Association between fatty acid metabolism gene mutations and Mycobacterium tuberculosis transmission revealed by whole genome sequencing.

BACKGROUND: Fatty acid metabolism greatly promotes the virulence and pathogenicity of Mycobacterium tuberculosis (M.tb). However, the regulatory mechanism of fatty acid metabolism in M.tb remains to be elucidated, and limited evidence about the effects of gene mutations in fatty acid metabolism on the transmission of M.tb was reported. RESULTS: Overall, a total of 3193 M.tb isolates were included in the study, of which 1596 (50%) were genomic clustered isolates. Most of the tuberculosis isolates belonged to lineage2(n = 2744,85.93%), followed by lineage4(n = 439,13.75%) and lineage3(n = 10,0.31%).Regression results showed that the mutations of gca (136,605, 317G > C, Arg106Pro; OR, 22.144; 95% CI, 2.591-189.272), ogt(1,477,346, 286G > C ,Gly96Arg; OR, 3.893; 95%CI, 1.432-10.583), and rpsA (1,834,776, 1235 C > T, Ala412Val; OR, 3.674; 95% CI, 1.217-11.091) were significantly associated with clustering; mutations in gca and rpsA were also significantly associated with clustering of lineage2. Mutation in arsA(3,001,498, 885 C > G, Thr295Thr; OR, 6.278; 95% CI, 2.508-15.711) was significantly associated with cross-regional clusters. We also found that 20 mutation sites were positively correlated with cluster size, while 11 fatty acid mutation sites were negatively correlated with cluster size. CONCLUSION: Our research results suggested that mutations in genes related to fatty acid metabolism were related to the transmission of M.tb. This research could help in the future control of the transmission of M.tb.

Association between diagnostic delay and prognosis of pulmonary tuberculosis in Shandong, China: a retrospective study.

BACKGROUND: Tuberculosis (TB) is one of the main infectious diseases that seriously threatens global health, while diagnostic delay (DD) and treatment dramatically threaten TB control. METHODS: Between 2005 and 2017 in Shandong, China, we enrolled pulmonary tuberculosis (PTB) patients with DD. DD trends were evaluated by Joinpoint regression, and associations between PTB patient characteristics and DD were estimated by univariate and multivariate logistic regression. The influence of DD duration on prognosis and sputum smear results were assessed by Spearman correlation coefficients. RESULTS: We identified 208,822 PTB cases with a median DD of 33 days (interquartile range (IQR) 18-63). The trend of PTB with DD declined significantly between 2009 and 2017 (annual percent change (APC): - 4.0%, P = 0.047, 2009-2013; APC: - 6.6%, P = 0.001, 2013-2017). Patients aged > 45 years old (adjusted odds ratio (aOR): 1.223, 95% confidence interval (CI) 1.189-1.257, 46-65 years; aOR: 1.306, 95% CI 1.267-1.346, > 65 years), farmers (aOR: 1.520, 95% CI 1.447-1.596), and those with a previous treatment history (aOR: 1.759, 95% CI 1.699-1.821) were prone to developing long DD (> 30 days, P < 0.05). An unfavorable outcome was negatively associated with a short DD (OR: 0.876, 95% CI 0.843-0.910, P < 0.001). Sputum smear positive rate and unfavorable outcomes were positively correlated with DD duration (Spearman correlation coefficients (rs) = 1, P < 0.001). CONCLUSIONS: The DD situation remains serious; more efficient and comprehensive strategies are urgently required to minimize DD, especially for high-risk patients.

Trends in the Notification Rates and Treatment Outcome of Tuberculosis in Shandong Province, China, 2005-2021.

