Метаболиты, ассоциированные с бронхиальной астмой у детей: систематический обзор

Обоснование. С развитием современных омиксных технологий возрос интерес к поиску в разных биологических материалах биомаркеров как нового диагностического инструмента в будущей неинвазивной диагностике бронхиальной астмы (БА), особенно тех, которые можно использовать в клинической практике. В связи с этим появилась потребность в систематизации данных об особенностях метаболических профилей у детей с БА и о выявлении биохимических реакций, связанных с патогенезом заболевания.
Цель исследования — обобщить результаты исследований метаболитов, определенных методом масс-спектрометрии и ассоциированных с БА у детей.
Методы. В обзор включали исследования с участием детей с БА в возрасте до 18 лет, у которых изучали метаболом (совокупность эндогенных метаболитов, образующихся в процессе обмена веществ в организме) в биологических образцах, полученных с использованием неинвазивных или малоинвазивных методов, с применением методов масс-спектрометрии. Поиск опубликованных работ выполнен в базах данных Medline и eLibrary. Период поиска — до августа 2025 г.
Результаты. Обнаружено 29 исследований, в которых анализировали метаболом в образцах конденсата выдыхаемого воздуха (13 исследований), сыворотки крови (11), мочи (5) и кала (1). Нецелевой анализ метаболитов выполнен в 18 исследованиях, целевой — в 11. В числе метаболитов изучали соединения, связанные с обменом липидов, белков и аминокислот, окислительным стрессом, соединения никотинамидного пути, летучие органические соединения, желчные кислоты, гемовые метаболиты.
Заключение. Выявлены многочисленные изменения молекулярного профиля у детей с БА. Многие из метаболитов при БА ассоциированы с воспалительными процессами.

1. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1204–1222. doi: https://doi.org/10.1016/S0140-6736(20)30925-9

2. 2023 GINA Main Report. In: Global Initiative for Asthma: Official website. Available online: https://ginasthma.org/2023-gina-mainreport. Accessed February 20, 2024.

3. Xu S, Panettieri RA, Jude J. Metabolomics in asthma: A platform for discovery. Mol Aspects Med. 2022;85:100990. doi: https://doi.org/10.1016/j.mam.2021.100990

4. Peel AM, Wilkinson M, Sinha A, et al. Volatile organic compounds associated with diagnosis and disease characteristics in asthma — A systematic review. Respir Med. 2020;169:105984. doi: https://doi.org/10.1016/j.rmed.2020.105984

5. Shahbazi Khamas S, Alizadeh Bahmani AH, Vijverberg SJH, et al. Exhaled volatile organic compounds associated with risk factors for obstructive pulmonary diseases: a systematic review. ERJ Open Res. 2023;9(4):00143–02023. doi: https://doi.org/10.1183/23120541.00143-2023

6. Papamichael MM, Katsardis C, Sarandi E, et al. Application of Metabolomics in Pediatric Asthma: Prediction, Diagnosis and Personalized Treatment. Metabolites. 2021;11(4):251. doi: https://doi.org/10.3390/metabo11040251

7. Amelink M, de Groot JC, de Nijs SB, et al. Severe adult-onset asthma: A distinct phenotype. J Allergy Clin Immunol. 2013;132(2):336–341. doi: https://doi.org/10.1016/j.jaci.2013.04.052

8. Ray A, Camiolo M, Fitzpatrick A, et al. Are We Meeting the Promise of Endotypes and Precision Medicine in Asthma? Physiol Rev. 2020;100(3):983–1017. doi: https://doi.org/10.1152/physrev.00023.2019

9. Kelly RS, Dahlin A, McGeachie MJ, et al. Asthma Metabolomics and the Potential for Integrative Omics in Research and the Clinic. Chest. 2017;151(2):262–277. doi: https://doi.org/10.1016/j.chest.2016.10.008

10. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372. doi: https://doi.org/10.1136/bmj.n71

11. Vandenbroucke J.P., von Elm E., Altman D.G. и др. Повышение качества отчетов о наблюдательных исследованиях в эпидемиологии (STROBE): разъяснения и уточнения // Вопросы современной педиатрии. — 2022. — Т. 21. — № 3. — С. 173–208. — doi: https://doi.org/10.15690/vsp.v21i3.2426

