Humanities
Skip to main content Skip to main navigation menu Skip to site footer
  • Register
  • Login
  • Menu
  • Home
  • Current
  • Archives
  • Announcements
  • About
    • About the Journal
    • Submissions
    • Editorial Team
    • Privacy Statement
    • Contact
  • Register
  • Login

Journal of Education, Health and Sport

The importance of metabolomics in research into pathological processes leading to neurodegenerative diseases
  • Home
  • /
  • The importance of metabolomics in research into pathological processes leading to neurodegenerative diseases
  1. Home /
  2. Archives /
  3. Vol. 85 (2025) /
  4. Medical Sciences

The importance of metabolomics in research into pathological processes leading to neurodegenerative diseases

Authors

  • Katarzyna Wajda University of Rzeszów al. Tadeusza Rejtana 16C, 35-310 Rzeszów, Poland https://orcid.org/0009-0008-6631-8923
  • Wiktoria Mika Provincial Clinical Hospital No. 2 St. Jadwiga the Queen in Rzeszów, Poland https://orcid.org/0009-0007-6853-5342
  • Justyna Słowik Provincial Clinical Hospital No. 2 St. Jadwiga the Queen in Rzeszów, Poland https://orcid.org/0009-0006-9219-8377
  • Izabela Sieradzka Provincial Clinical Hospital No. 2 St. Jadwiga the Queen in Rzeszów, Poland https://orcid.org/0009-0004-3849-9844

DOI:

https://doi.org/10.12775/JEHS.2025.85.66541

Keywords

metabolomics, neurodegenerative diseases, Alzheimer's disease, Parkinson's disease, Huntington's disease, metabolic biomarkers

Abstract

Objective: The aim of this article is to review and analyse the current state of knowledge on the role of metabolomics in explaining the pathological processes underlying neurodegenerative diseases, in particular Alzheimer's, Parkinson's and Huntington's diseases. The analysis focuses on assessing the potential of this field in discovering early diagnostic biomarkers and identifying new therapeutic targets.

Materials and methods: A systematic review of the scientific literature was conducted using the PubMed, Scopus and Web of Science databases. The analysis included studies using mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy to profile metabolites in biological fluids (cerebrospinal fluid, plasma) and brain tissue from patients and preclinical models.

Results: Neurodegenerative diseases are characterised by common metabolic disorders, such as mitochondrial dysfunction, impaired energy metabolism and oxidative stress. Disease-specific signatures have also been identified: xanthine metabolism disorders and impaired kynurenine pathway in Parkinson's disease, dysregulation of lipid (including ceramide and sphingolipid) and glucose metabolism in Alzheimer's disease, and early changes in the tryptophan/kynurenine pathway in Huntington's disease.

Conclusions: This work highlights the role of metabolic dysregulation as an early mechanism in the pathogenesis of Alzheimer’s, Parkinson’s, and Huntington’s diseases. Metabolomics enables a systemic view of these disorders as disruptions of complex metabolic networks, providing a comprehensive picture of pathology rather than focusing on individual proteins. Its clinical potential includes the development of non-invasive biomarkers for early diagnosis and disease monitoring. Identification of key metabolic pathways, such as lipid and energy metabolism, also points to new therapeutic targets, forming the basis for precision medicine in neurodegenerative diseases.

References

Alzheimer's Association. (2023). 2023 Alzheimer's disease facts and figures. Alzheimer's & Dementia, 19(4), 1598–1695. ⁦https://doi.org/10.1002/alz.13016⁩

Anderson, N. D. (2019). State of the science on mild cognitive impairment (MCI). CNS Spectrums, 24(S1), 78–87. https://doi.org/10.1017/S1092852918001347

Ashton, N. J., Pascoal, T. A., Karikari, T. K., Vrillon, A., Preece, P., Lussier, F., Gonzalez-Escalada, G., Servaes, S., Weston, P., Gauthier, S., Rosa-Neto, P., Zetterberg, H., Blennow, K., & Schöll, M. (2021). A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease. Science Advances, 7(17), eabf6274. ⁦https://doi.org/10.1126/sciadv.aau7220⁩

