Evidence map›Paper›PMID 37103652›Full record

ArticleClinical and experimental medicine2023

Metabolic profiling of patients with different idiopathic inflammatory myopathy subtypes reveals potential biomarkers in plasma.

Qianqian Zhao, Qiu Hu, Shuhui Meng, Qinguo Zhang, Tingting Wang, Cuilian Liu, Dongzhou Liu, Zhenyou Jiang, Xiaoping Hong

Open access · hybridAbstract read
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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Qianqian Zhao *Department of Rheumatology and Immunology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, 518020, China.
Qiu Hu *Department of Rheumatology and Immunology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, 518020, China.
Shuhui MengDepartment of Rheumatology and Immunology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, 518020, China.
Qinguo ZhangThe Office of Healthcare Committee of Shenzhen Municipal, Shenzhen, 518020, China.
Tingting WangDepartment of Rheumatology and Immunology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, 518020, China.
Cuilian LiuDepartment of Rheumatology and Immunology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, 518020, China.
Dongzhou LiuDepartment of Rheumatology and Immunology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, 518020, China.
Zhenyou JiangDepartment of Microbiology and Immunology, College of Basic Medicine and Public Hygiene, Jinan University, Guangzhou, 510632, China. tjzhy@jnu.edu.cn.
Xiaoping HongDepartment of Rheumatology and Immunology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, 518020, China. hong_xiaoping@hotmail.com.
Jinan University · CNShenzhen Municipal People's Government · CN

Funding

China Postdoctoral Science Foundation 2022M721350Guangdong Basic and Applied Basic Research Foundation 2022A1515110868
6 · The paper itself

Abstract

Idiopathic inflammatory myopathy (IIM) are heterogeneous autoimmune diseases that primarily affect the proximal muscles. IIM subtypes include dermatomyositis (DM), polymyositis (PM), and anti-synthetase syndrome (ASS). Metabolic disturbances may cause irreversible structural damage to muscle fibers in patients with IIM. However, the metabolite profile of patients with different IIM subtypes remains elusive. To investigate metabolic alterations and identify patients with different IIM subtypes, we comprehensively profiled plasma metabolomics of 46 DM, 13 PM, 12 ASS patients, and 30 healthy controls (HCs) using UHPLC-Q Exactive HF mass spectrometer. Multiple statistical analyses and random forest were used to discover differential metabolites and potential biomarkers. We found that tryptophan metabolism, phenylalanine and tyrosine metabolism, fatty acid biosynthesis, beta-oxidation of very long chain fatty acids, alpha-linolenic acid and linoleic acid metabolism, steroidogenesis, bile acid biosynthesis, purine metabolism, and caffeine metabolism are all enriched in the DM, PM, and ASS groups. We also found that different subtypes of IIM have their unique metabolic pathways. We constructed three models (five metabolites) to identify DM, PM, ASS from HC in the discovery and validation sets. Five to seven metabolites can distinguish DM from PM, DM from ASS, and PM from ASS. A panel of seven metabolites can identify anti-melanoma differentiation-associated gene 5 positive (MDA5 +) DM with high accuracy in the discovery and validation sets. Our results provide potential biomarkers for diagnosing different subtypes of IIM and a better understanding of the underlying mechanisms of IIM.

Indexed as

Autoimmune DiseasesDermatomyositisMyositisPolymyositisBiomarkersHumansBiomarkersAnti-MDA5 positive dermatomyositisBiomarkerIdiopathic inflammatory myopathyMetabolomics

Identifiers

PMID37103652
PMCPMC10618316
OpenAlexW4367173944

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.