Plasma biomarkers for prediction of Alzheimer's disease neuropathologic change

Abstract

While plasma biomarkers for Alzheimer's disease (AD) are increasingly being evaluated for clinical diagnosis and prognosis, few population-based autopsy studies have evaluated their utility in the context of predicting neuropathological changes. Our goal was to investigate the utility of clinically available plasma markers in predicting Braak staging, neuritic plaque score, Thal phase, and overall AD neuropathological change (ADNC).We utilized a population-based prospective study of 350 participants with autopsy and antemortem plasma biomarker testing using clinically available antibody assay (Quanterix) consisting of Aβ42/40 ratio, p-tau181, GFAP, and NfL. We utilized a variable selection procedure in cross-validated (CV) logistic regression models to identify the best set of plasma predictors along with demographic variables, and a subset of neuropsychological tests comprising the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo-PACC). ADNC was best predicted with plasma GFAP, NfL, p-tau181 biomarkers along with APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.798). Braak staging was best predicted using plasma GFAP, p-tau181, and cognitive scores (CV AUC = 0.774). Neuritic plaque score was best predicted using plasma Aβ42/40 ratio, p-tau181, GFAP, and NfL biomarkers (CV AUC = 0.770). Thal phase was best predicted using GFAP, NfL, p-tau181, APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.754). We found that GFAP and p-tau provided non-overlapping information on both neuritic plaque and Braak stage scores whereas Aβ42/40 and NfL were mainly useful for prediction of neuritic plaque scores. Separating participants by cognitive status improved predictive performance, particularly when plasma biomarkers were included. Plasma biomarkers can differentially inform about overall ADNC pathology, Braak staging, and neuritic plaque score when combined with demographics and cognitive variables and have significant utility for earlier detection of AD.

Keywords: Alzheimer’s disease; Neuropathology; Personalized medicine; Plasma biomarkers.

Fig. 1

Comparison of plasma biomarker concentrations for Aβ42/40 ratio, GFAP, NfL, and p-tau181 when stratified by high and low ADNC groups. ADNC Alzheimer’s disease neuropathologic change; Aβ42/40 ratio: amyloid-β 42/40 ratio; NfL neurofilament light; p-tau181 phosphorylated tau 181

Fig. 2

Comparison of plasma biomarker concentrations for Aβ42/40 ratio, GFAP, NfL, and p-tau181 when stratified by high and low Braak stage. Aβ42/40 ratio amyloid-β 42/40 ratio; NfL neurofilament Light; p-tau181 phosphorylated tau 181

Fig. 3

Comparison of plasma biomarker concentrations for Aβ42/40 ratio, GFAP, NfL, and p-tau181 when stratified by high and low neuritic plaque burden. Aβ42/40 ratio amyloid-β 42/40 ratio; NfL neurofilament light; p-tau181 phosphorylated tau 181

Fig. 4

Comparison of plasma biomarker concentrations for Aβ42/40 ratio, GFAP, NfL, and p-tau181 when stratified by high and low Thal amyloid phase. Aβ42/40 ratio amyloid-β 42/40 ratio; NfL neurofilament light; p-tau181 phosphorylated tau 181

Fig. 5

Comparison of predictive performance of neuropathologic scales with different pools of variables available. Plasma was the best model selected from just the plasma markers, Plasma + Demographics was the best model selected when including plasma markers plus covariates in the election pool, and Plasma + Demographics + PACC was the best model selected when additionally including PACC in the selection pool. * indicates p < 0.05, ** indicates p < 0.01