Analysis of discrepant results between the Genotype® MTBDRplus assay and an antimicrobial drug susceptibility test for isoniazid-resistant tuberculosis

TB or not TB? Definitive determination of species within the Mycobacterium tuberculosis complex in unprocessed sputum from adults with presumed multidrug-resistant tuberculosis

Objectives

Differences among Mycobacterium tuberculosis complex (MTC) species may predict drug resistance or treatment success. Thus, we optimised and deployed the genotype MTBC assay (gMTBC) to identify MTC to the species level, and then performed comparative genotypic drug‐susceptibility testing to anti‐tuberculosis drugs from direct sputum of patients with presumed multidrug‐resistant tuberculosis (MDR‐TB) by the MTBDRplus/sl reference method.

Methods

Patients with positive Xpert^® MTB/RIF (Xpert) results were consented to provide early‐morning‐sputum for testing by the gMTBC and the reference MTBDRplus/sl. Chi‐square or Fisher’s exact test compared proportions. Modified Poisson regression modelled detection of MTC by gMTBC.

Results

Among 73 patients, 53 (73%) were male and had a mean age of 43 (95% CI; 40–45) years. In total, 34 (47%), 36 (49%) and 38 (55%) had positive gMTBC, culture and MTBDR respectively. Forty patients (55%) had low quantity MTC by Xpert, including 31 (78%) with a negative culture. gMTBC was more likely to be positive in patients with chest cavity 4.18 (1.31–13.32, P = 0.016), high‐quantity MTC by Xpert 3.03 (1.35–6.82, P = 0.007) and sputum smear positivity 1.93 (1.19–3.14, P = 0.008). The accuracy of gMTBC in detecting MTC was 95% (95% CI; 86–98; κ = 0.89) compared to MTBDRplus/sl. All M. tuberculosis/canettii identified by gMTB were susceptible to fluoroquinolone and aminoglycosides/capreomycin.

Conclusions

The concordance between the gMTBC assay and MTBDRplus/sl in detecting MTC was high but lagged behind the yield of Xpert MTB/RIF. All M. tuberculosis/canettii were susceptible to fluoroquinolones, a core drug in MDR‐TB treatment regimens.

Systematic Review of Mutations Associated with Isoniazid Resistance Points to Continuing Evolution and Subsequent Evasion of Molecular Detection, and Potential for Emergence of Multidrug Resistance in Clinical Strains of Mycobacterium tuberculosis

Molecular testing is rapidly becoming an integral component of global tuberculosis (TB) control. Uncommon mechanisms of resistance escape detection by these platforms and undermine our ability to contain outbreaks. This article is a systematic review of published articles that reported isoniazid (INH) resistance-conferring mutations between September 2013 and December 2019. The genes katG, inhA, and fabG1, and the intergenic region oxyR'-ahpC were considered in this review. Fifty-two articles were included that described 9,306 clinical isolates (5,804 INH resistant [INH^r] and 3,502 INH susceptible [INH^s]) from 31 countries. The three most frequently mutated loci continue to be locus 315 of katG (katG315; n = 4,271), locus -15 of inhA (inhA-15; n = 787), and locus -8 of inhA (inhA-8; 106). However, the diagnostic value of inhA-8 is far lower than previously thought, as it only appears in 25 (0.4%) of the INH^r isolates lacking the first two mutations. I catalogued 45 new loci (29 katG, nine inhA, and seven ahpC) associated with INH resistance and identified 59 loci (common to this and previous reviews) as a reliable basis for molecular diagnostics. Including all observed mutations provides a cumulative sensitivity of 85.6%. In 14.4% of resistant isolates, no mechanism of resistance was detected, making them likely to escape molecular detection, and in the case of INH monoresistance, likely to convert to multidrug-resistant TB (MDR-TB). Integrating the information cataloged in this study into current diagnostic tools is essential for combating the emergence of MDR-TB, and its exclusion can lead to an unintended selection against common mechanisms and to diversifying evolution. Observation of many low-frequency resistance-conferring mutations points to an advantage of whole-genome sequencing (WGS) for diagnostics. Finally, I provide five recommendations for future diagnostic platforms.

Genomic Prediction of Antimicrobial Resistance: Ready or Not, Here It Comes!

BACKGROUND

Next-generation sequencing (NGS) technologies are being used to predict antimicrobial resistance. The field is evolving rapidly and transitioning out of the research setting into clinical use. Clinical laboratories are evaluating the accuracy and utility of genomic resistance prediction, including methods for NGS, downstream bioinformatic pipeline components, and the clinical settings in which this type of testing should be offered.

CONTENT

We describe genomic sequencing as it pertains to predicting antimicrobial resistance in clinical isolates and samples. We elaborate on current methodologies and workflows to perform this testing and summarize the current state of genomic resistance prediction in clinical settings. To highlight this aspect, we include 3 medically relevant microorganism exemplars: Mycobacterium tuberculosis, Staphylococcus aureus, and Neisseria gonorrhoeae. Last, we discuss the future of genomic-based resistance detection in clinical microbiology laboratories.

SUMMARY

Antimicrobial resistance prediction by genomic approaches is in its infancy for routine patient care. Genomic approaches have already added value to the current diagnostic testing landscape in specific circumstances and will play an increasingly important role in diagnostic microbiology. Future advancements will shorten turnaround time, reduce costs, and improve our analysis and interpretation of clinically actionable results.

Clinical implications of discrepant results between genotypic MTBDRplus and phenotypic Löwenstein-Jensen method for isoniazid or rifampicin drug susceptibility tests in tuberculosis patients

BACKGROUND

The widespread use of molecular, genotypic drug susceptibility tests (DSTs) for antituberculosis (anti-TB) drugs has led to the dilemma of interpreting discordant results between genotypic and conventional, phenotypic DSTs. We investigated the clinical characteristics, including treatment patterns and outcomes, of TB patients with a genotype-phenotype discrepancy in susceptibility to isoniazid (INH) or rifampicin (RIF).

METHODS

We retrospectively reviewed the medical records of TB patients who had results for 2 DSTs (genotypic method, MTBDRplus test for INH and RIF, and phenotypic method) treated between August 2010 and October 2016 in a tertiary university hospital.

RESULTS

Among 1,069 TB patients, 63 (5.9%) had discrepant results for the 2 DSTs. Of the 57 multidrug-resistant (MDR) TB cases diagnosed by either DST, 18 (31.6%) showed discordant results for INH or RIF. The most frequent pattern of discordance was genotypic susceptibility with phenotypic resistance to INH. RIF-discordant subjects with genotypic resistance were more likely to have been exposed previously to anti-TB drugs and to have an MDR TB diagnosis and concurrent INH resistance. Forty-five of the 54 patients managed in our hospital (83.3%) had a favorable outcome with a mean treatment duration of 14.0 months. Ten of the 16 INH-discrepant patients with a genotypic mutation continued taking INH, but more than half patients in the RIF-discrepant group (8/14) with a genotypic mutation discontinued taking RIF.

CONCLUSIONS

Despite the low frequency, discordant results were obtained between the genotypic and phenotypic DSTs for INH or RIF, especially for patients with MDR TB or INH resistance. Furthermore, it seemed that RIF discrepancy with a genotypic mutation might have a greater impact on the clinical outcome than INH discrepancy.