Multidrug-resistant tuberculosis.

Tuberculosis (TB) remains the foremost cause of death by an infectious disease globally. Multidrug-resistant or rifampicin-resistant TB (MDR/RR-TB; resistance to rifampicin and isoniazid, or rifampicin alone) is a burgeoning public health challenge in several parts of the world, and especially Eastern Europe, Russia, Asia and sub-Saharan Africa. Pre-extensively drug-resistant TB (pre-XDR-TB) refers to MDR/RR-TB that is also resistant to a fluoroquinolone, and extensively drug-resistant TB (XDR-TB) isolates are additionally resistant to other key drugs such as bedaquiline and/or linezolid. Collectively, these subgroups are referred to as drug-resistant TB (DR-TB). All forms of DR-TB can be as transmissible as rifampicin-susceptible TB; however, it is more difficult to diagnose, is associated with higher mortality and morbidity, and higher rates of post-TB lung damage. The various forms of DR-TB often consume >50% of national TB budgets despite comprising <5-10% of the total TB case-load. The past decade has seen a dramatic change in the DR-TB treatment landscape with the introduction of new diagnostics and therapeutic agents. However, there is limited guidance on understanding and managing various aspects of this complex entity, including the pathogenesis, transmission, diagnosis, management and prevention of MDR-TB and XDR-TB, especially at the primary care physician level.

The epidemiology, transmission, diagnosis, and management of drug-resistant tuberculosis-lessons from the South African experience.

Drug-resistant tuberculosis (DR-TB) threatens to derail tuberculosis control efforts, particularly in Africa where the disease remains out of control. The dogma that DR-TB epidemics are fueled by unchecked rates of acquired resistance in inadequately treated or non-adherent individuals is no longer valid in most high DR-TB burden settings, where community transmission is now widespread. A large burden of DR-TB in Africa remains undiagnosed due to inadequate access to diagnostic tools that simultaneously detect tuberculosis and screen for resistance. Furthermore, acquisition of drug resistance to new and repurposed drugs, for which diagnostic solutions are not yet available, presents a major challenge for the implementation of novel, all-oral, shortened (6-9 months) treatment. Structural challenges including poverty, stigma, and social distress disrupt engagement in care, promote poor treatment outcomes, and reduce the quality of life for people with DR-TB. We reflect on the lessons learnt from the South African experience in implementing state-of-the-art advances in diagnostic solutions, deploying recent innovations in pharmacotherapeutic approaches for rapid cure, understanding local transmission dynamics and implementing interventions to curtail DR-TB transmission, and in mitigating the catastrophic socioeconomic costs of DR-TB. We also highlight globally relevant and locally responsive research priorities for achieving DR-TB control in South Africa.

Genotype-Phenotype Characterization of Serial Mycobacterium tuberculosis Isolates in Bedaquiline-Resistant Tuberculosis.

BACKGROUND: Emerging resistance to bedaquiline (BDQ) threatens to undermine advances in the treatment of drug-resistant tuberculosis (DRTB). Characterizing serial Mycobacterium tuberculosis (Mtb) isolates collected during BDQ-based treatment can provide insights into the etiologies of BDQ resistance in this important group of DRTB patients. METHODS: We measured mycobacteria growth indicator tube (MGIT)-based BDQ minimum inhibitory concentrations (MICs) of Mtb isolates collected from 195 individuals with no prior BDQ exposure who were receiving BDQ-based treatment for DRTB. We conducted whole-genome sequencing on serial Mtb isolates from all participants who had any isolate with a BDQ MIC >1 collected before or after starting treatment (95 total Mtb isolates from 24 participants). RESULTS: Sixteen of 24 participants had BDQ-resistant TB (MGIT MIC ≥4 µg/mL) and 8 had BDQ-intermediate infections (MGIT MIC = 2 µg/mL). Participants with pre-existing resistance outnumbered those with resistance acquired during treatment, and 8 of 24 participants had polyclonal infections. BDQ resistance was observed across multiple Mtb strain types and involved a diverse catalog of mmpR5 (Rv0678) mutations, but no mutations in atpE or pepQ. Nine pairs of participants shared genetically similar isolates separated by <5 single nucleotide polymorphisms, concerning for potential transmitted BDQ resistance. CONCLUSIONS: BDQ-resistant TB can arise via multiple, overlapping processes, including transmission of strains with pre-existing resistance. Capturing the within-host diversity of these infections could potentially improve clinical diagnosis, population-level surveillance, and molecular diagnostic test development.

