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Please use this identifier to cite or link to this item: http://hdl.handle.net/1974/6003

Title: A candidate gene analysis of response to citalopram and escitalopram treatment in patients with major depressive disorder and generalized anxiety disorder
Authors: GEDGE, L

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Keywords: depression
anxiety
candidate gene analysis
citalopram
escitalopram
Issue Date: 2010
Series/Report no.: Canadian theses
Abstract: Objective: To determine whether genotype at the catechol-O-methyltransferase rs4680, dopamine D2 receptor rs1800497, serotonin receptor 1A rs6295 or serotonin transporter 5-HTTLPR single nucleotide polymorphisms is associated with response to citalopram and escitalopram treatment in patients with major depressive disorder and generalized anxiety disorder. Methods: Twenty one patients with depression or anxiety who were treated with citalopram or escitalopram for greater than one year, and who stopped the medication for a period of time during which their symptoms returned, and upon re-commencing the medication their symptoms were again reduced, were classified as responders. Patients were assessed using the Sheehan Disability Scale and the Quick Inventory of Depressive Symptomology- self report. The control group consisted of 146 healthy participants. Genotype was determined at each of the candidate genes studied: catechol-O-methyltransferase, dopamine D2 receptor, serotonin receptor 1A and serotonin transporter. Chi squared tests were used to compare genotypic and allele frequencies between responders and controls. Results: There was no significant difference in genotypic or allele frequencies between responders and controls at each of the genes analyzed. Conclusions: This pilot study suggests that genotype at the catechol-O-methyltransferase, dopamine D2 receptor, serotonin receptor 1A and serotonin transporter genes is not associated with response to citalopram and escitalopram treatment in patients with depression and anxiety. A larger sample size, along with a genome-wide scan are needed to identify genetic variants that predict medication response in future patients.
Description: Thesis (Master, Neuroscience Studies) -- Queen's University, 2010-08-31 12:26:21.402
URI: http://hdl.handle.net/1974/6003
Appears in Collections:Neuroscience Studies Graduate Theses
Queen's Theses & Dissertations

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