Evidence map›Paper›PMID 36160171›Full record

ArticleFrontiers in medicine2022

Untargeted serum metabolomics reveals specific metabolite abnormalities in patients with Crohn's disease.

Huanhuan Liu, Minmin Xu, Qiongzi He, Peng Wei, Mengying Ke, Shijia Liu

Abstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

13 citing papers in PubMed.

  1. Review
  2. Dissecting inflammation in the immunemetabolomic era.Cellular and molecular life sciences : CMLS · 2025
    Review
  3. Article
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  6. Article
  7. Review
  8. Article
  9. Article
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  11. Review
  12. Review
  13. Metabolic changes during exclusive enteral nutrition in pediatric Crohn's disease patients.Metabolomics : Official journal of the Metabolomic Society · 2022
    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

6 authors.

Huanhuan LiuDepartment of Pharmacy, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Minmin XuDepartment of Pharmacy, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Qiongzi HeDepartment of Pharmacy, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Peng WeiDepartment of Pharmacy, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Mengying KeCollege of Pharmacy, Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, China.
Shijia LiuDepartment of Pharmacy, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crohn's disease (CD) is a subtype of inflammatory bowel disease (IBD) characterized by skip intestinal lesions that can occur in any part of the gastrointestinal tract. Currently, the diagnosis of CD is based on clinical history, physical examination and complementary diagnostic tests. It is challenging for physicians to make a definitive diagnosis. This study aimed to analyze the variation in metabolites in CD serum and identify potential predictive biomarkers of CD diagnosis. We collected serum samples from 316 subjects, including patients with CD and healthy controls (HCs). Serum metabolomics was conducted using liquid chromatography coupled to mass spectrometry. Potential biomarkers were screened and evaluated by univariate and multivariate analyses. A panel of two metabolites (deoxycholic acid and palmitic amide) was identified as a specific biomarker of CD. Receiver operating characteristic analysis (ROC) showed that the panel had a sensitivity of 80.25% with a specificity of 95.54% in discriminating CD patients from healthy controls. The biomarkers identified are increased in CD compared with healthy controls. Our approach successfully identified serum biomarkers associated with CD patients. The potential biomarkers indicated that CD metabolic disturbance might be associated with bile acid biosynthesis, fatty acids and energy metabolism.

Indexed as

biomarkerCrohn's diseaseLC-MSmetabolite profileserum metabolomics

Identifiers

PMID36160171
PMCPMC9492954

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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.