ABSTRACT
Background: Understanding the role of crucial biomolecules and mechanistic pathways supporting coronavirus disease 2019 (COVID-19) pathophysiology is essential to handle the immune dysregulation and complications driven by uncontrolled severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Thus, we evaluated the proteomics, metabolomics and lipidomics plasma profile in a well-characterized cohort of COVID-19 patients ranging from asymptomatic to critical illness. Methods: This multicenter case-control study enrolled 273 adults with SARS-CoV-2 infection, confirmed by Polymerase chain reaction (PCR), who were recruited within the first 21 days of the infection during the first wave (March-May 2020) of COVID-19 pandemic. Participants were categorized into three groups of severity according to the inclusion criteria described in "Diagnosis and Treatment Protocol for COVID-19 Patients" and distributed as mild (n=77), severe (n=134) and critical (n=62). Serum profile of COVID-19 patients was characterized in the acute phase of the infection using a nontargeted multiomics approach. Univariate and multivariate analyses were performed to identify key molecules involved in critical COVID-19 and to evaluate their predictive power as biomarkers of COVID-19 severity. Results: COVID-19 critically ill patients presented a well-differentiated blood pattern for severe disease. The multiomic analysis identified specific alterations in pathways linked to complement and coagulation cascades, platelet activation, cell adhesion, acute inflammation, energy production (Krebs cycle and Warburg effect), amino acid catabolism and lipid transport as hallmarks of critical COVID-19. A new biomarker panel including the combination of selected proteins, metabolites and lipids predicted with high accuracy the most adverse COVID-19 outcomes (AUC: 0.994, 85.9% specificity and 100% sensitivity). Conclusion: The identification of predictive molecules related to critical COVID-19 outcomes provides a valuable tool for the rapid and efficient identification of clinical worsening in the early stage of SARS-CoV-2 infection. The association of a distinctive proteomic, metabolomic and lipidomic fingerprint with COVID-19 severity provides a better understanding of the immunopathogenesis and the host response to SARS-CoV-2 infection which could help in the identification of potential therapeutic targets.
ABSTRACT
OBJECTIVE: Population-based data on the current Covid-19 pandemic is scarce. This study investigated incidence and risk to suffer Covid-19 by baseline underlying conditions in people ≥50 years in Tarragona region across march-april 2020. METHODS: Population-based retrospective cohort study involving 79,071 adults ≥50 years-old in Tarragona region (Southern Catalonia, Spain). Cohort characteristics (age, sex, residence, vaccinations history and comorbidities) were established at baseline, and Covid-19 cases occurring between 01/03/2020-30/04/2020 were registered. Cox regression analysis calculating Hazard ratios (HRs) adjusted by age, sex and comorbidities was used to estimate risk for Covid-19. RESULTS: Across study period, 1,547 cohort members were PCR tested (22.6% positive) and 367 were presumptive cases without PCR tested. Considering PCR-confirmed Covid-19, incidence (per 100,000 persons-period) was 441 overall (248, 141, 424, 1,303 and 3,135 in 50-59, 60-69, 70-79, 80-89 and ≥90 years-old, respectively;380 in men and 497 in women;259 in community-dwelling and 10,571 in nursing-home). By comorbidities, maximum incidence emerged among persons with neurological disease (2,723), atrial fibrillation (1,348), chronic renal failure (1,050), cardiac disease (856), respiratory disease (798) and diabetes (706). Lower incidence appeared in rheumatic diseases (230) and smokers (180). In multivariable analysis focused on community-dwelling individuals (N=77,671), only cardiac disease (HR: 1.47;95% CI: 1.01-2.15;p=0.045) and respiratory disease (HR: 1.75;95% CI: 1.00-3.02;p=0.051) were associated with an increased risk, whereas smoking (HR:0.43;95% CI: 0.25-0.74;p=0.002) and influenza vaccinated (HR: 0.63;95% CI: 0.43-0.92;p=0.015) appeared associated with a decreased risk. CONCLUSIONS: Apart of increasing age and nursing-home residence, chronic respiratory and cardiac disease appear at increased risk for suffering covid19. This study investigated population-based incidence of Covid-19 infection by underlying conditions among adults ≥50 years in Tarragona (Southern Catalonia, Spain) across two first months pandemic period.