Selective Serotonin Reuptake Inhibitors Response Research Articles

Exploring genetic causal relationship between antidepressants use and congenital malformations

Existing studies have demonstrated that the use of antidepressants is associated with congenital malformations; however, the conclusions are inconsistent, and the potential causal relationship remains unclear. Based on large-scale genetic data, we conducted a two-sample Mendelian randomization (MR) study. The exposure datasets included the use of antidepressants, responses to selective serotonin reuptake inhibitors (SSRIs), and the use of four SSRIs-related antidepressants: fluoxetine, citalopram, paroxetine, and sertraline. The outcome datasets encompassed congenital malformations across 12 major organ systems, as well as overall congenital malformations. All datasets were of European ancestry. We employed inverse variance weighting (IVW), MR-Egger, and weighted median methods as our MR analytical approaches. Additionally, the robustness of the MR results was evaluated through a series of sensitivity analyses. After Bonferroni multiple comparisons, MR results did not reveal a significant association between the use of all antidepressants and any congenital malformations. However, IVW provided a suggestive positive association between antidepressants use and congenital digestive malformations (OR = 1.28, 95 % CI = 1.01–1.62, P = 0.039), as well as between SSRIs response and respiratory system malformations (OR = 1.21, 95 % CI = 1.02–1.44, P = 0.033), and fluoxetine use and nervous system malformations (P = 0.026). This study did not find evidence of an association between the use of citalopram, paroxetine, or sertraline and any congenital malformations. Our study provides evidence of a causal association between exposure to antidepressants and certain specific congenital malformations. However, further in-depth research is needed to confirm this association and explore the underlying biological mechanisms.

The Impact of Development on Antidepressant and Placebo Response in Anxiety Disorders: A Bayesian Hierarchical Meta-Analytic Examination of Randomized Controlled Trials in Children, Adolescents, and Adults.

Background: Understanding how development influences medication and placebo responses in anxiety disorders could inform treatment decisions, including age-specific first- versus second-line psychopharmacological interventions. Objective: To meta-analytically compare the trajectory of selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and placebo response in youth and adults with anxiety disorders. Methods: Weekly symptom severity data were extracted from prospective, randomized, parallel-group, placebo-controlled trials of SSRIs and SNRIs in children, adolescents, and adults with anxiety disorders (generalized, separation, and social anxiety disorders as well as panic disorder). Treatment response was modeled for the standardized change in continuous measures of anxiety using a Bayesian hierarchical model. Change in symptom severity was evaluated as a function of time, and post hoc analyses were conducted to determine the sensitivity of these results across sample heterogeneity and alternative functional forms. Results: Data were included from 11 trials of youth (SSRI, κ = 7; SNRI, κ = 4) and 71 studies of adults (SSRI, κ = 46; SNRI, κ = 25). In total, 1067 youth participated in SSRI trials and 1024 in SNRI trials. In total, 10,826 adults participated in SSRI trials (placebo, n = 5367; SSRI n = 5,459) and 6232 in SNRI trials (placebo, n = 3,128; SNRI n = 3,094). A logarithmic model best described the response. Placebo response was similar in youth and adults (mean difference = -1.98 ± 6.21, 95% credible interval [CrI]: -10.2 to 14.2, p = 0.750), and statistically significant improvement from baseline emerged by week 2 in both adults (mean difference: -18.34 + 1.017, 95% CrI: -20.3 to 16.3, p < 0.001) and youth (mean difference: -23.74 + 3.736, 95% CrI: -31.1 to -16.4, p < 0.001). SSRIs produced similar improvements for youth and adults (p = 0.129), but SNRIs produced slower improvement in youth than adults (p = 0.018). Conclusions: Antidepressant-related improvement occurs early in youth and adults with anxiety disorders. SSRI response is similar in adults and youth; however, SNRIs produce greater responses in adults than youth, potentially representing a developmental effect.

