Подписывайтесь на канал Ассоциации в MAX
Национальная ассоциация экспертов по коморбидной неврологии
Scientific and practical journal

COMORBIDITY NEUROLOGY

COMORBIDITY NEUROLOGY
|
ISSN 3034-185X (Print) ISSN 3033-7445 (Online)
The journal is a peer-reviewed scientific and practical publication
The journal was founded in 2023. Publication frequency: 4 issues per year
Registration number: PI No. FS 77-86353 dated 27.11.2023
Back
Original article
May 2025 №2 Том 2
DOI: https://doi.org/10.62505/3034-185x-2025-2-2-28-38
Download PDF
Comparison of the Metabolomic Profile of Cerebrospinal Fluid and Blood Plasma of Patients With Relapsing-Remitting Multiple Sclerosis

ABSTRACT

INTRODUCTION. Multiple sclerosis is a chronic demyelinating neurodegenerative disease of the central nervous system of autoimmune origin. Molecular processes associated with the onset and progression of multiple sclerosis, as well as its etiology, have not been sufficiently studied. The profile of final and intermediate metabolic products (metabolome) is a reflection of metabolic processes that can shed light on the pathophysiological basis of multiple sclerosis and improve the diagnostic and therapeutic aspects of clinical practice.

AIM. Evaluation of the profile of low-molecular metabolites of cerebrospinal fluid and blood plasma in patients with relapsing-remitting multiple sclerosis using liquid chromatography with mass spectrometric detection.

MATERIALS AND METHODS. The study included 16 patients suffering from various subtypes of multiple sclerosis. Blood plasma and cerebrospinal fluid were collected from the patients for metabolomic analysis.

RESULTS AND DISCUSSION. 24 metabolites were identified that allow reliable differentiation between the stages of relapsing-remitting multiple sclerosis. The metabolites combined into profiles reflect the predominant involvement of the proinflammatory link during exacerbation of relapsing-remitting multiple sclerosis, and the remyelination link during remission.

CONCLUSION. The obtained metabolite profiles indicate differences in the prevailing pathophysiological processes, and individual metabolites can be used as markers of the activity of the inflammatory process of multiple sclerosis.

KEYWORDS: multiple sclerosis, metabolomics, cerebrospinal fluid, biomarker, neuroinflammation, neurodegeneration

For citation: Markin D.S., Predtechenskaia E.V., Rogachev A.D., Gaisler E.V., Aleksandrova Zh.I. Comparison of the Metabolomic Profile of Cerebrospinal Fluid and Blood Plasma of Patients With Relapsing-Remitting Multiple Sclerosis. Comorbidity Neurology. 2025; 2 (2): 28-38. https://doi.org/10.62505/3034-185x-2025-2-2-28-38

*For correspondence: Elena V. Predtechenskaia, Dr. Sci. (Med.), professor, Department of Neurosciences, Novosibirsk State University, Novosibirsk, Russia, e-mail: elena_pred@mail.ru

REFERENCES

1.Socha E., Koba M., Kośliński P. Amino acid profiling as a method of discovering biomarkers for diagnosis of neurodegenerative diseases. Amino Acids. 2019 Mar; 51 (3): 367-371. https://doi.org/10.1007/s00726-019-02705-6

2.Adachi Y., Ono N., Imaizumi A. et al. Plasma amino acid profile in severely frail elderly patients in Japan. Int J Gerontol. 2018; 12: 290-293. https://doi.org/10.1016/j.ijge.2018.03.003

3.Corso G., Cristofano A., Sapere N. et al. Serum Amino Acid Profiles in Normal Subjects and in Patients with or at Risk of Alzheimer Dementia. Dement Geriatr Cogn Dis Extra. 2017 May 4; 7 (1): 143-159. https://doi.org/10.1159/000466688

4.Figura M., Kuśmierska K., Bucior E. et al. Serum amino acid profile in patients with Parkinson's disease. PLoS One. 2018 Jan 29;13 (1): e0191670. https://doi.org/10.1371/journal.pone.0191670