The effect of M. tuberculosis lineage on clinical phenotype.

Six lineages of Mycobacterium tuberculosis sensu stricto (which excludes M. africanum) are described. Single-country or small observational data suggest differences in clinical phenotype between lineages. We present strain lineage and clinical phenotype data from 12,246 patients from 3 low-incidence and 5 high-incidence countries. We used multivariable logistic regression to explore the effect of lineage on site of disease and on cavities on chest radiography, given pulmonary TB; multivariable multinomial logistic regression to investigate types of extra-pulmonary TB, given lineage; and accelerated failure time and Cox proportional-hazards models to explore the effect of lineage on time to smear and culture-conversion. Mediation analyses quantified the direct effects of lineage on outcomes. Pulmonary disease was more likely among patients with lineage(L) 2, L3 or L4, than L1 (adjusted odds ratio (aOR) 1.79, (95% confidence interval 1.49-2.15), p<0.001; aOR = 1.40(1.09-1.79), p = 0.007; aOR = 2.04(1.65-2.53), p<0.001, respectively). Among patients with pulmonary TB, those with L1 had greater risk of cavities on chest radiography versus those with L2 (aOR = 0.69(0.57-0.83), p<0.001) and L4 strains (aOR = 0.73(0.59-0.90), p = 0.002). L1 strains were more likely to cause osteomyelitis among patients with extra-pulmonary TB, versus L2-4 (p = 0.033, p = 0.008 and p = 0.049 respectively). Patients with L1 strains showed shorter time-to-sputum smear conversion than for L2. Causal mediation analysis showed the effect of lineage in each case was largely direct. The pattern of clinical phenotypes seen with L1 strains differed from modern lineages (L2-4). This has implications for clinical management and could influence clinical trial selection strategies.

New Horizons in the Diagnosis of Tuberculosis of the Spine: The Role of Whole Genome Sequencing.

STUDY DESIGN: Prospective study. PURPOSE: To evaluate the utility of whole genome sequencing (WGS) in drug resistance testing, lineage of the organisms, and organism- related factors responsible for bacilli settling in the spine. OVERVIEW OF LITERATURE: The workstream for the diagnosis of tuberculosis (TB) involves isolation and culture of the organism and drug resistance testing using phenotypic methods. Xpert MTB/RIF Ultra is a genetic-based method that detects for Mycobacterium tuberculosis DNA in the rpoB gene. Meanwhile, WGS is a newer genetic-based method that assesses the whole genome of the bacterium. Very few studies have reported the use of WGS for extrapulmonary TB. Herein, we used WGS to diagnose spinal TB. METHODS: Tissues from 61 patients undergoing surgery for spinal TB underwent histologic examination, Xpert MTB/RIF Ultra, and culture and sensitivity testing. DNA from the cultured bacteria was sent for WGS. The test bacterial genome was compared to a reference strain of pulmonary TB. RESULTS: Acid-fast bacilli were observed in 9/58 specimens. Meanwhile, histology confirmed TB in all the patients. Bacilli were cultured in 28 patients (48.3%), and the average time to culture was 18.7 days. Xpert MTB/RIF Ultra was positive in 47 patients (85%). WGS was performed in 23 specimens. Overall, 45% of the strains belonged to lineage 2 (East Asian). There was one case of multidrug- resistant TB and two cases of non-tuberculous mycobacteria on WGS. We could not confirm any genomic difference between pulmonary and spinal TB strains. CONCLUSIONS: Xpert MTB/RIF Ultra of tissues or pus is the investigation of choice when diagnosing spinal TB. Meanwhile, WGS can diagnose multidrug-resistant TB and non-tuberculous mycobacteria more accurately. No mutations were identified in spinal and pulmonary TB bacteria.

The effect of M. tuberculosis lineage on clinical phenotype.

