Abstract
During the last decades, the rapid development in molecular biology has contributed to the understanding of genetic factors underlying many adverse drug reactions. Until recently, most research in this area has focused on genes coding for drug-metabolizing enzymes. Inactivating mutations have been found in genes coding for enzymes belonging to the cytochrome P-450 system, which is the major system for drug metabolism in humans, but also in genes coding for other enzymes. Subjects with a lack of functional activity in these enzymes should be treated with very low doses of drugs metabolized by the same enzyme in order to avoid excessive drug levels and thereby toxic effects. In the last years, increasing attention has been directed towards genes coding for drug targets. Hitherto, most studies have been carried out on single genes known to be or assumed to be functionally related to a given adverse drug reaction. Another approach, which may become more common in the future, is testing for complex single nucleotide polymorphism patterns that may be associated with adverse drug reactions, although the functional relationship between them may be completely unknown. Due to the influence of non-genetic factors in the development of adverse drug reactions, the association between a specific genotype and an adverse drug reaction will always be lower than 100%. Therefore, there is a need for prospective large-scale studies in order to elucidate the extent of environmental influences on the adverse drug reactions for which a genetic basis has been suggested. Despite these obstacles, pharmacogenetic testing will hopefully in the future identify at least some clear-cut situations where a drug should be avoided in certain individuals in order to reduce the risk of adverse drug reactions.
Keywords: Genotyping, drug-metabolizing enzymes, pharmacogenetic
Current Topics in Medicinal Chemistry
Title: Genotyping as a Tool to Predict Adverse Drug Reactions
Volume: 4 Issue: 13
Author(s): Cuneyt Guzey and Olav Spigset
Affiliation:
Keywords: Genotyping, drug-metabolizing enzymes, pharmacogenetic
Abstract: During the last decades, the rapid development in molecular biology has contributed to the understanding of genetic factors underlying many adverse drug reactions. Until recently, most research in this area has focused on genes coding for drug-metabolizing enzymes. Inactivating mutations have been found in genes coding for enzymes belonging to the cytochrome P-450 system, which is the major system for drug metabolism in humans, but also in genes coding for other enzymes. Subjects with a lack of functional activity in these enzymes should be treated with very low doses of drugs metabolized by the same enzyme in order to avoid excessive drug levels and thereby toxic effects. In the last years, increasing attention has been directed towards genes coding for drug targets. Hitherto, most studies have been carried out on single genes known to be or assumed to be functionally related to a given adverse drug reaction. Another approach, which may become more common in the future, is testing for complex single nucleotide polymorphism patterns that may be associated with adverse drug reactions, although the functional relationship between them may be completely unknown. Due to the influence of non-genetic factors in the development of adverse drug reactions, the association between a specific genotype and an adverse drug reaction will always be lower than 100%. Therefore, there is a need for prospective large-scale studies in order to elucidate the extent of environmental influences on the adverse drug reactions for which a genetic basis has been suggested. Despite these obstacles, pharmacogenetic testing will hopefully in the future identify at least some clear-cut situations where a drug should be avoided in certain individuals in order to reduce the risk of adverse drug reactions.
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Cite this article as:
Guzey Cuneyt and Spigset Olav, Genotyping as a Tool to Predict Adverse Drug Reactions, Current Topics in Medicinal Chemistry 2004; 4 (13) . https://dx.doi.org/10.2174/1568026043387791
DOI https://dx.doi.org/10.2174/1568026043387791 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
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