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 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
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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. |
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| 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 |
| Author_xml | – sequence: 1 givenname: Bradford C 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 – sequence: 2 givenname: David A surname: Wolk fullname: Wolk, David A |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/22189451$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Contributor | Jack, Jr, Clifford R Romirowsky, Aliza Schuff, Norbert Roberts, Peggy Kielb, Stephanie Shaw, Les Johnson, Kris Doody, Rachelle S Frank, Richard Molchan, Susan Chen, Kewei Duara, Ranjan Onyike, Chiadi Arnold, Steven E Jagust, William Mintun, Mark A Petrella, Jeffrey R Green, Robert C Grossman, Hillel Felmlee, Joel Pawluczyk, Sonia de Leon, Mony J Jicha, Greg Weiner, Michael Montine, Tom Dolen, Sara Varon, Daniel Oakley, Mary Ann Thompson, Paul DeCarli, Charles Fox, Nick Griffith, Randall Hardy, Peter Glodzik, Lidia Kachaturian, Zaven Mitsis, Effie Smith, Charles D Rusinek, Henry Wolk, David Korecka, Magdalena Schneider, Stacy Walter, Sarah Quinn, Joseph Bell, Karen L Villanueva-Meyer, Javier Liu, Enchi Bandy, Dan Neu, Scott Sather, Tamie Aisen, Paul Morris, John Stern, Yaakov Lord, Joanne L Marson, Daniel Reiman, Eric M Trojanowki, J Q Morris, John C Lopez, Oscar L Shah, Raj C Kornak, John Foster, Norm Mathis, Chet Foroud, Tatiana M Heidebrink, Judith Lee, Virginia M Y Kaye, Jeffrey Saykin, Andrew J Chowdhury, Munir Harvey, Danielle Koeppe, Robert A Potki |
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| DOI | 10.1212/WNL.0b013e31823efc6c |
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| Discipline | Medicine |
| EISSN | 1526-632X |
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| References_xml | – reference: 11459114 - J Int Neuropsychol Soc. 2001 Jul;7(5):631-9 – 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 – reference: 16389197 - Arch Gen Psychiatry. 2006 Jan;63(1):57-62 – reference: 16801647 - Neurology. 2006 Jun 27;66(12):1837-44 – reference: 9010004 - Brain. 1996 Dec;119 ( Pt 6):2001-7 – reference: 1961359 - Neurobiol Aging. 1991 Jul-Aug;12(4):295-312 – reference: 18632739 - Cereb Cortex. 2009 Mar;19(3):497-510 – reference: 17438217 - Neurology. 2007 Apr 17;68(16):1268-73 – reference: 19296504 - Ann Neurol. 2009 Apr;65(4):403-13 – 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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| 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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