Eight lineages of Mycobacterium tuberculosis sensu stricto are described. Single-country or small observational data suggest differences in clinical phenotype between lineages. We present strain lineage and clinical phenotype data from 12,246 patients from 3 low-incidence and 5 high-incidence countries. We used multivariable logistic regression to explore the effect of lineage on site of disease and on cavities on chest radiography, given pulmonary TB; multivariable multinomial logistic regression to investigate types of extra-pulmonary TB, given lineage; and accelerated failure time and Cox proportional-hazards models to explore the effect of lineage on time to smear and culture-conversion. Mediation analyses quantified the direct effects of lineage on outcomes. Pulmonary disease was more likely among patients with lineage(L) 2, L3 or L4, than L1 (adjusted odds ratio (aOR) 1.79, (95% confidence interval 1.49-2.15), p<0.001; aOR=1.40(1.09-1.79), p=0.007; aOR=2.04(1.65-2.53), p<0.001, respectively). Among patients with pulmonary TB, those with L1 had greater risk of cavities on chest radiography versus those with L2 (aOR=0.69(0.57-0.83), p<0.001) and L4 strains (aOR=0.73(0.59-0.90), p=0.002). L1 strains were more likely to cause osteomyelitis among patients with extra-pulmonary TB, versus L2-4 (p=0.033, p=0.008 and p=0.049 respectively). Patients with L1 strains showed shorter time-to-sputum smear conversion than for L2. Causal mediation analysis showed the effect of lineage in each case was largely direct. The pattern of clinical phenotypes seen with L1 strains differed from modern lineages (L2-4). This has implications for clinical management and could influence clinical trial selection strategies.

Assessment of epidemiological and genetic characteristics and clinical outcomes of resistance to bedaquiline in patients treated for rifampicin-resistant tuberculosis: a cross-sectional and longitudinal study.

BACKGROUND: Bedaquiline improves outcomes of patients with rifampicin-resistant and multidrug-resistant (MDR) tuberculosis; however, emerging resistance threatens this success. We did a cross-sectional and longitudinal analysis evaluating the epidemiology, genetic basis, and treatment outcomes associated with bedaquiline resistance, using data from South Africa (2015-19). METHODS: Patients with drug-resistant tuberculosis starting bedaquiline-based treatment had surveillance samples submitted at baseline, month 2, and month 6, along with demographic information. Culture-positive baseline and post-baseline isolates had phenotypic resistance determined. Eligible patients were aged 12 years or older with a positive culture sample at baseline or, if the sample was invalid or negative, a sample within 30 days of the baseline sample submitted for bedaquiline drug susceptibility testing. For the longitudinal study, the first surveillance sample had to be phenotypically susceptible to bedaquiline for inclusion. Whole-genome sequencing was done on bedaquiline-resistant isolates and a subset of bedaquiline-susceptible isolates. The National Institute for Communicable Diseases tuberculosis reference laboratory, and national tuberculosis surveillance databases were matched to the Electronic Drug-Resistant Tuberculosis Register. We assessed baseline resistance prevalence, mutations, transmission, cumulative resistance incidence, and odds ratios (ORs) associating risk factors for resistance with patient outcomes. FINDINGS: Between Jan 1, 2015, and July 31, 2019, 8041 patients had surveillance samples submitted, of whom 2023 were included in the cross-sectional analysis and 695 in the longitudinal analysis. Baseline bedaquiline resistance prevalence was 3·8% (76 of 2023 patients; 95% CI 2·9-4·6), and it was associated with previous exposure to bedaquiline or clofazimine (OR 7·1, 95% CI 2·3-21·9) and with rifampicin-resistant or MDR tuberculosis with additional resistance to either fluoroquinolones or injectable drugs (pre-extensively-drug resistant [XDR] tuberculosis: 4·2, 1·7-10·5) or to both (XDR tuberculosis: 4·8, 2·0-11·7). Rv0678 mutations were the sole genetic basis of phenotypic resistance. Baseline resistance could be attributed to previous bedaquiline or clofazimine exposure in four (5·3%) of 76 patients and to primary transmission in six (7·9%). Odds of successful treatment outcomes were lower in patients with baseline bedaquiline resistance (0·5, 0·3-1). Resistance during treatment developed in 16 (2·3%) of 695 patients, at a median of 90 days (IQR 62-195), with 12 of these 16 having pre-XDR or XDR. INTERPRETATION: Bedaquiline resistance was associated with poorer treatment outcomes. Rapid assessment of bedaquiline resistance, especially when patients were previously exposed to bedaquiline or clofazimine, should be prioritised at baseline or if patients remain culture-positive after 2 months of treatment. Preventing resistance by use of novel combination therapies, current treatment optimisation, and patient support is essential. FUNDING: National Institute for Communicable Diseases of South Africa.

