ABSTRACT
BACKGROUND AND AIMS: The SARS-CoV-2 pandemic has overwhelmed the treatment capacity of the health care systems during the highest viral diffusion rate. Patients reaching the emergency department had to be either hospitalized (inpatients) or discharged (outpatients). Still, the decision was taken based on the individual assessment of the actual clinical condition, without specific biomarkers to predict future improvement or deterioration, and discharged patients often returned to the hospital for aggravation of their condition. Here, we have developed a new combined approach of omics to identify factors that could distinguish coronavirus disease 19 (COVID-19) inpatients from outpatients. METHODS: Saliva and blood samples were collected over the course of two observational cohort studies. By using machine learning approaches, we compared salivary metabolome of 50 COVID-19 patients with that of 270 healthy individuals having previously been exposed or not to SARS-CoV-2. We then correlated the salivary metabolites that allowed separating COVID-19 inpatients from outpatients with serum biomarkers and salivary microbiota taxa differentially represented in the two groups of patients. RESULTS: We identified nine salivary metabolites that allowed assessing the need of hospitalization. When combined with serum biomarkers, just two salivary metabolites (myo-inositol and 2-pyrrolidineacetic acid) and one serum protein, chitinase 3-like-1 (CHI3L1), were sufficient to separate inpatients from outpatients completely and correlated with modulated microbiota taxa. In particular, we found Corynebacterium 1 to be overrepresented in inpatients, whereas Actinomycetaceae F0332, Candidatus Saccharimonas, and Haemophilus were all underrepresented in the hospitalized population. CONCLUSION: This is a proof of concept that a combined omic analysis can be used to stratify patients independently from COVID-19.
ABSTRACT
Lianhuaqingwen (LHQW) capsule, a herb medicine product, has been clinically proved to be effective in coronavirus disease 2019 (COVID-19) pneumonia treatment. However, human exposure to LHQW components and their pharmacological effects remain largely unknown. Hence, this study aimed to determine human exposure to LHQW components and their anti-COVID-19 pharmacological activities. Analysis of LHQW component profiles in human plasma and urine after repeated therapeutic dosing was conducted using a combination of HRMS and an untargeted data-mining approach, leading to detection of 132 LHQW prototype and metabolite components, which were absorbed via the gastrointestinal tract and formed via biotransformation in human, respectively. Together with data from screening by comprehensive 2D angiotensin-converting enzyme 2 (ACE2) biochromatography, 8 components in LHQW that were exposed to human and had potential ACE2 targeting ability were identified for further pharmacodynamic evaluation. Results show that rhein, forsythoside A, forsythoside I, neochlorogenic acid and its isomers exhibited high inhibitory effect on ACE2. For the first time, this study provides chemical and biochemical evidence for exploring molecular mechanisms of therapeutic effects of LHQW capsule for the treatment of COVID-19 patients based on the components exposed to human. It also demonstrates the utility of the human exposure-based approach to identify pharmaceutically active components in Chinese herb medicines.