12. Montuschi P, Martello S, Felli M, et al. Liquid chromatography/ mass spectrometry analysis of exhaled leukotriene B4 in asthmatic children. Respir Res. 2005;6(1):119. doi: https://doi.org/10.1186/1465-9921-6-119

13. Glowacka E, Jedynak-Wasowicz U, Sanak M, Lis G. Exhaled eicosanoid profiles in children with atopic asthma and healthy controls. Pediatr Pulmonol. 2013;48(4):324–335. doi: https://doi.org/10.1002/ppul.22615

14. Sachs-Olsen C, Sanak M, Lang AM, et al. Eoxins: a new inflammatory pathway in childhood asthma. J Allergy Clin Immunol. 2010;126(4):859–867.e9. doi: https://doi.org/10.1016/j.jaci.2010.07.015

15. Carraro S, Giordano G, Piacentini G, et al. Asymmetric dimethylarginine in exhaled breath condensate and serum of children with asthma. Chest. 2013;144(2):405–410. doi: https://doi.org/10.1378/chest.12-2379

16. Hanusch B, Sinningen K, Brinkmann F, et al. Characterization of the L-Arginine/Nitric Oxide Pathway and Oxidative Stress in Pediatric Patients with Atopic Diseases. Int J Mol Sci. 2022;23(4):2136. doi: https://doi.org/10.3390/ijms23042136

17. Houssni L, Srdjan M, Tobias B, et al. Breath profiles in paediatric allergic asthma by proton transfer reaction mass spectrometry. BMJ Open Respir Res. 2025;12(1):e003223. doi: https://doi.org/10.1136/bmjresp-2025-003223

18. Caldeira M, Barros AS, Bilelo MJ, et al. Profiling allergic asthma volatile metabolic patterns using a headspace-solid phase microextraction/gas chromatography based methodology. J Chromatogr A. 2011;1218(24):3771–3780. doi: https://doi.org/10.1016/j.chroma.2011.04.026

19. Mattarucchi E, Baraldi E, Guillou C. Metabolomics applied to urine samples in childhood asthma; differentiation between asthma phenotypes and identification of relevant metabolites. Biomedical Chromatography. 2012;26(1):89–94. doi: https://doi.org/10.1002/bmc.1631

20. Crestani E, Harb H, Charbonnier LM, et al. Untargeted Metabolomic Profiling Identifies Disease-specific Signatures in Food Allergy and Asthma. J Allergy Clin Immunol. 2020;145(3):897–906. doi: https://doi.org/10.1016/j.jaci.2019.10.014

21. Rzetecka N, Matysiak J, Plewa S, et al. Biomarker Discovery in Childhood Asthma: A Pilot Study of Serum Metabolite Analysis for IgE-Dependent Allergy. Med Sci Monit. 2025;31:e948478. doi: https://doi.org/10.12659/MSM.948478

22. Baraldi E, Giordano G, Pasquale MF, et al. 3-Nitrotyrosine, a marker of nitrosative stress, is increased in breath condensate of allergic asthmatic children. Allergy. 2006;61(1):90–96. doi: https://doi.org/10.1111/j.1398-9995.2006.00996.x

23. Celio S, Troxler H, Durka SS, et al. Free 3-nitrotyrosine in exhaled breath condensates of children fails as a marker for oxidative stress in stable cystic fibrosis and asthma. Nitric Oxide. 2006;15(3): 226–232. doi: https://doi.org/10.1016/j.niox.2006.06.008

24. Carraro S, Cogo PE, Isak I, et al. EIA and GC/MS analysis of 8-isoprostane in EBC of children with problematic asthma. Eur Respir J. 2010;35(6):1364–1369. doi: https://doi.org/10.1183/09031936.00074909

25. Dallinga JW, Robroeks CMHHT, van Berkel JJBN, et al. Volatile organic compounds in exhaled breath as a diagnostic tool for asthma in children. Clin Exp Allergy. 2010;40(1):68–76. doi: https://doi.org/10.1111/j.1365-2222.2009.03343.x

26. Gahleitner F, Guallar-Hoyas C, Beardsmore CS, et al. Metabolomics pilot study to identify volatile organic compound markers of childhood asthma in exhaled breath. Bioanalysis. 2013;5(18):2239–2247. doi: https://doi.org/10.4155/bio.13.184

