Biomarker approaches in major depressive disorder evaluated in the context of current hypotheses

A longitudinal study of the mediator role of physical activity in the bidirectional relationships of cognitive function and specific dimensions of depressive symptoms

BACKGROUND

The bidirectional relationship between cognitive function and depressive symptoms has been extensively reported. However, the potential mechanisms are still not clear. We aim to longitudinally investigate whether physical activity mediates the bidirectional relationships between cognitive function and specific dimensions of depressive symptoms.

METHODS

Data from 6,787 individuals aged ≥50 of 2014/15 (T1), 2016/17 (T2), and 2018/19 (T3) waves of the English Longitudinal Study of Ageing (ELSA). Cognitive function was assessed by domains of memory, orientation in time, and executive function. Physical activity was measured with the intensity and frequency of participation. Specific dimensions of depressive symptoms were assessed by the 8-item Center for Epidemiologic Studies Depression Scale, distinguishing between cognitive-affective and somatic symptoms. Cross-lagged panel models were used to investigate the mediating role of physical activity in the bidirectional relationships between cognitive function and two dimensions of depressive symptoms.

RESULTS

Poorer cognitive function was indirectly associated with worse cognitive-affective symptoms (indirect effect = -0.002, 95%CI: -0.004, -0.001) through lower physical activity levels. Poorer cognitive function was also indirectly associated with worse somatic symptoms (indirect effect = -0.003, 95%CI: -0.006, -0.002) through lower physical activity levels, and the reverse mediation was observed as well (indirect effect = -0.002, 95%CI: -0.004, -0.001).

LIMITATIONS

There is no distinction between potential within-person and between-person effects.

CONCLUSIONS

Collaborative interventions of physical activity are beneficial in protecting cognitive function and mental health in older adults.

Tissue-specific gene expression of genome-wide significant loci associated with major depressive disorder subtypes

Major depressive disorder (MDD) is a clinically and genetically heterogeneous disorder. To reduce heterogeneity, large-scale genome-wide association studies have recently identified genome-wide significant loci associated with seven MDD subtypes. However, it was unclear in which tissues the genes near those loci are specifically expressed. We investigated whether genes related to specific MDD subtypes would be preferably expressed in a specific tissue. At 14 novel subtype-specific loci related to seven MDD subtypes-(1) non-atypical-like features MDD, (2) early-onset MDD, (3) recurrent MDD, (4) MDD with suicidal thoughts, (5) MDD without suicidal thoughts, (6) MDD with moderate impairment, and (7) postpartum depression, we investigated whether 22 genome-wide significant genetic variant-mapped genes were tissue-specifically expressed in brain, female reproductive, male specific, cardiovascular, gastrointestinal, or urinary tissues in the Genotype-Tissue Expression (GTEx) subjects (n ≤ 948). To confirm the tissue-specific expression in the GTEx, we used independent Human Protein Atlas (HPA) RNA-seq subjects (n ≤ 95). Of 22 genes, nine and five genes were tissue-specifically expressed in brain and female reproductive tissues, respectively (p < 2.27 × 10-3). RTN1, ERBB4, and AMIGO1 related to early-onset MDD, recurrent MDD, or MDD with suicidal thoughts were highly expressed in brain tissues (d = 1.19-2.71), while OAS1, LRRC9, DHRS7, PSMA5, SYPL2, and GULP1 related to non-atypical-like features MDD, early-onset MDD, MDD with suicidal thoughts, or postpartum depression were expressed at low levels in brain tissues (d = -0.17--1.48). DFNA5, CTBP2, PCNX4, SDCCAG8, and GULP1, which are related to early-onset MDD, MDD with moderate impairment, or postpartum depression, were highly expressed in female reproductive tissues (d = 0.80-2.08). Brain and female reproductive tissue-specific expression was confirmed in the HPA RNA-seq subjects. Our findings suggest that brain and female reproductive tissue-specific expression might contribute to the pathogenesis of MDD subtypes.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

Assessment of biomarker stability and assay performance parameters for medical diagnosis: a case study of diagnosis of major depressive disorder

Aim: Assessing the stability profiles and assay performance of 24 biomarker assays in 32 biomarker/body fluid combinations identified as relevant for prediction of major depressive disorder. Materials & methods: Combinations were tested for stability and assay performance with ELISA at different storage and freeze-thaw conditions in pooled samples of 40 patients. Results: Stability and assay performance issues were found in almost all cases except three biomarkers in urine and three in serum. Conclusion: This study shows that, to produce reliable measurement data, assessments of stability and assay performance are essential. In development, other quality assurance parameters might be implemented to increase the level of measurement reliability by increasing assay performance control.

Neuropsychological Effects of Antidepressants: Translational Studies

Pharmacological treatments that improve mood were first identified serendipitously, but more than half a century later, how these drugs induce their antidepressant effects remains largely unknown. With the help of animal models, a detailed understanding of their pharmacological targets and acute and chronic effects on brain chemistry and neuronal function has been achieved, but it remains to be elucidated how these effects translate to clinical efficacy. Whilst the field has been dominated by the monoamine and neurotrophic hypotheses, the idea that the maladaptive cognitive process plays a critical role in the development and perpetuation of mood disorders has been discussed since the 1950s. Recently, studies using objective methods to quantify changes in emotional processing found acute effects with conventional antidepressants in both healthy volunteers and patients. These positive effects on emotional processing and cognition occur without a change in the subjective ratings of mood. Building from these studies, behavioural methods for animals that quantify similar cognitive affective processes have been developed. Integrating these behavioural approaches with pharmacology and targeted brain manipulations, a picture is beginning to emerge of the underlying mechanisms that may link the pharmacology of antidepressants, these neuropsychological constructs and clinical efficacy. In this chapter, we discuss findings from animal studies, experimental medicine and patients investigating the neuropsychological effects of antidepressant drugs. We discuss the possible neural circuits that contribute to these effects and discuss whether a neuropsychological model of antidepressant effects could explain the temporal differences in clinical benefits observed with conventional delayed-onset antidepressants versus rapid-acting antidepressants.

Effects of Anxious Depression on Antidepressant Treatment Response

Anxious depression represents a subtype of major depressive disorder and is associated with increased suicidality, severity, chronicity and lower treatment response. Only a few studies have investigated the differences between anxious depressed (aMDD) and non-anxious depressed (naMDD) patients regarding treatment dosage, serum-concentration and drug-specific treatment response. In our naturalistic and prospective study, we investigated whether the effectiveness of therapy including antidepressants (SSRI, SNRI, NaSSA, tricyclics and combinations) in aMDD patients differs significantly from that in naMDD patients. In a sample of 346 patients, we calculated the anxiety somatization factor (ASF) and defined treatment response as a reduction (≥50%) in the Hamilton Depression Rating Scale (HDRS)-21 score after 7 weeks of pharmacological treatment. We did not observe an association between therapy response and the baseline ASF-scores, or differences in therapy outcomes between aMDD and naMDD patients. However, non-responders had higher ASF-scores, and at week 7 aMDD patients displayed a worse therapy outcome than naMDD patients. In subgroup analyses for different antidepressant drugs, venlafaxine-treated aMDD patients showed a significantly worse outcome at week 7. Future prospective, randomized-controlled studies should address the question of a worse therapy outcome in aMDD patients for different psychopharmaceuticals individually.

