Recent advances in predicting responses to antidepressant treatment

Real-world assessment of treatment inertia in the management of patients treated for major depressive disorder in the USA

Aim: Major depressive disorder (MDD) is a debilitating illness in which depressive symptoms may persist after treatment. Treatment inertia is the continued use of the same pharmacotherapy regimen when treatment goals are not met. This study assessed the frequency of treatment inertia among adult patients with MDD treated in a real-world setting. Patients & methods: This was a retrospective, observational study of patients with MDD identified in the Decision Resources Group Real World Evidence US Data Repository from January 2014 to June 2018. Patients (≥18 years) had an elevated Patient Health Questionnaire-9 (PHQ-9) score (≥5) following 8 weeks of stable baseline antidepressant use with/without mental-health outpatient therapy. Treatment inertia, modification and discontinuation were evaluated over a 16-week follow-up period (timeline based on the APA Practice Guidelines). The primary outcome was the proportion of MDD patients experiencing treatment inertia. Results: 2850 patients (median age, 55 years; 74% female) met the study criteria. Of these patients, 834 (29%) had study-defined treatment inertia, 1534 (54%) received treatment modification and 482 (17%) discontinued treatment. Use of mirtazapine (Odd ratio [OR]: 0.63; 95% confidence interval [CI]: 0.50-0.79), selective serotonin reuptake inhibitors (OR: 0.64; 95% CI: 0.54-0.75) or bupropion (OR: 0.71; 95% CI: 0.60-0.84) in the baseline period was associated with an increased likelihood of treatment modification versus not receiving treatment with these medications. Frequency of treatment inertia may differ among those who do not have a documented PHQ-9 score. Conclusion: Effective symptom management is critical for optimal outcomes in MDD. Results demonstrate that treatment inertia is common in MDD despite guidelines recommending treatment modification in patients not reaching remission.

A non-hallucinogenic LSD analog with therapeutic potential for mood disorders

Hallucinations limit widespread therapeutic use of psychedelics as rapidly acting antidepressants. Here we profiled the non-hallucinogenic lysergic acid diethylamide (LSD) analog 2-bromo-LSD (2-Br-LSD) at more than 33 aminergic G protein-coupled receptors (GPCRs). 2-Br-LSD shows partial agonism at several aminergic GPCRs, including 5-HT2A, and does not induce the head-twitch response (HTR) in mice, supporting its classification as a non-hallucinogenic 5-HT2A partial agonist. Unlike LSD, 2-Br-LSD lacks 5-HT2B agonism, an effect linked to cardiac valvulopathy. Additionally, 2-Br-LSD produces weak 5-HT2A β-arrestin recruitment and internalization in vitro and does not induce tolerance in vivo after repeated administration. 2-Br-LSD induces dendritogenesis and spinogenesis in cultured rat cortical neurons and increases active coping behavior in mice, an effect blocked by the 5-HT2A-selective antagonist volinanserin (M100907). 2-Br-LSD also reverses the behavioral effects of chronic stress. Overall, 2-Br-LSD has an improved pharmacological profile compared with LSD and may have profound therapeutic value for mood disorders and other indications.

Using Machine Learning to Predict Antidepressant Treatment Outcome From Electronic Health Records

Objective

To evaluate if a machine learning approach can accurately predict antidepressant treatment outcome using electronic health records (EHRs) from patients with depression.

Method

This study examined 808 patients with depression at a New York City-based outpatient mental health clinic between June 13, 2016 and June 22, 2020. Antidepressant treatment outcome was defined based on trend in depression symptom severity over time and was categorized as either "Recovering" or "Worsening" (i.e., non-Recovering), measured by the slope of individual-level Patient Health Questionnaire-9 (PHQ-9) score trajectory spanning 6 months following treatment initiation. A patient was designated as "Recovering" if the slope is less than 0 and as "Worsening" if the slope was no less than 0. Multiple machine learning (ML) models including L2 norm regularized Logistic Regression, Naive Bayes, Random Forest, and Gradient Boosting Decision Tree (GBDT) were used to predict treatment outcome based on additional data from EHRs, including demographics and diagnoses. Shapley Additive Explanations were applied to identify the most important predictors.

