Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years

Are There Biological Correlates of Response to Yoga-Based Interventions in Depression? A Critical Scoping Review

Depression is the most common mental disorder worldwide. Both antidepressants and psychotherapy are effective in treating depression, but the response to these treatments is often incomplete. Yoga-based interventions (YBIs) have been advocated by some researchers as a promising form of alternative treatment for depression. Recent research has attempted to identify the biological mechanisms associated with the antidepressant actions of YBIs. In this scoping review, conducted according to the PRISMA-ScR guidelines, the PubMed and Scopus databases were searched to retrieve research on biomarkers of response to YBIs in patients with depression. These studies were also critically reviewed to evaluate their methodological quality and any sources of bias. Nineteen studies were included in the review. Based on these studies, there is preliminary evidence that YBIs may be associated with increased serum brain-derived neurotrophic factor (BDNF) and reduced serum cortisol and interleukin-6 (IL-6) in patients with depression. However, many of these changes were also observed in the control arms, and the overall quality of the research was low. At present, it cannot be concluded that there are reliable biomarkers of response to YBIs in depression, though there are some potential biological correlates. Further advances in this field will depend critically on improvements in study design, particularly the minimization of sources of bias and the selection of more specific and sensitive biomarkers based on existing evidence from other treatment modalities.

The association between gray matter volume in the hippocampal subfield and antidepressant efficacy mediated by abnormal dynamic functional connectivity

An abnormality of structures and functions in the hippocampus may have a key role in the pathophysiology of major depressive disorder (MDD). However, it is unclear whether structure factors of the hippocampus effectively impact antidepressant responses by hippocampal functional activity in MDD patients. We collected longitudinal data from 36 MDD patients before and after a 3-month course of antidepressant pharmacotherapy. Additionally, we obtained baseline data from 43 healthy controls matched for sex and age. Using resting-state functional magnetic resonance imaging (rs-fMRI), we estimated the dynamic functional connectivity (dFC) of the hippocampal subregions using a sliding-window method. The gray matter volume was calculated using voxel-based morphometry (VBM). The results indicated that patients with MDD exhibited significantly lower dFC of the left rostral hippocampus (rHipp.L) with the right precentral gyrus, left superior temporal gyrus and left postcentral gyrus compared to healthy controls at baseline. In MDD patients, the dFC of the rHipp.L with right precentral gyrus at baseline was correlated with both the rHipp.L volume and HAMD remission rate, and also mediated the effects of the rHipp.L volume on antidepressant performance. Our findings suggested that the interaction between hippocampal structure and functional activity might affect antidepressant performance, which provided a novel insight into the hippocampus-related neurobiological mechanism of MDD.

A genome-wide association study of antidepressant-induced mania

Antidepressant-induced mania (AIM) is a side effect of antidepressant treatment that is characterized by mania or hypomania after the start of medication. It is likely polygenic, but its genetic component remains largely unexplored. We aim to conduct the first genome-wide association study of AIM in 814 bipolar disorder patients of European ancestry. We report no significant findings from our single-marker or gene-based analyses. Our polygenic risk score analyses also did not yield significant results with bipolar disorder, antidepressant response, or lithium response. Our suggestive findings on the hypothalamic-pituitary-adrenal axis and the opioid system in AIM require independent replications.

Clinical pharmacological innovation in the treatment of depression

INTRODUCTION

Deficiencies in standard of care antidepressants are driving novel drug discovery. A new age of antidepressant medications has emerged with the introduction of rapid-acting antidepressants with efficacy in treatment-resistant patients.

AREAS COVERED

The newly approved medicines and those in clinical development for major depressive disorder (MDD) are documented in this scoping review of newly approved and emerging antidepressants. Compounds are evaluated for clinical efficacy, tolerability, and safety and compared to those of standard of care medicines.

EXPERT OPINION

A new age of antidepressant discovery relies heavily on glutamatergic mechanisms. New medicines based upon the model of ketamine have been delivered and are in clinical development. Rapid onset and the ability to impact treatment-resistant depression, raises the question of the best first-line medicines for patients. Drugs with improvements in tolerability are being investigated (e.g. mGlu_2/3 receptor antagonists, AMPA receptor potentiators, and novel NMDA receptor modulators). Multiple companies are working toward the identification of novel psychedelic drugs where the requirement for psychedelic activity is not fully known. Gaps still exist - methods for matching patients with specific medicines are needed, and medicines for the prevention of MDD and its disease progression need research attention.

