Selective Serotonin Reuptake Inhibitors Treatment Response Research Articles

Altered Serotonin 1B Receptor Binding After Escitalopram for Depression Is Correlated With Treatment Effect.

Major depressive disorder (MDD) is commonly treated with selective serotonin reuptake inhibitors (SSRIs). SSRIs inhibit the serotonin transporter (5-HTT), but the downstream antidepressant mechanism of action of these drugs is poorly understood. The serotonin 1B (5-HT1B) receptor is functionally linked to 5-HTT and 5-HT1B receptor binding and 5-HT1B receptor mRNA is reduced in the raphe nuclei after SSRI administration in primates and rodents, respectively. The effect of SSRI treatment on 5-HT1B receptor binding in patients with MDD has not been examined previously. This positron emission tomography (PET) study aimed to quantify brain 5-HT1B receptor binding changes in vivo after SSRI treatment for MDD in relation to treatment effect. Eight unmedicated patients with moderate to severe MDD underwent PET with the 5-HT1B receptor radioligand [11C]AZ10419369 before and after 3 to 4 weeks of treatment with the SSRI escitalopram 10mg daily. Depression severity was assessed at time of PET and after 6 to 7 weeks of treatment with the Montgomery-Åsberg Depression Rating Scale. We observed a significant reduction in [11C]AZ10419369 binding in a dorsal brainstem (DBS) region containing the median and dorsal raphe nuclei after escitalopram treatment (P = .036). Change in DBS [11C]AZ10419369 binding correlated with Montgomery-Åsberg Depression Rating Scale reduction after 3-4 (r = 0.78, P = .021) and 6-7 (r = 0.94, P < .001) weeks' treatment. Our findings align with the previously reported reduction of 5-HT1B receptor binding in the raphe nuclei after SSRI administration and support future studies testing change in DBS 5-HT1B receptor binding as an SSRI treatment response marker.

Developing an Electroencephalography-Based Model for Predicting Response to Antidepressant Medication

Untreated depression is a growing public health concern, with patients often facing a prolonged trial-and-error process in search of effective treatment. Developing a predictive model for treatment response in clinical practice remains challenging. To establish a model based on electroencephalography (EEG) to predict response to 2 distinct selective serotonin reuptake inhibitor (SSRI) medications. This prognostic study developed a predictive model using EEG data collected between 2011 and 2017 from 2 independent cohorts of participants with depression: 1 from the first Canadian Biomarker Integration Network in Depression (CAN-BIND) group and the other from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) consortium. Eligible participants included those aged 18 to 65 years who had a diagnosis of major depressive disorder. Data were analyzed from January to December 2022. In an open-label trial, CAN-BIND participants received an 8-week treatment regimen of escitalopram treatment (10-20 mg), and EMBARC participants were randomized in a double-blind trial to receive an 8-week sertraline (50-200 mg) treatment or placebo treatment. The model's performance was estimated using balanced accuracy, specificity, and sensitivity metrics. The model used data from the CAN-BIND cohort for internal validation, and data from the treatment group of the EMBARC cohort for external validation. At week 8, response to treatment was defined as a 50% or greater reduction in the primary, clinician-rated scale of depression severity. The CAN-BIND cohort included 125 participants (mean [SD] age, 36.4 [13.0] years; 78 [62.4%] women), and the EMBARC sertraline treatment group included 105 participants (mean [SD] age, 38.4 [13.8] years; 72 [68.6%] women). The model achieved a balanced accuracy of 64.2% (95% CI, 55.8%-72.6%), sensitivity of 66.1% (95% CI, 53.7%-78.5%), and specificity of 62.3% (95% CI, 50.1%-73.8%) during internal validation with CAN-BIND. During external validation with EMBARC, the model achieved a balanced accuracy of 63.7% (95% CI, 54.5%-72.8%), sensitivity of 58.8% (95% CI, 45.3%-72.3%), and specificity of 68.5% (95% CI, 56.1%-80.9%). Additionally, the balanced accuracy for the EMBARC placebo group (118 participants) was 48.7% (95% CI, 39.3%-58.0%), the sensitivity was 50.0% (95% CI, 35.2%-64.8%), and the specificity was 47.3% (95% CI, 35.9%-58.7%), suggesting the model's specificity in predicting SSRIs treatment response. In this prognostic study, an EEG-based model was developed and validated in 2 independent cohorts. The model showed promising accuracy in predicting treatment response to 2 distinct SSRIs, suggesting potential applications for personalized depression treatment.