Altered IL-3 and lipocalin-2 levels are associated with the pathophysiology of major depressive disorder: a case-control study

BACKGROUND

Major Depressive Disorder (MDD) is a common mental ailment and is the primary reason for disability. It manifests a severe impact on moods, thoughts, and physical health. At present, this disorder has become a concern in the field of public health. Alteration of neurochemicals is thought to be involved in the pathogenesis of many psychiatric disorders. Therefore, we aimed to evaluate serum IL-3 and lipocalin-2 in MDD patients and healthy controls (HCs).

METHOD

We included a total of 376 participants in this study. Among them, 196 were MDD patients, and 180 were age-sex-matched HCs. MDD patients were recruited from the Psychiatry Department of Bangabandhu Sheikh Mujib Medical University (BSMMU), but the controls were from different parts of Dhaka. All study participants were evaluated by a psychiatrist using the DSM-5 criteria. To assess the severity of the depression, we used the Hamilton depression (Ham-D) rating scale. Serum IL-3 and lipocalin-2 levels were measured using commercially available enzyme-linked immune-sorbent assay kits (ELISA kits).

RESULTS

According to this study, we observed elevated serum levels of IL-3 (1,024.73 ± 29.84 pg/mL) and reduced levels of serum lipocalin-2 (29.019 ± 2.073 ng/mL) in MDD patients compared to HCs (911.11 ± 20.55 pg/mL and 48.065 ± 3.583 ng/mL, respectively). No associations between serum levels of IL-3 and lipocalin-2 and depression severity were observed in patients.

CONCLUSIONS

According to the present findings, alterations of serum IL-3 and lipocalin might be associated with the pathogenesis of MDD. These results support that altered serum neurochemicals can serve as early risk assessment markers for depression. Further interventional studies are recommended for a better understanding of the role of IL-3 and lipocalin-2 in the pathophysiology of depression.

Polyunsaturated fatty acids changes during electroconvulsive therapy in major depressive disorder

Polyunsaturated fatty acids (PUFAs) have important electrochemical properties and have been implicated in the pathophysiology of major depressive disorder (MDD) and its treatment. However, the relation of PUFAs with electroconvulsive therapy (ECT) has never been investigated. Therefore, we aimed to explore the associations between PUFA concentrations and response to ECT in patients with MDD. We included 45 patients with unipolar MDD in a multicentre study. To determine PUFA concentrations, we collected blood samples at the first (T0) and twelfth (T12) ECT-session. We assessed depression severity using the Hamilton Rating Scale for Depression (HAM-D) at T0, T12 and at the end of the ECT-course. ECT-response was defined as 'early response' (at T12), 'late response' (after ECT-course) and 'no' response (after the ECT-course). The PUFA chain length index (CLI), unsaturation index (UI) and peroxidation index (PI) and three individual PUFAs (eicosapentaenoic acid [EPA], docosahexaenoic acid [DHA] and nervonic acid [NA]) were associated with response to ECT using linear mixed models. Results showed a significant higher CLI in 'late responders' compared to 'non responders'. For NA, 'late responders' showed significantly higher concentrations compared to 'early'- and 'non responders'. In conclusion, this study provides the first indication that PUFAs are associated with the efficacy of ECT. This indicates that PUFAs' influence on neuronal electrochemical properties and neurogenesis may affect ECT outcomes. Thereby, PUFAs form a potentially modifiable factor predicting ECT outcomes, that warrants further investigation in other ECT-cohorts.

DNA Methylation of POMC and NR3C1-1F and Its Implication in Major Depressive Disorder and Electroconvulsive Therapy

INTRODUCTION

Precision medicine in psychiatry is still in its infancy. To establish patient-tailored treatment, adequate indicators predicting treatment response are required. Electroconvulsive therapy (ECT) is considered one of the most effective options for pharmacoresistant major depressive disorder (MDD), yet remission rates were reported to be below 50%.

METHODS

Since epigenetics of the stress response system seem to play a role in MDD, we analyzed the DNA methylation (DNAm) of genes encoding the glucocorticoid receptor (NR3C1) and proopiomelanocortin (POMC) through Sanger Sequencing. For analysis, blood was taken before and after the first and last ECT from MDD patients (n=31), unmedicated depressed controls (UDC; n=19, baseline), and healthy controls (HC; n=20, baseline).

RESULTS

Baseline DNAm in NR3C1 was significantly lower in UDCs compared to both other groups (UDC: 0.014(±0.002), ECT: 0.031(±0.001), HC: 0.024(±0.002); p<0.001), whereas regarding POMC, ECT patients had the highest DNAm levels (ECT: 0.252(±0.013), UDC: 0.156(±0.015), HC: 0.162(±0.014); p<0.001). NR3C1m and POMCm decreased after the first ECT (NR3C1: p<0.001; POMC: p=0.001), and responders were less methylated compared to non-responders in NR3C1(p<0.001).

DISCUSSION

Our findings indicate that both genes might play a role in the chronification of depression and NR3C1 may be relevant for ECT response prediction.

Excess body weight and specific types of depressive symptoms: Is there a mediating role of systemic low-grade inflammation?

OBJECTIVES

Obesity is associated with an increased risk of depression. Systemic low-grade inflammation, a plausible consequence of obesity, has also been linked to depression. However, the potential mediating effects of systemic low-grade inflammation on the association between excess body weight and specific symptom domains of depression remain uncertain. This study examined whether systemic low-grade inflammation mediated the associations of excess body weight (overweight and obesity) with subsequent overall, cognitive-affective, and somatic depressive symptoms.

DESIGN

This study used a prospective cohort design.

