TB and COVID-19: An Exploration of the Characteristics and Resulting Complications of Co-infection

Prevalence and Patterns of Drug-Resistant Mycobacterium tuberculosis in Newly Diagnosed Patients in China: A Systematic Review and Meta-Analysis

BACKGROUND

Tuberculosis (TB), one of the deadliest infectious diseases globally, is increasingly exacerbated in China by the emergence of resistant Mycobacterium tuberculosis (MTB) strains. Drug-resistant TB, including mono-drug resistant TB, multidrug-resistant TB (MDR-TB), and extensively drug-resistant TB (XDR-TB), presents significant public health challenges.

METHODS

We conducted a systematic literature review from January 2010 to February 2024 using databases such as PubMed, Embase, Web of Science, and Google Scholar. Our focus was on empirical data related to drug resistance patterns in newly diagnosed TB cases. Non-empirical studies were excluded through meticulous filtering. For meta-analysis, we used Review Manager (RevMan) 5.2 and assessed evidence quality using the Newcastle-Ottawa Scale (NOS).

RESULTS

Our search strategy identified 40 studies that met the inclusion criteria, encompassing a total sample size of 87,667 participants. Among new TB cases, the estimated prevalence of MDR-TB in China was 6.9% (95% CI: 5.6-8.1%). Prevalence rates for mono-drug resistance to first-line anti-TB medications were as follows: isoniazid at 18.2% (95% CI: 16.4-20.6%), rifampicin at 10.5% (95% CI: 8.6-12.8%), and ethambutol at 5.7% (95% CI: 4.1-7.3%). The prevalence of streptomycin resistance, a former first-line anti-TB drug, was 17.1% (95% CI: 14.6-19.1%). The prevalence of other types of mono-drug resistance was 15.2% (95% CI: 13.9-17.3%), and for XDR-TB, it was 0.9% (95% CI: 0.6-1.4%).

CONCLUSIONS

The high prevalence of drug-resistant TB in China poses a significant public health challenge. There is an urgent need for targeted interventions and continued surveillance to combat the spread of drug-resistant TB.

Differences in Responses of Immunosuppressed Kidney Transplant Patients to Moderna mRNA-1273 versus Pfizer-BioNTech

Immunosuppressed kidney transplant (KT) recipients produce a weaker response to COVID-19 vaccination than immunocompetent individuals. We tested antiviral IgG response in 99 KT recipients and 66 healthy volunteers who were vaccinated with mRNA-1273 Moderna or BNT162b2 Pfizer-BioNTech vaccines. A subgroup of participants had their peripheral blood leukocytes (PBLs) evaluated for the frequency of T helper 1 (Th1) cells producing IL-2, IFN-γ and/or TNF-α, and IL-10-producing T-regulatory 1 (Tr) cells. Among KT recipients, 45.8% had anti-SARS-CoV-2 IgG compared to 74.1% of healthy volunteers (p = 0.009); also, anti-viral IgG levels were lower in recipients than in volunteers (p = 0.001). In terms of non-responders (≤2000 U/mL IgG), Moderna's group had 10.8% and Pfizer-BioNTech's group had 34.3% of non-responders at 6 months (p = 0.023); similarly, 15.7% and 31.3% were non-responders in Moderna and Pfizer-BioNTech groups at 12 months, respectively (p = 0.067). There were no non-responders among controls. Healthy volunteers had higher Th1 levels than KT recipients, while Moderna produced a higher Th1 response than Pfizer-BioNTech. In contrast, the Pfizer-BioNTech vaccine induced a higher Tr1 response than the Moderna vaccine (p < 0.05); overall, IgG levels correlated with Th1(fTTNF-α)/Tr1(fTIL-10) ratios. We propose that the higher number of non-responders in the Pfizer-BioNTech group than the Moderna group was caused by a more potent activity of regulatory Tr1 cells in KT recipients vaccinated with the Pfizer-BioNTech vaccine.

Tuberculosis Coinfection among COVID-19 Patients: Clinical Presentation and Mortality in a Tertiary Lung Hospital in Indonesia

BACKGROUND

Tuberculosis (TB) and coronavirus disease 2019 (COVID-19) are the top two killers of infectious disease. We aimed to determine the association of TB coinfection with the inhospital mortality of COVID-19 patients in Indonesia as a TB-endemic country.

