Metabolic consequences of non-severe burn injury are associated with increased plasma markers of inflammation and cardiovascular disease risk.

Ryan, M. J.; Raby, E.; Masuda, R.; Lodge, S.; Nitschke, P.; Maker, G. L.; Wist, J.; Holmes, E.; Whiley, L.; Wood, F. M.; Nicholson, J. K.; Fear, M. W.; Gray, N.

doi:10.1101/2023.04.24.537960

bioRxiv · 10.1101/2023.04.24.537960

Metabolic consequences of non-severe burn injury are associated with increased plasma markers of inflammation and cardiovascular disease risk.

Ryan, M. J.·Raby, E.·Masuda, R.·Lodge, S.·Nitschke, P.·Maker, G. L.·Wist, J.·Holmes, E.·Whiley, L.·Wood, F. M.·Nicholson, J. K.·Fear, M. W.·Gray, N.

View original source ↗Export metadata ↓

Abstract

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic co-morbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on impact of non-severe injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of non-severe burn injury, longitudinal plasma was collected from adults (n=35) who presented at hospital with a non-severe burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from non-burn control participants (n=14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoproteins signatures and 852 lipid species from across 20 subclasses. Multivariate data modelling (Orthogonal projection to latent structures-discriminate analysis) revealed alterations in lipoprotein and lipid metabolism when comparing baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value <1.0e-4), low density lipoprotein-2 subfractions (Variable importance in projection score; VIP >6.83e-1) and monoacyglyceride (20:4)(p-value <1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP >7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of non-severe burn injury. The phenotype is indicative of an acute inflammatory profile which continues to be sustained post-injury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have elevated incidence post-burn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalise intervention strategies and improve acute care, reducing risk of chronic co-morbidity.

Explore related subjects

systems biology Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Ryan, M. J., Raby, E., Masuda, R., Lodge, S., Nitschke, P., Maker, G. L., Wist, J., Holmes, E., Whiley, L., Wood, F. M., Nicholson, J. K., Fear, M. W., Gray, N.. 2023-04-28. Metabolic consequences of non-severe burn injury are associated with increased plasma markers of inflammation and cardiovascular disease risk.. https://doi.org/10.1101/2023.04.24.537960

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Limit-pushing overexpression reveals constraints on protein abundance

Proteins are often classified as toxic or non-toxic without measuring the abundance reached, leaving constraints on tolerable protein abundance unresolved. We established a limit-pushing approach in Saccharomyces cerevisiae combining strong inducible expression with gTOW-mediated high-copy selection to counteract copy-number compensation while measuring protein abundance and growth. Nearly all of approximately 80 chromosome I proteins severely inhibited growth or reduced viability at sufficiently high abundance. We established IE50, the expression level associated with a 50% reduction in growth rate, to quantify their widely varying overexpression tolerance. IE50 was positively associated with predicted structural order and cytoplasmic localization propensity and negatively associated with sulphur content. Single-cell imaging linked higher tolerance to proteins remaining cytoplasmic without becoming aggregation-positive and revealed abundance-dependent changes in localization and organelle morphology. At extreme abundance, Fun12, Nup60, and Pex22 generated distinct large-scale intracellular states through specific sequence regions. These findings establish overexpression toxicity as a quantitative property linked to protein characteristics and reveal both constraints on tolerable abundance and sequence-dependent capacities for intracellular organization.

systems biology↗

bioRxiv2026

Accessing Enzyme Kinetic Data and Prediction Methods at Scale

Enzyme kinetic parameters inform metabolic models, yet experimental measurements are sparse. A growing body of work predicts them from protein and substrate features, but software fragmentation hinders adoption, so downstream tools lock into the most accessible method. We present OpenKinetics Predictor (at predictor.openkinetics.org), an open-source platform integrating thirteen methods in isolated environments behind one interface. The platform optionally reports similarity between query proteins and each method's training data to contextualise reliability. A common featurisation-prediction abstraction keeps it extensible, and independent parties, including original authors, contributed many methods. We pair it with a data portal (at data.openkinetics.org) that exposes CatLog, a curated kinetic dataset, with precomputed embeddings, predicted binding sites, and standardised splits. Both offer a web interface and an API, and the GECKO modelling toolbox already calls the predictor API. As a case study, we predict across an E. coli model and find inter-predictor agreement varies with metabolic context and data availability.

systems biology↗

bioRxiv2026

A thermoregulatory design principle for transitions into hypometabolism

Mammals entering torpor or hibernation undergo an abrupt transition from normothermia to hypothermia, yet how thermoregulation enables this switch remains poorly understood. Here, we identify dynamical signatures that precede these transitions and a mathematical principle that can generate them. In fasting-induced torpor in mice, body-temperature fluctuations increased before torpor onset, providing an early-warning signal that tracked proximity to the transition better than temperature decline alone. A heat-balance model showed that reducing how strongly the effective heat-loss coefficient depends on body temperature reorganizes thermoregulatory stability, allowing a low-temperature equilibrium to emerge while the normothermic state remains stable. This organization is consistent with a symmetry-broken pitchfork involving a saddle-node. Similar increases in temperature fluctuations preceded hibernation onset in hamsters. These findings link pre-transition temperature dynamics to changes in the underlying thermoregulatory landscape and provide a framework for detecting and understanding transitions from normothermia to hypothermia.

systems biology↗