Sexual dysfunction during treatment with serotonergic and noradrenergic antidepressants: Clinical description and the role of the 5-HTTLPR

Objectives. Sexual dysfunction (SD) is a frequently reported side-effect of antidepressant treatment, particularly of selective serotonin reuptake inhibitors (SSRIs). In the multicentre clinical and pharmacogenetic GENDEP study (Genome-based Therapeutic Drugs for Depression), the effect of the serotonin transporter gene promoter polymorphism 5-HTTLPR on sexual function was investigated during treatment with escitalopram (SSRI) and nortriptyline (tricyclic antidepressant). Methods. A total of 494 subjects with an episode of DSM-IV major depression were randomly assigned to treatment with escitalopram or nortriptyline. Over 12 weeks, depressive symptoms and SD were measured weekly with the Montgomery-Asberg Depression Rating Scale, the Antidepressant Side-Effect Checklist, the UKU Side Effect Rating Scale, and the Sexual Functioning Questionnaire. Results. The incidence of reported SD after 12 weeks of treatment was relatively low, and did not differ significantly between antidepressants (14.9% escitalopram, 19.7% nortriptyline). There was no significant interaction between the 5-HTTLPR and antidepressant on SD. Improvement in depressive symptoms and younger age were both associated with lower SD. The effect of age on SD may have been moderated by the 5-HTTLPR. Conclusions. In GENDEP, rates of reported SD during treatment were lower than those described in previous reports. There was no apparent effect of the 5-HTTLPR on the observed decline in SD. © 2011 Informa Healthcare.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Genetic predictors of antidepressant side effects:a grouped candidate gene approach in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study

BACKGROUND: The unwanted side effects associated with antidepressants are key determinants of treatment adherence in depression; propensity to experience these adverse drug reactions (ADRs) may be influenced by genetic variation. However, previous work attempting to ascertain the genetic variants involved has had limited success, in part due to the range of ADRs reported with antidepressants. METHOD: ADRs reported with antidepressant treatment were categorised using their likely pharmacological basis; adrenergic, cholinergic, serotonergic and histaminergic. To identify genetic predictors of susceptibility to each group of ADRs, a candidate gene analysis was performed with data from 431 depressed patients (from a total sample size of 811 patients) enrolled in the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, who were randomly allocated to receive treatment with escitalopram or nortriptyline. Data from 474 patients treated with citalopram or reboxetine in the GenPod project (total sample of 601 patients) were used for replication of significant findings. RESULTS: We found no significant predictors of presumed adrenergic, cholinergic and histaminergic ADRs. Putative serotonergic ADRs were significantly associated with variation in the gene encoding the serotonin 2C receptor (HTR2C, rs6644093, odds ratio (OR)=1.72, 95% confidence interval (CI)=1.31-2.25, p=7.43×10(-5)) in GENDEP. However, this finding was not replicated in GenPod. CONCLUSIONS: The association between serotonergic side effects and variation in the HTR2C gene in the GENDEP sample supports the hypothesis that serotonin receptor-mediated mechanisms underlie these adverse reactions, however this finding was not replicated in GenPod

Genes associated with anhedonia: a new analysis in a large clinical trial (GENDEP)

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10-9) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10-5). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson's Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies

Methodology for clinical genotyping of CYP2D6 and CYP2C19

Many antidepressants, atomoxetine, and several antipsychotics are metabolized by the cytochrome P450 enzymes CYP2D6 and CYP2C19, and guidelines for prescribers based on genetic variants exist. Although some laboratories offer such testing, there is no consensus regarding validated methodology for clinical genotyping of CYP2D6 and CYP2C19. The aim of this paper was to cross-validate multiple technologies for genotyping CYP2D6 and CYP2C19 against each other, and to contribute to feasibility for clinical implementation by providing an enhanced range of assay options, customizable automated translation of data into haplotypes, and a workflow algorithm. AmpliChip CYP450 and some TaqMan single nucleotide variant (SNV) and copy number variant (CNV) data in the Genome-based therapeutic drugs for depression (GENDEP) study were used to select 95 samples (out of 853) to represent as broad a range of CYP2D6 and CYP2C19 genotypes as possible. These 95 included a larger range of CYP2D6 hybrid configurations than have previously been reported using inter-technology data. Genotyping techniques employed were: further TaqMan CNV and SNV assays, xTAGv3 Luminex CYP2D6 and CYP2C19, PharmacoScan, the Ion AmpliSeq Pharmacogenomics Panel, and, for samples with CYP2D6 hybrid configurations, long-range polymerase chain reactions (L-PCRs) with Sanger sequencing and Luminex. Agena MassARRAY was also used for CYP2C19. This study has led to the development of a broader range of TaqMan SNV assays, haplotype phasing methodology with TaqMan adaptable for other technologies, a multiplex genotyping method for efficient identification of some hybrid haplotypes, a customizable automated translation of SNV and CNV data into haplotypes, and a clinical workflow algorithm

Identifying the Common Genetic Basis of Antidepressant Response

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response

Identifying the Common Genetic Basis of Antidepressant Response

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. ----- Methods: Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. ----- Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response

Identifying the Common Genetic Basis of Antidepressant Response

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.</p