Combination of plasma amyloid beta(1-42/1-40) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology

Abstract

Background: Blood-based biomarkers for Alzheimer's disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta_(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity.

Methods: We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET-), mild cognitive impairment (26 PET+, 24 PET-), or AD-dementia (132 PET+). Plasma Abeta_(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald's backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman's correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA).

Results: Abeta_(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p < 0.001 respectively), and GFAP and NfL independently associated with syndrome diagnosis (p = 0.001 and p = 0.048 respectively). The optimal panel identifying a positive amyloid status included Abeta_(1-42/1-40) and GFAP, alongside age and APOE (AUC = 88% (95% CI 83-93%), 82% sensitivity, 86% specificity), while excluding NfL and sex. GFAP and NfL robustly associated with cognitive performance on global cognition and all major cognitive domains (GFAP: range standardized β (sβ) = - 0.40 to - 0.26; NfL: range sβ = - 0.35 to - 0.18; all: p < 0.002), whereas Abeta_(1-42/1-40) associated with global cognition, memory, attention, and executive functioning (range sβ = 0.22 - 0.11; all: p < 0.05) but not language. GFAP and NfL showed moderate positive correlations with MTA (both: Spearman's rho> 0.33, p < 0.001). Abeta_(1-42/1-40) showed a moderate negative correlation with MTA (Spearman's rho = - 0.24, p = 0.001).

Discussion and conclusions: Combination of plasma Abeta_(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring.

Keywords: Alzheimer’s continuum; Amyloid pathology; Blood-based biomarkers; Plasma GFAP; Plasma amyloid beta.

Fig. 1

Boxplots of raw plasma biomarker levels for amyloid PET negative (−) and amyloid PET positive (+) individuals. Statistical analysis was conducted using age and sex adjusted two-way ANOVAs for amyloid PET status and syndrome diagnosis on the plasma biomarker levels, of which the p value of the independent effect of PET status is presented. Plasma GFAP and plasma NfL, levels were natural log transformed prior to statistical analysis. Abeta, amyloid beta; GFAP, glial fibrillary acidic protein; NfL, neurofilament light; PET, positron emission tomography

Fig. 2

Boxplots of raw plasma biomarker levels for amyloid PET status (negative: -; positive: +) in function of the syndrome diagnostic groups. Statistical analysis was conducted using age and sex adjusted two-way ANOVAs evaluating the independent effects of amyloid PET status and syndrome diagnosis on the plasma biomarker levels. For plasma Abeta_(1-42/1-40), PET status had a main effect (p = 0009) but not syndrome diagnosis (p = 0.192). For GFAP, both PET (p < 0.001) and syndrome diagnosis (p = 0.048) had main effects. For NfL, syndrome diagnosis (p = 0.001) but not PET status (p = 0.155) had a main effect. Plasma GFAP and plasma NfL levels were natural log transformed prior to ANOVA. Abeta, amyloid beta; GFAP, glial fibrillary acidic protein; NfL, neurofilament light; PET, positron emission tomography

Fig. 3

ROCs for amyloid PET positivity in the total study population (a) and non-demented subset (b). Individual plasma biomarkers GFAP, Abeta_(1-42/1-40), and NfL are plotted as well as the combined panel best predicting amyloid PET positivity. Panel in the total population (a) are the predicted values of the combined plasma Abeta_(1-42/1-40), plasma GFAP, age, and APOE ε4 carriership panel (AUC = 0.88 (95% CI 0.83–0.93)). Panel in the non-demented population (SCD + MCI) (b) are the predicted values of the combined plasma Abeta_(1-42/1-40), plasma GFAP, and APOE ε4 carriership panel (AUC = 0.84 (95% CI 0.76–0.92)). GFAP, glial fibrillary acidic protein; Abeta, amyloid beta; NfL, neurofilament light

Fig. 4

Heat plots with predicted probabilities for amyloid PET positivity in the total study population. Heat plots were constructed by filling out the logistic regression formula with constant = 0.839, and beta’s B = − 19.02 for Abeta_(1-42/1-40), B = 0.019 for GFAP, B = − 0.618 for age (dichotomous variable: younger (= 0) versus older (= 1) than cohort’s average age of 63 years) and B = 1.625 for APOE ε4 carriership (non-carrier = 0, carrier = 1). Abeta, amyloid beta; GFAP, glial fibrillary acidic protein; APOE, apolipoprotein E

Fig. 5

Associations of plasma biomarkers with cognitive performance across the total study cohort, presented as standardized effect sizes with 95% confidence intervals of age, sex, and education (according to Verhage (1965) system) adjusted linear regression analysis between plasma biomarker levels and cognitive domain scores. Plasma Abeta_(1-42/1-40) levels were inverted prior to analysis, so that the direction of effect sizes are comparable for all markers. Abeta, amyloid beta; GFAP, glial fibrillary acidic protein; NfL, neurofilament light