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 [INHr] and 3,502 INH susceptible [INHs]) 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 INHr 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.