TY - JOUR
T1 - A blood-based algorithm for the detection of Alzheimer's disease
AU - O'Bryant, Sid E.
AU - Xiao, Guanghua
AU - Barber, Robert
AU - Reisch, Joan
AU - Hall, James
AU - Cullum, C. Munro
AU - Doody, Rachelle
AU - Fairchild, Thomas
AU - Adams, Perrie
AU - Wilhelmsen, Kirk
AU - Diaz-Arrastia, Ramon
PY - 2011/9
Y1 - 2011/9
N2 - Background: We previously created a serum-based algorithm that yielded excellent diagnostic accuracy in Alzheimer's disease. The current project was designed to refine that algorithm by reducing the number of serum proteins and by including clinical labs. The link between the biomarker risk score and neuropsychological performance was also examined. Methods: Serum-protein multiplex biomarker data from 197 patients diagnosed with Alzheimer's disease and 203 cognitively normal controls from the Texas Alzheimer's Research Consortium were analyzed. The 30 markers identified as the most important from our initial analyses and clinical labs were utilized to create the algorithm. Results: The 30-protein risk score yielded a sensitivity, specificity, and AUC of 0.88, 0.82, and 0.91, respectively. When combined with demographic data and clinical labs, the algorithm yielded a sensitivity, specificity, and AUC of 0.89, 0.85, and 0.94, respectively. In linear regression models, the biomarker risk score was most strongly related to neuropsychological tests of language and memory. Conclusions: Our previously published diagnostic algorithm can be restricted to only 30 serum proteins and still retain excellent diagnostic accuracy. Additionally, the revised biomarker risk score is significantly related to neuropsychological test performance.
AB - Background: We previously created a serum-based algorithm that yielded excellent diagnostic accuracy in Alzheimer's disease. The current project was designed to refine that algorithm by reducing the number of serum proteins and by including clinical labs. The link between the biomarker risk score and neuropsychological performance was also examined. Methods: Serum-protein multiplex biomarker data from 197 patients diagnosed with Alzheimer's disease and 203 cognitively normal controls from the Texas Alzheimer's Research Consortium were analyzed. The 30 markers identified as the most important from our initial analyses and clinical labs were utilized to create the algorithm. Results: The 30-protein risk score yielded a sensitivity, specificity, and AUC of 0.88, 0.82, and 0.91, respectively. When combined with demographic data and clinical labs, the algorithm yielded a sensitivity, specificity, and AUC of 0.89, 0.85, and 0.94, respectively. In linear regression models, the biomarker risk score was most strongly related to neuropsychological tests of language and memory. Conclusions: Our previously published diagnostic algorithm can be restricted to only 30 serum proteins and still retain excellent diagnostic accuracy. Additionally, the revised biomarker risk score is significantly related to neuropsychological test performance.
KW - Algorithm, blood-based
KW - Alzheimer's disease
KW - Diagnosis
UR - http://www.scopus.com/inward/record.url?scp=80051941304&partnerID=8YFLogxK
U2 - 10.1159/000330750
DO - 10.1159/000330750
M3 - Article
C2 - 21865746
AN - SCOPUS:80051941304
SN - 1420-8008
VL - 32
SP - 55
EP - 62
JO - Dementia and Geriatric Cognitive Disorders
JF - Dementia and Geriatric Cognitive Disorders
IS - 1
ER -