UN General Assembly tuberculosis targets: are we on track?

Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis

The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of medications for tuberculosis therapy, resulting in increased morbidity and mortality globally. Tuberculosis spreads from the lungs to other parts of the body, including the brain and spine. Developing a single drug can take several decades, making drug discovery costly and time-consuming. Machine learning algorithms like support vector machines (SVM), k-nearest neighbor (k-NN), random forest (RF) and Gaussian naive base (GNB) are fast and effective and are commonly used in drug discovery. These algorithms are ideal for the virtual screening of large compound libraries to classify molecules as active or inactive. For the training of the models, a dataset of 307 was downloaded from BindingDB. Among 307 compounds, 85 compounds were labeled as active, having an IC50 below 58 mM, while 222 compounds were labeled inactive against thymidylate kinase, with 87.2% accuracy. The developed models were subjected to an external ZINC dataset of 136,564 compounds. Furthermore, we performed the 100-ns dynamic simulation and post trajectories analysis of compounds having good interaction and score in molecular docking. As compared to the standard reference compound, the top three hits revealed greater stability and compactness. In conclusion, our predicted hits can inhibit thymidylate kinase overexpression to combat Mycobacterium tuberculosis.Communicated by Ramaswamy H. Sarma.

Early culture conversion is a poor marker of treatment outcome among people with HIV and drug-resistant TB

OBJECTIVE

Our objective was to determine associations between early (≤2 months) culture conversion (ECC) among people with HIV and drug-resistant tuberculosis (DRTB) in Uganda.

METHODS

This was a countrywide retrospective cohort of people with bacteriologically confirmed DRTB and a positive baseline culture at 16 centres in Uganda between 2013 and 2019. Data were abstracted from treatment files and unit DRTB registers. Monthly sputum cultures were performed using the Lowenstein-Jensen solid medium.

RESULTS

We included 664 people with DRTB and a positive baseline culture, of whom 353 (53.4%) also had HIV. Among those living with HIV, 225 (63.7%) were male and 331 (94.3%) were on antiretroviral therapy. The median month of culture conversion was 2 (interquartile range [IQR] 1-3). ECC was observed among 226 people living with HIV (64.0%; 95% confidence interval [CI] 58.9-68.9). A DRTB treatment regimen of six or more drugs was associated with ECC among people living with HIV (adjusted odds ratio [aOR]  3.82; 95% CI 1.06-13.82; p = 0.041). Cure and overall treatment success was observed among 232 (65.7%) and 269 (76.2%) people living with HIV, respectively. However, ECC was not associated with cure (crude odds ratio [OR]  0.97; 95% CI 0.61-1.54; p = 0.901), death (OR 1.12; 95% CI 0.61-2.29; p = 0.610), or overall treatment success (OR 1.29; 95% CI 0.78-2.13; p = 0.326).

CONCLUSION

The majority of people living with HIV and DRTB achieve ECC. However, ECC does not predict cure, death, or treatment success. Moreover, it may require six or more drugs to achieve ECC. ECC is not an excellent indicator of the effectiveness of DRTB regimens among people living with HIV.

A 10-year Review of TB Notifications and Mortality Trends Using a Joint Point Analysis in Zambia - a High TB burden country

BACKGROUND

Zambia is one of the TB high-burden countries. It is important to track the progress being made towards enhancing case finding and reducing mortality. We reviewed routine TB notifications and mortality trends, over a decade from all facilities in Zambia.

METHODS

A 10-year retrospective study of TB notifications and mortality trends was performed using a Joint Point Analysis version 4.9.0.0, NCI. We extracted the annual national TB program data for the period under review.

RESULTS

There was a decline in annual point average for notification between 2010 and 2020 in both males and females, but the females notification rates had a higher rate of decline (AAPC = -6.7, 95%CI:-8.3 to -5.0), p<0.001) compared to the decline in males notification rate (AAPC = -4.1, 95%CI:-4.1 to -5.1, P<0.001). We found a significant growth rate in the proportion of TB patients that were bacteriologically confirmed (AAPC = 6.1, 95% CI: 3.6 to 8.7, p< 0.001), while the proportion of clinically diagnosed patients declined (AAPC= -0.1, 95%CI: -2.3 to 2.1, p<0.001). Notification of drug-resistant TB increased exponentially (AAPC=27.3, 95% CI: 13 to 41), p< 0.001) while mortality rate declined from 21.3 in 2011 to 12.7 in 2019 per 100,000 population (AAP=-5.6, 95%CI: -9.6 to -1.5, p=0.008).

CONCLUSIONS

This study has illustrated the importance of reviewing and analyzing routinely collected TB data by national programs. The study revealed areas of improvement in terms of TB control and underscores the need for increased and sustained investment in case detection and diagnostics.

Recovering from the Impact of the Covid-19 Pandemic and Accelerating to Achieving the United Nations General Assembly Tuberculosis Targets

In 2020, the novel COVID-19 pandemic replaced TB as the world’s top cause of death from an infectious disease. The October 21, 2020 the UN Secretary-General report on progress towards implementation of the UNHLM political declaration on TB stresses that although high-level commitments and targets had galvanized global and national progress towards ending TB, urgent and more ambitious investments and actions were required, especially in lieu of the COVID-19 pandemic where associated public health measures and travel restrictions, have disrupted health services universally. The report sets out 10 priority recommendations to get the world on track to reach agreed targets by 2022. Political commitment is more critical than ever. COVID-19 diagnostic and vaccination health services need to be aligned to TB services with active early case finding in communities, engaging the private sector care providers and mitigation of fear and stigma. Healthcare staff and community workers and leaders need to be provided with COVID-19 vaccination and personal protective equipment. The UNHLM declaration committed to mobilize 15 billion USD per annum for TB, of which 13 billion USD is for TB care and 2 billion USD per annum for TB R&D. The Global Fund needs to increase funding for TB. Learning from the unprecedented speed of COVID-19 vaccine development, fastracking development and evaluation of TB vaccines is essential. World leaders need to urgently address and reverse the socio-economic consequences of the COVID-19 pandemic and these will determine to what extent they will impact on achieving TB targets.