Results

The GBDT achieved the best results of predicting "Recovering" (AUC: 0.7654 ± 0.0227; precision: 0.6002 ± 0.0215; recall: 0.5131 ± 0.0336). When excluding patients with low PHQ-9 scores (<10) at baseline, the results of predicting "Recovering" (AUC: 0.7254 ± 0.0218; precision: 0.5392 ± 0.0437; recall: 0.4431 ± 0.0513) were obtained. Prior diagnosis of anxiety, psychotherapy, recurrent depression, and baseline depression symptom severity were strong predictors.

Conclusions

The results demonstrate the potential utility of using ML in longitudinal EHRs to predict antidepressant treatment outcome. Our predictive tool holds the promise to accelerate personalized medical management in patients with psychiatric illnesses.

S-adenosyl-l-methionine antidepressant-like effects involve activation of 5-HT1A receptors

S-adenosyl-l-methionine (SAMe), a methyl donor, induces antidepressant effects in preclinical and clinical studies of depression. However, the mechanisms behind these effects have been poorly investigated. Since SAMe is involved in monoamine metabolism, this work aimed at 1) testing the effects induced by systemic treatment with SAMe in mice submitted to the forced swimming test (FST) and tail suspension test (TST); 2) investigating the involvement of serotonergic neurotransmission in the behavioral effects induced by SAMe. To do that, male Swiss mice received systemic injections (1 injection/day, 1 or 7 days) of imipramine (30 mg/kg), L-methionine (400, 800, 1600, and 3200 mg/kg), SAMe (10, 25, 50, 100, and 200 mg/kg), or vehicle (10 ml/kg) and were submitted to the FST or TST, 30 min after the last injection. The effect of SAMe (50 mg/kg) was further investigated in independent groups of male Swiss mice pretreated with p-chlorophenylalanine (PCPA, serotonin synthesis inhibitor, 150 mg/kg daily, 4 days) or with WAY100635 (5-HT_1A receptor antagonist, 0.1 mg/kg, 1 injection). One independent group was submitted to the FST and euthanized immediately after for collection of brain samples for neurochemical analyses. Serotonin (5-HT) and noradrenaline (NA) levels were measured in the hippocampus (HPC) and prefrontal cortex (PFC). Furthermore, to investigate if the treatments used could induce any significant exploratory/motor effect which would interfere with the FST results, the animals were also submitted to the open field test (OFT). The administration of imipramine (30 mg/kg), L-methionine (400, 800, 1600, and 3200 mg/kg), and SAMe (10 and 50 mg/kg) reduced the immobility time in the FST, an effect blocked by pretreatment with PCPA and WAY100635. None of the treatments increased the locomotion in the OFT. In conclusion, our results suggest that the antidepressant-like effects induced by SAMe treatment are dependent on serotonin synthesis and 5-HT_1A receptor activation.

Waking inactivity as a welfare indicator in laboratory mice: investigating postures, facial expressions and depression-like states

Animal welfare assessment relies on valid and practical indicators of affect. In mice, the most widely used research vertebrates, lying still with eyes open, inactive-but-awake (IBA) in the home cage, has potential to be one such indicator. IBA is elevated in barren, conventional housing compared with well-resourced, enriched housing, and predicts immobility in Forced Swim Tests, a common measure of 'helplessness' in depression research. In Experiment 1, using females from three strains (C57BL/6, Balb/c and DBA/2), we first replicated past findings, confirming higher levels of IBA in conventional cages and a positive relationship between IBA and helplessness. We then extended this research to three other signs of depression: changes in weight and sleep, and reduced hippocampal volume. Here, IBA positively covaried with body mass index, with sleep in DBA/2s and conventionally housed BALB/cs, and negatively covaried with hippocampal volume in conventionally housed C57BL/6s. In Experiment 2, we sought to refine the phenotype of IBA to improve its accuracy as a welfare indicator. Here, scoring IBA performed in hunched postures appeared to improve its accuracy as an indicator in Balb/c mice. Additional research is now needed to further refine the phenotype of IBA and to confirm whether it reflects states consistent with depression, or instead other underlying poor welfare conditions.

