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Amyloid deposition, hypometabolism, and longitudinal cognitive decline

dc.contributor.authorLandau, Susan M.en_US
dc.contributor.authorMintun, Mark A.en_US
dc.contributor.authorJoshi, Abhinay D.en_US
dc.contributor.authorKoeppe, Robert A.en_US
dc.contributor.authorPetersen, Ronald C.en_US
dc.contributor.authorAisen, Paul S.en_US
dc.contributor.authorWeiner, Michael W.en_US
dc.contributor.authorJagust, William J.en_US
dc.date.accessioned2012-11-07T17:04:31Z
dc.date.available2013-11-15T16:44:23Zen_US
dc.date.issued2012-10en_US
dc.identifier.citationLandau, Susan M.; Mintun, Mark A.; Joshi, Abhinay D.; Koeppe, Robert A.; Petersen, Ronald C.; Aisen, Paul S.; Weiner, Michael W.; Jagust, William J. (2012). "Amyloid deposition, hypometabolism, and longitudinal cognitive decline." Annals of Neurology 72(4): 578-586. <http://hdl.handle.net/2027.42/94245>en_US
dc.identifier.issn0364-5134en_US
dc.identifier.issn1531-8249en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/94245
dc.description.abstractObjective: Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) population, we examined (1) cross‐sectional relationships between amyloid deposition, hypometabolism, and cognition, and (2) associations between amyloid and hypometabolism measurements and longitudinal cognitive measurements. Methods: We examined associations between mean cortical florbetapir uptake, mean 18 F‐fluorodeoxyglucose–positron emission tomography (FDG‐PET) within a set of predefined regions, and Alzhiemer's Disease Assessment Scale (ADAS‐cog) performance in 426 ADNI participants (126 normal, 162 early mild cognitive impairment [EMCI], 85 late MCI [LMCI], 53 Alzheimer disease [AD] patients). For a subset of these (76 normal, 81 LMCI) we determined whether florbetapir and FDG‐PET were associated with retrospective decline in longitudinal ADAS‐cog measurements. Results: Twenty‐nine percent of normal subjects, 43% of EMCI patients, 62% of LMCI patients, and 77% of AD patients were categorized as florbetapir positive. Florbetapir was negatively associated with concurrent FDG and ADAS‐cog in both MCI groups. In longitudinal analyses, florbetapir‐positive subjects in both normal and LMCI groups had greater ongoing ADAS‐cog decline than those who were florbetapir negative. However, in normal subjects, florbetapir positivity was associated with greater ADAS‐cog decline than FDG, whereas in LMCI, FDG positivity was associated with greater decline than florbetapir. Interpretation: Although both hypometabolism and β‐amyloid (Aβ) deposition are detectable in normal subjects and all diagnostic groups, Aβ showed greater associations with cognitive decline in normal participants. In view of the minimal cognitive deterioration overall in this group, this suggests that amyloid deposition has an early and subclinical impact on cognition that precedes metabolic changes. At moderate and later stages of disease (LMCI/AD), hypometabolism becomes more pronounced and more closely linked to ongoing cognitive decline. ANN NEUROL 2012;72:578–586en_US
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.titleAmyloid deposition, hypometabolism, and longitudinal cognitive declineen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelPsychiatryen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Radiology, University of Michigan Medical School, Ann Arbor, MIen_US
dc.contributor.affiliationotherLife Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CAen_US
dc.contributor.affiliationotherVeterans Affairs and University of California at San Francisco, San Francisco, CAen_US
dc.contributor.affiliationotherDepartment of Neurosciences, University of California at San Diego, San Diego, CAen_US
dc.contributor.affiliationotherDepartment of Neurology, Mayo Clinic College of Medicine, Rochester, MNen_US
dc.contributor.affiliationotherHelen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CAen_US
