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Plasma metabonomics study of the patients with acute anterior uveitis based on ultra-performance liquid chromatography–mass spectrometry

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Abstract

Background

The identification of the biomarkers of patients with acute anterior uveitis (AAU) may allow for a less invasive and more accurate diagnosis, as well as serving as a predictor in AAU progression and treatment response. The aim of this study was to identify the potential biomarkers and the metabolic pathways from plasma in patients with AAU.

Methods

Both plasma metabolic biomarkers and metabolic pathways in the AAU patients versus healthy volunteers were investigated using ultra-performance liquid chromatography–mass spectrometry (UPLC–MS) and a metabonomics approach. The principal component analysis (PCA) was used to separate AAU patients from healthy volunteers as well as to identify the different biomarkers between the two groups. Metabolic compounds were matched to the KEGG, METLIN, and HMDB databases, and metabolic pathways associated with AAU were identified.

Results

The PCA for UPLC–MS data shows that the metabolites in AAU patients were significantly different from those of healthy volunteers. Of the 4,396 total features detected by UPLC–MS, 102 features were significantly different between AAU patients and healthy volunteers according to the variable importance plot (VIP) values (greater than two) of partial least squares discriminate analysis (PLS-DA). Thirty-three metabolic compounds were identified and were considered as potential biomarkers. Meanwhile, ten metabolic pathways were found that were related to the AAU according to the identified biomarkers.

Conclusions

These data suggest that metabolomics study can identify potential metabolites that differ between AAU patients and healthy volunteers. Based on the PCA, PLS-DA, several potential metabolic biomarkers and pathways in AAU patients were found and identified. In addition, the UPLC–MS technique combined with metabonomics could be a suitable systematic biology tool in research in clinical problems in ophthalmology, and can provide further insight into the pathophysiology of AAU.

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References

  1. Baarsma GS (1992) The epidemiology and genetics of uveitis. Curr Eye Res 11:1–9

    Article  PubMed  Google Scholar 

  2. Rothova A, Suttorp-van Schulten MS, First Treffers W, Kijlstra A (1996) Causes and frequency of blindness in patients with intraocular inflammatory disease. Br J Ophthalmol 80:332–336

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. Rosenbaum JT, Rosenzweig HL, Smith JR, Martin TM, Planck SR (2008) Uveitis secondary to bacterial products. Ophthalmic Res 40:165–168

    Article  PubMed  Google Scholar 

  4. Islam N, Pavesio C (2010) Uveitis (acute anterior). Clin Evid (Online) 04:705–711

    Google Scholar 

  5. Luger D, Caspi RR (2008) New perspectives on effector mechanisms in uveitis. Semin Immunopathol 30:135–143

    Article  PubMed Central  PubMed  Google Scholar 

  6. Tabbara KF (2000) Infectious uveitis: a review. Arch Soc Esp Oftalmol 75:215–259

    CAS  PubMed  Google Scholar 

  7. Onal S, Kazokoglu H, Incili B, Demiralp EE, Yavuz S (2006) Prevalence and levels of serum antibodies to gram negative microorganisms in Turkish patients with HLA-B27 positive acute anterior uveitis and controls. Ocul Immunol Inflamm 14(5):293–299

    Article  CAS  PubMed  Google Scholar 

  8. Read RW (2006) Uveitis: advances in understanding of pathogenesis. Curr Rheumatol Rep 8:260–266

    Article  PubMed  Google Scholar 

  9. Hong L, Lei H, Kun SJ, Hai Y, Dong W, Ke Z, Ping X, Hao C (2012) A preliminary investigation on NSCLP plasma and urine in Guizhou province in CHINA using NMR-based metabonomics. Cleft Palate Craniofac J. doi:10.1597/11-175

    PubMed  Google Scholar 

  10. Batur M, Halmurat U, Hao FH, Aiziz R, Aynur M (2012) Correlative analysis of neoplasm patients with phlegm-stasis or abnormal Savda syndrome based on metabonomics. J Tradit Chin Med 32:119–124

