Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Jun 15;209(12):1486-1496.
doi: 10.1164/rccm.202309-1583OC.

A Nanopore Sequencing-based Pharmacogenomic Panel to Personalize Tuberculosis Drug Dosing

Affiliations

A Nanopore Sequencing-based Pharmacogenomic Panel to Personalize Tuberculosis Drug Dosing

Renu Verma et al. Am J Respir Crit Care Med. .

Abstract

Rationale: Standardized dosing of antitubercular drugs leads to variable plasma drug levels, which are associated with adverse drug reactions, delayed treatment response, and relapse. Mutations in genes affecting drug metabolism explain considerable interindividual pharmacokinetic variability; however, pharmacogenomic assays that predict metabolism of antitubercular drugs have been lacking. Objectives: We sought to develop a Nanopore sequencing panel and validate its performance in patients with active tuberculosis (TB) to personalize treatment dosing. Methods: We developed a Nanopore sequencing panel targeting 15 SNPs in five genes affecting the metabolism of antitubercular drugs. For validation, we sequenced DNA samples (n = 48) from the 1,000 Genomes Project and compared the variant calling accuracy with that of Illumina genome sequencing. We then sequenced DNA samples from patients with active TB (n = 100) from South Africa on a MinION Mk1C and evaluated the relationship between genotypes and pharmacokinetic parameters for isoniazid (INH) and rifampin (RIF). Measurements and Main Results: The pharmacogenomic panel achieved 100% concordance with Illumina sequencing in variant identification for the samples from the 1,000 Genomes Project. In the clinical cohort, coverage was more than 100× for 1,498 of 1,500 (99.8%) amplicons across the 100 samples. Thirty-three percent, 47%, and 20% of participants were identified as slow, intermediate, and rapid INH acetylators, respectively. INH clearance was 2.2 times higher among intermediate acetylators and 3.8 times higher among rapid acetylators, compared with slow acetylators (P < 0.0001). RIF clearance was 17.3% (2.50-29.9) lower in individuals with homozygous AADAC rs1803155 G→A substitutions (P = 0.0015). Conclusions: Targeted sequencing can enable the detection of polymorphisms that influence TB drug metabolism on a low-cost, portable instrument to personalize dosing for TB treatment or prevention.

Keywords: NAT2; Nanopore; pharmacogenomics; targeted sequencing; tuberculosis.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
(A) Nanopore pharmacogenomic (PGx) panel. The top row indicates the antitubercular drugs for which pharmacogenomic associations were identified from published studies. Genes and their location on the Chr are listed in Rows 2 and 3. On the basis of the position of targeted SNPs, targets were divided into eight amplicons corresponding to five genes (fourth row, red). The amplicons are not scaled to their product length. The last row contains information on the positions in pharmacogenes that were included in the PGx panel. (B) Amplicon coverage in PGx panel: sequencing coverage (log10 scale) per amplicon in 100 samples from the pharmacokinetic cohort, sequenced on a MinION Mk1C sequencer in a single-tube reaction. BDQ = bedaquiline; chr = chromosome; INH = isoniazid; LZD = linezolid; RIF = rifampin; TB = tuberculosis.
Figure 2.
Figure 2.
(A) Distribution of homozygous wild-type (purple), homozygous alternate (blue), and heterozygous (yellow) alleles at 15 polymorphic sites in patients with active tuberculosis (n = 100) from a pharmacokinetic cohort sequenced on a MinION sequencer. (B) NAT2 haplotypes indicated in red are slow acetylator types, and those indicated in green are rapid acetylator haplotypes. Connections in red indicate two slow acetylator haplotypes, those in green indicate two rapid haplotypes, and those in yellow indicate one rapid and one slow haplotype (intermediate acetylation).
Figure 3.
Figure 3.
The area under the plasma drug concentration–time curve (AUC) for 0–24 hours in INH. Predicted slow acetylators (light blue), intermediate acetylators (blue), and rapid acetylators (purple). AUC was lowest for rapid acetylators, moderate for intermediate acetylators, and highest in slow acetylators. INH = isoniazid.
Figure 4.
Figure 4.
The area under the plasma drug concentration–time curve (AUC) for 0–24 hours in rifampin. Homozygous alternate (purple) for AADAC rs1803155 G→A substitutions, heterozygous (blue), and homozygous wild-type (light blue) alleles.

Update of

Comment in

Similar articles

Cited by

References

    1. Merle CS, Fielding K, Sow OB, Gninafon M, Lo MB, Mthiyane T, et al. OFLOTUB/Gatifloxacin for Tuberculosis Project A four-month gatifloxacin-containing regimen for treating tuberculosis. N Engl J Med . 2014;371:1588–1598. - PubMed
    1. Dorman SE, Nahid P, Kurbatova EV, Goldberg SV, Bozeman L, Burman WJ, et al. AIDS Clinical Trials Group and the Tuberculosis Trials Consortium High-dose rifapentine with or without moxifloxacin for shortening treatment of pulmonary tuberculosis: study protocol for TBTC study 31/ACTG A5349 phase 3 clinical trial. Contemp Clin Trials . 2020;90:105938. - PMC - PubMed
    1. Fei CM, Zainal H, Ali IAH. Evaluation of adverse reactions induced by anti-tuberculosis drugs in Hospital Pulau Pinang. Malays J Med Sci . 2018;25:103–114. - PMC - PubMed
    1. Forget EJ, Menzies D. Adverse reactions to first-line antituberculosis drugs. Expert Opin Drug Saf . 2006;5:231–249. - PubMed
    1. Choi H, Park HA, Hyun IG, Kim JH, Hwang YI, Jang SH, et al. Incidence and outcomes of adverse drug reactions to first-line anti-tuberculosis drugs and their effects on the quality of life: a multicenter prospective cohort study. Pharmacoepidemiol Drug Saf . 2022;31:1153–1163. - PubMed