Evidence mapPaperPMID 42413022Full record

ArticleJournal of proteome research2026

Deep Plasma Proteomics-Based Diagnostic Panel for Early Detection of Amnestic Mild Cognitive Impairment.

Hui Shan, Gaigai Lu, Yuyao Yuan, Qiongye Dong, Chongzhou Fang, Keyan Yu, Lele Chen, Zhuonan Wei, Hui Chen, Lin Hu and 9 more

Abstract read
In one paragraph

Article in Journal of proteome research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

19 authors.

Hui ShanInstitute of Precision Medicine, Peking University Shenzhen Hospital, Shenzhen518036, China.
Gaigai LuDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.ORCID 0009-0007-3734-8800
Yuyao YuanInstitute of Systems Biomedicine, Beijing Key Laboratory of Tumor Systems Biology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing100191, China.ORCID 0000-0002-8893-0696
Qiongye DongInstitute of Precision Medicine, Peking University Shenzhen Hospital, Shenzhen518036, China.
Chongzhou FangCentral Laboratory, Peking University Shenzhen Hospital, Shenzhen518036, China.
Keyan YuDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Lele ChenDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Zhuonan WeiDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Hui ChenDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Lin HuDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Tong WuDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Silin TaoDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Yunchen ChenDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Juan LuoInstitute of Precision Medicine, Peking University Shenzhen Hospital, Shenzhen518036, China.
Yulong QiDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Jun HuDepartment of Neurology, Peking University Shenzhen Hospital, Shenzhen518036, China.
Guanxun ChengDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Xiang FanDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen518036, China.
Yuxin YinInstitute of Precision Medicine, Peking University Shenzhen Hospital, Shenzhen518036, China.

Funding

National Natural Science Foundation of China 62103397Science and Technology Foundation of Shenzhen City KCXFZ20211020163408012Shenzhen High-level Hospital Construction Fund NAShenzhen Municipal Fundamental Research Program JCYJ20220818102811024
6 · The paper itself

Abstract

Amnestic mild cognitive impairment (aMCI) is often considered an early clinical stage of Alzheimer's disease (AD), but its subtle presentation leads to infrequent neurological evaluations. Early plasma biomarker screening during routine check-ups in community hospitals could enhance aMCI detection rates. Advances in proteomics, particularly mass spectrometry, have enabled the detection of low-abundance plasma proteins, opening new possibilities for aMCI biomarker identification. This study included 84 participants from the STAR cohort. We utilized deep plasma proteomics to detect low-abundance proteins, enriched with nanoparticle magnetic beads. An early diagnostic model for aMCI was developed through bioinformatics and machine learning, with performance compared to the Simoa assay. We identified 4268 low-abundance plasma proteins and constructed a 12-protein diagnostic panel (AUC = 0.992 in the training set, AUC = 0.933 in the testing set), outperforming the Simoa assay (accuracy: 93.9% vs 24.4%). In conclusion, the 12-protein panel provides a cost-effective method for early aMCI detection, potentially improving screening efficacy.

Indexed as

AmnesiaBlood ProteinsCognitive DysfunctionProteomicsAgedAlzheimer DiseaseBiomarkersEarly DiagnosisFemaleHumansMachine LearningMaleBiomarkersBlood Proteinsamnestic mild cognitive impairmentdiagnostic modelmachine learningmass spectrometryplasma proteomics

Identifiers

PMID42413022
PMCPMC13459555

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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.