    Article  PubMed  Google Scholar 

  11. Sun L, Hu W, Liu Q, Hao Q, Sun B, Zhang Q, Mao S, Qiao J, Yan X (2012) Metabonomics reveals plasma metabolic changes and inflammatory marker in polycystic ovary syndrome patients. J Proteome Res 11:2937–2946

    Article  CAS  PubMed  Google Scholar 

  12. Zheng P, Gao HC, Li Q, Shao WH, Zhang ML, Cheng K, de Yang Y, Fan SH, Chen L, Fang L, Xie P (2012) Plasma metabonomics as a novel diagnostic approach for major depressive disorder. J Proteome Res 11:1741–1748

    Article  CAS  PubMed  Google Scholar 

  13. Ala-Korpela M, Salomaa V, Kvalheim OM (2011) Clinical and epidemiological metabonomics. J Biomed Biotechnol 2011:843150

    Article  PubMed Central  PubMed  Google Scholar 

  14. Nicholson JK, Lindon JC, Holmes E (1999) ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29:1181–1189

    Article  CAS  PubMed  Google Scholar 

  15. Fiehn O, Kopka J, Dörmann P, Altmann T, Trethewey RN, Willmitzer L (2000) Metabolite profiling for plant functional genomics. Nat Biotechnol 18:1157–1161

    Article  CAS  PubMed  Google Scholar 

  16. Wilson I (2011) Global metabolic profiling (metabonomics/metabolomics) using dried blood spots: advantages and pitfalls. Bioanalysis 3:2255–2257

    Article  CAS  PubMed  Google Scholar 

  17. Pasikanti KK, Ho PC, Chan EC (2008) Gas chromatography mass spectrometry in metabolic profiling of biological fluids. J Chromatogr B Analyt Technol Biomed Life Sci 871:202–211

    Article  CAS  PubMed  Google Scholar 

  18. Gika HG, Macpherson E, Theodoridis GA, Wilson ID (2008) Evaluation of the repeatability of ultra-performance liquid chromatography-TOF-MS for global metabolic profiling of human urine samples. J Chromatogr B Analyt Technol Biomed Life Sci 871:299–305

    Article  CAS  PubMed  Google Scholar 

  19. Dobrinas M, Choong E, Noetzli M, Cornuz J, Ansermot N, Eap CB (2011) Quantification of nicotine, cotinine, trans-3'-hydroxycotinine and varenicline in human plasma by a sensitive and specific UPLC-tandem mass-spectrometry procedure for a clinical study on smoking cessation. J Chromatogr B Analyt Technol Biomed Life Sci 879:3574–3582

    Article  CAS  PubMed  Google Scholar 

  20. Wang X, Sun H, Zhang A, Wang P, Han Y (2011) Ultra-performance liquid chromatography coupled to mass spectrometry as a sensitive and powerful technology for etabolomic studies. J Sep Sci 34:3451–3459

    Article  CAS  PubMed  Google Scholar 

  21. Waterman DS, Bonner FW, Lindon JC (2009) Spectroscopic and statistical methods in metabonomics. Bioanalysis 1:1559–1578

    Article  CAS  PubMed  Google Scholar 

  22. Lindon JC, Nicholson JK (2008) Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics. Annu Rev Anal Chem 1:45–69

    Article  CAS  Google Scholar 

  23. Osborn MP, Park Y, Parks MB, Burgess LG, Uppal K, Lee K, Jones DP (2013) Brantley MA Jr (2013) Metabolome-wide association study of neovascular age-related macular degeneration. PLoS One 8(8):e72737

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  24. Young SP, Nessim M, Falciani F, Trevino V, Banerjee SP, Scott RA, Murray PI, Wallace GR (2009) Metabolomic analysis of human vitreous humor differentiates ocular inflammatory disease. Mol Vis 15:1210–1217