Cortical Thickness Predicts Response Following 2 Weeks of SSRI Regimen in First-Episode, Drug-Naive Major Depressive Disorder: An MRI Study.

ObjectiveMajor depression disorder (MDD) is a harmful disorder, and the pathological mechanism remains unclear. The primary pharmacotherapy regimen for MDD is selective serotonin reuptake inhibitors (SSRIs), but fewer than 40% of patients with MDD are in remission following initial treatment. Neuroimaging biomarkers of treatment efficacy can be used to guide personalized treatment in MDD. This study aims to determine if cortical thickness can be used as a predictor for SSRIs.MethodsA total of 126 first-episode, drug-naive MDD patients (MDDs) and 71 healthy controls (HCs) were enrolled in our study. Demographic data were collected according to the self-made case report form (CRF) at the baseline of all subjects. Magnetic resonance imaging (MRI) scanning was performed for all the participants at baseline, and all imaging was processed using the DPABISurf software. All MDDs were treated with SSRIs, and symptoms were assessed at both the baseline and 2 weeks using the 17-item Hamilton Rating Scale (HAMD-17). According to HAMD-17 total score improvement from baseline to the end of 2 weeks, the MDDs were divided into the non-responder group (defined as ≤ 20% HAMD-17 reduction) and responder group (defined as ≥50% HAMD-17 reduction). The receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of MDDs' and HCs' cortical thickness for MDD. Correlation analysis was performed for the responder group and the non-responder group separately to identify the relationship between cortical thickness and SSRI treatment efficacy. To analyze whether cortical thickness was sufficient to differentiate responders and non-responders at baseline, we used ROC curve analysis.ResultsSignificant decreases were found in the cortical thickness of the right supplementary motor area (SMA) in MDDs at the baseline (corrected by the Monte Carlo permutation correction, cluster-wise significant threshold at p < 0.025 and vertex-wise threshold at p = 0.001), area under the curve (AUC) = 0.732 [95% confidence interval (CI) = 0.233–0.399]. In the responder group, the cortical thickness of the right SMA was significantly thinner than in the non-responder group at baseline. There was a negative correlation (r = −0.373, p = 0.044) between the cortical thickness of SMA (0 weeks) and HAMD-17 reductive rate (2 weeks) in the responder group. The results of ROC curve analyses of the responder and non-responder groups were AUC = 0.885 (95% CI = 0.803–0.968), sensitivity = 73.5%, and specificity = 96.6%, and the cutoff value was 0.701.ConclusionLower cortical thickness of the right SMA in MDD patients at the baseline may be a neuroimaging biomarker for MDD diagnosis, and a greater extent of thinner cortical thickness in the right SMA at baseline may predict improved SSRI treatment response. Our study shows the potential of cortical thickness as a possible biomarker that predicts a patient's clinical treatment response to SSRIs in MDD.

Alterations in acylcarnitines, amines, and lipids inform about the mechanism of action of citalopram/escitalopram in major depression

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines—including arginine, proline, and methionine sulfoxide—were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (<30% reduction in HRSD17). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics—including acylcarnitine metabolism, transport, and its link to β-oxidation—and lipid membrane remodeling may play roles in SSRI treatment response.

SSRI Treatment Response Prediction in Depression Based on Brain Activation by Emotional Stimuli.

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.

The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression.

Selective serotonin reuptake inhibitors (SSRIs) are first-line antidepressants for the treatment of major depressive disorder (MDD). However, treatment response during an initial therapeutic trial is often poor and is difficult to predict. Heterogeneity of response to SSRIs in depressed patients is partly driven by co-occurring somatic disorders such as coronary artery disease (CAD) and obesity. CAD and obesity may also be associated with metabolic side effects of SSRIs. In this study, we assessed the association of CAD and obesity with treatment response to SSRIs in patients with MDD using a polygenic score (PGS) approach. Additionally, we performed cross-trait meta-analyses to pinpoint genetic variants underpinnings the relationship of CAD and obesity with SSRIs treatment response. First, PGSs were calculated at different p value thresholds (PT) for obesity and CAD. Next, binary logistic regression was applied to evaluate the association of the PGSs to SSRIs treatment response in a discovery sample (ISPC, N = 865), and in a replication cohort (STAR*D, N = 1,878). Finally, a cross-trait GWAS meta-analysis was performed by combining summary statistics. We show that the PGSs for CAD and obesity were inversely associated with SSRIs treatment response. At the most significant thresholds, the PGS for CAD and body mass index accounted 1.3%, and 0.8% of the observed variability in treatment response to SSRIs, respectively. In the cross-trait meta-analyses, we identified (1) 14 genetic loci (including NEGR1, CADM2, PMAIP1, PARK2) that are associated with both obesity and SSRIs treatment response; (2) five genetic loci (LINC01412, PHACTR1, CDKN2B, ATXN2, KCNE2) with effects on CAD and SSRIs treatment response. Our findings implicate that the genetic variants of CAD and obesity are linked to SSRIs treatment response in MDD. A better SSRIs treatment response might be achieved through a stratified allocation of treatment for MDD patients with a genetic risk for obesity or CAD.