27. Gmachowska K, Podlecka D, Bonikowski R, et al. Exhaled volatile organic compounds (VOCs) for prediction of asthma exacerbation in children. Int J Occup Med Environ Health. 2024;37(3):351–359. doi: https://doi.org/10.13075/ijomeh.1896.02442

28. Li J, Li X, Liu X, et al. Untargeted metabolomic study of acute exacerbation of pediatric asthma via HPLC-Q-Orbitrap-MS. J Pharm Biomed Anal. 2022;215:114737. doi: https://doi.org/10.1016/j.jpba.2022.114737

29. Tao JL, Chen YZ, Dai QG, et al. Urine metabolic profiles in paediatric asthma. Respirology. 2019;24(6):572–581. doi: https://doi.org/10.1111/resp.13479

30. Matysiak J, Klupczynska A, Packi K, et al. Alterations in SerumFree Amino Acid Profiles in Childhood Asthma. Int J Environ Res Public Health. 2020;17(13):4758. doi: https://doi.org/10.3390/ijerph17134758

31. Kelly RS, Sordillo JE, Lasky-Su J, et al. Plasma Metabolite Profiles in Children with Current Asthma. Clin Exp Allergy. 2018;48(10): 1297–1304. doi: https://doi.org/10.1111/cea.13183

32. Caldeira M, Perestrelo R, Barros AS, et al. Allergic asthma exhaled breath metabolome: a challenge for comprehensive twodimensional gas chromatography. J Chromatogr A. 2012;1254: 87–97. doi: https://doi.org/10.1016/j.chroma.2012.07.023

33. Rago D, Pedersen CET, Huang M, et al. Characteristics and Mechanisms of a Sphingolipid-associated Childhood Asthma Endotype. Am J Respir Crit Care Med. 2021;203(7):853–863. doi: https://doi.org/10.1164/rccm.202008-3206OC

34. Chen Y, Checa A, Zhang P, et al. Sphingolipid classes and the interrelationship with pediatric asthma risk factors and clinical asthma phenotypes. Allergy. 2024;79(2):404–418. doi: https://doi.org/10.1111/all.15942

35. Hong X, Nadeau K, Wang G, et al. Metabolomic profiles during early childhood and risk of food allergies and asthma in multiethnic children from a prospective birth cohort. J Allergy Clin Immunol. 2024;154(1): 168–178. doi: https://doi.org/10.1016/j.jaci.2024.02.024

36. Lee-Sarwar K, Kelly RS, Lasky-Su J, et al. Dietary and Plasma Polyunsaturated Fatty Acids Are Inversely Associated with Asthma and Atopy in Early Childhood. J Allergy Clin Immunol Pract. 2019;7(2):529–538.e8. doi: https://doi.org/10.1016/j.jaip.2018.07.039

37. Zheng P, Bian X, Zhai Y, et al. Metabolomics reveals a correlation between hydroxyeicosatetraenoic acids and allergic asthma: Evidence from three years’ immunotherapy. Pediatr Allergy Immunol. 2021;32(8):1654–1662. doi: https://doi.org/10.1111/pai.13569

38. Carraro S, Bozzetto S, Giordano G, et al. Wheezing preschool children with early-onset asthma reveal a specific metabolomic profile. Pediatr Allergy Immunol. 2018;29(4):375–382. doi: https://doi.org/10.1111/pai.12879

39. Lee-Sarwar KA, Kelly RS, Lasky-Su J, et al. Integrative Analysis of the Intestinal Metabolome of Childhood Asthma. J Allergy Clin Immunol. 2019;144(2):442–454. doi: https://doi.org/10.1016/j.jaci.2019.02.032

40. Checkley W, Deza MP, Klawitter J, et al. Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches. Respir Med. 2016;121:59–66. doi: https://doi.org/10.1016/j.rmed.2016.10.011

41. Leff AR. Regulation of leukotrienes in the management of asthma: biology and clinical therapy. Annu Rev Med. 2001;52:1–14. doi: https://doi.org/10.1146/annurev.med.52.1.1

42. Kuruvilla ME, Lee FEH, Lee GB. Understanding Asthma Phenotypes, Endotypes, and Mechanisms of Disease. Clin Rev Allergy Immunol. 2019;56(2):219–233. doi: https://doi.org/10.1007/s12016-018-8712-1

