Interethnic Comparisons of Important Pharmacology Genes Using SNP Databases: Potential Application to Drug Regulatory Assessments

Abstract

Background: The frequencies of alleles implicated in drug-response variability provide vital information for public health management. Differences in frequencies between genetically diverse groups of individuals can hamper drug assessments, particularly in populations where clinical data are not readily available. Materials & methods: Making use of large, publicly available population genotype databases and population genetics tools, we developed a quick and efficient methodology to assess population divergence, which could be integrated into drug assessment and regulatory processes. To showcase its effectiveness, we present an analysis of population differences in a set of 42 important pharmacogenomics genes (PharmGKB) by utilizing allele frequencies of SNPs shared among three ethnic groups in the recently completed Singapore Genome Variation Project (Chinese, Malay and Indian) and four populations in the International HapMap project. Results: The analyses facilitate comparisons across populations, such as identification of genes that exhibit moderate-to-high divergence between the main ethnic groups in Singapore and Caucasians, the dominant population in most drug-development programs. Conclusion: A potential use of the analyses is for regulators to develop a decision tree based on the extent of population divergence in key drug targets, metabolizing enzymes or transporter pathways when reviewing foreign clinical trial data. The methodology can be readily extended to other genes and countries with diverse ethnic groups. We continue to explore ways of integrating the information from these population genetics tools into stratifying the risk that the drug response established in one population could be translated to another.

KEYWORDS::

• drug metabolism
• haplotype diversity
• interethnic variation
• pharmacogenomics
• population divergence
• population pharmacogenetics
• SNP
• transporter

Acknowledgements

We are very grateful to Professor Kee Seng Chia and the Singapore Genome Variation Project (SGVP) Team for early access to the SGVP database. We also wish to acknowledge our appreciation to Cheng Leng Chan, Division Director of Vigilance, Compliance and Enforcement, Dr Christina Lim, Deputy Group Director of Health Products Regulation Group, and Dr John Lim, CEO of Health Sciences Authority and members of the HSA Pharmacogenetics Advisory Committee for encouraging us to pursue this research to advance the regulatory functions at the Health Sciences Authority. We also thank other scientists at the Genome Institute of Singapore and HSA: Kar Seng Sim for technical assistance with the analyses and Drs Neil Clarke, Mark Seielstad, JJ Liu and Huei-Xin Lou for helpful discussions and comments. We acknowledge Ambrose Chia for legal counsel and review.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.