BackgroundThough persons of African descent have one of the widest genetic variability, genetic polymorphisms of drug-metabolising enzymes such as N-Acetyltransferase-2 (NAT2) are understudied. This study aimed to identify prevalent NAT2 single nucleotide polymorphisms (SNPs) and infer their potential effects on enzyme function among Kenyan volunteers with tuberculosis (TB) infection. Genotypic distribution at each SNP and non-random association of alleles were evaluated by testing for Hardy-Weinberg Equilibrium (HWE) and Linkage Disequilibrium (LD).MethodsWe isolated genomic DNA from cryopreserved Peripheral Blood Mononuclear Cells of 79 volunteers. We amplified the protein-coding region of the NAT2 gene by polymerase chain reaction (PCR) and sequenced PCR products using the Sanger sequencing method. Sequencing reads were mapped and aligned to the NAT2 reference using the Geneious software (Auckland, New Zealand). Statistical analyses were performed using RStudio version 4.3.2 (2023.09.1 + 494).ResultsThe most frequent haplotype was the wild type NAT2*4 (37%). Five genetic variants: 282C > T (NAT2*13), 341 T > C (NAT2*5), 803A > G (NAT2*12), 590G > A (NAT2*6) and 481C > T (NAT2*11) were observed with allele frequencies of 29%, 18%, 6%, 6%, and 4% respectively. According to the bimodal distribution of acetylation activity, the predicted phenotype was 76% rapid (mainly consisting of the wildtype NAT2*4 and the NAT2*13A variant). A higher proportion of rapid acetylators were female, 72% vs 28% male (p = 0.022, odds ratio [OR] 3.48, 95% confidence interval [CI] 1.21 to 10.48). All variants were in HWE. NAT2 341 T > C was in strong complete LD with the 590G > A variant (D′ = 1.0, r2 = − 0.39) but not complete LD with the 282C > T variant (D′ = 0.94, r2 = − 0.54).ConclusionThe rapid acetylation haplotypes predominated. Despite the LD observed, none of the SNPs could be termed tag SNP. This study adds to the genetic characterisation data of African populations at NAT2, which may be useful for developing relevant pharmacogenomic tools for TB therapy. To support optimised, pharmacogenomics-guided TB therapy, we recommend genotype-phenotype studies, including studies designed to explore gender-associated differences.