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.

This study investigated the association between COVID-19 infection and host metabolic signatures as prognostic markers for disease severity and mortality. We enrolled 82 patients with RT-PCR confirmed COVID-19 infection who were classified as mild, moderate, or severe/critical based upon their WHO clinical severity score and compared their results with 31 healthy volunteers. Data on demographics, comorbidities and clinical/laboratory characteristics were obtained from medical records. Peripheral blood samples were collected at the time of clinical evaluation or admission and tested by quantitative mass spectrometry to characterize metabolic profiles using selected metabolites. The findings in COVID-19 (+) patients reveal changes in the concentrations of glutamate, valeryl-carnitine, and the ratios of Kynurenine/Tryptophan (Kyn/Trp) to Citrulline/Ornithine (Cit/Orn). The observed changes may serve as predictors of disease severity with a (Kyn/Trp)/(Cit/Orn) Receiver Operator Curve (ROC) AUC = 0.95. Additional metabolite measures further characterized those likely to develop severe complications of their disease, suggesting that underlying immune signatures (Kyn/Trp), glutaminolysis (Glutamate), urea cycle abnormalities (Cit/Orn) and alterations in organic acid metabolism (C5) can be applied to identify individuals at the highest risk of morbidity and mortality from COVID-19 infection. We conclude that host metabolic factors, measured by plasma based biochemical signatures, could prove to be important determinants of Covid-19 severity with implications for prognosis, risk stratification and clinical management.

Platinum resistance in gynecologic malignancies: Response, disease free and overall survival are predicted by biochemical signature: A metabolomic analysis.

OBJECTIVE: Platinum resistance, defined as the lack of response or relapse within six months of platinum-based chemotherapy, is an important determinant of survival in gynecologic cancer. We used quantitative Mass Spectrometry to identify metabolic signatures that predict platinum resistance in patients receiving chemotherapy for gynecologic cancers. METHODS: In this study 47 patients with adenocarcinoma of the ovary or uterus who were candidates for carboplatin plus paclitaxel submitted blood for quantitation of metabolites and surgical specimens for the isolation 3-dimensional organoids used to measure individual patient platinum resistance, ex vivo. Results were correlated with response, time to progression and survival. RESULTS: Of 47 patients, 27 (64.3%) achieved complete remission with a mean time to progression of 1.9 years (± 1.5), disease-free survival of 1.7 years (± 1.4) and overall survival of 2.6 years (± 1.6) and a mean cisplatin lethal concentration 50% (LC50) = 1.15 µg/ml (range 0.4-3.1). Cisplatin LC50's correlated with a non-significant decrease in complete remission (RR [95% CI] =0.76 [0.46-1.27]), diminished disease-free survival (median: 1.15 vs. 2.99 years, p = 0.038) and with biochemical signatures of 186 metabolites. Receiver operating curves (ROC) of lipid ratios, branched chain amino acids and the tryptophan to kynurenine ratio identified patients at the highest risk of relapse and death (AUC = 0.933) with a sensitivity of 92.0% and specificity of 86.0% (p < 0.001). CONCLUSIONS: Metabolic signatures in gynecologic cancer identify patients at the highest risk of relapse and death offering new diagnostic and prognostic tools for management of the advanced gynecologic tumors.