Pharmacological targeting of cognitive impairment in depression: recent developments and challenges in human clinical research

Impaired cognition is often overlooked in the clinical management of depression, despite its association with poor psychosocial functioning and reduced clinical engagement. There is an outstanding need for new treatments to address this unmet clinical need, highlighted by our consultations with individuals with lived experience of depression. Here we consider the evidence to support different pharmacological approaches for the treatment of impaired cognition in individuals with depression, including treatments that influence primary neurotransmission directly as well as novel targets such as neurosteroid modulation. We also consider potential methodological challenges in establishing a strong evidence base in this area, including the need to disentangle direct effects of treatment on cognition from more generalised symptomatic improvement and the identification of sensitive, reliable and objective measures of cognition.

Baseline patterns of resting functional connectivity within posterior default-mode intranetwork associated with remission to antidepressants in major depressive disorder

BACKGROUND

The default mode network (DMN) is implicated in the pathophysiology of major depressive disorder (MDD), and functional connectivity (FC) involved in DMN is suggested to be associated with antidepressant remission. The goal of this study is to recognize relationships between FC within DMN and early amelioration in MDD patients and to further test the capacity of FC to predict early efficacy.

METHODS

In total 66 MDD patients and 57 healthy controls were recruited for resting-state functional magnetic resonance imaging scans at baseline. After four weeks of treatment with Escitalopram or Venlafaxine, patients were divided into subgroups with remitters (R, n = 31) and non-remitters (NR, n = 35). Independent component analysis (ICA) was used to compare intranetwork functional connectivity (intra-FC) in DMN between the three groups.

RESULTS

Relative to NR-MDD group and HCs, the R-MDD group showed significantly higher intra-FC in the right angular gyrus of DMN, and the intra-FC was positively correlated with the reduction ratio of the depressive symptom scores. The ROC curve analysis revealed that intra-FC exhibited a high diagnostic value for remission.

CONCLUSION

These findings indicated that intra-FC related to the DMN is a prognostic marker that can potentially predict early remission of symptoms after antidepressant treatment.

Abnormal Dynamic Functional Connectivity of the Left Rostral Hippocampus in Predicting Antidepressant Efficacy in Major Depressive Disorder

OBJECTIVE

Some pharmacological treatments are ineffective in parts of patients with major depressive disorder (MDD), hence this needs prediction of effective treatment responses. The study aims to examine the relationship between dynamic functional connectivity (dFC) of the hippocampal subregion and antidepressant improvement of MDD patients and to estimate the capability of dFC to predict antidepressant efficacy.

METHODS

The data were from 70 MDD patients and 43 healthy controls (HC); the dFC of hippocampal subregions was estimated by sliding-window approach based on resting-state functional magnetic resonance imaging (R-fMRI). After 3 months treatment, 36 patients underwent second R-fMRI scan and were then divided into the response group and non-response group according to clinical responses.

RESULTS

The result manifested that MDD patients exhibited lower mean dFC of the left rostral hippocampus (rHipp.l) compared with HC. After 3 months therapy, the response group showed lower dFC of rHipp.l compared with the non-response group. The dFC of rHipp.l was also negatively correlated with the reduction rate of Hamilton Depression Rating Scale.

CONCLUSION

These findings highlighted the importance of rHipp in MDD from the dFC perspective. Detection and estimation of these changes might demonstrate helpful for comprehending the pathophysiological mechanism and for assessment of treatment reaction of MDD.