METHODS

The final analytical sample included 4,942 adults aged ≥50 years drawn from the English Longitudinal Study of Ageing (ELSA). Body mass index (BMI) and covariates were ascertained at baseline (wave 4, 2008/09). Continuous BMI scores were divided into four categories: 'normal weight' (18.5 ≤ BMI <25 kg/m2); 'overweight' (25 ≤ BMI <30 kg/m2); 'obesity' (BMI ≥30 kg/m2); in addition to 'excess body weight' ('overweight' and 'obesity' combined). Covariates included sociodemographic variables, behavioural factors, and chronic physical conditions. Serum concentrations of CRP were measured at wave 6 (2012/13). Depressive symptoms were assessed at baseline and ten years later (wave 9, 2018/19), using the 8-item Centre for Epidemiological Studies Depression (CES-D) Scale. Two symptom domains were constructed, distinguishing between cognitive-affective (depressed mood, loneliness, sadness, enjoyment in life, and happiness) and somatic (sleep problems, low energy levels, and fatigue) symptoms. Mediation analyses were performed to examine whether CRP statistically mediated the associations between BMI categories and depressive symptoms.

RESULTS

In multivariable-adjusted analyses, excess body weight was associated with elevated somatic (OR = 1.231, 95% CI: 1.029, 1.473), but not cognitive-affective or overall depressive symptoms at follow-up. Higher CRP was associated with elevated somatic (OR = 1.156, 95% CI: 1.061, 1.259), but not cognitive-affective or overall depressive symptoms. CRP acted as a partial mediator (14.92%) of the association between excess body weight and elevated somatic, but not cognitive-affective, or overall depressive symptoms.

CONCLUSION

Systemic low-grade inflammation may partially explain the association of excess body weight with somatic depressive symptoms, but not the associations with cognitive-affective or overall depressive symptoms.

Is depression the missing link between inflammatory mediators and cancer?

Patients with cancer are at greater risk of developing depression in comparison to the general population and this is associated with serious adverse effects, such as poorer quality of life, worse prognosis and higher mortality. Although the relationship between depression and cancer is now well established, a common underlying pathophysiological mechanism between the two conditions is yet to be elucidated. Existing theories of depression, based on monoamine neurotransmitter system dysfunction, are insufficient as explanations of the disorder. Recent advances have implicated neuroinflammatory mechanisms in the etiology of depression and it has been demonstrated that inflammation at a peripheral level may be mirrored centrally in astrocytes and microglia serving to promote chronic levels of inflammation in the brain. Three major routes to depression in cancer in which proinflammatory mediators are implicated, seem likely. Activation of the kynurenine pathway involving cytokines, increases tryptophan catabolism, resulting in diminished levels of serotonin which is widely acknowledged as being the hallmark of depression. It also results in neurotoxic effects on brain regions thought to be involved in the evolution of major depression. Proinflammatory mediators also play a crucial role in impairing regulatory glucocorticoid mediated feedback of the hypothalamic-pituitary-adrenal axis, which is activated by stress and considered to be involved in both depression and cancer. The third route is via the glutamatergic pathway, whereby glutamate excitotoxicity may lead to depression associated with cancer. A better understanding of the mechanisms underlying these dysregulated and other newly emerging pathways may provide a rationale for therapeutic targeting, serving to improve the care of cancer patients.

Combined serum IL-6, C-reactive protein, and cortisol may distinguish patients with anhedonia in major depressive disorder

Neuroinflammation and anhedonia in major depressive disorder (MDD) are closely connected, though the exact mechanism is unclear. This study aimed to investigate the relationships between cytokines, C-reactive protein (CRP), cortisol, and anhedonia, revealing the potential predictive value in identifying anhedonic MDD. In total, 66 patients with MDD (29 with anhedonia and 37 without anhedonia) and 66 healthy controls (HCs) were included. The severity of depression and anhedonia was evaluated using the Hamilton Rating Scale for Depression-24 (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS), respectively. Serum cytokines were measured using flow cytofluorometric kits, while CRP and cortisol were measured using enzyme-linked immunosorbent assay kits. We found higher serum levels of interleukin-2 (IL-2), IL-6, and cortisol in MDD than in HC where anhedonic MDD was highest. CRP and IL-6 were positively associated with anhedonia, and cortisol levels were related to both anhedonia and depression. A combination of IL-6, CRP, and cortisol had optimal predictive value for distinguishing anhedonic MDD. Anhedonic MDD has unique neuroendocrine-immune characteristics compared with those without anhedonia. The combination of IL-6, CRP, and cortisol might be an early marker to distinguish anhedonic MDD.

A game changer for bipolar disorder diagnosis using RNA editing-based biomarkers

In clinical practice, differentiating Bipolar Disorder (BD) from unipolar depression is a challenge due to the depressive symptoms, which are the core presentations of both disorders. This misdiagnosis during depressive episodes results in a delay in proper treatment and a poor management of their condition. In a first step, using A-to-I RNA editome analysis, we discovered 646 variants (366 genes) differentially edited between depressed patients and healthy volunteers in a discovery cohort of 57 participants. After using stringent criteria and biological pathway analysis, candidate biomarkers from 8 genes were singled out and tested in a validation cohort of 410 participants. Combining the selected biomarkers with a machine learning approach achieved to discriminate depressed patients (n = 267) versus controls (n = 143) with an AUC of 0.930 (CI 95% [0.879-0.982]), a sensitivity of 84.0% and a specificity of 87.1%. In a second step by selecting among the depressed patients those with unipolar depression (n = 160) or BD (n = 95), we identified a combination of 6 biomarkers which allowed a differential diagnosis of bipolar disorder with an AUC of 0.935 and high specificity (Sp = 84.6%) and sensitivity (Se = 90.9%). The association of RNA editing variants modifications with depression subtypes and the use of artificial intelligence allowed developing a new tool to identify, among depressed patients, those suffering from BD. This test will help to reduce the misdiagnosis delay of bipolar patients, leading to an earlier implementation of a proper treatment.

Role of Brain Imaging in Drug Development for Psychiatry

Background:

Over the last decades, many brain imaging studies have contributed to new insights in the pathogenesis of psychiatric disease. However, in spite of these developments, progress in the development of novel therapeutic drugs for prevalent psychiatric health conditions has been limited.

Objective:

In this review, we discuss translational, diagnostic and methodological issues that have hampered drug development in CNS disorders with a particular focus on psychiatry. The role of preclinical models is critically reviewed and opportunities for brain imaging in early stages of drug development using PET and fMRI are discussed. The role of PET and fMRI in drug development is reviewed emphasizing the need to engage in collaborations between industry, academia and phase I units.

Conclusion:

Brain imaging technology has revolutionized the study of psychiatric illnesses, and during the last decade, neuroimaging has provided valuable insights at different levels of analysis and brain organization, such as effective connectivity (anatomical), functional connectivity patterns and neurochemical information that may support both preclinical and clinical drug development. Since there is no unifying pathophysiological theory of individual psychiatric syndromes and since many symptoms cut across diagnostic boundaries, a new theoretical framework has been proposed that may help in defining new targets for treatment and thus enhance drug development in CNS diseases. In addition, it is argued that new proposals for data-mining and mathematical modelling as well as freely available databanks for neural network and neurochemical models of rodents combined with revised psychiatric classification will lead to new validated targets for drug development.

