Evidence map›Paper›PMID 39889701›Full record

ArticleCell genomics2025

Uncovering dark mass in population proteomics: Pan-analysis of single amino acid polymorphism relevant to cognition and aging.

Xiaojing Gao, Yuanyuan Yin, Yiqian Chen, Ling Lu, Jian Zhao, Xu Lin, Jiarui Wu, Qingrun Li, Rong Zeng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell genomics, 2025. 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. Article
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.

Xiaojing GaoShanghai Clinical Research and Trial Center, ShanghaiTech University, Shanghai 201210, China; Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai 201210, China; School of Life Sciences and Technology, ShanghaiTech University, Shanghai 201210, China.
Yuanyuan YinKey Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
Yiqian ChenShanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; School of Life Sciences and Technology, ShanghaiTech University, Shanghai 201210, China.
Ling LuKey Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
Jian ZhaoShanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai 201210, China; School of Life Sciences and Technology, ShanghaiTech University, Shanghai 201210, China.
Xu LinKey Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
Jiarui WuNational Facility for Protein Science Shanghai (NFPSS), Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China; School of Life Sciences and Technology, ShanghaiTech University, Shanghai 201210, China.
Qingrun LiNational Facility for Protein Science Shanghai (NFPSS), Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China. Electronic address: liqr@sari.ac.cn.
Rong ZengShanghai Clinical Research and Trial Center, ShanghaiTech University, Shanghai 201210, China; National Facility for Protein Science Shanghai (NFPSS), Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China; Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; School of Life Sciences and Technology, ShanghaiTech University, Shanghai 201210, China. Electronic address: zengrong@shanghaitech.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human proteome data across populations have been analyzed extensively to reveal protein quantitative associations with physiological or pathological states, while the single amino acid polymorphism (SAP) has been rarely investigated. In this work, we introduce a pan-SAP workflow that relies on pan-database searching independent of individual genome sequencing. Using ten cohorts comprising 2,004 individuals related to cognition disorder and aging, we quantify the SAP sites in key proteins, such as apolipoprotein E (APOE) in plasma and cerebrospinal fluid at the proteome level. Specifically, the quantification of heterozygous APOE-C112R, including its abundance and ratio, provides insights into the dosage effect and relationship with cognition disorder, which cannot be interpreted at the genomic level. Furthermore, our approach could precisely track age-related changes in APOE-C112R levels. Taken together, this pan-SAP workflow uncovered existing but hidden SAPs in multi-populations, connecting SAP quantification to disease progression and paving the way for broader proteomic investigations in complex diseases.

Indexed as

AgingApolipoproteins ECognitionPolymorphism, Single NucleotideProteomicsAgedAged, 80 and overFemaleHumansMaleMiddle AgedProteomeApolipoproteins EProteomeagingAlzheimer’s diseaseAPOE2APOE4body fluidpopulation proteomicssingle amino acid polymorphism

Identifiers

PMID39889701
PMCPMC11872527

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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 OpenQuestion graph.