dc.contributor.affiliationotherAvid Radiopharmaceuticals, Inc., Philadelphia, PAen_US
dc.contributor.affiliationother118 Barker Hall MC #3190, UC Berkeley, Berkeley, CA 94720‐3190en_US
dc.contributor.affiliationotherSchool of Public Health, University of California at Berkeley, Berkeley, CAen_US
dc.identifier.pmid23109153en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/94245/1/23650_ftp.pdf
dc.identifier.doi10.1002/ana.23650en_US
dc.identifier.sourceAnnals of Neurologyen_US
dc.identifier.citedreferenceShimada H, Ataka S, Takeuchi J, et al. Pittsburgh compound B‐negative dementia: a possibility of misdiagnosis of patients with non‐Alzheimer disease‐type dementia as having AD. J Geriatr Psychiatry Neurol 2011; 24: 123 – 126.en_US
dc.identifier.citedreferenceOkello A, Koivunen J, Edison P, et al. Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C‐PIB PET study. Neurology 2009; 73: 754 – 760.en_US
dc.identifier.citedreferenceJack CR Jr, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol 2010; 9: 119 – 128.en_US
dc.identifier.citedreferenceForster S, Grimmer T, Miederer I, et al. Regional expansion of hypometabolism in Alzheimer's disease follows amyloid deposition with temporal delay. Biol Psychiatry 2012; 71: 792 – 797.en_US
dc.identifier.citedreferenceEwers M, Insel P, Jagust WJ, et al. CSF biomarker and PIB‐PET‐derived beta‐amyloid signature predicts metabolic, gray matter, and cognitive changes in nondemented subjects. Cereb Cortex, first published online October 29, 2011 doi:10.1093/cercor/bhr271.en_US
dc.identifier.citedreferenceKadir A, Almkvist O, Forsberg A, et al. Dynamic changes in PET amyloid and FDG imaging at different stages of Alzheimer's disease. Neurobiol Aging 2012; 33: 198.e1 – 198.e14.en_US
dc.identifier.citedreferenceOssenkoppele R, Tolboom N, Foster‐Dingley JC, et al. Longitudinal imaging of Alzheimer pathology using [(11)C]PIB, [(18)F]FDDNP and [(18)F]FDG PET. Eur J Nucl Med Mol Imaging 2012; 39: 990 – 1000.en_US
dc.identifier.citedreferenceClark CM, Schneider JA, Bedell BJ, et al. Use of florbetapir‐PET for imaging beta‐amyloid pathology. JAMA 2011; 305: 275 – 283.en_US
dc.identifier.citedreferenceMcKhann G, Drachman D, Folstein M, et al. 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.en_US
dc.identifier.citedreferenceRosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer's disease. Am J Psychiatry 1984; 141: 1356 – 1364.en_US
dc.identifier.citedreferenceAshburner J, Friston KJ. Unified segmentation. Neuroimage 2005; 26: 839 – 851.en_US
dc.identifier.citedreferenceJagust WJ, Landau SM, Shaw LM, et al. Relationships between biomarkers in aging and dementia. Neurology 2009; 73: 1193 – 1199.en_US
dc.identifier.citedreferenceLandau SM, Harvey D, Madison CM, et al. Associations between cognitive, functional, and FDG‐PET measures of decline in AD and MCI. Neurobiol Aging 2011; 32: 1207 – 1218.en_US
dc.identifier.citedreferenceJoshi AD, Pontecorvo MJ, Clark CM, et al. Performance Characteristics of Amyloid PET with Florbetapir F 18 in Patients with Alzheimer's Disease and Cognitively Normal Subjects. J Nucl Med 2012; 53: 378 – 384.en_US
dc.identifier.citedreferenceMormino EC, Kluth JT, Madison CM, et al. Episodic memory loss is related to hippocampal‐mediated beta‐amyloid deposition in elderly subjects. Brain 2009; 132: 1310 – 1323.en_US
dc.identifier.citedreferenceRowe 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.en_US
dc.identifier.citedreferenceMintun MA, Larossa GN, Sheline YI, et al. [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology 2006; 67: 446 – 452.en_US
dc.identifier.citedreferenceFleisher AS, Chen K, Liu X, et al. Using positron emission tomography and florbetapir F18 to image cortical amyloid in patients with mild cognitive impairment or dementia due to Alzheimer disease. Arch Neurol 2011; 68: 1404 – 1411.en_US
