{"title":"利用生物信息学工具表征非洲复杂的结核病药物基因组学景观。","authors":"Carola Oelofse, Anwani Siwada, Khaleila Flisher, Marlo Möller, Caitlin Uren","doi":"10.1093/bib/bbaf484","DOIUrl":null,"url":null,"abstract":"<p><p>Currently, many of the world's most culturally and genetically diverse populations, located in Africa, risk exclusion from advancements in pharmacogenomics (PGx) and personalized medicine. Optimizing treatment outcomes for these populations is crucial, particularly for widespread diseases such as tuberculosis (TB). Reducing adverse drug reactions is essential for improving treatment adherence and overall outcomes. However, investigating the PGx landscape in African populations is challenging due to the lack of genotype and phenotype data, as well as limited computational tools and resources tailored to their genetic diversity. This study assessed various bioinformatic methodologies to characterize variations in the absorption, distribution, metabolism, and excretion (ADME) of anti-TB drugs in a large African cohort (>21 populations from public and in-house datasets). Special focus was placed on the Khoe-San, one of Africa's most genetically diverse groups, and the South African Coloured (SAC) community, whose richly diverse genetic background arises from recent admixture. We developed a graphic resource to support the investigation of anti-TB drug PGx in Africa. African-specific genomic studies addressing major health challenges on the continent are critical for informing the development of relevant genotyping and reference panels, enabling more cost-efficient personalized care in the region. This study offers a comprehensive assessment of the TB PGx landscape in Africa and highlights the potential of computational methods to promote the inclusion of genomically diverse African populations in PGx research.</p>","PeriodicalId":9209,"journal":{"name":"Briefings in bioinformatics","volume":"26 5","pages":""},"PeriodicalIF":7.7000,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12450348/pdf/","citationCount":"0","resultStr":"{\"title\":\"Characterization of the complex TB pharmacogenomic landscape in Africa using bioinformatic tools.\",\"authors\":\"Carola Oelofse, Anwani Siwada, Khaleila Flisher, Marlo Möller, Caitlin Uren\",\"doi\":\"10.1093/bib/bbaf484\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Currently, many of the world's most culturally and genetically diverse populations, located in Africa, risk exclusion from advancements in pharmacogenomics (PGx) and personalized medicine. Optimizing treatment outcomes for these populations is crucial, particularly for widespread diseases such as tuberculosis (TB). Reducing adverse drug reactions is essential for improving treatment adherence and overall outcomes. However, investigating the PGx landscape in African populations is challenging due to the lack of genotype and phenotype data, as well as limited computational tools and resources tailored to their genetic diversity. This study assessed various bioinformatic methodologies to characterize variations in the absorption, distribution, metabolism, and excretion (ADME) of anti-TB drugs in a large African cohort (>21 populations from public and in-house datasets). Special focus was placed on the Khoe-San, one of Africa's most genetically diverse groups, and the South African Coloured (SAC) community, whose richly diverse genetic background arises from recent admixture. We developed a graphic resource to support the investigation of anti-TB drug PGx in Africa. African-specific genomic studies addressing major health challenges on the continent are critical for informing the development of relevant genotyping and reference panels, enabling more cost-efficient personalized care in the region. This study offers a comprehensive assessment of the TB PGx landscape in Africa and highlights the potential of computational methods to promote the inclusion of genomically diverse African populations in PGx research.</p>\",\"PeriodicalId\":9209,\"journal\":{\"name\":\"Briefings in bioinformatics\",\"volume\":\"26 5\",\"pages\":\"\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2025-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12450348/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Briefings in bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/bib/bbaf484\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Briefings in bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bib/bbaf484","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Characterization of the complex TB pharmacogenomic landscape in Africa using bioinformatic tools.
Currently, many of the world's most culturally and genetically diverse populations, located in Africa, risk exclusion from advancements in pharmacogenomics (PGx) and personalized medicine. Optimizing treatment outcomes for these populations is crucial, particularly for widespread diseases such as tuberculosis (TB). Reducing adverse drug reactions is essential for improving treatment adherence and overall outcomes. However, investigating the PGx landscape in African populations is challenging due to the lack of genotype and phenotype data, as well as limited computational tools and resources tailored to their genetic diversity. This study assessed various bioinformatic methodologies to characterize variations in the absorption, distribution, metabolism, and excretion (ADME) of anti-TB drugs in a large African cohort (>21 populations from public and in-house datasets). Special focus was placed on the Khoe-San, one of Africa's most genetically diverse groups, and the South African Coloured (SAC) community, whose richly diverse genetic background arises from recent admixture. We developed a graphic resource to support the investigation of anti-TB drug PGx in Africa. African-specific genomic studies addressing major health challenges on the continent are critical for informing the development of relevant genotyping and reference panels, enabling more cost-efficient personalized care in the region. This study offers a comprehensive assessment of the TB PGx landscape in Africa and highlights the potential of computational methods to promote the inclusion of genomically diverse African populations in PGx research.
期刊介绍:
Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data.
The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.