Immunometabolic signatures predict risk of progression to sepsis in COVID-19

Abstract

Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986–0.995), with sensitivity of 0.978 (0.963–0.992) and specificity of 0.920 (0.890–0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952–0.977), with sensitivity of 0.993(0.984–1.000) and specificity of 0.851 (0.815–0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800–0.858), with sensitivity of 0.738 (0.695–0.781) and specificity of 0.781 (0.735–0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788–0.874), with sensitivity of 0.765 (0.697–0.832) and specificity of 0.817 (0.770–0.865).

Towards risk stratification and prediction of disease severity and mortality in COVID-19: Next generation metabolomics for the measurement of host response to COVID-19 infection

“…Our findings are in agreement with the recent study reported by Herrera-Van Oostdam et al [ 27 ] that identified immune-metabolic signatures as predictors of COVID-19 progression to sepsis. Among the similarities are perturbations in the Kynurenine/Tryptophan ratios, changes in phosphatidylcholine / lyso-phosphatidylcholine ratios and alterations in valeryl-carnitine.…”

“…Increased inflammation associated with a decline in phosphatidyl cholines and a rise in lysophosphatidyl cholines, the result of phospholipase activation [ 26 ], reflects the inflammatory response to COVID-19 characteristic of hyper-immunity and an increased risk of morbidity and mortality as recently reported [ 27 ].…”

The tryptophan catabolite or kynurenine pathway in COVID-19 and critical COVID-19: a systematic review and meta-analysis

“…[26,27,31,[43][44][45][46][47][48][49][50][51][52][53]. In this meta-analysis, we considered case-control and retrospective studies.…”

The tryptophan catabolite or kynurenine pathway in COVID-19 and critical COVID-19: a systematic review and meta-analysis

“…Nineteen full-text papers were eligible for the systematic review after 11 records were removed from the initial number of articles. Finally, the meta-analysis involved 14 articles as 5 papers were excluded for reasons listed in ESF, Table 3 (Blasco, Bessy et al 2020, Fraser, Slessarev et al 2020, Kimhofer, Lodge et al 2020, Robertson, Gostner et al 2020, Thomas, Stefanoni et al 2020, Ansone, Briviba et al 2021, D’Amora, Silva et al 2021, Herrera-Van Oostdam, Castaneda-Delgado et al 2021, Lawler, Gray et al 2021, Lionetto, Ulivieri et al 2021, Mangge, Herrmann et al 2021, Marin-Corral, Rodriguez-Morato et al 2021, Michaelis, Zelzer et al 2021, Xiao, Nie et al 2021).…”