The associations of CNR1 SNPs and haplotypes with vulnerability and treatment response phenotypes in Han Chinese with major depressive disorder: A case-control association study

BACKGROUND

Understanding how genetic polymorphisms are associated with the pathophysiology of major depressive disorder (MDD) may aid in diagnosis and the development of personalized treatment strategies. CNR1 is the gene coding Cannabinoid type 1 receptor which is highly involved in emotional processing and in regulating neurotransmitter releases. We aimed to investigate the associations of CNR1 single-nucleotide polymorphisms (SNPs) with MDD susceptibility and treatment response.

METHODS

The study reported data on 181 Han Chinese with MDD and 80 healthy controls. The associations of CNR1 genetic polymorphisms with MDD susceptibility and treatment response were examined, wherein the MDD patients were subgrouped further by responding to antidepressant treatment, compared with healthy controls separately.

RESULTS

The CNR1 SNPs rs806367 and rs6454674 and haplotype C-T-T-C of rs806366, rs806367, rs806368, and rs806370 were associated with increased susceptibility for MDD and antidepressant treatment resistance, but the association was not detected in other SNPs or the haplotype block of rs806368 and rs806370.

CONCLUSION

The CNR1 is a promising candidate for the genetic association study of MDD. Larger and well-characterized samples are required to confirm the genetic association of CNR1 with MDD because of the limitations such as relatively small sample size and lack of information for correcting confounding factors.

Affect fluctuations examined with ecological momentary assessment in patients with current or remitted depression and anxiety disorders

BACKGROUND

There is increasing interest in day-to-day affect fluctuations of patients with depressive and anxiety disorders. Few studies have compared repeated assessments of positive affect (PA) and negative affect (NA) across diagnostic groups, and fluctuation patterns were not uniformly defined. The aim of this study is to compare affect fluctuations in patients with a current episode of depressive or anxiety disorder, in remitted patients and in controls, using affect instability as a core concept but also describing other measures of variability and adjusting for possible confounders.

METHODS

Ecological momentary assessment (EMA) data were obtained from 365 participants of the Netherlands Study of Depression and Anxiety with current (n = 95), remitted (n = 178) or no (n = 92) DSM-IV defined depression/anxiety disorder. For 2 weeks, five times per day, participants filled-out items on PA and NA. Affect instability was calculated as the root mean square of successive differences (RMSSD). Tests on group differences in RMSSD, within-person variance, and autocorrelation were performed, controlling for mean affect levels.

RESULTS

Current depression/anxiety patients had the highest affect instability in both PA and NA, followed by remitters and then controls. Instability differences between groups remained significant when controlling for mean affect levels, but differences between current and remitted were no longer significant.

CONCLUSIONS

Patients with a current disorder have higher instability of NA and PA than remitted patients and controls. Especially with regard to NA, this could be interpreted as patients with a current disorder being more sensitive to internal and external stressors and having suboptimal affect regulation.

Retinal structural changes in mood disorders: The optical coherence tomography to better understand physiopathology?

BACKGROUND

Mood disorders are particularly common, disabling conditions. Diagnosis can be difficult as it may involve different pathophysiological assumptions. This could explain why such disorders are resistant to treatment. The retina is part of the central nervous system and shares a common embryonic origin with the brain. Optical coherence tomography (OCT) is an imaging technique for analysing the different layers of the retina. We reviewed studies that examined the retina with OCT in mood disorders.

METHODS

We conducted Pubmed search and additional manual research based on the bibliography in each of selected articles. We found and analysed 11 articles relevant to our subject.

RESULTS

This literature review confirms that it is possible to use OCT to detect neurodegeneration and neuroinflammation in mood disorders. Their impact is thought to depend on the duration and severity of the disease, and whether it is in acute or chronic stage. The differences seen in studies dealing with depression and those looking at bipolar disorder may reflect the particular characteristics of each disorder. A number of OCT parameters can be proposed as biomarkers of active or chronic inflammation and neurodegeneration. Markers of predisposition to an at-risk mental state are also suggested.

LIMITATIONS

The main limitation is selection bias, studies including more varied population would help to confirm and precise these results.

CONCLUSION

OCT is thus a particularly promising tool for evaluating some of the etiopathogenetic mechanisms involved in mood disorders. The combination with other approaches could help to find more specific biomarkers.

Brain-derived neurotrophic factor (BDNF) and inflammatory markers: Perspectives for the management of depression

BACKGROUND

Mood disorders, including major depressive disorder, are among the main causes of disability and early mortality and constitute an important public health problem. Despite the search for a neurobiological explanation for these disorders, diagnosis and treatment are still based on subjective symptoms and psychometric assessments. Biomarkers, used as indicators of normal biological and pathological processes or pharmacological responses to a clinical intervention, may be useful in improving the current classification of psychiatric disorders, which can help understand the role of biological information in diagnosis, prognosis, and assessment of responses to intervention.

OBJECTIVES

This review aims to analyze the existing literature on Brain-Derived Neurotrophic Factor (BDNF) and inflammatory markers related to depression and to assess the advances and perspectives of their applicability in the diagnosis, prognosis, and assessment of responses to intervention in order to understand the importance of these biomarkers for the management of depression.

RESULTS

Evidence shows that BDNF is an important biomarker for the pathogenesis of depression; reduced levels are linked to reduced synaptic plasticity and neuronal atrophy, while elevated levels are associated with survival and neuronal differentiation, which is compatible with the neurogenic hypothesis of depression. Although the use of this biomarker is not yet established, literature shows that the concentration of BDNF is a useful measure for the differentiation between healthy and depressed individuals. Based on the inflammatory theory of depression, studies have found higher levels of inflammation in depressed individuals when compared to healthy ones, as well as an association between chronic inflammation and depressive symptoms. Studies have also found anti-inflammatory agents with anti-depressant effects. Markers such as IL-6, IL-1β, TNFα, and C-reactive protein (CRP) are potential markers of depression, but the role of cytokines in human brain activity is still insufficiently established.

CONCLUSIONS

Despite the large number of potential biological markers not yet fully established in the pathophysiology of depression, which is a challenge for psychobiology, it is clear that the concentrations of these substances are altered in psychiatric diagnoses related to the disease activity. Thus, although more research is needed, the current body of knowledge on biomarkers allows us to predict their use in the management of depression.