Bassett, D. S., & Gazzaniga, M. S. (2011). Understanding complexity in the human brain. Trends in Cognitive Sciences, 15(5), 200–209. ⁦https://doi.org/10.1016/j.tics.2011.03.006⁩

Ben-Shlomo, Y., Darweesh, S., Llibre-Guerra, J., Marras, C., San Luciano, M., & Tanner, C. (2024). The epidemiology of Parkinson's disease. The Lancet, 403(10423), 283–292. ⁦https://doi.org/10.1016/S0140-6736(23)01419-8⁩

Bertram, L., Lill, C. M., & Tanzi, R. E. (2010). The genetics of Alzheimer's disease: Back to the future. Neuron, 68(2), 270–281. ⁦https://doi.orgorg/10.1016/j.neuron.2010.10.013⁩

Brown, M., Dunn, W. B., Dobson, P., Patel, Y., Winder, C. L., Francis-McIntyre, S., Begley, P., Carroll, K., Broadhurst, D., Tseng, A., Swainston, N., Spasic, I., Goodacre, R., & Kell, D. B. (2009). Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics. The Analyst, 134(7), 1322–1332. ⁦https://doi.org/10.1039/b901179j

Chen, P., & Geng, X. (2023). Research progress on the kynurenine pathway in the prevention and treatment of Parkinson's disease. Journal of enzyme inhibition and medicinal chemistry, 38(1), 2225800. https://doi.org/10.1080/14756366.2023.2225800

Chen, S. D., Li, H. Q., Cui, M., Dong, Q., & Yu, J. T. (2020). Pluripotent stem cells for neurodegenerative disease modeling: an expert view on their value to drug discovery. Expert Opinion on Drug Discovery, 15(9), 1081–1094. ⁦https://doi.org/10.1080/17460441.2020.1767579⁩

Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Small, G. W., Roses, A. D., Haines, J. L., & Pericak-Vance, M. A. (1993). Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science, 261(5123), 921–923. ⁦https://doi.org/10.1126/science.8346443⁩

Dong, Y., Song, X., Wang, X., Wang, S., & He, Z. (2024). The early diagnosis of Alzheimer's disease: Blood-based panel biomarker discovery by proteomics and metabolomics. CNS Neuroscience & Therapeutics, 30(11), e70060. ⁦https://doi.org/10.1111/cns.70060⁩

Fiehn, O. (2002). Metabolomics: The link between genotypes and phenotypes. Plant Molecular Biology, 48(1-2), 155–171. ⁦https://doi.org/10.1023/a:1013713905833⁩

Flores-Torres, M. H., Peng, X., Jeanfavre, S., Clish, C., Wang, Y., McCullough, M. L., Healy, B., Schwarzschild, M. A., Bjornevik, K., & Ascherio, A. (2025). Plasma metabolomics profiles in prodromal and clinical Parkinson's disease. Movement Disorders. Advance online publication. ⁦https://doi.org/10.1002/mds.30308⁩

Forsyth, D. (2018). Probability and statistics for computer science. Springer Publishing Company.

Geschwind, D. H., & Konopka, G. (2009). Neuroscience in the era of functional genomics and systems biology. Nature, 461(7266), 908–915. ⁦https://doi.org/10.1038/nature08537⁩

González-Guevara, E., Cárdenas, G., Pérez-Severiano, F., & Martínez-Lazcano, J. C. (2020). Dysregulated Brain Cholesterol Metabolism Is Linked to Neuroinflammation in Huntington's Disease. Movement disorders : official journal of the Movement Disorder Society, 35(7), 1113–1127. https://doi.org/10.1002/mds.28089

Graham, S. F., Kumar, P., Yilmaz, A., Tibshirani, M., O'Donnell, A., Cedazo-Minguez, A., & Björkhem, I. (2018). Targeted biochemical profiling of brain from Huntington's disease patients reveals novel metabolic pathways of interest. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, 1864(9, Part A), 2822–2830. ⁦https://doi.org/10.1016/j.bbadis.2018.04.012⁩

