Evidence map›Paper›PMID 29371982›Full record

ArticleOncotarget2017

Biomarkers identification by a combined clinical and metabonomics analysis in Henoch-Schonlein purpura nephritis children.

Lin Sun, Biao Xie, Qiuju Zhang, Yupeng Wang, Xinyu Wang, Bing Gao, Meina Liu, Maoqing Wang

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 15% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Modern biomarkers in IgA vasculitis with nephritis in children.Central-European journal of immunology · 2025
    Review
  5. Review
  6. 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

8 authors at 1 institution in 1 country.

Lin SunDepartment of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, P. R. China.
Biao XieDepartment of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, P. R. China.
Qiuju ZhangDepartment of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, P. R. China.
Yupeng WangDepartment of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, P. R. China.
Xinyu WangDepartment of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, P. R. China.
Bing GaoDepartment of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, P. R. China.
Meina LiuDepartment of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, P. R. China.
Maoqing WangDepartment of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, P. R. China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn children with Henoch-Schonlein purpura (HSP), the severity of Henoch-Schonlein purpura nephritis (HSPN) is considered responsible for the prognosis of HSP. The pathological process from HSP to HSPN is not clear yet and current diagnostic tools have shortcomings in accurate diagnosis of HSPN. This study aims to assess clinical characteristics of HSP and HSPN, to identify metabolic perturbations involved in HSP progress, and to combine metabolic biomarkers and clinical features into a better prediction for HSPN.

methodsA total of 162 children were recruited, including 109 HSP patients and 53 healthy children (HC). The clinical characteristics were compared between HSPN and HSP without nephritis (HSPWN). The serum metabonomics analysis was performed to determine the metabolic differences in HSP and HC.

resultsAmong 109 HSP children, 57 progressed to HSPN. The increased D-dimer level was significantly associated with renal damage in HSP. The metabonomic profiles revealed alterations between various subgroups of HSP and HC, making it possible to investigate small-molecule metabolites related to the pathological process of HSP. In total, we identified 9 biomarkers for HSP vs. HC, 7 for HSPWN vs. HC, 9 for HSPN vs. HC, and 3 for HSPN vs. HSPWN.

conclusions(S)-3-hydroxyisobutyric acid, p-Cresol sulfate, and 3-carboxy-4-methyl-5-pentyl-2-furanpropanoic acid were found associated with the progress of HSP to HSPN. Moreover, resulting biomarkers, when combined with D-dimer, allowed improving the HSPN prediction with high sensitivity (94.7%) and specificity (80.8%). Together these findings highlighted the strength of the combination of metabonomics and clinical analysis in the research of HSP.

Indexed as

biomarkersclinicalHSPHSPNmetabonomics

Identifiers

PMID29371982
PMCPMC5768399
OpenAlexW2772798474

What OpenQuestion holds

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LicenceCC BY
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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.