METHODS

We conducted a retrospective cohort study in a tertiary lung hospital in Indonesia. All TB-coinfected COVID-19 patients who were hospitalized between January 2020 and December 2021 were included in the study. COVID-19 patients without TB were randomly selected for the control group. Clinical characteristics and laboratory results were assessed. Survival analysis was performed to determine the estimated death rate and median survival time (MST). Multivariate Cox regression analysis was conducted to define the association of TB coinfection with the in-hospital mortality of COVID-19.

RESULTS

We included 86 (8.3%) TB coinfections among 1034 confirmed COVID-19 patients. TB coinfection patients had younger age, malnutrition, and different symptoms compared to the COVID-19 group. TB-coinfected patients had a lower estimated death rate than the COVID-19 group (6.5 vs. 18.8 per 1000 population). MST in the COVID-19 group was 38 (interquartile range 16-47) days, whereas the same observation time failed to determine the MST in the TB coinfection group. TB coinfection had a crude hazard ratio of mortality 0.37 (95% confidence interval [CI] 0.15-0.94, P = 0. 004). The final model analysis including age, sex, and lymphocyte as confounding factors resulted in an adjusted HR of mortality 0.31 (95% CI 0.1-0.9).

CONCLUSION

This study showed TB coinfection was negatively associated with the in-hospital mortality of COVID-19.

Host Genetic Impact on Infectious Diseases among Different Ethnic Groups

Infectious diseases such as malaria, tuberculosis (TB), human immunodeficiency virus (HIV), and the coronavirus disease of 2019 (COVID-19) are problematic globally, with high prevalence particularly in Africa, attributing to most of the death rates. There have been immense efforts toward developing effective preventative and therapeutic strategies for these pathogens globally, however, some remain uncured. Disease susceptibility and progression for malaria, TB, HIV, and COVID-19 vary among individuals and are attributed to precautionary measures, environment, host, and pathogen genetics. While studying individuals with similar attributes, it is suggested that host genetics contributes to most of an individual's susceptibility to disease. Several host genes are identified to associate with these pathogens. Interestingly, many of these genes and polymorphisms are common across diseases. This paper analyzes genes and genetic variations within host genes associated with HIV, TB, malaria, and COVID-19 among different ethnic groups. The differences in host-pathogen interaction among these groups, particularly of Caucasian and African descent, and which gene polymorphisms are prevalent in an African population that possesses protection or risk to disease are reviewed. The information in this review could potentially help develop personalized treatment that could effectively combat the high disease burden in Africa.

COVID-19 and tuberculosis coinfection: A case-control study from a tertiary care center in South India

Context

Coronavirus disease 2019 (COVID-19) and tuberculosis (TB), are presently the major infectious diseases imposing a consequential public health threat and their coinfection has a significant impact on the outcome.

Aims

To evaluate the clinical features and outcomes of COVID-19-TB coinfected cases compared to solely COVID-19-infected cases.

Settings and Design

A retrospective observational study was conducted between August 1, 2020, to February 28, 2022, at a tertiary care hospital.

Materials and Methods

In this case-control study, an equal number of gender-age-matched COVID-19 and TB coinfected patients and COVID-19 cases without TB were included using simple random sampling.

Statistical Analysis Used

The data was analyzed using SPSS v 26. Categorical variables were compared using the Chi-square test, and an independent t-test or Mann-Whitney U test was applied for the quantitative variables in the univariate analysis. A P-value of less than 0.05 was considered significant.

Results

A total of 27 patients were included in each group. Upper lobe involvement (44%) and pleural effusion (22%) were significantly more common in TB-COVID-19 cases when compared to the control group (7% and 4%, respectively; P < 0.05). Moreover, median levels of C-reactive protein and ferritin were significantly higher in TB-COVID-19 coinfection.

Conclusions

Chest radiology and a higher level of certain biomarkers like C-reactive protein and ferritin can help to suspect TB in COVID-19 patients and vice-versa.