Jack, C. R., Jr., Bennett, D. A., Blennow, K., Carrillo, M. C., Dunn, B., Haeberlein, S. B., Holtzman, D. M., Jagust, W., Jessen, F., Karlawish, J., Liu, E., Molinuevo, J. L., Montine, T., Phelps, C., Rankin, K. P., Rowe, C. C., Scheltens, P., Siemers, E., Snyder, H. M., & Sperling, R. (2018). NIA-AA research framework: Toward a biological definition of Alzheimer's disease. Alzheimer's & Dementia, 14(4), 535–562. ⁦https://doi.org/10.1016/j.jalz.2018.02.018⁩

Jiménez, B., Mirnezami, R., Kinross, J., Cloarec, O., Keun, H. C., Holmes, E., Goldin, R. D., Ziprin, P., Darzi, A., & Nicholson, J. K. (2013). 1H HR-MAS NMR spectroscopy of tumor-induced local metabolic "field-effects" enables colorectal cancer staging and prognostication. Journal of Proteome Research, 12(2), 959–968. ⁦https://doi.org/10.1021/pr3010106⁩

Lawson, J. F. (2019). The impacts of plastic on Indonesian migratory birds. Department of Conservation.

Lichtman, J. W., Pfister, H., & Shavit, N. (2014). The big data challenges of connectomics. Nature Neuroscience, 17(11), 1448–1454. ⁦https://doi.org/10.1038/nn.3837⁩

Livingston, G., Huntley, J., Sommerlad, A., Ames, D., Ballard, C., Banerjee, S., Brayne, C., Corso, A., Gussekloo, J., J Jessen, F., Kivimäki, M., Larson, E. B., Mukadam, N., & an Brayne, C. (2020). Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. The Lancet, 396(10248), 413–446. ⁦https://doi.org/10.1016/S0140-6736(20)30367-6⁩

Long, J. M., & Holtzman, D. M. (2019). Alzheimer disease: An update on pathobiology and treatment strategies. Cell, 179(2), 312–339. ⁦https://doi.org/10.1016/j.cell.2019.09.001⁩

Matthews, K. A., Xu, W., Gaglioti, A. H., Holt, J. B., Keyserling, T. C., Hidden, S. L., & Pletcher, M. J. (2018). The global burden of neurological disorders: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology, 18(5), 459–480. ⁦https://doi.org/10.1016/S1474-4422(18)30499-X⁩

Morgan, S., & Orrell, R. W. (2016). Pathogenesis of amyotrophic lateral sclerosis. British Medical Bulletin, 119(1), 87–98. ⁦https://doi.org/10.1093/bmb/ldw026⁩

Nichols, E., & Vos, T. (2022). The global burden of dementia: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Public Health, 7(2), e105–e125.

Oliver, S. G., Winson, M. K., Kell, D. B., & Baganz, F. (1998). Systematic functional analysis of the yeast genome. Trends in Biotechnology, 16(9), 373–378. ⁦https://doi.org/10.1016/s0167-7799(98)01214-1⁩

Palmqvist, S., Tideman, P., Cullen, N., Zetterberg, H., Blennow, K., Dage, J. L., Stomrud, E., Janelidze, S., Mattsson-Carlgren, N., & Hansson, O. (2021). Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures. Nature Medicine, 27(6), 1034-1042. ⁦https://doi.org/10.1038/s41591-021-01348-z⁩

Przedborski, S., Vila, M., & Jackson-Lewis, V. (2003). Neurodegeneration: what is it and where are we? The Journal of Clinical Investigation, 111(1), 3–10. ⁦https://doi.org/10.1172/JCI17522⁩

Ramautar, R., Mayboroda, O. A., Somsen, G. W., & de Jong, G. J. (2011). CE-MS for metabolomics: Developments and applications in the period 2008-2010. Electrophoresis, 32(1), 52–65. ⁦https://doi.org/10.1002/elps.201000378⁩

Sadigh-Eteghad, S., Talebi, M., & Farhoudi, M. (2012). Association of metabolomics and Alzheimer's disease. Journal of the Neurological Sciences, 322(1-2), 86-92.