MDR M. tuberculosis outbreak clone in Eswatini missed by Xpert has elevated bedaquiline resistance dated to the pre-treatment era.

BACKGROUND: Multidrug-resistant (MDR) Mycobacterium tuberculosis complex strains not detected by commercial molecular drug susceptibility testing (mDST) assays due to the RpoB I491F resistance mutation are threatening the control of MDR tuberculosis (MDR-TB) in Eswatini. METHODS: We investigate the evolution and spread of MDR strains in Eswatini with a focus on bedaquiline (BDQ) and clofazimine (CFZ) resistance using whole-genome sequencing in two collections ((1) national drug resistance survey, 2009-2010; (2) MDR strains from the Nhlangano region, 2014-2017). RESULTS: MDR strains in collection 1 had a high cluster rate (95%, 117/123 MDR strains) with 55% grouped into the two largest clusters (gCL3, n = 28; gCL10, n = 40). All gCL10 isolates, which likely emerged around 1993 (95% highest posterior density 1987-1998), carried the mutation RpoB I491F that is missed by commercial mDST assays. In addition, 21 (53%) gCL10 isolates shared a Rv0678 M146T mutation that correlated with elevated minimum inhibitory concentrations (MICs) to BDQ and CFZ compared to wild type isolates. gCL10 isolates with the Rv0678 M146T mutation were also detected in collection 2. CONCLUSION: The high clustering rate suggests that transmission has been driving the MDR-TB epidemic in Eswatini for three decades. The presence of MDR strains in Eswatini that are not detected by commercial mDST assays and have elevated MICs to BDQ and CFZ potentially jeopardizes the successful implementation of new MDR-TB treatment guidelines. Measures to limit the spread of these outbreak isolates need to be implemented urgently.

Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

Patterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resistant TB cases in KwaZulu-Natal, South Africa, diagnosed in 2011-2014. We tested scenarios in which cases were missing at random, missing differentially by clinical characteristics, or missing differentially by transmission (i.e., cases with many links were under- or oversampled). Under the assumption that cases were missing randomly, the mean number of transmissions per case in the complete network needed to be larger than 20, far higher than expected, to reproduce the observed network. Instead, the most likely scenario involved undersampling of high-transmitting cases, and models provided evidence for super-spreading. To our knowledge, this is the first analysis to have assessed support for different mechanisms of missingness in a TB transmission study, but our results are subject to the distributional assumptions of the network models we used. Transmission studies should consider the potential biases introduced by incomplete sampling and identify host, pathogen, or environmental factors driving super-spreading.

Social Mixing and Clinical Features Linked With Transmission in a Network of Extensively Drug-resistant Tuberculosis Cases in KwaZulu-Natal, South Africa.

BACKGROUND: Tuberculosis (TB) is the leading infectious cause of death globally, and drug-resistant TB strains pose a serious threat to controlling the global TB epidemic. The clinical features, locations, and social factors driving transmission in settings with high incidences of drug-resistant TB are poorly understood. METHODS: We measured a network of genomic links using Mycobacterium tuberculosis whole-genome sequences. RESULTS: Patients with 2-3 months of cough or who spent time in urban locations were more likely to be linked in the network, while patients with sputum smear-positive disease were less likely to be linked than those with smear-negative disease. Associations persisted using different thresholds to define genomic links and irrespective of assumptions about the direction of transmission. CONCLUSIONS: Identifying factors that lead to many transmissions, including contact with urban areas, can suggest settings instrumental in transmission and indicate optimal locations and groups to target with interventions.