426 Selective serotonin reuptake inhibitor response in people with cystic fibrosis

426 Selective serotonin reuptake inhibitor response in people with cystic fibrosis

Shorter telomere length predicts poor antidepressant response and poorer cardiometabolic indices in major depression

Telomere length (TL) is a marker of biological aging, and shorter telomeres have been associated with several medical and psychiatric disorders, including cardiometabolic dysregulation and Major Depressive Disorder (MDD). In addition, studies have shown shorter TL to be associated with poorer response to certain psychotropic medications, and our previous work suggested shorter TL and higher telomerase activity (TA) predicts poorer response to Selective Serotonin Reuptake Inhibitor (SSRI) treatment. Using a new group of unmedicated medically healthy individuals with MDD (n = 48), we sought to replicate our prior findings demonstrating that peripheral blood mononuclear cell (PBMC) TL and TA predict response to SSRI treatment and to identify associations between TL and TA with biological stress mediators and cardiometabolic risk indices. Our results demonstrate that longer pre-treatment TL was associated with better response to SSRI treatment (β = .407 p = .007). Additionally, we observed that TL had a negative relationship with allostatic load (β = − .320 p = .017) and a cardiometabolic risk score (β = − .300 p = .025). Our results suggest that PBMC TL reflects, in part, the cumulative effects of physiological stress and cardiovascular risk in MDD and may be a biomarker for predicting SSRI response.

Impact of CYP2C19 metaboliser status on SSRI response: a retrospective study of 9500 participants of the Australian Genetics of Depression Study

BackgroundVariation within the CYP2C19 gene has been linked to differential metabolism of selective serotonin reuptake inhibitors (SSRIs). Pharmacogenetic recommendations based on the effect of CYP2C19 variants have been made available and are used increasingly by clinical practitioners. Nonetheless, the underlying assumption linking differential metabolism to efficacy or adverse side effects remains understudied. Here, we aim to fill this gap by studying CYP2C19 polymorphisms and inferred metabolism and patient-reported antidepressant response in a sample of 9531 Australian adults who have taken SSRIs.MethodsMetaboliser status was inferred for participants based on CYP2C19 alleles. Primary analysis consisted of assessing differences in treatment efficacy and tolerability between normal (reference) and: ultrarapid, rapid, intermediate and poor metabolisers.ResultsAcross medications, poor metabolisers reported a higher efficacy, whereas rapid metabolisers reported higher tolerability. When stratified by drug, associations between metaboliser status and efficacy did not survive multiple testing correction. Intermediate metabolisers were at greater odds of reporting any side effect for sertraline and higher number of side effects across medications and for sertraline.ConclusionsThe effects between metaboliser status and treatment efficacy, tolerability and side effects were in the expected direction. Our power analysis suggests we would detect moderate to large effects, at least nominally. Reduced power may also be explained by heterogeneity in antidepressant dosages or concomitant medications, which we did not measure. The fact that we identify slower metabolisers to be at higher risk of side effects even without adjusting for clinical titration, and the nominally significant associations consistent with the expected metabolic effects provide new evidence for the link between CYP2C19 metabolism and SSRI response. Nonetheless, longitudinal and interventional designs such as randomized clinical trials that stratify by metaboliser status are necessary to establish the effects of CYP2C19 metabolism on SSRI treatment efficacy or adverse effects.

The Impact of Marijuana on Antidepressant Treatment in Adolescents: Clinical and Pharmacologic Considerations.

The neuropharmacology of marijuana, including its effects on selective serotonin reuptake inhibitor (SSRI)/antidepressant metabolism and the subsequent response and tolerability in youth, has received limited attention. We sought to (1) review clinically relevant pharmacokinetic (PK) and pharmacodynamic (PD) interactions between cannabinoids and selected SSRIs, (2) use PK models to examine the impact of cannabinoids on SSRI exposure (area under curve (AUC)) and maximum concentration (CMAX) in adolescents, and (3) examine the frequency of adverse events reported when SSRIs and cannabinoids are used concomitantly. Cannabinoid metabolism, interactions with SSRIs, impact on relevant PK/PD pathways and known drug–drug interactions were reviewed. Then, the impact of tetrahydrocannabinol (THC) and cannabidiol (CBD) on exposure (AUC24) and CMAX for escitalopram and sertraline was modeled using pediatric PK data. Using data from the Food and Drug Administration Adverse Events Reporting System (FAERS), the relationship between CBD and CYP2C19-metabolized SSRIs and side effects was examined. Cannabis and CBD inhibit cytochrome activity, alter serotonergic transmission, and modulate SSRI response. In PK models, CBD and/or THC increases sertraline and es/citalopram concentrations in adolescents, and coadministration of CBD and CYP2C19-metabolized SSRIs increases the risk of cough, diarrhea, dizziness, and fatigue. Given the significant SSRI–cannabinoid interactions, clinicians should discuss THC and CBD use in youth prescribed SSRIs and be aware of the impact of initiating, stopping, or decreasing cannabinoid use as this may significantly affect es/citalopram and sertraline exposure.

