Metabolomics reveals elevated urinary excretion of collagen degradation and epithelial cell turnover products in irritable bowel syndrome patients

Abstract

Introduction

Irritable bowel syndrome (IBS), the most commonly diagnosed functional gastrointestinal (GI) disorder in developed countries, is characterized by chronic abdominal pain, and altered bowel habits.

Objectives

Accurate and timely diagnosis is challenging as it relies on symptoms and an evolving set of exclusion criteria to distinguish it from other related GI disorders reflecting a complex etiology that remains poorly understood. Herein, nontargeted metabolite profiling of repeat urine specimens collected from a cohort of IBS patients (n = 42) was compared to healthy controls (n = 20) to gain insights into the underlying pathophysiology.

Methods

An integrated data workflow for characterization of the urine metabolome with stringent quality control was developed to authenticate reliably measured (CV < 30%) and frequently detected (> 75%) metabolites using multisegment injection-capillary electrophoresis-mass spectrometry. Complementary statistical methods were then used to rank differentially excreted urinary metabolites after normalization to osmolality that were subsequently identified by high resolution tandem mass spectrometry and their electrophoretic migration behavior.

Results

Our work revealed ten consistently elevated urinary metabolites in repeat samples collected from IBS patients at two different time points (q < 0.05 after age and Benjamini-Hochberg/FDR adjustment), which were associated with greater collagen degradation and intestinal mucosal turn-over processes likely due to low-grade inflammation. IBS-specific metabolites identified in urine included a series of hydroxylysine metabolites (O-glycosylgalactosyl-hydroxylysine, O-galactosyl-hydroxylysine, lysine), mannopyranosy-l-tryptophan, imidazole propionate, glutamine, serine, ornithine, dimethylglycine and dimethylguanosine. A major limitation in this retrospective case-control study was significant co-morbidity of IBS patients with other illnesses, including depression and prescribed medications as compared to healthy controls.

Conclusion

This work provides new mechanistic insights into the pathophysiology of IBS while also offering a convenient way to monitor patient disease progression and treatment responses to therapy based on a panel of urinary metabolites that avoids invasive blood sampling, colonoscopy and/or tissue biopsies.

Graphical Abstract

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Data availability

Creatinine and osmolality normalized urine metabolomics data matrices for IBS patients, healthy controls and quality controls are available in the supporting information as excel files.

References

  1. Abdalla, M. I., Sandler, R. S., Kappelman, M. D., Martin, C. F., Chen, W., Anton, K., et al. (2017). Prevalence and impact of inflammatory bowel disease—irritable bowel syndrome on patient-reported outcomes in CCFA partners. Inflammatory Bowel Diseases, 23, 325–331.

    PubMed  PubMed Central  Google Scholar 

  2. Ahmed, I., Greenwood, R., Costello, B. D. L., Ratcliffe, N. M., & Probert, C. S. (2013). An investigation of fecal volatile organic metabolites in irritable bowel syndrome. PLoS ONE, 8, e58204.

    PubMed  PubMed Central  Google Scholar 

  3. Azpiroz, F., Bouin, M., Camilleri, M., Mayer, E. A., Poitras, P., Serra, J., et al. (2007). Mechanisms of hypersensitivity in IBS and functional disorders. Neurogastroenterology and Motility, 19, 62–88.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Baranska, A., Mujagic, Z., Smolinska, A., Dallinga, J. W., Jonkers, D. M. A. E., Tigchelaar, E. F., et al. (2016). Volatile organic compounds in breath as markers for irritable bowel syndrome: A metabolomic approach. Alimentary Pharmacology & Therapeutics, 44, 45–56.

    CAS  Google Scholar 

  5. Bateman, J. F., Mascara, T., Chan, D., & Cole, W. G. (1984). Abnormal type I collagen metabolism by cultured fibroblasts in lethal perinatal osteogenesis imperfecta. Biochemical Journal, 217, 103–115.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Bercik, P., Verdú, E. F., Foster, J. A., Lu, J., Scharringa, A., Kean, I., et al. (2009). Role of gut-brain axis in persistent abnormal feeding behavior in mice following eradication of Helicobacter pylori infection. American Journal of Physiology - Regulatory, Integrative and Comparative Physiology, 296, R587–R594.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Bockenhauer, D., & Aitkenhead, H. (2011). The kidney speaks: interpreting urinary sodium and osmolality. Archives of Disease in Childhood, 96, 223–227.