Pre-detection history of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa.

Antimicrobial-resistant (AMR) infections pose a major threat to global public health. Similar to other AMR pathogens, both historical and ongoing drug-resistant tuberculosis (TB) epidemics are characterized by transmission of a limited number of predominant Mycobacterium tuberculosis (Mtb) strains. Understanding how these predominant strains achieve sustained transmission, particularly during the critical period before they are detected via clinical or public health surveillance, can inform strategies for prevention and containment. In this study, we employ whole-genome sequence (WGS) data from TB clinical isolates collected in KwaZulu-Natal, South Africa to examine the pre-detection history of a successful strain of extensively drug-resistant (XDR) TB known as LAM4/KZN, first identified in a widely reported cluster of cases in 2005. We identify marked expansion of this strain concurrent with the onset of the generalized HIV epidemic 12 y prior to 2005, localize its geographic origin to a location in northeastern KwaZulu-Natal ∼400 km away from the site of the 2005 outbreak, and use protein structural modeling to propose a mechanism for how strain-specific rpoB mutations offset fitness costs associated with rifampin resistance in LAM4/KZN. Our findings highlight the importance of HIV coinfection, high preexisting rates of drug-resistant TB, human migration, and pathoadaptive evolution in the emergence and dispersal of this critical public health threat. We propose that integrating whole-genome sequencing into routine public health surveillance can enable the early detection and local containment of AMR pathogens before they achieve widespread dispersal.

Linezolid resistance in patients with drug-resistant TB and treatment failure in South Africa.

OBJECTIVES: Limited data exist on clinical associations and genotypic correlates of linezolid resistance in Mycobacterium tuberculosis. We aimed to describe mutations and clinical factors associated with phenotypic linezolid resistance from patients with drug-resistant TB at two public sector facilities in South Africa. METHODS: Adults and adolescents with treatment failure (culture positivity ≥4 months) on a linezolid-containing regimen were retrospectively identified. Phenotypic resistance, as defined by a linezolid MIC >1 mg/L, was assessed for retrieved isolates using broth microdilution. Targeted sequencing of rrl and rplC was performed, irrespective of growth on subculture. RESULTS: Thirty-nine patients with linezolid-based treatment failure were identified, 13 (33%) of whom had phenotypic or genotypic linezolid resistance after a median duration of 22 months (range = 7-32) of linezolid therapy. Paired MIC testing and genotyping was performed on 55 unique isolates. All isolates with phenotypic resistance (n = 16) were associated with known resistance mutations, most frequently due to the T460C substitution in rplC (n = 10); rrl mutations included G2814T, G2270C/T and A2810C. No mutations were detected in isolates with MICs at or below the critical concentration. CONCLUSIONS: Linezolid resistance occurred in a third of patients with drug-resistant TB and treatment failure. Resistance occurred late and was predicted by a limited number of mutations in rrl and rplC. Screening for genotypic resistance should be considered for patients with a positive culture after 4 months of linezolid therapy in order to optimize treatment and avoid the toxicity of ineffective linezolid therapy.

Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe.

Two billion people are infected with Mycobacterium tuberculosis, leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor, which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations.  Here we present a new tool, Mykrobe, which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates. Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data.  We measure the ability of Mykrobe-based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools.

Extensively drug-resistant tuberculosis in South Africa: genomic evidence supporting transmission in communities.

Despite evidence that transmission is driving an extensively drug-resistant TB (XDR-TB) epidemic, our understanding of where and between whom transmission occurs is limited. We sought to determine whether there was genomic evidence of transmission between individuals without an epidemiologic connection.We conducted a prospective study of XDR-TB patients in KwaZulu-Natal, South Africa, during the 2011-2014 period. We collected sociodemographic and clinical data, and identified epidemiologic links based on person-to-person or hospital-based connections. We performed whole-genome sequencing (WGS) on the Mycobacterium tuberculosis isolates and determined pairwise single nucleotide polymorphism (SNP) differences.Among 404 participants, 123 (30%) had person-to-person or hospital-based links, leaving 281 (70%) epidemiologically unlinked. The median SNP difference between participants with person-to-person and hospital-based links was 10 (interquartile range (IQR) 8-24) and 16 (IQR 10-23), respectively. The median SNP difference between unlinked participants and their closest genomic link was 5 (IQR 3-9) and half of unlinked participants were within 7 SNPs of at least five participants.The majority of epidemiologically-unlinked XDR-TB patients had low pairwise SNP differences with at least one other participant, consistent with transmission. These data suggest that much of transmission may result from casual contact in community settings between individuals not known to one another.