Multi-Omic Sex-Specific Biology in MDD: eQTL Correlates of Depression and SSRI Treatment Outcomes

Major Depressive Disorder (MDD) is the leading psychiatric illness, and women are affected at a rate of 2:1. The Mayo Clinic PGRN-AMPS trial applied a metabolomics-informed-pharmacogenomic approach to yield novel mechanistic insights into MDD pathophysiology and Selective Serotonin Reuptake Inhibitor (SSRI) response. We hypothesized that this approach could establish sex-specific markers (in women) of MDD pathophysiology, SSRI response, or both. We leveraged metabolomics data from an independent cohort of the Combining Medications to Enance Depression Outcomes (CO-MED) study to replicate our PGRN-AMPS findings.

Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings

Heterogeneity in the clinical presentation of major depressive disorder and response to antidepressants limits clinicians’ ability to accurately predict a specific patient’s eventual response to therapy. Validated depressive symptom profiles may be an important tool for identifying poor outcomes early in the course of treatment. To derive these symptom profiles, we first examined data from 947 depressed subjects treated with selective serotonin reuptake inhibitors (SSRIs) to delineate the heterogeneity of antidepressant response using probabilistic graphical models (PGMs). We then used unsupervised machine learning to identify specific depressive symptoms and thresholds of improvement that were predictive of antidepressant response by 4 weeks for a patient to achieve remission, response, or nonresponse by 8 weeks. Four depressive symptoms (depressed mood, guilt feelings and delusion, work and activities and psychic anxiety) and specific thresholds of change in each at 4 weeks predicted eventual outcome at 8 weeks to SSRI therapy with an average accuracy of 77% (p = 5.5E-08). The same four symptoms and prognostic thresholds derived from patients treated with SSRIs correctly predicted outcomes in 72% (p = 1.25E-05) of 1996 patients treated with other antidepressants in both inpatient and outpatient settings in independent publicly-available datasets. These predictive accuracies were higher than the accuracy of 53% for predicting SSRI response achieved using approaches that (i) incorporated only baseline clinical and sociodemographic factors, or (ii) used 4-week nonresponse status to predict likely outcomes at 8 weeks. The present findings suggest that PGMs providing interpretable predictions have the potential to enhance clinical treatment of depression and reduce the time burden associated with trials of ineffective antidepressants. Prospective trials examining this approach are forthcoming.

ERICH3: vesicular association and antidepressant treatment response

Selective serotonin reuptake inhibitors (SSRIs) are standard of care for major depressive disorder (MDD) pharmacotherapy, but only approximately half of these patients remit on SSRI therapy. Our previous genome-wide association study identified a single-nucleotide polymorphism (SNP) signal across the glutamate-rich 3 (ERICH3) gene that was nearly genome-wide significantly associated with plasma serotonin (5-HT) concentrations, which were themselves associated with SSRI response for MDD patients enrolled in the Mayo Clinic PGRN-AMPS SSRI trial. In this study, we performed a meta-analysis which demonstrated that those SNPs were significantly associated with SSRI treatment outcomes in four independent MDD trials. However, the function of ERICH3 and molecular mechanism(s) by which it might be associated with plasma 5-HT concentrations and SSRI clinical response remained unclear. Therefore, we characterized the human ERICH3 gene functionally and identified ERICH3 mRNA transcripts and protein isoforms that are highly expressed in central nervous system cells. Coimmunoprecipitation identified a series of ERICH3 interacting proteins including clathrin heavy chain which are known to play a role in vesicular function. Immunofluorescence showed ERICH3 colocalization with 5-HT in vesicle-like structures, and ERICH3 knock-out dramatically decreased 5-HT staining in SK-N-SH cells as well as 5-HT concentrations in the culture media and cell lysates without changing the expression of 5-HT synthesizing or metabolizing enzymes. Finally, immunofluorescence also showed ERICH3 colocalization with dopamine in human iPSC-derived neurons. These results suggest that ERICH3 may play a significant role in vesicular function in serotonergic and other neuronal cell types, which might help explain its association with antidepressant treatment response.