Fluoxetine Modulates Spontaneous and Conditioned Behaviors to Carbon Dioxide (CO2) Inhalation and Alters Forebrain–Midbrain Neuronal Activation

Panic disorder (PD), a prevalent anxiety disorder, is characterized by unexpected panic attacks, persistent anxiety and avoidance of panic contexts. Selective serotonin reuptake inhibitors (SSRIs) are effective in treating PD; however, the mechanisms underlying SSRI efficacy are poorly understood. Using CO2-inhalation, a PD-relevant translational paradigm, we examined the effect of chronic SSRI (fluoxetine) treatment on unconditioned and context-conditioned defensive behaviors, as well as respiratory responses, in mice. In addition, cFos expression was evaluated as a measure of the functional activity and interregional correlation matrices were used to explore the neurocircuitry recruited in CO2-conditioned behavior and SSRI treatment response. Chronic fluoxetine attenuated CO2-induced passive (freezing) behavior during inhalation and active (rearing) behavior on re-exposure to context, in addition to reducing CO2-evoked respiratory responses. Brain mapping in CO2-context-conditioned mice revealed altered regional neuronal activation within and correlations across midbrain regions subserving defensive behaviors (periaqueductal gray (PAG) and raphe nuclei) and forebrain emotional and contextual processing loci (medial prefrontal cortex, insular cortex and hippocampus). Importantly, fluoxetine treatment normalized these alterations. Collectively, our results provide novel information on fluoxetine modulation of panic-relevant defensive behaviors and neurocircuitry, facilitating increased understanding of panic neurobiology in the context of treatment response.

Pretreatment and early-treatment cortical thickness is associated with SSRI treatment response in major depressive disorder.

To date, there are no biomarkers for major depressive disorder (MDD) treatment response in clinical use. Such biomarkers could allow for individualized treatment selection, reducing time spent on ineffective treatments and the burden of MDD. In search of such a biomarker, multisite pretreatment and early-treatment (1 week into treatment) structural magnetic resonance (MR) images were acquired from 184 patients with MDD randomized to an 8-week trial of the selective serotonin reuptake inhibitor (SSRI) sertraline or placebo. This study represents a large, multisite, placebo-controlled effort to examine the association between pretreatment differences or early-treatment changes in cortical thickness and treatment-specific outcomes. For standardization, a novel, robust site harmonization procedure was applied to structural measures in a priori regions (rostral and caudal anterior cingulate, lateral orbitofrontal, rostral middle frontal, and hippocampus), chosen based on previously published reports. Pretreatment cortical thickness or volume did not significantly associate with SSRI response. Thickening of the rostral anterior cingulate cortex in the first week of treatment was associated with better 8-week responses to SSRI (p = 0.010). These findings indicate that frontal lobe structural alterations in the first week of treatment may be associated with long-term treatment efficacy. While these associational findings may help to elucidate the specific neural targets of SSRIs, the predictive accuracy of pretreatment or early-treatment structural alterations in classifying treatment remitters from nonremitters was limited to 63.9%. Therefore, in this large sample of adults with MDD, structural MR imaging measures were not found to be clinically translatable biomarkers of treatment response to SSRI or placebo.

Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder.

Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.

