Pharmacogenomics: the relevance of emerging genotyping technologies

Medical Laboratory Observer, March, 2006 by Tina Hernandez-Boussard, Teri E. Klein, Russ B. Altman

Analysis of genotype-phenotype relationships, particularly drug effects due to genetic variation--pharmacogenomics--has greatly evolved over the past several years. Advances in genomic technologies, best defined as methods used to manipulate and analyze genomic information, have catalyzed this evolution. Before 1980, few human genes had been identified as genetic risk factors for hereditary disorders; and few links between ethnicity or inheritance and deviant drug responses to a gene were made by biochemical studies. These disorders and drug responses were mostly monogenic. Analyses of these monogenic relationships relied on the knowledge of the disease-associated or drug-associated gene located in a specific chromosomal region.

[FIGURE 1 OMITTED]

With cloning of DNA in the early 1980s, molecular genetics vastly expanded the opportunity to study variations in DNA and their effects on disease and drug reactions. From about 1992 to 2002, microsatellite markers were the "hot" technology used to study these disease- or drug-associated genes, particularly in linkage-analysis studies. In these time-consuming and costly studies, about 300 to 800 microsatellite markers were identified throughout a genomic region and studied in a single DNA sample. Between microsatellites and arrays was the five-year-long "re-sequence" era--expensive but useful for discovering single nucleotide polymorphisms (SNP).

More recently, high-density genotyping arrays have become available for the study of genetic variation. These genome-wide technologies use in situ hybridization for SNP detection and contain anywhere from 1,000 to 500,000 SNP markers, with about one marker per five kilobase, or 5 kb. These arrays, in conjunction with the abundance of genomic-sequence information now available, have lead to a new era in biology.

What will new genotyping technologies bring to pharmacogenomics, and how will this information eventually lead into the clinical arena to produce individualized drug therapy?

Where are we today

We are in an era of post-genome biology. The human genome has been sequenced, and genetic variation is being characterized. We have an understanding of what different parts of the genome vary; we know what certain variations mean, (i.e., silent versus functional SNPs), and it is estimated that there are more than 10 million SNPs where the less-common allele occurs in at least 1% of the population. (1) These SNPs can contribute directly to disease predisposition by modifying the function of a gene, or they can be used as a marker to find nearby disease-causing mutations through association or family-based studies.

There are three basic classes of SNPs:

* those that cause an alteration in gene function;

* those that cause more subtle gene function modifications and may predispose an individual to disease in conjunction with other genetic variants and environmental factors; and

* those that are silent with respect to gene function.

We are now able to measure genetic variation in DNA sequences expressed in phenotypes at the molecular, cellular, organ, and system levels. We can only learn about the consequences of these variants by studying these in parts.

There is a growing list of gene variants that contribute to aberrant drug responses, from drug-metabolizing enzymes to drug transporters to drug targets as well as variants that are disease-related. Before genome-wide analyses were available, most aberrant gene-variant correlations were monogenic, such as those found in Mendelian-inheritance patterns. Candidate gene approaches have been used for these tedious, costly studies. Single genes related to an adverse drug reaction were based on clinical pharmacological studies of proteins (receptors) and pathways known to be involved in a drug pharmaco-kinetic or -dynamic response. An example is thiopurine S-methyltransferase (TPMT) and its enhancement of the S-methylation of thiopurine drugs--an effect due to genetic variation that can be responsible for thiopurine toxicity. (2) It is clear, however, that monogenic relations are not the case for most diseases, such as diabetes, cancer, heart disease, and pharmacological deviants. With the completion of the Human Genome Project and the recent advances in genome technology, we now have the capabilities to analyze pharmacogenomic data in a timely and cost-efficient manner.

Types of studies being performed

Several different types of studies addressing genetic variation are being performed today on these emerging genome-wide technologies, depending on the marker density of a genotyping array. Broadly speaking, whole genome genotyping arrays containing 3,000 to 10,000 markers are sufficient for linkage-analysis studies; arrays containing 10,000 to 100,000 are sufficient in marker density to study loss of heterozygosity and comparative genomic hybridization. Association studies, however, require a large number of study subjects (cases and controls) and high-density arrays, such as those with 100,000 to 500,000 markers on a single array. (3)