Melatonin and Depression: A Translational Perspective From Animal Models to Clinical Studies

Daily rhythm of melatonin synchronizes the body to the light/dark environmental cycle. Several hypotheses have been raised to understand the intersections between melatonin and depression, in which changes in rest-activity and sleep patterns are prominent. This review describes key experimental and clinical evidence that link melatonin with the etiopathology and symptomatology of depressive states, its role in the follow up of therapeutic response to antidepressants, as well as the clinical evidence of melatonin as MDD treatment. Melatonin, as an internal temporal cue contributing to circadian organization and best studied in the context of circadian misalignment, is also implicated in neuroplasticity. The monoaminergic systems that underly MDD and melatonin production overlap. In addition, the urinary metabolite 6-sulfatoxymelatonin (aMT6) has been proposed as biomarker for antidepressant responders, by revealing whether the blockage of noradrenaline uptake has taken place within 24 h from the first antidepressant dose. Even though animal models show benefits from melatonin supplementation on depressive-like behavior, clinical evidence is inconsistent vis-à-vis prophylactic or therapeutic benefits of melatonin or melatonin agonists in depression. We argue that the study of melatonin in MDD or other psychiatric disorders must take into account the specificities of melatonin as an integrating molecule, inextricably linked to entrainment, metabolism, immunity, neurotransmission, and cell homeostasis.

Label-Free Liquid Chromatography-Mass Spectrometry Proteomic Analysis of the Urinary Proteome for Measuring the Escitalopram Treatment Response From Major Depressive Disorder

Major depressive disorder (MDD) is a common mental disorder that can cause substantial impairments in quality of life. Clinical treatment is usually built on a trial-and-error method, which lasts ~12 weeks to evaluate whether the treatment is efficient, thereby leading to some inefficient treatment measures. Therefore, we intended to identify early candidate urine biomarkers to predict efficient treatment response in MDD patients. In this study, urine samples were collected twice from 19 respondent and 10 non-respondent MDD patients receiving 0-, 2-, and 12-week treatments with escitalopram. Differential urinary proteins were subsequently analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Our two pilot tests suggested that the urine proteome reflects changes associated with major depressive disorder at the early stage of treatment measures. On week 2, 20 differential proteins were identified in the response group compared with week 0, with 14 of these proteins being associated with the mechanisms of MDD. In the non-response group, 60 differential proteins were identified at week 2, with 28 of these proteins being associated with the mechanisms of MDD. In addition, differential urinary proteins at week 2 between the response and non-response groups can be clearly distinguished by using orthogonal projection on latent structure-discriminant analysis (OPLS-DA). Our small pilot tests indicated that the urine proteome can reflect early effects of escitalopram therapy between the response and non-response groups since at week 2, which may provide potential early candidate urine biomarkers to predict efficient treatment measures in MDD patients.

Novel candidate genes for ECT response prediction-a pilot study analyzing the DNA methylome of depressed patients receiving electroconvulsive therapy

Background

Major depressive disorder (MDD) represents a serious global health concern. The urge for efficient MDD treatment strategies is presently hindered by the incomplete knowledge of its underlying pathomechanism. Despite recent progress (highlighting both genetics and the environment, and thus DNA methylation, to be relevant for its development), 30–50% of MDD patients still fail to reach remission with standard treatment approaches. Electroconvulsive therapy (ECT) is one of the most powerful options for the treatment of pharmacoresistant depression; nevertheless, ECT remission rates barely reach 50% in large-scale naturalistic population-based studies. To optimize MDD treatment strategies and enable personalized medicine in the long- term, prospective indicators of ECT response are thus in great need. Because recent target-driven analyses revealed DNA methylation baseline differences between ECT responder groups, we analyzed the DNA methylome of depressed ECT patients using next-generation sequencing. In this pilot study, we did not only aim to find novel targets for ECT response prediction but also to get a deeper insight into its possible mechanism of action.

Results

Longitudinal DNA methylation analysis of peripheral blood mononuclear cells isolated from a cohort of treatment-resistant MDD patients (n = 12; time points: before and after 1st and last ECT, respectively) using a TruSeq-Methyl Capture EPIC Kit for library preparation, led to the following results: (1) The global DNA methylation differed neither between the four measured time points nor between ECT responders (n = 8) and non-responders (n = 4). (2) Analyzing the DNA methylation variance for every probe (=1476812 single CpG sites) revealed eight novel candidate genes to be implicated in ECT response (protein-coding genes: RNF175, RNF213, TBC1D14, TMC5, WSCD1; genes encoding for putative long non-coding RNA transcripts: AC018685.2, AC098617.1, CLCN3P1). (3) In addition, DNA methylation of two CpG sites (located within AQP10 and TRERF1) was found to change during the treatment course.

Conclusions

We suggest ten novel candidate genes to be implicated in either ECT response or its possible mechanism. Because of the small sample size of our pilot study, our findings must be regarded as preliminary.

Gender Differences in Developing Biomarker-Based Major Depressive Disorder Diagnostics

The identification of biomarkers associated with major depressive disorder (MDD) holds great promise to develop an objective laboratory test. However, current biomarkers lack discriminative power due to the complex biological background, and not much is known about the influence of potential modifiers such as gender. We first performed a cross-sectional study on the discriminative power of biomarkers for MDD by investigating gender differences in biomarker levels. Out of 28 biomarkers, 21 biomarkers were significantly different between genders. Second, a novel statistical approach was applied to investigate the effect of gender on MDD disease classification using a panel of biomarkers. Eleven biomarkers were identified in men and eight in women, three of which were active in both genders. Gender stratification caused a (non-significant) increase of Area Under Curve (AUC) for men (AUC = 0.806) and women (AUC = 0.807) compared to non-stratification (AUC = 0.739). In conclusion, we have shown that there are differences in biomarker levels between men and women which may impact accurate disease classification of MDD when gender is not taken into account.

Entropy analysis of heart rate variability and its application to recognize major depressive disorder: A pilot study

BACKGROUND

The current method to evaluate major depressive disorder (MDD) relies on subjective clinical interviews and self-questionnaires.

OBJECTIVE

Autonomic imbalance in MDD patients is characterized using entropy measures of heart rate variability (HRV). A machine learning approach for screening depression based on the entropy is demonstrated.

METHODS

The participants experience five experimental phases: baseline (BASE), stress task (MAT), stress task recovery (REC1), relaxation task (RLX), and relaxation task recovery (REC2). The four entropy indices, approximate entropy, sample entropy, fuzzy entropy, and Shannon entropy, are extracted for each phase, and a total of 20 features are used. A support vector machine classifier and recursive feature elimination are employed for classification.

RESULTS

The entropy features are lower in the MDD group; however, the disease does not have a significant effect. Experimental tasks significantly affect the features. The entropy did not recover during REC1. The differences in the entropy features between the two groups increased after MAT and showed the largest gap in REC2. We achieved 70% accuracy, 64% sensitivity, and 76% specificity with three optimal features during RLX and REC2.

