|Title||MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults.|
|Publication Type||Journal Article|
|Year of Publication||2012|
|Authors||Dickerson, BC, Wolk, DA|
|Corporate Authors||Alzheimer's Disease Neuroimaging Initiative|
|Date Published||2012 Jan 10|
|Keywords||Aged, Aged, 80 and over, Alzheimer Disease, Amyloid beta-Peptides, Biomarkers, Cerebral Cortex, Cognition Disorders, Disease Progression, Female, Humans, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Predictive Value of Tests, Psychiatric Status Rating Scales, Risk Factors|
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: 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.
|PubMed Central ID||PMC3466670|
|Grant List||K01 AG030514 / AG / NIA NIH HHS / United States |
K23-AG028018 / AG / NIA NIH HHS / United States
P30 AG010129 / AG / NIA NIH HHS / United States
P30 AG019610 / AG / NIA NIH HHS / United States
P30AG010124 / AG / NIA NIH HHS / United States
P50-AG005134 / AG / NIA NIH HHS / United States
R01 AG012101 / AG / NIA NIH HHS / United States
R01 AG022374 / AG / NIA NIH HHS / United States
R01-AG29411 / AG / NIA NIH HHS / United States
R21-AG29840 / AG / NIA NIH HHS / United States
U01 AG024904 / AG / NIA NIH HHS / United States
UL1 RR033173 / RR / NCRR NIH HHS / United States