Long-term effects of amyloid, hypometabolism, and atrophy on neuropsychological functions

Neurology

Volumn 82, Issue 20, 2014, Pages 1768-1775

  Ossenkoppele, Rik ^a,b   Van Der Flier, Wiesje M ^a,b   Verfaillie, Sander C J ^a   Vrenken, Hugo ^a   Versteeg, Adriaan ^a   Van Schijndel, Ronald A ^a   Sikkes, Sietske A ^a,b   Twisk, Jos ^a   Adriaanse, Sofie M ^a,b   Zwan, Marissa D ^a,b   Boellaard, Ronald ^a   Windhorst, Albert D ^a   Barkhof, Frederik ^a   Scheltens, Philip ^b   Lammertsma, Adriaan A ^a   Van Berckel, Bart N M ^a  

^a ACADEMIC MEDICAL CENTER   (Netherlands)

^b VU UNIVERSITY AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

AMYLOID; FLUORODEOXYGLUCOSE F 18; PITTSBURGH COMPOUND B;

ADULT; AGED; ALZHEIMER DISEASE; ARTICLE; ATTENTION; BRAIN ATROPHY; BRAIN SIZE; CLINICAL ARTICLE; COGNITION; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; DISORDERS OF CARBOHYDRATE METABOLISM; EXECUTIVE FUNCTION; FEMALE; FOLLOW UP; GLUCOSE HYPOMETABOLISM; GRAY MATTER; HUMAN; LANGUAGE; LONGITUDINAL STUDY; MALE; MEMORY; MILD COGNITIVE IMPAIRMENT; MINI MENTAL STATE EXAMINATION; NEUROPSYCHOLOGICAL TEST; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; PET SCANNER; POSITRON EMISSION TOMOGRAPHY; PRIORITY JOURNAL;

AGED; AGED, 80 AND OVER; ALZHEIMER DISEASE; AMYLOID; ATROPHY; ATTENTION; BRAIN; COGNITION; DEMENTIA; DISEASE PROGRESSION; EXECUTIVE FUNCTION; FEMALE; GLUCOSE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MILD COGNITIVE IMPAIRMENT; NEUROPSYCHOLOGICAL TESTS;

EID: 84902183814     PISSN: 00283878     EISSN: 1526632X     Source Type: Journal    
DOI: 10.1212/WNL.0000000000000432     Document Type: Article

References (37)

