TY - JOUR
T1 - Improving CSF biomarker accuracy in predicting prevalent and incident Alzheimer disease
AU - Roe, C. M.
AU - Fagan, A. M.
AU - Williams, M. M.
AU - Ghoshal, N.
AU - Aeschleman, M.
AU - Grant, E. A.
AU - Marcus, D. S.
AU - Mintun, M. A.
AU - Holtzman, D. M.
AU - Morris, J. C.
N1 - Funding Information:
Dr. Roe receives research and salary support from the NIH/NIA and from the Charles and Joanne Knight Alzheimer Research Initiative of the Knight Alzheimer's Disease Research Center. Dr. Fagan serves on the speakers' bureau for the Alzheimer's Association. Dr. Williams serves on a scientific advisory board for Centene; serves on a speakers' bureau for the Alzheimer's Association; and receives research support from Eli Lilly and Company, Bristol-Myers Squibb, and the NIH. Dr. Ghoshal receives research support from Elan Corporation/Janssen, Eli Lilly and Company, Wyeth/Pfizer Inc, Novartis, Bristol-Myers Squibb, and the NIH (NIA/NINDS). Ms. Aeschleman reports no disclosures. Dr. Grant receives research and salary support from the NIH/NIA. Dr. Marcus has a patent pending re: a software system to select and perform automated medical imaging analysis; serves as a consultant for Avid Radiopharmaceuticals, Inc.; and receives research support from the US Department of Defense and the NIH. Dr. Mintun is currently employed as Chief Medical Officer for Avid Radiopharmaceuticals, Inc. (all work on this project was done while faculty at Washington University); has served as a consultant for Avid Radiopharmaceuticals, Inc.; and receives research support from the NIH. Dr. Holtzman serves on scientific advisory boards for Satori Pharmaceuticals and EnVivo Pharmaceuticals; serves as an Associate Editor of Annals of Neurology, the Journal of Neuroscience, Neurobiology of Disease, and Experimental Neurology; may accrue revenue on pending patents re: Methods for Measuring the Metabolism of Neurally Derived Biomolecules in Vivo; Use of Anti-AB Antibody to Treat Traumatic Brain Injury; Methods to Treat Alzheimer's Disease or Other Amyloid Beta Accumulation Associated Disorders; Humanized Antibodies That Sequester abeta Peptide; Diagnostic for Early Stage Alzheimer's Disease; and Predictive Diagnostic for Alzheimer's Disease; serves as a consultant to Merck Serono, Eli Lilly and Company, Takeda Pharmaceutical Company Limited, Abbott, Comentis, Inc., Eisai Inc., and AstraZeneca; is cofounder of and receives board of directors compensation from C2N Diagnostics LLC; receives research support from AstraZeneca, Pfizer Inc., Eli Lilly and Company, Elan Corporation, Forest Laboratories, Inc., the NIH, Cure Alzheimer's Fund, and Fidelity Foundation; has received compensation from Washington University from license revenue received for licensing of patent applications to C2N Diagnostics LLC; and may receive future royalty payments for Washington University licensing patents to C2N Diagnostics, LLC and Eli Lilly and Company. Dr. Morris serves on scientific advisory boards for AstraZeneca, Bristol-Myers Squibb, Genentech, Inc., Merck Serono, Novartis, Pfizer Inc, Schering-Plough Corp., Eli Lilly and Company, Wyeth, and Elan Corporation; serves on the editorial advisory board of Alzheimer's Disease and Associated Disorders; receives royalties from publishing Mild Cognitive Impairment and Early Alzheimer's Disease (John Wiley and Sons, 2008), Dementia (Clinical Publishing, 2007), Handbook of Dementing Illnesses, 2nd edition (Taylor & Francis, 2006) and for an editorial in Lancet Neurology (Elsevier, 2008); and receives research support from Elan Corporation, Wyeth, Eli Lilly and Company, Novartis, Pfizer Inc, Avid Radiopharmaceuticals, the NIH, and from the Dana Foundation.
