Abstract The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and ...error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5–10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R2 ) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug.
Abstract The primary objective of this review is to give an overview of the main findings of the European multicenter project “Patterns of Treatment Resistance and Switching Strategies in Affective ...Disorder”, performed by the Group for the Study of Resistant Depression (GSRD). The aim was to study methodological issues, operational criteria, clinical characteristics, and genetic variables associated with treatment resistant depression (TRD), that is failure to reach response after at least two consecutive adequate antidepressant trials. The primary findings of clinical variables associated with treatment resistance include comorbid anxiety disorders as well as non-response to the first antidepressant received lifetime. Although there is a plethora of hints in textbooks that switching the mechanism of action should be obtained in case of nonresponse to one medication, the results of the GSRD challenge this notion by demonstrating in retrospective and prospective evaluations that staying on the same antidepressant mechanism of action for a longer time is more beneficial than switching, however, when switching is an option there is no benefit to switch across class. The GSRD candidate gene studies found that metabolism status according to cytochrome P450 gene polymorphisms may not be helpful to predict response and remission rates to antidepressants. Significant associations with MDD and antidepressant treatment response were found for COMT SNPs. Investigating the impact of COMT on suicidal behaviour, we found a significant association with suicide risk in MDD patients not responding to antidepressant treatment, but not in responders. Further significant associations with treatment response phenotypes were found with BDNF , 5HTR2A and CREB1 . Additional investigated candidate genes were DTNBP1 , 5HT1A , PTGS2 , GRIK4 and GNB3.
Mental health disorders are ambiguously defined and diagnosed. The established diagnosis technique, which is based on structured interviews, questionnaires and data subjectively reported by the ...patients themselves, leaves the mental health field behind other medical areas. We support these statements with examples from major depressive disorder (MDD). The National Institute of Mental Health (NIMH) launched the Research Domain Criteria (RDoC) project in 2009 as a new framework to investigate psychiatric pathologies from a multidisciplinary point of view. This is a good step in the right direction. Contemporary psychiatry considers mental illnesses as diseases that manifest in the mind and arise from the brain, expressed as a behavioral condition; therefore, we claim that these syndromes should be characterized primarily using behavioral characteristics. We suggest the use of smartphones and wearable devices to passively collect quantified behavioral data from patients by utilizing digital biomarkers of mental disorder symptoms. Various digital biomarkers of MDD symptoms have already been detected, and apps for collecting this longitudinal behavioral data have already been developed. This quantified data can be used to determine a patient’s diagnosis and personalized treatment, and thereby minimize the diagnosis rate of comorbidities. As there is a wide spectrum of human behavior, such a fluidic and personalized approach is essential.
Indirect evidence suggests that common genetic variation contributes to individual differences in antidepressant efficacy among individuals with major depressive disorder, but previous studies may ...have been underpowered to detect these effects.
A meta-analysis was performed on data from three genome-wide pharmacogenetic studies (the Genome-Based Therapeutic Drugs for Depression GENDEP project, the Munich Antidepressant Response Signature MARS project, and the Sequenced Treatment Alternatives to Relieve Depression STAR*D study), which included 2,256 individuals of Northern European descent with major depressive disorder, and antidepressant treatment outcomes were prospectively collected. After imputation, 1.2 million single-nucleotide polymorphisms were tested, capturing common variation for association with symptomatic improvement and remission after up to 12 weeks of antidepressant treatment.
No individual association met a genome-wide threshold for statistical significance in the primary analyses. A polygenic score derived from a meta-analysis of GENDEP and MARS participants accounted for up to approximately 1.2% of the variance in outcomes in STAR*D, suggesting a weakly concordant signal distributed over many polymorphisms. An analysis restricted to 1,354 individuals treated with citalopram (STAR*D) or escitalopram (GENDEP) identified an intergenic region on chromosome 5 associated with early improvement after 2 weeks of treatment.
Despite increased statistical power accorded by meta-analysis, the authors identified no reliable predictors of antidepressant treatment outcome, although they did identify modest, direct evidence that common genetic variation contributes to individual differences in antidepressant response.
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.
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.
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.
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.
Treatment-resistant depression (TRD) is an important clinical challenge and may present differently between age groups.
A total of 893 depressed patients recruited within the framework of the ...European research consortium "Group for the Studies of Resistant Depression" were assessed by generalized linear models regarding age effects (both as numerical and factorial predictors) on treatment outcome, number of lifetime depressive episodes, hospitalization time, and duration of the current episode. Effects of age as numerical predictor on the severity of common depressive symptoms, measured with Montgomery-Åsberg Depression Rating Scale (MADRS) for two-time points, were assessed by linear mixed models, respectively, for patients showing TRD and treatment response. A corrected
threshold of 0.001 was applied.
