Detection of Alzheimer's disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkersAbstract Introduction
There is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimer's disease (AD). Autoantibodies are abundant and ubiquitous in human sera and have been previously demonstrated as disease-specific biomarkers capable of accurately diagnosing mild-moderate stages of AD and Parkinson's disease.
Methods
Sera from 236 subjects, including 50 mild cognitive impairment (MCI) subjects with confirmed low CSF Aβ42 levels, were screened with human protein microarrays to identify potential biomarkers for MCI. Autoantibody biomarker performance was evaluated using Random Forest and Receiver Operating Characteristic curves.
Results
Autoantibody biomarkers can differentiate MCI patients from age-matched and gender-matched controls with an overall accuracy, sensitivity, and specificity of 100.0%. They were also capable of differentiating MCI patients from those with mild-moderate AD and other neurologic and non-neurologic controls with high accuracy.
Discussion
Autoantibodies can be used as noninvasive and effective blood-based biomarkers for early diagnosis and staging of AD.
IntroductionAD is a devastating and progressive neurodegenerative disease affecting approximately 5.3 million people in the United States, including almost half of the population at 85 years and older. Microscopic hallmarks of the disease include neuritic plaques containing amyloid beta peptide (Aβ42) and neurofibrillary tangles composed of hyperphosphorylated tau. Despite intensive research throughout the past two decades, a clear understanding of AD pathogenesis remains elusive and controversial. At best, current treatments only temporarily alleviate some symptoms and provide no relief for the pathology.
One point of agreement is that, in a high percentage of those afflicted, AD-related pathologic changes begin in the brain at least a decade before the emergence of telltale symptoms and clinical presentation. This makes it difficult to identify AD patients at early, pre-symptomatic disease stages, at a time when treatments are likely to be most beneficial. In view of this, intensive research is underway worldwide to discover and develop accurate, reliable, and cost-effective methods for early AD detection that can be widely implemented.
Much effort is being devoted to identification of soluble components in blood and cerebrospinal fluid (CSF) that can serve as useful and reliable AD biomarkers. In CSF, the most established biomarkers include Aβ42, total tau, and phosphorylated tau (p-tau) and their relative ratios. Low CSF Aβ42 levels in individuals with mild cognitive impairment (MCI) are now considered to be strongly indicative of the presence of early ongoing AD pathology as well as predictive of the likelihood of rapid disease progression to AD.
A key limitation to the use of CSF in general is the means by which it is obtained, through a lumbar spinal puncture, which is considered invasive and not without risk. By contrast, procurement of blood is less invasive, and plasma proteins, lipids as well as proteins and microRNAs enclosed within exosomes and lysosomal derivatives have all shown promise as biomarkers for early detection of AD pathology.
Parallel advancements for early AD detection have been made in neuroimaging, such as magnetic resonance imaging (MRI) and positron emission tomography (PET) using tracers like Florbetapir (18F), Pittsburgh compound B (PiB), and fluorodeoxyglucose. The high cost of these procedures and inconsistencies in interpretation prohibits their use as initial disease screeners, and they may not be readily available to individuals in economically disadvantaged areas or remote geographical locations.
Using human protein microarrays as a platform, we have shown that humans possess thousands of autoantibodies in their blood, and that individual autoantibody profiles are influenced by age, gender, and the presence of disease. Previous studies have suggested that autoantibodies may be useful as biomarkers for detection of neurodegenerative diseases, including AD and Parkinson's diseases (PD).
Ultimately, the practical utility of potential biomarkers depends on their capacity to accurately, specifically and reliably detect these diseases at early stages. Recently, we showed that a small panel of only four autoantibodies was sufficient to identify individuals with early-stage PD, as well as distinguish them from healthy individuals and others with mild-moderate PD. In addition, these early PD biomarkers exhibited disease specificity by distinguishing subjects with early-stage PD from those with other neurodegenerative diseases, such as MCI, mild-moderate AD, multiple sclerosis, and early-stage breast cancer.
In the present study involving 236 subjects, our objective was to determine if autoantibodies can be used as biomarkers to accurately diagnose individuals with MCI that is driven by early stages of AD pathology. We obtained sera from MCI subjects exhibiting low CSF AΒ42 from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Low CSF AΒ42 levels have been shown to be an independent surrogate biochemical biomarker indicative of the presence of ongoing early-stage AD pathology and a high likelihood of rapid progression to AD. Our results show that a small panel of blood-borne autoantibody biomarkers can be used to distinguish subjects with AD-associated MCI from age-matched and gender-matched controls with an overall accuracy of 100%.