AP-1 controls the p11-dependent antidepressant response

Selective serotonin reuptake inhibitors (SSRIs) are the most widely prescribed drugs for mood disorders. While the mechanism of SSRI action is still unknown, SSRIs are thought to exert therapeutic effects by elevating extracellular serotonin levels in the brain, and remodel the structural and functional alterations dysregulated during depression. To determine their precise mode of action, we tested whether such neuroadaptive processes are modulated by regulation of specific gene expression programs. Here we identify a transcriptional program regulated by activator protein-1 (AP-1) complex, formed by c-Fos and c-Jun that is selectively activated prior to the onset of the chronic SSRI response. The AP-1 transcriptional program modulates the expression of key neuronal remodeling genes, including S100a10 (p11), linking neuronal plasticity to the antidepressant response. We find that AP-1 function is required for the antidepressant effect in vivo. Furthermore, we demonstrate how neurochemical pathways of BDNF and FGF2, through the MAPK, PI3K, and JNK cascades, regulate AP-1 function to mediate the beneficial effects of the antidepressant response. Here we put forth a sequential molecular network to track the antidepressant response and provide a new avenue that could be used to accelerate or potentiate antidepressant responses by triggering neuroplasticity.

Pronounced Inter-Individual Variation in Plasma Cortisol Response to Fluoxetine Hydrochloride in the Pig.

Animal welfare assessment requires measures for positive affective state. Pharmacological agents that manipulate affective state can be used to evaluate novel biomarkers for affective state assessment. However, to validate that an agent has modified brain function, a reliable indicator is required. Circulating cortisol has been used as a reporter for effective delivery of the antidepressant selective serotonin reuptake inhibitor (SSRI) fluoxetine hydrochloride to the brain in humans and sheep. Here, we tested cortisol as a reporter for effective delivery of fluoxetine hydrochloride to the pig brain. We hypothesized that following administration of SSRI, innervation of the serotonergic reward pathway would result in activation of the hypothalamic-pituitary-adrenal (HPA) axis, leading to increased circulating cortisol levels. Large White-Landrace gilts received either a single intravenous dose of 100 mg fluoxetine hydrochloride suspended in 10 mL saline (n = 4), or 10 mL saline alone (n = 4). Blood samples were collected every 15 min for one hour prior to, and six hours post-treatment. The interaction of treatment x time on mean plasma cortisol levels between 15-165 min post-treatment was significant (p = 0.048) with highest cortisol concentrations of SSRI treated pigs versus controls (+ 98%) at 135 min post-treatment. However, individual cortisol profiles after SSRI treatment revealed high inter-individual variation in response. We conclude that, while combined data imply that plasma cortisol may be a readout for SSRI efficacy, inter-individual variation in SSRI response may preclude application of this approach in the pig. Given the current limited sample size, further research to confirm these findings is needed.

Pharmacogenomics-Driven Prediction of Antidepressant Treatment Outcomes: A Machine-Learning Approach With Multi-trial Replication.