Biomarkers as predictors of treatment response to tricyclic antidepressants in major depressive disorder: A systematic review

Tricyclic antidepressants (TCAs) are frequently prescribed in case of non-response to first-line antidepressants in Major Depressive Disorder (MDD). Treatment of MDD often entails a trial-and-error process of finding a suitable antidepressant and its appropriate dose. Nowadays, a shift is seen towards a more personalized treatment strategy in MDD to increase treatment efficacy. One of these strategies involves the use of biomarkers for the prediction of antidepressant treatment response. We aimed to summarize biomarkers for prediction of TCA specific (i.e. per agent, not for the TCA as a drug class) treatment response in unipolar nonpsychotic MDD. We performed a systematic search in PubMed and MEDLINE. After full-text screening, 36 papers were included. Seven genetic biomarkers were identified for nortriptyline treatment response. For desipramine, we identified two biomarkers; one genetic and one nongenetic. Three nongenetic biomarkers were identified for imipramine. None of these biomarkers were replicated. Quality assessment demonstrated that biomarker studies vary in endpoint definitions and frequently lack power calculations. None of the biomarkers can be confirmed as a predictor for TCA treatment response. Despite the necessity for TCA treatment optimization, biomarker studies reporting drug-specific results for TCAs are limited and adequate replication studies are lacking. Moreover, biomarker studies generally use small sample sizes. To move forward, larger cohorts, pooled data or biomarkers combined with other clinical characteristics should be used to improve predictive power.

Skin conductance while facing emotional pictures at day 7 helps predicting antidepressant response at three months in patients with a major depressive episode

There are currently no reliable biological markers to identify antidepressant responders in patients suffering from major depressive disorder. In this longitudinal pilot study, we measured skin conductance response (SCR) to assess patients' emotional reactivity after antidepressant treatment initiation. Fifty-four adult patients with a major depressive episode were recruited and followed up for 3 months. After one day of antidepressant treatment (D1) and then at day 7 (D7), emotional stimuli were presented on a computer screen while SCR and subjective emotional response were recorded. Three months later, we used Montgomery and Åsberg Depression Rating Scale (MADRS) to screen patients for treatment response, and distinguished responders (N = 28) from non-responders (N = 15). While SCR at D1 did not differ between responders and non-responders, SCR at D7 was higher in responders for both positive, negative and neutral stimuli. Skin conductance rates at D7 had a relatively poor negative predictive value (38%) but a strong positive predictive value (95%). Further studies are needed to replicate in a larger sample, and validate, these preliminary results which suggest that electrodermal activity after treatment initiation could help predict antidepressant efficacy.

Changes in RNA expression levels during antidepressant treatment: a systematic review

More than a third of patients treated with antidepressants experience treatment resistance. Furthermore, molecular pathways involved in antidepressant effect have yet to be fully understood. Therefore, we performed a systematic review of clinical studies that examined changes in RNA expression levels produced by antidepressant treatment. Literature search was performed through April 2021 for peer-reviewed studies measuring changes in mRNA or non-coding RNA levels before and after antidepressant treatment in human participants following PRISMA guidelines. Thirty-one studies were included in qualitative synthesis. We identified a large amount of heterogeneity between the studies for genes/RNAs measured, antidepressants used, and treatment duration. Of the six RNAs examined by more than one study, expression of the brain-derived neurotrophic factor (BDNF) gene and genes in the inflammation pathway, particularly IL-1β, were consistently reported to be altered by antidepressant treatment. Limitations of this review include heterogeneity of the studies, possibility of positive publication bias, and risk of false-negative findings secondary to small sample sizes. In conclusion, our systematic review provides an updated synthesis of RNA expression changes produced by antidepressant treatment in human participants, where genes in the BDNF and inflammatory pathways were identified as potential targets of antidepressant effect. Importantly, these findings also highlight the need for replication of the included studies in multiple strong, placebo-controlled studies for the identification of evidence-based markers that can be targeted to improve treatment outcomes.

Functional connectivity of the hippocampus in predicting early antidepressant efficacy in patients with major depressive disorder

BAKGROUD

The hippocampus is involved in the pathophysiology of major depressive disorder (MDD), and its structure and function have been reported to be related to the antidepressant response. This study aimed to identify relationships between hippocampal functional connectivity (FC) and early improvement in patients with MDD and to further explore the ability of hippocampal FC to predict early efficacy.

METHODS

Thirty-six patients with nonpsychotic MDD were recruited and underwent resting-state functional magnetic resonance imaging scans at baseline. After two weeks of treatment with escitalopram, patients were divided into subgroups with early improved depression (EID, n= 19) and nonimproved depression (NID, n=17) . A voxelwise FC analysis was performed with the bilateral hippocampus as seeds, two-sample t-tests were used to compare hippocampal FC between groups. Receiver operating characteristic (ROC) curves were constructed to determine the best FC measures and optimal threshold for differentiating EID from END.

