Blood-based protein biomarkers for diagnosis of Alzheimer disease.
OBJECTIVE
To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD).


METHODS
Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data.


METHODS
General community-based, prospective, longitudinal study of aging.


METHODS
A total of 754 healthy individuals serving as controls and 207 participants with AD from the Australian Imaging Biomarker and Lifestyle study (AIBL) cohort with identified biomarkers that were validated in 58 healthy controls and 112 individuals with AD from the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort.


RESULTS
A biomarker panel was identified that included markers significantly increased (cortisol, pancreatic polypeptide, insulinlike growth factor binding protein 2, β(2) microglobulin, vascular cell adhesion molecule 1, carcinoembryonic antigen, matrix metalloprotein 2, CD40, macrophage inflammatory protein 1α, superoxide dismutase, and homocysteine) and decreased (apolipoprotein E, epidermal growth factor receptor, hemoglobin, calcium, zinc, interleukin 17, and albumin) in AD. Cross-validated accuracy measures from the AIBL cohort reached a mean (SD) of 85% (3.0%) for sensitivity and specificity and 93% (3.0) for the area under the receiver operating characteristic curve. A second validation using the ADNI cohort attained accuracy measures of 80% (3.0%) for sensitivity and specificity and 85% (3.0) for area under the receiver operating characteristic curve.


CONCLUSIONS
This study identified a panel of plasma biomarkers that distinguish individuals with AD from cognitively healthy control subjects with high sensitivity and specificity. Cross-validation within the AIBL cohort and further validation within the ADNI cohort provides strong evidence that the identified biomarkers are important for AD diagnosis.
The Australian E-Health Research Centre, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
James D
JD
Doecke
Simon M
SM
Laws
Noel G
NG
Faux
William
W
Wilson
Samantha C
SC
Burnham
Chiou-Peng
CP
Lam
Alinda
A
Mondal
Justin
J
Bedo
Ashley I
AI
Bush
Belinda
B
Brown
Karl
K
De Ruyck
Kathryn A
KA
Ellis
Christopher
C
Fowler
Veer B
VB
Gupta
Richard
R
Head
S Lance
SL
Macaulay
Kelly
K
Pertile
Christopher C
CC
Rowe
Alan
A
Rembach
Mark
M
Rodrigues
Rebecca
R
Rumble
Cassandra
C
Szoeke
Kevin
K
Taddei
Tania
T
Taddei
Brett
B
Trounson
David
D
Ames
Colin L
CL
Masters
Ralph N
RN
Martins
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000097:blood* / Q000175:diagnosis* / Q000235:genetics; D001057:Apolipoproteins E / Q000235:genetics; D001315:Australia; D015415:Biomarkers / Q000097:blood*; D001798:Blood Proteins / Q000378:metabolism*; D001921:Brain / Q000473:pathology; D015331:Cohort Studies; D005260:Female; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D008297:Male; D008609:Mental Status Schedule; D008875:Middle Aged; D059906:Neuroimaging; D015203:Reproducibility of Results; D012111:Residence Characteristics; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric
D001057:Apolipoproteins E; D015415:Biomarkers; D001798:Blood Proteins