Prediction of remission of depression with clinical variables, neuropsychological performance, and serotonergic/dopaminergic gene polymorphisms

Human Psychopharmacology Clinical and Experimental (Impact Factor: 2.19). 11/2012; 27(6):577-86. DOI: 10.1002/hup.2267
Source: PubMed


The aim of our work is to study the possible role of clinical variables, neuropsychological performance, and the 5HTTLPR, rs25531, and val108/58Met COMT polymorphisms on the prediction of depression remission after 12 weeks' treatment with fluoxetine. These variables have been studied as potential predictors of depression remission, but they present poor prognostic sensitivity and specificity by themselves.
Seventy-two depressed patients were genotyped according to the aforementioned polymorphisms and were clinically and neuropsychologically assessed before a 12-week fluxetine treatment.
Only the La allele of rs25531 polymorphism and the GG and AA forms of the val 108/158 Met polymorphism predict major depressive disorder remission after 12 weeks' treatment with fluoxetine. None of the clinical and neuropsychological variables studied predicted remission.
Our results suggest that clinical and neuropsychological variables can initially predict early response to fluoxetine and mask the predictive role of genetic variables; but in remission, where clinical and neuropsychological symptoms associated with depression tend to disappear thanks to the treatment administered, the polymorphisms studied are the only variables in our model capable of predicting remission. However, placebo effects that are difficult to control require cautious interpretation of the results.

Download full-text


Available from: Beatriz Camarena, Sep 22, 2014
15 Reads
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The prediction of remission in pharmacologically-treated MDD patients has been scarcely studied. The goal of our work is to study the possible effect of clinical variables, neuropsychological performance, and the 5HTTLPR, the rs25531 of the SLC6A4 gene, and the val108/58Met of the COMT gene polymorphisms on the prediction of the speed of remission in MDD patients. Seventy-two depressed patients were genotyped according to the aforementioned polymorphisms and were clinically and neuropsychologically assessed before a 12-week fluoxetine treatment. From this original sample 51 patients were considered as remitters at the end of week 12. Thirteen out of those showed a rapid response pattern, 24 showed an oscillating response pattern, and 14 showed a slow response pattern. The following variable combination is capable of showing a statistically significant relationship with the pattern of remission of patients with MDD: initial Hamilton score, age at first depressive episode, AG and GG alleles of the val108/58Met COMT polymorphism, Stroop PC, and SWM Strategy. We have a slightly small sample size, which came to prominence during the data analysis since we were working with 3 subgroups. In this study, the placebo effect has not been controlled. Our data suggest that the patients with MDD who remit after a 12-week treatment with fluoxetine show one of the following time-course patterns: a rapid symptomatic improvement, or a slow or oscillating pattern of remission. A combination of clinical, neuropsychological, and genetic variables allows us to predict these response patterns.
    Journal of Affective Disorders 06/2013; 150(3). DOI:10.1016/j.jad.2013.04.024 · 3.38 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Introduction: The genetic background of antidepressant response represents a unique opportunity to identify biological markers of treatment outcome. Encouraging results alternating with inconsistent findings made antidepressant pharmacogenetics a stimulating but often discouraging field that requires careful discussion about cumulative evidence and methodological issues. Areas covered: The present review discusses both known and less replicated genes that have been implicated in selective serotonin reuptake inhibitors (SSRIs) efficacy and side effects. Candidate genes studies and genome-wide association studies (GWAS) were collected through MEDLINE database search (articles published till January 2014). Further, GWAS signals localized in promising genetic regions according to candidate gene studies are reported in order to assess the general comparability of results obtained through these two types of pharmacogenetic studies. Finally, a pathway enrichment approach is applied to the top genes (those harboring SNPs with p < 0.0001) outlined by previous GWAS in order to identify possible molecular mechanisms involved in SSRI effect. Expert opinion: In order to improve the understanding of SSRI pharmacogenetics, the present review discusses the proposal of moving from the analysis of individual polymorphisms to genes and molecular pathways, and from the separation across different methodological approaches to their combination. Efforts in this direction are justified by the recent evidence of a favorable cost-utility of gene-guided antidepressant treatment.
    Expert Opinion on Drug Metabolism &amp Toxicology 06/2014; 10(8):1-26. DOI:10.1517/17425255.2014.928693 · 2.83 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The pharmacogenetics of antidepressants has been not only a challenging but also frustrating research field since its birth in the 1990s. Indeed, great expectations followed the first evidence of familiar aggregation of antidepressant response. Despite the progress from candidate gene studies to genome-wide association studies (GWAS), results fell out the expectations and they were often inconsistent. Anyway, the cumulative evidence supports the involvement of some genes and molecular pathways in antidepressant efficacy. The best single genes are SLC6A4, HTR2A, BDNF, GNB3, FKBP5, ABCB1, and cytochrome P450 genes (CYP2D6 and CYP2C19). Molecular pathways involved in inflammation and neuroplasticity show the greatest support. The first studies evaluating benefits of genotype-guided antidepressant treatments provided encouraging results and confirmed the relevance of SLC6A4, HTR2A, ABCB1, and cytochrome P450 genes. Further progress in genotyping and data analysis would allow to move forward and complete the understanding of antidepressant pharmacogenetics and its translation into clinical applications.
    Current Psychiatry Reports 07/2015; 17(7). DOI:10.1007/s11920-015-0594-9 · 3.24 Impact Factor