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Updated: Sep 19, 2026

Demonstrating a Multi-drug Resistant Mycobacterium tuberculosis Amplification Microarray
Published on: April 25, 2014
Molecular Signatures of Concurrent Mutations in Drug Resistant Mycobacterium Tuberculosis: Association with Treatment
Nikita Panwalkar1, Zeba Khan1, Aseem Rangnekar1
1Department of Microbiology, Bhopal Memorial Hospital and Research Centre, Bhopal, M.P. 462038 India.
Background:
Mutations in genes responsible for resistance to anti tubercular drugs are pivotal in the emergence of drug resistant tuberculosis. Although studies have examined individual resistance mutations, the impact of concurrent mutations on treatment outcomes remains insufficiently understood. This study aimed to investigate the concurrent mutations in genes responsible for first and second line drug resistance in Mycobacterium tuberculosis (MTB) isolates and their association with treatment outcomes.
Methods:
A line probe assay was conducted to identify mutations that confer resistance to first and second line drugs. Treatment outcomes were extracted from the Ni-kshay portal (a Government initiated online portal to maintain TB patient data).
Results:
86.1% of patients achieved successful treatment outcomes, while 13.8% experienced unsuccessful outcomes. The concurrent mutations in genes (gyrA, rpoB, and katG) were associated with higher odds of unsuccessful treatment outcome (OR = 3.27, 95% CI: 0.89-12.03); however, this association was not statistically significant. Six concurrent mutation patterns were observed in MTB isolates from patients with unsuccessful outcomes only.
Conclusion:
MTB isolates harbouring concurrent mutations were predominantly associated with successful treatment outcomes. These findings suggest that the presence of multiple mutations alone may not necessarily predict an increased risk of treatment failure. Although the coexistence of multiple mutations may contribute cumulatively to drug resistance, further studies involving larger, multicentric cohorts are required to validate our findings and support mutation-based risk stratification in drug resistant TB management.
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