Doecke, J. D, Laws, S. M, Faux, N. G, Wilson, W., Burnham, S., Lam, C. P, Mondal, A., Bedo, J., Bush, A. I, Brown, B. M, De Ruyck, K., Ellis, K. A, Fowler, C. J, Gupta, V. B, Head, R., Macaulay, S. L, Pertile, K. K, Rowe, C. C, Rembach, A. R, Rodrigues, M. A, Rumble, R., Szoeke, C., Taddei, K., Taddei, T., Trounson, B., Ames, D., Masters, C. L & Martins, RN. (2012). Blood-based protein biomarkers for diagnosis of Alzheimer disease. Archives of Neurology, Retrieved from https://doi.org/10.1001/archneurol.2012.1282
Objective To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD). Design Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data. Setting General community-based, prospective, longitudinal study of aging. Participants 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, β2 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. Alzheimer disease (AD) is the most common form of dementia, affecting more than 27 million persons worldwide and predicted to affect 86 million people by the year 2050.1 The disease is characterized morphologically by an overall loss of synapses and neurons and an overall reduction in brain volume.2 The identification of peripheral biomarkers of the disease process leading to an effective and early diagnostic test for AD would allow for presymptomatic detection of disease and would be valuable for monitoring the efficacy of disease interventions during clinical trials. Currently, cerebrospinal fluid (CSF) has provided the most promising source of validated AD biomarkers. A decline in β-amyloid (Aβ) levels in the CSF has been reported to help distinguish between patients with AD and elderly individuals without AD.3- 7 In particular, the longer 42–amino acid isoform Aβ1-42 in combination with levels of the phosphorylated microtubule-associated protein tau (p-tau) has been advocated for use in the diagnosis of AD.8 Perrin and colleagues9 identified other biomarkers, including neuronal cell adhesion molecule, YKL-40 (YKL represents the first 3 N-terminal amino acids and 40 denotes molecular mass in kilodaltons; also known as human chitinase 3–like 1, cartilage glycoprotein 39, and chondrex), chromogranin A, and carnosinase I, which improved the diagnostic accuracy of Aβ1-42 and p-tau. Craig-Schapiro and colleagues10 used a biomarker discovery method from rules-based medicine (RBM) to identify novel CSF biomarkers that distinguish between very mild dementia, mild dementia, and no dementia. Compared with CSF, blood analysis has advantages as an approach to population-based disease screening because it is simpler and less invasive. As such, there has been strong interest in obtaining usable blood-based biomarkers for AD diagnosis. Ray et al11 identified a panel of 18 biomarkers from a group of 120 signaling proteins and, more recently, O’Bryant and colleagues12,13 used a panel from RBM to identify a list of 30 biomarkers to detect AD. Soares and colleagues14 describe a list of biomarkers identified within the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort in this issue. Herein, we describe a short articulated panel of blood-based biomarker candidates obtained by comparing clinical factors with blood-based measures from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, a prospective longitudinal cohort study of aging in Australia.15 This biomarker panel was then validated in the ADNI cohort. The biomarkers identified in this cross-sectional analysis of data from the AIBL study may contribute toward the development of a blood-based diagnostic test, which together with appropriate imaging phenotypes may deliver an accurate means to diagnose AD.
Institute for Health and Ageing
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