# Metabolomics Signatures of a Respiratory Tract Infection During an Altitude Training Camp in Elite Rowers

**Authors:** Félix Boudry, Fabienne Durand, Corentine Goossens

PMC · DOI: 10.3390/metabo15060408 · Metabolites · 2025-06-17

## TL;DR

This study uses metabolomics to detect respiratory infections in elite rowers during altitude training, identifying unique metabolic signatures that could help monitor and manage athlete health.

## Contribution

The study introduces a metabolomics-based approach to distinguish respiratory illness from altitude training effects in athletes.

## Key findings

- Respiratory illness was associated with specific metabolites like kynurenine and tryptophan.
- Altitude training was linked to metabolites such as creatine and citrate.
- Metabolomics can differentiate between illness and training-induced metabolic changes.

## Abstract

Background: Respiratory pathologies, such as COVID-19 and bronchitis, pose significant challenges for high-level athletes, particularly during demanding altitude training camps. Metabolomics offers a promising approach for early detection of such pathologies, potentially minimizing their impact on performance. This study investigates the metabolic differences between athletes with and without respiratory illnesses during an altitude training camp using urine samples and multivariate analysis. Methods: Twenty-seven elite rowers (15 males, 12 females) participated in a 12-day altitude training camp at 1850 m. Urine samples were collected daily, with nine athletes developing respiratory pathologies (8 COVID-19, 1 bronchitis). Nuclear Magnetic Resonance spectroscopy was used to analyze the samples, followed by data processing with Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), allowing to use Variable Importance in Projection (VIP) scores to identify key metabolites contributing to group separation. Results: The PLS-DA model for respiratory illness showed good performance (R2 = 0.89, Q2 = 0.35, p < 0.05). Models for altitude training achieved higher predictive power (Q2 = 0.51 and 0.72, respectively). Metabolites kynurenine, N-methylnicotinamide, pyroglutamate, propionate, N-formyltryptophan, tryptophan and glucose were significantly highlighted in case of respiratory illness while trigonelline, 3-hydroxyphenylacetate, glutamate, creatine, citrate, urea, o-hydroxyhippurate, creatinine, hippurate and alanine were correlated to effort in altitude. This distinction confirms that respiratory illness induces a unique metabolic profile, clearly separable from hypoxia and training-induced adaptations. Conclusions: This study highlights the utility of metabolomics in identifying biomarkers of respiratory pathologies in athletes during altitude training, offering the potential for improved monitoring and intervention strategies. These findings could enhance athlete health management, reducing the impact of illness on performance during critical training periods. Further research with larger cohorts is warranted to confirm these results and explore targeted interventions.

## Linked entities

- **Chemicals:** kynurenine (PubChem CID 846), N-methylnicotinamide (PubChem CID 457), pyroglutamate (PubChem CID 7405), propionate (PubChem CID 104745), N-formyltryptophan (PubChem CID 152933), tryptophan (PubChem CID 1148), glucose (PubChem CID 5793), trigonelline (PubChem CID 5570), 3-hydroxyphenylacetate (PubChem CID 5055), glutamate (PubChem CID 611), creatine (PubChem CID 586), citrate (PubChem CID 31348), urea (PubChem CID 1176), o-hydroxyhippurate (PubChem CID 10253), creatinine (PubChem CID 588), hippurate (PubChem CID 464), alanine (PubChem CID 239)
- **Diseases:** COVID-19 (MONDO:0100096), bronchitis (MONDO:0003781)

## Full-text entities

- **Diseases:** Respiratory Tract Infection (MESH:D012141), respiratory illness (MESH:D012140), COVID-19 (MESH:D000086382), bronchitis (MESH:D001991), hypoxia (MESH:D000860)
- **Chemicals:** propionate (MESH:D011422), alanine (MESH:D000409), N (MESH:D009584), trigonelline (MESH:C009560), kynurenine (MESH:D007737), creatine (MESH:D003401), urea (MESH:D014508), -formyltryptophan (-), creatinine (MESH:D003404), glucose (MESH:D005947), citrate (MESH:D019343), pyroglutamate (MESH:D011761), glutamate (MESH:D018698), tryptophan (MESH:D014364), hippurate (MESH:C030514), 3-hydroxyphenylacetate (MESH:C026245)

## Full text

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## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12195379/full.md

## References

54 references — full list in the complete paper: https://tomesphere.com/paper/PMC12195379/full.md

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Source: https://tomesphere.com/paper/PMC12195379