Metabolomics in systemic sclerosis.
Metabolome
Metabolomics
Systemic sclerosis
Journal
Rheumatology international
ISSN: 1437-160X
Titre abrégé: Rheumatol Int
Pays: Germany
ID NLM: 8206885
Informations de publication
Date de publication:
09 Jul 2024
09 Jul 2024
Historique:
received:
13
02
2024
accepted:
28
05
2024
medline:
10
7
2024
pubmed:
10
7
2024
entrez:
9
7
2024
Statut:
aheadofprint
Résumé
Systemic sclerosis is a rare autoimmune condition leading to incurable complications. Therefore fast and precise diagnosis is crucial to prevent patient death and to maintain quality of life. Unfortunately, currently known biomarkers do not meet this need. To address this problem researchers use diverse approaches to elucidate the underlying aberrations. One of the methods applied is metabolomics. This modern technique enables a comprehensive assessment of multiple compound concentrations simultaneously. As it has been gaining popularity, we found it necessary to summarize metabolomic studies presented so far in a narrative review. We found 11 appropriate articles. All of the researchers found significant differences between patients and control groups, whereas the reported findings were highly inconsistent. Additionally, we have found the investigated groups in most studies were scarcely described, and the inclusion/exclusion approach was diverse. Therefore, further study with meticulous patient assessment is necessary.
Identifiants
pubmed: 38981905
doi: 10.1007/s00296-024-05628-y
pii: 10.1007/s00296-024-05628-y
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
Références
Bergamasco A, Hartmann N, Wallace L, Verpillat P (2019) Epidemiology of systemic sclerosis and systemic sclerosis-associated interstitial lung disease. Clin Epidemiol 11:257–273. https://doi.org/10.2147/CLEP.S191418
doi: 10.2147/CLEP.S191418
pubmed: 31114386
pmcid: 6497473
Cutolo M, Soldano S, Smith V (2019) Pathophysiology of systemic sclerosis: current understanding and new insights. Expert Rev Clin Immunol 15(7):753–763. https://doi.org/10.1080/1744666X.2019.1614915
doi: 10.1080/1744666X.2019.1614915
pubmed: 31046487
Gwinutt JM, Wieczorek M, Balanescu A et al (2023) 2021 EULAR recommendations regarding lifestyle behaviours and work participation to prevent progression of rheumatic and musculoskeletal diseases. Ann Rheum Dis 82:48–56 https://doi.org/10.1136/annrheumdis-2021-222020
Gupta L, Ahmed S, Jain A, Misra R (2018) Emerging role of metabolomics in rheumatology. Int J Rheum 21:1468–1477. https://doi.org/10.1111/1756-185X.13353
doi: 10.1111/1756-185X.13353
Jacob M, Lopata AL, Dasouki M, Abdel Rahman AM (2019) Metabolomics toward personalized medicine. Mass Spectrom Rev 38:221–238 https://doi.org/10.1002/mas.21548
Wishart DS, Guo AC, Oler E et al (2022) HMDB 5.0: the human metabolome database for 2022. Nucleic Acids Res 50:D622–D631. https://doi.org/10.1093/nar/gkab1062
doi: 10.1093/nar/gkab1062
pubmed: 34986597
Fernández-Ochoa Á, Brunius C, Borrás-Linares I et al (2020) Metabolic disturbances in urinary and plasma samples from seven different systemic autoimmune diseases detected by HPLC-ESI-QTOF-MS. J Proteome Res 19(8):3220–3229. https://doi.org/10.1021/acs.jproteome.0c00179Dsd
doi: 10.1021/acs.jproteome.0c00179Dsd
pubmed: 32460496
Bengtsson AA, Trygg J, Wuttge DM et al (2016) Metabolic profiling of systemic lupus erythematosus and comparison with primary Sjögren’s syndrome and systemic sclerosis. PLoS ONE 11(7):e0159384. https://doi.org/10.1371/journal.pone.0159384
doi: 10.1371/journal.pone.0159384
pubmed: 27441838
pmcid: 4956266
Guo M, Liu D, Jiang Y et al (2023) Serum metabolomic profiling reveals potential biomarkers in systemic sclerosis. Metabolism 144:155587 https://doi.org/10.1016/j.metabol.2023.155587
Meier C, Freiburghaus K, Bovet C et al (2020) Serum metabolites as biomarkers in systemic sclerosis-associated interstitial lung disease. Sci Rep 14;10(1):21912 https: https://doi.org/10.1038/s41598-020-78951-6
