MRI and CSF biomarkers in normal, MCI, and AD subjects: predicting future clinical change.
OBJECTIVE
To investigate the relationship between baseline MRI and CSF biomarkers and subsequent change in continuous measures of cognitive and functional abilities in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and to examine the ability of these biomarkers to predict time to conversion from aMCI to AD.


METHODS
Data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN, aMCI, and AD cohorts with both CSF and MRI, were used. Baseline CSF (t-tau, Abeta(1-42), and p-tau(181P)) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like features in MRI, were computed for each subject.


RESULTS
Change on continuous measures of cognitive and functional performance was modeled as average Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination scores over a 2-year period. STAND was a better predictor of subsequent cognitive/functional change than CSF biomarkers. Single-predictor Cox proportional hazard models for time to conversion from aMCI to AD showed that STAND and log (t-tau/Abeta(1-42)) were both predictive of future conversion. The age-adjusted hazard ratio for an interquartile change (95% confidence interval) of STAND was 2.6 (1.7, 4.2) and log (t-tau/Abeta(1-42)) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance.


CONCLUSIONS
MRI and CSF provide complimentary predictive information about time to conversion from amnestic mild cognitive impairment to Alzheimer disease and combination of the 2 provides better prediction than either source alone. However, we found that MRI was a slightly better predictor of future clinical/functional decline than the CSF biomarkers tested.
Vemuri
P
P
Aging and Dementia Imaging Research Laboratory, Department of Radiology, Mayo Clinic and Foundation, Rochester, MN 55905, USA.
Wiste
H J
HJ
Weigand
S D
SD
Shaw
L M
LM
Trojanowski
J Q
JQ
Weiner
M W
MW
Knopman
D S
DS
Petersen
R C
RC
Jack
C R
CR
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid* / Q000473:pathology* / Q000503:physiopathology; D016229:Amyloid beta-Peptides / Q000032:analysis / Q000134:cerebrospinal fluid; D015415:Biomarkers / Q000032:analysis / Q000134:cerebrospinal fluid; D001921:Brain / Q000378:metabolism* / Q000473:pathology* / Q000503:physiopathology; D003072:Cognition Disorders / Q000134:cerebrospinal fluid* / Q000473:pathology* / Q000503:physiopathology; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D003937:Diagnosis, Differential; D018450:Disease Progression; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D008297:Male; D008569:Memory Disorders / Q000134:cerebrospinal fluid / Q000473:pathology / Q000503:physiopathology; D008875:Middle Aged; D009483:Neuropsychological Tests; D010446:Peptide Fragments / Q000032:analysis / Q000134:cerebrospinal fluid; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D016875:tau Proteins / Q000032:analysis / Q000134:cerebrospinal fluid
D016229:Amyloid beta-Peptides; D015415:Biomarkers; D010446:Peptide Fragments; C075222:amyloid beta-protein (1-42); D016875:tau Proteins