MRI and CSF biomarkers in normal, MCI, and AD subjects: diagnostic discrimination and cognitive correlations.
OBJECTIVE
To assess the correlations of both MRI and CSF biomarkers with clinical diagnosis and with cognitive performance in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD).


METHODS
This is a cross-sectional study with data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN subjects, subjects with aMCI, and subjects with AD with both CSF and MRI. 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 anatomic features on MRI, were computed for each subject.


RESULTS
We found no significant correlation between CSF biomarkers and cognitive scores in any of the 3 clinical groups individually. Conversely, STAND scores correlated with both Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination in aMCI and AD (p < or = 0.01). While STAND and all CSF biomarkers were predictors of clinical group membership (CN, aMCI, or AD) univariately (p < 0.001), STAND was more predictive than CSF both univariately and in combined models.


CONCLUSIONS
CSF and MRI biomarkers independently contribute to intergroup diagnostic discrimination and the combination of CSF and MRI provides better prediction than either source of data alone. However, MRI provides greater power to effect cross-sectional groupwise discrimination and better correlation with general cognition and functional status cross-sectionally. We therefore conclude that although MRI and CSF provide complementary information, MRI reflects clinically defined disease stage better 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; D003071:Cognition / Q000502:physiology; D003072:Cognition Disorders / Q000134:cerebrospinal fluid* / Q000473:pathology* / Q000503:physiopathology; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009419:Nerve Tissue Proteins / Q000032:analysis / Q000134:cerebrospinal fluid; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D012016:Reference Values; D012720:Severity of Illness Index; D016875:tau Proteins / Q000032:analysis / Q000134:cerebrospinal fluid
D016229:Amyloid beta-Peptides; D015415:Biomarkers; D009419:Nerve Tissue Proteins; D016875:tau Proteins