Document Type

Journal Article




School of Medical Sciences




National Health and Medical Research Council

Grant Number

NHMRC Number : 1009292


Gupta, V. B., Doecke, J. D., Hone, E., Pedrini, S., Laws, S. M., Thambisetty, M., ... & Masters, C. L. (2016). Plasma apolipoprotein J as a potential biomarker for Alzheimer's disease: Australian Imaging, Biomarkers and Lifestyle study of aging. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 3, 18-26.



For early detection of Alzheimer's disease (AD), the field needs biomarkers that can be used to detect disease status with high sensitivity and specificity. Apolipoprotein J (ApoJ, also known as clusterin) has long been associated with AD pathogenesis through various pathways. The aim of this study was to investigate the potential of plasma apoJ as a blood biomarker for AD.


Using the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, the present study assayed plasma apoJ levels over baseline and 18 months in 833 individuals. Plasma ApoJ levels were analyzed with respect to clinical classification, age, gender, apolipoprotein E (APOE) ε4 allele status, mini-mental state examination score, plasma amyloid beta (Aβ), neocortical Aβ burden (as measured by Pittsburgh compound B-positron emission tomography), and total adjusted hippocampus volume.


ApoJ was significantly higher in both mild cognitive impairment (MCI) and AD groups as compared with healthy controls (HC; P < .0001). ApoJ significantly correlated with both "standardized uptake value ratio" (SUVR) and hippocampus volume and weakly correlated with the plasma Aβ1-42/Aβ1-40 ratio. Plasma apoJ predicted both MCI and AD from HC with greater than 80% accuracy for AD and greater than 75% accuracy for MCI at both baseline and 18-month time points.


Mean apoJ levels were significantly higher in both MCI and AD groups. ApoJ was able to differentiate between HC with high SUVR and HC with low SUVR via APOE ε4 allele status, indicating that it may be included in a biomarker panel to identify AD before the onset of clinical symptoms.



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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