Among the 300 COVID-19, males were more frequently encountered than females, especially in deceased cases. Previous studies also demonstrated that male cases outnumbered female cases, and males tended to have a more severe disease or at a critical status of illness. Further, males have been demonstrated to have 2.4 times risk of death compared to females [12,13,14,15]. There is no documented explanation for such gender preponderance of COVID-19 among males. However, it has been recently explored that such gender difference can be attributed to some comorbidities that indirectly increase the risk of infection or death among males. For instance, cardiovascular risk factors (heart disease, hypertension, and diabetes) and high-risk behaviors (social isolation, tobacco-smoking, alcohol use, and certain occupational exposures) are mostly associated with male gender [16]. Female sex hormones may also influence immune response regulation. Experimentally, it has been demonstrated that female mice were less prone to develop SARS-CoV infection than males. Further, increased mortality rate was increased among ovariectomized mice or female mice treated with estrogen receptor antagonist. It was concluded that estrogen receptor signaling may have a protective effects against SARS-CoV infection in females [17].
Age was a further risk factor for evolution of COVID-19, and the fifth decade may represent a critical age. Further, the results demonstrated that age can be considered as a death-associated risk factor. Most of Chinese data in this context agree that the infection was mostly observed in cases with advanced ages. Among 32,583 laboratory-confirmed COVID-19 cases from Wuhan (China), the median age of patients was 56.7 years, and elderly patients were at a higher risk of having severe or critical illness [13]. In a further Chinese study, 52 critically ill adult COVID-19 patients were explored. Their mean age was 59.7 years, and 61.5% of them died 28 days post-infection [14]. In a report from Korea, it has been found that age of COVID-19 patients showed M shape with two age peaks: 20s and 50s [18]. These findings might be expected because elderlies tend to have a higher prevalence of chronic diseases (for instance, cardiovascular diseases and diabetes) [19]. Further, reduced production of B and T cells in primary lymphoid organs and declined function of mature lymphocytes in secondary lymphoid tissues have been associated with aging [20]. These consequences will certainly increase the morbidity and mortality rates caused by viral and bacterial infections (including COVID-19) in elderlies.
Besides age and gender, ABO blood groups may also serve as susceptibility biomarkers for COVID-19. In this study, the overall distribution of the four phenotypes (A, B, AB, and O) showed a significant variation between patients (all cases, recovered, and deceased) and controls. In terms of individual phenotype, each group of patients was presented with specific profile. Among all cases of COVID-19, logistic regression analysis depicted an OR of 3.10 (95% CI 1.59–6.05) for group AB; therefore, such analysis suggested the susceptibility potential of this phenotype in the evolution COVID-19. Whereas, recovered cases were in favor of no significant association with ABO blood group phenotypes. On the contrary, deceased cases were markedly associated with group A (OR = 14.60; 95% CI 2.85–74.88). However, the three groups of patients shared a decreased frequency of group O, and the protective potential of such phenotype against evolution of COVID-19 was suggested. Recent studies have also depicted the significance of group O in lowering COVID-19 risk [4, 5, 10]. However, the three groups of investigators demonstrated the significance of groups A, B, or AB in increasing the risk of infection. Zhao and colleagues demonstrated further that group A was associated with a higher risk of death [5]. Together, these findings suggest that ABO antigens may interplay with pathogenesis of COVID-19; however, the mechanism(s) by which these molecules confer susceptibility or protection is subjected to speculations.
It has been speculated that infectious agents may influence human genome evolution through natural selection of specific alleles that may prone the population to the risk of infection. Further, these agents often use glycosylated cell-surface receptors for their successful attachment, and by such pathway, ABO determinants may affect host-pathogen interactions through utilization of glycosylation [7]. In SARS-CoV infection, it has been demonstrated that O-glycosylation plays a fundamental role in the virus pathogenesis [21]. Natural occurring anti-A and anti-B antibodies may also influence susceptibility to COVID-19 infection. In SARS-CoV infection, it has been hypothesized that these antibodies may decrease the rate of infection, and the degree of protection, may be influenced by the ABO antibody titer, secretor status, and incidence of group O in the population [9].