title: Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults.
abstract: OBJECTIVE
  Since Alzheimer disease (AD) neuropathology is thought to develop years before dementia, it may be possible to detect subtle AD-related atrophy in preclinical AD. Here we hypothesized that the "disease signature" of AD-related cortical thinning, previously identified in patients with mild AD dementia, would be useful as a biomarker to detect anatomic abnormalities consistent with AD in cognitively normal (CN) adults who develop AD dementia after longitudinal follow-up.
  
  
  METHODS
  We studied 2 independent samples of adults who were CN when scanned. In sample 1, 8 individuals developing AD dementia (CN-AD converters) after an average of 11.1 years were compared to 25 individuals who remained CN (CN-stable). In sample 2, 7 CN-AD converters (average follow-up 7.1 years) were compared to 25 CN-stable individuals.
  
  
  RESULTS
  AD-signature cortical thinning in CN-AD converters in both samples was remarkably similar, about 0.2 mm (p < 0.05). Despite this small absolute difference, Cohen d effect sizes for these differences were very large (> 1). Of the 11 CN individuals with baseline low AD-signature thickness (≥ 1 SD below cohort mean), 55% developed AD dementia over nearly the next decade, while none of the 9 high AD-signature thickness individuals (≥ 1 SD above mean) developed dementia. This marker predicted time to diagnosis of dementia (hazard ratio = 3.4, p < 0.0005); 1 SD of thinning increased dementia risk by 3.4.
  
  
  CONCLUSIONS
  By focusing on cortical regions known to be affected in AD dementia, subtle but reliable atrophy is identifiable in asymptomatic individuals nearly a decade before dementia, making this measure a potentially important imaging biomarker of early neurodegeneration.
authors.affiliation: Department of Neurology, Massachusetts Alzheimer’s Disease Research Center, Massachusetts General Hospital, MA, USA. bradd@nmr.mgh.harvard.edu
authors.forename: B C
authors.initials: BC
authors.lastname: Dickerson
authors.forename: T R
authors.initials: TR
authors.lastname: Stoub
authors.forename: R C
authors.initials: RC
authors.lastname: Shah
authors.forename: R A
authors.initials: RA
authors.lastname: Sperling
authors.forename: R J
authors.initials: RJ
authors.lastname: Killiany
authors.forename: M S
authors.initials: MS
authors.lastname: Albert
authors.forename: B T
authors.initials: BT
authors.lastname: Hyman
authors.forename: D
authors.initials: D
authors.lastname: Blacker
authors.forename: L
authors.initials: L
authors.lastname: Detoledo-Morrell
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000503:physiopathology*; D015415:Biomarkers; D002540:Cerebral Cortex / Q000473:pathology*; D016009:Chi-Square Distribution; D003071:Cognition / Q000502:physiology*; D003704:Dementia / Q000175:diagnosis*; D018450:Disease Progression; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008609:Mental Status Schedule; D011237:Predictive Value of Tests; D012044:Regression Analysis
chemical_list: D015415:Biomarkers