Approved Research

Characterisation of ADME gene star alleles across African-ancestry populations and comparison with other global populations

Lay summary

Background, Rationale, and Aims: Drug response varies across patients-ranging from those who experience treatment failure to those who may suffer adverse drug reactions (ADRs). Genetic variation affecting proteins involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs can considerably alter drug efficacy and contribute to ADRs. This ADME genetic variation is usually represented in the form of star alleles (shorthand for complex variant combinations and structural variants in DNA). An example of ADME genes is cytochrome P450 2D6 (CYP2D6). CYP2D6 metabolises about 20% of commonly prescribed drugs, meaning that variations in CYP2D6 could have a significant impact on the treatment of multiple diseases. CYP2D6 has over 170 star alleles according to research curated by the Pharmacogene Variation Consortium (PharmVar). This includes normal function, decreased function, non-functional, increased function, and unknown function star alleles. It is important to characterise the star allele diversity in ADME genes to lay the foundation for pharmacogenetics testing across clinical settings globally. At present the full catalogue of star alleles in major ADME genes such as CYP2D6 is unknown, while the distribution of known star alleles is also unclear across majority of global populations. The availability of full genomes generated by large consortia and biobanks provides the opportunity to address these gaps in knowledge and to catalyse the implementation of individualised medicine. Our research therefore aims to characterise and compare the genetic diversity in major drug metabolism, drug transporter, and modifier genes across diverse populations represented in the Human, Heredity, and Health in Africa (H3Africa) Consortium data catalogue and the UK Biobank. This study will contribute to identifying potentially novel ADME star alleles that may impact drug response. We are aware that some ADME genes such as CYP2D6 are complex to analyse using standard variant calling bioinformatics tools. We therefore plan to use StellarPGx (pharmacogenomics tool developed by our group) which we specifically tailored to characterising structural variants and identifying novel star alleles in these genes.

Project Duration: 3 years

Public Health Impact: Our proposed study will contribute to characterising the landscape of genetic variation that could impact drug response across populations represented in the UK Biobank and other major data catalogues. Understanding the extent of this pharmacogenomic variation across multi-ancestry cohorts will inform the development of suitable pharmacogenetics testing platforms and guide drug dosing algorithms to promote drug efficacy and minimise the risk of adverse drug reactions.