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The International Society for Bipolar Disorders (ISBD) Task Force Report on Antidepressant Use in Bipolar Disorders

Isabella Pacchiarotti et al.Sep 13, 2013

Philosophy

Clinical Psychology

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Clinical Factors Associated With Treatment Resistance in Major Depressive Disorder

Daniel Souery et al.Jul 15, 2007

Article Abstract Objectives: Very few studies have investigated clinical features associated with treatment-resistant depression (TRD) defined as failure of at least 2 consecutive antidepressant trials. The primary objective of this multicenter study was to identify specific clinical and demographic factors associated with TRD in a large sample of patients with major depressive episodes that failed to reach response or remission after at least 2 consecutive adequate antidepressant treatments. Method: A total of 702 patients with DSM-IV major depressive disorder, recruited from January 2000 to February 2004, were included in the analysis. Among them, 346 patients were considered as nonresistant. The remaining 356 patients were considered as resistant, with a 17-item Hamilton Rating Scale for Depression score remaining greater than or equal to 17 after 2 consecutive adequate antidepressant trials. Cox regression models were used to examine the association between individual clinical variables and TRD. Results: Among the clinical features investigated, 11 variables were found to be associated with TRD. We found anxiety comorbidity (p < .001, odds ratio = 2.6), comorbid panic disorder (p 1 (p = .003, OR = 1.6), recurrent episodes (p = .009, OR = 1.5), early age at onset (p = .009, OR = 2.0), and nonresponse to the first antidepressant received lifetime (p = .019, OR = 1.6) to be the factors associated with TRD. Conclusions: Our findings provide a set of 11 relevant clinical variables associated with treatment resistance in major depressive disorder that can be explored at the clinical level. The statistical model used in this analysis allowed for a hierarchy of these variables (based on the OR) showing that comorbid anxiety disorder is the most powerful clinical factor associated with TRD.

Pharmacology

Internal Medicine

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An Inflammatory Biomarker as a Differential Predictor of Outcome of Depression Treatment With Escitalopram and Nortriptyline

Rudolf Uher et al.Jul 14, 2014

Objective: Major depressive disorder has been linked with inflammatory processes, but it is unclear whether individual differences in levels of inflammatory biomarkers could help match patients to treatments that are most likely to be beneficial. The authors tested the hypothesis that C-reactive protein (CRP), a commonly available marker of systemic inflammation, predicts differential response to escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor). Method: The hypothesis was tested in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study, a multicenter open-label randomized clinical trial. CRP was measured with a high-sensitivity method in serum samples from 241 adult men and women with major depressive disorder randomly allocated to 12-week treatment with escitalopram (N=115) or nortriptyline (N=126). The primary outcome measure was the score on the Montgomery-Åsberg Depression Rating Scale (MADRS), administered weekly. Results: CRP level at baseline differentially predicted treatment outcome with the two antidepressants (CRP-drug interaction: β=3.27, 95% CI=1.65, 4.89). For patients with low levels of CRP (<1 mg/L), improvement on the MADRS score was 3 points higher with escitalopram than with nortriptyline. For patients with higher CRP levels, improvement on the MADRS score was 3 points higher with nortriptyline than with escitalopram. CRP and its interaction with medication explained more than 10% of individual-level variance in treatment outcome. Conclusions: An easily accessible peripheral blood biomarker may contribute to improvement in outcomes of major depressive disorder by personalizing treatment choice.

Biochemistry

Internal Medicine

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Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms

Rudolf Uher et al.Sep 20, 2011

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Background Symptom dimensions have not yet been comprehensively tested as predictors of the substantial heterogeneity in outcomes of antidepressant treatment in major depressive disorder. Method We tested nine symptom dimensions derived from a previously published factor analysis of depression rating scales as predictors of outcome in 811 adults with moderate to severe depression treated with flexibly dosed escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP). The effects of symptom dimensions were tested in mixed-effect regression models that controlled for overall initial depression severity, age, sex and recruitment centre. Significant results were tested for replicability in 3637 adult out-patients with non-psychotic major depression treated with citalopram in level I of Sequenced Treatment Alternatives to Relieve Depression (STAR*D). Results The interest-activity symptom dimension (reflecting low interest, reduced activity, indecisiveness and lack of enjoyment) at baseline strongly predicted poor treatment outcome in GENDEP, irrespective of overall depression severity, antidepressant type and outcome measure used. The prediction of poor treatment outcome by the interest-activity dimension was robustly replicated in STAR*D, independent of a comprehensive list of baseline covariates. Conclusions Loss of interest, diminished activity and inability to make decisions predict poor outcome of antidepressant treatment even after adjustment for overall depression severity and other clinical covariates. The prominence of such symptoms may require additional treatment strategies and should be accounted for in future investigations of antidepressant response.