Sun C, Zhu H, Wang Y et al (2023) Serum metabolite differences detected by HILIC UHPLC-Q-TOF MS in systemic sclerosis. Clin Rheumatol 42:125–134. https://doi.org/10.1007/s10067-022-06372-z
doi: 10.1007/s10067-022-06372-z
pubmed: 36127550
Bellocchi C, Fernández-Ochoa Á, Montanelli G et al (2018) Microbial and metabolic multi-omic correlations in systemic sclerosis patients. Ann N Y Acad Sci 1421:97–109. https://doi.org/10.1111/nyas.13736
doi: 10.1111/nyas.13736
pubmed: 29749635
Bögl T, Mlynek F, Himmelsbach M et al (2022) Plasma metabolomic profiling reveals four possibly disrupted mechanisms in systemic sclerosis. Biomedicines 10(3):607. https://doi.org/10.3390/biomedicines10030607
doi: 10.3390/biomedicines10030607
pubmed: 35327409
pmcid: 8945346
Ottria A, Hoekstra AT, Zimmermann M et al (2020) Fatty acid and carnitine metabolism are dysregulated in systemic sclerosis patients. Front Immunol 11:822. https://doi.org/10.3389/fimmu.2020.00822
doi: 10.3389/fimmu.2020.00822
pubmed: 32528464
pmcid: 7256194
Fernández-Ochoa Á, Quirantes-Piné R, Borrás-Linares I et al (2019) Urinary and plasma metabolite differences detected by HPLC-ESI-QTOF-MS in systemic sclerosis patients. J Pharm Biomed Anal 162:82–90. https://doi.org/10.1016/j.jpba.2018.09.021
doi: 10.1016/j.jpba.2018.09.021
pubmed: 30227356
Murgia F, Svegliati S, Poddighe S et al (2018) Metabolomic profile of systemic sclerosis patients. Sci Rep 8(1):7627. https://doi.org/10.1038/s41598-018-25992-7
doi: 10.1038/s41598-018-25992-7
Smolenska Z, Zabielska-Kaczorowska M, Wojteczek A, Kutryb-Zajac B, Zdrojewski Z (2020) Metabolic Pattern of Systemic Sclerosis: Association of Changes in Plasma Concentrations of Amino Acid-Related Compounds With Disease Presentation. Front Mol Biosci 7:585161 https://doi.org/10.3389/fmolb.2020.585161
Alotabi M, Shao J, Pauciulo MW et al (2023) Metabolomic profiles differentiate Scleroderma-PAH from idiopathic PAH and correspond with worsened functional capacity. Chest 163(1):204–215. https://doi.org/10.1016/j.chest.2022.08.2230
doi: 10.1016/j.chest.2022.08.2230
Deidda M, Piras C, Cadeddu Dessalvi C et al (2017) Distinctive metabolomic fingerprint in scleroderma patients with pulmonary arterial hypertension. Int J Cardiol 241:401–406. https://doi.org/10.1016/j.ijcard.2017.04.024
doi: 10.1016/j.ijcard.2017.04.024
pubmed: 28476520
Simpson CE, Ambade AS, Harlan R et al (2023) Kynurenine pathway metabolism evolves with development of preclinical and scleroderma-associated pulmonary arterial hypertension. Am J Physiol Lung Cell Mol Physiol 325(5):L617–L627. https://doi.org/10.1152/ajplung.00177.2023
doi: 10.1152/ajplung.00177.2023
pubmed: 37786941
Du Q, Wang X, Chen J et al (2023) Urine and serum metabolic profiling combined with machine learning for autoimmune disease discrimination and classification. Chem Commun (camb) 59(65):9852–9855. https://doi.org/10.1039/d3an01051a
doi: 10.1039/d3an01051a
pubmed: 37490058
Du Q, Wang X, Chen J al (2023) Machine learning encodes urine and serum metabolic patterns for autoimmune disease discrimination, classification and metabolic dysregulation analysis. Analyst 148(18):4318–4330. https://doi.org/10.1039/d3cc01861j
doi: 10.1039/d3cc01861j
pubmed: 37547947
Park J, Kim M, Kang SG, Jannasch AH, Cooper B, Petterson J, Kim CH (2015) Short-chain fatty acids induce both effector and regulatory T cells by suppression of histone deacetylases and regulation of the mTOR-S6K pathway. Mucosal Immunol 8:80–93. https://doi.org/10.1038/mi.2014.44
doi: 10.1038/mi.2014.44
pubmed: 24917457
Cucchi D, Camacho-Muñoz D, Certo M, Pucino V, Nicolaou A, Mauro C (2019) Fatty acids - from energy substrates to key regulators of cell survival, proliferation and effector function. Cell Stress 4(1):9–23. https://doi.org/10.15698/cst2020.01.209
doi: 10.15698/cst2020.01.209
pubmed: 31922096
pmcid: 6946016
Cleophas MCP, Ratter JM, Bekkering S, Quintin J, Schraa K, Stroes E, Netea M, Joosten LAB (2019) Effects of oral butyrate supplementation on inflammatory potential of circulating peripheral blood mononuclear cells in healthy and obese males. Sci Rep 9(1):775. https://doi.org/10.1038/s41598-018-37246-7