RESULTS

The EID group showed significantly higher FC between the left hippocampus and left inferior frontal gyrus and precuneus than the END group. And the left hippocampal FC of these two regions were positively correlated with the reduction ratio of the depressive symptom scores. The ROC curve analysis revealed that summed FC scores for these two regions exhibited the highest area under the curve, with a sensitivity of 0.947 and specificity of 0.882 at a summed score of 0.14.

LIMITATIONS

The sample used in this study was relatively small.

CONCLUSIONS

These findings demonstrated that FC of the left hippocampus can predict early efficacy of antidepressant.

[The link of platelet cytochrome C-oxidase activity with some clinical parameters of depression in elderly patients]

OBJECTIVE

To search for correlations between platelet cytochrome c-oxidase (COX) activity and the quality of therapeutic outcomes and other clinical parameters of depression in elderly patients.

MATERIAL AND METHODS

Twenty elderly women, aged 55-78 years, with depressive episodes in recurrent depressive disorder (RDD) or bipolar affective disorder (BD) were studied. COX activity and severity of depression were evaluated twice: before the beginning of antidepressant treatment and at the 28-th day of the therapy, using the Hamilton Depression Rating Scale (HAMD-17) and the Hamilton Anxiety Rating Scale (HAM-A).

RESULTS

Significant correlations were revealed between platelet COX activity and some clinical parameters of the disease and the severity of depression in patients after treatment. The baseline level of the platelet COX activity was correlated with the age of disease onset (R= -0.63, p=0.003) and its duration (R=0.55, p=0.010). Significant negative correlations were also found between the baseline level of COX activity and depression severity (HAMD-17 total score) (R= -0.48, p=0.032) and the severity of anxiety (HARSHAM-A total score) (R= -0.54, p=0.010) after 28-day treatment.

CONCLUSION

This pilot study has revealed a link between platelet COX activity and the severity of depression and anxiety after a 28-day antidepressant therapy. The results indicate the prospects for further study of COX as a biomarker of therapeutic outcomes in elderly patients with depression.

Using EEG to Predict Clinical Response to Electroconvulsive Therapy in Patients With Major Depression: A Comprehensive Review

Introduction: An important approach to improve the therapeutic effect of electroconvulsive therapy (ECT) may be to early characterize patients who are more likely to respond. Our objective was to explore whether baseline electroencephalography (EEG) settings before the beginning of ECT treatment can predict future clinical response to ECT in patients with depressive disorder. Methods: We conducted a systematic search in the MEDLINE, EMBASE, PsycINFO, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL) databases to identify studies using EEG in adults with depressive disorder treated by ECT. To investigate the predictive value of baseline EEG on clinical outcomes of ECT, we extracted from the retrieved studies and qualitatively described the association between the baseline EEG markers characteristics and the rates of future responders and/or remitters to ECT. Results: The primary search yielded 2,531 potentially relevant citations, and 12 articles were selected according to inclusion criteria. Most of the studies were prospective studies with small sample size. Sociodemographic and clinical characteristics of patients, ECT settings, EEG settings, and outcomes were heterogeneous. Event-related potential (ERP) paradigms were used in three studies, polysomnography was used in three studies, and the six other studies used EEG to measure cerebral connectivity and activity. Conclusions: P300 amplitude, coherence, and connectivity measures were correlated with remission in patients with depression treated by ECT. Sleep EEG recordings seemed not to be correlated with remission after ECT. Further prospective studies with large sample size are needed to determine optimal EEG parameters associated with clinical response to ECT in depressive disorder. Systematic Review Registration: PROSPERO CRD42020181978.