Pharmacology

Internal Medicine

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Genome-Wide Pharmacogenetics of Antidepressant Response in the GENDEP Project

Rudolf Uher et al.Apr 2, 2010

Objective The purpose of this study was to identify genetic variants underlying the considerable individual differences in response to antidepressant treatment. The authors performed a genome-wide association analysis of improvement of depression severity with two antidepressant drugs. Method High-quality Illumina Human610-quad chip genotyping data were available for 706 unrelated participants of European ancestry treated for major depression with escitalopram (N=394) or nortriptyline (N=312) over a 12-week period in the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, a partially randomized open-label pharmacogenetic trial. Results Single nucleotide polymorphisms in two intergenic regions containing copy number variants on chromosomes 1 and 10 were associated with the outcome of treatment with escitalopram or nortriptyline at suggestive levels of significance and with a high posterior likelihood of true association. Drug-specific analyses revealed a genome-wide significant association between marker rs2500535 in the uronyl 2-sulphotransferase gene and response to nortriptyline. Response to escitalopram was best predicted by a marker in the interleukin-11 (IL11) gene. A set of 72 a priori-selected candidate genes did not show pharmacogenetic associations above a chance level, but an association with response to escitalopram was detected in the interleukin-6 gene, which is a close homologue of IL11. Conclusions While limited statistical power means that a number of true associations may have been missed, these results suggest that efficacy of antidepressants may be predicted by genetic markers other than traditional candidates. Genome-wide studies, if properly replicated, may thus be important steps in the elucidation of the genetic basis of pharmacological response.

Genetics

Pharmacology

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Combining psychopharmacotherapy and psychotherapy is not associated with better treatment outcome in major depressive disorder - evidence from the European Group for the Study of Resistant Depression

Lucie Bartova et al.Sep 1, 2021

Despite plenty of effective antidepressant (AD) treatments, the outcome of major depressive disorder (MDD) is often unsatisfactory, probably due to improvable exploitation of available therapies. This European, cross-sectional, naturalistic multicenter study investigated the frequency of additional psychotherapy in terms of a manual-driven psychotherapy (MDP) in 1410 adult in- and outpatients with MDD, who were primarily treated with AD psychopharmacotherapy. Socio-demographic and clinical patterns were compared between patients receiving both treatments and those lacking concomitant MDP. In a total of 1279 MDD patients (90.7%) with known status of additional MDP, those undergoing a psychopharmacotherapy-MDP combination (31.2%) were younger, higher educated, more often employed and less severely ill with lower odds for suicidality as compared to patients receiving exclusively psychopharmacotherapy (68.8%). They experienced an earlier mean age of MDD onset, melancholic features, comorbid asthma and migraine and received lower daily doses of their first-line ADs. While agomelatine was more often established in these patients, MDD patients without MDP received selective serotonin reuptake inhibitors more frequently. These two patient groups did not differ in terms of response, non-response and treatment resistant depression (TRD). Accordingly, the employment of additional MDP could not be related to better treatment outcomes in MDD. The fact that MDP was applied in a minority of patients with rather beneficial socio-demographic and clinical characteristics might reflect inferior accessibility of these psychotherapeutic techniques for socially and economically disadvantaged populations.

Pharmacology

Clinical Psychology

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Assessing 42 inflammatory markers in 321 control subjects and 887 major depressive disorder cases: BMI and other confounders and overall predictive ability for current depression

