Evidence map›Paper›PMID 34043214›Full record

ArticleJournal of endocrinological investigation2021

Urinary complement proteins and risk of end-stage renal disease: quantitative urinary proteomics in patients with type 2 diabetes and biopsy-proven diabetic nephropathy.

L Zhao, Y Zhang, F Liu, H Yang, Y Zhong, Y Wang, S Li, Q Su, L Tang, L Bai and 10 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of endocrinological investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
6.2field-weighted citation impact, top 2% of its field
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

19 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
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  8. Complement anaphylatoxins: Potential therapeutic target for diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025
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  15. Pursuing Diabetic Nephropathy through Aqueous Humor Proteomics Analysis.Oxidative medicine and cellular longevity · 2022
    Article
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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

20 authors at 2 institutions in 2 countries.

L ZhaoDivision of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
Y Zhang *Key Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
F LiuDivision of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China. liufangfh@163.com.ORCID http://orcid.org/0000-0003-1121-3004
H Yang *Key Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China. yanghao@scu.edu.cn.
Y ZhongKey Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
Y WangDivision of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
S LiDivision of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
Q SuDivision of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
L TangHistology and Imaging Platform, Core Facility of West China Hospital, Chengdu, Sichuan, China.
L BaiHistology and Imaging Platform, Core Facility of West China Hospital, Chengdu, Sichuan, China.
H RenDivision of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
Y ZouDivision of Nephrology, Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
S WangKey Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
S ZhengKey Laboratory of Transplant Engineering and Immunology, MOH, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan Province, China.
H XuDivision of Pathology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
L LiDivision of Pathology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
J ZhangHistology and Imaging Platform, Core Facility of West China Hospital, Chengdu, Sichuan, China.
Z ChaiDepartment of Diabetes, Central Clinical School, Monash University, Melbourne, Australia.
M E CooperDepartment of Diabetes, Central Clinical School, Monash University, Melbourne, Australia.
N TongDivision of Endocrinology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
Sichuan University · CNMonash University · AU

Funding

Key Research and Development Project of Sichuan Science Technology Department 19ZDYF1273National Natural Science Foundation of China 81970626Popularization Project of the Science and Technology Project of the Sichuan Health Planning Committee under Grant 19PJ250
6 · The paper itself

Abstract

purposeTo investigate the association between urinary complement proteins and renal outcome in biopsy-proven diabetic nephropathy (DN).

methodsUntargeted proteomic and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses and targeted proteomic analysis using parallel reaction-monitoring (PRM)-mass spectrometry was performed to determine the abundance of urinary complement proteins in healthy controls, type 2 diabetes mellitus (T2DM) patients, and patients with T2DM and biopsy-proven DN. The abundance of each urinary complement protein was individually included in Cox proportional hazards models for predicting progression to end-stage renal disease (ESRD).

resultsUntargeted proteomic and functional analysis using the KEGG showed that differentially expressed urinary proteins were primarily associated with the complement and coagulation cascades. Subsequent urinary complement proteins quantification using PRM showed that urinary abundances of C3, C9, and complement factor H (CFAH) correlated negatively with annual estimated glomerular filtration rate (eGFR) decline, while urinary abundances of C5, decay-accelerating factor (DAF), and CD59 correlated positively with annual rate of eGFR decline. Furthermore, higher urinary abundance of CFAH and lower urinary abundance of DAF were independently associated with greater risk of progression to ESRD. Urinary abundance of CFAH and DAF had a larger area under the curve (AUC) than that of eGFR, proteinuria, or any pathological parameter. Moreover, the model that included CFAH or DAF had a larger AUC than that with only clinical or pathological parameters.

conclusionUrinary abundance of complement proteins was significantly associated with ESRD in patients with T2DM and biopsy-proven DN, indicating that therapeutically targeting the complement pathway may alleviate progression of DN.

Indexed as

Complement System ProteinsDiabetic NephropathiesKidney Failure, ChronicBiopsyCorrelation of DataDiabetes Mellitus, Type 2Disease ProgressionDrug DiscoveryFemaleHumansKidneyKidney Function TestsMaleMiddle AgedPrognosisProportional Hazards ModelsComplement System ProteinsComplementDiabetic nephropathyEnd-stage renal diseaseUrinary proteomics

Identifiers

PMID34043214
PMCPMC8572220
OpenAlexW3165585075

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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.