5.Liu Z., Waters J., Rui B. Metabolomics as a promising tool for improving understanding of multiple sclerosis: A review of recent advances. Biomed J. 2022 Aug; 45 (4): 594-606. https://doi.org/10.1016/j.bj.2022.01.004

6. Singh J., Cerghet M., Poisson L.M. et al. Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis. J Neuroimmune Pharmacol. 2019 Jun; 14 (2): 241-250. https://doi.org/10.1007/s11481-018-9815-4

7.Cicalini I., Rossi C., Pieragostino D., et al. Integrated Lipidomics and Metabolomics Analysis of Tears in Multiple Sclerosis: An Insight into Diagnostic Potential of Lacrimal Fluid. Int J Mol Sci. 2019 Mar 13; 20 (6): 1265. https://doi.org/10.3390/ijms20061265

8.Lozhkina N.G., Gushchina O.I., Basov N.V., et al. Ceramides As Potential New Predictors of the Severity of Acute Coronary Syndrome in Conjunction with SARS-CoV-2 Infection. Acta Naturae. 2024 Apr-Jun; 16 (2): 53-60. https://doi.org/10.32607/actanaturae.27400.

9.Jones L.L., McDonald D.A., Borum P.R. Acylcarnitines: role in brain. Prog Lipid Res. 2010 Jan; 49 (1): 61-75. https://doi.org/10.1016/j.plipres.2009.08.004

10.Židó M., Kačer D., Valeš K., et al. Metabolomics of Cerebrospinal Fluid in Multiple Sclerosis Compared With Healthy Controls: A Pilot Study. Front Neurol. 2022 May 26;13: 874121. https://doi.org/10.3389/fneur.2022.874121

11.Židó M., Kačer D., Valeš K., et al. Metabolomics of Cerebrospinal Fluid Amino and Fatty Acids in Early Stages of Multiple Sclerosis. Int J Mol Sci. 2023 Nov 13; 24 (22): 16271. https://doi.org/10.3390/ijms242216271

12.Kasakin M.F., Rogachev A.D., Predtechenskaya E.V., et al. Targeted metabolomics approach for identification of relapsing-remitting multiple sclerosis markers and evaluation of diagnostic models. Medchemcomm. 2019 Aug 12; 10 (10): 1803-1809. https://doi.org/10.1039/c9md00253g

13.Kasakin M.F., Rogachev A.D., Predtechenskaya E.V. et al. Changes in Amino Acid and Acylcarnitine Plasma Profiles for Distinguishing Patients with Multiple Sclerosis from Healthy Controls. Mult Scler Int. 2020 Jul 15: 9010937. https://doi.org/10.1155/2020/9010937

14.Romano A., Koczwara J.B., Gallelli C.A. et al. Fats for thoughts: An update on brain fatty acid metabolism. Int J Biochem Cell Biol. 2017 Mar; 84: 40-45. https://doi.org/10.1016/j.biocel.2016.12.015

15.Mansuy-Aubert V., Ravussin Y. Short chain fatty acids: the messengers from down below. Front Neurosci. 2023 Jul 6; 17: 1197759. https://doi.org/10.3389/fnins.2023.1197759

16.Yu H., Bai S., Hao Y., Guan Y. Fatty acids role in multiple sclerosis as «metabokines». J Neuroinflammation. 2022 Jun 17;19 (1): 157. https://doi.org/10.1186/s12974-022-02502-1

17.Gisevius B., Duscha A., Poschmann G., et al. Propionic acid promotes neurite recovery in damaged multiple sclerosis neurons. Brain Commun. 2024 Jun 3; 6 (3): fcae182.  https://doi.org/10.1093/braincomms/fcae182

18.Podbielska M., O'Keeffe J., Pokryszko-Dragan A. New Insights into Multiple Sclerosis Mechanisms: Lipids on the Track to Control Inflammation and Neurodegeneration. Int J Mol Sci. 2021 Jul 7; 22 (14): 7319. https://doi.org/10.3390/ijms22147319