43. Fajt ML, Gelhaus SL, Freeman B, et al. Prostaglandin D2 pathway upregulation: Relation to asthma severity, control, and TH2 inflammation. J Allergy Clin Immunol. 2013;131(6):1504–1512. doi: https://doi.org/10.1016/j.jaci.2013.01.035

44. Hannun YA, Obeid LM. Sphingolipids and their metabolism in physiology and disease. Nat Rev Mol Cell Biol. 2018;19(3): 175–191. doi: https://doi.org/10.1038/nrm.2017.107

45. Roviezzo F, D’Agostino B, Brancaleone V, et al. Systemic administration of sphingosine-1-phosphate increases bronchial hyperresponsiveness in the mouse. Am J Respir Cell Mol Biol. 2010;42(5):572–577. doi: https://doi.org/10.1165/rcmb.2009-0108OC

46. Orange JS, Ballow M, Stiehm ER, et al. Use and interpretation of diagnostic vaccination in primary immunodeficiency: a working group report of the Basic and Clinical Immunology Interest Section of the American Academy of Allergy, Asthma & Immunology. J Allergy Clin Immunol. 2012;130(3 Suppl):S1–S24. doi: https://doi.org/10.1016/j.jaci.2012.07.002

47. Ono JG, Kim BI, Zhao Y, et al. Decreased sphingolipid synthesis in children with 17q21 asthma-risk genotypes. J Clin Invest. 2020;130(2):921–926. doi: https://doi.org/10.1172/JCI130860

48. Miller M, Rosenthal P, Beppu A, et al. Oroscomucoid like protein 3 (ORMDL3) transgenic mice have reduced levels of sphingolipids including sphingosine-1-phosphate and ceramide. J Allergy Clin Immunol. 2017;139(4):1373–1376.e4. doi: https://doi.org/10.1016/j.jaci.2016.08.053

49. Ahmad T, Mabalirajan U, Ghosh B, Agrawal A. Altered asymmetric dimethyl arginine metabolism in allergically inflamed mouse lungs. Am J Respir Cell Mol Biol. 2010;42(1):3–8. doi: https://doi.org/10.1165/rcmb.2009-0137RC

50. Tajti G, Papp C, Kardos L, et al. Positive correlation of airway resistance and serum asymmetric dimethylarginine (ADMA) in bronchial asthma patients lacking evidence for systemic inflammation. Allergy Asthma Clin Immunol. 2018;14:2. doi: https://doi.org/10.1186/s13223-017-0226-5

51. Morris CR, Poljakovic M, Lavrisha L, et al. Decreased arginine bioavailability and increased serum arginase activity in asthma. Am J Respir Crit Care Med. 2004;170(2):148–153. doi: https://doi.org/10.1164/rccm.200309-1304OC

52. Neinast M, Murashige D, Arany Z. Branched Chain Amino Acids. Annu Rev Physiol. 2019;81:139–164. doi: https://doi.org/10.1146/annurev-physiol-020518-114455

53. Mishra V, Banga J, Silveyra P. Oxidative stress and cellular pathways of asthma and inflammation: Therapeutic strategies and pharmacological targets. Pharmacol Ther. 2018;181:169–182. doi: https://doi.org/10.1016/j.pharmthera.2017.08.011

54. Abalenikhina YV, Kosmachevskaya OV, Topunov AF. Peroxynitrite: Toxic Agent and Signaling Molecule (Review). Appl Biochem Microbiol. 2020;56(6):611–623. doi: https://doi.org/10.1134/S0003683820060022

55. Ahsan H. 3-Nitrotyrosine: A biomarker of nitrogen free radical species modified proteins in systemic autoimmunogenic conditions. Hum Immunol. 2013;74(10):1392–1399. doi: https://doi.org/10.1016/j.humimm.2013.06.009

56. Козина О.В., Огородова Л.М., Геренг Е.А. и др. Вклад токсических метаболитов оксида азота в формирование эозинофильного воспаления при бронхиальной астме // Пульмонология. — 2009. — № 4. — С. 69–73. — doi: https://doi.org/10.18093/0869-0189-2009-4-69-73

