PreprintCited by 3Stress Responses and CortisolMetabolomics and Mass Spectrometry StudiesEmotion and Mood Recognition

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New Insights into Stress Metabolomics. Looking for new Diagnostic Biomarkers.

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Frempong, Gifty Animwaa, Goni, Guillermina, Lorenzo-Tejedor, Mónica, Cámara, Concepción de la, Lázaro, Jesús, Rasia, Eugenia Mangialavori, Aguiló, Jordi, Bailon, Raquel, Bernal, María Luisa·2025·Scientific Reports

Preprint — published as 10.1038/s41598-025-29572-4 · Paper page

Abstract

Stress is associated with the onset of various neurological disorders such as depression, PTSD, and anxiety. Despite the extensive research performed, metabolic changes triggered in response to acute psychological stress remain unclear. This study evaluates acute stress biomarkers and its adverse effects in university students through psychometric, biochemical, and metabolomic analyses, implementing Machine Learning on statistical models. In the study, forty participants were subject to relaxation and stress induction using autogenic training and a modified Trier Social Stress Test (TSST-M). Psychometric questionnaires confirmed the achievement of these states, while saliva and blood were sampled for biochemical analyses. Additionally, blood samples were applied to untargeted metabolomic approaches. The results reveal that although most biomarkers showed changes under stress state, the machine learning predictive model successfully identified salivary α-amylase and State-Trait Anxiety Inventory-state (STAI-s) as prominent stress markers. Additionally, several metabolic pathways, including steroid hormone biosynthesis, glycerophospholipid metabolism, linoleic acid metabolism, tyrosine metabolism, and aminoacyl-tRNA biosynthesis, were affected. Alterations of this sort, we conclude, allow us to gain further understanding into the adverse effects systematically associated with stress. In this way, our findings highlight the significant impact of acute mental stress on multiple metabolic pathways directly implicated in stress-related disorders.

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Metadata

Authors
Frempong, G. A., Goni, G., Lorenzo-Tejedor, M., Cámara, C. D. L., Lázaro, J., Rasia, E. M., Aguiló, J., Bailon, R., & Bernal, M. L.
Affiliations
  • Universidad de Zaragoza (ES)
  • University of Zaragoza
  • Aragon Institute of Health Research (IIS Aragon)
  • National Scientific and Technical Research Council
  • Universitat Autònoma de Barcelona (ES)
Venue
Scientific Reports
Published
2025-06-11
Volume
16
Issue
1
Pages
1567-1567
ISSN
2045-2322 (ISSN-L)
OpenAlex
W7119575705
Cited by
3
References
1
Citations by year
2026: 3
FWCI
13.66
Type
journal article
Language
en
Open access
Locations
  • Scientific Reports (publishedVersion, cc-by-nc-nd)
  • Research Square (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • Zaguan (Universidad de Zaragoza) (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Ministerio de Ciencia e Innovación (TED2021, TED2021-131106B-I00)
  • Gobierno de Aragón (T39_23R)
  • Universitat Politècnica de València
  • European Social Fund
Topics
  • Life Sciences › Neuroscience › Behavioral Neuroscience › Stress Responses and Cortisol
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Keywords
acute psychological stress, stress response, young adults, university students, salivary amylase, stress biomarkers, untargeted metabolomics, metabolic pathways, steroidogenesis, glycerophospholipid metabolism, linoleic acid metabolism, tyrosine metabolism, aminoacyl-tRNA biosynthesis, Trier Social Stress Test, stress-related disorders
MeSH terms
Machine Learning, Adolescent, Adult, Anxiety, Female, Humans, Male, Psychometrics, Saliva, Stress, Psychological, Biomarkers, Salivary alpha-Amylases, Metabolomics, Young Adult

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