Population genetic structure of variable drug response

• Published in: Nature genetics Vol. 29; no. 3; pp. 265 - 269
• Main Authors: Goldstein, David B, Wilson, James F, Weale, Michael E, Smith, Alice C, Gratrix, Fiona, Fletcher, Benjamin, Thomas, Mark G, Bradman, Neil
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group 01.11.2001
• Subjects: Biological and medical sciences; Chi-Square Distribution; Chromosomes, Human, Pair 1 - genetics; Cluster Analysis; Continental Population Groups - genetics; Cytochrome P-450 Enzyme System - genetics; Cytochrome P-450 Enzyme System - metabolism; Drugs; Enzymes - genetics; Enzymes - metabolism; Ethnic Groups - genetics; Fundamental and applied biological sciences. Psychology; Gene Frequency - genetics; Genes; Genes. Genome; Genetic variation; Genetic Variation - genetics; Genetics; Genotype; Human genetics; Humans; Identification and classification; Male; Metabolism; Microsatellite Repeats - genetics; Molecular and cellular biology; Molecular genetics; Multifactorial Inheritance - genetics; Mutation; Oxidation-Reduction; Pharmaceutical Preparations - metabolism; Pharmacogenetics; Physiological aspects; Polymorphism, Single Nucleotide - genetics; Population; Publishing; Software; X Chromosome - genetics; United Kingdom; United Kingdom > UK; Drug; Population structure; Genetic variability; Response variability; Population genetics
• ISSN: 1061-4036; 1546-1718
• DOI: 10.1038/ng761

Geographic patterns of genetic variation, including variation at drug metabolizing enzyme (DME) loci and drug targets, indicate that geographic structuring of inter-individual variation in drug response may occur frequently. This raises two questions: how to represent human population genetic structure in the evaluation of drug safety and efficacy, and how to relate this structure to drug response. We address these by (i) inferring the genetic structure present in a heterogeneous sample and (ii) comparing the distribution of DME variants across the inferred genetic clusters of individuals. We find that commonly used ethnic labels are both insufficient and inaccurate representations of the inferred genetic clusters, and that drug-metabolizing profiles, defined by the distribution of DME variants, differ significantly among the clusters. We note, however, that the complexity of human demographic history means that there is no obvious natural clustering scheme, nor an obvious appropriate degree of resolution. Our comparison of drug-metabolizing profiles across the inferred clusters establishes a framework for assessing the appropriate level of resolution in relating genetic structure to drug response.