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Systematic Review of Recent Lipidomics Approaches Toward Inflammatory Bowel Disease

  • Received : 2021.07.22
  • Accepted : 2021.08.18
  • Published : 2021.11.01

Abstract

Researchers have endeavored to identify the etiology of inflammatory bowel diseases, including Crohn's disease and ulcerative colitis. Though the pathogenesis of inflammatory bowel diseases remains unknown, dysregulation of the immune system in the host gastrointestinal tract is believed to be the major causative factor. Omics is a powerful methodological tool that can reveal biochemical information stored in clinical samples. Lipidomics is a subset of omics that explores the lipid classes associated with inflammation. One objective of the present systematic review was to facilitate the identification of biochemical targets for use in future lipidomic studies on inflammatory bowel diseases. The use of high-resolution mass spectrometry to observe alterations in global lipidomics might help elucidate the immunoregulatory mechanisms involved in inflammatory bowel diseases and discover novel biomarkers for them. Assessment of the characteristics of previous clinical trials on inflammatory bowel diseases could help researchers design and establish patient selection and analytical method criteria for future studies on these conditions. In this study, we curated literature exclusively from four databases and extracted lipidomics-related data from literature, considering criteria. This paper suggests that the lipidomics approach toward research in inflammatory bowel diseases can clarify their pathogenesis and identify clinically valuable biomarkers to predict and monitor their progression.

Keywords

Acknowledgement

This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (NRF-2018R1A5A2024425).

References

  1. Baumgart, D. C. and Carding, S. R. (2007) Inflammatory bowel disease: cause and immunobiology. Lancet 369, 1627-1640. https://doi.org/10.1016/S0140-6736(07)60750-8
  2. Baumgart, D. C. and Sandborn, W. J. (2007) Inflammatory bowel disease: clinical aspects and established and evolving therapies. Lancet 369, 1641-1657. https://doi.org/10.1016/S0140-6736(07)60751-X
  3. Bazarganipour, S., Hausmann, J., Oertel, S., El-Hindi, K., Brachtendorf, S., Blumenstein, I., Kubesch, A., Sprinzl, K., Birod, K., Hahnefeld, L., Trautmann, S., Thomas, D., Herrmann, E., Geisslinger, G., Schiffmann, S. and Grosch, S. (2019) The lipid status in patients with ulcerative colitis: sphingolipids are disease-dependent regulated. J. Clin. Med. 8, 971. https://doi.org/10.3390/jcm8070971
  4. Bene, J., Komlosi, K., Havasi, V., Talian, G., Gasztonyi, B., Horvath, K., Mozsik, G., Hunyady, B., Melegh, B. and Figler, M. (2006) Changes of plasma fasting carnitine ester profile in patients with ulcerative colitis. World J. Gastroenterol. 12, 110-113. https://doi.org/10.3748/wjg.v12.i1.110
  5. Bennike, T., Birkelund, S., Stensballe, A. and Andersen, V. (2014) Biomarkers in inflammatory bowel diseases: current status and proteomics identification strategies. World J. Gastroenterol. 20, 3231-3244. https://doi.org/10.3748/wjg.v20.i12.3231
