Feasibility of an early Alzheimer's disease immunosignature diagnostic test

https://doi.org/10.1016/j.jneuroim.2012.09.014Get rights and content

Abstract

A practical diagnostic test is needed for early Alzheimer's disease (AD) detection. Immunosignaturing, a technology that employs antibody binding to a random-sequence peptide microarray, generates profiles that distinguish transgenic mice engineered with familial AD mutations (APPswe/PSEN1-dE9) from non-transgenic littermates. It can also detect an AD-like signature in humans. Here, we assess the changes in the immunosignature at different time points of the disease in mice and humans. We also evaluate the accuracy of the late-stage signature as a test to discriminate between young mice with familial AD mutations from non-transgenic littermates. Plasma samples from AD patients were assayed 3–12 months apart, while APPswe/PSEN1-dE9 and non-transgenic controls supplied plasma at monthly intervals until they reached 15 months of age. Microarrays with 10,000 random-sequence peptides were used to compare antibody binding patterns. These patterns gradually changed over the life-span of mice. Strong, characteristic signatures were observed in transgenic mice at early, mid and late stages, but these profiles had minimal overlap. The signature of young transgenic mice had an error rate of 18% at classifying plasma samples from late-stage transgenic mice. Conversely, the late-stage transgenic mice signature discriminated between young transgenic mice and littermates with an error rate of 21%. Less distinctive profiles were recognizable throughout the transgenic mice lifespan, being detectable as early as 2 months. The human signature had minimal change on short-term follow-up. Our results call for a reappraisal of the way incipient AD is studied, as biomarkers seen in late-stages of the disease may not be relevant in earlier stages.

Introduction

Alzheimer's disease (AD) is the most common cause of dementia, affecting about 35.6 million people world-wide (Chui and Lee, 2002, Abbott, 2011). Because AD cannot be prevented or cured, the number of affected persons doubles every two decades, causing crippling cognitive disability and economic losses in excess of $604 billion per year. Early detection and treatment will be essential to control this problem (Buckholtz, 2011). In spite of recent advances (Shaw et al., 2007, Shaw et al., 2009, Ewers et al., 2011), no specific tests are universally used to diagnose AD. As pathology slowly progresses for decades before initial symptoms emerge (Shaw et al., 2009), and since initial manifestations are generally subtle (Morris et al., 2001, Kawas, 2003, Grundman et al., 2004), a potential diagnostic test for AD must be highly sensitive. Given that future treatments are likely to target people with mild or no symptoms (Shaw et al., 2007, Shaw et al., 2009, Buckholtz, 2011), the test must also be highly specific. Considering the challenges involved in obtaining samples from subjects with early AD stages, we explored the utility of a test developed using plasma samples from the terminal phase of the illness as a pre-symptomatic diagnostic tool.

Immunosignaturing is a general diagnostic technology which involves diluting blood and applying it to an array consisting of 10,000 random-sequence peptides (Legutki et al., 2010, Restrepo et al., 2011, Kukreja et al., 2012b, Stafford et al., 2012, Hughes et al., 2012). Antibodies bind to the array revealing a signature affected by the health status of the individual. The initial application of this technology showed that both transgenic mice with cerebral amyloidosis and humans with AD have distinctive immunosignatures relative to healthy age-matched controls (Restrepo et al., 2011), but no investigation of the signature stability over time was undertaken. Since the clinical diagnosis of AD is corroborated by autopsy in 65–80% of cases (Chui and Lee, 2002), a non-invasive blood test could be useful in clinical practice. More importantly, the application of this technology to the pre-symptomatic diagnosis of AD could help prevent or delay the onset of dementia if disease-modifying therapies become available. The simplest approach to developing such a test is to use the signature of autopsy-confirmed AD to create an indicator for early stages of dementia. Here we use a mouse model of AD, APPswe/PSEN1-dE9 mice, to explore this possibility.

Section snippets

Microarray

The protocols, performance, sample preparation methods and statistical analyses of the technology are described elsewhere (Brown et al., 2011, Restrepo et al., 2011, Halperin et al., 2012, Hughes et al., 2012, Kroening et al., 2012, Kukreja et al., 2012a, Kukreja et al., 2012b, Stafford et al., 2012). Briefly, an immunoassay was developed using 10,000 random-sequence 20-mers covalently attached to a glass slide. Peptides were designed with random sequences, except for glycine–serine–cysteine

Results

Results from immunosignaturing assays require an understanding of the characteristics of the technology. While expression or SNP microarrays demonstrate a one-to-one binding between RNA or DNA and the target probe, the immunosignaturing peptide arrays enable multiple specificities of antibody to bind a single peptide while a single antibody may bind multiple peptides (Kukreja et al., 2012b). This effect is accommodated by the statistical methods used to select peptides and is noted as the

Discussion

Evaluating the potential of immunosignaturing as a diagnostic test for early AD, we first looked at the stability of the signatures in age-matched people with and without AD. We observed a distinctive AD signature, which remained stable in samples taken 3–12 months apart in the same person. We previously identified an AD-specific signature (Restrepo et al., 2011), but now show that the signature remains stable over the short term. A relative proportion of the signature is personal, while another

Disclosure statement

P.S. and S.A.J. have jointly filed a patent for immunosignaturing. L.R. disclosed no potential or actual conflicts of interest, financial or otherwise.

Acknowledgments

This work was supported by grants from the Arizona Alzheimer's Consortium (# AGR200737) and the Alzheimer's Drug Discovery Foundation (# 291001) to SAJ. We are indebted to Alex Roher for providing human plasma samples, and Kathy Goehring and Stephen W. Coons for their assistance with immunohistochemistry. We also acknowledge Bart Legutki and John Lainson for their help in developing the immunoassay and for the production and quality-control of microarray slides, respectively. Finally, we are

References (33)

  • J. Brown et al.

    Statistical methods for analyzing immunosignatures

    BMC Bioinformatics

    (2011)
  • N.S. Buckholtz

    In search of biomarkers

    Nature

    (2011)
  • R.J. Caiazzo et al.

    Autoantibody microarrays for biomarker discovery

    Expert Rev. Proteomics

    (2007)
  • S. Cenci et al.

    Managing and exploiting stress in the antibody factory

    FEBS Lett.

    (2007)
  • H. Chui et al.

    Clinical criteria for demential subtypes

  • J. Cooperman et al.

    Cell division rates of primary human precursor B cells in culture reflect in vivo rates

    Stem Cells

    (2004)
  • Cited by (0)

    View full text