title: MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults.
abstract: 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.
authors.affiliation: 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
authors.forename: Bradford C
authors.initials: BC
authors.lastname: Dickerson
authors.forename: David A
authors.initials: DA
authors.lastname: Wolk
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid* / Q000150:complications / Q000175:diagnosis*; D016229:Amyloid beta-Peptides / Q000134:cerebrospinal fluid; D015415:Biomarkers / Q000134:cerebrospinal fluid; D002540:Cerebral Cortex / Q000473:pathology*; D003072:Cognition Disorders / Q000134:cerebrospinal fluid* / Q000175:diagnosis* / Q000209:etiology; D018450:Disease Progression; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D011569:Psychiatric Status Rating Scales; D012307:Risk Factors
chemical_list: D016229:Amyloid beta-Peptides; D015415:Biomarkers