  6. Braun, A., Treede, I., Gotthardt, D., Tietje, A., Zahn, A., Ruhwald, R., Schoenfeld, U., Welsch, T., Kienle, P., Erben, G., Lehmann, W. D., Fuellekrug, J., Stremmel, W. and Ehehalt, R. (2009) Alterations of phospholipid concentration and species composition of the intestinal mucus barrier in ulcerative colitis: a clue to pathogenesis. Inflamm. Bowel Dis. 15, 1705-1720. https://doi.org/10.1002/ibd.20993
  7. Bryan, P. F., Karla, C., Edgar Alejandro, M. T., Sara Elva, E. P., Gemma, F. and Luz, C. (2016) Sphingolipids as mediators in the crosstalk between microbiota and intestinal cells: implications for inflammatory bowel disease. Mediators Inflamm. 2016, 9890141. https://doi.org/10.1155/2016/9890141
  8. Cajka, T. and Fiehn, O. (2014) Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry. Trends Analyt. Chem. 61, 192-206. https://doi.org/10.1016/j.trac.2014.04.017
  9. Daniluk, U., Daniluk, J., Kucharski, R., Kowalczyk, T., Pietrowska, K., Samczuk, P., Filimoniuk, A., Kretowski, A., Lebensztejn, D. and Ciborowski, M. (2019) Untargeted metabolomics and inflammatory markers profiling in children with Crohn's disease and ulcerative colitis-a preliminary study. Inflamm. Bowel Dis. 25, 1120-1128. https://doi.org/10.1093/ibd/izy402
  10. Dennis, E. A. and Norris, P. C. (2015) Eicosanoid storm in infection and inflammation. Nat. Rev. Immunol. 11, 511-523. https://doi.org/10.1038/nri3859
  11. Diab, J., Hansen, T., Goll, R., Stenlund, H., Ahnlund, M., Jensen, E., Moritz, T., Florholmen, J. and Forsdahl, G. (2019) Lipidomics in ulcerative colitis reveal alteration in mucosal lipid composition associated with the disease state. Inflamm. Bowel Dis. 25, 1780-1787. https://doi.org/10.1093/ibd/izz098
  12. Duan, R. D. and Nilsson, A. (2009) Metabolism of sphingolipids in the gut and its relation to inflammation and cancer development. Prog. Lipid Res. 48, 62-72. https://doi.org/10.1016/j.plipres.2008.04.003
  13. Ehehalt, R., Wagenblast, J., Erben, G., Lehmann, W. D., Hinz, U., Merle, U. and Stremmel, W. (2004) Phosphatidylcholine and lysophosphatidylcholine in intestinal mucus of ulcerative colitis patients. A quantitative approach by nanoelectrospray-tandem mass spectrometry. Scand. J. Gastroenterol. 39, 737-742. https://doi.org/10.1080/00365520410006233
  14. Espaillat, M. P., Snider, A. J., Qiu, Z., Channer, B., Coant, N., Schuchman, E. H., Kew, R. R., Sheridan, B. S., Hannun, Y. A. and Obeid, L. M. (2018) Loss of acid ceramidase in myeloid cells suppresses intestinal neutrophil recruitment. FASEB J. 32, 2339-2353. https://doi.org/10.1096/fj.201700585r
  15. Ezri, J., Marques-Vidal, P. and Nydegger, A. (2012) Impact of disease and treatments on growth and puberty of pediatric patients with inflammatory bowel disease. Digestion 85, 308-319. https://doi.org/10.1159/000336766
  16. Fahy, E., Subramaniam, S., Murphy, R. C., Nishijima, M., Raetz, C. R. H., Shimizu, T., Spener, F., Van Meer, G., Wakelam, M. J. O. and Dennis, E. A. (2009) Update of the LIPID MAPS comprehensive classification system for lipids. J. Lipid Res. 50, S9-S14. https://doi.org/10.1194/jlr.R800095-JLR200
