Predicting Alzheimer disease from a blood-based biomarker profile: a 54-month follow-up

Samantha C. Burnham*, Christopher C. Rowe, David Baker, Ashley I. Bush, James D. Doecke, Noel G. Faux, Simon M. Laws, Ralph N. Martins, Paul Maruff, S. Lance Macaulay, Stephanie Rainey-Smith, Greg Savage, David Ames, Colin L. Masters, William Wilson, Victor L. Villemagne

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    20 Citations (Scopus)

    Abstract

    Objective: We assessed a blood-based signature, which previously demonstrated high accuracy at stratifying individuals with high or low neocortical β-amyloid burden (NAB), to determine whether it could also identify individuals at risk of progression to Alzheimer disease (AD) within 54 months. Methods: We generated the blood-based signature for 585 healthy controls (HCs) and 74 participants with mild cognitive impairment (MCI) from the Australian Imaging, Biomarkers and Lifestyle Study who underwent clinical reclassification (blinded to biomarker findings) at 54-month follow-up. The individuals were split into estimated high and low NAB groups based on a cutoff of 1.5 standardized uptake value ratio. We assessed the predictive accuracy of the high and low NAB groupings based on progression to mild cognitive impairment or AD according to clinical reclassification at 54-month follow-up. Results: Twelve percent of HCs with estimated high NAB progressed in comparison to 5% of HCs with estimated low NAB (odds ratio 2.4). Forty percent of the participants with MCI who had estimated high NAB progressed in comparison to 5% of the participants with MCI who had estimated low NAB (odds ratio 12.3). These ratios are in line with those reported for Pittsburgh compound B-PET results. Individuals with estimated high NAB had faster rates of memory decline than those with estimated low NAB. Conclusion: These findings suggest that a simple blood-based signature not only provides estimates of NAB but also predicts cognitive decline and disease progression, identifying individuals at risk of progressing toward AD at the prodromal and preclinical stages.

    Original languageEnglish
    Pages (from-to)1093-1101
    Number of pages9
    JournalNeurology
    Volume87
    Issue number11
    DOIs
    Publication statusPublished - 13 Sep 2016

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