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Böhning, D., Böhning, W., Guha, N., Cowan, D. A., Sönksen, P. H., & Holt, R. I. G. (2016). Statistical methodology for age-adjustment of the GH-2000 score detecting growth hormone misuse. BMC Medical Research Methodology, 16, 147.

    PubMed  PubMed Central  Google Scholar 

  9. Bouatra, S., Aziat, F., Mandal, R., Guo, A. C., Wilson, M. R., Knox, C., et al. (2013). The human urine metabolome. PLoS ONE, 8, e73076.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Bowen, B. P., & Northen, T. R. (2010). Dealing with the unknown: Metabolomics and metabolite atlases. Journal of the American Society for Mass Spectrometry, 21, 1471–1476.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Brunius, C., Shi, L., & Landberg, R. (2016). Large-scale untargeted LC-MS metabolomics data correction using between-batch feature alignment and cluster-based within-batch signal intensity drift correction. Metabolomics, 12, 173.

    PubMed  PubMed Central  Google Scholar 

  12. Camilleri, M., Shin, A., Busciglio, I., Carlson, P., Acosta, A., Bharucha, A. E., et al. (2014). Validating biomarkers of treatable mechanisms in irritable bowel syndrome. Neurogastroenterology and Motility, 26, 1677–1685.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Carrieri, M., Trevisan, A., & Bartolucci, G. B. (2000). Adjustment to concentration-dilution of spot urine samples: Correlation between specific gravity and creatinine. International Archives of Occupational and Environmental Health, 74, 63–67.

    Google Scholar 

  14. Chadha, V., Garg, U., & Alon, U. S. (2001). Measurement of urinary concentration: A critical appraisal of methodologies. Pediatric Nephrology, 16, 374–382.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Changhyun, L., et al. (2017). The increased level of depression and anxiety in irritable bowel syndrome patients compared with healthy controls: Systematic review and meta-analysis. Journal of Neurogastroenterology and Motility, 23, 349–362.

    Google Scholar 

  16. Chong, J., Soufan, O., Li, C., Caraus, I., Li, S., Bourque, G., et al. (2018). Metaboanalyst 4.0: Towards more transparent and integrative metabolomics analysis. Nucleic Acids Research, 46, W486–W494.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Cleare, A., Pariante, C. M., Young, A. H., Anderson, I. M., Christmas, D., Cowen, P. J., et al. (2015). Evidence-based guidelines for treating depressive disorders with antidepressants: A revision of the 2008 British Association for Psychopharmacology guidelines. Journal of Psychopharmacology, 29, 459–525.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Cunningham, L. W., Ford, J. D., & Segrest, J. P. (1967). The isolation of identical hydroxylysyl glycosides from hydrolysates of soluble collagen and from human urine. Journal of Biological Chemistry, 242, 2570–2571.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Dahl, H., Stephanson, N., Beck, O., & Helander, A. (2002). Comparison of urinary excretion characteristics of ethanol and ethyl glucuronide. Journal of Analytical Toxicology, 26, 201–204.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Deiteren, A., De Man, J. G., Pelckmans, P. A., & De Winter, B. Y. (2015). Histamine H4 receptors in the gastrointestinal tract. British Journal of Pharmacology, 172, 1165–1178.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. DiBattista, A., McIntosh, N., Lamoureux, M., Al-Dirbashi, O. Y., Chakraborty, P., & Britz-McKibbin, P. (2017a). Temporal signal pattern recognition in mass spectrometry: A method for rapid identification and accurate quantification of biomarkers for inborn errors of metabolism with quality assurance. Analytical Chemistry, 89, 8112–8121.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. DiBattista, A., McIntosh, N., Lamoureux, M., Al-Dirbashi, O. Y., Chakraborty, P., & Britz-McKibbin, P. (2019). Metabolic signatures of cystic fibrosis identified in dried blood spots for newborn screening without carrier identification. Jorunal of Proteome Research, 18, 841–854.

    CAS  Google Scholar 

  23. DiBattista, A., Rampersaud, D., Lee, H., Kim, M., & Britz-McKibbin, P. (2017b). High throughput screening method for systematic surveillance of drugs of abuse by multisegment injection–capillary electrophoresis–mass spectrometry. Analytical Chemistry, 89, 11853–11861.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Diederen, K., Hoekman, D. R., Hummel, T. Z., Meij, T. G., Koot, B. G. P., Tabbers, M. M., et al. (2016). The prevalence of irritable bowel syndrome-type symptoms in paediatric inflammatory bowel disease, and the relationship with biochemical markers of disease activity. Alimentary Pharmacology & Therapeutics, 44, 181–188.