Waking inactivity as a welfare indicator in laboratory mice: investigating postures, facial expressions and depression-like states

Animal welfare assessment relies on valid and practical indicators of affect. In mice, the most widely used research vertebrates, lying still with eyes open, inactive-but-awake (IBA) in the home cage, has potential to be one such indicator. IBA is elevated in barren, conventional housing compared with well-resourced, enriched housing, and predicts immobility in Forced Swim Tests, a common measure of 'helplessness' in depression research. In Experiment 1, using females from three strains (C57BL/6, Balb/c and DBA/2), we first replicated past findings, confirming higher levels of IBA in conventional cages and a positive relationship between IBA and helplessness. We then extended this research to three other signs of depression: changes in weight and sleep, and reduced hippocampal volume. Here, IBA positively covaried with body mass index, with sleep in DBA/2s and conventionally housed BALB/cs, and negatively covaried with hippocampal volume in conventionally housed C57BL/6s. In Experiment 2, we sought to refine the phenotype of IBA to improve its accuracy as a welfare indicator. Here, scoring IBA performed in hunched postures appeared to improve its accuracy as an indicator in Balb/c mice. Additional research is now needed to further refine the phenotype of IBA and to confirm whether it reflects states consistent with depression, or instead other underlying poor welfare conditions.

Antidepressant-like Effects of BDNF and NGF Individual Loop Dipeptide Mimetics Depend on the Signal Transmission Patterns Associated with Trk

Neurotrophins are considered as an attractive target for the development of antidepressants with a novel mechanism of action. Previously, the dimeric dipeptide mimetics of individual loops of nerve growth factor, NGF (GK-6, loop 1; GK-2, loop 4) and brain-derived neurotrophic factor, BDNF (GSB-214, loop 1; GTS-201, loop 2; GSB-106, loop 4) were designed and synthesized. All the mimetics of NGF and BDNF in vitro after a 5–180 min incubation in a HT-22 cell culture were able to phosphorylate the tropomyosin-related kinase A (TrkA) or B (TrkB) receptors, respectively, but had different post-receptor signaling patterns. In the present study, we conduct comparative research of the antidepressant-like activity of these mimetics at acute and subchronic administration in the forced swim test in mice. Only the dipeptide GSB-106 that in vitro activates mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK), phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) and phospholipase C-gamma (PLC_γ) post-receptor pathways exhibited antidepressant-like activity (0.1 and 1.0 mg/kg, ip) at acute administration. At the same time, the inhibition of any one of these signaling pathways completely prevented the antidepressant-like effects of GSB-106 in the forced swim test. All the NGF mimetics were inactive after a single injection regardless of post-receptor in vitro signaling patterns. All the investigated dipeptides, except GTS-201, not activating PI3K/AKT in vitro unlike the other compounds, were active at subchronic administration. The data obtained demonstrate that the low-molecular weight BDNF mimetic GSB-106 that activates all three main post-receptor TrkB signaling pathways is the most promising for the development as an antidepressant.