Purpose: To analyze the time trends in the notification rates of registered tuberculosis (TB) and bacteriologically confirmed TB in Shandong Province. And analyze the changes in TB treatment outcomes during 2005-2021. Patients and Methods: The information of TB patients registered in the Shandong Information Center for Disease Control and Prevention (CDC) was collected during 2005-2021. We calculated the notification rates of registered TB and bacteriologically confirmed TB. Moreover, we calculated the year-to-year change rate of TB in treatment outcomes before and after COVID-19. The time trends were analyzed using the joinpoint regression method and illustrated as the annual percentage change (APC) of notification rates. Results: A total of 236,898 cases of TB were diagnosed during 2005-2021, of which 51.11% were bacteriologically confirmed cases. Since 2008, the notification rates of registered TB have declined. The notification rates of bacteriologically confirmed TB had been declining during 2005-2016, then remained stable after 2016. In subgroup, the notification rates of both registered TB and bacteriologically confirmed TB were higher among men, rural residents, and people aged ≥ 60 years. Compared with clinically confirmed TB, bacteriologically confirmed TB has shown higher rates of poor outcomes since 2008 and higher case fatality rate since 2005. The rate of poor outcomes remained stable during 2008-2019. However, after the COVID-19 outbreak, the rate of poor outcomes and case fatality rate of TB has risen significantly. Conclusion: After unremitting efforts to fight against TB, the notification rates of registered TB and bacteriologically confirmed TB declined in Shandong Province. The rate of poor outcomes remained stable during 2008-2019, then rise significantly after the COVID-19 outbreak. In the context of the long-term existence of COVID-19, further efforts should be made in TB diagnosis and treatment among high-risk population, especially with regard to males, rural residents and older adults.

Associations of residential greenness exposure and ambient air pollutants with newly-diagnosed drug-resistant tuberculosis cases.

Growing evidence has found the health protective effects of greenness exposure on tuberculosis (TB) and the impact of ambient air pollutants on TB drug-resistance. However, it remains unclear whether residential greenness is also beneficial to reduce TB drug-resistance, and whether air pollution modify the greenness-TB resistance relationship. We enrolled 5006 newly-diagnosed TB patients from Shandong, China, during 2014 to 2021. Normalized Difference Vegetation Index (NDVI) in 250 m and 500 m buffer around individuals' residential zone was used to assess greenness exposure. All patients were divided by quartiles of NDVI250-m and NDVI500-m (from low to high: Q1, Q2, Q3, Q4) respectively. Six logistic regression models (NDVI, NDVI + PM2.5/PM10/SO2/NO2/O3) were used to estimate the association of NDVI and TB drug-resistance when adjusting different air pollutants or not. All models were adjusted for age, gender, body mass index, complications, smoking, drinking, population density, nighttime light index, road density. Compared with participants in NDVI250-m Q1 and NDVI500-m Q1, other groups had lower rates of MDR-TB, PDR-TB, RFP-resistance, SM-resistance, RFP + SM resistance, INH + RFP + EMB + SM resistance. NDVI500-m reduced the risk of multidrug resistant tuberculosis (MDR-TB) and the adjusted odds ratio (aOR, 95% confidence interval, CI) compared with NDVI500-m Q1 were 0.736 (0.547-0.991) in NDVI + PM10 model, 0.733 (0.544-0.986) in NDVI + PM2.5 model, 0.735(0.546-0.99) in NDVI + SO2 model, 0.736 (0.546-0.991) in NDVI + NO2 model, respectively, P < 0.05. NDVI500-m contributed to a decreased risk of streptomycin (SM)-resistance. The aOR of rifampicin (RFP) + SM resistance were 0.132 (NDVI250-m, Q4 vs Q1, 95% CI: 0.03-0.578), 0.199 (NDVI500-m, Q3 vs. Q1, 95% CI: 0.057-0.688) and 0.264 (NDVI500-m, Q4 vs. Q1, 95% CI: 0.087-0.799). The adjusted ORs (Q2 vs. Q1, 95% CI) of isoniazid (INH) + RFP + ethambutol (EMB) + SM resistance in 500 m buffer were 0.276 (0.119-0.639) in NDVI model, 0.279 (0.11-0.705) in NDVI + PM10 model, 0.281 (0.111-0.713) in NDVI + PM2.5 model, 0.279 (0.11-0.709) in NDVI + SO2 model, 0.296 (0.117-0.754) in NDVI + NO2 model, 0.294 (0.116-0.748) in NDVI + O3 model, respectively. The study showed, for the first time, that residential greenness exposure in 500 m buffer is beneficial for reducing newly-diagnosed DR-TB (including PDR-RB, MDR-TB, MR-TB), and ambient air pollutants may partially mediate this association.

