Search

Antidepressant-induced hippocampal neurogenesis (AHN) is hypothesized to contribute to increases in hippocampal volume among major depressive disorder patients after long-term treatment. Furthermore, rodent studies suggest AHN may be the cellular mechanism mediating the therapeutic benefits of antidepressants. Here, we perform the first investigation of genome-wide expression changes associated with AHN in human cells. We identify gene expression networks significantly activated during AHN, and we perform gene set analyses to probe the molecular relationship between AHN, hippocampal volume, and antidepressant response. The latter were achieved using genome-wide association summary data collected from 30,717 individuals as part of the ENIGMA Consortium (genetic predictors of hippocampal volume dataset), and data collected from 1,222 major depressed patients as part of the NEWMEDS Project (genetic predictors of response to antidepressants dataset). Our results showed that the selective serotonin reuptake inhibitor, escitalopram evoked AHN in human cells; dose-dependently increasing the differentiation of cells into neuroblasts, as well as increasing gliogenesis. Activated genome-wide expression networks relate to axon and microtubule formation, and ribosomal biogenesis. Gene set analysis revealed that gene expression changes associated with AHN were nominally enriched for genes predictive of hippocampal volume, but not for genes predictive of therapeutic response., (© 2017 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.)

The mechanisms by which antidepressants have their effects are not clear and the reasons for variability in treatment outcomes are also unknown. However, there is evidence from candidate gene research that indicates gene expression changes may be involved in antidepressant action. In this study, we examined antidepressant-induced alterations in gene expression on a transcriptome-wide scale, exploring associations with treatment response. Blood samples were taken from a subset of depressed patients from the GENDEP study (n=136) before and after eight weeks of treatment with either escitalopram or nortriptyline. Transcriptomic data were obtained from these samples using Illumina HumanHT-12 v4 Expression BeadChip microarrays. When analysing individual genes, we observed that changes in the expression of two genes (MMP28 and KXD1) were associated with better response to nortriptyline. Considering connectivity between genes, we identified modules of genes that were highly coexpressed. In the whole sample, changes in one of the ten identified coexpression modules showed significant correlation with treatment response (cor=0.27, p=0.0029). Using transcriptomic approaches, we have identified gene expression correlates of the therapeutic effects of antidepressants, highlighting possible molecular pathways involved in efficacious antidepressant treatment., (Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.)

Objective: Major depressive disorder has been linked with inflammatory processes, but it is unclear whether individual differences in levels of inflammatory biomarkers could help match patients to treatments that are most likely to be beneficial. The authors tested the hypothesis that C-reactive protein (CRP), a commonly available marker of systemic inflammation, predicts differential response to escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor)., Method: The hypothesis was tested in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study, a multicenter open-label randomized clinical trial. CRP was measured with a high-sensitivity method in serum samples from 241 adult men and women with major depressive disorder randomly allocated to 12-week treatment with escitalopram (N=115) or nortriptyline (N=126). The primary outcome measure was the score on the Montgomery-Åsberg Depression Rating Scale (MADRS), administered weekly., Results: CRP level at baseline differentially predicted treatment outcome with the two antidepressants (CRP-drug interaction: β=3.27, 95% CI=1.65, 4.89). For patients with low levels of CRP (<1 mg/L), improvement on the MADRS score was 3 points higher with escitalopram than with nortriptyline. For patients with higher CRP levels, improvement on the MADRS score was 3 points higher with nortriptyline than with escitalopram. CRP and its interaction with medication explained more than 10% of individual-level variance in treatment outcome., Conclusions: An easily accessible peripheral blood biomarker may contribute to improvement in outcomes of major depressive disorder by personalizing treatment choice.

Although antidepressants are widely used in the pharmacotherapy of major depressive disorder (MDD), their efficacy is still insufficient as approximately one-third of the patients do not fully recover even after several treatment trials. Inter-individual genetic differences are thought to contribute to the variability in antidepressant response; however, current findings from pharmacogenetic studies are uncertain or not clearly replicated. Here we report the first application of full exome sequencing for the analysis of pharmacogenomics on antidepressant treatment. After 12 weeks of treatment with the selective serotonin re-uptake inhibitor escitalopram, we selected five clear responders and five clear non-responders for exome sequencing. By comparing the allele counts of previously known single nucleotide polymorphisms and novel polymorphisms we selected 38 markers for further genotyping in two independent patient samples treated with escitalopram (n=116 and n=394). The A allele, carried by approximately 30% of the patients with MDD, of rs41271330 in the bone morphogenetic protein (BMP5) gene showed strong association with worse treatment response in both sample sets (p=0.001), indicating that this is an promising pharmacogenetic marker for prediction of antidepressant therapeutic outcome.

