Evidence map›Paper›PMID 40914747›Full record

ArticleGeroScience2026

Prediction of cognitive decline and Alzheimer's disease conversion by a plasma biomarker panel in non-demented individuals.

Min-Koo Park, Jinhyun Ahn, Jin-Muk Lim, Sung-Joo Hwang, Keun-Cheol Kim

Abstract read
In one paragraph

Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Min-Koo ParkDepartment of Biological Sciences, College of Natural Sciences, Kangwon National University, Kangwon, 24341, Republic of Korea. mkparc@kangwon.ac.kr.ORCID http://orcid.org/0000-0002-5555-2588
Jinhyun AhnDepartment of Management Information Systems, College of Economics & Commerce, Jeju National University, Jeju, 63243, Republic of Korea.
Jin-Muk LimPrecision Medicine Research Institute, Innowl, Co., Ltd, Seoul, 08350, Republic of Korea.
Sung-Joo HwangIntegrated Medicine Institute, Loving Care Hospital, Gyeonggi, 463400, Republic of Korea.
Keun-Cheol KimDepartment of Biological Sciences, College of Natural Sciences, Kangwon National University, Kangwon, 24341, Republic of Korea. kckim@kangwon.ac.kr.

Funding

Ministry of Science and ICT, South Korea RS-2024-00348897National IT Industry Promotion Agency A0121-23-2335
6 · The paper itself

Abstract

Alzheimer's disease (AD) represents a growing global health burden, underscoring the urgent need for reliable diagnostic and prognostic biomarkers. Although several disease-modifying treatments have recently become available, their effects remain limited, as they primarily delay rather than halt disease progression. Thus, the early and accurate identification of individuals at elevated risk for conversion to AD dementia is crucial to maximize the effectiveness of these therapies and to facilitate timely intervention strategies. Baseline plasma concentrations of amyloid beta 40 (Aβ40), amyloid beta 42 (Aβ42), glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), and tau phosphorylated at residue 181 and 217 (pTau181, pTau217) were quantified in 233 non-demented participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and followed for up to 11 years. Covariates included demographic variables and neuropsychological measures. Longitudinal cognitive trajectories were modelled with linear mixed-effects models (LMM), and the risk of progression to AD dementia was evaluated with logistic regression and Cox proportional-hazards analyses. Longitudinally, higher baseline plasma levels of GFAP, NFL, pTau181, and pTau217 independently predicted steeper cognitive decline. Cross-sectional analyses demonstrated significant associations of pTau217, pTau181, and Aβ42 with baseline memory impairment. A logistic regression model incorporating five plasma biomarkers-Aβ42, GFAP, NFL, pTau181, and pTau217-demonstrated robust predictive accuracy for discrimination of future converters to AD dementia. The addition of demographic variables and a baseline memory score further improved model specificity and positive predictive value. These findings support the utility of a concise plasma biomarker panel comprising Aβ42, GFAP, NFL, pTau181, and pTau217 for predicting both longitudinal cognitive deterioration and conversion to AD dementia. This less-invasive blood-based panel could serve as a practical triage tool to enrich clinical trials and facilitate timely therapeutic interventions with emerging disease-modifying treatments.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgedAged, 80 and overAmyloid beta-PeptidesBiomarkersDisease ProgressionFemaleGlial Fibrillary Acidic ProteinHumansMaleNeurofilament ProteinsNeuropsychological TestsPeptide FragmentsPredictive Value of Teststau ProteinsAmyloid beta-Peptidesamyloid beta-protein (1-42)BiomarkersGlial Fibrillary Acidic ProteinNeurofilament ProteinsPeptide Fragmentstau ProteinsAlzheimer’s disease (AD)Cognitive declineMCI-to-AD conversionMild cognitive impairment (MCI)Plasma biomarker

Identifiers

PMID40914747
PMCPMC13356247

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.