MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults

New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD woul...

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Veröffentlicht in:Neurology Jg. 78; H. 2; S. 84
Hauptverfasser: Dickerson, Bradford C, Wolk, David A
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 10.01.2012
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ISSN:1526-632X, 1526-632X
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Abstract New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD would be at elevated risk for cognitive decline. The Alzheimer's Disease Neuroimaging Initiative database was interrogated for CN individuals. MRI data were processed using a published set of a priori regions of interest to derive a single measure known as the AD signature (ADsig). Each individual was classified as ADsig-low (≥ 1 SD below the mean: high risk for preclinical AD), ADsig-average (within 1 SD of mean), or ADsig-high (≥ 1 SD above mean). A 3-year cognitive decline outcome was defined a priori using change in Clinical Dementia Rating sum of boxes and selected neuropsychological measures. Individuals at high risk for preclinical AD were more likely to experience cognitive decline, which developed in 21% compared with 7% of ADsig-average and 0% of ADsig-high groups (p = 0.03). Logistic regression demonstrated that every 1 SD of cortical thinning was associated with a nearly tripled risk of cognitive decline (p = 0.02). Of those for whom baseline CSF data were available, 60% of the high risk for preclinical AD group had CSF characteristics consistent with AD while 36% of the ADsig-average and 19% of the ADsig-high groups had such CSF characteristics (p = 0.1). This approach to the detection of individuals at high risk for preclinical AD-identified in single CN individuals using this quantitative ADsig MRI biomarker-may provide investigators with a population enriched for AD pathobiology and with a relatively high likelihood of imminent cognitive decline consistent with prodromal AD.
AbstractList New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD would be at elevated risk for cognitive decline.OBJECTIVENew preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD would be at elevated risk for cognitive decline.The Alzheimer's Disease Neuroimaging Initiative database was interrogated for CN individuals. MRI data were processed using a published set of a priori regions of interest to derive a single measure known as the AD signature (ADsig). Each individual was classified as ADsig-low (≥ 1 SD below the mean: high risk for preclinical AD), ADsig-average (within 1 SD of mean), or ADsig-high (≥ 1 SD above mean). A 3-year cognitive decline outcome was defined a priori using change in Clinical Dementia Rating sum of boxes and selected neuropsychological measures.METHODSThe Alzheimer's Disease Neuroimaging Initiative database was interrogated for CN individuals. MRI data were processed using a published set of a priori regions of interest to derive a single measure known as the AD signature (ADsig). Each individual was classified as ADsig-low (≥ 1 SD below the mean: high risk for preclinical AD), ADsig-average (within 1 SD of mean), or ADsig-high (≥ 1 SD above mean). A 3-year cognitive decline outcome was defined a priori using change in Clinical Dementia Rating sum of boxes and selected neuropsychological measures.Individuals at high risk for preclinical AD were more likely to experience cognitive decline, which developed in 21% compared with 7% of ADsig-average and 0% of ADsig-high groups (p = 0.03). Logistic regression demonstrated that every 1 SD of cortical thinning was associated with a nearly tripled risk of cognitive decline (p = 0.02). Of those for whom baseline CSF data were available, 60% of the high risk for preclinical AD group had CSF characteristics consistent with AD while 36% of the ADsig-average and 19% of the ADsig-high groups had such CSF characteristics (p = 0.1).RESULTSIndividuals at high risk for preclinical AD were more likely to experience cognitive decline, which developed in 21% compared with 7% of ADsig-average and 0% of ADsig-high groups (p = 0.03). Logistic regression demonstrated that every 1 SD of cortical thinning was associated with a nearly tripled risk of cognitive decline (p = 0.02). Of those for whom baseline CSF data were available, 60% of the high risk for preclinical AD group had CSF characteristics consistent with AD while 36% of the ADsig-average and 19% of the ADsig-high groups had such CSF characteristics (p = 0.1).This approach to the detection of individuals at high risk for preclinical AD-identified in single CN individuals using this quantitative ADsig MRI biomarker-may provide investigators with a population enriched for AD pathobiology and with a relatively high likelihood of imminent cognitive decline consistent with prodromal AD.CONCLUSIONSThis approach to the detection of individuals at high risk for preclinical AD-identified in single CN individuals using this quantitative ADsig MRI biomarker-may provide investigators with a population enriched for AD pathobiology and with a relatively high likelihood of imminent cognitive decline consistent with prodromal AD.
