Evidence map›Paper›PMID 40328427›Full record

ArticleJournal of advanced research2026

Plasma proteomics identify novel biomarkers and dynamic patterns of biological aging.

Ling-Zhi Ma, Wei-Shi Liu, Yu He, Yi Zhang, Jia You, Jian-Feng Feng, Lan Tan, Wei Cheng, Jin-Tai Yu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of advanced research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

9 authors.

Ling-Zhi MaDepartment of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.
Wei-Shi LiuDepartment of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
Yu HeDepartment of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
Yi ZhangDepartment of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
Jia YouDepartment of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.
Jian-Feng FengInstitute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
Lan TanDepartment of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China. Electronic address: dr.tanlan@163.com.
Wei ChengDepartment of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China. Electronic address: wcheng@fudan.edu.cn.
Jin-Tai YuDepartment of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China. Electronic address: jintai_yu@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPlasma proteomics examines levels of thousands of proteins and has the potential to identify clinical biomarkers for healthy aging.

objectivesThis large proteomics study aims to identify clinical biomarkers for healthy aging and further explore potential mechanisms involved in aging.

methodsThis study analyzed data from 51,904 UK Biobank participants to explore the association between 2,923 plasma proteins and nine aging-related phenotypes, including PhenoAge, KDM-Biological Age, healthspan, parental lifespan, frailty, and longevity. Protein levels were measured using proteomics, and associations were assessed with a significance threshold of P < 1.90E-06. We utilized the DE-SWAN method to detect and measure the nonlinear alterations in plasma proteome during the process of biological aging. Mendelian randomization was applied to assess causal relationships, and a PheWAS explored the broader health impacts of these proteins.

resultsWe identified 227 proteins significantly associated with aging (P < 1.90E-06), with the pathway of inflammation and regeneration being notably implicated. Our findings revealed fluctuating patterns in the plasma proteome during biological aging in middle-aged adults, pinpointing specific peaks of biological age-related changes at 41, 60, and 67 years, alongside distinct age-related protein change patterns across various organs. Furthermore, mendelian randomization further supported the causal association between plasma levels of CXCL13, DPY30, FURIN, IGFBP4, SHISA5, and aging, underscoring the significance of these drug targets. These five proteins have broad-ranging effects. The PheWAS analysis of proteins associated with aging highlighted their crucial roles in vital biological processes, particularly in overall mortality, health maintenance, and cardiovascular health. Moreover, proteins can serve as mediators in healthy lifestyle and aging processes.

conclusionThese significant discoveries underscore the importance of monitoring and intervening in the aging process at critical periods, alongside identifying potential biomarkers and therapeutic targets for age-related disorders within the plasma proteomic landscape, thus offering valuable insights into healthy aging.

Indexed as

AgingBiomarkersBlood ProteinsHealthy AgingProteomeProteomicsAdultAgedFemaleHumansLongevityMaleMendelian Randomization AnalysisMiddle AgedBiomarkersBlood ProteinsProteomeBiological ageBiomarkersHealth agingNonlinear changeProteomics

Identifiers

PMID40328427
PMCPMC12869252

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.