Evidence map›Paper›PMID 36459277›Full record

ArticleClinical and experimental medicine2023

Diagnostic serum biomarkers associated with ankylosing spondylitis.

Huan Li, Liang Wang, Jing Zhu, Jialing Xiao, Huining Yang, Huanyue Hai, Jiarui Hu, Lin Li, Yi Shi, Man Yu and 7 more

Abstract read
PubMed Publisher
In one paragraph

Article in Clinical and experimental medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Guideline
  2. Pooled it
  3. Review
  4. Metabolomics in spondylarthritis.BMC rheumatology · 2025
    Article
  5. 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

17 authors.

Huan Li *Department of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Liang Wang *Department of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Jing Zhu *Department of Rheumatology and Immunology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Jialing Xiao *Department of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Huining YangDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Huanyue HaiDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Jiarui HuDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Lin LiHuman Disease Genes Key Laboratory of Sichuan Province and Institute of Laboratory Medicine, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Yi ShiHuman Disease Genes Key Laboratory of Sichuan Province and Institute of Laboratory Medicine, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Man YuDepartment of Ophthalmology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 The First Ring Road West 2, Chengdu, 610072, Sichuan, China.
Ping ShuaiDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Yuping LiuDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Xueming JuDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Gang WuDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Yu ZhouDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Bolin DengDepartment of Ophthalmology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 The First Ring Road West 2, Chengdu, 610072, Sichuan, China. 396665760@qq.com.
Bo GongDepartment of Health Management, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China. gongbo@med.uestc.edu.cn.

Funding

National Natural Science Foundation of China 81870683National Natural Science Foundation of China 81970825National Natural Science Foundation of China 82070928National University Basic funding ZYGX2018J098National University Basic funding ZYGX2021J026Science & Technology Department of Sichuan Province 2020JDTD0028Science & Technology Department of Sichuan Province 2020YJ0450Science & Technology Department of Sichuan Province 2020YJ0460Science & Technology Department of Sichuan Province 2022JDTD0024Science & Technology Department of Sichuan Province 22JCQN0028the Department of Sichuan Provincial Health 150188the Department of Sichuan Provincial Health 19PJ117the Scientific Research Project of Chengdu Science and Technology Bureau 2021-YF05-00498-SNthe Scientific Research Project of Sichuan Provincial People's Hospital 2020LY11the Scientific Research Project of Sichuan Provincial People's Hospital 2021kflx007the Scientific Research Project of Sichuan Provincial People's Hospital 2021LY15the Youth Scientific Research Fund of Sichuan Provincial People's Hospital 2017QN02
6 · The paper itself

Abstract

Ankylosing spondylitis (AS) is an autoimmune rheumatic disease that mostly affects the axial skeleton. This study aimed to investigate reliable diagnostic serum biomarkers for AS. Serum samples were collected from 20 AS patients and 20 healthy controls (HCs) and analyzed using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The differential metabolites between the AS patients and HCs were profiled using univariate and multivariate statistical analyses. Pathway analysis and a heat map were also conducted. Random forest (RF) analysis and the least absolute shrinkage and selection operator (LASSO) were used to establish predictive and diagnostic models. After controlling the variable importance in the projection (VIP) value > 1 and false discovery rate (FDR) < 0.05, a total of 61 differential metabolites were identified from 995 metabolites, which exhibited significant differences in the pathway analysis and heat map between the AS patients and HCs. RF as a predictive model also identified differential metabolites with 95% predictive accuracy and a high area under the curve (AUC) of 1. A diagnostic model comprising nine metabolites (cysteinylglycine disulfide, choline, N6, N6, N6-trimethyllysine, histidine, sphingosine, fibrinopeptide A, glycerol 3-phosphate, 1-linoleoyl-GPA (18:2), and fibrinopeptide A (3-16)) was generated using LASSO regression, capable of distinguishing HCs from AS with a high AUC of 1. Our results indicated that the UPLC-MS/MS analysis method is a powerful tool for identifying AS metabolite profiles. We developed a nine-metabolites-based model serving as a diagnostic tool to separate AS patients from HCs, and the identified diagnostic biomarkers appeared to have a diagnostic value for AS.

Indexed as

MetabolomicsSpondylitis, AnkylosingBiomarkersChromatography, LiquidFibrinopeptide AHumansTandem Mass SpectrometryBiomarkersFibrinopeptide AAnkylosing spondylitisBiomarkersMetabolomicsUPLC-MS/MS

Identifiers

PMID36459277

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.