    CAS  PubMed Central  PubMed  Google Scholar 

  25. Namazi MR (2004) The beneficial and detrimental effects of linoleic acid on autoimmune disorders. Autoimmunity 37:73–75

    Article  CAS  PubMed  Google Scholar 

  26. Jabs DA, Nussenblatt RB, Rosenbaum JT (2005) Standardization of Uveitis Nomenclature (SUN) Working Group. Standardization of uveitis nomenclature for reporting clinical data: results of the First International Workshop. Am J Ophthalmol 140:509–516

    Article  PubMed  Google Scholar 

  27. Yang MM, Lai TY, Tam PO, Chiang SW, Chan CK, Luk FO, Ng TK, Pang CP (2011) CFH 184G as a genetic risk marker for anterior uveitis in Chinese females. Mol Vis 17:2655–2664

    CAS  PubMed Central  PubMed  Google Scholar 

  28. Wang X, Sun H, Zhang A, Wang P, Han Y (2011) Ultra-performance liquid chromatography coupled to mass spectrometry as a sensitive and powerful technology for metabolomic studies. J Sep Sci 34:3451–3459

    Article  CAS  PubMed  Google Scholar 

  29. Agudo-Barriuso M, Lahoz A, Nadal-Nicolás FM, Sobrado-Calvo P, Piquer-Gil M, Díaz-Llopis M, Vidal-Sanz M, Mullor JL (2013) Metabolomic changes in the rat retina after optic nerve crush. Invest Ophthalmol Vis Sci 54(6):4249–4259

    Article  CAS  PubMed  Google Scholar 

  30. Vethe NT, Bergan S (2006) Determination of inosine monophosphate dehydrogenase activity in human CD4+ cells isolated from whole blood during mycophenolic acid therapy. Ther Drug Monit 28:608–613

    Article  CAS  PubMed  Google Scholar 

  31. Khalil PN, Erb N, Khalil MN, Escherich G, Janka-Schaub GE (2006) Validation and application of a high-performance liquid chromatographic-based assay for determination of the inosine 5'-monophosphate dehydrogenase activity in erythrocytes. J Chromatogr B Analyt Technol Biomed Life Sci 842:1–7

    Article  CAS  PubMed  Google Scholar 

  32. Serkova NJ, Standiford TJ, Stringer KA (2011) The emerging field of quantitative blood metabolomics for biomarker discovery in critical illnesses. Am J Respir Crit Care Med 184(6):647–655

    Article  CAS  PubMed Central  PubMed  Google Scholar 

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Acknowledgments

The present work was supported by the foundation from the National Natural Science Foundation of China (81072961, 81373826), the Development Project of Medicine and Health Science Technology of Shandong Province (2013WS0251), Development Project of Science and Technology of Traditional Chinese Medicine of Shandong Province (2013ZDZK-083). The authors would like to thank the Waters Corporation, especially Yun Wang Ph.D and Lankun Song, for their assistance with UPLC–MS experiments on the research described in this manuscript.

Conflict of interest

The authors declare that they have no conflict or financial interest in the subject matter of this manuscript.

Presentation at conference

The paper abstract was used as written communication on 5th Chinese Congress of Research in Vision and Ophthalmology,CCRVO 2013; Submitted paper abstract to The 18th Congress of Chinese Ophthalmological Society (September 13–17, 2013 Xiamen International Convention and Exhibition Center).

Clinical trial registration

The study was approved by the Eye Institute of Shandong University of TCM, reference number 2012003.

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Correspondence to Hongsheng Bi.

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Guo, J., Yan, T., Bi, H. et al. Plasma metabonomics study of the patients with acute anterior uveitis based on ultra-performance liquid chromatography–mass spectrometry. Graefes Arch Clin Exp Ophthalmol 252, 925–934 (2014). https://doi.org/10.1007/s00417-014-2619-1

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  • DOI: https://doi.org/10.1007/s00417-014-2619-1

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