Tony Wyss-Coray at Stanford University and Sandip Ray, who co-founded the startup biotech company Satori with Wyss-Coray.
The process of AD features a vigorous inflammatory response. Astrocytes and microglia become activated and cause the secretion of a large number of proteins, including cytokines, chemokines, growth factors, proteases, and protease inhibitors, which together mediate communication between these cells in the brain. Lymphocytes chime in, as well, especially in vascular forms of the disease. An increasing number of studies indicate that this CNS reaction communicates with the periphery, particularly with peripheral macrophages, lymphocytes, and myeloid cells, Wyss-Coray said. Some of these can travel into the brain, assess its state, and either leave or induce production of factors or even initiate immune responses.
The larger point is that every disease, in every organ, leads to changes in plasma, Wyss-Coray said. The blood is the body’s most complex organ in terms of protein moieties, and Wyss-Coray started his study from the question of whether one can understand a disease process by studying plasma. Scientists have measured individual markers by ELISA, but the low power of this approach has left many studies that report initial discrimination with individual factors without replication by other labs. Mass spectrometry has matured as a tool for mining the proteome, but problems persist there, too, as the method is asked to keep apart many tens to 100,000 different proteins, fragments, and post-translational modifications. Abundant proteins such as albumin tend to overload the system, and efforts to deplete them take down other proteins that may be of interest. This approach is not reproducible enough yet to be clinically useful, Wyss-Coray said. (See also an independent recent attempt to identify a new candidate biomarker set focused around neuroprotective and complement proteins, see Selle et al., 2005.)
The scientists decided on a middle-of-the-road approach between these two extremes. The scientists first picked a set of proteins that might be important in the disease process. “We call this a candidate-based approach by tuning in to the language of cells. How do they communicate when healthy, how when stressed and diseased? Hopefully, we get a disease-specific picture,” Wyss-Coray said.
The scientists gradually whittled down an initial group of 300 proteins from among cytokines, chemokines, growth factors, neurotrophins, hormone-like proteins, acute-phase proteins, complement factors, soluble receptors, proteases, and inhibitors to a set of 12 predictors. They developed an ELISA array of a membrane with monoclonal antibodies specific against these proteins, incubated it with patient plasma samples, and read the signal with chemiluminescence. This yields a picture of relative levels of expression of these 12 factors, which can be quantified.
A first, small study used 48 cases in various stages of AD as well as 50 age-matched controls from seven centers around the world. Of the 17 who have since died, the test had predicted their condition with 100 percent accuracy, Wyss-Coray said. Of the cases that have not yet come to autopsy, the difference in the relative probability of having AD between control and AD groups was large, Wyss-Coray said.
Software developed at Stanford, called significance analysis of microarray (SAM), pulled up 44 proteins whose blood levels differed between AD and controls. Individually, none of these factors predict AD, but together they do, Wyss-Coray said, and a separate procedure of unbiased clustering of these 44 markers based merely on their expression levels reproduced the AD and control groups.
To analyze further whether these plasma differences could predict AD, the scientists turned to another form of analysis called predictive analysis of microarrays (PAM). This algorithm tries to identify a minimal set of markers that can discriminate and predict the proper sample groups without having seen the primary data. In multiple iterations, it adds proteins from within a training data set and calculates their predictive power until it has reached maximal accuracy. This minimal set included 12 proteins, which predicted whether a sample came from AD or control with 97 percent accuracy (i.e., a composite score of 100 percent sensitivity and 94 percent specificity). When the algorithm then applied this information to a different test set it had not seen before, it classified 32 of 33 samples correctly.
The top 12 factors are involved in immune function, energy metabolism, and vascular function. Wyss-Coray proposed that the most abundant changes are consistent with immune and macrophage impairment. There is scarce data on this topic, but a growing trickle of studies is suggesting that mononuclear cells or macrophages isolated from AD patients are impaired in a number of ways and respond poorly to stimulation. (For a current review on serum-based proteomics of neurodegenerative diseases, see Sheta et al., 2006.)
Next on Wyss-Coray’s list is to study related dementias. Initial work on ALS, Parkinson disease, multiple sclerosis, and peripheral neuropathy indicates the AD fingerprint is specific to this disease and does not merely reflect a generic inflammation. The hope is that related dementias will prove to have their own unique pattern of plasma predictors, suggesting that a top 12 set may be found for them, as well.
One important caveat with blood tests is that infections or flu could mask AD in plasma samples. While the scientists have not ruled this out, Wyss-Coray said individual markers clearly change in response to a flu, but a defined set of 12 may not. Confounders such as this imply, however, that an ultimate test for AD may need more than 12 predictors. The present data aim to prove the concept; it is not a commercial test just yet, Wyss-Coray said. —Gabrielle Strobel.
See also part 1, part 2, part 3, and part 4 of this series.