Defining Outcomes of Tuberculosis (Treatment): From the Past to the Future

Adjunctive administration of parabiotic Lactobacillus sakei CVL-001 ameliorates drug-induced toxicity and pulmonary inflammation during antibiotic treatment for tuberculosis

Tuberculosis (TB) treatment requires a long therapeutic duration and induces adverse effects such as hepatotoxicity, causing discontinuation of treatment. Reduced adherence to TB medications elevates the risk of recurrence and the development of drug resistance. Additionally, severe cavitary TB with a high burden of Mycobacterium tuberculosis (Mtb) and inflammation-mediated tissue damage may need an extended treatment duration, resulting in a higher tendency of drug-induced toxicity. We previously reported that the administration of Lactobacillus sakei CVL-001 (L. sakei CVL-001) regulates inflammation and improves mucosal barrier function in a murine colitis model. Since accumulating evidence has reported the functional roles of probiotics in drug-induced liver injury and pulmonary inflammation, we employed a parabiotic form of the L. sakei CVL-001 to investigate whether this supplement may provide beneficial effects on the reduction in drug-induced liver damage and pulmonary inflammation during chemotherapy. Intriguingly, L. sakei CVL-001 administration slightly reduced Mtb burden without affecting lung inflammation and weight loss in both Mtb-resistant and -susceptible mice. Moreover, L. sakei CVL-001 decreased T cell-mediated inflammatory responses and increased regulatory T cells along with an elevated antigen-specific IL-10 production, suggesting that this parabiotic may restrain excessive inflammation during antibiotic treatment. Furthermore, the parabiotic intervention significantly reduced levels of alanine aminotransferase, an indicator of hepatotoxicity, and cell death in liver tissues. Collectively, our data suggest that L. sakei CVL-001 administration has the potential to be an adjunctive therapy by reducing pulmonary inflammation and liver damage during anti-TB drug treatment and may benefit adherence to TB medication in lengthy treatment.

Identification of hub genes and establishment of a diagnostic model in tuberculosis infection

Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable respiratory disease with a substantial susceptibility burden. This study was designed to identify new potential therapeutic targets for TB and establish a diagnostic model. mRNA expression data for TB were from GEO database, followed by conducting differential expression analysis. The top 50 genes with differential expression were subjected to GO and KEGG enrichment analyses. To establish a PPI network, the STRING database was utilized, and hub genes were identified utilizing five algorithms (EPC, MCC, MNC, Radiality, and Stress) within the cytoHubba plugin of Cytoscape software. Furthermore, a hub gene co-expression network was constructed using the GeneMANIA database. Consistency clustering was performed on hub genes, and ssGSEA was utilized to analyze the extent of immune infiltration in different subgroups. LASSO analysis was employed to construct a diagnostic model, and ROC curves were used for validation. Through the analysis of GEO data, a total of 159 genes were identified as differentially expressed. Further, GO and KEGG enrichment analyses revealed that these genes were mainly enriched in viral defense, symbiotic defense, and innate immune response-related pathways. Hub genes, including DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15, were identified using cytoHubba analysis of the PPI network. The GeneMANIA analysis unmasked that the co-expression rate of hub genes was 81.55%, and the physical interaction rate was 12.27%. Consistency clustering divided TB patients into two subgroups, and ssGSEA revealed different degrees of immune infiltration in different subgroups. LASSO analysis identified IFIT1, IFIT2, IFIT3, IFIH1, RSAD2, OAS1, OAS2, and STAT1 as eight immune-related key genes, and a diagnostic model was constructed. The ROC curve demonstrated that the model exhibited excellent diagnostic performance. DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15 were hub genes in TB, and the diagnostic model based on eight immune-related key genes exhibited good diagnostic performance.

Updates in pulmonary drug-resistant tuberculosis pharmacotherapy: A focus on BPaL and BPaLM

Drug-resistant tuberculosis (TB) is a major public health concern and contributes to high morbidity and mortality. New evidence supports the use of shorter duration, all-oral regimens, which represent an encouraging treatment strategy for drug-resistant TB. As a result, the landscape of drug-resistant TB pharmacotherapy has drastically evolved regarding treatment principles and preferred agents. This narrative review focuses on the key updates of drug-resistant TB treatment, including the use of short-duration all-oral regimens, while calling attention to current gaps in knowledge that may be addressed in future observational studies.

