No genetic causal association between systemic lupus erythematosus and COVID-19.

Objective: Emerging evidence suggests an increased prevalence of coronavirus disease 2019 (COVID-19) in patients with systemic lupus erythematosus (SLE), the prototype of autoimmune disease, compared to the general population. However, the conclusions were inconsistent, and the causal relationship between COVID-19 and SLE remains unknown. Methods: In this study, we aimed to evaluate the bidirectional causal relationship between COVID-19 and SLE using bidirectional Mendelian randomization (MR) analysis, including MR-Egger, weighted median, weighted mode, and the inverse variance weighting (IVW) method. Results: The results of IVW showed a negative effect of SLE on severe COVID-19 (OR = 0.962, p = 0.040) and COVID-19 infection (OR = 0.988, p = 0.025), which disappeared after Bonferroni correction. No causal effect of SLE on hospitalized COVID-19 was observed (OR = 0.983, p = 0.148). In the reverse analysis, no causal effects of severe COVID-19 infection (OR = 1.045, p = 0.664), hospitalized COVID-19 (OR = 0.872, p = 0.109), and COVID-19 infection (OR = 0.943, p = 0.811) on SLE were found. Conclusion: The findings of our bidirectional causal inference analysis did not support a genetically predicted causal relationship between SLE and COVID-19; thus, their association observed in previous observational studies may have been caused by confounding factors.

Impact of the eHealth literacy, knowledge and attitudes on COVID-19 prevention behavior among residents in the second year of the COVID-19 pandemic: A cross-sectional study in Anhui Province, China.

Objective: The pandemic of COVID-19 continues to challenge people's health worldwide. In the second year of the pandemic, adherence to COVID-19 preventive behavior is key to continuing efforts to overcome the epidemic. This study aims to assess the COVID-19-related knowledge, attitude, and prevention behavior (KAP) and electronic health literacy (eHealth literacy) among Anhui residents in China. Methods: From January 30 to March 27, 2021, the cross-sectional study was performed among Anhui residents in China, including 16 cities. An online survey was adopted to assess KAP regarding COVID-19, and eHealth, involving a total of 2,122 citizens. Following informed consent, residents were recruited by convenience sampling. Frequencies and proportions were calculated. Additionally, Mann-Whitney U tests were used to analyze the variables. Independent predictors of preventive behavior of COVID-19 were ascertained using a multivariable logistic regression model. Result: Residents demonstrated good knowledge, positive attitudes, acceptable practices, and good eHealth literacy. Online news and WeChat are the main health information resources. Citizens who had good knowledge, a positive attitude, good eHealth, and did not participate in the online lectures or training COVID-19 were more likely to take preventive measures. Those with poor health, who were male, did not have family members working in health care facilities, and did not work in a face-to-face environment were less likely to take precautions. Compared with a master's degree and above, participants with middle school education level and below took preventive behavior sometimes. Residents who browse the COVID-19 webpage <15 min weekly seldom took preventive actions. Conclusion: The study showed that in the second year of the COVID-19 pandemic, Chinese residents had adequate knowledge of COVID-19, positive attitudes, appropriate preventive practices, and basic eHealth literacy. To prevent the rebound of the COVID-19 epidemic, the government and health agencies should inform citizens concerning which information channels or websites to use and assist the underprivileged population who lacks basic infrastructure. In addition, increasing the level of knowledge and attitude, enhancing eHealth literacy and the Health Belief Model (HBM), and implementing the Health Code were seen as ways to reinforce adherence to preventive behavior. Targeting men, implementing public awareness campaigns, community engagement strategies, and health education programs are recommended.

Association between multiple sleep dimensions and functional bowel disorders among Chinese college freshmen.

