The present study examined changes in plasma biomarkers in the ADNI cohort. Statistical analysis showed on average 80% to 90% sensitivity across models, and incorporation of plasma analytes improved specificity from 40% up to 70% and 80% in differentiating patients with AD from HCs, suggesting some usefulness of the multiplex immunoassay panel as a screening tool. Increases in PP, TN-C, MMP-1, eotaxin 3, and NT-proBNP levels and decreases in IgM and ApoE levels were consistently observed across all group comparisons in the ADNI cohort. Notably, ApoE protein levels were lowest in patients with MCI who progressed to dementia. Perhaps the most intriguing observation was the identification of a biochemical profile based on ApoE genotype in the AD, MCI, and HC arms.
have described blood-based biomarkers in patients having AD, with little consistency across studies. When the same platform is applied across cohorts, similarities in the biomarkers begin to emerge. Specifically, increases in PP, eotaxin 3, and plasma NT-proBNP levels, observed in the present ADNI cohort, have been previously described in CSF samples obtained from patients with AD.22,23
In addition, evidence from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Aging group (H.D.S., written communication, June 2012) and from the Texas Alzheimer’s Research Consortium17
shows increased levels of PP, TN-C, and eotaxin 3 in plasma samples, suggesting that changes in these analytes are robust across cohorts when tested on the same platform. It should be noted that the Texas Alzheimer’s Research Consortium used an earlier version of the panel (which did not include ApoE or NT-proBNP) than that used in the present study.
Perhaps the most notable finding from the ADNI cohort was the identification of a protein profile associated with ApoE
allelic status, a known risk factor for AD. For example, ApoE protein, C-reactive protein, and gamma interferon plasma protein levels were lowest in Apo
carriers, while IL-13 levels were elevated. Many of the plasma-based biomarkers previously described in the literature13,15,17,26–30
(eg, Cortisol, cystatin C, chromogranin A, tissue inhibitor of metalloproteinases, alpha-1 antichymotrypsin, and pregnancy-associated plasma protein CA 19-9) also showed some associations with the ApoE
genotype (eTables 1–3 and eAppendix), suggesting that differences may in part be driven by genotypic status in addition to dementia status. The present data support a phenotypic plasma signature associated with the ApoE
genotype and could provide some explanation for the biological variability of blood-based biomarkers of AD described in the literature.13,15,18
Clearly, examination in much larger cohorts is needed.
Three common biological themes seemed to be associated with the top plasma biomarker changes in the ADNI cohort. The first biological theme appeared to be associated with metabolic markers that might be altered by cholinergic tone but most likely were driven by concomitant medication use (eg, PP). In fact, evidence indicates that acetylcholinesterase inhibitors can alter PP release,31
suggesting that alterations in PP observed in the ADNI cohort may be a function of acetylcholinesterase use. Alternatively, abnormal cholinergic tone may be driving abnormal expression of PP in patients with AD. The second biological theme appeared to be linked to vascular pathologic conditions (eg, TN-C, MMP-1, and NT-proBNP). For example, TN-C has been associated with vascular remodeling, and NT-proBNP has long been studied in the context of cardiovascular disease.32,33
A recent study34
examining 464 individuals 75 years or older without dementia demonstrated a significant association of NT-proBNP levels with cognitive decline, and NT-proBNP has been reported to be elevated in patients with subcortical vascular dementia.35
Notably, increases in natriuretic peptide levels in patients with AD have previously been described by Ewers et al11,12
and by Buerger and colleagues,36
with speculation that endothelial remodeling during dementia might be detectable by peripheral vascular markers. The third biological theme seemed to revolve around the phenotypic signature of an ApoE
genotype, perhaps best characterized by ApoE protein levels, the acute-phase C-reactive protein, and a subset of interleukins, and is probably the most notable of the categories. It has been hypothesized that ApoE is critical for Aβ clearance, although it remains less clear whether low levels of ApoE
actually contribute to AD pathologic changes.37,38
genotype also seems to be loosely associated with increases in several inflammatory cytokines. Indeed, eotaxin 3, one of the top biomarkers in the ADNI plasma data set, can be released following stimulation with interleukins such as IL-3 and IL-4,39
and levels might be driven by modulation of interleukin levels. Further longitudinal studies relating changes in plasma and CSF ApoE and cytokine concentrations over time to changes in cognition and AD brain pathologic conditions in at-risk older individuals will likely further clarify the biological relevance of these associations.
Significant care should be taken in the interpretation of the present data set. For example, many of the observed changes may be a function of concurrent medication use (eg, PP). Furthermore, several common comorbidities exist in patients with AD, including cardiovascular disease and diabetes mellitus, that may be more reflective of vascular pathologic conditions (eg, TN-C, MMP-1, and NT-proBNP) and are not that specific to AD. Finally, changes in one biomarker may drive changes in others within the panel (eg, interleukin influence on eotaxin 3), suggesting that many of the top biomarkers may be redundant and part of a larger common signaling cascade.
In summary, the ADNI plasma biomarker data confirm CSF studies reporting increased levels of PP, eotaxin 3, tenascin C, and NT-proBNP in patients with AD and MCI. When plasma biomarkers were combined with baseline demographics, the combined models showed high sensitivity and improved specificity, suggesting their usefulness as a potential screening tool. Further studies to confirm these findings are merited. Finally, the ADNI plasma biomarker data suggest a distinct phenotypic profile associated with ApoE allelic status. Additional research will help to delineate whether a blood-based multiplex immunoassay panel that includes these analytes can deliver as a screening tool for AD.