    CAS  Google Scholar 

  25. Dinan, T. G., & Cryan, J. F. (2017). Brain–gut–microbiota axis—mood, metabolism and behaviour. Nature Reviews Gastroenterology & Hepatology, 14, 69.

    CAS  Google Scholar 

  26. Drossman, D. A. (2016). Functional gastrointestinal disorders: History, pathophysiology, clinical features, and Rome IV. Gastroenterology, 150, 1262–1279.

    Google Scholar 

  27. Dumas, M.-E., Barton, R. H., Toye, A., Cloarec, O., Blancher, C., Rothwell, A., et al. (2006). Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proceedings of the National academy of Sciences of the United States of America, 103, 12511–12516.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Edamatsu, T., Fujieda, A., & Itoh, Y. (2018). Phenyl sulfate, indoxyl sulfate and p-cresyl sulfate decrease glutathione level to render cells vulnerable to oxidative stress in renal tubular cells. PLoS ONE, 13, e0193342.

    PubMed  PubMed Central  Google Scholar 

  29. Eisenstein, M. (2016). Microbiome: Bacterial broadband. Nature, 533, S104–S106.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Enck, P., Aziz, Q., Barbara, G., Farmer, A. D., Fukudo, S., Mayer, E. A., et al. (2016). Irritable bowel syndrome. Nature Reviews Disease Primers, 2, 16014.

    PubMed  PubMed Central  Google Scholar 

  31. Forough, F., Brock, E., & Jan, I. E. (2006). Functional gastrointestinal disorders and mood disorders in patients with inactive inflammatory bowel disease: Prevalence and impact on health. Inflammatory Bowel Diseases, 12, 38–46.

    Google Scholar 

  32. Fowler, D. I., Norton, P. M., Cheung, M. W., & Pratt, E. L. (1957). Observations on the urinary amino acid excretion in man: the influence of age and diet. Archives of Biochemistry and Biophysics, 68, 452–466.

    CAS  PubMed  Google Scholar 

  33. Friesen, R. W., Novak, E. M., Hasman, D., & Innis, S. M. (2007). Relationship of dimethylglycine, choline, and betaine with oxoproline in plasma of pregnant women and their newborn infants. The Journal of Nutrition, 137, 2641–2646.

    CAS  PubMed  Google Scholar 

  34. García Rodríguez, L. A., Ruigómez, A., Wallander, M. A., Johansson, S., & Olbe, L. (2000). Detection of colorectal tumor and inflammatory bowel disease during follow-up of patients with initial diagnosis of irritable bowel syndrome. Scandinavian Journal of Gastroenterology, 35, 306–311.

    PubMed  PubMed Central  Google Scholar 

  35. Geremia, A., Biancheri, P., Allan, P., Corazza, G. R., & Di Sabatino, A. (2014). Innate and adaptive immunity in inflammatory bowel disease. Autoimmunity Reviews, 13, 3–10.

    CAS  PubMed  Google Scholar 

  36. Goo, Y. A., Cain, K., Jarrett, M., Smith, L., Voss, J., Tolentino, E., et al. (2012). Urinary proteome analysis of irritable bowel syndrome (IBS) symptom subgroups. Journal of Proteome Research, 11, 5650–5662.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Graber, C. D., Goust, J. M., Glassman, A. D., Kendall, R., & Loadholt, C. B. (1981). Immunomodulating properties of dimethylglycine in humans. The Journal of Infectious Diseases, 143, 101–105.

    CAS  PubMed  Google Scholar 

  38. Gwee, K.-A., Collins, S. M., Read, N. W., Rajnakova, A., Deng, Y., Graham, J. C., et al. (2003). Increased rectal mucosal expression of interleukin 1β in recently acquired post-infectious irritable bowel syndrome. Gut, 52, 523–526.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Halmos, E. P., Power, V. A., Shepherd, S. J., Gibson, P. R., & Muir, J. G. (2014). A diet low in FODMAPs reduces symptoms of irritable bowel syndrome. Gastroenterology, 146, 67–75.