In addition, MCI subjects were successfully differentiated from those with mild-moderate AD with similar overall accuracy, suggesting that this approach may also be useful for delineation of discrete disease stages along the MCI-to-AD continuum. Finally, the panel of AD-associated MCI biomarkers described here was highly specific for MCI in that they accurately distinguished AD-associated MCI subjects from those with other neurodegenerative and non-neurodegenerative diseases, including early and mild-moderate PD, multiple sclerosis, and early-stage breast cancer.
'snip'
This study has a number of strengths. The first is that it describes a blood-based diagnostic approach that is independent of symptoms and, because all MCI subjects also possess low CSF Aβ42 levels, presumably linked directly to ongoing pathology. Given that AD has a long prodromal period that may extend for more than a decade during which the pathologic changes are well underway, the use of autoantibodies as biomarkers for AD may open the door to pre-symptomatic detection. Another strength is that this approach takes advantage of the body's own response to the presence of pathology.
Unlike many blood proteins and lipids, antibodies are unusually stable in the blood, a fact which ensures that their production and detection will be largely independent of circadian as well as day to day production variations. Also, it is noteworthy to highlight that the biomarker selection process used here is unbiased and that multiple biomarker discovery strategies yielded comparable results and overlapping biomarker panels, providing additional confirmation of the utility of specific autoantibodies as diagnostic indicators of AD-associated MCI.
We have taken advantage of recent progress in human protein microarray technology which has allowed us to use a very large number of potential protein targets (nearly 10,000 in this case) and cast as wide a net as possible in an effort to identify potentially useful autoantibody biomarkers. This has also helped us to gain a better appreciation for the complexity of individual autoantibody profiles that are typically present in human blood. Rather than selecting the biomarkers based on a highly restricted subset of likely favorites, we were able to compare the expression levels of thousands of autoantibodies among groups of diseased and nondiseased individuals in an unbiased fashion and identify those that are differentially expressed among the two groups and thus represent potentially useful diagnostic indicators.
Additional strengths of this study are the demonstration of disease specificity, especially in the context of other neurodegenerative diseases, and the ability to distinguish different pathologic stages of the disease. For the latter, a much larger study using clinically well-characterized samples (imaging data, CSF, blood work, neuropsychological tests, and so forth) and appropriate matched controls will be necessary to validate this capability and determine the number of stages that can be properly delineated.
Finally, in support of their direct link to disease pathology, our data suggest that autoantibodies cannot be effectively used to discriminate between disease stages that do not exhibit substantial differences in the site and/or extent of pathology, as was shown to be the case in our failed attempt to distinguish patients designated by ADNI as EMCI and LMCI.
This study has several weaknesses, the most obvious of which is that it is a very small study intended to be a “proof of concept” study that was focused on addressing the question of whether autoantibodies can potentially be used as biomarkers to detect early-stage AD pathology in patients diagnosed with MCI. As such, it is important to note that the data are limited to this group of ADNI MCI subjects, and it is acknowledged that much larger studies will be needed to determine the utility of the biomarkers chosen here or select additional biomarkers that will be needed for application to the general population.
Another limitation was that this study was not longitudinal. A longitudinal study would allow identification of more subtle, individual changes in autoantibody profiles associated with successive stages of disease progression, and then a determination of which changes are common among individuals at the same disease stage.
Another weakness is that the age-matched and gender-matched controls used here did not have measurements of CSF Aβ42 levels. Finally, we did not test the efficacy of the AD-associated MCI biomarker panel for use in distinguishing subjects with AD-associated MCI from patients with MCI due to other causes (e.g., cerebrovascular disease, drug side-effects, depression, excessive alcohol use, poor vascular perfusion of the brain, and neurodegeneration unrelated to AD).
In conclusion, we report here a method for early AD diagnosis at the MCI stage. Early diagnosis of dementia has many potential benefits for clinicians, patients, and family members alike. These benefits include, but are not limited to earlier treatment, which may delay symptom progression, enrollment into clinical trials, which could potentially facilitate the development of new therapies and drug targets, as well as the ability to make lifestyle arrangements and manage future medical care. In addition to MCI, this simple blood-based diagnostic method has also been verified in the detection and staging of early-stage PD, suggesting the potential for widespread application of this platform as a multi-disease diagnostic tool.
http://www.dadm.alzdem.com/article/S2352-8729%2816%2930015-X/fulltext
