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Introduction: Antimicrobial resistance (AMR) is one of the most significant global health threats to the public, animals, and the ecosystem. Inappropriate use of antibiotics in food animals is considered a major driver of AMR in humans. This study was conducted to assess the knowledge, attitude, practices, and risk perception (KAPP) of dairy farm owners/workers in Addis Ababa about antibiotic use and resistance. Methods: A face-to-face interview using a structured questionnaire was conducted with 281 respondents in four selected subcities of Addis Ababa. The responses provided by each participant were recoded into a binary scale based on the mean score of each domain. Pearson chi-square was used to check the association between the KAPP and sociodemographic characteristics of the respondents and logistic regression analysis was done to explore the factors associated with KAPP. Results: Overall, more than half of the surveyed dairy farm owners/workers had good knowledge (57.7%) and appropriate practice (53.0%), while less than half of the respondents showed desirable attitudes (47.7%) and positive risk perceptions (42.7%). The findings revealed a strong association between the respondents' KAPP and education and between knowledge and risk perception and farming experience. Conclusion: This study found that continuous education of dairy farm owners/workers regarding antimicrobial usage and antimicrobial resistance in dairy farms will increase their awareness and perception of risk as well as motivate them to adopt desirable attitudes and appropriate practices, and consequently limit inappropriate use of antimicrobials leading to mitigating emergence of AMR. [ABSTRACT FROM AUTHOR]

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub‐Saharan African (SSA) populations. We called star alleles from 961 high‐depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high‐coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21–47% and 2–19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0–6%, 3–10%, and 6–20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African‐ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single‐Molecule Real‐Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent. [ABSTRACT FROM AUTHOR]

Cytochrome P450 2D6 (CYP2D6) is a key enzyme in drug response owing to its involvement in the metabolism of ~ 25% of clinically prescribed medications. The encoding CYP2D6 gene is highly polymorphic, and many pharmacogenetics studies have been performed worldwide to investigate the distribution of CYP2D6 star alleles (haplotypes); however, African populations have been relatively understudied to date. In this study, the distributions of CYP2D6 star alleles and predicted drug metabolizer phenotypes—derived from activity scores—were examined across multiple sub‐Saharan African populations based on bioinformatics analysis of 961 high‐depth whole genome sequences. This was followed by characterization of novel star alleles and suballeles in a subset of the participants via targeted high‐fidelity Single‐Molecule Real‐Time resequencing (Pacific Biosciences). This study revealed varying frequencies of known CYP2D6 alleles and predicted phenotypes across different African ethnolinguistic groups. Twenty‐seven novel CYP2D6 star alleles were predicted computationally and two of them were further validated. This study highlights the importance of studying variation in key pharmacogenes such as CYP2D6 in the African context to better understand population‐specific allele frequencies. This will aid in the development of better genotyping panels and star allele detection approaches with a view toward supporting effective implementation of precision medicine strategies in Africa and across the African diaspora. [ABSTRACT FROM AUTHOR]