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.

Figure 1

Daily new confirmed coronavirus disease 2019 (COVID-19) cases by country shown in a rolling 7-day average up to December 1, 2020 (Source: Johns Hopkins University CSSE COVID-19 Data, https://ourworldindata.org).

Figure 2

Number of new coronavirus disease 2019 (COVID-19) cases reported on a daily basis in the United States since the beginning of the outbreak up to December 1, 2020. Bars denote new cases by day and graph line shows 7-day average. (Source: Centers for Disease Control and Prevention, https://www.cdc.gov).

Figure 3

Age-adjusted hospitalization rates by race and ethnicity for coronavirus disease 2019 (COVID-19) disease from March 1, 2020, to August 15, 2020 (Source: Centers for Disease Control and Prevention, https://www.cdc.gov). COVID-NET, Coronavirus Disease 2019 Associated Hospitalization Surveillance Network.

Figure 4

Coronavirus disease 2019 case fatality rate expressed as a percentage in different age groups separated for males (blue) and females (green) (Adapted from Scully et al⁴).

Figure 5

The percentage and number of cytokine/chemokine producing inflammatory monocyte macrophages (IMMs) expressed in male and female mice lung tissue after infection with mouse-adapted severe acute respiratory syndrome coronavirus (SARS-CoV) (Adapted from Channappanavar et al¹¹). IL, interleukin; IM, inflammatory monocyte macrophages; TNF, tumor necrosis factor.

Figure 6

Proposed schematic depicting the demographic and biological variables that may characterize the high-risk patient. ACE-2, angiotensin-converting enzyme 2; Rx, drug therapy.