Overall symptom load reflected by MADRS (
< 0.0001) and lifetime hospitalization time (
< 0.0001) increased with age in TRD patients but not treatment responders. In TRD, higher age was predicting symptom severity of inner tension, reduced appetite, concentrations difficulties, and lassitude (all
≤ 0.001). Regarding clinical significance, older TRD patients were more likely to report severe symptoms (item score > 4) for these items both before and after treatment (all
≤ 0.001).
In this naturalistic sample of severely ill depressed patients, antidepressant treatment protocols were equally effective in addressing TRD in old age. However, specific symptoms such as sadness, appetite, and concentration showed an age-dependent presentation, impacting residual symptoms in severely affected TRD patients and calling for a precision approach by a better integration of age profiles in treatment recommendations.
The major aim of this multicenter study of the European Group for the Study of Resistant Depression (GSRD) was to elucidate associations between major depressive disorder (MDD) and comorbid diabetes.
...Demographic and clinical information of 1410 patients with a primary MDD diagnosis according to DSM-IV were retrieved cross-sectionally between 2012 and 2016. By applying descriptive statistics, analyses of covariance (ANCOVA) and binary logistic regression analyses, a comparison between patient characteristics with and without comorbid diabetes was performed.
The point prevalence rate for comorbid diabetes across MDD patients was 6%. Individuals with MDD + comorbid diabetes were significantly older, heavier, more likely to be inpatient and diagnosed with additional comorbid chronic somatic diseases. In addition, current suicide risk was significantly increased and melancholic features were more likely pronounced. In general, patients in the MDD + diabetes group received a combination therapy with at least one additional antidepressant rather than various other augmentation strategies.
Our analyses depict a lower prevalence rate of diabetes in MDD patients than previous studies. However, in light of the prevalence of diabetes in the geographical area of the study, we found an increased risk for individuals with depression compared to the general population. Current suicide risk is markedly elevated and has to be thoroughly assessed in every patient with comorbid diabetes. Depression severity and treatment response remained unaffected by concurrent diabetes in MDD.
•Diabetes in depressed patients is more prevalent than in the general population.•Suicide risk in depressed patients with diabetes demands appropriate screening.•Diabetes in depressed patients has no impact on illness severity/treatment response.
Depressive symptoms and episodes dominate the course of bipolar disorder. However, the therapeutic armamentarium for bipolar depression is limited. Recent evidence points to the efficacy of second ...generation antipsychotics (SGAs) for the treatment of bipolar depression. We conducted a systematic review and meta-analysis of the efficacy and safety of SGAs (randomized, double-blind, placebo-controlled trials; used in monotherapy) in the treatment of adult patients with bipolar depression. Publication bias was corrected for by performing similar searches using the clinical trials register of the respective pharmaceutical companies, the Cochrane Database and ClinicalTrials.gov. Seven published papers were identified on the use of aripiprazole, olanzapine and quetiapine. Internal validity of the trials was fairly good, external validity only moderate. Different outcome measures of efficacy and safety were assessed. When the individual trials were looked at, quetiapine and to a lesser extent olanzapine demonstrated significant improvement in MADRS (Montgomery–Åsberg Depression Rating Scale) total scores. This was not demonstrated for aripiprazole. Efficacy was hampered by adverse events, such as weight gain, akathisia and somnolence/sedation. Both clinical heterogeneity of the included trials and statistical heterogeneity of the meta-analytic data were considerable. The number of quetiapine trials was disproportionate to the number of trials of aripiprazole and olanzapine. Further research is needed to assess differential efficacy of the different SGAs and their use in clinical practice.
Based on our preclinical data showing a potential accelerating effect of acetylsalicylic acid (ASA) in combination with fluoxetine in an animal model of depression, we examined the effect of ASA ...augmentation therapy on selective reuptake inhibitors (SSRI) in major depressed non-responder patients. Twenty-four non-responder patients having received at least 4 weeks of an adequate SSRI treatment were included in a pilot open-label study. Participants were treated openly during 4 weeks with 160 mg/day ASA in addition to their current antidepressant treatment. The combination SSRI-ASA was associated with a response rate of 52.4%. Remission was achieved in 43% of the total sample and 82% of the responder sample. In the responder group, a significant improvement was observed within week 1 (mean Hamilton Depression Rating Scale-21 items at day 0=29.3+/-4.5, at day 7=14.0+/-4.1; P<0.0001) and remained sustained until day 28. Despite limitations due to the open nature of this study, our preliminary results confirm our preclinical findings and are in favour of an accelerating effect of ASA in combination with SSRIs in the treatment of major depression. Potential physiological and biochemical mechanisms may involve an anti-inflammatory and/or neurotrophic effect.
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