19.Ladakis D.C., Pedrini E., Reyes-Mantilla M.I. et al. Metabolomics of Multiple Sclerosis Lesions Demonstrates Lipid Changes Linked to Alterations in Transcriptomics-Based Cellular Profiles. Neurol Neuroimmunol Neuroinflamm. 2024 May; 11 (3): e200219.  https://doi.org/10.1212/NXI.0000000000200219

20.Martin E., Aigrot M.S., Lamari F., Bachelin C., Lubetzki C., Nait Oumesmar B., Zalc B., Stankoff B. Teriflunomide Promotes Oligodendroglial 8,9-Unsaturated Sterol Accumulation and CNS Remyelination. Neurol Neuroimmunol Neuroinflamm. 2021 Oct 12; 8 (6): e1091. https://doi.org/10.1212/NXI.0000000000001091.

21.Stoessel D., Stellmann J.P., Willing A., et al. Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring. Front Hum Neurosci. 2018 Jun 4; 12: 226. https://doi.org/10.3389/fnhum.2018.00226

22.Lorefice L., Murgia F., Fenu G, et al. Assessing the Metabolomic Profile of Multiple Sclerosis Patients Treated with Interferon Beta 1a by 1H-NMR Spectroscopy. Neurotherapeutics. 2019 Jul; 16 (3): 797-807. https://doi.org/10.1007/s13311-019-00721-8

23.Cocco E., Murgia F., Lorefice L. et al. (1)H-NMR analysis provides a metabolomic profile of patients with multiple sclerosis. Neurol Neuroimmunol Neuroinflamm. 2015 Dec 24; 3(1): e185. https://doi.org/10.1212/NXI.0000000000000185

24.Nourbakhsh B., Bhargava P., Tremlett H., et al. Altered tryptophan metabolism is associated with pediatric multiple sclerosis risk and course. Ann Clin Transl Neurol. 2018 Sep 27; 5 (10): 1211-1221. https://doi.org/10.1002/acn3.637

25.Herman S., Åkerfeldt T., Spjuth O. et al. Biochemical Differences in Cerebrospinal Fluid between Secondary Progressive and Relapsing⁻Remitting Multiple Sclerosis. Cells. 2019 Jan 24; 8 (2): 84. https://doi.org/10.3390/cells8020084

26.Lim C.K., Bilgin A., Lovejoy D.B., et al. Kynurenine pathway metabolomics predicts and provides mechanistic insight into multiple sclerosis progression. Sci Rep. 2017 Feb 3; 7: 41473.  https://doi.org/10.1038/srep41473

27.Fitzgerald K.C., Smith M.D., Kim S., et al. Multi-omic evaluation of metabolic alterations in multiple sclerosis identifies shifts in aromatic amino acid metabolism. Cell Rep Med. 2021 Oct 19; 2 (10): 100424. https://doi.org/10.1016/j.xcrm.2021.100424

28.Ge A., Sun Y., Kiker T. et al. A metabolome-wide Mendelian randomization study prioritizes potential causal circulating metabolites for multiple sclerosis. J Neuroimmunol. 2023 Jun 15; 379: 578105. https://doi.org/10.1016/j.jneuroim.2023.578105

29.Ostojic S.M. Creatine and multiple sclerosis. Nutr Neurosci. 2022 May; 25 (5): 912-919.  https://doi.org/10.1080/1028415X.2020.1819108

30.Sylvestre D.A., Slupsky C.M., Aviv R.I. et al. Untargeted metabolomic analysis of plasma from relapsing-remitting multiple sclerosis patients reveals changes in metabolites associated with structural changes in brain. Brain Res. 2020 Apr 1; 1732: 146589. https://doi.org/10.1016/j.brainres.2019.146589

31.Noga M.J., Dane A., Shi S., et al. Metabolomics of cerebrospinal fluid reveals changes in the central nervous system metabolism in a rat model of multiple sclerosis. Metabolomics. 2012 Apr; 8 (2): 253-263. https://doi.org/10.1007/s11306-011-0306-3

32.Berezov T.T., Makletsova M.G., Fedorova T.N. Polyamines: their role in normal condition and in disorders of the central neural systems. Annals of Clinical and Experimental Neurology. 2012; 6 (2): 38-42. https://doi.org/10.17816/psaic271 (In Russ.)