Do greater levels of in-cage waking inactivity in laboratory mice reflect a spontaneous depression-like symptom? A pharmacological investigation

We previously identified in laboratory mice an inactive state [being awake with eyes open motionless within the home cage; inactive but awake, 'IBA'] sharing etiological factors and symptoms with human clinical depression. We further test the hypothesis that greater time spent displaying IBA indicates a depression-like state in mice by investigating whether the antidepressant Venlafaxine, environmental enrichment, and their combination, alleviate IBA. Seventy-two C57BL/6J and 72 DBA/2J female mice were pseudo-randomly housed post-weaning in mixed strain-pairs in non-enriched (NE; 48 pairs) or in environmentally enriched (EE; 24 pairs) cages. After 34 days, half of the mice housed in NE cages were either relocated to EE cages or left in NE cages. For each of these conditions, half of the mice drank either a placebo or the antidepressant Venlafaxine (10 mg/kg). The 48 mice housed in EE cages were all relocated to NE cages and allocated to either the placebo (n = 24) or Venlafaxine (n = 24). IBA data were collected prior to and after environmental adjustment by trained observers blind to the pharmacological and environmental adjustment treatments. Data were analyzed using GLM models. NE cages triggered more IBA than EE cages (Likelihood-Ratio-Test Chi²₃ = 53.501, p < 0.0001). Venlafaxine and environmental enrichment appeared equally effective at reducing IBA (LRT Chi²₃ = 18.262, p < 0.001), and combining these approaches did not magnify their effects. Enrichment removal triggered IBA increase (LRT Chi²₁ = 23.050, p < 0.001), but Venlafaxine did not overcome the increase in IBA resulting from enrichment loss (LTR Chi²₁ = 0.081, p = 0.775). Theoretical implications for putative depression-like states in mice, and further research directions, are discussed.

Interactions between maternal fluoxetine exposure, the maternal gut microbiome and fetal neurodevelopment in mice

Selective serotonin reuptake inhibitors (SSRIs) are the most widely used treatment by women experiencing depression during pregnancy. However, the effects of maternal SSRI use on early offspring development remain poorly understood. Recent studies suggest that SSRIs can modify the gut microbiota and interact directly with particular gut bacteria, raising the question of whether the gut microbiome impacts host responses to SSRIs. In this study, we investigate effects of prenatal SSRI exposure on fetal neurodevelopment and further evaluate potential modulatory influences of the maternal gut microbiome. We demonstrate that maternal treatment with the SSRI fluoxetine induces widespread alterations in the fetal brain transcriptome during midgestation, including increases in the expression of genes relevant to synaptic organization and neuronal signaling and decreases in the expression of genes related to DNA replication and mitosis. Notably, maternal fluoxetine treatment from E7.5 to E14.5 has no overt effects on the composition of the maternal gut microbiota. However, maternal pretreatment with antibiotics to deplete the gut microbiome substantially modifies transcriptional responses of the fetal brain to maternal fluoxetine treatment. In particular, maternal fluoxetine treatment elevates localized expression of the opioid binding protein/cell adhesion molecule like gene Opcml in the fetal thalamus and lateral ganglionic eminence, which is prevented by maternal antibiotic treatment. Together, these findings reveal that maternal fluoxetine treatment alters gene expression in the fetal brain through pathways that are impacted, at least in part, by the presence of the maternal gut microbiota.

An individualized treatment rule to optimize probability of remission by continuation, switching, or combining antidepressant medications after failing a first-line antidepressant in a two-stage randomized trial

BACKGROUND

There is growing interest in using composite individualized treatment rules (ITRs) to guide depression treatment selection, but best approaches for doing this are not widely known. We develop an ITR for depression remission based on secondary analysis of a recently published trial for second-line antidepression medication selection using a cutting-edge ensemble machine learning method.

METHODS

Data come from the SUN(^_^)D trial, an open-label, assessor blinded pragmatic trial of previously-untreated patients with major depressive disorder from 48 clinics in Japan. Initial clinic-level randomization assigned patients to 50 or 100 mg/day sertraline. We focus on the 1549 patients who failed to remit within 3 weeks and were then rerandomized at the individual-level to continuation with sertraline, switching to mirtazapine, or combining mirtazapine with sertraline. The outcome was remission 9 weeks post-baseline. Predictors included socio-demographics, clinical characteristics, baseline symptoms, changes in symptoms between baseline and week 3, and week 3 side effects.

