Inter-individual variability in lipoprotein proteomics reveals distinct patient clusters informative for disease pathogenesis and severity
Nguyen, M.; Timouma, S.; Qin, H.; Mi, Y.; Hinds, C.; McKechnie, S.; Gautier, T.; Knight, J. C.
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Lipoprotein composition is altered in sepsis, and supplementation with high-density lipoproteins has been reported to improve outcomes in experimental settings. In this study, we aimed to investigate the nature and inter-individual variability in the lipoprotein proteome to inform risk stratification and opportunities for precision medicine approaches. In a large proteomic dataset including 1134 patients (1781 samples) with sepsis and 149 healthy volunteers, we analysed 18 protein components of lipoproteins. We characterise heterogeneity of the lipoprotein proteome, defining three step-wise sub-phenotypes associated with increasing disease severity, one close to health, then an early phase patient group showing increased abundance of proteins that integrate HDL under inflammatory conditions (SAA1 and SAA2), then a group with decreased abundance of proteins that are components of HDL under healthy conditions that was associated with higher organ failure intensity (SOFA score) and increased mortality. We developed and externally validated a quantitative score reflective of lipoproteins alterations in sepsis, and machine learning predictive models to predict the LP class, advancing future individualised lipoproteins-based therapeutics in sepsis.
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