Literature DB >> 26653129

Diagnostic and Prognostic Metabolites Identified for Joint Symptoms in the KORA Population.

Noha A Yousri1,2, Gabi Kastenmüller3,4, Wessam G AlHaq5, Rolf Holle6, Stefan Kääb7,8, Robert P Mohney9, Christian Gieger10, Annette Peters4,11, Jerzy Adamski4,12,13, Karsten Suhre1,3, Thurayya Arayssi5.   

Abstract

This study aims at identifying metabolites that significantly associate with self-reported joint symptoms (diagnostic) and metabolites that can predict the change from a symptom-free status to the development of self-reported joint symptoms after a 7 years period (prognostic). More than 300 metabolites were analyzed for 2246 subjects from the longitudinal study of the KORA (Cooperative Health Research in the Region of Augsburg, Germany), specifically the fourth survey S4 and its 7-year follow-up study F4. Two types of self-reported symptoms, chronic joint inflammation and worn out joints, were used for the analyses. Diagnostic analysis identified dysregulated metabolites in cases with symptoms compared with controls. Prognostic analysis identified metabolites that differentiate subjects in S4 who remained symptom-free after 7 years (F4) from those who developed any combination of symptoms. 48 metabolites were identified as nominally significantly (p < 0.05) associated with the self-reported symptoms in the diagnostic analysis, among which steroids show Bonferroni significance. 45 metabolites were identified as nominally significantly associated with developing symptoms after 7 years, among which hippurate showed Bonferroni significance. We show that metabolic profiles of self-reported joint symptoms are in line with metabolites known to associate with various forms of arthritis and suggest that future studies may benefit from that by investigating the possible use of self-reporting/questionnaire along with metabolic markers for the early referral of patients for further diagnostic workup and treatment of arthritis.

Entities:  

Keywords:  arthritis; diagnosis; joint inflammation; metabolomics; prognosis; rheumatoid arthritis

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Year:  2016        PMID: 26653129     DOI: 10.1021/acs.jproteome.5b00951

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  2 in total

Review 1.  Immunometabolism in early and late stages of rheumatoid arthritis.

Authors:  Cornelia M Weyand; Jörg J Goronzy
Journal:  Nat Rev Rheumatol       Date:  2017-03-31       Impact factor: 20.543

2.  Large Scale Metabolic Profiling identifies Novel Steroids linked to Rheumatoid Arthritis.

Authors:  Noha A Yousri; Karim Bayoumy; Wessam Gad Elhaq; Robert P Mohney; Samar Al Emadi; Mohammed Hammoudeh; Hussein Halabi; Basel Masri; Humeira Badsha; Imad Uthman; Robert Plenge; Richa Saxena; Karsten Suhre; Thurayya Arayssi
Journal:  Sci Rep       Date:  2017-08-22       Impact factor: 4.379

  2 in total

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