Corticotropin releasing hormone receptor CRHR1 gene is associated with tianeptine antidepressant response in a large sample of outpatients from real-life settings

Polymorphisms of genes involved in the hypothalamic-pituitary-adrenocortical (HPA) axis have been associated with response to several antidepressant treatments in patients suffering of depression. These pharmacogenetics findings have been reported from independent cohorts of patients mostly treated with selective serotonin reuptake inhibitors, tricyclic antidepressant, and mirtazapine. Tianeptine, an atypical antidepressant, recently identified as a mu opioid receptor agonist, which prevents and reverses the stress induced by glucocorticoids, has been investigated in this present pharmacogenetics study. More than 3200 Caucasian outpatients with a major depressive episode (MDE) from real-life settings were herein analyzed for clinical response to tianeptine, a treatment initiated from 79.5% of the subjects, during 6-8 weeks follow-up, assessing polymorphisms targeting four genes involved in the HPA axis (NR3C1, FKPB5, CRHR1, and AVPR1B). We found a significant association (p < 0.001) between CRHR1 gene variants rs878886 and rs16940665, or haplotype rs878886*C-rs16940665*T, and tianeptine antidepressant response and remission according to the hospital anxiety and depression scale. Analyses, including a structural equation model with simple mediation, suggest a moderate effect of sociodemographic characteristics and depressive disorder features on treatment response in individuals carrying the antidepressant responder allele rs8788861 (allele C). These findings suggest direct pharmacological consequences of CRHR1 polymorphisms in the antidepressant tianeptine response and remission, in MDE patients. This study replicates the association of the CRHR1 gene, involved in the HPA axis, with (1) a specificity attributed to treatment response, (2) a lower risk of chance finding, and in (3) an ecological situation.

Analyzing Non-verbal Behavior Throughout Recovery in a Sample of Depressed Patients Receiving Deep Brain Stimulation

BACKGROUND

Traditional rating scales for depression rely heavily on patient self-report, and lack detailed measurement of non-verbal behavior. However, there is evidence that depression is associated with distinct non-verbal behaviors, assessment of which may provide useful information about recovery. This study examines non-verbal behavior in a sample of patients receiving Deep Brain Stimulation (DBS) treatment of depression, with the purpose to investigate the relationship between non-verbal behaviors and reported symptom severity.

METHODS

Videotaped clinical interviews of twelve patients participating in a study of DBS for treatment-resistant depression were analyzed at three time points (before treatment and after 3 months and 6 months of treatment), using an ethogram to assess the frequencies of 42 non-verbal behaviors. The Beck Depression Inventory (BDI) and Hamilton Depression Rating Scale (HDRS-17) were also collected at all time points.

RESULTS

Factor analysis grouped non-verbal behaviors into three factors: react, engage/fidget, and disengage. Two-way repeated measures ANOVA showed that scores on the three factors change differently from each other over time. Mixed effects modelling assessed the relationship between BDI score and frequency of non-verbal behaviors, and provided evidence that the frequency of behaviors related to reactivity and engagement increase as BDI score decreases.

LIMITATIONS

This study assesses a narrow sample of patients with a distinct clinical profile at limited time points.

CONCLUSIONS

Non-verbal behavior provides information about clinical states and may be reliably quantified using ethograms. Non-verbal behavior may provide distinct information compared to self-report.

Impact of number of sleep ultradian cycles on polysomnographic parameters related to REM sleep in major depression: Implications for future sleep research in psychiatry

Given the contradictory data on REMS alterations in major depression, the aim of this study was to empirically demonstrate that based on the number of sleep ultradian cycles, it was possible to highlight different subtypes of major depression characterized by specific patterns of REMS alterations. Demographic and polysomnographic data from 211 individuals (30 healthy controls and 181 untreated major depressed individuals) recruited from the sleep laboratory database were analyzed. Major depressed individuals with sleep ultradian cycles <4 showed alterations consistent with REMS deficiency (non-shortened REM latency as well as decrease in REMS percentage, REMS duration and REMS/NREMS ratio) whereas major depressed individuals with sleep ultradian cycles >4 showed alterations consistent with REMS disinhibition (shortened REM latency as well as increase in REMS percentage, REMS duration and REMS/NREMS ratio). Regarding major depressed individuals with 4 sleep ultradian cycles, their REMS alterations were intermediate to those present in major depressed individuals with sleep ultradian cycles <4 and >4. Thus, in major depressed individuals, the highlighting of this heterogeneity of REMS alterations based on the number of sleep ultradian cycles seems to suggest the involvement of distinct pathophysiological mechanisms and could open new perspectives for future sleep research in psychiatry.

