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The World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis. However, molecular diagnostics to date have focused largely on first-line drugs and predicting susceptibilities in a binary manner (classifying strains as either susceptible or resistant). Here, we used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration (MIC) in 15,211 Mycobacterium tuberculosis clinical isolates from 23 countries across five continents. We identified 492 unique MIC-elevating variants across 13 drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms.

Original publication

DOI

10.1038/s41467-023-44325-5

Type

Journal article

Journal

Nature communications

Publication Date

01/2024

Volume

15

Keywords

CRyPTIC Consortium, Humans, Mycobacterium tuberculosis, Tuberculosis, Tuberculosis, Multidrug-Resistant, Antitubercular Agents, Microbial Sensitivity Tests, Drug Resistance, Multiple, Bacterial, Mutation