1. Cummings JL. Alzheimer's disease. N Engl J Med 2004; 351:56-67.
2. Hardy JA, Higgins GA. Alzheimer's disease: the amyloid cascade hypothesis. Science 1992;256:184-185.
3. Klunk WE, Engler H, Nordberg A, et al. Imaging brain amyloid in Alzheimer's disease with Pittsburgh compound B. Ann Neurol 2004;55:306-319.
4. Rowe CC, Ellis KA, Rimajova M, et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiol Aging 2010;31: 1275-1283.
5. Aizenstein HJ, Nebes RD, Saxton JA, et al. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch Neurol 2008;65:1509-1517.
6. Morris JC, Roe CM, Grant EA, et al. Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease. Arch Neurol 2009;66:1469-1475.
7. Villemagne VL, Pike K, Chetelat G, et al. Longitudinal assessment of Ab and cognition in aging and Alzheimer disease. Ann Neurol 2011;69:181-192.
8. Doraiswamy PM, Sperling RA, Coleman RE, et al. Amyloid-beta assessed by Florbetapir F18 PET and 18-month cognitive decline: a multicenter study. Neurology 2012;79:1636-1644.
9. Ossenkoppele R, Berckel BNM, Prins N. Amyloid imaging in prodromal Alzheimer's disease. Alzheimers Res Ther 2011;3:26-28.
10. Braskie MN, Thompson JC. Understanding cognitive deficits in Alzheimer's disease based on neuroimaging findings. Trends Cogn Sci 2013;17:510-516.
11. Chetelat G, Villemagne VL, Pike K, et al. Relationships between memory performance and beta-amyloid deposition at different stages of Alzheimer's disease. Neurodegen Dis 2012;10:141-144.
12. Grimmer T, Henriksen G, Wester HJ, et al. Clinical severity of Alzheimer's disease is associated with PIB uptake in PET. Neurobiol Aging 2009;30:1902-1909.
13. Ossenkoppele R, Zwan M, Tolboom N, et al. Amyloid burden and metabolic function in early-onset Alzheimer's disease: parietal lobe involvement. Brain 2012;135: 2115-2125.
14. Jack CR Jr, Knopman D, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013;12:207-216.
15. Ossenkoppele R, Tolboom N, Foster-Dingley JC, et al. Longitudinal imaging of Alzheimer pathology using [11C] PIB, [18F]FDDNP and [18F]FDG PET. Eur J Nucl Med Mol Imaging 2012;39:990-1000.
16. Chetelat G, Desgranges B, de la Sayette V, Viader F, Eustache F, Baron JC. Mild cognitive impairment: can FDG-PET predict who is to rapidly convert to Alzheimer's disease? Neurology 2003;60:1374-1377.
17. Jagust WJ, Landau SM, Shaw LM, et al. Relationships between biomarkers in aging and dementia. Neurology 2009;73:1193-1199.
18. Landau SM, Mintun MA, Joshi AD, et al. Amyloid deposition, hypometabolism, and longitudinal cognitive decline. Ann Neurol 2012;72:578-586.
19. Mormino EC, Kluth JT, Madison CM, et al. Episodic memory loss is related to hippocampal-mediated betaamyloid deposition in elderly subjects. Brain 2009;132: 1310-1323.
20. van der Vlies AE, Staekenborg SS, Admiraal-Behloul F, et al. Associations between magnetic resonance imaging measures and neuropsychological impairment in early and late onset Alzheimer's disease. J Alzheimer Dis 2013;35;169-178.
21. Sluimer JD, Vrenken H, Blankenstein MA, et al. Whole brain atrophy rate in Alzheimer disease: identifying fast progressors. Neurology 2008;70:1836-1841.
22. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. 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. Neurology 1984;34:939-944.
23. Albert MS, DeKosky ST, Dickson DW, et al. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer Dement 2011;7:270-279.
24. Harten A, Visser PJ, Pijnenburg YAL, et al. Cerebrospinal fluid Ab42 is the best predictor of clinical progression in patients with subjective complaints. Alzheimer Dement 2013;9:481-487.
25. Ossenkoppele R, Prins N, Pijnenburg YAL, et al. Impact of molecular imaging on the diagnostic process in a memory clinic. Alzheimer Dement 2013;9: 481-487.
26. Brix G, Zaers J, Adam LE, et al. Performance evaluation of a whole-body PET scanner using the NEMA protocol. J Nucl Med 1997;38:1614-1623.
27. Svarer C, Madsen K, Hasselbalch SG, et al. MR-based automatic delineation of volumes of interest in human brain PET images using probability maps. Neuro Image 2005;24:969-979.
28. Wu Y, Carson R. Noise reduction in the simplified reference tissue model for neuroreceptor functional imaging. J Cereb Blood Flow Metab 2002;22:1440-1452.
29. Yaqub M, Tolboom N, Boellaard R, et al. Simplified parametric methods for [11C]PIB studies. Neuro Image 2008; 42:76-86.
30. Herholz K, Salmon E, Perani D, et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuro Image 2002;17: 302-316.
31. Smith SM, Jenkinson M, Woolrich MW, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuro Image 2004;23:208-219.
32. Smith SM, Zhang Y, Jenkinson M, et al. Accurate, robust and automated longitudinal and cross-sectional brain change analysis. Neuro Image 2002;17:479-489.
33. Popescu V, Battaglini M, Hoogstrate WS, et al. Optimizing parameter choice for FSL-Brain extraction tool (BET) on 3D T1 images in multiple sclerosis. Neuro Image 2012; 61:1484-1494.
34. Forster S, Grimmer T, Miederer I, et al. Regional expansion of hypometabolism in Alzheimer's disease follows amyloid deposition with temporal delay. Biol Psych 2012;481-487.
35. Cover KS, van Schijndel R, van Dijk BW, et al. Assessing the reproducibility of the SienaX and Siena brain atrophy measures using the ADNI back-toback MP-RAGE MRI scans. Psych Res 2011;193: 182-190.
36. Nelson PT, Alafuzoff I, Bigio EH, et al. Correlation of Alzheimer disease neuropathological changes with cognitive status: a review of the literature. J Neuropathol Exp Neurol 2012;71:362-381.
37. Verhage F. In: Van Gorcum, editor. Intelligentie en leeftijd: onderzoek bij Nederlanders van twaalf tot zevenenzeventig jaar [Intelligence and age: study with Dutch people aged 12 to 77]. Assen, 1964.