Different functioning of prefrontal cortex predicts treatment response after a selective serotonin reuptake inhibitor treatment in patients with major depression

BackgroundMajor depressive disorder (MDD) is often resistant to treatment with usual approaches. Patients with MDD have shown hypofunction of the frontotemporal cortex in verbal fluency test (VFT)-related near-infrared spectroscopy (NIRS). MethodsWe examined whether the reactions to drug treatment in treatment-naive patients with MDD could be predicted by NIRS outcomes at the initial investigation. All subjects underwent psychological testing to determine levels of anxiety and depression. VFT was used to examine the functioning of the frontotemporal lobes. We administered selective serotonin reuptake inhibitors (SSRIs) for 12 weeks. Subjects included 28 patients with MDD with response to SSRIs (Response group), 19 with no response (Non-Response group), and 63 age-, sex-, and education years-matched healthy controls (HC). ResultsWe found in the frontotemporal region that hemodynamic responses were significantly smaller in patients with Response and Non-Response groups than in HC before treatment. We also found in the medial frontal region that hemodynamic responses were significantly larger in patients with Response groups than in patients with Non-Response group before treatment. Patients with MDD scored significantly higher anxiety and depressive states than those in HC on several measures. The Response and Non-Response groups also had higher scores in future denial, threat prediction, self-denial, past denial, and interpersonal threat sections of Anxiety Cognition Scale (DACS). According to the stepwise regression analysis, one variable was determined as independent predictors of response: confusion (Post-POMS). LimitationsThe number of patients and healthy controls was relatively small, and we will increase the number of participants in future studies. NIRS has reduced spatial resolution, which confuses the identification of the measurement position when using NIRS alone. ConclusionCognitive vulnerabilities are associated with predictors of SSRI treatment response. Different hemodynamic activities in the frontotemporal cortex predict response to SSRI treatment in MDD.

Polygenic Score for Cardiometabolic and Psychiatric Phenotypes Predict Response to Treatment with Selective Serotonin Reuptake Inhibitors in Major Depressive Disorder

Selective serotonin reuptake inhibitors (SSRIs) are the first line antidepressants to treat major depressive disorder (MDD). Among other factors, the co-morbidity of depression with other psychiatric and cardiometabolic disorders may negatively influence antidepressants treatment response. Moreover, response to antidepressants is considered as a complex trait with substantial contribution from a large number of common genetic variants of small effect. Hence, polygenic scores (PGSs) could be a useful tool to estimate the overall effect of genetically driven factors on the treatment outcome.Here, we evaluated whether PGSs derived from 25 recognized comorbid cardiometabolic and psychiatric disorders, personality traits and educational parameters predict treatment response to SSRIs in MDD. In order to create the PGSs, we used genome-wide genotype data obtained from 865 MDD patients who received SSRIs treatment and GWAS summary statistics for the 25 disorders and phenotypes. The PGSs were calculated within a P-value threshold (PT) as the sum of the single nucleotide polymorphisms effect allele multiplied by its corresponding GWAS effect size (β- coefficient or log (OR)) weighted by the sum of the GWAS effect sizes.Clinical, demographic and SSRIs treatment response data were collected from 865 MDD patients by the ISPC. Baseline and follow-up SSRIs treatment response were measured using the 17-item Hamilton Rating Scale for Depression (HRSD-17). After 4 weeks of treatment, patients with at least 50% reduction in HRSD-17 from the baseline score were classified as responders and patients with a score of less than or equal to seven were considered as remitters. Once the PGSs were calculated, binary logistic regression analyses were performed between the dependent variables (response or remission to SSRIs) and the PGSs in each of the 25 disorders and phenotypes adjusted for the covariates (age, sex and study sites). Finally, we reported the best-predictive PGS for each disorder and phenotype that predicts the treatment outcome with the smallest p-value. A statistically significant association was determined at P < 0.05.We found that the PGSs for MDD, depressive symptoms, type 2 diabetes, body mass index, plasma levels of fasting proinsulin or fasting glucose, openness personality trait, subjective wellbeing and educational attainment significantly (P < 0.05) predicted both response and remission to SSRIs treatment in MDD patients. Additionally, the PGS for coronary artery disease, plasma level of total cholesterol, agreeableness and conscientiousness personality traits showed a significant association with remission, but not with response. Our findings suggest that the influence of cardiometabolic and psychiatric co-morbidities on antidepressants treatment response could be at least partly determined at a genetic level.

