Evidence mapPaperPMID 40975835Full record

ArticleBriefings in bioinformatics2025

Characterization of the complex TB pharmacogenomic landscape in Africa using bioinformatic tools.

Carola Oelofse, Anwani Siwada, Khaleila Flisher, Marlo Möller, Caitlin Uren

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Carola OelofseSouth African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.ORCID 0000-0002-9477-6998
Anwani SiwadaSouth African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Khaleila FlisherSouth African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Marlo MöllerSouth African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Caitlin UrenSouth African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.ORCID 0000-0003-2358-0135

Funding

Grants Innovation and Product Development unit of the South African Medical Research CouncilNovartis and GSK R&D GSKNVS1/202101/001
6 · The paper itself

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.

Indexed as

Antitubercular AgentsComputational BiologyPharmacogeneticsTuberculosisAfricaGenotypeHumansPrecision MedicineAntitubercular Agentsbioinformaticsgenotype imputationinteractive web applicationpharmacogeneticsprecision medicinetuberculosis

Identifiers

PMID40975835
PMCPMC12450348

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.