Timothy Powell et al.May 21, 2018

Inflammatory markers such as cytokines represent potential biomarkers for major depressive disorder (MDD). Many, generally small studies have examined the role of single markers and found significant associations. We assessed 42 inflammatory markers, namely cytokines, in the blood of 321 control subjects and 887 MDD cases. We tested whether individual inflammatory marker levels were significantly affected by MDD case/control status, current episode, or current depression severity, co-varying for age, sex, body mass index (BMI), smoking, current antidepressant use, ethnicity, assay batch and study effects. We further used machine learning algorithms to investigate if we could use our data to blindly discriminate MDD patients, or those in a current episode. We found broad and powerful influences of confounding factors on log-protein levels. Notably, IL-6 levels were very strongly influenced by BMI (p = 1.37 x 10-43, variance explained = 18%), while Interleukin-16 was the most significant predictor of current depressive episode (p = 0.003, variance explained = 0.9%, q < 0.1). No single inflammatory marker predicted MDD case/control status when a subject was not in a depressed episode, nor did any predict depression severity. Machine learning results revealed that using inflammatory marker data with clinical confounder information significantly increased precision for differentiating MDD patients who were in an episode. To conclude, a wide panel of inflammatory markers alongside clinical information may aid in predicting the onset of symptoms, but no single inflammatory protein is likely to represent a clinically useful biomarker for MDD diagnosis or prognosis. We note that the potential influence of physical health related and population stratification related confounders on inflammatory biomarker studies in psychiatry is considerable.

Biochemistry

Oncology

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Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: meta-analysis of data from genome-wide association studies

Chiara Fabbri et al.Feb 6, 2018

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects. CYP2C19 phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was percentage symptom improvement and remission. Side effect data were available at weeks 2-4, 6 and 9 in three of the investigated samples. A fixed-effects meta-analysis was performed using EM as the reference group. Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD=0.43, CI=0.19-0.66) and higher remission rates (OR=1.55, CI=1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR=1.26, CI=1.08-1.47), neurological (OR=1.28, CI=1.07-1.53) and sexual side effects (OR=1.52, CI=1.23-1.87; week 6 values similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups. CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs are relatively rare among Caucasians (~2%).

Genetics

Pharmacology

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Cross-validation of technologies for genotyping CYP2D6 and CYP2C19

Beatriz Henriques et al.Dec 26, 2019

Background: CYP2D6 and CYP2C19 are cytochrome P450 enzymes involved in the metabolism of many medications from multiple therapeutic classes. The genes encoding them, CYP2D6 and CYP2C19, have multiple functional variants that have been associated with different levels of enzyme activity. There is evidence that methodology for identifying such variants (genotyping) effectively and efficiently could lead to substantial health care costs savings. There are various genotyping technologies available; we cross-validated several against each other. Methods: Ninety-six samples with a variety of CYP2D6 and CYP2C19 genotypes according to prior AmpliChip CYP450 and TaqMan CYP2C19*17 data were selected from the Genome-based therapeutic drugs for depression (GENDEP) study. Genotyping was performed with TaqMan copy number variant (CNV) analysis using probes specific for three different regions (CYP2D6 only), the next generation sequencing-based Ion S5 AmpliSeq Pharmacogenomics Panel, PharmacoScan, and long-range polymerase chain reaction (XL-PCR) followed by TaqMan single nucleotide variant (SNV) analysis or the Agena MassARRAY. Variant to star allele translation was automated. Results: The inter-platform concordance for CYP2C19 was high (94-98%). For CYP2D6, the IonS5-PharmacoScan concordance was 94% for a range of variants tested apart from those with at least one extra copy of a CYP2D6 gene (occurring at a frequency of 3.8%, 33/853), or a pseudogene-gene conversion (2%, 18/853). Conclusions: Inter-platform concordance for CYP2C19 was high, and, moreover, the Ion S5 and PharmacoScan data were 100% concordant with that from a TaqMan CYP2C19*2 assay. The level of concordance was also good for CYP2D6, apart from those with at least one extra copy of a CYP2D6 gene or a pseudogene-gene conversion. We have also demonstrated feasibility of using a NGS platform for genotyping CYP2D6 and CYP2C19, with automated data interpretation methodology. CYP2D6 and CYP2C19 genotyping may thereby become much more readily accessible, with potential substantial savings in health care costs and public benefit.

Genetics

Immunology

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New insights on the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation

Chiara Fabbri et al.Feb 20, 2017

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at SNP, gene and pathway level. Coverage of genetic variants was increased compared to previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) served for replication. 7,062,950 SNPs were analysed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (p=1.80e-08, ITGA9 (integrin alpha 9)) and rs76191705 (p=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At gene level, no consistent effect was found. At pathway level, the Gene Ontology terms GO:0005694 (chromosome) and GO:0044427 (chromosomal part) were associated with improvement (corrected p=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (p=0.047), while rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, no convincing replication was achieved. Further studies may help in clarifying their role.

Genetics

Molecular Biology

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Genetics

Molecular Biology

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