ArticleBriefings in bioinformatics2025
Characterization of the complex TB pharmacogenomic landscape in Africa using bioinformatic tools.
Article in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.