AbstractWhilst antidepressants are widely prescribed, there is a large degree of variation between patients in terms of treatment outcomes. Furthermore, the mechanisms by which these drugs exert their effects remain unclear. In this thesis, genetic biomarkers of antidepressant outcomes have been explored, in order to better understand the molecular mechanisms underpinning effective antidepressant treatment. The research presented here use data from the GENDEP project, which is a large pharmacogenetic study of depressed patients receiving antidepressant treatment.
Firstly, the pharmacological underpinnings of antidepressant-associated side effects were used to categorise these side effects and conduct a candidate gene analysis. Whilst a significant association between variation within the HTR2C gene and serotonergic side effects was found, the observation was not replicated in a second sample.
Secondly, the role of variability in drug metabolism rates in treatment outcomes was investigated. Examining genotypic information on the cytochrome P450 enzymes, no associations with treatment response, side effects or study discontinuation were observed. Furthermore, serum concentrations of antidepressant were unrelated to treatment response or overall burden of side effects, predicting only a minority of specific side effects.
Thirdly, transcriptomic changes with drug administration were explored in relation to treatment efficacy. Two genes were identified where changes in expression levels were significantly associated with treatment response amongst patients taking nortriptyline. Furthermore, using a network-based approach, changes in gene expression across one module of coexpressed genes showed significant correlation with symptom improvement; this biological network generalised across different antidepressant medications.
Finally, genomic and transcriptomic data were combined, in an examination of the genetic control of gene expression. This analysis then was used to gain an insight into the molecular processes that link genotype to phenotype.
The evidence presented within this thesis, when considered in combination with existing literature, highlights that antidepressant efficacy is a complex trait, influenced by many genes of small effect. Nevertheless, by layering together different levels of information, we can begin to dissect the molecular mechanisms involved in antidepressant action.
|Date of Award
|Peter McGuffin (Supervisor) & Richard Dobson (Supervisor)