Saiki S, Hatano T, Fujimaki M, Ishikawa KI, Mori A, Oji Y, Okuzumi A, Fukuhara T, Koinuma T, Imamichi Y, et al. Decreased long-chain acylcarnitines from insufficient beta-oxidation as potential early diagnostic markers for Parkinson's disease. Sci Rep. 2017;7:7328. https://doi.org/10.1038/s41598-017-06767-y

Tang-Wai, D. F., Graff-Radford, N. R., Boeve, B. F., Dickson, D. W., Parisi, J. E., Crook, R., Caselli, R. J., Knopman, D. S., & Petersen, R. C. (2004). Clinical, genetic, and neuropathologic characteristics of posterior cortical atrophy. Neurology, 63(7), 1168–1174. ⁦https://doi.org/10.1212/01.wnl.0000140289.18472.15⁩

Tarawneh, R., & Holtzman, D. M. (2012). The clinical problem of symptomatic Alzheimer disease and mild cognitive impairment. Cold Spring Harbor Perspectives in Medicine, 2(5), a006148. ⁦https://doi.org/10.1101/cshperspect.a006148⁩

Tullo, S., Miranda, A. S., Del Cid-Pellitero, E., Lim, M. P., Gallino, D., Attaran, A., Patel, R., Novikov, V., Park, M., Beraldo, F. H., Luo, W., Shlaifer, I., Durcan, T. M., Bussey, T. J., Saksida, L. M., Fon, E. A., Prado, V. F., Prado, M. A. M., & Chakravarty, M. M. (2024). Neuroanatomical and cognitive biomarkers of alpha-synuclein propagation in a mouse model of synucleinopathy prior to onset of motor symptoms. Journal of Neurochemistry, 168(8), 1546–1564. ⁦https://doi.org/10.1111/jnc.15967⁩

Veres, G., Molnár, M., Zádori, D., Szentirmai, M., Szalárdy, L., Török, R., Fazekas, E., Ilisz, I., Vécsei, L., & Klivényi, P. (2015). Central nervous system-specific alterations in the tryptophan metabolism in the 3-nitropropionic acid model of Huntington's disease. Pharmacology, biochemistry, and behavior, 132, 115–124. https://doi.org/10.1016/j.pbb.2015.03.002

Vermunt, L., Sikkes, S. A. M., van den Hout, A., Handels, R., Bos, I., van der Flier, W. M., Kern, S., Ousset, P. J., Maruff, P., Skoog, I., Verhey, F. R. J., Freund-Levi, Y., Tsolaki, M., Wallin, A., & Visser, P. J. (2019). Duration of preclinical, prodromal, and dementia stages of Alzheimer's disease in relation to age, sex, and APOE genotype. Alzheimer's & Dementia, 15(7), 888–898. ⁦https://doi.org/10.1016/j.jalz.2019.04.001⁩

Villain, N., Planche, V., Lilamand, M., Cordonnier, C., Soto-Martin, M., Mollion, H., Bombois, S., Delrieu, J., & French Federation of Memory Clinics Work Group on Anti-Amyloid Immunotherapies. (2025). Lecanemab for early Alzheimer's disease: Appropriate use recommendations from the French federation of memory clinics. The Journal of Prevention of Alzheimer's Disease, 12(4), 100094. ⁦https://doi.org/10.1016/j.tjpad.2025.100094⁩

Villoslada, P., Steinman, L., & Baranzini, S. E. (2009). Systems biology and its application to the understanding of neurological diseases. Annals of Neurology, 65(2), 124–139. ⁦https://doi.org/10.1002/ana.21634⁩

Zacharias, H. U., Kaleta, C., Cossais, F., Schaeffer, E., Berndt, H., Best, L., Dost, T., Glüsing, S., Groussin, M., Poyet, M., Heinzel, S., Bang, C., Siebert, L., Demetrowitsch, T., Leypoldt, F., Adelung, R., Bartsch, T., Bosy-Westphal, A., Schwarz, K., & Berg, D. (2022). Microbiome and metabolome insights into the role of the gastrointestinal-brain axis in Parkinson's and Alzheimer's disease: Unveiling potential therapeutic targets. Metabolites, 12(12), 1222. ⁦https://doi.org/10.3390/metabo12121222⁩

Zampar, S., Di Gregorio, S. E., Grimmer, G., Watts, J. C., & Ingelsson, M. (2024). Prion-like seeding and propagation of oligomeric protein assemblies in neurodegenerative disorders. Frontiers in Neuroscience, 18, 1436262. ⁦https://doi.org/10.3389/fnins.2024.1436262⁩