We set out to determine whether machine learning–based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 white outpatients with MDD treated with citalopram/escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN‐AMPS; n = 398), Sequenced Treatment Alternatives to Relieve Depression (STAR*D; n = 467), and International SSRI Pharmacogenomics Consortium (ISPC; n = 165) trials. A genomewide association study for PGRN‐AMPS plasma metabolites associated with SSRI response (serotonin) and baseline MDD severity (kynurenine) identified single nucleotide polymorphisms (SNPs) in DEFB1,ERICH3,AHR, and TSPAN5 that we tested as predictors. Supervised machine‐learning methods trained using SNPs and total baseline depression scores predicted remission and response at 8 weeks with area under the receiver operating curve (AUC) > 0.7 (P < 0.04) in PGRN‐AMPS patients, with comparable prediction accuracies > 69% (P ≤ 0.07) in STAR*D and ISPC. These results demonstrate that machine learning can achieve accurate and, importantly, replicable prediction of SSRI therapy response using total baseline depression severity combined with pharmacogenomic biomarkers.

Functional connectivity of the raphe nucleus as a predictor of the response to selective serotonin reuptake inhibitors in obsessive-compulsive disorder.

Selective serotonin reuptake inhibitors (SSRIs) are first-line pharmacological agents for treating obsessive-compulsive disorder (OCD). However, because nearly half of patients show insufficient SSRI responses, serotonergic dysfunction in heterogeneous OCD patients should be investigated for precision medicine. We aimed to determine whether functional connectivity (FC) of the raphe nucleus (RN), the major source of most serotonergic neurons, was altered in OCD patients and could predict the SSRI response. A total of 102 medication-free OCD patients and 101 matched healthy control (HC) subjects participated in resting-state functional magnetic resonance imaging. Among them, 54 OCD patients were treated with SSRIs for 16 weeks, resulting in 26 responders and 28 nonresponders. Seed-based whole brain FC with the RN as a seed region was compared between the OCD and HC groups, as well as between SSRI responders and nonresponders. FC cluster values showing significant group differences were used to investigate factors correlated with symptomatic severity before treatment and predictive of SSRI response. Compared to HCs, OCD patients exhibited significantly larger FC between the RN and temporal cortices including the middle temporal gyrus (MTG), paracingulate gyrus, amygdala, hippocampus, putamen, thalamus, and brain stem. Greater RN-left MTG FC was positively correlated with OC symptom severity at baseline. In addition, larger FC of the RN-left MTG was also found in SSRI nonresponders compared to responders, which was a significant predictor of SSRI response after 16 weeks. The FC of RN may reflect the neurobiological underpinning of OCD and could aid future precision medicine as a differential brain-based biomarker.

Examining raphe-amygdala structural connectivity as a biological predictor of SSRI response

BackgroundOur lab has previously found that structural integrity in tracts from the raphe nucleus (RN) to the amygdala, measured by fractional anisotropy (FA), predicts remission to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder (MDD). This could potentially serve as a biomarker for remission that can guide clinical decision-making. To enhance repeatability and reproducibility, we replicated our study in a larger, more representative multi-site sample. Methods64 direction DTI was collected in 144 medication-free patients with MDD from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) study. We performed probabilistic tractography between the RN and bilateral amygdala and hippocampus and calculated weighted FA in these tracts. Patients were treated with either sertraline or placebo, and their change in Hamilton Depression Rating Scale (HDRS) score reported. Pretreatment weighted FA was compared between remitters and nonremitters, and correlation between FA and percent change in HDRS score was assessed. Exploratory moderator and voxel analyses were also performed. ResultsContrary to our hypotheses, FA was greater in nonremitters than in remitters in RN-left and right amygdala tracts (p = 0.02 and 0.01, respectively). Pretreatment FA between the raphe and left amygdala correlated with greater, not reduced, HDRS (r = 0.18, p = 0.04). This finding was found to be greater in the placebo group. Moderator and voxel analyses yielded no significant findings. ConclusionsWe found greater FA in nonremitters between the RN and amygdala than in remitters, and a correlation between FA and symptom worsening, particularly with placebo. These findings may help reveal more about the nature of MDD, as well as guide research methods involving placebo response.

Increased ventromedial prefrontal cortex activity and connectivity predict poor sertraline treatment outcome in late-life depression.