Polyketide synthases mutation in tuberculosis transmission revealed by whole genomic sequence, China, 2011-2019.

Introduction: Tuberculosis (TB) is an infectious disease caused by a bacterium called Mycobacterium tuberculosis (Mtb). Previous studies have primarily focused on the transmissibility of multidrug-resistant (MDR) or extensively drug-resistant (XDR) Mtb. However, variations in virulence across Mtb lineages may also account for differences in transmissibility. In Mtb, polyketide synthase (PKS) genes encode large multifunctional proteins which have been shown to be major mycobacterial virulence factors. Therefore, this study aimed to identify the role of PKS mutations in TB transmission and assess its risk and characteristics. Methods: Whole genome sequences (WGSs) data from 3,204 Mtb isolates was collected from 2011 to 2019 in China. Whole genome single nucleotide polymorphism (SNP) profiles were used for phylogenetic tree analysis. Putative transmission clusters (≤10 SNPs) were identified. To identify the role of PKS mutations in TB transmission, we compared SNPs in the PKS gene region between "clustered isolates" and "non-clustered isolates" in different lineages. Results: Cluster-associated mutations in ppsA, pks12, and pks13 were identified among different lineage isolates. They were statistically significant among clustered strains, indicating that they may enhance the transmissibility of Mtb. Conclusion: Overall, this study provides new insights into the function of PKS and its localization in M. tuberculosis. The study found that ppsA, pks12, and pks13 may contribute to disease progression and higher transmission of certain strains. We also discussed the prospective use of mutant ppsA, pks12, and pks13 genes as drug targets.

Impact of alcohol drinking and tobacco smoking on the drug-resistance of newly diagnosed tuberculosis: a retrospective cohort study in Shandong, China, during 2004-2020.

OBJECTIVES: To investigate the independent and collective impact of alcohol drinking and tobacco smoking on the drug-resistance of newly diagnosed tuberculosis (TB). DESIGN: This was a retrospective cohort study. SETTING: Shandong, China. PARTICIPANTS: Patients with newly diagnosed TB from 1 January 2004 to 31 December 2020 were collected. Exclusive criteria: retreated cases; extrapulmonary tuberculosis; without information on drug susceptibility testing results, smoking or drinking habits; bacteriological identification as non-tuberculous mycobacteria. PRIMARY AND SECONDARY OUTCOME MEASURES: Patients were classified into four groups including smokers only (G1), drinker only (G2), smoker +drinker (G3), non-smoker +non-drinker group (G0). We described the drug-resistant profiles, clinical factors and calculated the ORs of different drug-resistance among G1, G2, G3, compared with G0 through univariate and multivariate logistics regression models. RESULTS: Of the 7996 TB cases enrolled, the proportions of G1, G2, G3 and G0 were 8.25%, 3.89%, 16.46% and 71.40%, respectively. The rates of drug-resistant (DR)-TB, mono-resistant TB, multidrug resistant (MDR)-TB, polydrug resistant TB in G1, G2, G3 and G0 were 19.24%/16.4%/17.33%/19.08%, 11.52%/8.68%/10.94%/11.63%, 3.03%/2.57%/2.96%/3.66% and 4.70%/4.82%/3.34%/ 4.08%, respectively. G3 had a higher risk of MDR1: isoniazid +rifampin (adjusted OR (aOR)=1.91, 95% CI: 1.036 to 3.532), but had a lower risk of DR-TB (aOR=0.84, 95% CI: 0.71 to 0.99), rifampin-related resistance (aOR=0.68, 95% CI: 0.49 to 0.93), streptomycin-related resistance (aOR=0.82, 95% CI: 0.68 to 0.99), ethambutol-related resistance (aOR=0.57, 95% CI: 0.34 to 0.95), MDR3: isoniazid +rifampin+streptomycin (aOR=0.41, 95% CI: 0.19 to 0.85), any isoniazid +streptomycin resistance (aOR=0.85, 95% CI: 0.71 to 1.00). However, there were no significant differences between G1 and G0, G2 and G0 in all drug-resistant subtypes. Those patients with cavity had a higher risk of DR-TB among G3 (OR=1.35, 95% CI: 1.01 to 1.81). CONCLUSION: Although we did not found an independent impact of alcohol drinking or tobacco smoking on TB drug-resistance, respectively, these two habits had a combined effect on TB drug-resistance.

