Evidence mapPaperPMID 40852041Full record

ReviewPrecision clinical medicine2025

Glycosylation in kidney diseases.

Yingying Ling, Fei Cai, Tao Su, Yi Zhong, Ling Li, Bo Meng, Guisen Li, Meng Gong, Hao Yang, Xinfang Xie and 4 more

Abstract readReview
In one paragraph

Review in Precision clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
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  8. 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

14 authors.

Yingying LingDepartment of Nephrology, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
Fei CaiDepartment of Nephrology, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
Tao SuDepartment of Nephrology, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
Yi ZhongDepartment of Nephrology, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
Ling LiDepartment of Nephrology, Institute of Kidney Diseases, West China Hospital, Sichuan University, Chengdu 610041, China.
Bo MengTechnology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, China.
Guisen LiRenal Department and Institute of Nephrology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Sichuan Clinical Research Center for Kidney Diseases, Chengdu 611731, China.
Meng GongDepartment of Nephrology, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
Hao YangTransplant Center and NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu 610041, China.ORCID https://orcid.org/0000-0003-2214-9474
Xinfang XieDepartment of Nephrology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.
Zhenyu SunDepartment of Pathology, Johns Hopkins University, Baltimore, MD 21231, United States.
Yang ZhaoTechnology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, China.
Fang LiuDepartment of Nephrology, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
Yong ZhangDepartment of Nephrology, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.ORCID https://orcid.org/0000-0003-0513-8941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein glycosylation is a critical post-translational modification that influences protein folding, localization, stability, and functional interactions by attaching glycans to specific sites. This process is crucial for biological functions of glycoproteins, and aberrant glycosylation can lead to genetic disorders, immune system issues, and multi-organ pathologies. Recent advancements in glycoproteomic technologies have made the study of protein glycosylation a key focus for understanding the pathogenesis of kidney diseases. This review provides a comprehensive overview of protein glycosylation mechanisms, its biological roles, molecular pathways, and significant functions in renal physiology and pathology. It specifically highlights the dynamic changes and regulatory networks associated with aberrant glycosylation in kidney diseases such as immunoglobulin A nephropathy, diabetic kidney disease, autosomal dominant polycystic kidney disease, renal cell carcinoma, and acute kidney injury. It also evaluates the clinical applications of related technologies and biomarkers. Additionally, it discusses the challenges in developing glycosylation-targeted therapeutic strategies. Future research should focus on clarifying cell-specific glycosylation regulatory networks in the kidney, integrating glycobiology with multi-omics approaches, and improving precision diagnostics and treatment for kidney diseases.

Indexed as

biomarkersglycoproteomicsglycosylationkidney diseasesmass spectrometry

Identifiers

PMID40852041
PMCPMC12368498

What Socratic holds

Textmetadata
LicenceCC BY
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.