Spatial Patterns of Extensively Drug-Resistant Tuberculosis Transmission in KwaZulu-Natal, South Africa.

Background: Transmission is driving the global drug-resistant tuberculosis (TB) epidemic; nearly three-quarters of drug-resistant TB cases are attributable to transmission. Geographic patterns of disease incidence, combined with information on probable transmission links, can define the spatial scale of transmission and generate hypotheses about factors driving transmission patterns. Methods: We combined whole-genome sequencing data with home Global Positioning System coordinates from 344 participants with extensively drug-resistant (XDR) TB in KwaZulu-Natal, South Africa, diagnosed from 2011 to 2014. We aimed to determine if genomically linked (difference of ≤5 single-nucleotide polymorphisms) cases lived close to one another, which would suggest a role for local community settings in transmission. Results: One hundred eighty-two study participants were genomically linked, comprising 1084 case-pairs. The median distance between case-pairs' homes was 108 km (interquartile range, 64-162 km). Between-district, as compared to within-district, links accounted for the majority (912/1084 [84%]) of genomic links. Half (526 [49%]) of genomic links involved a case from Durban, the urban center of KwaZulu-Natal. Conclusions: The high proportions of between-district links with Durban provide insight into possible drivers of province-wide XDR-TB transmission, including urban-rural migration. Further research should focus on characterizing the contribution of these drivers to overall XDR-TB transmission in KwaZulu-Natal to inform design of targeted strategies to curb the drug-resistant TB epidemic.

Comparative accuracy of the REBA MTB MDR and Hain MTBDRplus line probe assays for the detection of multidrug-resistant tuberculosis: A multicenter, non-inferiority study.

INTRODUCTION: Despite recent diagnostic advances, the majority of multidrug-resistant tuberculosis (MDR-TB) cases remain undiagnosed. Line probes assays (LiPAs) hold great promise to curb the spread of MDR-TB as they can rapidly detect MDR-TB even when laboratory infrastructure is limited, yet few of these assays are currently widely available or supported by World Health Organization (WHO) policy. METHODS: The aim of this prospective, blinded, non-inferiority study was to compare the performance of YD Diagnostics REBA MTB MDR LiPA (YD) to the WHO-endorsed Hain MTBDRplus V1 LiPA (Hain V1) for the detection of rifampicin and isoniazid resistance. In phase 1, YD and Hain V1 diagnostic performance was assessed with selected culture isolates and results were compared to phenotypic drug susceptibility testing (DST) results and targeted sequencing data. In phase 2, both assays were tested on processed sputum samples and results were compared to phenotypic DST results. RESULTS: In phase 1, YD did not achieve non-inferiority to Hain V1. For isoniazid resistance detection, Hain V1 had a sensitivity of 89% (95%CI 83.8-93%) and specificity of 99.4% (95%CI 96.9-100%). While YD had a similar sensitivity of 92% (95%CI 87.3-95.4%), the specificity was inferior at 92.6% (95%CI 87.6-96%). For rifampicin resistance detection, Hain V1 had a sensitivity of 90.2% (95%CI 84.8-94.2%) and specificity of 98.5% (95%CI 95.7-99.7%) while YD had an inferior sensitivity of 72.4% (95%CI 65.1-78.9%) and a comparable specificity of 98% (95%CI 95-99.5%). Similar results were observed in phase 2. For MDR-TB detection, the sensitivity and specificity of Hain V1 was 93.4% (95%CI 88.2-96.2%) and 96.2% (95%CI 88.2-96.8%), respectively, compared to 75.7% (95%CI 68-82.2%) and 92% (95%CI 88.2-94.9%) for YD. CONCLUSIONS: YD did not achieve non-inferiority with Hain V1. Further improvements and repeat evaluation of YD is necessary prior to recommending its use for clinical settings.