Early Microbiologic Markers of Pulmonary Tuberculosis Treatment Outcomes

Rationale: Earlier biomarkers of pulmonary tuberculosis (PTB) treatment outcomes are critical to monitor shortened anti-TB treatment (ATT). Objectives: To identify early microbiologic markers of unfavorable TB treatment outcomes. Methods: We performed a subanalysis of 2 prospective TB cohort studies conducted from 2013 to 2019 in India. We included participants aged ⩾18 years who initiated 6-month ATT for clinically or microbiologically diagnosed drug-sensitive PTB and completed at least one follow-up visit. Sputum specimens were subjected to a baseline Xpert Mycobacterium tuberculosis/rifampin (MTB/RIF) assay, acid-fast bacilli (AFB) microscopy and liquid and solid cultures, and serial AFB microscopy and liquid and solid cultures at weeks 2, 4, and 8. Poisson regression was used to assess the impact of available microbiologic markers (test positivity, smear grade, time to detection, and time to conversion) on a composite outcome of failure, recurrence, or death by 18 months after the end of treatment. Models were adjusted for age, sex, nutritional status, diabetes, smoking, alcohol consumption, and regimen type. Results: Among 1,098 eligible cases, there were 251 (22%) adverse TB treatment outcomes: 127 (51%) treatment failures, 73 (29%) recurrences, and 51 (20%) deaths. The primary outcome was independently associated with the Xpert MTB/RIF assay (medium-positive adjusted incidence rate ratio [aIRR], 1.91; 95% confidence interval [CI], 1.07-3.40; high-positive aIRR, 2.51; 95% CI, 1.41-4.46), positive AFB smear (aIRR, 1.48; 95% CI, 1.06-2.06), and positive liquid culture (aIRR, 1.98; 95% CI, 1.21-3.23) at baseline; Week 2 positive liquid culture (aIRR, 1.47; 95% CI, 1.04-2.09); and Week 8 positive AFB smear (aIRR, 1.63; 95% CI, 1.06-2.50) and positive liquid culture (aIRR, 1.54; 95% CI, 1.07-2.22). There was no evidence of Mycobacterium tuberculosis growth in the Mycobacterium Growth Indicator Tube at Week 4 conferring a higher risk of adverse outcomes (aIRR, 1.25; 95% CI, 0.89-1.75). Conclusions: Our analysis identifies Week 2 respiratory mycobacterial culture as the earliest microbiologic marker of unfavorable PTB treatment outcomes.

Inflammation-mediated tissue damage in pulmonary tuberculosis and host-directed therapeutic strategies

Treatment of tuberculosis (TB) involves the administration of anti-mycobacterial drugs for several months. The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb, the causative agent) together with increased disease severity in people with co-morbidities such as diabetes mellitus and HIV have hampered efforts to reduce case fatality. In severe disease, TB pathology is largely attributable to over-exuberant host immune responses targeted at controlling bacterial replication. Non-resolving inflammation driven by host pro-inflammatory mediators in response to high bacterial load leads to pulmonary pathology including cavitation and fibrosis. The need to improve clinical outcomes and reduce treatment times has led to a two-pronged approach involving the development of novel antimicrobials as well as host-directed therapies (HDT) that favourably modulate immune responses to Mtb. HDT strategies incorporate aspects of immune modulation aimed at downregulating non-productive inflammatory responses and augmenting antimicrobial effector mechanisms to minimise pulmonary pathology and accelerate symptom resolution. HDT in combination with existing antimycobacterial agents offers a potentially promising strategy to improve the long-term outcome for TB patients. In this review, we describe components of the host immune response that contribute to inflammation and tissue damage in pulmonary TB, including cytokines, matrix metalloproteinases, lipid mediators, and neutrophil extracellular traps. We then proceed to review HDT directed at these pathways.

Comparison of treatment outcome definitions in drug-resistant tuberculosis patients with high incidence of acquired second-line drug resistance

Background

Simplified drug-resistant tuberculosis (DR-TB) treatment outcome definitions, mostly centred around receipt of treatment and sputum culture status at 6 months after treatment initiation, have been proposed, but have not been widely evaluated in resource-limited settings.

Objectives

To compare DR-TB treatment outcomes, as defined by the World Health Organization (WHO) at the time of treatment, with simplified definitions.

Methods

We performed retrospective folder reviews of a cohort of 246 South African DR-TB patients, most of whom developed second-line drug resistance. Sequential treatment outcomes were assigned retrospectively using both simplified Tuberculosis Network European Trials Group (TBNET)-based and 2013 WHO-based definitions.

Results

Of 246 patients, 40% were HIV-positive, and 88% developed second-line drug resistance. Patients were observed for a median of 38 (interquartile range 24 - 63) months from DR-TB treatment initiation. Using WHO-based definitions, 93% of patients had >1 sequential outcome, whereas with simplified definitions, 25% of patients had >1 outcome. Fewer outcomes of cure (3% v. 9%) and more outcomes of treatment failure (42% v. 22%) were assigned using simplified definitions.

Conclusion

Simplified outcome definitions applied to real-world patients with long, often complex treatment histories resulted in underestimating cures and overestimating treatment failures compared with WHO-based definitions. Simplified definitions may identify more individuals at higher risk for treatment failure than WHO-based definitions, but without consistent programmatic follow-up it may be difficult to distinguish cure, failure and loss to follow-up.