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5 Antemortem Plasma GFAP Predicts Alzheimer’s Disease Neuropathological Changes

Published online by Cambridge University Press:  21 December 2023

Madeline Ally*
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Henrik Zetterberg
Affiliation:
University of Gothenburg, Mölndal, Sweden.
Kaj Blennow
Affiliation:
University of Gothenburg, Mölndal, Sweden.
Nicholas J. Ashton
Affiliation:
University of Gothenburg, Mölndal, Sweden.
Thomas K. Karikari
Affiliation:
University of Gothenburg, Mölndal, Sweden.
Hugo Aparicio
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Michael A. Sugarman
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Brandon Frank
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Yorghos Tripodis
Affiliation:
Boston University School of Public Health, Boston, MA, USA
Brett Martin
Affiliation:
Boston University School of Public Health, Boston, MA, USA
Joseph N. Palmisano
Affiliation:
Boston University School of Public Health, Boston, MA, USA
Eric G. Steinberg
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Irene Simkina
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Lindsay Farrer
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Gyungah Jun
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Katherine W. Turk
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Andrew E. Budson
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Maureen K. O’Connor
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Rhoda Au
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Wei Qiao Qiu
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Lee E. Goldstein
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Ronald Killiany
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Neil W. Kowall
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Robert A. Stern
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Jesse Mez
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Bertran R. Huber
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Ann C. McKee
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Thor D. Stein
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
Michael L. Alosco
Affiliation:
Boston University School of Medicine, Boston, MA, USA.
*
Correspondence: Madeline Ally, Boston University School of Medicine, mally@bu.edu.
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Abstract

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Objective:

Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).

Participants and Methods:

This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.

Results:

Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.

Conclusions:

The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.

Type
Poster Session 04: Aging | MCI
Copyright
Copyright © INS. Published by Cambridge University Press, 2023