Tuberculosis and COVID-19 in the elderly: factors driving a higher burden of disease

Mycobacterium tuberculosis (M.tb) and SARS-CoV-2 are both infections that can lead to severe disease in the lower lung. However, these two infections are caused by very different pathogens (Mycobacterium vs. virus), they have different mechanisms of pathogenesis and immune response, and differ in how long the infection lasts. Despite the differences, SARS-CoV-2 and M.tb share a common feature, which is also frequently observed in other respiratory infections: the burden of disease in the elderly is greater. Here, we discuss possible reasons for the higher burden in older adults, including the effect of co-morbidities, deterioration of the lung environment, auto-immunity, and a reduced antibody response. While the answer is likely to be multifactorial, understanding the main drivers across different infections may allow us to design broader interventions that increase the health-span of older people.

Latent TB Infection, Vitamin D Status and COVID-19 Severity in Mongolian Patients

We aimed to determine potential risk factors for COVID-19 severity including serum vitamin D levels and latent TB infection among Mongolian inpatients diagnosed with COVID-19, and to study the effects of disease complications and treatment outcomes. This study included patients admitted to the Mongolian National Center for Communicable Disease, a main referral center for infectious disease in Mongolia, with COVID-19 ascertained by a positive PCR test. Patients' demographic, clinical, and laboratory data were analyzed. Of the 270 patients enrolled, 125 (46%) had mild-to-moderate illness, 86 (32%) had severe illness, and 59 (22%) had critical illness. Ten (91%) of the 11 patients who had active TB were hospitalized with severe or critical COVID-19, suggesting that they had a higher risk of falling into the severe category (OR = 10.6 [1.2; 92.0] 95% CI). Severe vitamin D deficiency (25(OH)D < 10 ng/mL) was present in 32% of the patients, but was not significantly associated with the severity of illness (p = 0.65). Older age, being male, having active TB and/or COPD were associated with greater COVID-19 severity, whereas a history of COVID-19 vaccination and the presence of a BCG vaccination scar were protective in terms of disease severity.

Tackling Drug-Resistant Tuberculosis: New Challenges from the Old Pathogen Mycobacterium tuberculosis

Antibiotics have played a crucial role in the reduction in the incidence of TB globally as evidenced by the fact that before the mid-20th century, the mortality rate within five years of the onset of the disease was 50%. The use of antibiotics has eliminated TB as a devastating disease, but the challenge of resistance to anti-TB drugs, which had already been described at the time of the introduction of streptomycin, has become a major global issue in disease management. Mismanagement of multidrug-resistant tuberculosis (MDR-TB) cases, resulting from intermittent drug use, prescription errors, and non-compliance of patients, has been identified as a critical risk factor for the development of extensively drug-resistant tuberculosis (XDR-TB). Antimicrobial resistance (AMR) in TB is a multi-factorial, complex problem of microbes evolving to escape antibiotics, the gradual decline in antibiotic development, and different economic and social conditions. In this review, we summarize recent advances in our understanding of how Mycobacterium tuberculosis evolves drug resistance. We also highlight the importance of developing shorter regimens that rapidly reach bacteria in diverse host environments, eradicating all mycobacterial populations and preventing the evolution of drug resistance. Lastly, we also emphasize that the current burden of this ancient disease is driven by a combination of complex interactions between mycobacterial and host factors, and that only a holistic approach that effectively addresses all the critical issues associated with drug resistance will limit the further spread of drug-resistant strains throughout the community.

Cross-Risk Between Tuberculosis and COVID-19 in East Java Province, Indonesia: An Analysis of Tuberculosis and COVID-19 Surveillance Registry Period 2020-2022

INTRODUCTION

Tuberculosis (TB) and COVID-19 are highly transmissible diseases and pose a serious risk to public health. Unfortunately, information on cross-risk between the two diseases was still sparse. Our main objective was to estimate the excess risk among TB patients in getting COVID-19 infection and vice versa.

METHODS

The study design was a series of analyses of existing data from TB and COVID-19 registries in East Java Province, Indonesia. The study period was from January 2020 to June 2022. Case-by-case data for this study were obtained from the registration systems for TB and COVID-19 in separate databases. In comparing risk across different groups, adjusting for differences in risk factors that influence the outcome was essential. We overcame this problem by employing a standardized morbidity ratio.

RESULTS

Among 92,424 newly diagnosed TB patients, 1,326 were subsequently infected with COVID-19 during the study period, compared with 1,679 expected. The standardized morbidity ratio (95% confidence interval) was 72.61% (60.19%, 85.03%). Among 635,946 newly diagnosed COVID-19-infected patients, 987 subsequently got active TB during the study period against 1,679 expected. The standardized morbidity ratio (95% confidence interval) was 55.33% (49.24%, 61.42%).

