Evidence map›Paper›PMID 29442259›Full record

ArticleClinical rheumatology2018

LC-MS-based serum metabolomics reveals a distinctive signature in patients with rheumatoid arthritis.

Ju Li, Nan Che, Lingxiao Xu, Qian Zhang, Qi Wang, Wenfeng Tan, Miaojia Zhang

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Clinical rheumatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed
5.7field-weighted citation impact, top 3% 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

59 citing papers in PubMed, 117 citations in OpenAlex.

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  13. Exploring the Metabolic Effects of a Herbal Remedy ofAntioxidants (Basel, Switzerland) · 2024
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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

7 authors at 2 institutions in 1 country.

Ju LiDepartment of Rheumatology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
Nan CheDepartment of Rheumatology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
Lingxiao XuDepartment of Rheumatology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
Qian ZhangDepartment of Rheumatology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
Qi WangDepartment of Rheumatology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
Wenfeng TanDepartment of Rheumatology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
Miaojia ZhangDepartment of Rheumatology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China. zhangmiaojia2016@163.com.
Jiangsu Province Hospital · CNNanjing Medical University · CN

Funding

National Natural Science Foundation of China 81671615Special Project of Clinical Medicine from Jiangsu Province BL2013034
6 · The paper itself

Abstract

Metabolomics has been applied to explore altered metabolite profiles in disease and identify unique metabolic signatures in recent years. We aim to characterize the metabolic profile of rheumatoid arthritis patients and explore its underlying pathological processes using metabolomics approach. Serum samples from 30 rheumatoid arthritis (RA) patients, 30 primary Sjogren's syndrome (pSS) patients, and 32 healthy controls (HC) were collected. The sample was analyzed by ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UPLC-HRMS). Potential biomarkers were screened from orthogonal projection to latent structure discriminate analysis (OPLS-DA) and further evaluated by receiver operating characteristic analysis (ROC). Compared with HC and pSS patients, the RA patients had increased serum levels of 4-methoxyphenylacetic acid, glutamic acid, L-leucine, L-phenylalanine, L-tryptophan, L-proline, glyceraldehyde, fumaric acid, and cholesterol as well as decreased capric acid, argininosuccinic acid, and billirubin. A total of eight potential biomarkers were screened and tentatively identified for RA. A panel of three metabolites (4-methoxyphenylacetic acid, L-phenylalanine, and L-leucine) was identified as specific biomarkers of RA. ROC analysis showed that the panel had a sensitivity of 93.30% with a specificity of 95.20% in discrimination RA from other groups. UPLC-HRMS-based quantification of circulating metabolites was a useful tool for identifying RA patients from pSS patients and healthy controls. The potential biomarkers indicated that the RA metabolic disturbance might be associated with inflammation injury, amino acid metabolism, oxidative stress, and phospholipid metabolism.

Indexed as

MetabolomeAdultArthritis, RheumatoidBiomarkersCase-Control StudiesChromatography, LiquidFemaleHumansMaleMass SpectrometryMetabolomicsMiddle AgedSjogren's SyndromeYoung AdultBiomarkersBiomarkersMetabolomicsOrthogonal projection to latent structure discriminate analysisRheumatoid arthritis

Identifiers

PMID29442259
OpenAlexW2791851260

What OpenQuestion holds

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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.