Transcriptional differences in interleukin-11 (IL11) after antidepressant treatment have been found to correspond to clinical response in major depressive disorder (MDD) patients. Expression differences were partly mediated by a single-nucleotide polymorphism (rs1126757), identified as a predictor of antidepressant response as part of a genome-wide association study. Here we attempt to identify whether DNA methylation, another baseline factor known to affect transcription factor binding, might also predict antidepressant response, using samples collected from the Genome-based Therapeutic Drugs for Depression project (GENDEP). DNA samples from 113 MDD individuals from the GENDEP project, who were treated with either escitalopram (n=80) or nortriptyline (n=33) for 12 weeks, were randomly selected. Percentage change in Montgomery-Åsberg Depression Rating Scale scores between baseline and week 12 were utilized as our measure of antidepressant response. The Sequenom EpiTYPER platform was used to assess DNA methylation across the only CpG island located in the IL11 gene. Regression analyses were then used to explore the relationship between CpG unit methylation and antidepressant response. We identified a CpG unit predictor of general antidepressant response, a drug by CpG unit interaction predictor of response, and a CpG unit by rs1126757 interaction predictor of antidepressant response. The current study is the first to investigate the potential utility of pharmaco-epigenetic biomarkers for the prediction of antidepressant response. Our results suggest that DNA methylation in IL11 might be useful in identifying those patients likely to respond to antidepressants, and if so, the best drug suited to each individual.

Converging evidence suggests that the activation of the inflammatory cytokine pathway is important in the pathophysiology of unipolar depression. Antidepressants have anti-inflammatory properties and evidence suggests that inter-individual variability in response to antidepressants may reflect genetic differences in the inflammatory cytokine pathway. In particular, protein levels of Tumor Necrosis Factor (TNF) and the SNPs rs1126757 in interleukin-11 (IL11), and rs7801617 in interleukin-6 (IL6), have previously been implicated in the clinical response to the selective serotonin reuptake inhibitor (SSRI) antidepressant escitalopram. This study investigated the transcription of TNF, IL11 and IL6 as well as genes in the wider inflammatory cytokine pathway both at baseline and after escitalopram treatment in depressed patients who were either clinical "responders" (n=25) or "non-responders" (n=21). Samples were obtained as a subset of the Genome-Based Therapeutic Drugs for Depression (GENDEP) project and response status is based on changes in the Montgomery-Asberg Depression Rating Scores over a 12 wk treatment period. Binary logistic regressions revealed significant expression differences at baseline between responders and non-responders in TNF, and after escitalopram treatment in TNF and IL11. Differences in IL11 after treatment were found to be driven by drug-induced allele-specific expression differences relating to rs1126757. Top hits in the wider inflammatory cytokine pathway at both baseline and after escitalopram treatment were found to be targets of TNF. The current study adds substantial support for the role of the inflammatory cytokine pathway in mediating response to the SSRI escitalopram, and is the first to identify TNF and its targets as putative transcriptomic predictors of clinical response., (Copyright © 2012 Elsevier B.V. and ECNP. All rights reserved.)

The inflammatory cytokine pathway may be a potential therapeutic target for major depressive disorder (MDD). Previous reports suggest that antidepressants have anti-inflammatory properties and can cause a reduction in proinflammatory cytokines. Recent evidence suggests this might be mediated at the level of the transcriptome. The current study investigated the transcription of 86 genes in the inflammatory cytokine pathway both at baseline and after eight weeks of escitalopram treatment in MDD patients who were either clinical responders (n=25) or non-responders (n=21), using a subset of samples in the Genome-Based Therapeutic Drugs for Depression project (GENDEP). Changes in expression between baseline and eight weeks of treatment were assessed using two-tailed t-tests. To establish if any significant expression changes related to clinical response, the magnitude of the relative expression change between baseline and eight weeks of treatment was established and binary logistic regressions were used to compare differences between responders and non-responders. ATP-binding cassette sub-family F member 1 (ABCF1), a translational regulator of the inflammatory cytokine pathway showed a significant increase in expression after escitalopram treatment which was significantly greater in responders compared to non-responders, suggesting that ABCF1 may play a role in mediating antidepressant response.