Genetic Polymorphisms in the Host and COVID-19 Infection.

The outbreak of the COVID-19 pandemic shows a marked geographical variation in its prevalence and mortality. The question arises if the host genetic variation may (partly) affect the prevalence and mortality of COVID-19. We postulated that the geographical variation of human polymorphisms might partly explain the variable prevalence of the infection. We investigated some candidate genes that have the potential to play a role in the immune defense against COVID-19: complement component 3 (C3), galactoside 2-alpha-L-fucosyltransferase 2 (FUT2), haptoglobin (Hp), vitamin D binding protein (DBP), human homeostatic iron regulator protein (HFE), cystic fibrosis transmembrane conductance regulator (CFTR), and angiotensin-converting enzyme 1 (ACE1). In a univariate approach, ACE1 D/I, C3, CFTR, and HFE polymorphisms correlated significantly with COVID-19 prevalence/mortality, whereas Hp and FUT2 polymorphism did not show any significant correlations. In a multivariate analysis, only ACE1 D/I and C3 polymorphisms were determinants for COVID-19 prevalence/mortality. The other polymorphisms (CFTR, DBP, FUT2, HFE, and Hp) did not correlate with COVID-19 prevalence/mortality. Whereas ACE1 D/I polymorphism shows functional links with ACE2 (which is the receptor for the virus) in COVID-19, C3 can act as a critical step in the virus-induced inflammation. Our findings plead against a bystander role of the polymorphisms as a marker for historical migrations, which comigrate with causal genes involved in COVID-19 infection. Further studies are required to assess the clinical outcome of COVID-19 in C3S and ACE1 D allele carriers and to study the role of C3 and ACE1 D/I polymorphisms in COVID-19 and their potential effects on treatment response.

Risk Factors for Mortality of COVID-19 Patient Based on Clinical Course: A Single Center Retrospective Case-Control Study.

Background: Epidemiological factors, clinical characteristics, and risk factors for the mortality of COVID-19 patients have been studied, but the role of complementary systems, possible inflammatory and immune response mechanisms, and detailed clinical courses are uncertain and require further study. Methods: In this single center, retrospective case-control study, we included all COVID-19 inpatients transferred or admitted to Wuhan Tongji Hospital from January 3 to March 30 2020 who had definite clinical outcomes (cured or deceased) with complete laboratory and radiological results. Clinical data were extracted from the electronic medical records, and compared between the cured and deceased patients. ROC curves were used to evaluate the prognostic value of the clinical parameters, and multivariable logistic regression analysis was performed to explore the risk factors for mortality. The correlation between the variables was evaluated by Spearman correlation analysis. Results: 208 patients were included in this study, 182 patients were cured and discharged, 26 patients died from COVID-2019. Most patients had comorbidities, with hypertension as the most common chronic disease (80; 38%). The most common symptoms at onset were fever (149; 72%), cough (137; 66%), and dyspnea (113; 54%). Elevated leucocytes, neutrophils, inflammatory biomarkers (CRP, ferritin, IL6, IL8, procalcitonin), PT, D-dimer, myocardial enzymes, BUN, decreased lymphocyte and subsets (T cells, CD4 T cells, CD8 T cells, NK cells, T cells + B cells + NK cells), and immunological factors (C3, C4) indicated poor outcome. PT, C3, and T cells were confirmed as independent prognostic factors for mortality by logistic regression models. IL6 and CPR were positively correlated with neutrophils, but negatively with lymphocytes and lymphocyte subsets except B cells. IL8 and ferritin were negatively related to T cells and CD4 T cells. Positive associations existed between C3 and T cells, CD4 T cells, and CD8 T cells, whereas there was no significant correlation between C4 and lymphocyte subsets. PT was found positively correlated with IL6, IL8, and CRP. Reverse correlations were explored between C3, C4, and PT, CK-MB, total bilirubin. Conclusions: T cells, C3, and PT were identified as independent prognostic factors for mortality. Decreased C3 and C4, dysregulation of lymphocyte subsets and cytokines may lead to death after SARS-CoV-2 infection.