CONCLUSION

There was no evidence of excess risk in either direction, the excess risk among TB patients in getting COVID-19 infection and vice versa.

Initial immune response after exposure to Mycobacterium tuberculosis or to SARS-COV-2: similarities and differences

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) and Coronavirus disease-2019 (COVID-19), whose etiologic agent is severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), are currently the two deadliest infectious diseases in humans, which together have caused about more than 11 million deaths worldwide in the past 3 years. TB and COVID-19 share several aspects including the droplet- and aerosol-borne transmissibility, the lungs as primary target, some symptoms, and diagnostic tools. However, these two infectious diseases differ in other aspects as their incubation period, immune cells involved, persistence and the immunopathological response. In this review, we highlight the similarities and differences between TB and COVID-19 focusing on the innate and adaptive immune response induced after the exposure to Mtb and SARS-CoV-2 and the pathological pathways linking the two infections. Moreover, we provide a brief overview of the immune response in case of TB-COVID-19 co-infection highlighting the similarities and differences of each individual infection. A comprehensive understanding of the immune response involved in TB and COVID-19 is of utmost importance for the design of effective therapeutic strategies and vaccines for both diseases.

Combined System for the Simultaneous Delivery of Levofloxacin and Rifampicin: Structural and Functional Properties and Antibacterial Activity

The therapy of resistant forms of tuberculosis requires the simultaneous use of several drugs, in particular, a combination of rifampicin and levofloxacin. In this paper, we aimed to design a combined system for the simultaneous delivery of these drugs for potential inhalation administration. A feature of this system is the incorporation of rifampicin into optimized liposomal vesicles capable of forming a multipoint non-covalent complex with chitosan-β-cyclodextrin conjugates. Levofloxacin is incorporated into cyclodextrin tori by forming a host-guest complex. Here, a comprehensive study of the physicochemical properties of the obtained systems was carried out and special attention was paid to the kinetics of cargo release for individual drugs and in the combined system. The release of levofloxacin in combined system is slow and is described by the Higuchi model in all cases. The release of rifampicin from liposomes during the formation of complexes with polymeric conjugates is characterized by the change of the Higuchi model to the Korsmeyer-Peppas model with the main type of diffusion against Fick's law. Microbiological studies in solid and liquid growth media a consistently high antibacterial activity of the obtained systems was shown against B. subtilis and E. coli.

Deep Learning Classification of Tuberculosis Chest X-rays

Background Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. It primarily affects the lungs but can also affect other organs, such as the kidneys, bones, and brain. TB is transmitted through the air when an infected individual coughs, sneezes, or speaks, releasing tiny droplets containing the bacteria. Despite significant efforts to combat TB, challenges such as drug resistance, co-infection with human immunodeficiency virus (HIV), and limited resources in high-burden settings continue to pose obstacles to its eradication. TB remains a significant global health challenge, necessitating accurate and timely detection for effective management.  Methods This study aimed to develop a TB detection model using chest X-ray images obtained from Kaggle.com, utilizing Google's Collaboration Platform. Over 1196 chest X-ray images, comprising both TB-positive and normal cases, were employed for model development. The model was trained to recognize patterns within the TB chest X-rays to efficiently recognize TB within patients in order to be treated in time. Results The model achieved an average precision of 0.934, with precision and recall values of 94.1% each, indicating its high accuracy in classifying TB-positive and normal cases. Sensitivity and specificity values were calculated as 96.85% and 91.49%, respectively. The F1 score was also calculated to be 0.941. The overall accuracy of the model was found to be 94%.  Conclusion These results highlight the potential of machine learning algorithms for TB detection using chest X-ray images. Further validation studies and research efforts are needed to assess the model's generalizability and integration into clinical practice, ultimately facilitating early detection and improved management of TB.

