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Circulating blood metabolite trajectories and risk of rheumatoid arthritis among military personnel in the Department of Defense Biorepository
  1. Karen H Costenbader1,2,
  2. Michael DiIorio3,
  3. Su H Chu4,
  4. Jing Cui1,
  5. Jeffrey A Sparks1,
  6. Bing Lu1,
  7. LauraKay Moss5,
  8. Lindsay Kelmenson5,
  9. Marie Feser5,
  10. Jess Edison6,
  11. Clary Clish7,
  12. Jessica Lasky-Su4,
  13. Kevin D Deane8,
  14. Elizabeth W Karlson1,9
  1. 1Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
  2. 2Medicine, Harvard Medical School, Boston, Massachusetts, USA
  3. 3Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
  4. 4Channing Department of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
  5. 5University of Colorado, Aurora, Colorado, USA
  6. 6Walter Reed National Military Medical Center, Bethesda, MD, USA
  7. 7Metabolomics Group, Broad Institute, Cambridge, Massachusetts, USA
  8. 8Division of Rheumatology, Department of Medicine, University of Colorado, Aurora, Colorado, USA
  9. 9Harvard Medical School, Boston, Massachusetts, USA
  1. Correspondence to Dr Karen H Costenbader, Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital Department of Medicine, Boston, MA 02115, USA; kcostenbader{at}


Objectives We sought to identify metabolic changes potentially related to rheumatoid arthritis (RA) pathogenesis occurring in the blood prior to its diagnosis.

Methods In a US military biorepository, serum samples collected at two timepoints prior to a diagnosis of RA were identified. These were matched to controls who did not develop RA by subject age, race and time between sample collections and RA diagnosis time to stored serum samples. Relative abundances of 380 metabolites were measured using liquid chromatography–tandem mass spectrometry. We determined whether pre-RA case versus control status predicted metabolite concentration differences and differences over time (trajectories) using linear mixed models, assessing for interactions between time, pre-RA status and metabolite concentrations. We separately examined pre-RA and pre-seropositive RA cases versus matched controls and adjusted for smoking. Multiple comparison adjustment set the false discovery rate to 0.05.

Results 291 pre-RA cases (80.8% pre seropositive RA) were matched to 292 controls, all with two serum samples (2.7±1.6 years; 1.0±0.9 years before RA/matched date). 52.0% were women; 52.8% were White, 26.8% Black and 20.4% other race. Mean age was 31.2 (±8.1) years at earliest blood draw. Fourteen metabolites had statistically significant trajectory differences among pre-RA subjects versus controls, including sex steroids, amino acid/lipid metabolism and xenobiotics. Results were similar when limited to pre seropositive RA and after adjusting for smoking.

Conclusions In this military case–control study, metabolite concentration trajectory differences in pre-RA cases versus controls implicated steroidogenesis, lipid/amino acid metabolism and xenobiotics in RA pathogenesis. Metabolites may have potential as biomarkers and/or therapeutic targets preceding RA diagnosis.

  • rheumatoid arthritis
  • arthritis
  • rheumatoid
  • epidemiology

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  • Handling editor Josef S Smolen

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  • Contributors All authors: Substantial contributions to the conception or design of the work or the acquisition, analysis or interpretation of data; drafting the work or revising it critically for important intellectual content; final approval of the version published and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

  • Funding This work was supported by National Institutes of Health (grant numbers R01 AR049880, K24 AR066109, K23 AR069688, R01 AR071326) and the Congressionally Directed Medical Research Program PR120839 (W81XWH-13-1-0408).

  • Disclaimer The identification of specific products or scientific instrumentation is considered an integral part of the scientific endeavor and does not constitute endorsement or implied endorsement on the part of the author, Department of Defense or any component agency. The views expressed in this presentation are those of the authors and do not reflect the official policy of the Department of Army/Navy/Air Force, Department of Defense or US Government. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

  • Competing interests KDD has served as ac consultant to Inova Diagnostics.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Ethics approval The study protocol was approved by the institutional review boards at Partners HealthCare System, the University of Colorado and Walter Reed National Military Medical Center.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available upon reasonable request. Data from this project can be considered for release if the appropriate IRB and publication clearances have been made, and a project is in keeping with the directives of the United States Department of Defense Serum Repository.

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