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Arthritis Research & Therapy
Published in: Arthritis Research & Therapy 1/2018

Open Access 01-12-2018 | Research article

Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis

Authors: Rekha Narasimhan, Roxana Coras, Sara B. Rosenthal, Shannon R. Sweeney, Alessia Lodi, Stefano Tiziani, David Boyle, Arthur Kavanaugh, Monica Guma

Published in: Arthritis Research & Therapy | Issue 1/2018

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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.
Appendix
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Literature
1.
Orr C, Vieira-Sousa E, Boyle DL, Buch MH, Buckley CD, Canete JD, et al. Synovial tissue research: a state-of-the-art review. Nat Rev Rheumatol. 2017;13(8):463–75.CrossRefPubMed
2.
3.
Kavanaugh A, Rosengren S, Lee SJ, Hammaker D, Firestein GS, Kalunian K, et al. Assessment of rituximab's immunomodulatory synovial effects (ARISE trial). 1: clinical and synovial biomarker results. Ann Rheum Dis. 2008;67(3):402–8.CrossRefPubMed
4.
Dennis G Jr, Holweg CT, Kummerfeld SK, Choy DF, Setiadi AF, Hackney JA, et al. Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics. Arthritis Res Ther. 2014;16(2):R90.CrossRefPubMedPubMedCentral
5.
Kelly S, Humby F, Filer A, Ng N, Di Cicco M, Hands RE, et al. Ultrasound-guided synovial biopsy: a safe, well-tolerated and reliable technique for obtaining high-quality synovial tissue from both large and small joints in early arthritis patients. Ann Rheum Dis. 2015;74(3):611–7.CrossRefPubMed
6.
Astorri E, Nerviani A, Bombardieri M, Pitzalis C. Towards a stratified targeted approach with biologic treatments in rheumatoid arthritis: role of synovial pathobiology. Curr Pharm Des. 2015;21(17):2216–24.CrossRefPubMed
7.
Pitzalis C, Kelly S, Humby F. New learnings on the pathophysiology of RA from synovial biopsies. Curr Opin Rheumatol. 2013;25(3):334–44.CrossRefPubMed
8.
Burska A, Boissinot M, Ponchel F. Cytokines as biomarkers in rheumatoid arthritis. Mediat Inflamm. 2014;2014:545493.
9.
Burska AN, Roget K, Blits M, Soto Gomez L, van de Loo F, Hazelwood LD, et al. Gene expression analysis in RA: towards personalized medicine. Pharmacogenomics J. 2014;14(2):93–106.CrossRefPubMedPubMedCentral
10.
Eckhart AD, Beebe K, Milburn M. Metabolomics as a key integrator for “omic” advancement of personalized medicine and future therapies. Clin Transl Sci. 2012;5(3):285–8.CrossRefPubMedPubMedCentral
11.
12.
Semerano L, Romeo PH, Boissier MC. Metabolomics for rheumatic diseases: has the time come? Ann Rheum Dis. 2015;74(7):1325–6.CrossRefPubMed
13.
Patti GJ, Tautenhahn R, Rinehart D, Cho K, Shriver LP, Manchester M, et al. A view from above: cloud plots to visualize global metabolomic data. Anal Chem. 2013;85(2):798–804.CrossRefPubMed
14.
Patti GJ, Yanes O, Shriver LP, Courade JP, Tautenhahn R, Manchester M, et al. Metabolomics implicates altered sphingolipids in chronic pain of neuropathic origin. Nat Chem Biol. 2012;8(3):232–4.CrossRefPubMedPubMedCentral
15.
Priori R, Scrivo R, Brandt J, Valerio M, Casadei L, Valesini G, et al. Metabolomics in rheumatic diseases: the potential of an emerging methodology for improved patient diagnosis, prognosis, and treatment efficacy. Autoimmun Rev. 2013;12(10):1022–30.CrossRefPubMed
16.
17.
Ludwig CEJ, Lodi A, Tiziani S, Manzoor SE, et al. Birmingham metabolite library: a publicly accessible database of 1-D H-1 and 2-D H-1 J-resolved NMR spectra of authentic metabolite standards (BML-NMR). Metabolomics. 2012;8:8–18.CrossRef
18.
19.
