Plasma proteins predict conversion to dementia from prodromal disease

Abstract

Background: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia.

Methods: Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays.

Results: Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%).

Conclusions: We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.

Keywords: Alzheimer's disease; Biomarker; Mild cognitive impairment; Pathology; Plasma; Prediction and magnetic resonance imaging.

Fig. 1

Feature selection workflow used to select the best attributes for mild cognitive impairment converter (MCI_c) classification.

Fig. 2

Receiver operating characteristic (ROC) curves obtained for the test set for (A) three models (proteins only, proteins + apolipoprotein E [APOE], and APOE only) from the full mild cognitive impairment, converter and nonconverter (MCI_c and MCI_nc) data sets and (B) for the test set for three models (proteins only, proteins + APOE + magnetic resonance imaging [MRI], and MRI only) in the subset with protein plus MRI imaging data.