The association of estimated cardiorespiratory fitness with COVID-19 incidence and mortality: A cohort study.

BACKGROUND: It has been suggested that cardiorespiratory fitness (CRF) may be used to identify those at greatest risk for severe COVID-19 illness. However, no study to date has examined the association between CRF and COVID-19. The objectives of this study were to determine whether CRF is independently associated with testing positive with or dying from COVID-19. METHODS: This is a prospective cohort study of 2,690 adults from the UK Biobank Study that were followed from March 16th, 2020 to July 26th, 2020. Participants who were tested for COVID-19 and had undergone CRF assessment were examined. CRF was estimated (eCRF) and categorized as low (<20th percentile), moderate (20th to 80th percentile) and high (≥80th percentile) within sex and ten-year age groups (e.g. 50-60 years). Participants were classified as having COVID-19 if they tested positive (primarily PCR tests) at an in-patient or out-patient setting as of July 26, 2020. Participants were classified as having died from COVID-19 if the primary or underlying cause of death was listed ICD-10 codes U071 or U072 by June 30th, 2020. Adjusted risk ratios (aRR) and 95% confidence intervals (CI) were estimated and a forward model building approach used to identify covariates. FINDINGS: There was no significant association between eCRF and testing positive for COVID-19. Conversely, individuals with moderate (aRR = 0.43, 95% CI: 0.25, 0.75) and high fitness (aRR = 0.37, 95% CI: 0.16, 0.85) had a significantly lower risk of dying from COVID-19 than those with low fitness. CONCLUSIONS: While eCRF was not significantly associated with testing positive for COVID-19, we observed a significant dose-response between having higher eCRF and a decreased risk of dying from COVID-19. This suggests that prior gains in CRF could be protective against dying from COVID-19 should someone develop the virus.

Measures of Adiposity and Risk of Testing Positive for SARS-CoV-2 in the UK Biobank Study.

Objective: To assess if body mass index (BMI) and high waist circumference (HWC) are associated with testing positive for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: 9,386 UK Biobank study participants tested for SARS-CoV-2 from March 16th 2020 to June 29th 2020 were analyzed. A forward model building approach was used to estimate adjusted risk ratios (RR) and 95% confidence intervals (95% CI). Analyses were stratified by age due to a significant first-order interaction between age and HWC. Results: Approximately 17% (n = 1,577) of participants tested positive for SARS-CoV-2. BMI category had a linear association with testing positive for SARS-CoV-2 among participants <65 years (RR = 1.09, 95% CI 1.02-1.17). For participants ≥65 years, only obesity class II (RR = 1.38, 95% CI 1.10-1.74) had a significantly greater risk of testing positive for SARS-CoV-2 than those who were underweight/normal weight. While HWC was not associated with testing positive for SARS-CoV-2 in those <65 years, having an HWC was associated with an increased risk of testing positive for SARS-CoV-2 in participants ≥65 years (RR = 1.12, 95% CI 1.00-1.27). Conclusion: The associations of BMI and HWC with testing positive for SARS-CoV-2 differed by age. Notably, HWC was associated with testing positive in those ≥65 years, but not those who were younger, independent of BMI. This suggests that measures of adiposity in addition to BMI may be used to identify older individuals at greater risk of testing positive for SARS-CoV-2.

Statistical power in COVID-19 case-control host genomic study design.

The identification of genetic variation that directly impacts infection susceptibility to SARS-CoV-2 and disease severity of COVID-19 is an important step towards risk stratification, personalized treatment plans, therapeutic, and vaccine development and deployment. Given the importance of study design in infectious disease genetic epidemiology, we use simulation and draw on current estimates of exposure, infectivity, and test accuracy of COVID-19 to demonstrate the feasibility of detecting host genetic factors associated with susceptibility and severity in published COVID-19 study designs. We demonstrate that limited phenotypic data and exposure/infection information in the early stages of the pandemic significantly impact the ability to detect most genetic variants with moderate effect sizes, especially when studying susceptibility to SARS-CoV-2 infection. Our insights can aid in the interpretation of genetic findings emerging in the literature and guide the design of future host genetic studies.