Using blood markers for Alzheimer disease in clinical practice?.
Neurology. 2012 Aug 28;79(9):846-7.
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Our article (Ray et al., 2007) gained a lot of attention, but it was very early days and we had to work with what was available. Our samples were from multiple centers, and the cases and controls were not perfectly matched for each. There was also a difference in age between cases and controls, and the analytical platform we had used was a somewhat moving target, because the manufacturer (RayBiotech) made several changes to the array during the time we used it. Nevertheless, I think several of the markers we identified have biological relevance in AD and brain aging, and we are pursuing some of them successfully (e.g., MCSF). I would also draw attention to work from our lab that has been overlooked (Britschgi et al., 2011). We used an independent set of samples, a different analytical platform, and an innovative new approach to predict pathological parameters in AD using plasma markers as variables. Several models we developed reproduced six proteins out of the 18-protein Ray signature. Most consistently, we found changes in MCSF, GCSF and IL-3.
Still, I think even now there are major challenges to find markers that will hold up in multiple studies across different centers and become clinical tools. It took maybe 10 years to achieve clinical utility with CSF Aβ and tau ELISAs, and I think it will take as long with any other protein-based assay (one at a time).
The main problem is that protein measurements are extremely difficult to standardize, and multiplex assays are notoriously inexact. Major problems with current assays are that the reagents (antibodies, standards) are "research use only" and not clinical grade. They may, therefore, change from batch to batch, leading to variations in sensitivity and absolute concentrations for a given protein. Another, more trivial problem is that assays (e.g., ELISAs, Luminex) from different manufacturers may detect different isoforms of the same protein, active versus pre-proteins, or post-translationally modified proteins versus unmodified, leading sometimes to completely opposite results between groups.
I think we are at a similar stage in this field as genetics was with SNP studies 10 years ago. Geneticists produced lists of more than 100 genes with linkage to AD, of which most did not hold up in the much larger GWAS. This showed that sample size is key. However, even if thousands of blood samples will be analyzed, we will still have the problem that the protein assays and sample collection are not standardized.
Our lab continues to develop and use protein screens, and we currently measure more than 600 proteins in blood plasma or CSF using antibody-based microarrays. We know these arrays produce false-positive and -negative results, but we run several hundred samples in one batch to reduce variability. We have identified several interesting new proteins and pathways that we are now validating in biological assays and animal models of AD. I think we will have to go this hard way and link biology to any of the proteins that come out of screens before they are worth the effort to produce a clinical-grade assay.
Ray S, Britschgi M, Herbert C, Takeda-Uchimura Y, Boxer A, Blennow K, Friedman LF, Galasko DR, Jutel M, Karydas A, Kaye JA, Leszek J, Miller BL, Minthon L, Quinn JF, Rabinovici GD, Robinson WH, Sabbagh MN, So YT, Sparks DL, Tabaton M, Tinklenberg J, Yesavage JA, Tibshirani R, Wyss-Coray T.
Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins.
Nat Med. 2007 Nov;13(11):1359-62.
Britschgi M, Rufibach K, Huang SL, Clark CM, Kaye JA, Li G, Peskind ER, Quinn JF, Galasko DR, Wyss-Coray T.
Modeling of pathological traits in Alzheimer's disease based on systemic extracellular signaling proteome.
Mol Cell Proteomics. 2011 Oct;10(10):M111.008862.
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