RESULTS

Optimized treatment was associated with significantly increased cross-validated week 9 remission rates in both samples [5.3% (2.4%), p = 0.016 50 mg/day sample; 5.1% (2.7%), p = 0.031 100 mg/day sample] compared to randomization (30.1-30.8%). Optimization was also associated with significantly increased remission in both samples compared to continuation [24.7% in both: 11.2% (3.8%), p = 0.002 50 mg/day sample; 11.7% (3.9%), p = 0.001 100 mg/day sample]. Non-significant gains were found for optimization compared to switching or combining.

CONCLUSIONS

An ITR can be developed to improve second-line antidepressant selection, but replication in a larger study with more comprehensive baseline predictors might produce stronger and more stable results.

Using Biomarkers to Predict Memantine Effects in Alzheimer's Disease: A Proposal and Proof-Of-Concept Demonstration

Memantine's benefits in Alzheimer's disease (AD) are modest and heterogeneous. We tested the feasibility of using sensitivity to acute memantine challenge to predict an individual's clinical response. Eight participants completed a double-blind challenge study of memantine (placebo versus 20 mg) effects on autonomic, subjective, cognitive, and neurophysiological measures, followed by a 24-week unblinded active-dose therapeutic trial (10 mg bid). Study participation was well tolerated. Subgroups based on memantine sensitivity on specific laboratory measures differed in their clinical response to memantine, some by large effect sizes. It appears feasible to use biomarkers to predict clinical sensitivity to memantine.

Predictors of response to antidepressants in women with postpartum depression: a systematic review

Antidepressants are the mainstay of drug treatment for moderate or severe postpartum depression. Knowledge of predictors of response could help optimize treatment and reduce the adverse consequences of postpartum depression. The purpose of this systematic review was to ascertain predictors of response or remission to antidepressant treatment in women with postpartum depression. The electronic databases of MEDLINE/PubMed, PsycINFO, CINAHL, Cochrane Database of Systematic Reviews, and Evidence-based Medicine Reviews were searched through December 2019. The search was limited to studies published in the English language. Reference lists of articles that met the inclusion criteria were also searched. We identified some predictors of response and remission that could potentially assist in the optimization of drug treatment of postpartum depression; however, caution is needed to apply these findings in clinical practice due to the heterogeneous nature of postpartum depression. The results of our review highlight the urgent need to identify predictors of response, non-response, or remission to antidepressants in women with postpartum depression.

Predicting differential diagnosis between bipolar and unipolar depression with multiple kernel learning on multimodal structural neuroimaging

One of the greatest challenges in providing early effective treatment in mood disorders is the early differential diagnosis between major depression (MDD) and bipolar disorder (BD). A remarkable need exists to identify reliable biomarkers for these disorders. We integrate structural neuroimaging techniques (i.e. Tract-based Spatial Statistics, TBSS, and Voxel-based morphometry) in a multiple kernel learning procedure in order to define a predictive function of BD against MDD diagnosis in a sample of 148 patients. We achieved a balanced accuracy of 73.65% with a sensitivity for BD of 74.32% and specificity for MDD of 72.97%. Mass-univariates analyses showed reduced grey matter volume in right hippocampus, amygdala, parahippocampal, fusiform gyrus, insula, rolandic and frontal operculum and cerebellum, in BD compared to MDD. Volumes in these regions and in anterior cingulate cortex were also reduced in BD compared to healthy controls (n = 74). TBSS analyses revealed widespread significant effects of diagnosis on fractional anisotropy, axial, radial, and mean diffusivity in several white matter tracts, suggesting disruption of white matter microstructure in depressed patients compared to healthy controls, with worse pattern for MDD. To best of our knowledge, this is the first study combining grey matter and diffusion tensor imaging in predicting BD and MDD diagnosis. Our results prompt brain quantitative biomarkers and multiple kernel learning as promising tool for personalized treatment in mood disorders.

Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE

Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice.

OBJECTIVE

To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment.

DESIGN, SETTING, AND PARTICIPANTS

In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019.

INTERVENTIONS

Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks.

