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Within-Host Heterogeneity of Mycobacterium tuberculosis Infection Is Associated With Poor Early Treatment Response: A Prospective Cohort Study.

ABSTRACT: The clinical management of tuberculosis is a major challenge in southern Africa. The prevalence of within-host genetically heterogeneous Mycobacterium tuberculosis infection and its effect on treatment response are not well understood. We enrolled 500 patients with tuberculosis in KwaZulu-Natal and followed them through 2 months of treatment. Using mycobacterial interspersed repetitive units-variable number of tandem repeats genotyping to identify mycobacterial heterogeneity, we report the prevalence and evaluate the association of heterogeneity with treatment response. Upon initiation of treatment, 21.1% of participants harbored a heterogeneous M. tuberculosis infection; such heterogeneity was independently associated with a nearly 2-fold higher odds of persistent culture positivity after 2 months of treatment (adjusted odds ratio, 1.90; 95% confidence interval, 1.03-3.50).

SUBMITTER: Cohen T

PROVIDER: S-EPMC4857469 | biostudies-other | 2016 Jun

REPOSITORIES: biostudies-other

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Within-Host Heterogeneity of Mycobacterium tuberculosis Infection Is Associated With Poor Early Treatment Response: A Prospective Cohort Study.

Cohen Ted T Chindelevitch Leonid L Misra Reshma R Kempner Maria E ME Galea Jerome J Moodley Prashini P Wilson Douglas D

The Journal of infectious diseases 20160114 11

The clinical management of tuberculosis is a major challenge in southern Africa. The prevalence of within-host genetically heterogeneous Mycobacterium tuberculosis infection and its effect on treatment response are not well understood. We enrolled 500 patients with tuberculosis in KwaZulu-Natal and followed them through 2 months of treatment. Using mycobacterial interspersed repetitive units-variable number of tandem repeats genotyping to identify mycobacterial heterogeneity, we report the preva ...[more]

PMID: 26768249

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Project description:Genomic tools have revealed genetically diverse pathogens within some hosts. Within-host pathogen diversity, which we refer to as "complex infection", is increasingly recognized as a determinant of treatment outcome for infections like tuberculosis. Complex infection arises through two mechanisms: within-host mutation (which results in clonal heterogeneity) and reinfection (which results in mixed infections). Estimates of the frequency of within-host mutation and reinfection in populations are critical for understanding the natural history of disease. These estimates influence projections of disease trends and effects of interventions. The genotyping technique MLVA (multiple loci variable-number tandem repeats analysis) can identify complex infections, but the current method to distinguish clonal heterogeneity from mixed infections is based on a rather simple rule. Here we describe ClassTR, a method which leverages MLVA information from isolates collected in a population to distinguish mixed infections from clonal heterogeneity. We formulate the resolution of complex infections into their constituent strains as an optimization problem, and show its NP-completeness. We solve it efficiently by using mixed integer linear programming and graph decomposition. Once the complex infections are resolved into their constituent strains, ClassTR probabilistically classifies isolates as clonally heterogeneous or mixed by using a model of tandem repeat evolution. We first compare ClassTR with the standard rule-based classification on 100 simulated datasets. ClassTR outperforms the standard method, improving classification accuracy from 48% to 80%. We then apply ClassTR to a sample of 436 strains collected from tuberculosis patients in a South African community, of which 92 had complex infections. We find that ClassTR assigns an alternate classification to 18 of the 92 complex infections, suggesting important differences in practice. By explicitly modeling tandem repeat evolution, ClassTR helps to improve our understanding of the mechanisms driving within-host diversity of pathogens like Mycobacterium tuberculosis.

Project description:BackgroundStudying within-host genetic diversity of Mycobacterium tuberculosis (Mtb) in patients during treatment may identify adaptations to antibiotic and immune pressure. Understanding the significance of genetic heteroresistance, and more specifically heterozygous resistance-associated variants (RAVs), is clinically important given increasing use of rapid molecular tests and whole genome sequencing (WGS).MethodsWe analyse data from six studies in KwaZulu-Natal, South Africa. Most patients (>75%) had baseline rifampicin resistance. Sputum was collected for culture at baseline and at between two and nine intervals until month six. Positive cultures underwent WGS. Mixed infections and reinfections were excluded from analysis.FindingsBaseline Mtb overall genetic diversity (at treatment initiation or major change to regimen) was associated with cavitary disease, not taking antiretroviral therapy if HIV infected, infection with lineage 2 strains and absence of second-line drug resistance on univariate analyses. Baseline genetic diversity was not associated with six-month outcome. Genetic diversity increased from baseline to weeks one and two before returning to previous levels. Baseline genetic heteroresistance was most common for bedaquiline (6/10 [60%] of isolates with RAVs) and fluoroquinolones (9/62 [13%]). Most patients with heterozygous RAVs on WGS with sequential isolates available demonstrated RAV persistence or fixation (17/20, 85%). New RAVs emerged in 9/286 (3%) patients during treatment. We could detect low-frequency RAVs preceding emergent resistance in only one case, although validation of deep sequencing to detect rare variants is required.InterpretationIn this study of single-strain Mtb infections, baseline within-host bacterial genetic diversity did not predict outcome but may reveal adaptations to host and drug pressures. Predicting emergent resistance from low-frequency RAVs requires further work to separate transient from consequential mutations.FundingWellcome Trust, NIH/NIAID.

Dataset Information

Within-Host Heterogeneity of Mycobacterium tuberculosis Infection Is Associated With Poor Early Treatment Response: A Prospective Cohort Study.

Publications

Within-Host Heterogeneity of Mycobacterium tuberculosis Infection Is Associated With Poor Early Treatment Response: A Prospective Cohort Study.

Similar Datasets

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