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Citalopram amplifies the influence of living conditions on mood in depressed patients enrolled in the STAR*D study.

ABSTRACT: Selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed antidepressant drugs, have a variable and incomplete efficacy. In order to better understand SSRI action, we explored the hypothesis that SSRIs do not affect mood per se but amplify the influence of the living conditions on mood. To this aim, we exploited the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) data set, selected a subpopulation of 591 patients with an overlapping clinical history and analyzed treatment outcome according to dosage -20 or 40?mg per day of citalopram. We found that sociodemographic characteristics affected treatment response in the same direction in the two dose groups, but these effects reached statistical significance only in the 40?mg per day dose group. In the latter, higher improvement rate was associated with having a working employment status (P=0.0219), longer education (P=0.0053), high income (P=0.01) or a private insurance (P=0.0031), and the higher remission rate was associated with having a working employment status (P=0.0326) or longer education (P=0.0484). Moreover, the magnitude of the effect of the sociodemographic characteristics on mood, measured as the percent of patients showing a positive outcome when exposed to favorable living conditions, was much greater-up to 37-fold-in the 40 compared to the 20?mg per day dose group. Overall, our results indicate that citalopram amplifies the influence of the living conditions on mood in a dose-dependent manner. These findings provide a potential explanation for the variable efficacy of SSRIs and might lead to the development of personalized strategies aimed at enhancing their efficacy.

SUBMITTER: Chiarotti F

PROVIDER: S-EPMC5416678 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Citalopram amplifies the influence of living conditions on mood in depressed patients enrolled in the STAR*D study.

Chiarotti F F Viglione A A Giuliani A A Branchi I I

Translational psychiatry 20170321 3

Selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed antidepressant drugs, have a variable and incomplete efficacy. In order to better understand SSRI action, we explored the hypothesis that SSRIs do not affect mood per se but amplify the influence of the living conditions on mood. To this aim, we exploited the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) data set, selected a subpopulation of 591 patients with an overlapping clinical history and analyz ...[more]

PMID: 28323288

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Project description:ObjectiveFew data exist to help clinicians predict likelihood of treatment response in individual patients with major depressive disorder (MDD). Our aim was to identify subgroups of MDD patients with differential treatment outcomes based on presenting clinical characteristics. We also sought to quantify the likelihood of treatment success based on the degree of improvement and side effects after 2 and 4 weeks of selective serotonin reuptake inhibitor (SSRI) pharmacotherapy.MethodWe analyzed data from the first treatment phase of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial, in which subjects with a DSM-IV diagnosis of MDD were treated for 8-14 weeks with open-label citalopram. A receiver operating characteristic (ROC) analysis was conducted to determine homogenous subgroups with different rates of response and remission in depressive symptoms. Included predictor variables were initial clinical characteristics, initial improvement, and side effects after 2 and 4 weeks of SSRI treatment. The primary outcome measures were treatment response (defined as a greater than 50% reduction in 17-item Hamilton Depression Rating Scale [HDRS-17] score from baseline) and remission (defined as an HDRS-17 score ≤ 17).ResultsBaseline clinical characteristics were able to identify subgroups from a low likelihood of response of 18% (income < $10,000, comorbid generalized anxiety disorder, < 16 years of education; P < .01) to a high likelihood of response of 68% (income ≥ $40,000, no comorbid posttraumatic stress disorder; P < .01). Among baseline clinical characteristics, employment status (N = 2,477; χ²₁ = 78.1; P < .001) and income level (N = 2,512; χ²₁ = 77.7; P < .001) were the most informative in predicting treatment outcome. For the models at weeks 2 and 4, treatment success was best predicted by early symptom improvement.ConclusionsSocioeconomic data such as low income, education, and unemployment were most discriminative in predicting a poor response to citalopram, even with disparities in access to care accounted for. This finding implies that socioeconomic factors may be more useful predictors of medication response than traditional psychiatric diagnoses or past treatment history.Trial registrationClinicalTrials.gov identifier: NCT00021528.

