Skip to main content
SpringerLink
Log in

Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients

  • Original Article
  • Published:
Indian Journal of Clinical Biochemistry Aims and scope Submit manuscript

Abstract

Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, noninvasive, inexpensive, and efficient diagnostic tool for various human diseases. Despite these advantages, urine is an under-investigated source of biomarkers for multiple sclerosis (MS). The objective was to investigate the level of some urinary metabolites (urea, uric acid and hippuric acid) in patients with MS and correlate their levels to the severity of the disease, MS subtypes and MS treatment. The urine samples were collected from 73 MS patients-48 with RRMS and 25 with SPMS- and age matched 75 healthy controls. The values of urinary urea, uric acid and hippuric acid in MS patients were significantly decreased, and these metabolites in SPMS pattern showed significantly decrease than RRMS pattern. Also showed significant inverse correlation with expanded disability status scale and number of relapses. Accordingly, they may act as a potential urinary biomarkers for MS, and correlate to disease progression.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Sospedra M, Martin R. Immunology of multiple sclerosis. Annu Rev Immunol. 2005;23:683–747.

    Article  CAS  PubMed  Google Scholar 

  2. Miller E, Walczak A, Saluk J, Ponczek MB, Majsterek I. Oxidative modification of patient’s plasma proteins and its role in pathogenesis of multiple sclerosis. Clin Biochem. 2012;45(1–2):26–30. doi:10.1016/j.clinbiochem.2011.09.021.

    Article  CAS  PubMed  Google Scholar 

  3. Tremlett H, van der Mei IA, Pittas F, Blizzard L, Paley G, Mesaros D, et al. Monthly ambient sunlight, infections and relapse rates in multiple sclerosis. Neuroepidemiology. 2008;31(4):271–9. doi:10.1159/000166602.

    Article  PubMed  Google Scholar 

  4. Marrie RA, Cohen JA. Interferons in secondary progressive multiple sclerosis, in multiple sclerosis therapeutics. 3rd ed. London: Informa Healthcare; 2007.

    Google Scholar 

  5. Gebregiworgis T, Massilamany C, Gangaplara A, Thulasingam S, Kolli V, Werth MT, et al. The potential of urinary metabolites for diagnosing multiple sclerosis. ACS Chem Biol. 2013;8(4):684–90. doi:10.1021/cb300673e.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lourenco AS, Baldeiras I, Graos M, Duarte CB. Proteomics-based technologies in the discovery of biomarkers for Multiple Sclerosis in the cerebrospinal fluid. Curr Mol Med. 2011;11(4):326–49.

    Article  CAS  PubMed  Google Scholar 

  7. Bielekova B, Martin R. Development of biomarkers in multiple sclerosis. Brain. 2004;127(Pt 7):1463–78.

    Article  PubMed  Google Scholar 

  8. Dobson R. Urine: an under-studied source of biomarkers in multiple sclerosis? Mult Scler Relat Disord. 2012;1(2):76–80. doi:10.1016/j.msard.2012.01.002.

    Article  CAS  PubMed  Google Scholar 

  9. Gholipour T, Ghazizadeh T, Babapour S, Mansouri B, Ghafarpour M, Siroos B, et al. Decreased urinary level of melatonin as a marker of disease severity in patients with multiple sclerosis. Iran J Allergy Asthma Immunol. 2015;14(1):91–7.

    PubMed  Google Scholar 

  10. Rejdak K, Leary SM, Petzold A, Thompson AJ, Miller DH, Giovannoni G. Urinary neopterin and nitric oxide metabolites as markers of interferon beta-1a activity in primary progressive multiple sclerosis. Mult Scler. 2010;16(9):1066–72. doi:10.1177/1352458510375100.

    Article  CAS  PubMed  Google Scholar 

  11. Dobson R, Miller RF, Palmer HE, Feldmann M, Thompson EJ, Thompson AJ, et al. Increased urinary free immunoglobulin light chain excretion in patients with multiple sclerosis. J Neuroimmunol. 2010;220(1–2):99–103. doi:10.1016/j.jneuroim.2010.01.012.