MAIN OUTCOMES AND MEASURES

Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit.

RESULTS

Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points.

CONCLUSIONS AND RELEVANCE

These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01407094.

Gene expression in peripheral blood in treatment-free major depression

BACKGROUND

Peripheral gene expression of several molecular pathways has been studied in major depressive disorder (MDD) with promising results. We sought to investigate some of these genes in a treatment-free Latino sample of Mexican descent.

MATERIAL AND METHODS

The sample consisted of 50 MDD treatment-free cases and 50 sex and age-matched controls. Gene expression of candidate genes of neuroplasticity (BDNF, p11, and VGF), inflammation (IL1A, IL1B, IL4, IL6, IL7, IL8, IL10, MIF, and TNFA), the canonical Wnt signaling pathway (TCF7L2, APC, and GSK3B), and mTOR, was compared in cases and controls. RNA was obtained from blood samples. We used bivariate analyses to compare subjects versus control mean mRNA quantification of target genes and lineal regression modelling to test for effects of age and body mass index on gene expression.

RESULTS

Most subjects were female (66%) with a mean age of 26.7 (SD 7.9) years. Only GSK3B was differentially expressed between cases and controls at a statistically significant level (p = 0.048). TCF7L-2 showed the highest number of correlations with MDD-related traits, yet these were modest in size.

DISCUSSION

GSK3B encodes a moderator of the canonical Wnt signaling pathway. It has a role in neuroplasticity, neuroprotection, depression, and other psychiatric phenotypes. We found that adding population diversity has the potential to elicit distinct peripheral gene expression markers in MDD and MDD-related traits. However, our results should only be considered as hypothesis-generating research that merits further replication in larger cohorts of similar ancestry.

S-Adenosylmethionine (SAMe) in major depressive disorder (MDD): a clinician-oriented systematic review

BACKGROUND

Major depressive disorder (MDD) is a recurrent illness with high rates of chronicity, treatment-resistance, and significant economic impact. S-Adenosylmethionine (SAMe), a molecule that is formed naturally in the human body, has shown antidepressant effects and may expand the available options for treating MDD. This systematic review examines the evidence concerning the efficacy of SAMe as monotherapy or in combination with antidepressants.

METHODS

A systematic search in Medline, Psychinfo, AMED, and Cochrane Controlled Trials Register was conducted for any reference recorded up to March 2020. Double-blind, randomised controlled trials, comparing the antidepressant efficacy of SAMe to placebo or/and to other antidepressants, were selected. Two authors evaluated each study independently and then, reconciled findings.

RESULTS

Eight trials, with a total of 11 arms and 1011 subjects, evaluating the efficacy of SAMe used as monotherapy or as adjunctive therapy (512 individuals), were included in this review. The study duration ranged between 2 and 12 weeks and the daily dose of SAMe varied from 200 to 3200 mg. Five comparisons evaluated the differences between SAMe and placebo and SAMe resulted significantly better than placebo in three of these studies. Four comparisons evaluated the differences between SAMe and other antidepressants (imipramine or escitalopram) and showed no significant difference. One study showed that SAMe was significantly better than placebo in accelerating the response to imipramine from day 4 to day 12, but the mean scores were not statistically different at the day 14 endpoint. One study showed that SAMe combined with serotonin reuptake inhibitors (SSRI) was better than PBO combined with SSRI. The studies reported only mild, transient or non-clinically relevant side effects.

CONCLUSIONS

The existing trials of SAMe, used as monotherapy or add on to another antidepressants, have shown encouraging and generally positive results. However, more evidence is necessary before definitive conclusions can be drawn. Larger, double-blind randomised controlled studies are warranted to confirm the antidepressant effectiveness of SAMe.

S-Adenosylmethionine (SAMe) monotherapy for depression: an 8-week double-blind, randomised, controlled trial

RATIONALE

Dysregulation of the one carbon cycle is documented in depression. Thereby, S-adenosylmethionine (SAMe), a one-carbon cycle nutraceutical compound with a favourable side effect profile, has a theoretical rationale for efficacy. However, further controlled studies are required to confirm SAMe's efficacy.