CONCLUSION

Monitoring of HRV complexity changes when a subject experiences autonomic arousal and recovery can potentially facilitate objective depression recognition.

Toward a New Model of Understanding, Preventing, and Treating Adolescent Depression Focusing on Exhaustion and Stress

OBJECTIVE

Adolescent depression is a heterogeneous disorder, with a wide variety of symptoms and inconsistent treatment response, and is not completely understood. A dysregulated stress system is a consistent finding, however, and exhaustion is a consistent trait in adolescent patients. The aim of this paper is to critically assess current hypotheses in adolescent depression research and reframe causes and treatment approaches.

METHODS

A mixed-method approach involved a review based on publications from PubMed, Embase and PsycInfo, and two exemplary adolescent cases.

RESULTS

Both cases show a spiral of stress and exhaustion, but with a different profile of symptoms and coping mechanisms. Reframing both cases from the perspective of coping behavior, searching for the sources of experienced stress and exhaustion, showed coping similarities. This proved essential in the successful personalized treatment and recovery process. In combination with recent evidence, both cases support the functional reframing of depression as the outcome of a stress- and exhaustion-related spiralling mechanism.

CONCLUSIONS

We propose to open up a symptom-based, mood-centered view to a model in which adolescent depression is framed as a consecutive failure of stress coping mechanisms and chronic exhaustion. Addressing exhaustion and coping primarily as a treatment strategy in adolescents and young adults might work in synergy with existing treatments and improve overall outcomes. This perspective warrants further investigation.

Weighted Gene Coexpression Network Analysis Identifies Specific Modules and Hub Genes Related to Major Depression

PURPOSE

Despite advances in characterizing the neurobiology of emotional disorders, there is still a significant lack of scientific understanding of the pathophysiological mechanisms governing major depressive disorder (MDD). This study attempted to elucidate the molecular circuitry of MDD and to identify more potential genes associated with the pathogenesis of the disease.

PATIENTS AND METHODS

Microarray data from the GSE98793 dataset were downloaded from the NCBI Gene Expression Omnibus (GEO) database, including 128 patients with MDD and 64 healthy controls. Weighted gene coexpression network analysis (WGCNA) was performed to find modules of differentially expressed genes (DEGs) with high correlations followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to obtain further biological insight into the top three key modules. The protein-protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed, as well.

RESULTS

We filtered 3276 genes that were considered significant DEGs for further WGCNA analysis. By performing WGCNA, we found that the turquoise, blue and brown functional modules were all strongly correlated with MDD development, including immune response, neutrophil degranulation, ribosome biogenesis, T cell activation, glycosaminoglycan biosynthetic process, and protein serine/threonine kinase activator activity. Hub genes were identified in the key functional modules that might have a role in the progression of MDD. Functional annotation showed that these modules primarily enriched such KEGG pathways as the TNF signaling pathway, T cell receptor signaling pathway, primary immunodeficiency, Th1, Th2 and Th17 cell differentiation, autophagy and RNA degradation and oxidative phosphorylation. These results suggest that these genes are closely related to autophagy and cellular immune function.

CONCLUSION

The results of this study may help to elucidate the pathophysiology of MDD development at the molecular level and explore the potential molecular mechanisms for new interventional strategies.

Association Between BDNF Gene Variant Rs6265 and the Severity of Depression in Antidepressant Treatment-Free Depressed Patients

BACKGROUND

Brain-derived neurotrophic factor (BDNF) plays an important role in neuronal plasticity, and its dysregulation has been associated with the pathogenesis of mood and anxiety disorders. Prolactin (PRL) is a pituitary hormone which is also produced as a cytokine by immune cells and could be a neurotrophic factor regulating the functional activity of stress-related mechanisms.

AIM

To investigate the possible relationship between depressive state and BDNF and PRL genotypes or levels with special reference to severity of depression.

METHODS

Participants of 18-70 years with a clinical diagnosis of depressive disorder of at least moderate severity were included. These patients had not been treated with antidepressant drugs before admission to hospital during the preceding period of the last 6 months, and 54.5% had never been treated with antidepressant drugs during their entire life. The DNA was genotyped for rs1341239 within the prolactin and for rs6265, rs7124442, and rs11030104 within the BDNF gene. Rs11030104 violated the Hardy-Weinberg equilibrium distribution and was excluded from further analyses. BDNF and prolactin concentration was measured in serum by MAGPIX multiplex analyzer (Luminex, USA) using MILLIPLEX^® MAP kit (Merck, Germany). Genetic associations were determined by sequentially regressing prolactin, BDNF, 17-items Hamilton's Depression (HAMD-17) and Clinical Global Impression scale, Severity (CGI-S) ratings, and depression (absent/present) on the available SNPs. Genetic associations were evaluated assuming an additive model.

RESULTS

A total of 186 depressed patients (of which 169 were women) and 94 healthy controls (67 women) were genotyped. After excluding subjects without genetic information on all three study SNPs, 217 remained of whom 138 suffered from depression. Within depressed patients we observed an association of rs6265 with HAMD-17: mean difference (MD) 2.33 (95%CI 0.49; 4.16; p = 0.014) and CGI-S: MD 0.38 (95%CI 0.09; 0.66; p = 0.011). No significant association was observed between the prolactin SNP rs1341239 and prolactin levels. Similarly the mean differences of BDNF SNPs did not show an association with BDNF: rs6265 -0.042 ln(pg/ml) (95%CI -0.198; 0.113), and rs7124442 0.006 ln(pg/ml) (95%CI -0.117; 0.130). No other association reached statistical significance.

CONCLUSION

We observed a significant association between BDNF gene variant rs6265 and the severity of depression in newly admitted, antidepressant treatment-free, depressed patients. Actual PRL and BDNF levels were not elevated sufficiently in depressed patients to reach statistical significance and were not associated with the studied genotypes.