    Article  CAS  PubMed  Google Scholar 

  12. Gebregiworgis T, Powers R. Application of NMR metabolomics to search for human disease biomarkers. Comb Chem High Throughput Screen. 2012;15(8):595–610.

    Article  CAS  PubMed  Google Scholar 

  13. Patassini S, Begley P, Reid SJ, Xu J, Church SJ, Curtis M, et al. Identification of elevated urea as a severe, ubiquitous metabolic defect in the brain of patients with Huntington’s disease. Biochem Biophys Res Commun. 2015;468(1–2):161–6. doi:10.1016/j.bbrc.2015.10.140.

    Article  CAS  PubMed  Google Scholar 

  14. Xu J, Begley P, Church SJ, Patassini S, Hollywood KA, Jüllig M, et al. Graded perturbations of metabolism in multiple regions of human brain in Alzheimer’s disease: snapshot of a pervasive metabolic disorder. Biochim Biophys Acta. 2016;1862(6):1084–92. doi:10.1016/j.bbadis.2016.03.001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Kutzing MK, Firestein BL. Altered uric acid levels and disease states. J Pharmacol Exp Ther. 2008;324(1):1–7.

    Article  CAS  PubMed  Google Scholar 

  16. Pakpoor J, Seminog OO, Ramagopalan SV, Goldacre MJ. Clinical associations between gout and multiple sclerosis, Parkinson’s disease and motor neuron disease: record-linkage studies. BMC Neurol. 2015;15:16. doi:10.1186/s12883-015-0273-9.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Lees HJ, Swann JR, Wilson ID, Nicholson JK, Holmes E. Hippurate: the natural history of a mammalian-microbial cometabolite. J Proteome Res. 2013;12(4):1527–46. doi:10.1021/pr300900b.

    Article  CAS  PubMed  Google Scholar 

  18. Cantarel BL, Waubant E, Chehoud C, Kuczynski J, DeSantis TZ, Warrington J, et al. Gut microbiota in multiple sclerosis: possible influence of immunomodulators. J Invest Med. 2015;63(5):729–34.

    Article  CAS  Google Scholar 

  19. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69(2):292–302. doi:10.1002/ana.22366.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33(11):1444–52.

    Article  CAS  PubMed  Google Scholar 

  21. Roxburgh RH, Seaman SR, Masterman T, Hensiek AE, Sawcer SJ, Vukusic S, et al. Multiple sclerosis severity score: using disability and disease duration to rate disease severity. Neurology. 2005;64(7):1144–51.

    Article  CAS  PubMed  Google Scholar 

  22. Trinder P. Determination of blood glucose using 4-amino phenazone as oxygen acceptor. J Clin Pathol. 1969;22(2):246.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Chaney A, Marbach E. Modified reagents for determination of urea and ammonia. Clin Chem. 1962;8:130–2.

    CAS  PubMed  Google Scholar 

  24. Tomokuni K, Ogata M. Direct colorimetric determination of hippuric acid in urine. Clin Chem. 1972;18(4):349–51.

    CAS  PubMed  Google Scholar 

  25. Wu J, Gao Y. Physiological conditions can be reflected in human urine proteome and metabolome. Expert Rev Proteom. 2015;12(6):623–36. doi:10.1586/14789450.2015.1094380.

    Article  CAS  Google Scholar 

  26. Gao Y. Urine-an untapped goldmine for biomarker discovery. Sci China Life Sci. 2013;56(12):1145–6. doi:10.1007/s11427-013-4574-1.

    Article  PubMed  Google Scholar 

  27. Schanstra JP, Mischak H. Proteomic urinary biomarker approach in renal disease: from discovery to implementation. Pediatr Nephrol. 2015;30(5):713–25. doi:10.1007/s00467-014-2790-y.

