- Title
- Potential simple and multifactorial drug-gene interactions of tricyclic antidepressants in older Australians
- Creator
- Biswas, Mohitosh; Dias, Thilani H.; Daneshi, Nilofar; Holliday, Elizabeth; Hancock, Stephen; Attia, John; Scott, Rodney; Newby, David; Kerr, Karen P.; Milward, Elizabeth A.
- Relation
- Journal of Advances in Medical Research Vol. 2, Issue 1
- Publisher Link
- http://dx.doi.org/10.5176/2345-7201_40
- Publisher
- Global Science and Technology Forum
- Resource Type
- journal article
- Date
- 2017
- Description
- Although tricyclic antidepressants are often used to treat depression in elderly people worldwide, the safety and efficacy of these drugs may be affected by both simple and multifactorial drug-gene interactions. The objective of the present study was to investigate the community prevalence of predicted simple and multifactorial drug-gene interactions for tricyclic anti-depressant drugs in a cohort of older Australians from the Hunter Community Study. Potential interacting co-prescribed medications were identified from self-reported medication data of 2,642 participants aged over 55, predominantly of European ancestry. Predicted simple and multifactorial drug-gene interactions were identified from genotyping data using Affymetrix Kaiser Axiom arrays and imputed data from the 1000 Genomes and HapMap Phase II European reference panels. Of 81 participants on tricyclic antidepressants, 74 (91%; 95% CI 85%-97%) were co-prescribed at least one potential interacting drug, with on average 3.5 possible interactions per participant. Of these, 24 (30%; 95% CI 20%-40%) were identified as being at risk of at least one clinically significant drug-drug interaction. Genotype data were available for 45 of the 81 participants taking tricyclic antidepressant drugs, of whom five participants (11%; 95% CI 2%-20%) were identified as being at risk of clinically significant simple DGI predicted to increase the likelihood of adverse effects and 40 participants (89%; 95% CI 80%-98%) as being at risk of clinically significant multifactorial DGI. Our results show that a substantial proportion of people on tricyclic antidepressants are likely to be exposed to simple or multifactorial drug-gene interactions that may increase susceptibility to adverse responses. It may therefore be of considerable clinical value to take pharmacogenomics of tricyclic anti-depressants into account in addition to drug interactions.
- Subject
- drugs; drug interaction; drug-gene interaction; personalized medicine; pharmacogenomics; precision medicine; tricyclic anti-depressant drugs
- Identifier
- http://hdl.handle.net/1959.13/1385815
- Identifier
- uon:32298
- Identifier
- ISSN:2345-7201
- Rights
- © The Author(s) 2017. This article is published with open access by the GSTF.
- Language
- eng
- Full Text
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