Funding Information:
Study funding: Supported by the NIH (NINDS P30 NS057105, NIA P50 AG005681, P01 AG003991, and P01 AG026276) ; the NCRR (KL2RR024994 and 1UL1RR024992) ; and the Charles F. and Joanne Knight Alzheimer's Research Initiative of the Washington University Alzheimer's Disease Research Center.
PY - 2011/2/8
Y1 - 2011/2/8
N2 - Objective: To investigate factors, including cognitive and brain reserve, which may independently predict prevalent and incident dementia of the Alzheimer type (DAT) and to determine whether inclusion of identified factors increases the predictive accuracy of the CSF biomarkers Aβ42, tau, ptau181, tau/Aβ42, and ptau181/Aβ42. Methods: Logistic regression identified variables that predicted prevalent DAT when considered together with each CSF biomarker in a cross-sectional sample of 201 participants with normal cognition and 46 with DAT. The area under the receiver operating characteristic curve (AUC) from the resulting model was compared with the AUC generated using the biomarker alone. In a second sample with normal cognition at baseline and longitudinal data available (n = 213), Cox proportional hazards models identified variables that predicted incident DAT together with each biomarker, and the models concordance probability estimate (CPE), which was compared to the CPE generated using the biomarker alone. Results: APOE genotype including an ϵ4 allele, male gender, and smaller normalized whole brain volumes (nWBV) were cross-sectionally associated with DAT when considered together with every biomarker. In the longitudinal sample (mean follow-up = 3.2 years), 14 participants (6.6%) developed DAT. Older age predicted a faster time to DAT in every model, and greater education predicted a slower time in 4 of 5 models. Inclusion of ancillary variables resulted in better cross-sectional prediction of DAT for all biomarkers (p < 0.0021), and better longitudinal prediction for 4 of 5 biomarkers (p < 0.0022). Conclusions: The predictive accuracy of CSF biomarkers is improved by including age, education, and nWBV in analyses.
AB - Objective: To investigate factors, including cognitive and brain reserve, which may independently predict prevalent and incident dementia of the Alzheimer type (DAT) and to determine whether inclusion of identified factors increases the predictive accuracy of the CSF biomarkers Aβ42, tau, ptau181, tau/Aβ42, and ptau181/Aβ42. Methods: Logistic regression identified variables that predicted prevalent DAT when considered together with each CSF biomarker in a cross-sectional sample of 201 participants with normal cognition and 46 with DAT. The area under the receiver operating characteristic curve (AUC) from the resulting model was compared with the AUC generated using the biomarker alone. In a second sample with normal cognition at baseline and longitudinal data available (n = 213), Cox proportional hazards models identified variables that predicted incident DAT together with each biomarker, and the models concordance probability estimate (CPE), which was compared to the CPE generated using the biomarker alone. Results: APOE genotype including an ϵ4 allele, male gender, and smaller normalized whole brain volumes (nWBV) were cross-sectionally associated with DAT when considered together with every biomarker. In the longitudinal sample (mean follow-up = 3.2 years), 14 participants (6.6%) developed DAT. Older age predicted a faster time to DAT in every model, and greater education predicted a slower time in 4 of 5 models. Inclusion of ancillary variables resulted in better cross-sectional prediction of DAT for all biomarkers (p < 0.0021), and better longitudinal prediction for 4 of 5 biomarkers (p < 0.0022). Conclusions: The predictive accuracy of CSF biomarkers is improved by including age, education, and nWBV in analyses.
UR - http://www.scopus.com/inward/record.url?scp=79951599654&partnerID=8YFLogxK
U2 - 10.1212/WNL.0b013e31820af900
DO - 10.1212/WNL.0b013e31820af900
M3 - Article
C2 - 21228296
AN - SCOPUS:79951599654
VL - 76
SP - 501
EP - 510
JO - Neurology
JF - Neurology
SN - 0028-3878
IS - 6
ER -