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SSRI response in depression may be influenced by SNPs in HTR1B and HTR1A.

ABSTRACT: OBJECTIVES:Desensitization of serotonin 1A (HTR1A) and 1B (HTR1B) autoreceptors has been proposed to be involved in the delayed onset of response to selective serotonin reuptake inhibitors (SSRIs). Variations in gene expression in these genes may thus affect SSRI response. METHODS:Here, we test this hypothesis in two samples from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D), and show evidence for involvement of several genetic variants alone and in interaction. Initially, three functional single nucleotide polymorphisms (SNPs) in the HTR1B gene and in the HTR1A gene were analyzed in 153 depressed patients treated with citalopram. The 16-item Quick Inventory of Depressive Symptomatology Clinician scores were evaluated over time with respect to genetic variation. RESULTS:Individuals homozygous for the -1019 G allele (rs6295) in HTR1A showed the higher baseline 16-item Quick Inventory of Depressive Symptomatology Clinician scores (P=0.033), and by 12 weeks had a significantly lower response rate (P=0.005). HTR1B haplotypes were estimated according to the previously reported in-vitro expression levels. Individuals who were homozygous for the high-expression haplotype showed significantly slower response to citalopram (P=0.034). We then analyzed more SNPs in the extended overall STAR*D sample. Although we could not directly test the same functional SNPs, we found that homozygotes for the G allele at rs1364043 in HTR1A (P=0.045) and the C allele of rs6298 in HTR1B showed better response to citalopram over time (P=0.022). Test for interaction between rs6298 in HTR1B and rs1364043 in HTR1A was significant (overall P=0.032). CONCLUSION:Our data suggest that an enhanced capacity of HTR1B or HTR1A transcriptional activity may impair desensitization of the autoreceptors during SSRI treatment.

SUBMITTER: Villafuerte SM

PROVIDER: S-EPMC2783179 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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SSRI response in depression may be influenced by SNPs in HTR1B and HTR1A.

Villafuerte Sandra M SM Vallabhaneni Kamala K Sliwerska Elzbieta E McMahon Francis J FJ Young Elizabeth A EA Burmeister Margit M

Psychiatric genetics 20091201 6

<h4>Objectives</h4>Desensitization of serotonin 1A (HTR1A) and 1B (HTR1B) autoreceptors has been proposed to be involved in the delayed onset of response to selective serotonin reuptake inhibitors (SSRIs). Variations in gene expression in these genes may thus affect SSRI response.<h4>Methods</h4>Here, we test this hypothesis in two samples from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D), and show evidence for involvement of several genetic variants alone and in interacti ...[more]

PMID: 19829169

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Project description:Introduction: The prediction of antidepressant treatment response may improve outcome. Functional magnetic resonance imaging (fMRI) of emotion processing in major depressive disorder (MDD) may reveal regional brain function serving as predictors of response to treatment with selective serotonin reuptake inhibitor (SSRI). Methods: We examined the association between pre-treatment neural activity by means of fMRI during the perception of emotional stimuli in 22 patients with MDD and the treatment outcome after 6 weeks' medication with an SSRI. A whole brain correlation analysis with Beck Depression Inventory (BDI) change between pre- to post-treatment was conducted to identify neural regions associated with treatment response. Results: During the perception of positive stimuli, responders were characterized by more activation in posterior cingulate cortex (PCC), medial prefrontal cortex, and thalamus as well as middle temporal gyrus. During perception of negative stimuli, PCC, and pregenual anterior cingulate cortex showed the highest correlation with treatment response. Furthermore, responders exhibited higher activation to emotional stimuli than to neutral stimuli in all the above-mentioned regions, while non-responders demonstrated an attenuated neural response to emotional compared to neutral stimuli. Conclusion: Our data suggest that the activity of distinct brain regions is correlated with SSRI treatment outcome and may serve as treatment response predictor. While some regions, in which activity was correlated with treatment response, can be assigned to networks that have been implied in the pathophysiology of depression, most of our regions of interest could also be matched to the default mode network (DMN). Higher DMN activity has been associated with increased rumination as well as negative self-referential processing in previous studies. This may suggest our responders to SSRI to be characterized by such dysregulations and that SSRIs might modify the function associated with this network.

Project description:BackgroundOur previous genome-wide association study (GWAS) on milk fatty acid traits in Chinese Holstein cows revealed, the SNP, BTB-01556197, was significantly associated with C10:0 at genome-wide level (P = 0.0239). It was located in the down-stream of 5-hydroxytryptamine receptor 1B (HTR1B) gene that has been shown to play an important role in the regulation of fatty acid oxidation. Hence, we considered it as a promising candidate gene for milk fatty acids in dairy cattle. In this study, we aimed to investigate whether the HTR1B gene had significant genetic effects on milk fatty acid traits.ResultsWe re-sequenced the entire coding region and 3000 bp of 5' and 3' flanking regions of HTR1B gene. A total of 13 SNPs was identified, containing one in 5' flanking region, two in 5' untranslated region (UTR), two in exon 1, five in 3' UTR, and three in 3' flanking region. By performing genotype-phenotype association analysis with SAS9.2 software, we observed that 13 SNPs were significantly associated with medium-chain saturated fatty acids such as C6:0, C8:0 and C10:0 (P < 0.0001 ~ 0.042). With Haploview 4.1 software, linkage disequilibrium (LD) analysis was performed. Two haplotype blocks formed by two and ten SNPs were observed. Haplotype-based association analysis indicated that both haplotype blocks were strongly associated with C6:0, C8:0 and C10:0 as well (P < 0.0001 ~ 0.0071). With regards to the missense mutation in exon 1 (g.17303383G > T) that reduced amino acid change from alanine to serine, we predicted that it altered the secondary structure of HTR1B protein with SOPMA. In addition, we predicted that three SNPs in promoter region, g.17307103A > T, g.17305206 T > G and g.17303761C > T, altered the binding sites of transcription factors (TFs) HMX2, PAX2, FOXP1ES, MIZ1, CUX2, DREAM, and PPAR-RXR by Genomatix. Of them, luciferase assay experiment further confirmed that the allele T of g.17307103A > T significantly increased the transcriptional activity of HTR1B gene than allele A (P = 0.0007).ConclusionsIn conclusion, our findings provided first evidence that the HTR1B gene had significant genetic effects on milk fatty acids in dairy cattle.

Project description:Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

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SSRI response in depression may be influenced by SNPs in HTR1B and HTR1A.

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SSRI response in depression may be influenced by SNPs in HTR1B and HTR1A.

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