Dataset Information

A cognitive-emotional biomarker for predicting remission with antidepressant medications: a report from the iSPOT-D trial.

ABSTRACT: Depression involves impairments in a range of cognitive and emotional capacities. It is unknown whether these functions can inform medication choice when considered as a composite predictive biomarker. We tested whether behavioral tests, grounded in the neurobiology of cognitive and emotional functions, predict outcome with common antidepressants. Medication-free outpatients with nonpsychotic major depressive disorder (N=1008; 665 completers) were assessed before treatment using 13 computerized tests of psychomotor, executive, memory-attention, processing speed, inhibitory, and emotional functions. Matched healthy controls (N=336) provided a normative reference sample for test performance. Depressed participants were then randomized to escitalopram, sertraline, or venlafaxine-extended release, and were assessed using the 16-item Quick Inventory of Depressive Symptomatology (QIDS-SR16) and the 17-item Hamilton Rating Scale for Depression. Given the heterogeneity of depression, analyses were furthermore stratified by pretreatment performance. We then used pattern classification with cross-validation to determine individual patient-level composite predictive biomarkers of antidepressant outcome based on test performance. A subgroup of depressed participants (approximately one-quarter of patients) were found to be impaired across most cognitive tests relative to the healthy norm, from which they could be discriminated with 91% accuracy. These patients with generally impaired cognitive task performance had poorer treatment outcomes. For this impaired subgroup, task performance furthermore predicted remission on the QIDS-SR16 at 72% accuracy specifically following treatment with escitalopram but not the other medications. Therefore, tests of cognitive and emotional functions can form a clinically meaningful composite biomarker that may help drive general treatment outcome prediction for optimal treatment selection in depression, particularly for escitalopram.

SUBMITTER: Etkin A

PROVIDER: S-EPMC4397406 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A cognitive-emotional biomarker for predicting remission with antidepressant medications: a report from the iSPOT-D trial.

Etkin Amit A Patenaude Brian B Song Yun Ju C YJ Usherwood Timothy T Rekshan William W Schatzberg Alan F AF Rush A John AJ Williams Leanne M LM

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 20141230 6

Depression involves impairments in a range of cognitive and emotional capacities. It is unknown whether these functions can inform medication choice when considered as a composite predictive biomarker. We tested whether behavioral tests, grounded in the neurobiology of cognitive and emotional functions, predict outcome with common antidepressants. Medication-free outpatients with nonpsychotic major depressive disorder (N=1008; 665 completers) were assessed before treatment using 13 computerized ...[more]

PMID: 25547711

Similar Datasets

Project description:Although the cost of poor treatment outcomes of depression is staggering, we do not yet have clinically useful methods for selecting the most effective antidepressant for each depressed person. Emotional brain activation is altered in major depressive disorder (MDD) and implicated in treatment response. Identifying which aspects of emotional brain activation are predictive of general and specific responses to antidepressants may help clinicians and patients when making treatment decisions. We examined whether amygdala activation probed by emotion stimuli is a general or differential predictor of response to three commonly prescribed antidepressants, using functional magnetic resonance imaging (fMRI). A test-retest design was used to assess patients with MDD in an academic setting as part of the International Study to Predict Optimized Treatment in Depression. A total of 80 MDD outpatients were scanned prior to treatment and 8 weeks after randomization to the selective serotonin reuptake inhibitors escitalopram and sertraline and the serotonin-norepinephrine reuptake inhibitor, venlafaxine-extended release (XR). A total of 34 matched controls were scanned at the same timepoints. We quantified the blood oxygen level-dependent signal of the amygdala during subliminal and supraliminal viewing of facial expressions of emotion. Response to treatment was defined by ⩾50% symptom improvement on the 17-item Hamilton Depression Rating Scale. Pre-treatment amygdala hypo-reactivity to subliminal happy and threat was a general predictor of treatment response, regardless of medication type (Cohen's d effect size 0.63 to 0.77; classification accuracy, 75%). Responders showed hypo-reactivity compared to controls at baseline, and an increase toward 'normalization' post-treatment. Pre-treatment amygdala reactivity to subliminal sadness was a differential moderator of non-response to venlafaxine-XR (Cohen's d effect size 1.5; classification accuracy, 81%). Non-responders to venlafaxine-XR showed pre-treatment hyper-reactivity, which progressed to hypo-reactivity rather than normalization post-treatment, and hypo-reactivity post-treatment was abnormal compared to controls. Impaired amygdala activation has not previously been highlighted in the general vs differential prediction of antidepressant outcomes. Amygdala hypo-reactivity to emotions signaling reward and threat predicts the general capacity to respond to antidepressants. Amygdala hyper-reactivity to sad emotion is involved in a specific non-response to a serotonin-norepinephrine reuptake inhibitor. The findings suggest amygdala probes may help inform the personal selection of antidepressant treatments.