[Personalized approach to the treatment of depression in the elderly]

AIM

To develop a personalized approach to the appointment of a complex antidepressant therapy in combination with drugs of neuroprotective and neurotrophic action in depressed elderly patients based on the selection of predictors of low therapeutic response (LTR).

MATERIAL AND METHODS

The study included 152 hospitalized patients, aged 60 years and older, with moderate and mild depression (ICD-10) who received monotherapy (44 people) with antidepressants of the new generation and complex therapy (108 people) with the same antidepressants in combination with neuroprotective drugs. In the monotherapy group, correlations between treatment efficacy (change in average total HAMD-17 scores) and a set of parameters, including socio-demographic data, results of psychopathological, somatic, standardized assessment and neuroimaging (CT) of the brain were analyzed. The validity of the established correlations as predictors of LTR was estimated based on a comparison of their frequency among the responders (≥50% reduction) and non-responders (<50% reduction). Comparison of the efficacy of therapy in groups of patients with mono - and complex therapy was carried out depending on the presence or absence of predictors of LTR.

RESULTS

LTR predictors are living alone, complaints about memory loss and signs of pronounced diffuse lesions of the subcortical white matter of the brain, which are significantly more frequently observed in non-responders (p<0.05). The increase in the number of predictors (2 and more) correlates with a significant decrease in therapeutic efficacy (p<0.001). Patients with complex in structure and protracted depressions tend to decrease in efficiency, and in most of them (more than 87% of cases) LTR predictors are detected. In patients with LTR predictors, the complex therapy is significantly more effective than monotherapy, allowing in all cases to achieve 50% reduction of depressive symptoms by the 4th week of treatment.

CONCLUSION

Personalized indications for the appointment of complex antidepressant therapy in combination with neuroprotective drugs in depressed elderly patients are formulated.

Alterations of neural network organisation during rapid eye movement sleep and slow-wave sleep in major depression: Implications for diagnosis, classification, and treatment

The aim of this study was to empirically investigate the network organisation during rapid eye movement sleep (REMS) and slow-wave sleep (SWS) using the effective connectivity measured using the Granger causality to identify new potential biomarkers for the diagnosis, classification, and potential favourable response to treatment in major depression. Polysomnographic data were analysed from 24 healthy individuals and 16 major depressed individuals recruited prospectively. To obtain the 19×19 connectivity matrix of all possible pairwise combinations of electrodes by the Granger causality method from our electroencephalographic data, we used the Toolbox MVGC multivariate Granger causality. The computation of network measures was realised by importing these connectivity matrices into the EEGNET Toolbox. Major depressed individuals (versus healthy individuals) and those with endogenous depression (versus those with neurotic depression) present alterations of small-world network organisation during REMS, whereas major depressed individuals with potential favourable response to electroconvulsive therapy (versus those with potential unfavourable response) have a less efficient small-world network organisation during SWS. Thus, alterations in network organisation during REMS could be biomarkers for the diagnosis and classification of major depressive episodes, whereas alterations of network organisation during SWS could be a biomarker to predict potential favourable response to treatment by electroconvulsive therapy.

The Urge to Decide and Act: Implications for Brain Function and Dysfunction

Humans and other animals are motivated to act so as to maximize their subjective reward rate. Here, we propose that reward rate maximization is accomplished by adjusting a context-dependent “urgency signal,” which influences both the commitment to a developing action choice and the vigor with which the ensuing action is performed. We review behavioral and neurophysiological data suggesting that urgency is controlled by projections from the basal ganglia to cerebral cortical regions, influencing neural activity related to decision making as well as activity related to action execution. We also review evidence suggesting that different individuals possess specific policies for adjusting their urgency signal to particular contextual variables, such that urgency constitutes an individual trait which jointly influences a wide range of behavioral measures commonly related to the overall quality and hastiness of one’s decisions and actions. Consequently, we argue that a central mechanism for reward rate maximization provides a potential link between personality traits such as impulsivity, as well as some of the motivation-related symptomology of clinical disorders such as depression and Parkinson’s disease.