Sweeney SR, Kavanaugh A, Lodi A, Wang B, Boyle D, Tiziani S, et al. Metabolomic profiling predicts outcome of rituximab therapy in rheumatoid arthritis. RMD Open. 2016;2(2):e000289.CrossRefPubMedPubMedCentral
20.
21.
Xia J, Wishart DS. Using MetaboAnalyst 3.0 for comprehensive metabolomics data analysis. Curr Protoc Bioinformatics. 2016;55:14. 0 1–0 91CrossRefPubMed
22.
Xia J, Psychogios N, Young N, Wishart DS. MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res. 2009;37(Web Server issue):W652–60.CrossRefPubMedPubMedCentral
23.
Xia J, Mandal R, Sinelnikov IV, Broadhurst D, Wishart DS. MetaboAnalyst 2.0–a comprehensive server for metabolomic data analysis. Nucleic Acids Res. 2012;40(Web Server issue):W127–33.CrossRefPubMedPubMedCentral
24.
Wijbrandts CA, Tak PP. Prediction of response to targeted treatment in rheumatoid arthritis. Mayo Clin Proc. 2017;92(7):1129–43.CrossRefPubMed
25.
Wijbrandts CA, Dijkgraaf MG, Kraan MC, Vinkenoog M, Smeets TJ, Dinant H, et al. The clinical response to infliximab in rheumatoid arthritis is in part dependent on pretreatment tumour necrosis factor alpha expression in the synovium. Ann Rheum Dis. 2008;67(8):1139–44.CrossRefPubMed
26.
Kapoor SR, Filer A, Fitzpatrick MA, Fisher BA, Taylor PC, Buckley CD, et al. Metabolic profiling predicts response to anti-tumor necrosis factor alpha therapy in patients with rheumatoid arthritis. Arthritis Rheum. 2013;65(6):1448–56.CrossRefPubMedPubMedCentral
27.
Garcia-Carbonell R, Divakaruni AS, Lodi A, Vicente-Suarez I, Saha A, Cheroutre H, et al. Critical role of glucose metabolism in rheumatoid arthritis fibroblast-like synoviocytes. Arthritis Rheumatol. 2016;68(7):1614–26.CrossRefPubMedPubMedCentral
28.
Guma M, Sanchez-Lopez E, Lodi A, Garcia-Carbonell R, Tiziani S, Karin M, et al. Choline kinase inhibition in rheumatoid arthritis. Ann Rheum Dis. 2015;74(7):1399–407.CrossRefPubMed
29.
Hugle T, Kovacs H, Heijnen IA, Daikeler T, Baisch U, Hicks JM, et al. Synovial fluid metabolomics in different forms of arthritis assessed by nuclear magnetic resonance spectroscopy. Clin Exp Rheumatol. 2012;30(2):240–5.PubMed
30.
Kim S, Hwang J, Xuan J, Jung YH, Cha HS, Kim KH. Global metabolite profiling of synovial fluid for the specific diagnosis of rheumatoid arthritis from other inflammatory arthritis. PLoS One. 2014;9(6):e97501.CrossRefPubMedPubMedCentral
31.
Kosinska MK, Liebisch G, Lochnit G, Wilhelm J, Klein H, Kaesser U, et al. Sphingolipids in human synovial fluid–a lipidomic study. PLoS One. 2014;9(3):e91769.CrossRefPubMedPubMedCentral
32.
Madsen RK, Lundstedt T, Gabrielsson J, Sennbro CJ, Alenius GM, Moritz T, et al. Diagnostic properties of metabolic perturbations in rheumatoid arthritis. Arthritis Res Ther. 2011;13(1):R19.CrossRefPubMedPubMedCentral
33.
34.
Volchenkov R, Dung Cao M, Elgstoen KB, Goll GL, Eikvar K, Bjorneboe O, et al. Metabolic profiling of synovial tissue shows altered glucose and choline metabolism in rheumatoid arthritis samples. Scand J Rheumatol. 2017;46(2):160–1.CrossRefPubMed
35.
Biniecka M, Canavan M, McGarry T, Gao W, McCormick J, Cregan S, Gallagher L, Smith T, Phelan JJ, Ryan J, O'sullivan J. Dysregulated bioenergetics: a key regulator of joint inflammation. Annals of the rheumatic diseases. 2016;75(12):2192-200.
36.
Roivainen A, Parkkola R, Yli-Kerttula T, Lehikoinen P, Viljanen T, Mottonen T, et al. Use of positron emission tomography with methyl-11C-choline and 2-18F-fluoro-2-deoxy-D-glucose in comparison with magnetic resonance imaging for the assessment of inflammatory proliferation of synovium. Arthritis Rheum. 2003;48(11):3077–84.CrossRefPubMed
37.