New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD would be at elevated risk for cognitive decline. The Alzheimer's Disease Neuroimaging Initiative database was interrogated for CN individuals. MRI data were processed using a published set of a priori regions of interest to derive a single measure known as the AD signature (ADsig). Each individual was classified as ADsig-low (≥ 1 SD below the mean: high risk for preclinical AD), ADsig-average (within 1 SD of mean), or ADsig-high (≥ 1 SD above mean). A 3-year cognitive decline outcome was defined a priori using change in Clinical Dementia Rating sum of boxes and selected neuropsychological measures. Individuals at high risk for preclinical AD were more likely to experience cognitive decline, which developed in 21% compared with 7% of ADsig-average and 0% of ADsig-high groups (p = 0.03). Logistic regression demonstrated that every 1 SD of cortical thinning was associated with a nearly tripled risk of cognitive decline (p = 0.02). Of those for whom baseline CSF data were available, 60% of the high risk for preclinical AD group had CSF characteristics consistent with AD while 36% of the ADsig-average and 19% of the ADsig-high groups had such CSF characteristics (p = 0.1). This approach to the detection of individuals at high risk for preclinical AD-identified in single CN individuals using this quantitative ADsig MRI biomarker-may provide investigators with a population enriched for AD pathobiology and with a relatively high likelihood of imminent cognitive decline consistent with prodromal AD.
Author Dickerson, Bradford C
Wolk, David A
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  surname: Dickerson
  fullname: Dickerson, Bradford C
  email: USA.bradd@nmr.mgh.harvard.edu
  organization: Frontotemporal Dementia Unit, Department of Neurology, Massachusetts Alzheimer's Disease Research Center, and Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, USA.bradd@nmr.mgh.harvard.edu
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/22189451$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
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Smith, Charles D
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Wolk, David
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Quinn, Joseph
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Villanueva-Meyer, Javier
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– reference: 21514248 - Alzheimers Dement. 2011 May;7(3):280-92
– reference: 8232972 - Neurology. 1993 Nov;43(11):2412-4
– reference: 9153461 - Neurology. 1997 May;48(5):1297-304
– reference: 18809227 - Neurobiol Aging. 2010 Jul;31(7):1099-106
– reference: 17562935 - Arch Neurol. 2007 Jun;64(6):862-71
– reference: 18814937 - Neurobiol Aging. 2010 Jul;31(7):1077-88
– reference: 21181717 - Ann Neurol. 2010 Dec;68(6):825-34
– reference: 19376612 - Neurobiol Aging. 2009 Jul;30(7):1026-36
– reference: 3185902 - Neurology. 1988 Nov;38(11):1682-7
– reference: 15236399 - Ann Neurol. 2004 Jul;56(1):27-35
– reference: 20008650 - Arch Neurol. 2009 Dec;66(12):1469-75
– reference: 17846109 - J Neurol Neurosurg Psychiatry. 2008 Jun;79(6):630-5
– reference: 19109536 - Neurology. 2009 Mar 24;72(12):1048-55
– reference: 18302232 - J Magn Reson Imaging. 2008 Apr;27(4):685-91
– reference: 11476837 - Lancet. 2001 Jul 21;358(9277):201-5
– reference: 22189450 - Neurology. 2012 Jan 10;78(2):80-1
– reference: 11559310 - Arch Neurol. 2001 Sep;58(9):1395-402
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– reference: 16801647 - Neurology. 2006 Jun 27;66(12):1837-44
– reference: 9010004 - Brain. 1996 Dec;119 ( Pt 6):2001-7
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– reference: 18632739 - Cereb Cortex. 2009 Mar;19(3):497-510
– reference: 17438217 - Neurology. 2007 Apr 17;68(16):1268-73
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– reference: 16247049 - Neurology. 2005 Oct 25;65(8):1227-31
– reference: 20479234 - Proc Natl Acad Sci U S A. 2010 Jun 1;107(22):10256-61
– reference: 20934914 - Lancet Neurol. 2010 Nov;9(11):1118-27
– reference: 20562467 - J Neurol Neurosurg Psychiatry. 2011 Jan;82(1):45-51
– reference: 8618671 - Neurology. 1996 Mar;46(3):707-19
– reference: 19260027 - Ann Neurol. 2009 Feb;65(2):176-83
– reference: 21490323 - Neurology. 2011 Apr 19;76(16):1395-402
– reference: 18056553 - Arch Gen Psychiatry. 2007 Dec;64(12):1443-50
– reference: 12557284 - Ann Neurol. 2003 Feb;53(2):181-8
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Snippet New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these...
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StartPage 84
SubjectTerms Aged
Aged, 80 and over
Alzheimer Disease - cerebrospinal fluid
Alzheimer Disease - complications
Alzheimer Disease - diagnosis
Amyloid beta-Peptides - cerebrospinal fluid
Biomarkers - cerebrospinal fluid
Cerebral Cortex - pathology
Cognition Disorders - cerebrospinal fluid
Cognition Disorders - diagnosis
Cognition Disorders - etiology
Disease Progression
Female
Humans
Magnetic Resonance Imaging
Male
Neuropsychological Tests
Predictive Value of Tests
Psychiatric Status Rating Scales
Risk Factors
Title MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults
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