Project description:Inflammation plays a significant role in the pathophysiology of depression. However, not all individuals exposed to inflammatory challenge develop depression, and identifying those at risk is necessary to develop targeted monitoring, prevention, and treatment strategies. Within a randomized double-blind placebo-controlled study (n = 115), we examined whether leukocyte transcriptome profiles predicted inflammation-induced depressed mood in volunteers who received low-dose intravenous endotoxin (n = 58; aged 18-50). At baseline, transcription factor (TF) activities were assessed using genome-wide transcriptional profiling of peripheral blood mononuclear cells and promoter-based bioinformatic analyses. Then, participants were administered endotoxin. Self-reported depressed mood was assessed using the Profile of Mood States. Based on extant studies linking transcriptional profiles to depressive disorder, we examined whether post-endotoxin depressed mood is predicted by baseline activity of TFs related to immune activation, sympathetic activation, and glucocorticoid insensitivity: respectively, nuclear factor kappa B (NF-kB), cAMP response element-binding protein (CREB), and glucocorticoid receptor (GR). Twenty-one participants (36%) experienced an increase in depressed mood from baseline to 2 h post endotoxin, when depressive response peaks. Bioinformatics analyses controlling for age, sex, ethnicity, body mass index, and physical sickness response revealed that post-endotoxin depressed mood was predicted by increased baseline activity of TFs related to inflammation (NF-kB) and beta-adrenergic signaling (CREB) and by decreased activity of GR-related TFs (P's < 0.001). Inflammation-induced depressed mood is predicted by peripheral transcriptome profiles related to immune activation, sympathetic activation, and glucocorticoid insensitivity. With further replication, these stress-related molecular profiles could be used for a novel genomic approach for identifying individuals at high-risk for the inflammatory subtype of depression.

Project description:Metabolomics provides valuable tools for the study of drug effects, unraveling the mechanism of action and variation in response due to treatment. In this study we used electrochemistry-based targeted metabolomics to gain insights into the mechanisms of action of escitalopram/citalopram focusing on a set of 31 metabolites from neurotransmitter-related pathways. Overall, 290 unipolar patients with major depressive disorder were profiled at baseline, after 4 and 8 weeks of drug treatment. The 17-item Hamilton Depression Rating Scale (HRSD17) scores gauged depressive symptom severity. More significant metabolic changes were found after 8 weeks than 4 weeks post baseline. Within the tryptophan pathway, we noted significant reductions in serotonin (5HT) and increases in indoles that are known to be influenced by human gut microbial cometabolism. 5HT, 5-hydroxyindoleacetate (5HIAA), and the ratio of 5HIAA/5HT showed significant correlations to temporal changes in HRSD17 scores. In the tyrosine pathway, changes were observed in the end products of the catecholamines, 3-methoxy-4-hydroxyphenylethyleneglycol and vinylmandelic acid. Furthermore, two phenolic acids, 4-hydroxyphenylacetic acid and 4-hydroxybenzoic acid, produced through noncanconical pathways, were increased with drug exposure. In the purine pathway, significant reductions in hypoxanthine and xanthine levels were observed. Examination of metabolite interactions through differential partial correlation networks revealed changes in guanosine-homogentisic acid and methionine-tyrosine interactions associated with HRSD17. Genetic association studies using the ratios of these interacting pairs of metabolites highlighted two genetic loci harboring genes previously linked to depression, neurotransmission, or neurodegeneration. Overall, exposure to escitalopram/citalopram results in shifts in metabolism through noncanonical pathways, which suggest possible roles for the gut microbiome, oxidative stress, and inflammation-related mechanisms.

Dataset Information

Citalopram amplifies the influence of living conditions on mood in depressed patients enrolled in the STAR*D study.

Publications

Citalopram amplifies the influence of living conditions on mood in depressed patients enrolled in the STAR*D study.

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