Previous studies of imaging predictors on acute treatment response in late-life depression (LLD) demonstrated that poor response to selective serotonin reuptake inhibitors (SSRIs) is associated with pre-treatment low functional connectivity (FC) within executive control network and high FC within default-mode network including the ventromedial prefrontal cortex (vmPFC). However, there is less research in regional resting-state functional activity that explains FC changes related to SSRI response. Thirty-six older major depressive disorder (MDD) patients not currently on antidepressant treatment had a baseline, pre-treatment resting-state functional magnetic resonance imaging scan, followed by sertraline treatment for 12weeks. Depression severity was assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS). Subjects whose MADRS score decreased less than 50% from baseline or who discontinued sertraline for any reason were classified as nonresponders (n=21). Subjects whose 12-week MADRS score dropped greater than or equal to 50% from baseline were defined as responders (n=15). We conducted the amplitude of low-frequency fluctuation (ALFF) and region of interest (ROI)-to-ROI FC analyses independently. Significance threshold was set at P<0.05 with false discovery rate (FDR) correction for multiple comparisons. Relative to the responder group, the nonresponder group showed significantly less ALFF in the dorsomedial prefrontal cortex (dmPFC) and greater ALFF in the vmPFC/subgenual cingulate area. For ROI-to-ROI connectivity, there was significantly greater connectivity between the vmPFC and the cerebellar vermis in the nonresponder group. Our study highlighted the association of vmPFC resting-state activity and connectivity with SSRI response. Future studies are warranted for understanding the role of vmPFC-vermis connectivity in LLD.

Plasma serotonin levels are associated with antidepressant response to SSRIs

BackgroundLess than half of patients with major depressive disorder (MDD) respond to their first antidepressant trial. Our understanding of the underlying mechanisms of selective serotonin reuptake inhibitors (SSRIs) remains poor, and there is no reliable method of predicting treatment response. MethodsThirty-seven MDD subjects and 41 healthy controls, somatically healthy and medication-free for at least six weeks, were recruited, and plasma serotonin (5-HT) levels were assessed at baseline. Twenty-six of the MDD subjects were then treated in an open-label manner with clinically appropriate doses of sertraline for 8 weeks, after which plasma 5-HT levels were again assessed. Response to treatment was defined as an improvement of 50% or more on the Hamilton Depression Rating Scale. ResultsNon-responders to sertraline treatment had significantly lower pre-treatment 5-HT levels compared to both healthy controls and responders (F = 4.4, p = 0.004 and p = 0.036, respectively). There was a significant decrease in 5-HT levels over treatment in all MDD subjects (t = 6.2, p = 0.000003). The decrease was significantly more prominent in responders compared to non-responders (t = 2.1, p = 0.047). There was no significant difference in post-treatment 5-HT levels between responders and non-responders. LimitationsThe study had a modest sample size. 5-HT levels in plasma may not reflect 5-HT levels in the brain. ConclusionsThe results indicate that SSRI response may be facilitated by adequate baseline plasma 5-HT content and that successful SSRI treatment is associated with greater decreases in circulating 5-HT. Plasma 5-HT content may be a predictor of SSRI treatment outcome. Potential underlying mechanisms are discussed.

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.

