| Autor: |
Verma R; Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.; Manipal Academy of Higher Education, Manipal, India.; Institute of Bioinformatics, International Tech Park, Bangalore, India., da Silva KE; Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California., Rockwood N; Wellcome Center for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine and Department Medicine.; Department of Infectious Diseases, Imperial College, London, United Kingdom.; Department of Medical Microbiology and Immunology, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka; and., Wasmann RE; Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa., Yende N; Department of Pathology and Institute of Infectious Disease and Molecular Medicine, and., Song T; Department of Pathology and Institute of Infectious Disease and Molecular Medicine, and., Kim E; Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California., Denti P; Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa., Wilkinson RJ; Wellcome Center for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine and Department Medicine.; Department of Infectious Diseases, Imperial College, London, United Kingdom.; Francis Crick Institute, London, United Kingdom., Andrews JR; Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California. |
| Abstrakt: |
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. |
