Context:
The Department of Biotechnology (DBT) has completed the genomic sequencing of a third, or 10,000 samples, of the target of 32,500 samples of mycobacterium tuberculosis the bacteria behind tuberculosis (TB) in a bid to improve the understanding of drug-resistant TB and capture unique genomic features of the TB bacterium in India. Of the sequenced samples, 7% are said to be resistant to a single drug.
Overview of the Initiative
- Launched by: Department of Biotechnology (DBT), Ministry of Science and Technology.
- Programme: Part of Data-Driven Research to Eradicate TB (Dare2eraD TB).
- Goal: Genomic sequencing of 32,500 Mycobacterium tuberculosis samples.
- Progress:
- 10,000 samples sequenced (one-third of target).
- Completion target: October 2025.
- Consortium Members:
- DBT, Council of Scientific and Industrial Research (CSIR), Indian Council of Medical Research (ICMR).
- Collective body: Indian Tuberculosis Genomic Surveillance Consortium.
- Genomic sequencing is a laboratory method used to determine the complete DNA sequence of an organism or cell type, providing insights into genetic makeup, disease, and evolutionary relationships.
Findings From Sequenced Samples
- Drug Resistance:
- 7% of sequenced TB strains showed resistance to a single drug.
- Demographic Insights:
- Majority of TB patients are between 18-45 years of age.
- Many patients are diabetic and underweight, indicating comorbidities.
National TB Eradication Goals
- India’s target: Eradicate TB by 2025, five years ahead of WHO’s 2030 target.
- Current TB prevalence (as of 2022):
- 1,990 cases per million, down from 2,370 per million in 2015.
- WHO’s elimination benchmark: 1 case per million.
- India’s share: Contributes to 28% of global new TB cases.
Challenges Highlighted
- Drug-Resistant TB:
- Major concern for treatment and public health.
- Latent TB Pool:
- Potentially up to 3,000 per million carry latent TB infections, facilitating undetected spread.
- Time-Consuming Testing:
- Current diagnostic confirmation can take up to three weeks.
Future Strategies
- Use of Artificial Intelligence (AI):
- Potential to reduce TB testing duration from three weeks to one week.
- Genomic insights:
- Aim to develop faster, more precise diagnostics and understand regional and genetic variations in TB strains.
Significance
- Global Impact: Progress in India is pivotal for global TB elimination efforts.
- Public Health Policy: Data will help shape drug development, targeted interventions, and national TB control strategies.
Source: TH