An Ecological Study of Tuberculosis Incidence in China, From 2002 to 2018.

INTRODUCTION: Tuberculosis is one of the main infectious diseases threatening global health, which is also the main cause of death from a single source of infection (above HIV/AIDS). China is a country with a high burden of tuberculosis in the world, ranking only behind India and Indonesia. However, there are few ecological studies on the burden of tuberculosis in China. This study aims to provide more research basis for the government to formulate tuberculosis policies by exploring the ecological factors associated with the incidence of tuberculosis, so as to achieve the goal of eliminating tuberculosis by 2030. METHODS: We collected data on the incidence of tuberculosis and ecological factors of 31 provinces, autonomous regions, and municipalities in Mainland China (excluding Taiwan, Hong Kong, and Macau) from 2002 to 2018. We constructed a framework of ecological factors affecting the incidence, which consists of 5 secondary indicators and 35 tertiary indicators. And we construct a dynamic panel data model based on the Lasso Regression to select variables to test the effect of each ecological factor on the incidence. RESULTS: Among the 35 tertiary indicators, economy 3,4,6,7, environment 1, recourses 1,3, demography 3, and lifecare 2,4,8,9,13 passed the significance test at the 1% level, economy 1,2,5, environment 2,9, lifecare 6,12 passed the significance test at the 5% level, lifecare 10 passed the significance test at the 10% level. Only economy 5 and economy 6 have a positive impact on the incidence, other statistically significant ecological indicators are negatively correlated with the incidence. CONCLUSIONS: Our study indicated that many ecological factors, including residents' income, unemployment rate, educational level, medical resources, population density, sunshine duration and dietary structure, are closely related to the incidence of tuberculosis. These findings contribute the government to taking targeted measures for tuberculosis prevention and control, including improving the level of economic development, increasing employment, expanding the scale of enrollment in colleges and universities, and ensuring that the prices of sources of animal protein are reasonable to meet the residents' intake of protein.

COVID-19 and Tuberculosis Coinfection: An Overview of Case Reports/Case Series and Meta-Analysis.

Background: Coronavirus disease 2019 (COVID-19) and tuberculosis (TB) are two major infectious diseases posing significant public health threats, and their coinfection (aptly abbreviated COVID-TB) makes the situation worse. This study aimed to investigate the clinical features and prognosis of COVID-TB cases. Methods: The PubMed, Embase, Cochrane, CNKI, and Wanfang databases were searched for relevant studies published through December 18, 2020. An overview of COVID-TB case reports/case series was prepared that described their clinical characteristics and differences between survivors and deceased patients. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) for death or severe COVID-19 were calculated. The quality of outcomes was assessed using GRADEpro. Results: Thirty-six studies were included. Of 89 COVID-TB patients, 19 (23.46%) died, and 72 (80.90%) were male. The median age of non-survivors (53.95 ± 19.78 years) was greater than that of survivors (37.76 ± 15.54 years) (p < 0.001). Non-survivors were more likely to have hypertension (47.06 vs. 17.95%) or symptoms of dyspnea (72.73% vs. 30%) or bilateral lesions (73.68 vs. 47.14%), infiltrates (57.89 vs. 24.29%), tree in bud (10.53% vs. 0%), or a higher leucocyte count (12.9 [10.5-16.73] vs. 8.015 [4.8-8.97] × 109/L) than survivors (p < 0.05). In terms of treatment, 88.52% received anti-TB therapy, 50.82% received antibiotics, 22.95% received antiviral therapy, 26.23% received hydroxychloroquine, and 11.48% received corticosteroids. The pooled ORs of death or severe disease in the COVID-TB group and the non-TB group were 2.21 (95% CI: 1.80, 2.70) and 2.77 (95% CI: 1.33, 5.74) (P < 0.01), respectively. Conclusion: In summary, there appear to be some predictors of worse prognosis among COVID-TB cases. A moderate level of evidence suggests that COVID-TB patients are more likely to suffer severe disease or death than COVID-19 patients. Finally, routine screening for TB may be recommended among suspected or confirmed cases of COVID-19 in countries with high TB burden.