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Abstract
Background: There were over 10.0 million cases of tuberculosis (TB) in the world in 2018, a number that has been relatively stable in recent years. The burden of the disease varies enormously among countries per year with most cases occurring in the WHO regions of South-East Asia (44%), Africa (24%), and the Western Pacific (18%). Based on the epidemic theory, epidemics continue to occur when one index case is replaced by one or more cases. This study addresses the problem of ongoing transmission of Mycobacterium tuberculosis (Mtb) in Sub-Saharan Africa by exploiting Mtb whole genome sequences, drug resistance candidate gene mutations, and interferon-gamma (IFN-γ) cytokine as biomarkers.
Methods: A cross-sectional and longitudinal study conducted in Rubaga division in Kampala Uganda were the data sources for this study. The time cough symptoms started, social network distances, drug resistance candidate gene mutations, and genetic distances among TB cases were analyzed to determine the transmission tree, reproduction numbers, identifiability score, and factors associated with being a source of infections. Concentrations of Mtb-specific antigen-induced IFN-γ cytokine in blood were quantified in Mtb uninfected, recently infected and remotely infected individuals.
Results: A total of 15 transmission clusters with the largest cluster comprising of 12 members and the smallest cluster of 2 members were identified. There were 36 (58.1%) individuals who were identified as potential sources of infection. MTBC genomes were classified as 78 % (62/79) Lineage four (L4), 18 % (14/79) L2 and 4 % (3/79) L3. Based on a certainty score of 20%, 5 transmission clusters were identified. Ancestor genomes were inversely associated with mutations in the rrs and rrl genes and positively associated with mutations in gyrA, ribD and ethR genes. Lastly, mean Interferon-γ blood levels in recently infected individuals were intermediate between uninfected and those with established infection and accurately predicted 69% of recently infected individuals at an optimal cutoff value of 2.58 IU/ml.
Conclusion: An identifiability score, MTBC lineage four strain-specific drug resistance candidate gene mutations, and interferon-γ can sufficiently identify individuals who are sources of TB infection or persons recently infected with Mtb in the community.
Methods: A cross-sectional and longitudinal study conducted in Rubaga division in Kampala Uganda were the data sources for this study. The time cough symptoms started, social network distances, drug resistance candidate gene mutations, and genetic distances among TB cases were analyzed to determine the transmission tree, reproduction numbers, identifiability score, and factors associated with being a source of infections. Concentrations of Mtb-specific antigen-induced IFN-γ cytokine in blood were quantified in Mtb uninfected, recently infected and remotely infected individuals.
Results: A total of 15 transmission clusters with the largest cluster comprising of 12 members and the smallest cluster of 2 members were identified. There were 36 (58.1%) individuals who were identified as potential sources of infection. MTBC genomes were classified as 78 % (62/79) Lineage four (L4), 18 % (14/79) L2 and 4 % (3/79) L3. Based on a certainty score of 20%, 5 transmission clusters were identified. Ancestor genomes were inversely associated with mutations in the rrs and rrl genes and positively associated with mutations in gyrA, ribD and ethR genes. Lastly, mean Interferon-γ blood levels in recently infected individuals were intermediate between uninfected and those with established infection and accurately predicted 69% of recently infected individuals at an optimal cutoff value of 2.58 IU/ml.
Conclusion: An identifiability score, MTBC lineage four strain-specific drug resistance candidate gene mutations, and interferon-γ can sufficiently identify individuals who are sources of TB infection or persons recently infected with Mtb in the community.