    CAS  PubMed  Google Scholar 

  40. Hamming, O. J., Kang, L., Svensson, A., Karlsen, J. L., Rahbek-Nielsen, H., Paludan, S. R., et al. (2012). Crystal structure of interleukin-21 receptor (IL-21R) bound to IL-21 reveals that sugar chain interacting with WSXWS motif is integral part of IL-21R. Journal of Biological Chemistry, 287, 9454–9460.

    CAS  PubMed  Google Scholar 

  41. Hayes, P. A., Fraher, M. H., & Quigley, E. M. M. (2014). Irritable bowel syndrome: The role of food in pathogenesis and management. Gastroenterology & Hepatology, 10, 164–174.

    Google Scholar 

  42. Hilska, M., Collan, Y., Peltonen, J., Gullichsen, R., Paajanen, H., & Laato, M. (1998). The distribution of collagen types I, III, and IV in normal and malignant colorectal mucosa. European Journal of Surgery, 164, 457–464.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Hofmann, A. F., & Hagey, L. R. (2008). Bile acids: Chemistry, pathochemistry, biology, pathobiology, and therapeutics. Cellular and Molecular Life Sciences, 65, 2461–2483.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Ihara, Y., Inai, Y., Ikezaki, M., Matsui, I.-S. L., Manabe, S., & Ito, Y. (2015). C-Mannosylation: Modification on tryptophan in cellular proteins. In N. Taniguchi, T. Endo, W. G. Hart, H. P. Seeberger, & C.-H. Wong (Eds.), Glycoscience: Biology and medicine (pp. 1091–1099). Tokyo: Springer Japan.

    Google Scholar 

  45. Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016). Metabolomics: Beyond biomarkers and towards mechanisms. Nature Review Molecular Cell Biology, 17, 451–459.

    CAS  Google Scholar 

  46. Kendig, D. M., & Grider, J. R. (2015). Serotonin and colonic motility. Neurogastroenterology and Motility, 27, 899–905.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Kennedy, P. J., Cryan, J. F., Dinan, T. G., & Clarke, G. (2014). Irritable bowel syndrome: A microbiome-gut-brain axis disorder? World Journal of Gastroenterology, 20, 14105–14125.

    PubMed  PubMed Central  Google Scholar 

  48. Keszthelyi, D., Troost, F. J., Jonkers, D. M., Kruimel, J. W., Leue, C., & Masclee, A. A. M. (2013). Decreased levels of kynurenic acid in the intestinal mucosa of IBS patients: Relation to serotonin and psychological state. Journal of Psychosomatic Research, 74, 501–504.

    PubMed  Google Scholar 

  49. Koh, A., Molinaro, A., Stahlman, M., Khan, M. T., Schmidt, C., Manneras-Holm, L., et al. (2018). Microbially produced imidazole propionate impairs insulin signalling through mTORC1. Cell, 175, 947–961.

    CAS  PubMed  Google Scholar 

  50. Krane, S. M., Kantrowitz, F. G., Byrne, M., Pinnell, S. R., & Singer, F. R. (1977). Urinary excretion of hydroxylysine and its glycosides as an index of collagen degradation. Journal of Clinical Investigation, 59, 819–827.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Kuehnbaum, N. L., Gillen, J. B., Kormendi, A., Lam, K. P., DiBattista, A., Gibala, M. J., et al. (2015). Multiplexed separations for biomarker discovery in metabolomics: Elucidating adaptive responses to exercise training. Electrophoresis, 36, 2226–2236.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Kuehnbaum, N. L., Kormendi, A., & Britz-McKibbin, P. (2013). Multisegment injection-capillary electrophoresis-mass spectrometry: A high throughput platform for metabolomics with high data fidelity. Analytical Chemistry, 85, 10664–10669.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Lacy, B. E. (2016). Perspective: An easier diagnosis. Nature, 533, S107–S107.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Lacy, B. E., Mearin, F., Chang, L., Chey, W. D., Lembo, A. J., Simren, M., et al. (2016). Bowel disorders. Gastroenterology, 150, 1393–1407.

    Google Scholar 

  55. Mahieu, N. G., & Patti, G. J. (2017). Systems-level annotation of a metabolomics data set reduces 25,000 features to fewer than 1000 unique metabolites. Analytical Chemistry, 89, 10397–10406.

