Autoimmune diseases and their genetic link to bronchiectasis: insights from a genetic correlation and Mendelian randomization study.

Background: Previous studies have demonstrated that autoimmune diseases are closely associated with bronchiectasis (BE). However, the causal effects between autoimmune diseases and BE remain elusive. Methods: All summary-level data were obtained from large-scale Genome-Wide Association Studies (GWAS). The univariate Mendelian randomization (UVMR) was utilized to investigate the genetic causal correlation (rg) of 12 autoimmune diseases and bronchiectasis, The Multivariable Mendelian Randomization (MVMR) method was used to explore the effects of the confounding factors. Further investigation was conducted to identify potential intermediate factors using mediation analysis. Finally, the linkage disequilibrium score regression (LDSC) method was used to identify genetic correlations among complex traits. A series of sensitivity analyses was performed to validate the robustness of the results. Results: The LDSC analysis revealed significant genetic correlations between BE and Crohn's disease (CD) (rg = 0.220, P = 0.037), rheumatoid arthritis (RA) (rg = 0.210, P = 0.021), and ulcerative colitis (UC) (rg = 0.247, P = 0.023). However, no genetic correlation was found with other autoimmune diseases (P > 0.05). The results of the primary IVW analysis suggested that for every SD increase in RA, there was a 10.3% increase in the incidence of BE (odds ratio [OR] = 1.103, 95% confidence interval [CI] 1.055-1.154, P = 1.75×10-5, FDR = 5.25×10-5). Furthermore, for every standard deviation (SD) increase in celiac disease (CeD), the incidence of BE reduced by 5.1% (OR = 0.949, 95% CI 0.902-0.999, P = 0.044, FDR = 0.044). We also observed suggestive evidence corresponding to a 3% increase in BE incidence with T1DM (OR = 1.033, 95% CI 1.001-1.066, P = 0.042, FDR = 0.063). Furthermore, MVMR analysis showed that RA was an independent risk factor for BE, whereas mediator MR analysis did not identify any mediating factors. The sensitivity analyses corroborated the robustness of these findings. Conclusion: LDSC analysis revealed significant genetic correlations between several autoimmune diseases and BE, and further MVMR analysis showed that RA is an independent risk factor for BE.

Risk factors associated with indoor transmission during home quarantine of COVID-19 patients.

Purpose: The study aimed to identify potential risk factors for family transmission and to provide precautionary guidelines for the general public during novel Coronavirus disease 2019 (COVID-19) waves. Methods: A retrospective cohort study with numerous COVID-19 patients recruited was conducted in Shanghai. Epidemiological data including transmission details, demographics, vaccination status, symptoms, comorbidities, antigen test, living environment, residential ventilation, disinfection and medical treatment of each participant were collected and risk factors for family transmission were determined. Results: A total of 2,334 COVID-19 patients participated. Compared with non-cohabitation infected patients, cohabitated ones were younger (p = 0.019), more commonly unvaccinated (p = 0.048) or exposed to infections (p < 0.001), and had higher rates of symptoms (p = 0.003) or shared living room (p < 0.001). Risk factors analysis showed that the 2019-nCov antigen positive (OR = 1.86, 95%CI 1.40-2.48, p < 0.001), symptoms development (OR = 1.86, 95%CI 1.34-2.58, p < 0.001), direct contact exposure (OR = 1.47, 95%CI 1.09-1.96, p = 0.010) were independent risk factors for the cohabitant transmission of COVID-19, and a separate room with a separate toilet could reduce the risk of family transmission (OR = 0.62, 95%CI 0.41-0.92, p = 0.018). Conclusion: Patients showing negative 2019-nCov antigen tests, being asymptomatic, living in a separate room with a separate toilet, or actively avoiding direct contact with cohabitants were at low risk of family transmission, and the study recommended that avoiding direct contact and residential disinfection could reduce the risk of all cohabitants within the same house being infected with COVID-19.

Advantages and challenges of metagenomic sequencing for the diagnosis of pulmonary infectious diseases.

OBJECTIVE: We aim to familiarize the application status of metagenomic sequencing in diagnosing pulmonary infections, to compare metagenomic sequencing with traditional diagnostic methods, to conclude the advantages and limitations of metagenomic sequencing, and to provide some advice for clinical practice and some inspiration for associated researches. DATA SOURCES: The data were obtained from peer-reviewed literature, white papers, and meeting reports. RESULTS: This review focused on the applications of untargeted metagenomic sequencing in lungs infected by bacteria, viruses, fungi, chlamydia pneumoniae, Mycoplasma pneumoniae, parasites, and other pathogens. Compared with conventional diagnostic methods, metagenomic sequencing is better in detecting novel, rare, and unexpected pathogens and being applied in co-infections. Meanwhile, it can also provide more comprehensive information about pathogens. However, metagenomic sequencing still has limitations. Also, the situations that should be applied in and how the results should be interpreted are discussed in this review. CONCLUSION: Metagenomic sequencing improves efficiency to identify pathogens compared with traditional diagnostic methods and can be applied in clinical diagnosis. However, the technology of metagenomic sequencing still needs to be improved. Also, clinicians should learn more about when to use metagenomic sequencing and how to interpret its results.

Assessing risk factors for SARS-CoV-2 infection in patients presenting with symptoms in Shanghai, China: a multicentre, observational cohort study.

Background: The outbreak of COVID-19 has led to international concern. We aimed to establish an effective screening strategy in Shanghai, China, to aid early identification of patients with COVID-19. Methods: We did a multicentre, observational cohort study in fever clinics of 25 hospitals in 16 districts of Shanghai. All patients visiting the clinics within the study period were included. A strategy for COVID-19 screening was presented and then suspected cases were monitored and analysed until they were confirmed as cases or excluded. Logistic regression was used to determine the risk factors of COVID-19. Findings: We enrolled patients visiting fever clinics from Jan 17 to Feb 16, 2020. Among 53 617 patients visiting fever clinics, 1004 (1·9%) were considered as suspected cases, with 188 (0·4% of all patients, 18·7% of suspected cases) eventually diagnosed as confirmed cases. 154 patients with missing data were excluded from the analysis. Exposure history (odds ratio [OR] 4·16, 95% CI 2·74-6·33; p<0·0001), fatigue (OR 1·56, 1·01-2·41; p=0·043), white blood cell count less than 4 × 109 per L (OR 2·44, 1·28-4·64; p=0·0066), lymphocyte count less than 0·8 × 109 per L (OR 1·82, 1·00-3·31; p=0·049), ground glass opacity (OR 1·95, 1·32-2·89; p=0·0009), and having both lungs affected (OR 1·54, 1·04-2·28; p=0·032) were independent risk factors for confirmed COVID-19. Interpretation: The screening strategy was effective for confirming or excluding COVID-19 during the spread of this contagious disease. Relevant independent risk factors identified in this study might be helpful for early recognition of the disease. Funding: National Natural Science Foundation of China.