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Neurology. 2016 Sep 13;87(11):1093-101. doi: 10.1212/WNL.0000000000003094. Epub 2016 Aug 17.

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

Author information

1
From eHealth (S.C.B.), CSIRO Health and Biosecurity, Floreat; Department of Nuclear Medicine and Centre for PET (C.C.R.), Austin Health, Heidelberg; Department of Medicine (C.C.R., V.L.V.), Austin Health, University of Melbourne, Heidelberg, Australia; Janssen Research and Development (D.B.), Titusville, NJ; Mental Health Research Institute (A.I.B., N.G.F.), Academic Unit for Psychiatry of Old Age, Department of Psychiatry (D.A.), and The Florey Institute (C.L.M., V.L.V.), University of Melbourne, Parkville; eHealth (J.D.D.), CSIRO Health and Biosecurity, Herston; Centre of Excellence for Alzheimer's Disease Research & Care (S.M.L., R.N.M., S.R.-S.), School of Medical Sciences, Edith Cowan University, Joondalup; School of Biomedical Sciences (S.M.L.), Faculty of Health Sciences, Curtin University, Bentley; Sir James McCusker Alzheimer's Disease Research Unit (Hollywood Private Hospital) (R.N.M., S.R.-S.), Perth; Cogstate (P.M.), Melbourne; CSIRO Food and Nutrition Flagship (S.L.M.), Melbourne; Department of Psychology (G.S.), Macquarie University, Sydney; and eHealth (W.W.), CSIRO Health and Biosecurity, North Ryde, Australia. samantha.burnham@csiro.au.
2
From eHealth (S.C.B.), CSIRO Health and Biosecurity, Floreat; Department of Nuclear Medicine and Centre for PET (C.C.R.), Austin Health, Heidelberg; Department of Medicine (C.C.R., V.L.V.), Austin Health, University of Melbourne, Heidelberg, Australia; Janssen Research and Development (D.B.), Titusville, NJ; Mental Health Research Institute (A.I.B., N.G.F.), Academic Unit for Psychiatry of Old Age, Department of Psychiatry (D.A.), and The Florey Institute (C.L.M., V.L.V.), University of Melbourne, Parkville; eHealth (J.D.D.), CSIRO Health and Biosecurity, Herston; Centre of Excellence for Alzheimer's Disease Research & Care (S.M.L., R.N.M., S.R.-S.), School of Medical Sciences, Edith Cowan University, Joondalup; School of Biomedical Sciences (S.M.L.), Faculty of Health Sciences, Curtin University, Bentley; Sir James McCusker Alzheimer's Disease Research Unit (Hollywood Private Hospital) (R.N.M., S.R.-S.), Perth; Cogstate (P.M.), Melbourne; CSIRO Food and Nutrition Flagship (S.L.M.), Melbourne; Department of Psychology (G.S.), Macquarie University, Sydney; and eHealth (W.W.), CSIRO Health and Biosecurity, North Ryde, Australia.

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.

PMID:
27534714
DOI:
10.1212/WNL.0000000000003094
[Indexed for MEDLINE]

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