novartis
  • Mayo Foundation for Medical Education and Research
  • Synarc
  • Elan
  • Eisai
  • National Institutes of Health (5u01ag024904-10, AG11378)
  • Genentech
  • National Institute on Aging (U01-AG-024904, R01AG11378, U01 AG024904-01, U01‐AG10483, P50‐AG16574, U01AG06786, P50-AG23501, RC1AG035427, AG24904-01, P01 AG 17586-10, R01AG030048, AG 024904, UO1AG029213-01, P30AG036468, U01AG016976, U01AG006786, 1 U01 AG 024904-05, P30AG010124, P01AG009215, P30 AG 10124-18, P01AG017586, U01AG010483, R01AG011378, 1P01 AG-19724-07, U01AG029213, AG023195, AG-11378, R01AG016381, R01AG023195, R01AG010897, U19AG010483, P01-AG19724, P01 AG 09215-20, R01-AG 10897, P01AG012435, P01AG019724, P50AG023501, R01 AG16381, P50AG016574)
  • National Heart, Lung, and Blood Institute (R01 HL70825, R01HL070825)
  • National Institute of Neurological Disorders and Stroke (P50NS053488, RC2NS069368, R01NS031966)
  • National Center for Research Resources (P41RR023953, C06RR018898, R24 RR021992)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
Keywords
Alzheimer's disease, amnestic mild cognitive impairment, normal aging, serial MRI, cerebrospinal fluid biomarkers, total tau, amyloid-beta 42, ventricular volume, APOE ε4, longitudinal change, cognitive decline, clinical trial sample size, Alzheimer's Disease Neuroimaging Initiative
MeSH terms
Age Factors, Aged, Aged, 80 and over, Aging, Alzheimer Disease, Apolipoproteins E, Brain, Cognition Disorders, Female, Humans, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Peptide Fragments, Reference Values, Regression Analysis, Severity of Illness Index, Biomarkers, Amyloid beta-Peptides, tau Proteins, Genetic Predisposition to Disease

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