Proteomic Changes during Human Heat Stress and Heat Acclimation
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".