Figure S6. Correlation between serum metabolites and synovial IL-1Î˛ and IL-8. (TIFF 14826 kb

Alessia Lodi (256296)

Arthur Kavanaugh (2683)

David Boyle (221745)

Monica Guma (814502)

Rekha Narasimhan (5594711)

Roxana Coras (5594714)

Sara Rosenthal (5594717)

Shannon Sweeney (5594720)

Stefano Tiziani (256302)

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Additional file 7: of Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis

Abstract Background Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients’ metabolomic profiles in blood, utilizing 1H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA). Methods Nineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700 MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS. Results Analysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-α synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels. Conclusion The relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA

Rekha Narasimhan

Roxana Coras

Sara B. Rosenthal

Shannon R. Sweeney

Alessia Lodi

Stefano Tiziani

David Boyle

Arthur Kavanaugh

Monica Guma

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Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis

BackgroundMetabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients' metabolomic profiles in blood, utilizing 1H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA).MethodsNineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700&nbsp;MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS.ResultsAnalysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-α synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels.ConclusionThe relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA

Narasimhan, Rekha

Coras, Roxana

Rosenthal, Sara B

Sweeney, Shannon R

Lodi, Alessia

Tiziani, Stefano

Boyle, David

Kavanaugh, Arthur

Guma, Monica

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Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis.

https://escholarship.org/content/qt85d1v2d9/qt85d1v2d9.pdf?t=qam7zq

Additional file 7: of Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis

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