BACKGROUND: Although sleep disorder is thought as a risk factor for functional bowel disorders, its impact role in adolescents remains unknown and the contribution of different sleep dimensions may deserve further attention. This study aimed to evaluate the relationship between multiple sleep dimensions and functional bowel disorders among Chinese college freshmen. METHODS: A cross-sectional survey was conducted in college freshmen from Huazhong University of Science and Technology in Wuhan, China in September 2019 with random cluster sampling method. All participants completed questionnaires about living habits, sleep and digestive symptoms. Diagnosis of irritable bowel syndrome and functional constipation were based on the Rome IV criteria. Univariate and multivariate logistic regression models were applied to assess the association of sleep dimensions with irritable bowel syndrome or functional constipation. RESULTS: Based on the 3335 individuals who completed the questionnaire, the overall prevalence of irritable bowel syndrome and functional constipation in college freshmen were 2.5% and 1.7%, respectively. Multivariate analysis revealed that compared with individuals reporting good sleep quality, those reporting poor (OR = 7.269, 95%CI: 2.876-18.370) were associated with increased risk of irritable bowel syndrome. Similarly, those reporting fair (OR = 2.068, 95%CI: 1.010-4.236) and poor (OR = 5.664, 95%CI: 1.864-17.205) were associated with increased risk of functional constipation. There was no statistically significant association between other sleep dimensions (sleep duration, sleep timing, or sleep latency) and irritable bowel syndrome or functional constipation. CONCLUSION: Self-reported poor sleep quality was a stronger independent predictor of functional bowel disorders than other sleep dimensions among Chinese college freshmen. Future intervention studies should consider the role of sleep quality for the prevention of FBDs in adolescents.

The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island.

INTRODUCTION: As of November 2021, older adults (aged ≥65 y) accounted for 81% of all deaths from COVID-19 in the US. Chronic lung diseases increase the risk for severe COVID-19 illness and death. The aim of this research was to examine the association between town-level rates of asthma and chronic obstructive pulmonary disease (COPD) and deaths from COVID-19 in 208 towns in Connecticut and Rhode Island. METHODS: We conducted a multistep analysis to examine the association between town-level chronic lung conditions and death from COVID-19. Pairwise correlations were estimated and bivariate maps were created to assess the relationship between COVID-19 deaths per 100,000 people and 1) asthma prevalence and 2) COPD prevalence among adults aged 65 years or older. We used multiple linear regression models to examine whether chronic lung conditions and other town-level factors were associated with COVID-19 death rates in Connecticut and Rhode Island. RESULTS: Initial bivariate correlation and mapping analyses suggested positive correlations between asthma and COPD prevalence and COVID-19 death rates. However, after controlling for town-level factors associated with chronic lung conditions and COVID-19 death rates, multiple linear regression models did not support an association, but town-level factors (African American race and Hispanic ethnicity, age ≥65 y, and low educational attainment) were significant predictors of COVID-19 death rates. CONCLUSION: We found significant associations between town-level factors and COVID-19, adding to the current understanding of the impact of social determinants of health on outcomes.

AntiV-SGN: a universal antiviral strategy to combat both RNA and DNA viruses by destroying their nucleic acids without sequence limitation.

Numerous viral outbreaks have threatened us throughout history. Here, we demonstrated a nucleic acid-based antiviral strategy named AntiV-SGN. Unlike those CRISPR-mediated methods, AntiV-SGN has advantages of no targets' sequence limitation, such as protospacer adjacent motif (PAM) or protospacer flanking sequence (PFS), being universal for both DNA and RNA viruses. AntiV-SGN was composed of a FEN1 protein and specific hpDNAs targeting viruses' nucleic acid. Its antiviral ability was tested on SARS-CoV-2 and HBV respectively. Reporter assays in human cells first illustrated the feasibility of AntiV-SGN. Then, it was verified that AntiV-SGN destroyed about 50% of live RNAs of SARS-CoV-2 in Vero cells and 90% cccDNA of HBV in HepG2.2.15 cells. It was also able to remove viral DNA integrated into the host's genome. In the mouse model, AntiV-SGN can be used to significantly reduce HBV expression at a level of 90%. Actually, in some cases, when viruses mutate to eliminate PAM/PFS or hosts were infected by both DNA and RNA viruses, AntiV-SGN could be a choice. Collectively, this study provided a proof-of-concept antiviral strategy of AntiV-SGN, which has potential clinical value for targeting a wide variety of human pathogens, both known and newly identified.

Spatial Distribution of COVID-19 and Comorbidities in New England

At the onset of the COVID-19 pandemic, the Centers for Disease Control and Prevention (CDC) identified chronic conditions which elevated the risk of COVID-19 complications: chronic obstructive pulmonary disease (COPD), diabetes, heart disease, kidney disease, and obesity. The aim of this study is to visualize the spatial distribution of confirmed cases of COVID-19 and local rates of comorbidities in CT, MA, NH, and RI and to identify the spatial clustering of hot spot between COVID-19 cases and rates of a summary measure of comorbidities across communities. This study collected data from state’s departments of public health in 4 New England states of confirmed COVID-19 cases as of February 25th, 2021 and extracted community-level rates of comorbidities among adults age 65+ from recent Healthy Aging Data Report (www.healthyagingdatareports.org). Results showed that the cities Bridgeport, CT (n=14,637), Boston, MA (n=57,912), Manchester, NH (n=9,658), and Providence, RI (n=26,792) had the highest rates of COVID-19 and the highest population density. The GIS based map illustrated that the largest cities with the highest population densities had both relatively high incidences of COVID-19 and heavy burdens of comorbidities. This study found that the hot spot areas of COVID-19 were observed in communities with the highest chronic disease burdens. These hot spots of COVID-19 and comorbidities are areas where resources (testing, masks, vaccines) should be surged to protect the community. The identification of hot spots may motivate residents to take every mitigation step to prevent and control COVID-19.

