Aims: Citalopram (CT) and escitalopram (S-CT) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder (MDD). We applied a genome-wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S-CT and their metabolites in MDD patients treated with CT or S-CT.
Methods: Our genome-wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within-subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single-nucleotide polymorphisms (SNPs) were modelled as additive allelic effects.
Results: Genome-wide significant associations were observed for S-CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10(-9) ) and with S-didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10(-16) ), supporting the important role of these cytochrome P450 (CYP) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation.
Conclusions: In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome-wide association study performed in MDD patients treated with CT or S-CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors.
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http://dx.doi.org/10.1111/bcp.12348 | DOI Listing |
Neuroimage Clin
January 2025
Backgrounds/objective: Deep brain stimulation (DBS) has proved the viability of alleviating depression symptoms by stimulating deep reward-related nuclei. This study aims to investigate the abnormal connectivity profiles among superficial, intermediate, and deep brain regions within the reward circuit in major depressive disorder (MDD) and therefore provides references for identifying potential superficial cortical targets for non-invasive neuromodulation.
Methods: Resting-state functional magnetic resonance imaging data were collected from a cohort of depression patients (N = 52) and demographically matched healthy controls (N = 60).
Sensors (Basel)
January 2025
University of Zagreb Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia.
Major depressive disorder (MDD) is associated with substantial morbidity and mortality, yet its diagnosis and treatment rates remain low due to its diverse and often overlapping clinical manifestations. In this context, electroencephalography (EEG) has gained attention as a potential objective tool for diagnosing depression. This study aimed to evaluate the effectiveness of EEG in identifying MDD by analyzing 140 EEG recordings from patients diagnosed with depression and healthy volunteers.
View Article and Find Full Text PDFJ ECT
January 2025
From the Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA.
Background: Electroconvulsive therapy (ECT) is an effective treatment for treatment-resistant depression (TRD). There are limited data on the improvement of anxiety symptoms in patients receiving ECT for TRD.
Objective: The aim of the study was to examine the extent to which anxiety symptom severity improves, relative to improvements in depressive symptoms, in TRD patients receiving an acute course of ECT.
Circ Cardiovasc Interv
January 2025
Division of Cardiology, Department of Medicine, University of Washington Medical Center, Seattle (E.J.S., T. Salahuddin, J.A.D.).
Background: Intravascular imaging (IVI) is widely recognized to improve outcomes after percutaneous coronary intervention (PCI). However, IVI is underutilized and is not yet established as a performance measure for quality PCI.
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Front Psychiatry
January 2025
Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea.
Background: Stress is a significant risk factor for psychiatric disorders such as major depressive disorder (MDD) and panic disorder (PD). This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the autonomic nervous system, which can be evaluated via heart rate variability (HRV).
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