Patterns of Membrane Protein Clustering in Peripheral Lymphocytes as Predictors of Therapeutic Outcomes in Major Depressive Disorder

There is an utmost necessity of developing novel biomarkers of depression that result in a more efficacious use of current antidepressant drugs. The present report reviews and discusses a recent series of experiments that focused on analysis of membrane protein clustering in peripheral lymphocytes as putative biomarkers of therapeutic efficacy for major depressive disorder. This review recapitulates how the ideas were originated, and the main findings demonstrated that analysis of serotonin transporter and serotonin 2 A receptor clustering in peripheral lymphocytes of naïve depression patients resulted in a discrimination of two subpopulations of depressed patients that showed a differential response upon 8 weeks of antidepressant treatment. The paper also reviews the usefulness of animal models of depression for an initial evaluation of membrane protein clustering in lymphocytes, which provides a screening tool to determine additional proteins to be further evaluated in depression patients. Finally, the present review provides a brief discussion of the general field of biomarkers of depression in relation to therapeutic outcomes and suggests additional ideas to provide extra value to the reviewed studies.

Predictors of the effectiveness of an early medication change strategy in patients with major depressive disorder

BACKGROUND

Patients with Major Depressive Disorder (MDD) who are non-improvers after two weeks of antidepressant treatment have a high risk of treatment failure. Recently, we did not find differences in outcomes in non-improvers randomized to an early medication change (EMC) strategy compared to treatment as usual (TAU). This secondary analysis investigated possible predictors of higher remission rates in the EMC strategy.

METHODS

Of 192 non-improvers (i.e. decrease of ≤20% on the HAMD-17 depression scale) after a two-week treatment with escitalopram, n = 97 were randomized to EMC (immediate switch to high doses of venlafaxine XR) and n = 95 to TAU (continued escitalopram until day 28 with non-responders switched to venlafaxine XR). We first analyzed patient characteristics, psychopathological features and subtypes of MDD by logistic regression analyses as possible predictors of remission rates. In a second investigation, we analyzed the predictors, which showed a significant association in the first analysis before Bonferroni-Holm correction by chi-squared tests separated for treatment groups. All analyses were corrected by Bonferroni-Holm method.

RESULTS

The first analyses yielded no statistically significant results after correction for multiple testing. In the second analyses, however, patients with prior medication at study entry showed higher remission rates in EMC than in TAU (24.2% versus 8.6%, p = 0.017; Bonferroni-Holm corrected significance level: p = 0.025.). Furthermore, patients with a recurrent course of MDD benefited less from treatment as usual (p = 0.009; Bonferroni-Holm corrected significance level: p = 0.025). Age, sex, age of onset, psychiatric or somatic comorbidities, and other subtypes of MDD did not predict remission rates.

CONCLUSIONS

Although in our first analysis we found statistically non-significant results, the second analysis showed significant differences in remission rates between patients with or without previous medication and in patients with recurrent MDD or the first depressive episode. It would therefore be valuable to examine in larger and prospective studies whether remission rates can be increased by quick escalation of treatment in certain subgroups of patients. Promising subgroups to be tested are patients who were previously medicated, and who show a recurrent course of MDD.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00974155 . Registered at the 10th of September 2009. Retrospectively registered.

Predictors of Response and Remission to Antidepressants in Geriatric Depression: A Systematic Review

BACKGROUND

Geriatric depression is a heterogeneous disorder that increases morbidity and mortality in a population that is already vulnerable. Predicting response and remission to antidepressants could help clinicians to optimize the management of antidepressants and reduce the consequences of depression.

METHOD

The aim of this article is to present results of a systematic review of the literature on predictive factors related to antidepressant response and remission in older adults with depression.

MAIN FINDINGS

We identified sociodemographic, clinical, neuropsychological, neuroimaging, and genetic factors that could be potential predictors of outcomes. Inconsistent findings and methodological differences among studies, however, limit the generalizability and application of these predictors in clinical practice. The results of our review confirm that geriatric depression includes many subgroups of patients with particular endophenotypes that may influence the course of depression.

CONCLUSION

Further studies are needed to characterize depression subgroups in order to better understand the pathophysiology of late life depression and to find specific predictors for each group of patients.