  17. Fan, F., Mundra, P. A., Fang, L., Galvin, A., Moore, X. L., Weir, J. M., Wong, G., White, D. A., Chin-Dusting, J., Sparrow, M. P., Meikle, P. J. and Dart, A. M. (2015) Lipidomic profiling in inflammatory bowel disease: comparison between ulcerative colitis and Crohn's disease. Inflamm. Bowel Dis. 21, 1511-1518. https://doi.org/10.1097/MIB.0000000000000394
  18. Furlan, A. D., Pennick, V., Bombardier, C. and Van Tulder, M. (2009) 2009 Updated method guidelines for systematic reviews in the cochrane back review group. Spine 34, 1929-1941. https://doi.org/10.1097/BRS.0b013e3181b1c99f
  19. Gallagher, K., Catesson, A., Griffin, J. L., Holmes, E. and Williams, H. R. T. (2021) Metabolomic analysis in inflammatory bowel disease: a systematic review. J. Crohns Colitis 15, 813-826. https://doi.org/10.1093/ecco-jcc/jjaa227
  20. Guan, S., Jia, B., Chao, K., Zhu, X., Tang, J., Li, M., Wu, L., Xing, L., Liu, K., Zhang, L., Wang, X., Gao, X. and Huang, M. (2020) UPLCQTOF-MS-based plasma lipidomic profiling reveals biomarkers for inflammatory bowel disease diagnosis. J. Proteome Res. 19, 600-609. https://doi.org/10.1021/acs.jproteome.9b00440
  21. Han, X. (2016) Lipidomics for studying metabolism. Nat. Rev. Endocrinol. 12, 668-679. https://doi.org/10.1038/nrendo.2016.98
  22. Horta, D., Moreno-Torres, M., Ramirez-Lazaro, M. J., Lario, S., Kuligowski, J., Sanjuan-Herraez, J. D., Quintas, G., Villoria, A. and Calvet, X. (2021) Analysis of the association between fatigue and the plasma lipidomic profile of inflammatory bowel disease patients. J. Proteome Res. 20, 381-392. https://doi.org/10.1021/acs.jproteome.0c00462
  23. Huan, T., Palermo, A., Ivanisevic, J., Rinehart, D., Edler, D., Phommavongsay, T., Benton, H. P., Guijas, C., Domingo-Almenara, X., Warth, B. and Siuzdak, G. (2018) Autonomous multimodal metabolomics data integration for comprehensive pathway analysis and systems biology. Anal. Chem. 90, 8396-8403. https://doi.org/10.1021/acs.analchem.8b00875
  24. Iwatani, S., Iijima, H., Otake, Y., Amano, T., Tani, M., Yoshihara, T., Tashiro, T., Tsujii, Y., Inoue, T., Hayashi, Y., Takeda, K., Hayashi, A., Fujita, S., Shinzaki, S. and Takehara, T. (2020) Novel mass spectrometry-based comprehensive lipidomic analysis of plasma from patients with inflammatory bowel disease. J. Gastroenterol. Hepatol. 35, 1355-1364. https://doi.org/10.1111/jgh.15067
  25. Jansson, J., Willing, B., Lucio, M., Fekete, A., Dicksved, J., Halfvarson, J., Tysk, C. and Schmitt-Kopplin, P. (2009) Metabolomics reveals metabolic biomarkers of Crohn's disease. PLoS ONE 4, e6386. https://doi.org/10.1371/journal.pone.0006386
  26. Lai, Y., Xue, J., Liu, C. W., Gao, B., Chi, L., Tu, P., Lu, K. and Ru, H. (2019) Serum metabolomics identifies altered bioenergetics, signaling cascades in parallel with exposome markers in Crohn's disease. Molecules 24, 449. https://doi.org/10.3390/molecules24030449
  27. Lee, Y., Choo, J., Kim, S. J., Heo, G., Pothoulakis, C., Kim, Y. H. and Im, E. (2017) Analysis of endogenous lipids during intestinal wound healing. PLoS ONE 12, e0183028. https://doi.org/10.1371/journal.pone.0183028
  28. Liebisch, G., Vizcaino, J. A., Kofeler, H., Trotzmuller, M., Griffiths, W. J., Schmitz, G., Spener, F. and Wakelam, M. J. O. (2013) Shorthand notation for lipid structures derived from mass spectrometry. J. Lipid Res. 54, 1523-1530. https://doi.org/10.1194/jlr.M033506