Zheng, Q., & Wang, X. (2025). Alzheimer's disease: insights into pathology, molecular mechanisms, and therapy. Protein & Cell, 16(2), 83–120. ⁦https://doi.org/10.1093/procel/pwae026⁩

Zou, X., Zou, G., Zou, X., Wang, K., & Chen, Z. (2024). Gut microbiota and its metabolites in Alzheimer's disease: from pathogenesis to treatment. PeerJ, 12, e17061. https://doi.org/10.7717/peerj.17061

Books and monographs

Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. C., LaMantia, A. S., McNamara, J. O., & White, L. E. (Eds.). (2008). Neuroscience (4th ed.). Sinauer Associates.

Journal of Education, Health and Sport

Downloads

  • PDF

Published

2025-11-13

How to Cite

1.
WAJDA, Katarzyna, MIKA, Wiktoria, SŁOWIK, Justyna and SIERADZKA, Izabela. The importance of metabolomics in research into pathological processes leading to neurodegenerative diseases. Journal of Education, Health and Sport. Online. 13 November 2025. Vol. 85, p. 66541. [Accessed 27 December 2025]. DOI 10.12775/JEHS.2025.85.66541.
  • ISO 690
  • ACM
  • ACS
  • APA
  • ABNT
  • Chicago
  • Harvard
  • IEEE
  • MLA
  • Turabian
  • Vancouver
Download Citation
  • Endnote/Zotero/Mendeley (RIS)
  • BibTeX

Issue

Vol. 85 (2025)

Section

Medical Sciences

License

Copyright (c) 2025 Katarzyna Wajda, Wiktoria Mika, Justyna Słowik, Izabela Sieradzka

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The periodical offers access to content in the Open Access system under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0

Stats

Number of views and downloads: 100
Number of citations: 0

Search

Search

Browse

  • Browse Author Index
  • Issue archive

User

User

Current Issue

  • Atom logo
  • RSS2 logo
  • RSS1 logo

Information

  • For Readers
  • For Authors
  • For Librarians

Newsletter

Subscribe Unsubscribe

Tags

Search using one of provided tags:

metabolomics, neurodegenerative diseases, Alzheimer's disease, Parkinson's disease, Huntington's disease, metabolic biomarkers
Up

Akademicka Platforma Czasopism

Najlepsze czasopisma naukowe i akademickie w jednym miejscu

apcz.umk.pl

Partners

  • Akademia Ignatianum w Krakowie
  • Akademickie Towarzystwo Andragogiczne
  • Fundacja Copernicus na rzecz Rozwoju Badań Naukowych
  • Instytut Historii im. Tadeusza Manteuffla Polskiej Akademii Nauk
  • Instytut Kultur Śródziemnomorskich i Orientalnych PAN
  • Instytut Tomistyczny
  • Karmelitański Instytut Duchowości w Krakowie
  • Ministerstwo Kultury i Dziedzictwa Narodowego
  • Państwowa Akademia Nauk Stosowanych w Krośnie
  • Państwowa Akademia Nauk Stosowanych we Włocławku
  • Państwowa Wyższa Szkoła Zawodowa im. Stanisława Pigonia w Krośnie
  • Polska Fundacja Przemysłu Kosmicznego
  • Polskie Towarzystwo Ekonomiczne
  • Polskie Towarzystwo Ludoznawcze
  • Towarzystwo Miłośników Torunia
  • Towarzystwo Naukowe w Toruniu
  • Uniwersytet im. Adama Mickiewicza w Poznaniu
  • Uniwersytet Komisji Edukacji Narodowej w Krakowie
  • Uniwersytet Mikołaja Kopernika
  • Uniwersytet w Białymstoku
  • Uniwersytet Warszawski
  • Wojewódzka Biblioteka Publiczna - Książnica Kopernikańska
  • Wyższe Seminarium Duchowne w Pelplinie / Wydawnictwo Diecezjalne „Bernardinum" w Pelplinie

© 2021- Nicolaus Copernicus University Accessibility statement Shop