Evidence map›Paper›PMID 33291298›Full record

ArticleJournal of clinical medicine2020

Serum Metabolomic Profiling of Patients with Non-Infectious Uveitis.

Hiroyuki Shimizu, Yoshihiko Usui, Masaki Asakage, Naoya Nezu, Ryo Wakita, Kinya Tsubota, Masahiro Sugimoto, Hiroshi Goto

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

  1. Review
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  5. ERJ open research · 2025
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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.

Hiroyuki ShimizuDepartment of Ophthalmology, Tokyo Medical University, Tokyo 160-0023, Japan.
Yoshihiko UsuiDepartment of Ophthalmology, Tokyo Medical University, Tokyo 160-0023, Japan.ORCID 0000-0002-1258-3587
Masaki AsakageDepartment of Ophthalmology, Tokyo Medical University, Tokyo 160-0023, Japan.
Naoya NezuDepartment of Ophthalmology, Tokyo Medical University, Tokyo 160-0023, Japan.
Ryo WakitaDepartment of Ophthalmology, Tokyo Medical University, Tokyo 160-0023, Japan.
Kinya TsubotaDepartment of Ophthalmology, Tokyo Medical University, Tokyo 160-0023, Japan.ORCID 0000-0002-7680-3745
Masahiro SugimotoHealth Promotion and Preemptive Medicine, Research and Development Center for Minimally Invasive Therapies, Institute of Medical Sciences, Tokyo Medical University, Tokyo 160-8402, Japan.ORCID 0000-0003-3316-2543
Hiroshi GotoDepartment of Ophthalmology, Tokyo Medical University, Tokyo 160-0023, Japan.

Funding

Japan Agency for Medical Research and Development 17ae0101016s0904The Ministry of Education, Culture, Sports, Science and Technology of Japan 16K11330The Ministry of Education, Culture, Sports, Science and Technology of Japan 19K09959The Ministry of Education, Culture, Sports, Science and Technology of Japan 19K09981
6 · The paper itself

Abstract

The activities of various metabolic pathways can influence the pathogeneses of autoimmune diseases, and intrinsic metabolites can potentially be used to diagnose diseases. However, the metabolomic analysis of patients with uveitis has not yet been conducted. Here, we profiled the serum metabolomes of patients with three major forms of uveitis (Behҫet's disease (BD), sarcoidosis, and Vogt-Koyanagi-Harada disease (VKH)) to identify potential biomarkers. This study included 19 BD, 20 sarcoidosis, and 15 VKH patients alongside 16 healthy control subjects. The metabolite concentrations in their sera were quantified using liquid chromatography with time-of-flight mass spectrometry. The discriminative abilities of quantified metabolites were evaluated by four comparisons: control vs. three diseases, and each disease vs. the other two diseases (such as sarcoidosis vs. BD + VKH). Among 78 quantified metabolites, 24 kinds of metabolites showed significant differences in these comparisons. Four multiple logistic regression models were developed and validated. The area under the receiver operating characteristic (ROC) curve (AUC) in the model to discriminate disease groups from control was 0.72. The AUC of the other models to discriminate sarcoidosis, BD, and VKH from the other two diseases were 0.84, 0.83, and 0.73, respectively. This study provides potential diagnostic abilities of sarcoidosis, BD, and VKH using routinely available serum samples that can be collected with minimal invasiveness.

Indexed as

Behҫet’s diseasebiomarkerliquid chromatography-mass spectrometrymetabolomicssarcoidosisserumVogt-Koyanagi-Harada disease

Identifiers

PMID33291298
PMCPMC7762156

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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.