dc.identifier.citedreferenceEdison P, Archer HA, Hinz R, et al. Amyloid, hypometabolism, and cognition in Alzheimer disease: an [11C]PIB and [18F]FDG PET study. Neurology 2007; 68: 501 – 508.en_US
dc.identifier.citedreferenceRabinovici GD, Rosen HJ, Alkalay A, et al. Amyloid vs FDG‐PET in the differential diagnosis of AD and FTLD. Neurology 2011; 77: 2034 – 2042.en_US
dc.identifier.citedreferenceMassoud F, Devi G, Stern Y, et al. A clinicopathological comparison of community‐based and clinic‐based cohorts of patients with dementia. Arch Neurol 1999; 56: 1368 – 1373.en_US
dc.identifier.citedreferenceRanginwala NA, Hynan LS, Weiner MF, White CL III. Clinical criteria for the diagnosis of Alzheimer disease: still good after all these years. Am J Geriatr Psychiatry 2008; 16: 384 – 388.en_US
dc.identifier.citedreferenceLim A, Tsuang D, Kukull W, et al. Clinico‐neuropathological correlation of Alzheimer's disease in a community‐based case series. J Am Geriatr Soc 1999; 47: 564 – 569.en_US
dc.identifier.citedreferencePearl GS. Diagnosis of Alzheimer's disease in a community hospital‐based brain bank program. South Med J 1997; 90: 720 – 722.en_US
dc.identifier.citedreferenceChetelat G, Villemagne VL, Pike KE, et al. Relationship between Memory Performance and beta‐Amyloid Deposition at Different Stages of Alzheimer's Disease. Neurodegener Dis 2012; 10: 141 – 144.en_US
dc.identifier.citedreferencePike KE, Ellis KA, Villemagne VL, et al. Cognition and beta‐amyloid in preclinical Alzheimer's disease: data from the AIBL study. Neuropsychologia 2011; 49: 2384 – 2390.en_US
dc.identifier.citedreferenceRodrigue KM, Kennedy KM, Devous MD Sr, et al. β‐Amyloid burden in healthy aging: regional distribution and cognitive consequences. Neurology 2012; 78: 387 – 395.en_US
dc.identifier.citedreferenceJack CR Jr, Lowe VJ, Weigand SD, et al. Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease. Brain 2009; 132 ( pt 5 ): 1355 – 1365.en_US
dc.identifier.citedreferenceResnick SM, Sojkova J, Zhou Y, et al. Longitudinal cognitive decline is associated with fibrillar amyloid‐beta measured by [11C]PiB. Neurology 2010; 74: 807 – 815.en_US
dc.identifier.citedreferenceReiman EM, Chen K, Alexander GE, et al. Functional brain abnormalities in young adults at genetic risk for late‐onset Alzheimer's dementia. Proc Natl Acad Sci U S A 2004; 101: 284 – 289.en_US
dc.identifier.citedreferencePetersen RC. Conceptual overview. In: Petersen RC, ed. Mild cognitive impairment: aging to alzheimer's disease. New York, NY: Oxford University Press, 2003: 1 – 14.en_US
dc.identifier.citedreferenceMosconi L, Mistur R, Switalski R, et al. FDG‐PET changes in brain glucose metabolism from normal cognition to pathologically verified Alzheimer's disease. Eur J Nucl Med Mol Imaging 2009; 36: 811 – 822.en_US
dc.identifier.citedreferenceDrzezga A, Lautenschlager N, Siebner H, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer's disease: a PET follow‐up study. Eur J Nucl Med Mol Imaging 2003; 30: 1104 – 1113.en_US
dc.identifier.citedreferenceLandau SM, Harvey D, Madison CM, et al. Comparing predictors of conversion and decline in mild cognitive impairment. Neurology 2010; 75: 230 – 238.en_US
dc.identifier.citedreferenceStorandt M, Mintun MA, Head D, Morris JC. Cognitive decline and brain volume loss as signatures of cerebral amyloid‐beta peptide deposition identified with Pittsburgh compound B: cognitive decline associated with Abeta deposition. Arch Neurol 2009; 66: 1476 – 1481.en_US
dc.identifier.citedreferenceVillemagne VL, Pike KE, Chetelat G, et al. Longitudinal assessment of Abeta and cognition in aging and Alzheimer disease. Ann Neurol 2011; 69: 181 – 192.en_US
dc.identifier.citedreferenceJack CR Jr, Wiste HJ, Vemuri P, et al. Brain beta‐amyloid measures and magnetic resonance imaging atrophy both predict time‐to‐progression from mild cognitive impairment to Alzheimer's disease. Brain 2010; 133: 3336 – 3348.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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