A discovery of screening markers for rheumatoid arthritis by liquid chromatography mass spectrometry: A metabolomic approach

Autor:	Doojin Kim, Mi-Kyoung Lim, Sohyen Kwon, Yoo-Jin Lee, Hee-Gyoo Kang, Seung Yeon Lee, You-Rim Lee, Jiyeong Lee, Sora Mun
Rok vydání:	2020
Předmět:	Male medicine.medical_specialty Metabolite Tandem mass spectrometry Gastroenterology Arthritis Rheumatoid 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Metabolomics Rheumatology Liquid chromatography–mass spectrometry Tandem Mass Spectrometry Internal medicine Synovial Fluid Medicine Humans Mass Screening 030212 general & internal medicine METLIN Chromatography High Pressure Liquid 030203 arthritis & rheumatology business.industry Area under the curve Middle Aged Fold change chemistry ROC Curve Female Docosapentaenoic acid business Biomarkers
Zdroj:	International journal of rheumatic diseasesREFERENCES. 23(10)
ISSN:	1756-185X
Popis:	Aim This study aimed to discover serum metabolite biomarkers for potential use in screening for rheumatoid arthritis (RA). Methods The sera from 43 healthy controls (HCs) and 49 RA patients were globally analyzed using high-performance liquid chromatography- tandem mass spectrometry. Molecular features (MFs) from samples were analyzed using volcano plots, partial least squares discriminant analysis, and variable importance in projection scores to select candidates. The spectra of candidate MFs were matched with the METLIN database. We confirmed the association between candidates and RA and analyzed the receiver-operating characteristic (ROC) curves. Results We selected a total of 57 candidate MFs that had a fold change ≥1.5, P value ≤.05, and over 80% of frequency. Among them, 18 MFs were identified as metabolites with the METLIN database. Six metabolites (dehydroepiandrosterone sulfate, androsterone sulfate, γ-linolenic acid, 9[E],11[E]-conjugated linoleic acid, docosahexaenoic acid, and docosapentaenoic acid [22n-3]) out of the 18 were associated with mechanisms of RA and were selected as final candidates. ROC curve analysis revealed their area under the curve (AUC) values were all above 0.75 and the combined AUC of the six candidates was 0.89. Conclusion Using six candidates as a marker set showed potential in distinguishing RA patients from HCs, based on high AUC values. Therefore, we propose that a marker set of these six candidates has potential clinical application in RA screening.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d8bfe7a5a84c604f3c5a2697c2f284c https://pubmed.ncbi.nlm.nih.gov/32845094 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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