SSRIs Appear Superior to SSNRIs for Pediatric Anxiety, Study Shows

Back to table of contents Previous article Next article Clinical and Research NewsFull AccessSSRIs Appear Superior to SSNRIs for Pediatric Anxiety, Study ShowsMark MoranMark MoranSearch for more papers by this authorPublished Online:5 Apr 2018https://doi.org/10.1176/appi.pn.2018.4a9AbstractThe serotonin system may mature earlier than the noradrenergic system, accounting for differences in how youth respond to selective serotonin reuptake inhibitors (SSRIs) and selective serotonin-norepinephrine reuptake inhibitors (SSNRIs).Selective serotonin reuptake inhibitors (SSRIs) appear to be superior to selective serotonin-norepinephrine reuptake inhibitors (SSNRIs) in the treatment of pediatric anxiety disorders, though both are associated with statistically significant improvement after two weeks, according to a meta-analysis posted February 7 in the Journal of the American Academy of Child and Adolescent Psychiatry. “These results are meaningful to clinicians as they choose which antidepressant class to use when treating anxious youth,” wrote Jeffrey Strawn, M.D., of the University of Cincinnati College of Medicine and colleagues. “Additionally, given the magnitude and trajectory of SSRI response, relative to SSNRI response observed herein, clinicians might preferentially use SSRIs as first-line psychopharmacologic interventions in pediatric patients with anxiety disorders.” Strawn and colleagues searched the literature for prospective, randomized, placebo-controlled trials (RCTs) that evaluated the efficacy of SSRIs or SSNRIs in the treatment of social, generalized, and/or separation anxiety disorder in children and adolescents. Overall, nine double-blind RCTs (1,805 patients) conducted between 1997 and 2014 were included in the analysis. Four SSRIs were evaluated: fluoxetine, fluvoxamine, paroxetine, and sertraline. Three SSNRIs were evaluated: atomoxetine, duloxetine, and venlafaxine. Five studies were federally funded, and four were funded by industry. All studies were conducted in outpatient settings. The primary outcome for these analyses was the change in Pediatric Anxiety Rating Scale (PARS) total score from baseline to endpoint at week 12.Patients taking both SSRIs and SSNRIs improved significantly by week two over those taking placebo and continued to have statistically significant improvement throughout the study period. However, treatment response among those taking SSRIs was statistically greater at week two than among those taking SSNRIs, and that difference remained statistically significant over the subsequent 10 weeks of treatment.Over time, response did not differ between high-dose SSRI treatment compared with low-dose treatment. However, statistically significant improvement occurred earlier (week 2) with high-dose treatment. At week 12, both high-dose and low-dose treatments were associated with significant improvement compared with baseline.Strawn and colleagues said the superiority of SSRIs may be because the pathophysiology of anxiety involves more serotonergic dysfunction relative to noradrenergic dysfunction. Additionally, the serotonin system matures earlier than the noradrenergic system, and this developmental lag in the noradrenergic system may underlie differences in the effectiveness of SNRI antidepressants that mechanistically target norepinephrine and SSRIs that target serotonin. “Our results suggest that antidepressant response in pediatric patients occurs early in the course of treatment and occurs with a greater magnitude and more rapid trajectory with SSRIs compared to SSNRIs,” Strawn and colleagues wrote. “These data raise the possibility that SSRIs should be first-line antidepressants in youth with anxiety disorders and extend prior observations in pediatric patients with anxiety that more serotonergically selective agents may be more effective.” ■“The Impact of Antidepressant Dose and Class on Treatment Response in Pediatric Anxiety Disorders: A Meta-Analysis” can be accessed here. ISSUES NewArchived

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.

MicroRNA-Mediated Regulation of ITGB3 and CHL1 Is Implicated in SSRI Action.

Background: Selective serotonin reuptake inhibitor (SSRI) antidepressant drugs are the first-line of treatment for major depressive disorder (MDD) but are effective in <70% of patients. Our earlier genome-wide studies indicated that two genes encoding for cell adhesion proteins, close homolog of L1 (CHL1) and integrin beta-3 (ITGB3), and microRNAs, miR-151a-3p and miR-221/222, are implicated in the variable sensitivity and response of human lymphoblastoid cell lines (LCL) from unrelated individuals to SSRI drugs.Methods: The microRNAs miR-221, miR-222, and miR-151-a-3p, along with their target gene binding sites, were explored in silico using miRBase, TargetScan, microRNAviewer, and the UCSC Genome Browser. Luciferase reporter assays were conducted for demonstrating the direct functional regulation of ITGB3 and CHL1 expression by miR-221/222 and miR-151a-3p, respectively. A human LCL exhibiting low sensitivity to paroxetine was utilized for studying the phenotypic effect of CHL1 regulation by miR-151a-3p on SSRI response.Results: By showing direct regulation of CHL1 and ITGB3 by miR-151a-3p and miR-221/222, respectively, we link these microRNAs and genes with cellular SSRI sensitivity phenotypes. We report that miR-151a-3p increases cell sensitivity to paroxetine via down-regulating CHL1 expression.Conclusions: miR-151a-3p, miR-221/222 and their (here confirmed) respective target-genes, CHL1 and ITGB3, are implicated in SSRI responsiveness, and possibly in the clinical response to antidepressant drugs.