  29. Manfredi, M., Conte, E., Barberis, E., Buzzi, A., Robotti, E., Caneparo, V., Cecconi, D., Brandi, J., Vanni, E., Finocchiaro, M., Astegiano, M., Gariglio, M., Marengo, E. and De Andrea, M. (2019) Integrated serum proteins and fatty acids analysis for putative biomarker discovery in inflammatory bowel disease. J. Proteomics 195, 138-149. https://doi.org/10.1016/j.jprot.2018.10.017
  30. Martin, F. P., Ezri, J., Cominetti, O., Da Silva, L., Kussmann, M., Godin, J. P. and Nydegger, A. (2016) Urinary metabolic phenotyping reveals differences in the metabolic status of healthy and inflammatory bowel disease (IBD) children in relation to growth and disease activity. Int. J. Mol. Sci. 17, 1310. https://doi.org/10.3390/ijms17081310
  31. Masoodi, M., Pearl, D. S., Eiden, M., Shute, J. K., Brown, J. F., Calder, P. C. and Trebble, T. M. (2013) Altered colonic mucosal polyunsaturated fatty acid (PUFA) derived lipid mediators in ulcerative colitis: new insight into relationship with disease activity and pathophysiology. PLoS ONE 8, e76532. https://doi.org/10.1371/journal.pone.0076532
  32. McShane, L. M., Cavenagh, M. M., Lively, T. G., Eberhard, D. A., Bigbee, W. L., Williams, P. M., Mesirov, J. P., Polley, M. Y. C., Kim, K. Y., Tricoli, J. V., Taylor, J. M. G., Shuman, D. J., Simon, R. M., Doroshow, J. H. and Conley, B. A. (2013) Criteria for the use of omics-based predictors in clinical trials. 502, 317-320. https://doi.org/10.1038/nature12564
  33. Moher, D., Liberati, A., Tetzlaff, J. and Altman, D. G. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339, b2535. https://doi.org/10.1136/bmj.b2535
  34. Molodecky, N. A., Panaccione, R., Ghosh, S., Barkema, H. W. and Kaplan, G. G. (2011) Challenges associated with identifying the environmental determinants of the inflammatory bowel diseases. Inflamm. Bowel Dis. 17, 1792-1799. https://doi.org/10.1002/ibd.21511
  35. Murgia, A., Hinz, C., Liggi, S., Denes, J., Hall, Z., West, J., Santoru, M. L., Piras, C., Manis, C., Usai, P., Atzori, L., Griffin, J. L. and Caboni, P. (2018) Italian cohort of patients affected by inflammatory bowel disease is characterised by variation in glycerophospholipid, free fatty acids and amino acid levels. Metabolomics 14, 140. https://doi.org/10.1007/s11306-018-1439-4
  36. Ng, S. C., Shi, H. Y., Hamidi, N., Underwood, F. E., Tang, W., Benchimol, E. I., Panaccione, R., Ghosh, S., Wu, J. C. Y., Chan, F. K. L., Sung, J. J. Y. and Kaplan, G. G. (2017) Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies. Lancet 390, 2769-2778. https://doi.org/10.1016/S0140-6736(17)32448-0
  37. Pearl, D. S., Masoodi, M., Eiden, M., Brummer, J., Gullick, D., Mckeever, T. M., Whittaker, M. A., Nitch-Smith, H., Brown, J. F., Shute, J. K., Mills, G., Calder, P. C. and Trebble, T. M. (2014) Altered colonic mucosal availability of n-3 and n-6 polyunsaturated fatty acids in ulcerative colitis and the relationship to disease activity. J. Crohns Colitis 8, 70-79. https://doi.org/10.1016/j.crohns.2013.03.013
  38. Roberts, L. D., McCombie, G., Titman, C. M. and Griffin, J. L. (2008) A matter of fat: an introduction to lipidomic profiling methods. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 871, 174-181. https://doi.org/10.1016/j.jchromb.2008.04.002