Persistent depressive symptoms, HPA-axis hyperactivity, and inflammation: the role of cognitive-affective and somatic symptoms

Hypothalamic-pituitary-adrenal (HPA)-axis hyperactivity and inflammation are thought to be prominent in the aetiology of depression. Although meta-analyses have confirmed this relationship, there is considerable variability in the effect sizes across studies. This could be attributed to a differential role of such biological systems in somatic versus cognitive-affective depressive symptoms which remains largely unexplored. Furthermore, most longitudinal research to date has focused on transient rather than persistent depressive symptoms. In the current study, we investigated the associations of hair cortisol and plasma C-reactive protein (CRP) with the longitudinal persistence and dimensions (cognitive-affective versus somatic) of depressive symptoms over a 14-year period using Trait-State-Occasion (TSO) structural equation modelling. The data came from a large sample of older adults from the English Longitudinal Study of Ageing. Depressive symptoms were assessed from wave 1 (2002-03) to wave 8 (2016-17). Hair cortisol (N = 4761) and plasma CRP (N = 5784) were measured in wave 6 (2012-13). Covariates included demographic, socioeconomic, lifestyle, chronic disease, and medication data. Our results revealed that higher cortisol and CRP levels were significantly associated with persistent depressive symptoms across the study period. Notably, both biomarkers exhibited stronger relationships with somatic than with cognitive-affective symptoms. The associations with somatic symptoms were also independent of relevant confounding factors. In contrast, their associations with cognitive-affective symptoms were weak after adjustment for all covariates. These distinct associations reveal the importance of considering symptom-specific effects in future studies on pathophysiological mechanisms. Ultimately, this will have the potential to advance the search for biomarkers of depression and facilitate more targeted treatments.

Investigating the potential role of BDNF and PRL genotypes on antidepressant response in depression patients: A prospective inception cohort study in treatment-free patients

BACKGROUND

Brain-derived neurotrophic factor (BDNF) is associated with response to antidepressant drugs in mood and anxiety disorders. Prolactin (PRL) is a pituitary hormone with behavioural effects, acting as a neurotrophic factor within the brain and may be involved in antidepressant response.

OBJECTIVES

To investigate the relationship between BDNF and PRL genotypes with antidepressant drug response.

METHODS

Prospective inception cohort of 186 Russian treatment-free participants (28 men and 158 women) between 18 and 70 years clinically diagnosed with depressive disorder who initiated antidepressant medication. DNA polymorphisms were genotyped for PRL rs1341239, BDNF rs6265 and rs7124442. Primary outcome was measured by differences in Hamilton Depression Rating Scale (∆HAM-D) scores between baseline/week two, week two/week four, and baseline/week four. Linear regression and independent t-test determined the significance between polymorphisms and ∆HAM-D.

RESULTS

Comparisons between genotypes did not reveal any significant differences in scores during the first two weeks of treatment. In the latter two weeks, BDNF rs7124442 homozygous C patients responded significantly worse in comparison to homozygous T patients during this period. Further analysis within women and in post-menopausal women found a similar comparison between alleles.

LIMITATIONS

Study lasted four weeks, which may be considered short to associate genuine antidepressant effects.

CONCLUSIONS

Patients taking tricylic antidepressants were noted to have a significant improvement in ∆HAM-D compared to patients taking SSRIs. Homozygous C BDNF rs712442 patients were found to respond significantly worse in the last two weeks of treatment.

Oral esketamine for treatment-resistant depression: rationale and design of a randomized controlled trial

BACKGROUND

There is an urgent need to develop additional treatment strategies for patients with treatment-resistant depression (TRD). The rapid but short-lived antidepressant effects of intravenous (IV) ketamine as a racemic mixture have been shown repeatedly in this population, but there is still a paucity of data on the efficacy and safety of (a) different routes of administration, and (b) ketamine's enantiomers esketamine and arketamine. Given practical advantages of oral over IV administration and pharmacodynamic arguments for better antidepressant efficacy of esketamine over arketamine, we designed a study to investigate repeated administration of oral esketamine in patients with TRD.

METHODS

This study features a triple-blind randomized placebo-controlled trial (RCT) comparing daily oral esketamine versus placebo as add-on to regular antidepressant medications for a period of 6 weeks, succeeded by a follow-up of 4 weeks. The methods support examination of the efficacy, safety, tolerability, mechanisms of action, and economic impact of oral esketamine in patients with TRD.

DISCUSSION

This is the first RCT investigating repeated oral esketamine administration in patients with TRD. If shown to be effective and tolerated, oral esketamine administration poses important advantages over IV administration.

TRIAL REGISTRATION

Dutch Trial Register, NTR6161. Registered 21 October 2016.

Major depressive disorder is associated with changes in a cluster of serum and urine biomarkers

Major Depressive Disorder (MDD) is a heterogeneous disorder with a considerable symptomatic overlap with other psychiatric and somatic disorders. This study aims at providing evidence for association of a set of serum and urine biomarkers with MDD. We analyzed urine and serum samples of 40 MDD patients and 47 age- and sex-matched controls using 40 potential MDD biomarkers (21 serum biomarkers and 19 urine biomarkers). All participants were of Caucasian origin. We developed an algorithm to combine the heterogeneity at biomarker level. This method enabled the identification of correlating biomarkers based on differences in variation and distribution between groups, combined the outcome of the selected biomarkers, and calculated depression probability scores (the "bio depression score"). Phenotype permutation analysis showed a significant discrimination between MDD and euthymic (control) subjects for biomarkers in urine (P < .001), in serum (P = .02) and in the combined serum plus urine result (P < .001). Based on this algorithm, a combination of 8 urine biomarkers and 9 serum biomarkers were identified to correlate with MDD, enabling an area under the curve (AUC) of 0.955 in a Receiver Operating Characteristic (ROC) analysis. Selection of either urine biomarkers or serum biomarkers resulted in AUC values of 0.907 and 0.853, respectively. Internal cross-validation (5-fold) confirmed the association of this set of biomarkers with MDD.

Sociodemographic, behavioral, and health-related risk factors for depression among men and women in a southern Brazilian city

OBJECTIVE

To assess the prevalence of depression and sociodemographic, behavioral, and health-related risk factors therefor in a southern Brazilian city.

METHODS

Population-based, cross-sectional study of adults from Rio Grande, state of Rio Grande do Sul, Brazil. Individuals (n=1,295) were selected using a multistage sampling procedure. The Patient Health Questionnaire-9 (PHQ-9) was used to screen for major depressive episodes (MDEs). We used a conceptual causal framework to organize and assess risk factors for MDE and calculated prevalence ratios (PR) using regression models.

RESULTS

The prevalence of MDE was 8.4% (95%CI 6.0-10.7) for men and 13.4% (95%CI 11.0-15.8) for women. For men, physical inactivity (PR 2.34, 95%CI 1.09-5.00) and perceived stress (PR 20.35, 95%CI 5.92-69.96) were associated with MDE. In women, MDE prevalence was higher among those in the first tertile of economic index (PR 2.61, 95%CI 1.53-4.45), with 0-8 years of schooling (PR 2.25, 95%CI 1.24-4.11), alcohol users (PR 1.91, 95%CI 1.21-3.02), those physically inactive (PR 2.49, 95%CI 1.22-5.09), with the highest perceived stress (PR 9.17, 95%CI 3.47-24.23), with another mental disorder (PR 1.85, 95%CI 1.32-2.59), and with more noncommunicable diseases (PR 1.85, 95%CI 1.06-3.22).