T30 - The Role Of Circulating Micrornas As Possible Biomarkers Predicting Response And Adverse Events In Depressed And Anxious Children And Adolescents Treated With Fluoxetine

Background Depression and anxiety disorders are among the most common childhood psychiatric disorders. Selective serotonin reuptake inhibitors (SSRIs) are generally considered first-line treatment for both depression and anxiety in this age group. However, it has been reported that 30%–40% of all patients who receive a sufficient dose and duration of treatment fail to respond. Moreover, SSRI use is frequently associated with serious adverse events (AE), including activation symptoms, manic switch and increased suicidal behavior. These are particularly relevant in pediatric populations because of concerns about the suicide threat of SSRIs, resulting in a black-box warning. Currently there is no way of knowing in advance who of the patients will respond or develop AE. The purpose of the current study is to examine the role of circulating small non-coding RNA's (ncRNA's) as a promising candidate biomarker for SSRI treatment response and AE in children and adolescents treated for depression and anxiety disorders. Methods Eighty patients who met DSM-IV criteria for major depressive disorder (MDD) or anxiety disorders participated in the study. Their age ranged from 6 to 18 (14.12 ± 2.30) years. The patients were treated with fluoxetine 20-40 mg/day for 8 weeks. Psychiatric evaluation was conducted using several standardized diagnostic instruments. The changes in depressive and anxiety symptoms from baseline to 8 weeks were assessed, and remitters and non-responders were compared. Suicidal events, as per convention in pharmacological trials, were defined as either a suicide attempt or an onset or worsening in suicidal ideation. Activation was assessed using a new scale devised by our group for the project and mania by the Young Mania Rating Scale. Blood samples from all the participants were collected before treatment initiation and after eight weeks. RNA was purified using QIAGEN kit and libraries were prepared for sequencing using the Illumina TruSeq Small RNA Library Preparation Kit. miRBase based quantification of miRNAs was carried out on each sample. Samples with less than 1,000,000 miRNA reads were excluded. DeSeq2 was performed for statistical analysis. Results The overall response rate was 67%. Seventeen children and adolescents (21%) responded with moderate or severe AE. In total 86 samples were analyzed. Ten differentially expressed miRNA’s were found between the responders with no AE vs. non-responders/responders + moderate or severe AE. Discussion Ongoing studies: A recruitment of a new cohort of children for validation of the finding in the first cohort will follow. The differentially regulated small ncRNA's will form the basis of a study in an animal model of juvenile depression which will hopefully enable us to gain insights into the mechanism of how these models are involved in the biology of response to treatment and perhaps even of juvenile depression.

Systems genetics analysis of pharmacogenomics variation during antidepressant treatment.

Selective serotonin reuptake inhibitors (SSRIs) are the most widely used antidepressants, but the efficacy of the treatment varies significantly among individuals. It is believed that complex genetic mechanisms play a part in this variation. We have used a network based approach to unravel the involved genetic components. Moreover, we investigated the potential difference in the genetic interaction networks underlying SSRI treatment response over time. We found four hub genes (ASCC3, PPARGC1B, SCHIP1 and TMTC2) with different connectivity in the initial SSRI treatment period (baseline to week 4) compared with the subsequent period (4-8 weeks after initiation), suggesting that different genetic networks are important at different times during SSRI treatment. The strongest interactions in the initial SSRI treatment period involved genes encoding transcriptional factors, and in the subsequent period genes involved in calcium homeostasis. In conclusion, we suggest a difference in genetic interaction networks between initial and subsequent SSRI response.

Catecholamine pathway polymorphisms and antidepressant response.

Genes that regulate the catecholamine metabolism pathways are potential targets for research in the antidepressant treatment response. This study was intended to determine whether antidepressant responses to selective serotonin reuptake inhibitors (SSRIs) are associated with genetic polymorphisms of the tyrosine or tryptophan gene in Chinese major depressive disorder (MDD) patients. A total of 290 MDD patients were recruited and received a 6-week SSRIs randomized double-blinded treatment. Allele, genotype, and haplotype frequencies were compared between responders and nonresponders in catecholamine genes. Genotype frequency of the rs1800544 polymorphism in the DRD4 gene was significantly different between responders and nonresponders after false discovery rate correction (P = 0.042). The frequency of the DRD4 rs1800544 CG genotype was significantly higher (P = 0.003) in responders (51.4%) than in nonresponders (35.8%), and patients with the CG genotype showed an 81.7% response rate. In comparison, the response rates were 73.9% and 52.2% in patients with the GG genotype and the CC genotype, respectively. The frequencies of the DRD4 rs1800544 CC and GG genotypes were significantly lower (P = 0.003) in responders (7.7%, 40.9%) than in the nonresponders (19.4%, 44.8%). No significant difference was found between two groups either in genotype or allele frequencies of single nucleotide polymorphisms in the TPH, SLC6A2, SLC6A3, or DRD2 genes. No significant difference was found between two groups in TPH, SLC6A2, SLC6A3, DRD2, orDRD4 gene haplotypes. Polymorphisms of the DRD4 gene appear to be associated with SSRI treatment response in Chinese MDD patients.