57. Yoshida Y, Umeno A, Shichiri M. Lipid peroxidation biomarkers for evaluating oxidative stress and assessing antioxidant capacity in vivo. J Clin Biochem Nutr. 2013;52(1):9–16. doi: https://doi.org/10.3164/jcbn.12-112

58. de Laurentiis G, Paris D, Melck D, et al. Metabonomic analysis of exhaled breath condensate in adults by nuclear magnetic resonance spectroscopy. Eur Respir J. 2008;32(5):1175–1183. doi: https://doi.org/10.1183/09031936.00072408

59. Saude EJ, Skappak CD, Regush S, et al. Metabolomic profiling of asthma: diagnostic utility of urine nuclear magnetic resonance spectroscopy. J Allergy Clin Immunol. 2011;127(3):757–764.e1–e6. doi: https://doi.org/10.1016/j.jaci.2010.12.1077

60. Carraro S, Rezzi S, Reniero F, et al. Metabolomics applied to exhaled breath condensate in childhood asthma. Am J Respir Crit Care Med. 2007;175(10):986–990. doi: https://doi.org/10.1164/rccm.200606-769OC

61. Sinha A, Krishnan V, Sethi T, et al. Metabolomic signatures in nuclear magnetic resonance spectra of exhaled breath condensate identify asthma. Eur Respir J. 2012;39(2):500–502. doi: https://doi.org/10.1183/09031936.00047711

62. Kang YP, Lee WJ, Hong JY, et al. Novel approach for analysis of bronchoalveolar lavage fluid (BALF) using HPLC-QTOF-MS-based lipidomics: lipid levels in asthmatics and corticosteroid-treated asthmatic patients. J Proteome Res. 2014;13(9):3919–3929. doi: https://doi.org/10.1021/pr5002059

63. Liang L, Hu M, Chen Y, et al. Metabolomics of bronchoalveolar lavage in children with persistent wheezing. Respir Res. 2022; 23(1):161. doi: https://doi.org/10.1186/s12931-022-02087-6

64. James RG, Reeves SR, Barrow KA, et al. Deficient Follistatinlike 3 Secretion by Asthmatic Airway Epithelium Impairs Fibroblast Regulation and Fibroblast-to-Myofibroblast Transition. Am J Respir Cell Mol Biol. 2018;59(1):104–113. doi: https://doi.org/10.1165/rcmb.2017-0025OC

65. Carraro S, Baraldi E, Giordano G, et al. Metabolomic Profile of Amniotic Fluid and Wheezing in the First Year of Life-A Healthy Birth Cohort Study. J Pediatr. 2018;196:264–269.e4. doi: https://doi.org/10.1016/j.jpeds.2018.01.012

66. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in metaanalyses. Eur J Epidemiol. 2010;25(9):603–605. doi: https://doi.org/10.1007/s10654-010-9491-z

67. Herzog R, lvarez-Pasquin MJ, D az C, et al. Are healthcare workers’ intentions to vaccinate related to their knowledge, beliefs and attitudes? A systematic review. BMC Public Health. 2013;13:154. doi: https://doi.org/10.1186/1471-2458-13-154

68. Nyamundanda G, Gormley IC, Fan Y, et al. MetSizeR: selecting the optimal sample size for metabolomic studies using an analysis based approach. BMC Bioinformatics. 2013;14(1):338. doi: https://doi.org/10.1186/1471-2105-14-338

69. Anwardeen NR, Diboun I, Mokrab Y, et al. Statistical methods and resources for biomarker discovery using metabolomics. BMC Bioinformatics. 2023;24(1):250. doi: https://doi.org/10.1186/s12859-023-05383-0

70. Turi KN, Romick-Rosendale L, Ryckman KK, Hartert TV. A review of metabolomics approaches and their application in identifying causal pathways of childhood asthma. J Allergy Clin Immunol. 2018;141(4): 1191–1201. doi: https://doi.org/10.1016/j.jaci.2017.04.021

71. Zhou J, Yin Y. Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry. Analyst. 2016;141(23):6362–6373. doi: https://doi.org/10.1039/c6an01753c

72. McGeachie MJ, Dahlin A, Qiu W, et al. The metabolomics of asthma control: a promising link between genetics and disease. Immun Inflamm Dis. 2015;3(3):224–238. doi: https://doi.org/10.1002/iid3.61