Beckmann J, Schubert J, Morhenn HG, Grau V, Schnettler R, Lips KS. Expression of choline and acetylcholine transporters in synovial tissue and cartilage of patients with rheumatoid arthritis and osteoarthritis. Cell Tissue Res. 2015;359(2):465–77.CrossRefPubMed
38.
39.
40.
Labuschagne CF, van den Broek NJ, Mackay GM, Vousden KH, Maddocks OD. Serine, but not glycine, supports one-carbon metabolism and proliferation of cancer cells. Cell Rep. 2014;7(4):1248–58.CrossRefPubMed
41.
42.
Ma EH, Bantug G, Griss T, Condotta S, Johnson RM, Samborska B, et al. Serine is an essential metabolite for effector T cell expansion. Cell Metab. 2017;25(2):345–57.CrossRefPubMed
43.
Mills EL, Kelly B, O'Neill LAJ. Mitochondria are the powerhouses of immunity. Nat Immunol. 2017;18(5):488–98.CrossRefPubMed
44.
Newman JC, Verdin E. Ketone bodies as signaling metabolites. Trends Endocrinol Metab. 2014;25(1):42–52.CrossRefPubMed
45.
Shimazu T, Hirschey MD, Newman J, He W, Shirakawa K, Le Moan N, et al. Suppression of oxidative stress by beta-hydroxybutyrate, an endogenous histone deacetylase inhibitor. Science. 2013;339(6116):211–4.CrossRefPubMed
46.
Youm YH, Nguyen KY, Grant RW, Goldberg EL, Bodogai M, Kim D, et al. The ketone metabolite beta-hydroxybutyrate blocks NLRP3 inflammasome-mediated inflammatory disease. Nat Med. 2015;21(3):263–9.CrossRefPubMedPubMedCentral
47.
Li Y, Zheng JY, Liu JQ, Yang J, Liu Y, Wang C, et al. Succinate/NLRP3 Inflammasome induces synovial fibroblast activation: therapeutical effects of clematichinenoside AR on arthritis. Front Immunol. 2016;7:532.PubMedPubMedCentral
48.
Mills E, O’Neill LA. Succinate: a metabolic signal in inflammation. Trends Cell Biol. 2014;24(5):313–20.CrossRefPubMed
49.
Chang CH, Curtis JD, Maggi LB Jr, Faubert B, Villarino AV, O'Sullivan D, et al. Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell. 2013;153(6):1239–51.CrossRefPubMedPubMedCentral
50.
Yu X, Li S. Non-metabolic functions of glycolytic enzymes in tumorigenesis. Oncogene. 2017;36(19):2629.
51.
Dumas M-E, Maibaum EC, Teague C, Ueshima H, Zhou B, Lindon JC, et al. Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP study. Anal Chem. 2006;78(7):2199–208.CrossRefPubMed
52.
Viant MR, Bearden DW, Bundy JG, Burton IW, Collette TW, Ekman DR, et al. International NMR-based environmental metabolomics intercomparison exercise. Environ Sci Technol. 2008;43(1):219–25.CrossRef
53.
54.
Wishart DS. Quantitative metabolomics using NMR. TrAC Trends Anal Chem. 2008;27(3):228–37.CrossRef
55.
Whitfield PD, German AJ, Noble PJM. Metabolomics: an emerging post-genomic tool for nutrition. Br J Nutr. 2004;92(4):549–55.CrossRefPubMed
56.
57.
Brown PM, Pratt AG, Isaacs JD. Mechanism of action of methotrexate in rheumatoid arthritis, and the search for biomarkers. Nat Rev Rheumatol. 2016;12(12):731–42.CrossRefPubMed
58.
Jubair WK, Hendrickson JD, Severs EL, Schulz HM, Adhikari S, Ir D, et al. Modulation of inflammatory arthritis by gut microbiota through mucosal inflammation and autoantibody generation. Arthritis Rheumatol. 2018.
59.
Maeda Y, Kurakawa T, Umemoto E, Motooka D, Ito Y, Gotoh K, et al. Dysbiosis contributes to arthritis development via activation of autoreactive T cells in the intestine. Arthritis Rheumatol. 2016;68(11):2646–61.CrossRefPubMed
60.
Metadata
Title
Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis
Authors
Rekha Narasimhan
Roxana Coras
Sara B. Rosenthal
Shannon R. Sweeney
Alessia Lodi
Stefano Tiziani
David Boyle
Arthur Kavanaugh
Monica Guma
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Arthritis Research & Therapy / Issue 1/2018
Electronic ISSN: 1478-6362
DOI
https://doi.org/10.1186/s13075-018-1655-3

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