33.Stevanovic I., Ninkovic M., Stojanovic I. et al. Beneficial effect of agmatine in the acute phase of experimental autoimmune encephalomyelitis in iNOS-/- knockout mice. Chem Biol Interact. 2013 Nov 25; 206 (2): 309-18. https://doi.org/10.1016/j.cbi.2013.09.006

 

 

ADDITIONAL INFORMATION

Denis S. Markin, student, Novosibirsk State University, Novosibirsk, Russia. E-mail: deeesik@gmail.com. ORCID: https://orcid.org/0009-0006-6845-1686

Elena V. Predtechenskaia, Dr. Sci. (Med.), Professor, Department of Neurosciences, Novosibirsk State University, Novosibirsk, Russia. E-mail: elena_pred@mail.ru. ORCID: https://orcid.org/0000-0003-3750-0634

Artem D. Rogachev, Ph.D. Sci. (Chem.), Senior Researcher, Vorozhtsov Novosibirsk Institute of Organic Chemistry of SB RAS; Novosibirsk State University, Novosibirsk, Russia. E-mail: artrogachev@yandex.ru. ORCID: https://orcid.org/0000-0002-3338-8529

Evgeny V. Gaisler, Ph.D. Sci. (Techn.), Senior Researcher, Novosibirsk State University, Novosibirsk, Russia. E-mail: evgeniy.gaysler@mail.ru. ORCID: https://orcid.org/0009-0005-4142-0129

Zhanel I. Aleksandrova, Neurologist, City Clinical Hospital of Emergency Medical Care No.2, Novosibirsk, Russia. E-mail: zhanel11.06@mail.ru

Author contributions. All authors confirm that their authorship complies with the international ICMJE criteria (all authors made a significant contribution to the development of the concept, the conduct of the study and the preparation of the article, read and approved the final version before publication). Special contributions:Predtechenskaia  E. V. , Rogachev A. D.  - conceptualization; Predtechenskaia E. V. ,  Rogachev A. D. , Gaisler  E. V.  - methodology; Rogachev A. D. , Gaisler   E. V. - software, formal analysis;  Predtechenskaia E. V. ,  Gaisler E. V. ,  Aleksandrova  Z. I.-  validation; Markin  D. S. , Rogachev A. D. , Aleksandrova   Z. I.- investigation; Markin  D. S. , Predtechenskaia E. V. ,  Aleksandrova   Z. I. - resources, writing — original draft; Predtechenskaia E. V. ,  Gaisler  E. V.  - data curation; Markin D. S. , Predtechenskaia E. V. , Rogachev A. D.   - writing — review & editing; Markin D. S. ,  Rogachev A. D. , Gaisler  E. V.   - visualization; Predtechenskaia  E. V.  - supervision,            funding acquisition; Predtechenskaia E. V. , Aleksandrova  Z. I. -  project administration

Funding. This study was not supported by any external sources of funding.

Disclosure. The authors declare no apparent or potential conflicts of interest related to the publication of this article.

Ethics Approval. The study was approved by the local ethics committee of the City Clinical Hospital of Emergency Medical Care No. 2 of Novosibirsk  ( Novosibirsk , Russia).

Informed consent for publication. All patients, and if it is impossible to review and sign, persons responsible for the patients (relatives, social workers, etc.) on behalf of the patients undergoing examination and participating in this study, signed informed consent.

 

 

The content is available under the Creative Commons Attribution 4.0 License.

©2025. Denis S. Markin, Elena V. Predtechenskaya, Artem D. Rogachev et al.