Mycobacterium tuberculosis and SARS-CoV-2 co-infections: The knowns and unknowns

Health impacts of Mycobacterium tuberculosis (Mtb) and SARS-CoV-2 co-infections are not fully understood. Both pathogens modulate host responses and induce immunopathology with extensive lung damage. With a quarter of the world's population harboring latent TB, exploring the relationship between SARS-CoV-2 infection and its effect on the transition of Mtb from latent to active form is paramount to control this pathogen. The effects of active Mtb infection on establishment and severity of COVID-19 are also unknown, despite the ability of TB to orchestrate profound long-lasting immunopathologies in the lungs. Absence of mechanistic studies and co-infection models hinder the development of effective interventions to reduce the health impacts of SARS-CoV-2 and Mtb co-infection. Here, we highlight dysregulated immune responses induced by SARS-CoV-2 and Mtb, their potential interplay, and implications for co-infection in the lungs. As both pathogens master immunomodulation, we discuss relevant converging and diverging immune-related pathways underlying SARS-CoV-2 and Mtb co-infections.

Transforming growth factor β (TGF-β) pathway in the immunopathogenesis of multiple sclerosis (MS); molecular approaches

INTRODUCTION

Multiple sclerosis (MS) is an acute demyelinating disease with an autoimmune nature, followed by gradual neurodegeneration and enervating scar formation. Dysregulated immune response is a crucial dilemma contributing to the pathogenesis of MS. The role of chemokines and cytokines, such as transforming growth factor-β (TGF-β), have been recently highlighted regarding their altered expressions in MS. TGF-β has three isoforms, TGF-β1, TGF-β2, and TGF-β3, that are structurally similar; however, they can show different functions.

RESULTS

All three isoforms are known to induce immune tolerance by modifying Foxp3⁺ regulatory T cells. Nevertheless, there are controversial reports concerning the role of TGF-β1 and 2 in the progression of scar formation in MS. At the same time, these proteins also improve oligodendrocyte differentiation and have shown neuroprotective behavior, two cellular processes that suppress the pathogenesis of MS. TGF-β3 shares the same properties but is less likely contributes to scar formation, and its direct role in MS remains elusive.

DISCUSSION

To develop novel neuroimmunological treatment strategies for MS, the optimal strategy could be the one that causes immune modulation, induces neurogenesis, stimulates remyelination, and prevents excessive scar formation. Therefore, regarding its immunological properties, TGF-β could be an appropriate candidate; however, contradictory results of previous studies have questioned its role and therapeutic potential in MS. In this review article, we provide an overview of the role of TGF-β in immunopathogenesis of MS, related clinical and animal studies, and the treatment potential of TGF-β in MS, emphasizing the role of different TGF-β isoforms.

Superimposed Pulmonary Tuberculosis (PTB) in a 26-Year-Old Female with No Underlying Co-Morbidities Recovering from COVID-19-Case Report

Tuberculosis before the COVID-19 pandemic is said to have killed more people globally than any other communicable disease and is ranked the 13th cause of death, according to the WHO. Tuberculosis also still remains highly endemic, especially in LIMCs with a high burden of people living with HIV/AIDS, in which it is the leading cause of mortality. Given the risk factors associated with COVID-19, the cross similarities between tuberculosis and COVID-19 symptoms, and the paucity of data on how both diseases impact each other, there is a need to generate more information on COVID-19-TB co-infection. In this case report, we present a young female patient of reproductive age with no underlying comorbidities recovering from COVID-19, who later presented with pulmonary tuberculosis. It describes the series of investigations performed and treatments given during the follow-up. There is a need for more surveillance for possible COVID-19-TB co-infection cases and further research to understand the impact of COVID-19 on tuberculosis and vice versa, especially in LMICs.

Biofilms possibly harbor occult SARS-CoV-2 may explain lung cavity, re-positive and long-term positive results

During the COVID-19 pandemic, there have been an increasing number of COVID-19 patients with cavitary or cystic lung lesions, re-positive or long-term positive nucleic acid tests, but the mechanism is still unclear. Lung cavities may appear at long time interval from initial onset of coronavirus infection, generally during the absorption phase of the disease. The main histopathological characteristic is diffuse alveolar damage and may have more severe symptoms after initial recovery from COVID-19 and an increased mortality rate. There are many possible etiologies of pulmonary cavities in COVID-19 patients and we hypothesize that occult SARS-CoV-2, in the form of biofilm, is harbored in the airway lacuna with other pathogenic microorganisms, which may be the cause of pulmonary cavities and repeated and long-term positive nucleic acid tests.