Evidence map›Paper›PMID 42293149›Full record

ArticleFrontiers in aging neuroscience2026

SVIP in plasma: a candidate blood-based biomarker for early detection of amnestic mild cognitive impairment.

Gaigai Lu, Hui Shan, Yuxin Yin, Lele Chen, Keyan Yu, Zhuonan Wei, Hui Chen, Lin Hu, Yulong Qi, Tong Wu and 3 more

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Gaigai Lu *Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Hui Shan *Institute of Precision Medicine, Peking University Shenzhen Hospital, Shenzhen, China.
Yuxin YinInstitute of Precision Medicine, Peking University Shenzhen Hospital, Shenzhen, China.
Lele ChenDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Keyan YuDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Zhuonan WeiDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Hui ChenDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Lin HuDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Yulong QiDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Tong WuDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Silin TaoDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Xiang FanDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.
Guanxun ChengDepartment of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Amnestic mild cognitive impairment (aMCI) represents a critical clinical window for early intervention in Alzheimer's disease (AD). Identifying readily detectable, high-abundance plasma biomarkers for aMCI remains clinically important. Overexpression of Valosin-Containing Protein (VCP) has been shown to enhance autophagy and reduce tau levels in AD animal models. Notably, VCP, with a molecular weight of 90 kDa, typically assembles into hexamers, which is hypothesized to restrict its ability to cross the blood-brain barrier even under neurodegenerative conditions. In contrast, the small VCP-interacting protein (SVIP), with a molecular weight of only 9 kDa, interacts with VCP to maintain the dynamic stability of autophagosomes within cells. Therefore, we aim to explore plasma SVIP as a peripheral blood biomarker for aMCI and assess whether it can outperform VCP in detecting aMCI. Methods: This was a retrospective study based on the STAR (Shenzhen Multi-modal Aging Research) cohort. Participants were recruited as a convenience sample. Eighty-four participants (44 cognitively unimpaired [CU], 40 aMCI) were included, with diagnostic classification based on standardized clinical and neuropsychological criteria. Plasma levels of SVIP and VCP were measured using deep plasma proteomics enriched with biofunctional magnetic beads. Diagnostic performance was evaluated using Receiver Operating Characteristic (ROC) analysis and DeLong's test. This study was registered in the Chinese Clinical Trial Registry (ChiCTR2200066700). Results: Compared to the CU group, the aMCI group showed significantly decreased SVIP ( Conclusion: Plasma SVIP demonstrates significantly higher diagnostic accuracy than VCP for the detection of aMCI, suggesting its potential as a candidate blood-based biomarker pending large-scale pathophysiological validation.

Indexed as

Alzheimer’s diseaseblood-based biomarkersdeep plasma proteomicsmild cognitive impairmentSVIPVCP

Identifiers

PMID42293149
PMCPMC13260444

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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 OpenQuestion graph.