Affiliations: [a] Department of Pathology, The University of Melbourne, Parkville, Melbourne, VIC, Australia | [b] Neuroproteomics Platform, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Melbourne, VIC, Australia | [c] Mental Health Research Institute, The University of Melbourne, Parkville, Melbourne, VIC, Australia | [d] Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia | [e] Department of Pharmacology, The University of Melbourne, Parkville, Melbourne, VIC, Australia
Correspondence:
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Correspondence to: Kevin J. Barnham, MHRI and Department of Pharmacology, The University of Melbourne, 3010, Victoria, Australia. Tel.: +61 3 83442555; Fax: +61 3 93476750; E-mail: kbarnham@unimelb.edu.au.
Abstract: Effective therapeutic interventions for Alzheimer's disease (AD) will require treatment regimes to move toward the earliest stages of the disease. For this to occur the field has to identify biomarkers that are able to accurately identify individuals at risk for progression toward AD in the presymptomatic stage. One very significant implication is that some form of population-based screening will need to be undertaken in order to identify those at risk. To date, efforts in neuroimaging brain amyloid-β (Aβ) and changes in cerebrospinal fluid Aβ and tau levels shows promise, however, it is questionable as to whether these methods are applicable for screening the general population. The Aβ peptide is also found in blood which is the most economical and efficient biological fluid to analyze. Unfortunately, investigations into blood-based diagnostic markers have produced mixed results. This variability is likely to be the result of differences in the preanalytical processing of samples and as such is delaying progress in the field. Reported preanalytical processing techniques from 87 recent articles focusing on the measurement of Aβ in blood were compared, to investigate whether basic sample-handling techniques were comparable between studies. This comparison revealed that not only is it likely that some of the variability in blood-based results is attributable to discrepancies in preanalytical methodologies but also that the field is failing to adequately report sample processing techniques. This review highlights the current shortcomings in methodological reporting and recommends a standardized blood collection methodology based on the limited consensus of the reviewed articles.