OBJECTIVES

To test the efficacy of SAMe versus placebo in unmedicated DSM-5 diagnosed (major depressive disorder) (MDD) patients with mild-to-moderate levels of depressive symptoms.

METHODS

We conducted an 8-week, double-blind, randomised controlled trial testing 800 mg/day of SAMe monotherapy versus placebo in 49 patients with MDD (Montgomery-Åsberg Depression Rating Scale [MADRS] score 14-25) who were not currently taking antidepressants. One-carbon cycle biomarkers, brain-derived neurotropic factor (BDNF), and relevant single nucleotide polymorphisms (SNPs) were analysed as potential treatment moderators.

RESULTS

A clinically relevant differential reduction from baseline to week 8 of 3.76 points occurred on the primary outcome (MADRS) in favour of SAMe. This however was not significant (p = 0.13) on an adjusted linear mixed model, notwithstanding a medium to large effect size of 0.72. A high placebo response rate of 53% occurred (> 50% reduction on MADRS). Exploratory analyses showed that SAMe was however effective in reducing depression amongst participants with milder depression severity (MADRS ≤ 22, p = 0.045). Response was not moderated by BDNF, SNPs, or one-carbon cycle biomarkers, although increased folate concentrations were correlated with improved symptoms in the SAMe group (r = - 0.57, p = 0.026). The treatment was safe and well tolerated.

CONCLUSIONS

Although a differential reduction in depression symptoms between groups was observed in favour of SAMe, the results of this pilot study were not statistically significant.

TRIAL REGISTRATION

ANZCTR-Australian New Zealand Clinical Trials Registry; No.: ACTRN12613001299796; URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364900.

Connectivity between the anterior insula and dorsolateral prefrontal cortex links early symptom improvement to treatment response

BACKGROUND

Early improvement (EI) following treatment with antidepressants is a widely reported predictor to the treatment response. This study aimed to identify the resting-state functional connectivity (rs-FC) and its related clinical features that link the treatment response at the time of EI.

METHODS

This study included 23 first-episode treatment-naive patients with MDD. After 2 weeks of antidepressant treatment, these patients received 3.0 Tesla resting-state functional magnetic resonance imaging scanning and were subgrouped into an EI group (N = 13) and a non-EI group (N = 10). Using the anterior insula (rAI) as a seed region, this study identified the rs-FC that were associated with both EI and the treatment response at week 12, and further tested the associations of the identified rs-FC with either the clinical features or the early symptom improvement.

RESULTS

Rs-FC between rAI and the left dorsolateral prefrontal cortex (dlPFC) was associated with EI (t₂₁ = -6.091, p = 0.022 after FDR correction for multiple comparisons). This rs-FC was also associated with an interaction between EI and the treatment response at the week 12 (t₂₁ = -5.361, p = 6.37e-5). Moreover, among the clinical features, this rs-FC was associated with the early symptom improvement in the insomnia, somatic symptoms, and anxiety symptoms, and these early symptom improvements were associated with the treatment response.

CONCLUSION

Rs-FC between the rAI and the left dlPFC played a crucial role in the early antidepressant effect, which linked the treatment response. The early treatment effect relating to rAI may represent an early symptom improvement in self-perceptual anxiety, somatic symptoms and insomnia.

