DNA damage contributes to age-associated differences in SARS-CoV-2 infection.

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is known to disproportionately affect older individuals. How aging processes affect SARS-CoV-2 infection and disease progression remains largely unknown. Here, we found that DNA damage, one of the hallmarks of aging, promoted SARS-CoV-2 infection in vitro and in vivo. SARS-CoV-2 entry was facilitated by DNA damage caused by extrinsic genotoxic stress or telomere dysfunction and hampered by inhibition of the DNA damage response (DDR). Mechanistic analysis revealed that DDR increased expression of angiotensin-converting enzyme 2 (ACE2), the primary receptor of SARS-CoV-2, by activation of transcription factor c-Jun. Importantly, in vivo experiment using a mouse-adapted viral strain also verified the significant roles of DNA damage in viral entry and severity of infection. Expression of ACE2 was elevated in the older human and mice tissues and positively correlated with γH2AX, a DNA damage biomarker, and phosphorylated c-Jun (p-c-Jun). Finally, nicotinamide mononucleotide (NMN) and MDL-800, which promote DNA repair, alleviated SARS-CoV-2 infection and disease severity in vitro and in vivo. Taken together, our data provide insights into the age-associated differences in SARS-CoV-2 infection and a novel approach for antiviral intervention.

Predictive Score of Risk Associated with Progression of Patients with COVID-19 Pneumonia in Wuhan, China: the ALA Score.

Background The Coronavirus Disease 2019 (COVID-19) had become a Public Health Emergency of International Concern with more than 90 million confirmed cases worldwide. Therefore, this study aims to establish a predictive score model of progression to severe type in patients with COVID-19. Methods This is a retrospective cohort study of 151 patients with COVID-19 diagnosed by nucleic acid test or specific serum antibodies from February 13, 2020, to March 14, 2020, hospitalized in a COVID-19-designed hospital in Wuhan, China. Results Of the 151 patients with average age of 63 years, 64 patients were male (42.4%), and 29 patients (19.2%) were classified as severe group. Multivariate analysis showed that age > 65 years (odds ratio [OR] = 9.72, 95%CI: 2.92-32.31, P < 0.001), lymphocyte count ≤ 1.1 × 109/L (OR = 3.42, 95%CI: 1.24-9.41, P = 0.017) and AST > 35 U/L (OR = 3.19, 95%CI: 1.11-9.19, P = 0.032) were independent risk factors for the disease severity. The area under curve (AUC) of receiver operating characteristic curve of the probabilities of the composite continuous variable (age + lymphocyte + AST) is 0.796. Finally, a predictive score model called ALA was established, and its AUC was 0.83 (95%CI: 0.75-0.92). Using a cutoff value of 9.5 points, the positive and negative predictive values were 54.1% (38-70.1%) and 92.1% (87.2-97.1%), respectively. Conclusion The ALA score model can quickly identify severe patients with COVID-19, so as to help clinicians to better choose accurate management strategy.

Knowledge, Attitudes, and Practices of Urban Residents Toward COVID-19 in Shaanxi During the Post-lockdown Period.

Background: The coronavirus disease 2019 (COVID-19) pandemic in China is essentially under control. Under global scrutiny, China has started reviving the social, cultural, and working lives of its inhabitants. However, localized outbreaks of COVID-19 are occurring, indicating that the country still needs to follow disease prevention and control measures. Previous studies have assessed the knowledge, attitudes, and behaviors of the general public in China regarding COVID-19 during the pandemic. However, little is known about knowledge, attitudes, and practices (KAP) of Chinese residents regarding COVID-19 after periods of lockdown. Therefore, this study was conducted to identify the KAP and other factors among the residents of Shaanxi Province during the post-lockdown period. Methods: A cross-sectional, network questionnaire survey was conducted in Shaanxi Province from October 1-30, 2020. A total of 1,175 urban residents were interviewed via Wen Juan Xing, an online questionnaire tool. A self-developed online KAP COVID-19 questionnaire was developed in this study. The questionnaire consisted of four parts: general information, knowledge, attitude, and practice. Descriptive statistics and binomial logistic regression analysis were used in the statistical analysis. Results: The majority of the participants were knowledgeable about COVID-19. They had optimistic attitudes and behaved appropriately toward COVID-19. Education was an associated factor for the knowledge of residents and the knowledge of COVID-19 was high among people with high academic qualifications. Attitudes were more positive in residents who lived with elderly people, women, and children. The score of practice was higher in residents with positive attitudes and high academic qualifications. There was a positive correlation between age and practice. Conclusion: We found that the KAP of residents in Shaanxi was at a relatively high level during the post-lockdown period. Although the lockdown was lifted, the epidemic is not over. Thus, it is necessary to develop targeted health education programs for residents with different demographic characteristics in Shaanxi.

