Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization.

Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences. We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n = 2956) and multi-ethnic populations (COVID-19 GWAS n = 10,908) to better understand extant causal associations between Type II Diabetes (GWAS n = 659,316), BMI (n = 681,275), diastolic and systolic blood pressure, and pulse pressure (n = 757,601 for each) and COVID-19 hospitalization risk across populations. Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI 1.67, 0.96-2.92) and pulse pressure (OR, 95% CI 1.27, 0.97-1.66) in the multi-ethnic sample. Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.

Neutrophil-to-Lymphocyte Ratios Are Closely Associated With the Severity and Course of Non-mild COVID-19.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is spreading worldwide. Measuring the prevention and control of the disease has become a matter requiring urgent focus. Objective: Based on coronavirus disease 2019 (COVID-19) clinical data from Wuhan, we conducted an in-depth analysis to clarify some of the pathological mechanisms of the disease and identify simple measures to predict its severity early on. Methods: A total of 230 patients with non-mild COVID-19 were recruited, and information on their clinical characteristics, inflammatory cytokines, and T lymphocyte subsets was collected. Risk factors for severity were analyzed by binary logistic regression, and the associations of neutrophil-to-lymphocyte ratios (N/LRs) with illness severity, disease course, CT grading, inflammatory cytokines, and T lymphocyte subsets were evaluated. Results: Our results showed that the N/LRs were closely related to interleukin (IL)-6 and IL-10 (P < 0.001, P = 0.024) and to CD3+ and CD8+ T lymphocytes (P < 0.001, P = 0.046). In particular, the N/LRs were positively correlated with the severity and course of the disease (P = 0.021, P < 0.001). Compared to the values at the first test after admission, IL-6 and IL-10 were significantly decreased and increased, respectively, as of the last test before discharge (P = 0.006, P < 0.001). More importantly, through binary logistic regression, we found that male sex, underlying diseases (such as cardiovascular disease), pulse, and N/LRs were all closely related to the severity of the disease (P = 0.004, P = 0.012, P = 0.013, P = 0.028). Conclusions: As a quick and convenient marker of inflammation, N/LRs may predict the disease course and severity level of non-mild COVID-19; male sex, cardiovascular disease, and pulse are also risk factors for the severity of non-mild COVID-19.