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Mailloux, R. J., Young, A., Chalker, J., Gardiner, D., O’Brien, M., Slade, L., et al. (2016). Choline and dimethylglycine produce superoxide/hydrogen peroxide from the electron transport chain in liver mitochondria. FEBS Letters, 590, 4318–4328.

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Marshall, J. K., Thabane, M., Borgaonkar, M. R., & James, C. (2007). Postinfectious irritable bowel syndrome after a food-borne outbreak of acute gastroenteritis attributed to a viral pathogen. Clinical Gastroenterology and Hepatology, 5, 457–460.

    PubMed  PubMed Central  Google Scholar 

  58. Massadeh, A. M., Gharaibeh, A. A., & Omari, K. W. (2009). A single-step extraction method for the determination of nicotine and cotinine in Jordanian smokers’ blood and urine samples by RP-HPLC and GC-MS. Journal of Chromatographic Science, 47, 170–177.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. McIntosh, K., Reed, D. E., Schneider, T., Dang, F., Keshteli, A. H., De Palma, G., et al. (2017). FODMAPs alter symptoms and the metabolome of patients with IBS: A randomised controlled trial. Gut, 66, 1241–1251.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Meleine, M., & Matricon, J. (2014). Gender-related differences in irritable bowel syndrome: Potential mechanisms of sex hormones. World Journal of Gastroenterology, 20, 6725–6743.

    PubMed  PubMed Central  Google Scholar 

  61. Monsbakken, K. W., Vandvik, P. O., & Farup, P. G. (2005). Perceived food intolerance in subjects with irritable bowel syndrome—Etiology, prevalence and consequences. European Journal of Clinical Nutrition, 60, 667–672.

    Google Scholar 

  62. Mortensen, J. H., Manon-Jensen, T., Jensen, M. D., Hagglund, P., Klinge, L. G., Kjeldsen, J., et al. (2017). Ulcreative colitis, Crohn’s disease and irratble bowel syndome have different profiles of extracellular matrix turnover, which also reflects disease activity in Crohn’s disease. PLoS ONE, 12, e0185855.

    PubMed  PubMed Central  Google Scholar 

  63. Nicholson, J. K., Connelly, J., Lindon, J. C., & Holmes, E. (2002). Metabonomics: A platform for studying drug toxicity and gene function. Nature Reviews Drug Discovery, 1, 153.

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Niddam, D. M., Tsai, S.-Y., Lu, C.-L., Ko, C.-W., & Hsieh, J.-C. (2011). Reduced hippocampal glutamate– glutamine levels in irritable bowel syndrome: Preliminary findings using magnetic resonance spectroscopy. American Journal of Gastroenterology, 106, 1503–1511.

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Nimni, M. E. (1983). Collagen: structure, function, and metabolism in normal and fibrotic tissues. Seminars in Arthritis Rheumatism, 13, 1–86.

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Nori de Macedo, A., Mathiaparanam, S., Brick, L., Keenan, K., Gonska, T., Pedder, L., et al. (2017). The sweat metabolome of screen-positive cystic fibrosis infants: Revealing mechanisms beyond impaired chloride transport. ACS Central Science, 3, 904–913.

    Google Scholar 

  67. Obrenovich, M. E., Tima, M. A., Polinkovsky, A., Zhang, R., Emancipator, S. N., & Donskey, C. J. (2017). A targeted metabolomics analysis identifies intestinal microbiota-derived urinary biomarkers of colonization resistance in antibiotic-treated mice. Antimicrobial Agents and Chemotherapy, 61, e00477–e00517.

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Peironcely, J. E., Reijmers, T., Coulier, L., Bender, A., & Hankemeier, T. (2011). Understanding and classifying metabolite space and metabolite-likeness. PLoS ONE, 6, e28966.

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Pero, R. W., Lund, H., & Leanderson, T. (2009). Antioxidant metabolism induced by quinic acid. Increased urinary excretion of tryptophan and nicotinamide. Phytotherapy Research, 23, 335–346.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Playdon, M. C., Sampson, J. N., Cross, A. J., Sinha, R., Guertin, K. A., Moy, K. A., et al. (2016). Comparing metabolite profiles of habitual diet in serum and urine. The American Journal of Clinical Nutrition, 104, 776–789.

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Qin, X. (2017). Damage of the mucus layer: The possible shared critical common cause for both inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS). Inflammatory Bowel Diseases, 23, E11–E12.