Role of the serotonin transporter gene locus in the response to SSRI treatment of major depressive disorder in late life.

It has been suggested that the serotonin or 5-hydroxytriptamine (5-HT) transporter (5-HTT) and its gene-linked polymorphic region (5-HTTLPR) are selective serotonin reuptake inhibitor (SSRI) response modulators in late-life depression (LLD), and particularly in late-life major depressive disorder (MDD). Previous studies differed in design and results. Our study aimed to investigate the solute carrier family 6 (neurotransmitter transporter and serotonin) member 4 (SLC6A4) gene locus, encoding 5-HTT and SSRI treatment response in late-life MDD. For a prospective cohort study, we enrolled 234 patients with late-life MDD to be treated with escitalopram, sertraline, paroxetine or citalopram for 6 months. The SLC6A4 polymorphisms rs4795541 (5-HTTLPR), rs140701 and rs3813034 genotypes spanning the SLC6A4 locus were investigated in blinded fashion. No placebo group was included. We assessed responder or non-responder phenotypes according to a reduction in the 21-item version of the Hamilton Depression Rating Scale (HDRS-21) score of ⩾ 50%. At follow-up, 30% of the late-life MDD patients were non-responders to SSRI treatment. No time-course of symptoms and responses was made. A poor response was associated with a higher baseline HDRS-21 score. We observed a significant over-representation of the rs4795541-S allele in the responder patients (0.436 versus 0.321; p = 0.023). The single S-allele dose-additive effect had OR = 1.74 (95% CI 1.12-2.69) in the additive regression model. Our findings suggested a possible influence of 5-HTTLPR on the SSRI response in patients with late-life MDD, which is potentially useful in identifying the subgroups of LLD patients whom need a different pharmacological approach.

SLC17A7 gene may be the indicator of selective serotonin reuptake inhibitor treatment response in the Chinese Han population.

Selective serotonin reuptake inhibitors (SSRIs) are widely used drugs for major depressive disorder (MDD), although the treatment outcomes vary in different people. The vesicular glutamate transporter 1 coded by SLC17A7 gene has been reported associated with MDD. According to its role in glutamate transmission, it is reasonable to consider it as a potential pharmacogenetic candidate in SSRI treatment. A total of 290 MDD patients who had been taking SSRIs for 6 weeks were recruited. Their genotypes were assessed for the presence of 4 single-nucleotide polymorphisms, which were selected from either the HapMap Chinese ethnic group or the literature report. Treatment effects were evaluated by the change rate of Hamilton Rating Scale for Depression. After the adjustment for the false discovery rate, 1 single-nucleotide polymorphism (rs74174284, false discovery rate; P = 0.032) demonstrated significant association with SSRI treatment response at week 6. Our results suggest that genetic variants in the SLC17A7 gene may be indicators of treatment response in MDD patients treated by SSRIs.

Brain-derived Neurotrophic Factor Genetic Variants are Associated with Major Depression Susceptibility and Serotonin Reuptake Inhibitor Antidepressant Treatment Response in Taiwanese

The involvement of neurotrophic factors, notably brain-derived neurotrophic factor (BDNF) has been suggested in the pathogenesis of major depressive disorder (MDD) and in the response of antidepressant treatment both in preclinical and clinical studies. Thus, genetic variation in human BDNF gene may be associated with MDD susceptibility and be related to treatment response to antidepressants in patients with MDD. Two hundred and eighty-eight Taiwanese patients diagnosed with MDD and 397 participants with similar mean age and gender distribution were enrolled in the study, and three markers, including rs6265 (Val66Met) in the BDNF gene were examined for their association with MDD and 4-week response to selective serotonin reuptake inhibitors (SSRI) (n = 216) using single- and haplotype-based analyses. The results showed that the Met allele of rs6265 was in allelic association with MDD. Haplotype analysis of marker combination rs2049046-rs7103411-rs6265 further indicated the association between BDNF genetic polymorphisms and MDD (global permutation p = 0.0007). Regarding 4-week SSRI treatment response and controlling the effect of relevant covariates using logistic regression, the heterozygotes of rs7103411 and rs6265 had higher treatment responder percentage than their homozygous analogs. Furthermore, MDD patients carrying AGA-TAG diplotype tended to be the responders to 4-week SSRIs treatment compared with the non-AGA-TAG diplotype carriers (corrected p= 0.048). One strength of our study is the relatively large sample size. Our findings suggest that BDNF may be a susceptibility gene for MDD, and may also confer a heterosis effect for antidepressant treatment response. Keywords: Brain-derived neurotrophic factor association, depression, heterosis effect, polymorphism, selective serotonin reuptake inhibitor.