Multicenter Noninferiority Evaluation of Hain GenoType MTBDRplus Version 2 and Nipro NTM+MDRTB Line Probe Assays for Detection of Rifampin and Isoniazid Resistance.

Less than 30% of multidrug-resistant tuberculosis (MDR-TB) patients are currently diagnosed, due to laboratory constraints. Molecular diagnostics enable rapid and simplified diagnosis. Newer-version line probe assays have not been evaluated against the WHO-endorsed Hain GenoType MTBDRplus (referred to as Hain version 1 [V1]) for the rapid detection of rifampin (RIF) and isoniazid (INH) resistance. A two-phase noninferiority study was conducted in two supranational reference laboratories to allow head-to-head comparisons of two new tests, Hain Genotype MTBDRplus version 2 (referred to as Hain version 2 [V2]) and Nipro NTM+MDRTB detection kit 2 (referred to as Nipro), to Hain V1. In phase 1, the results for 379 test strains were compared to a composite reference standard that used phenotypic drug susceptibility testing (DST) and targeted sequencing. In phase 2, the results for 644 sputum samples were compared to a phenotypic DST reference standard alone. Using a challenging set of strains in phase 1, the values for sensitivity and specificity for Hain V1, Hain V2, and Nipro, respectively, were 90.3%/98.5%, 90.3%/98.5%, and 92.0%/98.5% for RIF resistance detection and 89.1%/99.4%, 89.1%/99.4%, and 89.6%/100.0% for INH resistance detection. Testing of sputa in phase 2 yielded values for sensitivity and specificity of 97.1%/97.1%, 98.2%/97.8%, and 96.5%/97.5% for RIF and 94.4%/96.4%, 95.4%/98.8%, and 94.9%/97.6% for INH. Overall, the rates of indeterminate results were low, but there was a higher rate of indeterminate results with Nipro than with Hain V1 and V2 in samples with low smear grades. Noninferiority of Hain V2 and Nipro to Hain V1 was demonstrated for RIF and INH resistance detection in isolates and sputum specimens. These results serve as evidence for WHO policy recommendations on the use of line probe assays, including the Hain V2 and Nipro assays, for MDR-TB detection.

A subset of circulating blood mycobacteria-specific CD4 T cells can predict the time to Mycobacterium tuberculosis sputum culture conversion.

We investigated 18 HIV-negative patients with MDR-TB for M. tuberculosis (Mtb)- and PPD-specific CD4 T cell responses and followed them over 6 months of drug therapy. Twelve of these patients were sputum culture (SC) positive and six patients were SC negative upon enrollment. Our aim was to identify a subset of mycobacteria-specific CD4 T cells that would predict time to culture conversion. The total frequency of mycobacteria-specific CD4 T cells at baseline could not distinguish patients showing positive or negative SC. However, a greater proportion of late-differentiated (LD) Mtb- and PPD-specific memory CD4 T cells was found in SC positive patients than in those who were SC negative (p = 0.004 and p = 0.0012, respectively). Similarly, a higher co-expression of HLA-DR+ Ki67+ on Mtb- and PPD-specific CD4 T cells could also discriminate between sputum SC positive versus SC negative (p = 0.004 and p = 0.001, respectively). Receiver operating characteristic (ROC) analysis revealed that baseline levels of Ki67+ HLA-DR+ Mtb- and PPD-specific CD4 T cells were predictive of the time to sputum culture conversion, with area-under-the-curve of 0.8 (p = 0.027). Upon treatment, there was a significant decline of these Ki67+ HLA-DR+ T cell populations in the first 2 months, with a progressive increase in mycobacteria-specific polyfunctional IFNγ+ IL2+ TNFα+ CD4 T cells over 6 months. Thus, a subset of activated and proliferating mycobacterial-specific CD4 T cells (Ki67+ HLA-DR+) may provide a valuable marker in peripheral blood that predicts time to sputum culture conversion in TB patients at the start of treatment.