COVID-19: Understanding Inter-Individual Variability and Implications for Precision Medicine

Abstract

Coronavirus disease 2019 (COVID-19) is characterized by heterogeneity in susceptibility to the disease and severity of illness. Understanding inter-individual variation has important implications for not only allocation of resources but also targeting patients for escalation of care, inclusion in clinical trials, and individualized medical therapy including vaccination. In addition to geographic location and social vulnerability, there are clear biological differences such as age, sex, race, presence of comorbidities, underlying genetic variation, and differential immune response that contribute to variability in disease manifestation. These differences may have implications for precision medicine. Specific examples include the observation that androgens regulate the expression of the enzyme transmembrane protease, serine 2 which facilitates severe acute respiratory syndrome coronavirus 2 viral entry into the cell; therefore, androgen deprivation therapy is being explored as a treatment option in males infected with COVID-19. An immunophenotyping study of COVID-19 patients has shown that a subset develop T cytopenia which has prompted a clinical trial that is testing the efficacy of interleukin-7 in these patients. Predicting which COVID-19 patients will develop progressive disease that will require hospitalization has important implications for clinical trials that target outpatients. Enrollment of patients at low risk for progression of disease and hospitalization would likely not result in such therapy demonstrating efficacy. There are efforts to use artificial intelligence to integrate digital data from smartwatch applications or digital monitoring systems and biological data to enable identification of the high risk COVID-19 patient. The ultimate goal of precision medicine using such modern technology is to recognize individual differences to improve health for all.

The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype

“…The UK Biobank, one of the largest biobanks in the world in terms of data volume and depth including multi-organ imaging, is an example of one that has been integrated with pre-existing data of COVID-19 patients. UK Biobank's data has been used for research related to COVID-19 [for example, see Armstrong et al (2020) 2020), Kenneth and So (2020), Pereira et al (2020), Toh and Brody (2020), and Zimmerman and Kalra (2020), exist that have used biobanks' data for their development, and it is likely that the use of biobanks' data for the development of AI solutions will increase in the near future.…”

Allotypic variation in antigen processing controls antigenic peptide generation from SARS-CoV-2 S1 Spike Glycoprotein

“…Frequency distribution of generated peptides (7-14mers) produced by one or several different ERAP1 allotypes. The distribution is shown for both reaction conditions and per allotype (1)(2)(3)(4)(5)(6)(7)(8)(9)(10). Peptides produced by all 10 allotypes are not plotted.…”

SARS-CoV-2: Pathogenesis, Molecular Targets and Experimental Models

“…The COVID-19 infection exhibits inter-individual variability. It causes a wide range of severity, from the asymptomatic career to patients with multiple organ failure (Pereira et al, 2021). Studies illustrate the COVID-19 disease manifestation and progression has been correlated with the age, race, ethnicity, sex and the expression pattern of ACE-2, and immune regulation of the individuals (Benetti et al, 2020;Penna et al, 2020).…”