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© 2009 American Academy of Neurology MRI and CSF biomarkers in normal, MCI, and AD subjectsPredicting future clinical changeFrom the Aging and Dementia Imaging Research Laboratory, Department of Radiology (P.V., C.R.J.), Department of Health Sciences Research (H.J.W., S.D.W.), Department of Neurology (D.S.K., R.C.P.), Mayo Clinic and Foundation, Rochester, MN; Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), University of Pennsylvania School of Medicine, Philadelphia; and University of California at San Francisco and Center for Imaging of Neurodegenerative Diseases (M.W.W.), Department of Veterans Affairs Medical Center, San Francisco, CA. Address correspondence and reprint requests to Dr. Clifford R. Jack, Jr., Mayo Clinic and Foundation, 200 First Street SW, Rochester, MN 55905 jack.clifford{at}mayo.edu 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, Aβ1–42, and p-tau181P) 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/Aβ1–42) 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/Aβ1–42) 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.
Abbreviations: AD = Alzheimer disease; ADNI = Alzheimer's Disease Neuroimaging Initiative; aMCI = amnestic mild cognitive impairment; CDR-SB = Clinical Dementia Rating–sum of boxes score; CI = confidence interval; CN = cognitively normal; HR = hazard ratio; MMSE = Mini-Mental State Examination; NFT = neurofibrillary tangle; STAND = Structural Abnormality Index.
Received December 5, 2008. Accepted in final form May 7, 2009. Supplemental data at www.neurology.org See page 287 *Investigators of The Alzheimer's Disease Neuroimaging Initiative are listed at www.loni.ucla.edu\ADNI\Collaboration\ADNI_Manuscript_Citations.pdf. Supported by NIH grant AG11378; Robert H. Smith Family Foundation Research Fellowship; the Alexander Family AD Research Professorship of the Mayo Foundation; and U.S.A. and Opus building NIH grant C06 RR018898. Disclosure: Author disclosures are provided at the end of the article.
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