Project description:Single-nucleotide polymorphisms (SNPs) in the FKBP5, GRIK4, and HTR2A genes have been shown to be associated with response to citalopram treatment in the STAR(*)D sample, but only associations with FKBP5 have so far been tested in the Munich Antidepressant Response Signature (MARS) project. Response and remission of depressive symptoms after 5 weeks of antidepressant treatment were tested against 82 GRIK4 and 37 HTR2A SNPs. Association analysis was conducted in about 300 depressed patients from the MARS project, 10% of whom had bipolar disorder. The most predictive SNPs from these two genes and rs1360780 in FKBP5 were then genotyped in a total of 387 German depressed in-patients to analyze potential additive and interactive effects of these variants. We could not replicate previous findings of the Sequenced Treatment Alternatives to Relieve Depression (STAR(*)D) study in our sample. Although not statistically significant, the effect for the best GRIK4 SNP of STAR(*)D (rs1954787, p=0.076, p(corrected)=0.98) seemed to be in the same direction. On the other hand, the nominally significant association with the top HTR2A SNPs of STAR(*)D (rs7997012, allelic, p=0.043, p(corrected)=0.62) was with the opposite risk allele. The GRIK4 SNP (rs12800734, genotypic, p=0.0019, p(corrected)=0.12) and the HTR2A SNP (rs17288723, genotypic, p=0.0011, p(corrected)=0.02), which showed the strongest association with remission in our sample, had not been reported previously. Associations across all genetic markers within the GRIK4 (genotypic, p=0.022) or HTR2A (genotypic, p=0.012) locus using the Fisher's product method (FPM) were also significant. In all 374 patients, the best predictive model included a main effect for GRIK4 rs12800734 and two significant interactions between GRIK4 rs12800734 and FKBP5 rs1360780, and GRIK4 rs12800734 and HTR2A rs17288723. This three SNP model explained 13.1% of the variance for remission after 5 weeks (p=0.00051 for the model). Analyzing a sub-sample of 194 patients, plasma ACTH (p=0.002) and cortisol (p=0.021) responses of rs12800734 GG (GRIK4) carriers, who also showed favorable treatment response, were significantly lower in the second combined dexamethasone (dex)/corticotrophin-releasing hormone (CRH) test before discharge compared with the other two genotype groups. Despite large differences in ethnicity and design compared with the STAR(*)D study, our results from the MARS study further support both independent and interactive involvement of GRIK4, HTR2A and FKBP5 in antidepressant treatment response.

Project description:Late-life depression frequently co-occurs with cognitive impairment. To inform clinical management of these conditions, we examined the hypotheses that, relative to cognitively normal elders meeting DSM-IV criteria for major depressive disorder, those with cognitive impairment would require greater intensity of pharmacotherapy to reach criteria for antidepressant response and would take longer to respond.Using data from the MTLD-3 study, we conducted a series of secondary analyses examining the implications of cognitive impairment for short-term, open-trial pharmacotherapy of late-life depression (major depressive disorder in individuals 65 years and older). The treatment algorithm consisted of 3 steps: initial treatment with a selective serotonin reuptake inhibitor (SSRI), a switch to a serotonin-norepinephrine reuptake inhibitor (SNRI) if the patient did not respond, and addition of an atypical antipsychotic if the patient did not respond to the SNRI. The first subject entered the protocol in April 2004, and the last subject exited in September 2009. We examined data for participants who completed the acute phase of MTLD-3 as responders and received a cognitive diagnosis (N = 153) based on National Alzheimer's Coordinating Center (NACC) Uniform Data Set criteria. We divided participants into 3 groups on the basis of NACC cognitive diagnosis: no cognitive disorder (n = 74), mild cognitive impairment (n = 60), and dementia (n = 19). For each group, we calculated the proportion of participants requiring first- (SSRI), second- (SNRI), or third-step (add-on atypical antipsychotic) treatment to meet criteria for response (17-Item Hamilton Depression Rating Scale score ? 10 for 3 consecutive weeks). We compared time to response across groups and correlates of nonresponse.The 3 groups did not differ in intensity of pharmacotherapy (P = .68) or time to response (P = .84). Nonresponse was more strongly correlated with longer major depressive episode duration (P = .0015), presence of recurrent depression (P = .002), and younger current age (P = .047), rather than cognitive status (P = .61).Cognitive status does not appear to impact short-term pharmacotherapy response variability in individuals whose depression responds to treatment with open-trial antidepressants delivered in a supportive, university-based medication clinic.

Dataset Information

A cognitive-emotional biomarker for predicting remission with antidepressant medications: a report from the iSPOT-D trial.

Publications

A cognitive-emotional biomarker for predicting remission with antidepressant medications: a report from the iSPOT-D trial.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets