|
In 1994 alone over two million people in the U.S. suffered serious adverse drug reactions (ADRs), and of these approximately 100,000 were fatal. Many drugs are removed from the market due to unexpected or unpredictable side effects. An ADR may result from the direct effect of particular drug or may result from interaction between drugs or from the impact of environment, food, or a person’s health. For instance Baycol, a cholesterol-lowering drug, was removed from the market due to rare cases of rhabdomyolysis (muscle cell breakdown) and fatal kidney failure. Seldane, an antihistamine, would interact with any of several other drugs and cause arrhythmia. Another example is Posicor, a heart medication that did not pose a threat in itself, but combined with any of several other drugs would cause a toxic buildup of the other drug. The key to being better able to predict drug response lies in understanding the highly individual mechanisms of drug metabolism.
 Drugs go through a diverse and highly individual set of processes, starting at consumption and ending with elimination. When a drug is ingested, it undergoes a series of transformations to produce a water-soluble chemical that is easily excreted in the urine. Drug metabolism occurs in two distinct phases. Phase I metabolism consists of redox and hydrolysis reactions which expose or add functional groups to produce polar molecules. Phase II metabolism consists of synthesis and conjugation reactions that bind endogenous compounds to the molecules in order to further increase polarity. Not all substances need to undergo phase II metabolism, as the polarity may be adequate for excretion after phase I is complete.
The bulk of responsibility for phase I reactions rests on the cytochrome P450 (CYP450) superfamily of enzymes. These hemoproteins are localized in the endoplasmic reticulum and are the final step in an electron transfer chain. CYP450s catalyze the oxidation of therapeutic drugs and other xenobiotics as well as some endogenous compounds. While many tissues in the body contain these enzymes, the principle organs involved are the liver and intestines. When a drug is consumed, it may undergo a first-pass metabolism in the intestines and liver. Drugs can be absorbed intact, after moderate metabolic activity, or after extensive metabolic activity. A drug then circulates in the blood until it is acquired by another tissue. If the drug reaches the liver again, it may undergo a second-pass metabolism. The most extensive drug metabolism occurs in the liver where CYP450s make up 1-2% of the weight of hepatocytes. A particular metabolic response depends largely on the identity of the drug and an individual’s capacity for metabolism of that drug.
Pharmacogenomics
An individual’s ability to metabolize substances depends upon numerous factors including environment, age, gender, nutrition, and genetics. Genetic makeup can account for much of a person’s drug response. Mutations and polymorphic variations, including single nucleotide polymorphisms (SNPs), in CYP450 genes are widespread in the population and differ in their distribution among individuals and ethnic groups. Phenotypes resulting from these genetic changes influence the rate of drug metabolism. This can result in the drug being either eliminated too quickly to be effective or accumulated to toxic levels.
The focus of pharmacogenetics is to develop individualized drug therapies based upon a person’s genetic profile. The human genome contains 3 billion base pairs, and SNPs may occur as often as every 100 to 300 base pairs. Many mutations and SNPs with potential for altering the activity of proteins involved in drug metabolism have been discovered, but many more remain to be identified. The concept of personalized health care will not be realized until it approaches universal applicability. The same can be said for clinical drug trials. The key to developing effective drug therapies and personalized medical care is to obtain complete coverage of sequence changes in order to identify and categorize every variant in the genes involved for every individual screened. Only then will drugs become universally safer to administer, with increased efficacy, decreased adverse reactions, and fewer fatalities.
Most genotyping methods require a priori knowledge of the genetic change at the nucleotide level in order to design a detection assay. They are consequently ineffective for mutation or SNP discovery, and can be limited under conditions where changes at multiple sites within a discreet segment of DNA are to be assayed. On the other hand, DNA sequencing remains a well-understood, straightforward method to identify unknown mutations and to assay multiple site changes in a gene target. The DMG Diversity Navigators™ permit the detection of virtually all relevant genetic variants within a gene target by providing bidirectional sequence coverage for all the exons and flanking intronic regions. However, they have not been designed to detect larger scale genetic events like gene duplications and deletions or to identify changes substantially distant from an exon boundary within introns or promotor regions. Some DMG Diversity Navigators™ have been designed for coverage of both wild type and variant exons. Each contains optimized primers and buffers both for PCR amplification of the target sequences from genomic DNA samples and for sequencing of the amplified template by dideoxy-chain terminator chemistry.
Kit Design
Amplification primers are provided as premixed pairs and are designed to amplify the genomic target without co-amplification of gene family members or pseudogenes. Pseudogenes, as well as homologous and paralogous sequences of high similarity, can cause false positive results in screens for variants. During development, the primer pairs of The DMG Diversity Navigators™ are tested in PCR using the PCR buffer and conditions provided in the kits in order to determine the annealing temperature range over which the correct size product is made without co-amplification of nonspecific products. PCR samples prepared near the optimal annealing temperature are sequenced and compared to the target sequences. Sequence quality and possible regions of heterogeneous sequence are noted. The sequence data is subjected to BLAST analysis in order to determine which genomic sequences display the greatest identity to the amplified sequences. Putative interfering genomic sequences are thus identified and compared to the sequence data, particularly in the regions of noted possible sequence heterogeneity, to confirm that only the target sequence is amplified during PCR and that no co-amplification of interfering genomic sequences occurs. The PCR primer sequences are likewise subjected to BLAST analysis to confirm that mismatches occur between any primer pair and likely priming sites present on the putative interfering sequences.
Sequence primers are provided at a lower concentration than the amplification primers and are not premixed in pairs. The sequence primers are designed to yield high quality sequence data in dideoxy dye terminator reactions and to generate bidirectional sequence data with their partners. They are tested on the PCR products described above using the sequence buffer and conditions provided. The sequence primers are also often tested in pairwise fashion like the amplification primers, and may sometimes be used as PCR primers, particularly in nested or hemi-nested applications..
For each DMG Diversity Navigator™, product profile literature is provided which includes concise protocols for every step of the experimental process. Additional detailed protocols are available as is a troubleshooting guide.
A control DNA sample is provided in each DMG Diversity Navigator™ to allow a direct comparison to the experimental DNA samples from PCR amplification through genotype data analysis. In particular, for a project involving a large number of samples, it is recommended that several experimental DNA samples be tested side-by-side with the control DNA sample for one or two amplification primer sets under the recommended PCR conditions. If the amplification of experimental DNA samples is weak compared to the control, modifications to the project path might be necessary, including: re-evaluation of sample concentrations, cleaning of DNA samples by phenol:chloroform extraction or some other method, increasing the number of PCR cycles used beyond those recommended, or use of a secondary nested or hemi-nested PCR reaction.
Also, it is recommended that multiple control DNA samples be included in a 96-well plate (or other multi-sample format) of experimental samples. Negative controls, without genomic DNA, should also be included in the plate layout. These positive and negative controls, particularly if located asymmetrically on the plate with the experimental samples, will provide control information for every step of the process, including sample layout.
Web Based Technical Information
This web site offers a variety of technical support information including genotype data for the control DNA sample and CEPH 1347-02. Genomic structure and sequence information is available for each drug metabolizing gene.
Several reference sequences for each gene target are available at this site as downloadable FASTA text files. These include a full-length gene reference sequence, amplicon fragment sequences and exon sequences taken from the full-length reference, a wild type mRNA as well as its ORF sequence and derivative mRNA from the ATG start, the corresponding wild type amino acid sequence of the protein, and mirror sequences representing the biallelic alternatives to the full-length sequence and the amplicon fragments.
The full-length gene reference sequence available for each gene target contains the gene and several kilobases of flanking sequence which was downloaded from an earlier freeze of the Golden Path (www.genome.ucsc.edu) and fixed for use as an alignment and positional information reference. Boundaries of the exons from each DMG Diversity Navigator™, often including variant exons from Genbank or ACEview, are indicated by position on the full-length gene reference. Wild-type exon boundaries, where they differ from variant exons, are also indicated. The boundaries of the amplicon fragments generated by the primers from the DMG Diversity Navigator™ are listed, as are those boundaries between sequence primers providing bidirectional sequence overlap. All of these positions are listed in tabular form.
Also in tabular form are integrated results for each gene target of the nucleotide changes generated by the use of the DMG Diversity Navigator™ during development at BioVentures, Inc., variations catalogued by the Karolinska Institute (www.imm.ki.se/CYPalleles/), and variations from the NCBI dbSNP database (www.ncbi.nlm.nih.gov/SNP/). All are mapped to positions on the full-length gene reference as well as to corresponding positions on the amplicon reference fragments. The bases present at those positions in the reference fragment are indicated as well as the sequences flanking the changes in the reference, the nucleotide changes observed, positions on the reference mRNA numbered from the ATG start, effect upon the expression of the protein, activity of the protein, and heterozygosity, wherever the data is available. Identification of the changes are provided in Karolinska Institute notation, NCBI notation (rs ID number), and BioVentures, Inc. notation.
|