    Article  PubMed  Google Scholar 

  28. Jove M, Portero-Otin M, Naudi A, Ferrer I, Pamplona R. Metabolomics of human brain aging and age-related neurodegenerative diseases. J Neuropathol Exp Neurol. 2014;73(7):640–57. doi:10.1097/NEN.0000000000000091.

    Article  CAS  PubMed  Google Scholar 

  29. Miao Y, Liao JK. Potential serum biomarkers in the pathophysiological processes of stroke. Expert Rev Neurother. 2014;14(2):173–85. doi:10.1586/14737175.2014.875471.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Mangalam A, Poisson L, Nemutlu E, Datta I, Denic A, Dzeja P, et al. Profile of circulatory metabolites in a relapsing-remitting animal model of multiple sclerosis using global metabolomics. J Clin Cell Immunol. 2013;. doi:10.4172/2155-9899.1000150.

    PubMed  PubMed Central  Google Scholar 

  31. Bradford CM, Ramos I, Cross AK, Haddock G, McQuaid S, Nicholas AP, et al. Localisation of citrullinated proteins in normal appearing white matter and lesions in the central nervous system in multiple sclerosis. J Neuroimmunol. 2014;273(1–2):85–95. doi:10.1016/j.jneuroim.2014.05.007.

    Article  CAS  PubMed  Google Scholar 

  32. Pasquinelli S, Solaro C. Nutritional assessment and malnutrition in multiple sclerosis. Neurol Sci. 2008;29(Suppl 4):S367–9. doi:10.1007/s10072-008-1046-7.

    Article  PubMed  Google Scholar 

  33. Sorgun MH, Yucesan C, Tegin C. Is malnutrition a problem for multiple sclerosis patients? J Clin Neurosci. 2014;21(9):1603–5. doi:10.1016/j.jocn.2013.12.024.

    Article  PubMed  Google Scholar 

  34. Rentzos M, Nikolaou C, Anagnostouli M, Rombos A, Tsakanikas K, Economou M, et al. Serum uric acid and multiple sclerosis. Clin Neurol Neurosurg. 2006;108(6):527–31.

    Article  CAS  PubMed  Google Scholar 

  35. Amorini AM, Petzold A, Tavazzi B, Eikelenboom J, Keir G, Belli A, et al. Increase of uric acid and purine compounds in biological fluids of multiple sclerosis patients. Clin Biochem. 2009;42(10–11):1001–6. doi:10.1016/j.clinbiochem.2009.03.020.

    Article  CAS  PubMed  Google Scholar 

  36. Zoccolella S, Tortorella C, Iaffaldano P, Direnzo V, D’Onghia M, Luciannatelli E, et al. Low serum urate levels are associated to female gender in multiple sclerosis patients. PLoS ONE. 2012;7(7):e40608. doi:10.1371/journal.pone.0040608.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Mattle HP, Lienert C, Greeve I. Uric acid and multiple sclerosis. Ther Umsch. 2004;61(9):553–5.

    Article  CAS  PubMed  Google Scholar 

  38. Chittoor G, Kent JW Jr, Almeida M, Puppala S, Farook VS, Cole SA, et al. GWAS and transcriptional analysis prioritize ITPR1 and CNTN4 for a serum uric acid 3p26 QTL in Mexican Americans. BMC Genom. 2016;17:276. doi:10.1186/s12864-016-2594-5.

    Article  Google Scholar 

  39. Markowitz CE, Spitsin S, Zimmerman V, Jacobs D, Udupa JK, Hooper DC, et al. The treatment of multiple sclerosis with inosine. J Altern Complement Med. 2009;15(6):619–25. doi:10.1089/acm.2008.0513.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Guerrero AL, Gutiérrez F, Iglesias F, Martín-Polo J, Merino S, Martín-Serradilla J, et al. Serum uric acid levels in multiple sclerosis patients inversely correlate with disability. Neurol Sci. 2011;32(2):347–50. doi:10.1007/s10072-011-0488-5.

    Article  CAS  PubMed  Google Scholar 

  41. Peng F, Zhang B, Zhong X, Li J, Xu G, Hu X, et al. Serum uric acid levels of patients with multiple sclerosis and other neurological diseases. Mult Scler. 2008;14:188–96.

