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CSF peptides from VGF and other markers enhance prediction of MCI to AD progression using the ATN framework.

Authors :
Llano DA
Devanarayan P
Devanarayan V
Source :
Neurobiology of aging [Neurobiol Aging] 2023 Jan; Vol. 121, pp. 15-27. Date of Electronic Publication: 2022 Oct 01.
Publication Year :
2023

Abstract

The amyloid beta, tau, neurodegenerative markers framework has been proposed to serve as a system to classify and combine biomarkers for Alzheimer's Disease (AD). Although cerebrospinal (CSF) fluid AT (amyloid beta and tau)-based biomarkers have a well-established track record to distinguish AD from control subjects and to predict conversion from mild cognitive impairment (MCI) to AD, there is not an established non-tau based neurodegenerative ("N") marker from CSF. Here, we examine the ability of several candidate peptides in the CSF to serve as "N" markers to both classify disease state and predict MCI to AD conversion. We observed that although many putative N markers involved in synaptic processing and neuroinflammation were able to, when examined in isolation, distinguish MCI converters from non-converters, a derivative from VGF, when combined with AT markers, most strongly enhanced prediction of MCI to AD conversion. Low CSF VGF levels were also predictive of MCI to dementia conversion in the setting of normal AT markers, suggesting that it may serve as a very early predictor of dementia conversion. Other markers derived from neuronal pentraxin 2, GAP-43 and a 14-3-3 protein were also able to enhance MCI to AD prediction when used as a marker of neurodegeneration, but VGF had the highest predictive capacity. Thus, we propose that low levels of VGF in CSF may serve as "N" in the amyloid beta, tau, neurodegenerative markers framework to enhance the prediction of MCI to AD conversion.<br />Competing Interests: Disclosure statement DAL has consulted for Eisai Inc., Boston HealthCare and Techspert.io in the past year, VD is an employee of Eisai, Inc.<br /> (Copyright © 2022 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1558-1497
Volume :
121
Database :
MEDLINE
Journal :
Neurobiology of aging
Publication Type :
Academic Journal
Accession number :
36368195
Full Text :
https://doi.org/10.1016/j.neurobiolaging.2022.07.015