Analysis and Identification Genetic Effect of SARS-CoV-2 Infections to Alzheimer's Disease Patients by Integrated Bioinformatics.

BACKGROUND: COVID-19 pandemic is a global crisis which results in millions of deaths and causes long-term neurological sequelae, such as Alzheimer's disease (AD). OBJECTIVE: We aimed to explore the interaction between COVID-19 and AD by integrating bioinformatics to find the biomarkers which lead to AD occurrence and development with COVID-19 and provide early intervention. METHODS: The differential expressed genes (DEGs) were found by GSE147507 and GSE132903, respectively. The common genes between COVID-19 and AD were identified. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interactions (PPI) network analysis were carried out. Hub genes were found by cytoscape. A multivariate logistic regression model was constructed. NetworkAnalyst was used for the analysis of TF-gene interactions, TF-miRNA coregulatory network, and Protein-chemical Interactions. RESULTS: Forty common DEGs for AD and COVID-19 were found. GO and KEGG analysis indicated that the DEGs were enriched in the calcium signal pathway and other pathways. A PPI network was constructed, and 5 hub genes were identified (ITPR1, ITPR3, ITPKB, RAPGEF3, MFGE8). Four hub genes (ITPR1, ITPR3, ITPKB, RAPGEF3) which were considered as important factors in the development of AD that were affected by COVID-19 were shown by nomogram. Utilizing NetworkAnalyst, the interaction network of 4 hub genes and TF, miRNA, common AD risk genes, and known compounds is displayed, respectively. CONCLUSION: COVID-19 patients are at high risk of developing AD. Vaccination is required. Four hub genes can be considered as biomarkers for prediction and treatment of AD development caused by COVID-19. Compounds with neuroprotective effects can be used as adjuvant therapy for COVID-19 patients.

Nasopharyngeal Swabs Are More Sensitive Than Oropharyngeal Swabs for COVID-19 Diagnosis and Monitoring the SARS-CoV-2 Load.

Objective: Detection of SARS-CoV-2 by oropharyngeal swabs (OPS) and nasopharyngeal swabs (NPS) is an essential method for coronavirus disease 2019 (COVID-19) management. It is not clear how detection rate, sensitivity, and the risk of exposure for medical providers differ in two sampling methods. Methods: In this prospective study, 120 paired NPS and OPS specimens were collected from 120 inpatients with confirmed COVID-19. SARS-CoV-2 nucleic acid in swabs were detected by real-time RT-PCR. The SARS-CoV-2 detection rate, sensitivity, and viral load were analyzed with regards NPS and OPS. Sampling discomfort reported by patients was evaluated. Results: The SARS-CoV-2 detection rate was significantly higher for NPS [46.7% (56/120)] than OPS [10.0% (12/120)] (P < 0.001). The sensitivity of NPS was also significantly higher than that of OPS (P < 0.001). At the time of sampling, the time of detectable SARS-CoV-2 had a longer median duration (25.0 vs. 20.5 days, respectively) and a longer maximum duration (41 vs. 39 days, respectively) in NPS than OPS. The mean cycle threshold (Ct) value of NPS (37.8, 95% CI: 37.0-38.6) was significantly lower than that of OPS (39.4, 95% CI: 38.9-39.8) by 1.6 (95% CI 1.0-2.2, P < 0.001), indicating that the SARS-CoV-2 load was significantly higher in NPS specimens than OPS. Patient discomfort was low in both sampling methods. During NPS sampling, patients were significantly less likely to have nausea and vomit. Conclusions: NPS had significantly higher SARS-CoV-2 detection rate, sensitivity, and viral load than OPS. NPS could reduce droplets production during swabs. NPS should be recommended for diagnosing COVID-19 and monitoring SARS-CoV-2 load. Chinese Clinical Trial Registry, number: ChiCTR2000029883.