Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline

Nettiksimmons, J.; Harvey, D.; Brewer, J.; Carmichael, O.; DeCarli, C.; Jack, C.R.; Petersen, R.; Shaw, L.M.; Trojanowski, J.Q.; Weiner, M.W.; Beckett, L.; The Alzheimer's Disease Neuroimaging Initiative,

doi:10.1016/j.neurobiolaging.2010.04.025

« Previous Next »Neurobiology of Aging
Volume 31, Issue 8 , Pages 1419-1428, August 2010

Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline

J. Nettiksimmons
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, Davis, CA 95616, USA
D. Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, Davis, CA 95616, USA
J. Brewer
- Departments of Radiology and Neurosciences, University of California, San Diego, La Jolla, CA 92093-0949, USA
O. Carmichael
- Department of Neurology, University of California, Davis, Davis, CA 95616, USA
C. DeCarli
- Department of Neurology, University of California, Davis, Davis, CA 95616, USA
C.R. Jack Jr
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA
R. Petersen
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA
L.M. Shaw
- Institute on Aging, Alzheimer's Disease Core Center, Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
J.Q. Trojanowski
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
M.W. Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
L. Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, Davis, CA 95616, USA
- Corresponding author at. Tel.: (530) 754-7161; fax: (530) 752-3239
The Alzheimer's Disease Neuroimaging Initiative
- Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators is available at www.loni.ucla.edu/ADNI\Collaboration\ADNI_Manuscript_Citations.pdf.

Received 14 February 2010; received in revised form 19 April 2010; accepted 23 April 2010. published online 09 June 2010.

Abstract

Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer's disease (AD) that precede dementia. The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI), and subjects with AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD. Two hundred twenty-two NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. One hundred twelve also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over 3 years. Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-cog. Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.

Keywords: Alzheimer's disease, Dementia, Early diagnosis, Cerebrospinal fluid, Tau protein, Amyloid beta-protein, Structural magnetic resonance imaging, Hippocampal volume, Cognition, Clustering, Normal controls