ABCB6 , ABCB1 and ABCG1 Genetic Polymorphisms and Antidepressant Response of SSRIs in Chinese Depressive Patients

Major depressive disorder is a common psychiatric disorder with worldwide prevalence. The most widely prescribed antidepressants are selective serotonin reuptake inhibitors (SSRIs). ATP-binding cassette proteins are responsible for the membrane transport of various molecules including antidepressive drugs. We investigated whether SNPs in ABCB6, ABCB1 and ABCG1 were associated with the treatment response of SSRIs. A pharmacogenetic study genotyping nine SNPs was conducted in 290 major depressive disorder patients in the Chinese Han population. Allele and genotype frequencies were compared between responders and nonresponders. The allele frequencies of rs28401781 and rs4148739 in ABCB1 showed significant difference between responders and nonresponders before correction (p = 0.0297 and p = 0.0359, respectively). No significant associations were detected for the ABCB6 or ABCG1 gene. Our results suggest that ABCB1 polymorphisms might be associated with SSRIs treatment response in the Chinese Han population.

Augmentation strategies in obsessive–compulsive disorder

Around 40–60% of patients with obsessive–compulsive disorder do not show adequate response to selective serotonin reuptake inhibitors (SSRIs). Augmentation strategies are recommended in people who show partial response to SSRI treatment or poor response to multiple SSRIs. In this article, the authors review the evidence for augmentation strategies. The available evidence is predominantly based on small-scale, randomized controlled trials, open-label trials and case series. Antipsychotic augmentation, especially risperidone, haloperidol, aripiprazole and cognitive-behavior therapy have shown the best evidence. Ondansetron, memantine, riluzole, clomipramine, mirtazapine and repetitive transcranial magnetic stimulation over supplementary motor area show some preliminary evidence. Ablative neurosurgery or deep brain stimulation may be tried in carefully selected treatment refractory patients.

Prediction of SSRI treatment response in major depression based on serotonin transporter interplay between median raphe nucleus and projection areas

Recent mathematical models suggest restored serotonergic burst-firing to underlie the antidepressant effect of selective serotonin reuptake inhibitors (SSRI), resulting from down-regulated serotonin transporters (SERT) in terminal regions. This mechanism possibly depends on the interregional balance between SERTs in the raphe nuclei and in terminal regions before treatment. To evaluate these hypotheses on a systems level in humans in vivo, we investigated SERT availability and occupancy longitudinally in patients with major depressive disorder using positron emission tomography (PET) and the radioligand [11C]DASB. Measurements were performed before and after a single oral dose, as well as after three weeks (mean 24.73±3.3 days) of continuous oral treatment with either escitalopram (10 mg/day) or citalopram (20 mg/day). Data were analyzed using voxel-wise linear regression and ANOVA to evaluate SERT binding, occupancy and binding ratios (SERT binding of the entire brain compared to SERT binding in the dorsal and median raphe nuclei) in relation to treatment outcome. Regression analysis revealed that treatment response was predicted by pre-treatment SERT binding ratios, i.e., SERT binding in key regions of depression including bilateral habenula, amygdala-hippocampus complex and subgenual cingulate cortex in relation to SERT binding in the median but not dorsal raphe nucleus (p<0.05 FDR-corrected). Similar results were observed in the direct comparison of responders and non-responders. Our data provide a first proof-of-concept for recent modeling studies and further underlie the importance of the habenula and subgenual cingulate cortex in the etiology of and recovery from major depression. These findings may indicate a promising molecular predictor of treatment response and stimulate new treatment approaches based on regional differences in SERT binding.