Genetic variation and pharmacogenomics: concepts, facts, and challenges

Abstract

The analysis of genetic variation in candidate genes is an issue of central importance in pharmacogenomics. The specific approaches taken will have a critical impact on the successful identification of disease genes, the molecular correlates of drug response, and the establishment of meaningful relationships between genetic variants and phenotypes of biomedical and pharmaceutical importance in general. Against a historical background, this article distinguishes different approaches to candidate gene analysis, reflecting different stages in human genome research. Only recently has it become feasible to analyze genetic variation systematically at the ultimate level of resolution, ie, the DNA sequence. In this context, the importance of haplotype-based approaches to candidate gene analysis has at last been recognized; the determination of the specific combinations of variants for each of the two sequences of a gene defined as a haplotype is essential. An up-to-date summary of such maximum resolution data on the amount, nature, and structure of genetic variation in candidate genes will be given. These data demonstrate abundant gene sequence and haplotype diversity. Numerous individually different forms of a gene may exist. This presents major challenges to the analysis of relationships between genetic variation, gene function, and phenotype. First solutions seem within reach. The implications of naturally occurring variation for pharmacogenomics and "personalized" medicine are now evident. Future approaches to the identification, evaluation, and prioritization of drug targets, the optimization of clinical trials, and the development of efficient therapies must be based on in-depth knowledge of candidate gene variation as an essential prerequisite.

CD59 gene: 143 haplotypes of 22,718 nucleotides length by computational phasing in 113 individuals from different ethnicities

“…Although ethnically diverse, the pattern of CD59 haplotype frequencies in the mostly Caucasian FDA cohort and the African Ethiopia cohort was nearly identical (Figure 2). The largest fraction of haplotypes in both cohorts was constituted by rare haplotypes (observed once) due to the presence of 96 low prevalence (<1%) SNVs as commonly observed in many genes 48 (Supporting material S2). Such large numbers of rare haplotypes have previously been explained by population expansion, which can increase the number of segregating variants when negative selection is less effective 49,50 …”

Strategies to Improve the Clinical Outcomes for Direct-to-Consumer Pharmacogenomic Tests

“…For example, many genetic effects and modifications such as the presence of rare recombination events in specific populations, dominant negative effects of mutations in genes in drug metabolic pathways, gene duplication occasions in populations, epigenetic signatures in people, epistasis occurrence, variable expressivity through intra- and inter-families, and incomplete penetrance effects for some genetic alterations receive no attention during PGx tests. Therefore, the provided results may not depict the true potential of pharmacogenetic profiling and functioning of individuals [ 42 ]. Additionally, different specificity and sensitivity, mainly because of diverse genetic variations or allele/haplotype frequencies for the tested pharmacogenes, in addition to the presence of any linkage disequilibrium between the tested SNPs in population-specific panels and possible findings through comprehensive genotyping approaches such as WES and WGS, plus long-read sequencer outcomes, should be taken into account.…”

Treatment goals: response and nonresponse

“…The relevance of genetic parameters for pharmacodynamics, pharmacokinetics, and the genetic prediction of treatment response are detailed in this volume by Ackenheil and Weber, 22 Morris-Rosendahl and Fiebich, 23 and Hoehe and Kroslak. 24 …”

“…The role of genetic variation in the form of hypometabolism or hypermetabolism of a drug may cause treatment failure. 22 - 24 , 33 …”