Electroencephalography in Psychiatric Surgery: Past Use and Future Directions

The last two decades have seen a re-emergence of surgery for intractable psychiatric disease, in large part due to increased use of deep brain stimulation. The development of more precise, image-guided, less invasive interventions has improved the safety of these procedures, even though the relative merits of modulation at various targets remain under investigation. With an increase in the number and type of interventions for modulating mood/anxiety circuits, the need for biomarkers to guide surgeries and predict treatment response is as critical as ever. Electroencephalography (EEG) has a long history in clinical neurology, cognitive neuroscience, and functional neurosurgery, but has limited prior usage in psychiatric surgery. MEDLINE, Embase, and Psyc-INFO searches on the use of EEG in guiding psychiatric surgery yielded 611 articles, which were screened for relevance and quality. We synthesized three important themes. First, considerable evidence supports EEG as a biomarker for response to various surgical and non-surgical therapies, but large-scale investigations are lacking. Second, intraoperative EEG is likely more valuable than surface EEG for guiding target selection, but comes at the cost of greater invasiveness. Finally, EEG may be a promising tool for objective functional feedback in developing "closed-loop" psychosurgeries, but more systematic investigations are required.

Chronic Fluoxetine Treatment Induces Maturation-Compatible Changes in the Dendritic Arbor and in Synaptic Responses in the Auditory Cortex

Fluoxetine is a selective serotonin reuptake inhibitor (SSRI) used to treat mood and anxiety disorders. Chronic treatment with this antidepressant drug is thought to favor functional recovery by promoting structural and molecular changes in several forebrain areas. At the synaptic level, chronic fluoxetine induces an increased size and density of dendritic spines and an increased ratio of GluN2A over GluN2B N-methyl-D-aspartate (NMDA) receptor subunits. The "maturation"-promoting molecular changes observed after chronic fluoxetine should also induce structural remodeling of the neuronal dendritic arbor and changes in the synaptic responses. We treated adult rats with fluoxetine (0.7 mg/kg i.p. for 28 days) and performed a morphometric analysis using Golgi stain in limbic and nonlimbic cortical areas. Then, we focused especially on the auditory cortex, where we evaluated the dendritic morphology of pyramidal neurons using a 3-dimensional reconstruction of neurons expressing mRFP after in utero electroporation. With both methodologies, a shortening and decreased complexity of the dendritic arbors was observed, which is compatible with an increased GluN2A over GluN2B ratio. Recordings of extracellular excitatory postsynaptic potentials in the auditory cortex revealed an increased synaptic response after fluoxetine and were consistent with an enrichment of GluN2A-containing NMDA receptors. Our results confirm that fluoxetine favors maturation and refinement of extensive cortical networks, including the auditory cortex. The fluoxetine-induced receptor switch may decrease GluN2B-dependent toxicity and thus could be applied in the future to treat neurodegenerative brain disorders characterized by glutamate toxicity and/or by an aberrant network connectivity.

Understanding and Predicting Antidepressant Response: Using Animal Models to Move Toward Precision Psychiatry

There are two important gaps of knowledge in depression treatment, namely the lack of biomarkers predicting response to antidepressants and the limited knowledge of the molecular mechanisms underlying clinical improvement. However, individually tailored treatment strategies and individualized prescription are greatly needed given the huge socio-economic burden of depression, the latency until clinical improvement can be observed and the response variability to a particular compound. Still, individual patient-level antidepressant treatment outcomes are highly unpredictable. In contrast to other therapeutic areas and despite tremendous efforts during the past years, the genomics era so far has failed to provide biological or genetic predictors of clinical utility for routine use in depression treatment. Specifically, we suggest to (1) shift the focus from the group patterns to individual outcomes, (2) use dimensional classifications such as Research Domain Criteria, and (3) envision better planning and improved connections between pre-clinical and clinical studies within translational research units. In contrast to studies in patients, animal models enable both searches for peripheral biosignatures predicting treatment response and in depth-analyses of the neurobiological pathways shaping individual antidepressant response in the brain. While there is a considerable number of animal models available aiming at mimicking disease-like conditions such as those seen in depressive disorder, only a limited number of preclinical or truly translational investigations is dedicated to the issue of heterogeneity seen in response to antidepressant treatment. In this mini-review, we provide an overview on the current state of knowledge and propose a framework for successful translational studies into antidepressant treatment response.

The potential of predictive analytics to provide clinical decision support in depression treatment planning

PURPOSE OF REVIEW

To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD).

RECENT FINDINGS

Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem.

SUMMARY

Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.