doi: 10.1038/s41598-018-37246-7
pubmed: 30692581
pmcid: 6349871
Haghikia A, Jörg S, Duscha A et al (2015) Dietary fatty acids directly Impact Central Nervous System Autoimmunity via the small intestine. Immunity 43(4):817–829. https://doi.org/10.1038/S41598-018-37246-7
doi: 10.1038/S41598-018-37246-7
pubmed: 26488817
Russo E, Bellando-Randone S, Carboni D et al (2024) The differential crosstalk of the skin-gut microbiome axis as a new emerging actor in systemic sclerosis. Rheumatology (Oxford) 63(1):226–234. https://doi.org/10.1093/RHEUMATOLOGY/KEAD208
doi: 10.1093/RHEUMATOLOGY/KEAD208
pubmed: 37154625
Ji X, Wu L, Marion T, Luo Y (2023) Lipid metabolism in regulation of B cell development and autoimmunity. Cytokine Growth Factor Rev 73:40–51. https://doi.org/10.1016/j.cytogfr.2023.06.008
doi: 10.1016/j.cytogfr.2023.06.008
pubmed: 37419766
Gogulska Z, Smolenska Z, Turyn J, Mika A, Zdrojewski Z (2021) Lipid alterations in systemic sclerosis. Front Mol Biosc 8:761721. https://doi.org/10.3389/fmolb.2021.761721
doi: 10.3389/fmolb.2021.761721
Kowal-Bielecka O, Fransen J, Avouac J et al (2017) Update of EULAR recommendations for the treatment of systemic sclerosis. Ann Rheum 76:1327–1339. https://doi.org/10.1136/annrheumdis-2016-209909
doi: 10.1136/annrheumdis-2016-209909
Petan T, Manček-Keber M (2022) Half is enough: oxidized lysophospholipids as novel bioactive molecules. Free Radic Biol Med 188:351–362. https://doi.org/10.1016/j.freeradbiomed.2022.06.228
doi: 10.1016/j.freeradbiomed.2022.06.228
pubmed: 35779690
Perrin-Cocon L, Diaz O, André P, Lotteau (2013) Modified lipoproteins provide lipids that modulate dendritic cell immune function. Biochimie 95:103–108. https://doi.org/10.1016/j.biochi.2012.08.006
doi: 10.1016/j.biochi.2012.08.006
pubmed: 22959067
García-Martín A, Garrido-Rodríguez M, Navarrete C (2019) Cannabinoid derivatives acting as dual PPARγ/CB2 agonists as therapeutic agents for systemic sclerosis. Niochem Pharmacol 163:321–334. https://doi.org/10.1016/j.bcp.2019.02.029
doi: 10.1016/j.bcp.2019.02.029
Shea BS, Tager AM (2012) Sphingolipid regulation of tissue fibrosis. Open Rheumatol J 6:123. https://doi.org/10.2174/1874312901206010123
doi: 10.2174/1874312901206010123
pubmed: 22802910
pmcid: 3395890
Cartier A, Hla T (21019) Sphingosine 1-phosphate: lipid signaling in pathology and therapy. Science 366(6463):eaar5551. https://doi.org/10.1126/SCIENCE.AAR5551
Badawy AAB (2022) Tryptophan metabolism and disposition in cancer biology and immunotherapy. Biosci Rep 42:BSR20221682. https://doi.org/10.1042/BSR20221682
doi: 10.1042/BSR20221682
pubmed: 36286592
pmcid: 9653095
Ramprasath T, Han YM, Zhang D, Yu CJ, Zou MH (2021) Tryptophan catabolism and inflammation: a Novel Therapeutic Target for aortic diseases. Front Immunol 12:731701. https://doi.org/10.3389/FIMMU.2021.731701
doi: 10.3389/FIMMU.2021.731701
pubmed: 34630411
pmcid: 8496902
Perl A, Hanczko R, Lai ZW et al (2015) Comprehensive metabolome analyses reveal N-acetylcysteine-responsive accumulation of kynurenine in systemic lupus erythematosus: implications for activation of the mechanistic target of rapamycin. Metabolomics 11:1157. https://doi.org/10.1007/s11306-015-0772-0
doi: 10.1007/s11306-015-0772-0
pubmed: 26366134
pmcid: 4559110
Piranavan P, Bhamra M, Perl A (2020) Metabolic targets for treatment of Autoimmune diseases. Immunometabolism 2(2):e200012. https://doi.org/10.20900/IMMUNOMETAB20200012
doi: 10.20900/IMMUNOMETAB20200012
pubmed: 32341806
pmcid: 7184931
Mehta BK, Espinoza ME, Hinchcliff M, Whitfield ML (2020) Molecular omic signatures in systemic sclerosis. EUR J Rheumatol 7(Suppl 3):S173–S180. https://doi.org/10.5152/eurjrheum.2020.19192
doi: 10.5152/eurjrheum.2020.19192
pubmed: 33164732
pmcid: 7647683
Modified from http://www.prisma-statement.org/PRISMAStatement/FlowDiagram , Accessed 24 February 2024