    Article  CAS  PubMed  Google Scholar 

  42. Peng F, Zhong X, Deng X, Qiu W, Wu A, Long Y, et al. Serum uric acid levels and neuromyelitis optica. J Neurol. 2010;257:1021–6.

    Article  CAS  PubMed  Google Scholar 

  43. Kawai T, Ukai H, Inoue O, Maejima Y, Fukui Y, Ohashi F, et al. Evaluation of biomarkers of occupational exposure to toluene at low levels. Int Arch Occup Environ Health. 2008;81(3):253–62.

    Article  CAS  PubMed  Google Scholar 

  44. Castellani S, Ungar A, Cantini C, La Cava G, Di Serio C, Altobelli A, et al. Excessive vasoconstriction after stress by the aging kidney: inadequate prostaglandin modulation of increased endothelin activity. J Lab Clin Med. 1998;132(3):186–94.

    Article  CAS  PubMed  Google Scholar 

  45. Brahmachari S, Pahan K. Sodium benzoate, a food additive and a metabolite of cinnamon, modifies T cells at multiple steps and inhibits adoptive transfer of experimental allergic encephalomyelitis. J Immunol. 2007;179(1):275–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Pahan K. Immunomodulation of experimental allergic encephalomyelitis by cinnamon metabolite sodium benzoate. Immunopharmacol Immunotoxicol. 2011;33(4):586–93. doi:10.3109/08923973.2011.561861.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Ochoa-Reparaz J, Mielcarz DW, Ditrio LE, Burroughs AR, Foureau DM, Haque-Begum S, et al. Role of gut commensal microflora in the development of experimental auto-immune encephalomyelitis. J Immunol. 2009;183(10):6041–50. doi:10.4049/jimmunol.0900747.

    Article  CAS  PubMed  Google Scholar 

  48. Benzel F, Erdur H, Kohler S, Frentsch M, Thiel A, Harms L, et al. Immune monitoring of Trichuris suis egg therapy in multiple sclerosis patients. J Helminthol. 2012;86(3):339–47. doi:10.1017/S0022149X11000460.

    Article  CAS  PubMed  Google Scholar 

  49. Wilson JC, Furlano RI, Jick SS, Meier CR. Inflammatory bowel disease and the risk of autoimmune diseases. J Crohns Colitis. 2016;10(2):186–93. doi:10.1093/ecco-jcc/jjv193.

    Article  PubMed  Google Scholar 

  50. Schicho R, Shaykhutdinov R, Ngo J, Nazyrova A, Schneider C, Panaccione R, et al. Quantitative metabolomic profiling of serum, plasma, and urine by 1H NMR spectroscopy discriminates between patients with inflammatory bowel disease and healthy individuals. J Proteome Res. 2012;11(6):3344–57. doi:10.1021/pr300139q.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Williams HR, Cox IJ, Walker DG, Cobbold JF, Taylor-Robinson SD, Marshall SE, et al. Differences in gut microbial metabolism are responsible for reduced hippurate synthesis in Crohn’s disease. BMC Gastroenterol. 2010;10:108. doi:10.1186/1471-230X-10-108.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgement

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Biochemistry Department, Faculty of Pharmacy, Helwan University, Cairo, Egypt

    Hanaa B. Atya, Sahar A. Ali & Fathia Z. El Sharkawi

  2. Neurology Department, Faculty of Medicine, Cairo University, Cairo, Egypt

    Mohamed I. Hegazy

Authors
  1. Hanaa B. Atya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sahar A. Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohamed I. Hegazy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fathia Z. El Sharkawi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hanaa B. Atya.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interests related to the publication of this paper.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Atya, H.B., Ali, S.A., Hegazy, M.I. et al. Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients. Ind J Clin Biochem 33, 163–170 (2018). https://doi.org/10.1007/s12291-017-0661-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12291-017-0661-6

Keywords

Search

Navigation