Factors Associated with a Positive Severe Acute Respiratory Syndrome Coronavirus 2 Testing in Suspected Cases Presenting with Pneumonia: A Retrospective Cohort Study in a Single Medical Center.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a global emerging infectious disease. OBJECTIVES: To analyze the initial clinical characteristics of COVID-19 suspected and confirmed patients on admission in order to find out which kinds may be more likely to get positive nucleic acid testing results, and to explore the risk factors associated with all-cause death. METHODS: Medical records from 309 highly suspected cases with pneumonia were collected from February 13, 2020, to March 14, 2020, in a COVID-19-designated hospital of Wuhan. The majority of the clinical data were collected on the first day of hospital admission. RESULTS: Of 309 patients with median age 64 years (interquartile ranges [IQR], 53-72 years), 111 patients (35.9%) were confirmed by nucleic acid testing (median age 64 years, IQR: 56-71 years; 48 males). Of those 111 patients, 13 (11.7%) patients died. In multivariate analysis, factors associated with positive testing included fatigue (odds ratios [OR] = 3.14; 95% confidence interval [CI]: 1.88-5.24, p < 0.001), cough (OR = 0.55; 95% CI: 0.32-0.95, p = 0.032), no less than 1 comorbidity (OR = 1.77; 95% CI: 1.06-2.98, p = 0.030), and severe pneumonia (OR = 2.67; 95% CI: 1.20-5.97, p = 0.016). Furthermore, age, dyspnea, noneffective antibiotic treatment, white blood cell, lymphocyte, platelets, and organ dysfunction (e.g., higher lactate dehydrogenase) were significantly associated with all-cause in-hospital death in patients with COVID-19. CONCLUSION: Patients with severe forms of this disease were more likely to get positive results. Age and organ dysfunction were associated with a greater risk of death.

Ratios of neutrophil-to-lymphocyte and platelet-to-lymphocyte predict all-cause mortality in inpatients with coronavirus disease 2019 (COVID-19): a retrospective cohort study in a single medical centre.

The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a public health emergency of international concern. The current study aims to explore whether the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are associated with the development of death in patients with COVID-19. A total of 131 patients diagnosed with COVID-19 from 13 February 2020 to 14 March 2020 in a hospital in Wuhan designated for treating COVID-19 were enrolled in the current study. These 131 patients had a median age of 64 years old (interquartile range: 56-71 years old). Furthermore, among these patients, 111 (91.8%) patients were discharged and 12 (9.2%) patients died in the hospital. The pooled analysis revealed that the NLR at admission was significantly elevated for non-survivors, when compared to survivors (P < 0.001). The NLR of 3.338 was associated with all-cause mortality, with a sensitivity of 100.0% and a specificity of 84.0% (area under the curve (AUC): 0.963, 95% confidence interval (CI) 0.911-1.000; P < 0.001). In view of the small number of deaths (n = 12) in the current study, NLR of 2.306 might have potential value for helping clinicians to identify patients with severe COVID-19, with a sensitivity of 100.0% and a specificity of 56.7% (AUC: 0.729, 95% CI 0.563-0.892; P = 0.063). The NLR was significantly associated with the development of death in patients with COVID-19. Hence, NLR is a useful biomarker to predict the all-cause mortality of COVID-19.