Dataset Information

The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis.

ABSTRACT:

Background

Drug resistance poses a serious challenge for the control of tuberculosis in many settings. It is well established that the expected future trend in resistance depends on the reproductive fitness of drug-resistant Mycobacterium tuberculosis. However, the variability in fitness between strains with different resistance-conferring mutations has been largely ignored when making these predictions.

Methods

We developed a novel approach for incorporating the variable fitness costs of drug resistance-conferring mutations and for tracking this distribution of fitness costs over time within a transmission model. We used this approach to describe the effects of realistic fitness cost distributions on the future prevalence of drug-resistant tuberculosis.

Results

The shape of the distribution of fitness costs was a strong predictor of the long-term prevalence of resistance. While, as expected, lower average fitness costs of drug resistance-conferring mutations were associated with more severe epidemics of drug-resistant tuberculosis, fitness distributions with greater variance also led to higher levels of drug resistance. For example, compared to simulations in which the fitness cost of resistance was fixed, introducing a realistic amount of variance resulted in a 40% increase in prevalence of drug-resistant tuberculosis after 20 years.

Conclusions

The differences in the fitness costs associated with drug resistance-conferring mutations are a key determinant of the future burden of drug-resistant tuberculosis. Future studies that can better establish the range of fitness costs associated with drug resistance-conferring mutations will improve projections and thus facilitate better public health planning efforts.

SUBMITTER: Knight GM

PROVIDER: S-EPMC4583567 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Publications

The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis.

Knight Gwenan M GM Colijn Caroline C Shrestha Sourya S Fofana Mariam M Cobelens Frank F White Richard G RG Dowdy David W DW Cohen Ted T

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20151001

<h4>Background</h4>Drug resistance poses a serious challenge for the control of tuberculosis in many settings. It is well established that the expected future trend in resistance depends on the reproductive fitness of drug-resistant Mycobacterium tuberculosis. However, the variability in fitness between strains with different resistance-conferring mutations has been largely ignored when making these predictions.<h4>Methods</h4>We developed a novel approach for incorporating the variable fitness ...[more]

PMID: 26409276

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Project description:Extensively drug-resistant tuberculosis (XDR-TB), defined as resistance to at least isoniazid (INH), rifampicin (RIF), a fluoroquinolone (FQ) and a second-line injectable drug (SLID), is difficult to treat and poses a major threat to TB control. The transmission dynamics and distribution of XDR Mycobacterium tuberculosis (Mtb) strains have not been thoroughly investigated. Using whole genome sequencing data on 461 XDR-Mtb strains, we aimed to investigate the geographical distribution of XDR-Mtb strains in the Western Cape Province of South Africa over a 10 year period (2006-2017) and assess the association between Mtb sub-lineage, age, gender, geographical patient location and membership or size of XDR-TB clusters. First, we identified transmission clusters by excluding drug resistance-conferring mutations and using the 5 SNP cutoff, followed by merging clusters based on their most recent common ancestor. We then consecutively included variants conferring resistance to INH, RIF, ethambutol (EMB), pyrazinamide (PZA), SLIDs and FQs in the cluster definition. Cluster sizes were classified as small (2-4 isolates), medium (5-20 isolates), large (21-100 isolates) or very large (>100 isolates) to reflect the success of individual strains. We found that most XDR-TB strains were clustered and that including variants conferring resistance to INH, RIF, EMB, PZA and SLIDs in the cluster definition did not significantly reduce the proportion of clustered isolates (85.5-82.2 %) but increased the number of patients belonging to small clusters (4.3-12.4 %, P=0.56). Inclusion of FQ resistance-conferring variants had the greatest effect, with 11 clustered isolates reclassified as unique while the number of clusters increased from 17 to 37. Lineage 2 strains (lineage 2.2.1 typical Beijing or lineage 2.2.2 atypical Beijing) showed the large clusters which were spread across all health districts of the Western Cape Province. We identified a significant association between residence in the Cape Town metropole and cluster membership (P=0.016) but no association between gender, age and cluster membership or cluster size (P=0.39). Our data suggest that the XDR-TB epidemic in South Africa probably has its origin in the endemic spread of MDR Mtb and pre-XDR Mtb strains followed by acquisition of FQ resistance, with more limited transmission of XDR Mtb strains. This only became apparent with the inclusion of drug resistance-conferring variants in the definition of a cluster. In addition to the prevention of amplification of resistance, rapid diagnosis of MDR, pre-XDR and XDR-TB and timely initiation of appropriate treatment is needed to reduce transmission of difficult-to-treat TB.

Project description:BackgroundMultidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis are emerging worldwide. The Green Light Committee initiative supported programmatic management of drug-resistant tuberculosis in 90 countries. We used estimates from the Preserving Effective TB Treatment Study to predict MDR and XDR tuberculosis trends in four countries with a high burden of MDR tuberculosis: India, the Philippines, Russia, and South Africa.MethodsWe calibrated a compartmental model to data from drug resistance surveys and WHO tuberculosis reports to forecast estimates of incident MDR and XDR tuberculosis and the percentage of incident MDR and XDR tuberculosis caused by acquired drug resistance, assuming no fitness cost of resistance from 2000 to 2040 in India, the Philippines, Russia, and South Africa.FindingsThe model forecasted the percentage of MDR tuberculosis among incident cases of tuberculosis to increase, reaching 12·4% (95% prediction interval 9·4-16·2) in India, 8·9% (4·5-11·7) in the Philippines, 32·5% (27·0-35·8) in Russia, and 5·7% (3·0-7·6) in South Africa in 2040. It also predicted the percentage of XDR tuberculosis among incident MDR tuberculosis to increase, reaching 8·9% (95% prediction interval 5·1-12·9) in India, 9·0% (4·0-14·7) in the Philippines, 9·0% (4·8-14·2) in Russia, and 8·5% (2·5-14·7) in South Africa in 2040. Acquired drug resistance would cause less than 30% of incident MDR tuberculosis during 2000-40. Acquired drug resistance caused 80% of incident XDR tuberculosis in 2000, but this estimate would decrease to less than 50% by 2040.InterpretationMDR and XDR tuberculosis were forecast to increase in all four countries despite improvements in acquired drug resistance shown by the Green Light Committee-supported programmatic management of drug-resistant tuberculosis. Additional control efforts beyond improving acquired drug resistance rates are needed to stop the spread of MDR and XDR tuberculosis in countries with a high burden of MDR tuberculosis.FundingUS Agency for International Development and US Centers for Disease Control and Prevention, Division of Tuberculosis Elimination.

Dataset Information

The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis.

Background

Methods

Results

Conclusions

Publications

The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis.

Similar Datasets

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