    PubMed  PubMed Central  Google Scholar 

  72. Quigley, E. M. M. (2016). Editorial: serotonin and irritable bowel syndrome—Reconciling pharmacological effects with basic biology. Alimentary Pharmacology & Therapeutics, 43, 644–646.

    CAS  Google Scholar 

  73. Rattray, N. J. W., Deziel, N. C., Wallach, J. D., Khan, S. A., Vasiliou, V., Ioannidis, J. P. A., et al. (2018). Beyond genomics: Understanding exposotypes through metabolomics. Human Genomics, 12, 4.

    PubMed  PubMed Central  Google Scholar 

  74. Reap, E. A., & Lawson, J. W. (1990). Stimulation of the immune response by dimethylglycine, a nontoxic metabolite. The Journal of Laboratory and Clinical Medicine, 115, 481–486.

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Rodríguez, L. A. G., & Ruigómez, A. (1999). Increased risk of irritable bowel syndrome after bacterial gastroenteritis: cohort study. British Medical Journal, 318, 565.

    PubMed  PubMed Central  Google Scholar 

  76. Rothwell, J. A., Fillâtre, Y., Martin, J.-F., Lyan, B., Pujos-Guillot, E., Fezeu, L., et al. (2014). New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects. PLoS ONE, 9, e93474.

    PubMed  PubMed Central  Google Scholar 

  77. Ruttkies, C., Schymanski, E. L., Wolf, S., Hollender, J., & Neumann, S. (2016). MetFrag relaunched: Incorporating strategies beyond in silico fragmentation. Journal of Cheminformatics, 8, 3.

    PubMed  PubMed Central  Google Scholar 

  78. Savolainen, E. R., Miettinen, T. A., Pikkarainen, P., Salaspuro, M. P., & Kivirikko, K. I. (1983). Enzymes of collagen synthesis and type III procollagen aminopropeptide in the evaluation of D-penicillamine and medroxyprogesterone treatments of primary biliary cirrhosis. Gut, 24, 136–142.

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Simrén, M., Barbara, G., Flint, H. J., Spiegel, B. M. R., Spiller, R. C., Vanner, S., et al. (2013). Intestinal microbiota in functional bowel disorders: A Rome foundation report. Gut, 62, 159–176.

    PubMed  PubMed Central  Google Scholar 

  80. Simren, M., Mansson, A., Langkilde, A. M., Svedlund, J., Abrahamsson, H., Bengtsson, U., et al. (2001). Food-related gastrointestinal symptoms in the irritable bowel syndrome. Digestion, 63, 108–115.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Sinagra, E., Pompei, G., Tomasello, G., Cappello, F., Moreale, G. C., Amvrosiadis, G., et al. (2017). Inflammation in irriatbale bowel syndrome: Myth or new treatment strategy? World Journal of Gastroenterology, 22, 2242–2255.

    Google Scholar 

  82. Slattery, S. A., Niaz, O., Aziz, Q., Ford, A. C., & Farmer, A. D. (2015). Systematic review with meta-analysis: The prevalence of bile acid malabsorption in the irritable bowel syndrome with diarrhoea. Alimentary Pharmacology & Therapeutics, 42, 3–11.

    CAS  Google Scholar 

  83. Snaith, R. P. (2003). The hospital anxiety and depression scale. Health Quality Life Outcomes, 1, 29.

    Google Scholar 

  84. Spiller, R. C., Jenkins, D., Thornley, J. P., Hebden, J. M., Wright, T., Skinner, M., et al. (2000). Increased rectal mucosal enteroendocrine cells, T lymphocytes, and increased gut permeability following acute Campylobacter enteritis and in post-dysenteric irritable bowel syndrome. Gut, 47, 804–811.

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Storey, J. D. (2003). The positive false discovery rate: A Bayesian interpretation and the q-value. The Annals of Statistics, 31, 2013–2035.

    Google Scholar 

  86. Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., et al. (2007). Proposed minimum reporting standards for chemical analysis. Metabolomics, 3, 211–221.

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Thijssen, A. Y., Mujagic, Z., Jonkers, D. M. A. E., Ludidi, S., Keszthelyi, D., Hesselink, M. A., et al. (2016). Alterations in serotonin metabolism in the irritable bowel syndrome. Alimentary Pharmacology & Therapeutics, 43, 272–282.