  39. Sauer, C. G. and Kugathasan, S. (2009) Pediatric inflammatory bowel disease: highlighting pediatric differences in IBD. Gastroenterol. Clin. North Am. 38, 611-628. https://doi.org/10.1016/j.gtc.2009.07.010
  40. Schneider, H., Braun, A., Fullekrug, J., Stremmel, W. and Ehehalt, R. (2010) Lipid based therapy for ulcerative colitis-modulation of intestinal mucus membrane phospholipids as a tool to influence inflammation. Int. J. Mol. Sci. 11, 4149-4164. https://doi.org/10.3390/ijms11104149
  41. Scoville, E. A., Allaman, M. M., Brown, C. T., Motley, A. K., Horst, S. N., Williams, C. S., Koyama, T., Zhao, Z., Adams, D. W., Beaulieu, D. B., Schwartz, D. A., Wilson, K. T. and Coburn, L. A. (2018) Alterations in lipid, amino acid, and energy metabolism distinguish Crohn's disease from ulcerative colitis and control subjects by serum metabolomic profiling. Metabolomics 14, 17. https://doi.org/10.1007/s11306-017-1311-y
  42. Sewell, G. W., Hannun, Y. A., Han, X., Koster, G., Bielawski, J., Goss, V., Smith, P. J., Rahman, F. Z., Vega, R., Bloom, S. L., Walker, A. P., Postle, A. D. and Segal, A. W. (2012) Lipidomic profiling in Crohn's disease: abnormalities in phosphatidylinositols, with preservation of ceramide, phosphatidylcholine and phosphatidylserine composition. Int. J. Biochem. Cell Biol. 44, 1839-1846. https://doi.org/10.1016/j.biocel.2012.06.016
  43. Storr, M., Vogel, H. J. and Schicho, R. (2013) Metabolomics: is it useful for inflammatory bowel diseases? Curr. Opin. Gastroenterol. 29, 378-383. https://doi.org/10.1097/MOG.0b013e328361f488
  44. Tefas, C., Ciobanu, L., Tantau, M., Moraru, C. and Socaciu, C. (2020) The potential of metabolic and lipid profiling in inflammatory bowel diseases: a pilot study. Bosn. J. Basic Med. Sci. 20, 262-270.
  45. Titz, B., Gadaleta, R. M., Lo Sasso, G., Elamin, A., Ekroos, K., Ivanov, N. V., Peitsch, M. C. and Hoeng, J. (2018) Proteomics and lipidomics in inflammatory bowel disease research: from mechanistic insights to biomarker identification. Int. J. Mol. Sci. 19, 2775. https://doi.org/10.3390/ijms19092775
  46. Van Nuenen, M. H. M. C., Venema, K., Van Der Woude, J. C. J. and Kuipers, E. J. (2004) The metabolic activity of fecal microbiota from healthy individuals and patients with inflammatory bowel disease. Dig. Dis. Sci. 49, 485-491. https://doi.org/10.1023/B:DDAS.0000020508.64440.73
  47. Wang, R., Gu, X., Dai, W., Ye, J., Lu, F., Chai, Y., Fan, G., Gonzalez, F. J., Duan, G. and Qi, Y. (2016) A lipidomics investigation into the intervention of celastrol in experimental colitis. Mol. Biosyst. 12, 1436-1444. https://doi.org/10.1039/c5mb00864f
  48. Williams, H. R., Cox, I. J., Walker, D. G., Cobbold, J. F., Taylor-Robinson, S. D., Marshall, S. E. and Orchard, T. R. (2010) Differences in gut microbial metabolism are responsible for reduced hippurate synthesis in Crohn's disease. BMC Gastroenterol. 10, 108. https://doi.org/10.1186/1471-230X-10-108
  49. Zhang, C., Wang, K., Yang, L., Liu, R., Chu, Y., Qin, X., Yang, P. and Yu, H. (2018) Lipid metabolism in inflammation-related diseases. Analyst 143, 4526-4536. https://doi.org/10.1039/c8an01046c