Mass versus personalized medicine against COVID-19 in the "system sciences" era

Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients: Results from a Cohort Observational Study

Purpose: COVID-19 presents complex pathophysiology, and evidence collected points towards an intricate interaction between viral-dependent and individual immunological mechanisms. Identifying phenotypes through clinical and biological markers may provide a better understanding of the subjacent mechanisms and an early patient-tailored characterization of illness severity. Methods: A multicenter prospective cohort study was performed in 5 hospitals in Portugal and Brazil for one year between 2020-2021. All adult patients with an Intensive Care Unit admission with SARS-CoV-2 pneumonia were eligible. COVID-19 was diagnosed using clinical and radiologic criteria with a SARS-CoV-2 positive RT-PCR test. A two-step hierarchical cluster analysis was made using several class-defining variables. Results: 814 patients were included. The cluster analysis revealed a three-class model, allowing for the definition of three distinct COVID-19 phenotypes: 407 patients in phenotype A, 244 patients in phenotype B, and 163 patients in phenotype C. Patients included in phenotype A were significantly older, with higher baseline inflammatory biomarkers profile, and a significantly higher requirement of organ support and mortality rate. Phenotypes B and C demonstrated some overlapping clinical characteristics but different outcomes. Phenotype C patients presented a lower mortality rate, with consistently lower C-reactive protein, but higher procalcitonin and interleukin-6 serum levels, describing an immunological profile significantly different from phenotype B. Conclusions: Severe COVID-19 patients exhibit three different clinical phenotypes with distinct profiles and outcomes. Their identification could have an impact on patients' care, justifying different therapy responses and inconsistencies identified across different randomized control trial results.

Will Omics Biotechnologies Save Us from Future Pandemics? Lessons from COVID-19 for Vaccinomics and Adversomics

The COVID-19 pandemic had cross-cutting impacts on planetary health, quotidian life, and society. Mass vaccination with the current gene-based vaccines has helped control the pandemic but unfortunately it has not shown effectiveness in preventing the spread of the virus. In addition, not all individuals respond to these vaccines, while others develop adverse reactions that cannot be neglected. It is also a fact that some individuals are more susceptible to infection while others develop effective immunization post-infection. We note here that the person-to-person and population variations in vaccine efficacy and side effects have been studied in the field of vaccinomics long before the COVID-19 pandemic. Additionally, the field of adversomics examines the mechanisms of individual differences in the side effects of health interventions. In this review, we discuss the potential of a multi-omics approach for comprehensive profiling of the benefit/risk ratios of vaccines. Vaccinomics and adversomics stand to benefit planetary health and contribute to the prevention of future pandemics in the 21st century by offering precision guidance to clinical trials as well as promoting precision use of vaccines in ways that proactively respond to individual and population differences in their efficacy and safety. This vision of pandemic prevention based on personalized instead of mass vaccination also calls for equity in access to precision vaccines and diagnostics that support a vision and practice of vaccinomics and adversomics in planetary health.