    CAS  Google Scholar 

  88. Törnblom, H., Lindberg, G., Nyberg, B., & Veress, B. (2002). Full-thickness biopsy of the jejunum reveals inflammation and enteric neuropathy in irritable bowel syndrome. Gastroenterology, 123, 1972–1979.

    PubMed  PubMed Central  Google Scholar 

  89. Viant, M. R., Kurland, I. J., Jones, M. R., & Dunn, W. B. (2017). How close are we to complete annotation of metabolomes? Current Opinion in Chemical Biology, 36, 64–69.

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Walsh, M. C., Brennan, L., Malthouse, J. P. G., Roche, H. M., & Gibney, M. J. (2006). Effect of acute dietary standardization on the urinary, plasma, and salivary metabolomic profiles of healthy humans. The American Journal of Clinical Nutrition, 84, 531–539.

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Want, E. J., Wilson, I. D., Gika, H., Theodoridis, G., Plumb, R. S., Shockcor, J., et al. (2010). Global metabolic profiling procedures for urine using UPLC-M. Nature Protocols, 5, 1005–1018.

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Wess, L., Eastwood, M. A., Wess, T. J., Busuttil, A., & Miller, A. (1995). Cross linking of collagen is increased in colonic diverticulosis. Gut, 37, 91–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  93. William, T. B. (1978). Structure and biosynthesis of connective tissue proteoglycans. In H. Martin (Ed.), The Glycoconjugates. New York: Academic Press Inc.

    Google Scholar 

  94. Yamamoto, H., & Sasaki, K. (2017). Metabolomics-based approach for ranking the candidate structures of unidentified peaks in capillary electrophoresis time-of-flight mass spectrometry. Electrophoresis, 38, 1053–1059.

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Yamamoto, M., Ly, R., Gill, B., Zhu, Y., Moran-Mirabal, J., & Britz-McKibbin, P. (2016). Robust and high-throughput method for anionic metabolite profiling: Preventing polyimide aminolysis and capillary breakages under alkaline conditions in capillary electrophoresis-mass spectrometry. Analytical Chemistry, 88, 10710–10719.

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Yamanuchi, M., & Sricholpech, M. (2012). Lysine in post-translational modification of collagen. Essays Biochemistry, 52, 113–133.

    Google Scholar 

  97. Yano, Jessica M., Yu, K., Donaldson, Gregory P., Shastri, Gauri G., Ann, P., Ma, L., et al. (2015). Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell, 161, 264–276.

    CAS  PubMed  PubMed Central  Google Scholar 

  98. Zheng, Y.-F., Yang, J., Zhao, X.-J., Feng, B., Kong, H.-W., Chen, Y.-J., et al. (2005). Urinary nucleosides as biological markers for patients with colorectal cancer. World Journal of Gastroenterology, 11, 3871–3876.

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Zhou, Q., Souba, W. W., Croce, C. M., & Verne, G. N. (2010). MicroRNA-29a regulates intestinal membrane permeability in patients with irritable bowel syndrome. Gut, 59, 775–784.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

P.B.M. acknowledges funding support from the Natural Sciences and Engineering Research Council of Canada, Genome Canada, and McMaster University. P.B. also acknowledges support of a Foundation Grant from the Canadian Institutes of Health Research. We also acknowledge kind support from David Arndt, Zachary Budinski and David S. Wishart at the University Alberta with their assistance in uploading MS/MS spectra for urinary metabolites onto HMDB (www.hmdb.ca) identified in this work.

Author information

Affiliations

Authors

Contributions

MY prepared and analyzed all urine samples and conducted data pre-processing and final statistical analysis under the supervision of PBM. MY also wrote the initial draft of the manuscript with final edits performed by PBM. MIP-S and PB designed the study, recruited participants, collected patient urine samples and also provided feedback on the manuscript.

Corresponding author

Correspondence to Philip Britz-McKibbin.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

This study was approved by the Hamilton Integrated Research Ethics Board at McMaster University (REB Project #3992).

Informed consent

Informed consent was obtained from all individual participants included in this study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yamamoto, M., Pinto-Sanchez, M.I., Bercik, P. et al. Metabolomics reveals elevated urinary excretion of collagen degradation and epithelial cell turnover products in irritable bowel syndrome patients. Metabolomics 15, 82 (2019). https://doi.org/10.1007/s11306-019-1543-0

Download citation

Keywords

  • Metabolomics
  • Irritable bowel syndrome
  • Urine
  • Biomarkers
  • Mechanisms