Proteomic Changes during Human Heat Stress and Heat Acclimation
Notice bibliographique
Résumé
INTRODUCTION. To thrive in a warmer climate, humans will need to adapt physiologically. Improved thermoregulatory and cardiovascular responses during heat acclimation have been widely described. However, the cellular and molecular mechanisms mediating these improvements remain understudied in humans. The aim of this study was to perform a broad-spectrum, non-targeted proteomic analysis to determine how plasma protein levels change in response to moderate heat stress and heat acclimation. METHODS. Ten healthy adults (4F/6H, age: 25 ± 3 years) attended two laboratory visits performed before and after a 7-day heat acclimation protocol (hot water immersion, 60 min at a rectal temperature ≥38.5°C). During the visits, blood samples were drawn before and during passive heat stress (~1.5°C increase in esophageal temperature, water-perfused suit). Proteomic analyses were performed on 2938 plasma proteins using the Olink Explore 3072 assay. We quantified the number of proteins that changed by more than one log 2 (fold change) in concentration. RESULTS. Prior to acclimation, ~1% of the proteins (n=29) changed in concentration during heat stress. The change in concentration for 9 of these proteins reached the p value threshold. After acclimation, 54 proteins changed in concentration under a normothermic state. During subsequent heat stress, 175 proteins (~6%) increased in concentration and 19 (~0.6%) decreased. For 180 of these proteins, the change in concentration during heat stress was unique to the post-acclimation visit. The genes for proteins that changed in concentration during heat stress prior to acclimation are more highly expressed in brain (FGFBP3), arterial (TIMP4), skin (OBP2B), lung/salivary gland/esophageal (CXCL17) tissue. The genes for proteins that changed concentration in response to heat acclimation are highly expressed in skin (MMP7, CA6, KLK14) and brain tissue (DNER). The genes for proteins that only changed in concentration during heat stress post-acclimation are more highly expressed in brain (MOG, SMOC1, PTPRN2), and arterial (TNC, C1QTNF1, MATN2, NTF3, SMOC1) tissue. CONCLUSION. This untargeted and large-scale proteomic analysis identified novel plasma proteins that change in concentration during human heat stress and subsequent heat acclimation. The individual protein results can be utilized as external validation for other studies, as the basis of further data analysis explorations, and/or to guide targeted investigations of the biological responses and adaptations to heat exposure. Natural Sciences and Engineering Research Council of Canada. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».