CONCLUSION

Women had a higher prevalence of depression, and socioeconomic disadvantages were important for the occurrence of MDE; however, for men, only physical inactivity and stress were important predictors, suggesting possible different causal pathways for each sex.

The evolutionary old forebrain as site of action to develop new psychotropic drugs

BACKGROUND

Previously, the authors have developed a model of how reward-seeking and distress- avoiding behaviour is regulated by the human brain. The forebrain's evolution in vertebrates was taken as a starting point.

AIMS

The authors want to inspire colleagues to study in particular the pharmacological effects on the described ancient forebrain structures in order to modify specific symptoms of mental disorders.

METHODS

Compilation of data and ideas of previous articles, with examples to illustrate.

RESULTS

A primary (lamprey-like), secondary (frog-like) and tertiary (mammal-like) forebrain can be distinguished, organized according to a Russian doll model. The first constituent is primarily involved in producing the emotional response, while the last is principally concerned with constructing conscious cognitive behaviour (including verbal and written communication). Mental disorders comprise (partly related and partly unrelated) biological and rational phenomena. The secondary system regulates the intensity of reward-seeking and distress-avoiding behaviour. An essential component of the primary forebrain evaluates the results of behavioural actions: the lateral habenula-projecting pallidum. These neurons regulate the activity of ascending dopaminergic pathways. The authors suggest that these habenula-projecting pallidum neurons are targeted by subanaesthetic dosages of ketamine. The medial habenula is enriched with nicotinergic acetylcholine receptors and regulates the activity of ascending adrenergic and serotonergic neurons. This may link varenicline-induced hostility to selective serotonin reuptake inhibitor-induced aggression.

CONCLUSIONS

Studying the effects of new compounds on the primary and secondary brains in lampreys and frogs may yield interesting new treatments of mental disorders.

Psychopharmacology: From serendipitous discoveries to rationale design, but what next?

Psychopharmacology really developed as a discipline from the mid-20th century with the discovery of a number of new classes of psychoactive drugs which could modify behaviour. These drugs were discovered as a consequence of clinical observations of patients, often being treated for other conditions. These serendipitous discoveries were the start of an era of drug development which has led to the antidepressants, antipsychotics, anxiolytics and mood stabilisers used today. Subsequent research focused on understanding why these drugs were effective, and used this information to develop a second generation of drugs that were more selective for their therapeutic targets, and therefore had reduced side effects and improved safety and tolerability. After a period of decline in new discoveries and withdrawal of the majority of the major pharmaceutical companies from active development programmes in psychiatry, new avenues are emerging fuelling renewed interest in this area.

Automatic detection of major depressive disorder using electrodermal activity

Major depressive disorder (MDD) is a common psychiatric disorder and the leading cause of disability worldwide. However, current methods used to diagnose depression mainly rely on clinical interviews and self-reported scales of depressive symptoms, which lack objectivity and efficiency. To address this challenge, we present a machine learning approach to screen for MDD using electrodermal activity (EDA). Participants included 30 patients with MDD and 37 healthy controls. Their EDA was measured during five experimental phases consisted of baseline, mental arithmetic task, recovery from the stress task, relaxation task, and recovery from the relaxation task, which elicited multiple alterations in autonomic activity. Selected EDA features were extracted from each phase, and differential EDA features between two distinct phases were evaluated. By using these features as input data and performing feature selection with SVM-RFE, 74% accuracy, 74% sensitivity, and 71% specificity could be achieved by our decision tree classifier. The most relevant features selected by SVM-RFE included differential EDA features and features from the stress and relaxation tasks. These findings suggest that automatic detection of depression based on EDA features is feasible and that monitoring changes in physiological signal when a subject is experiencing autonomic arousal and recovery may enhance discrimination power.

Cortical Excitability and Activation of TrkB Signaling During Rebound Slow Oscillations Are Critical for Rapid Antidepressant Responses

Rapid antidepressant effects of ketamine become most evident when its psychotomimetic effects subside, but the neurobiological basis of this “lag” remains unclear. Laughing gas (N₂O), another NMDA-R (N-methyl-d-aspartate receptor) blocker, has been reported to bring antidepressant effects rapidly upon drug discontinuation. We took advantage of the exceptional pharmacokinetic properties of N₂O to investigate EEG (electroencephalogram) alterations and molecular determinants of antidepressant actions during and immediately after NMDA-R blockade. Effects of the drugs on brain activity were investigated in C57BL/6 mice using quantitative EEG recordings. Western blot and qPCR were used for molecular analyses. Learned helplessness (LH) was used to assess antidepressant-like behavior. Immediate-early genes (e.g., bdnf) and phosphorylation of mitogen-activated protein kinase—markers of neuronal excitability—were upregulated during N₂O exposure. Notably, phosphorylation of BDNF receptor TrkB and GSK3β (glycogen synthase kinase 3β) became regulated only gradually upon N₂O discontinuation, during a brain state dominated by slow EEG activity. Subanesthetic ketamine and flurothyl-induced convulsions (reminiscent of electroconvulsive therapy) also evoked slow oscillations when their acute pharmacological effects subsided. The correlation between ongoing slow EEG oscillations and TrkB-GSK3β signaling was further strengthened utilizing medetomidine, a hypnotic-sedative agent that facilitates slow oscillations directly through the activation of α₂-adrenergic autoreceptors. Medetomidine did not, however, facilitate markers of neuronal excitability or produce antidepressant-like behavioral changes in LH. Our results support a hypothesis that transient cortical excitability and the subsequent regulation of TrkB and GSK3β signaling during homeostatic emergence of slow oscillations are critical components for rapid antidepressant responses.

N-acetylcysteine as add-on to antidepressant medication in therapy refractory major depressive disorder patients with increased inflammatory activity: study protocol of a double-blind randomized placebo-controlled trial

BACKGROUND

A subgroup of depressed patients with increased inflammatory activity was shown to be more susceptible to develop Treatment Resistant Depression (TRD). Earlier studies with anti-inflammatory drugs have shown benefits in the treatment of major depressive disorder (MDD), but the effects are expected to be higher in patients with increased inflammatory activity. Supplementation of N-acetylcysteine (NAC) to ongoing antidepressant therapy may positively influence outcome of depression treatment in these patients. Therefore, this study aims to investigate the efficacy of NAC supplementation in patients with insufficient response to standard antidepressant treatment, and to explore potential roles of inflammation and oxidative stress involved in the alleged pathophysiological processes of TRD.

METHODS/DESIGN

A double-blind randomized placebo-controlled study comparing NAC versus placebo as add-on medication to antidepressant treatment with 12-week treatment and 8-week follow up in patients with TRD and increased inflammatory activity. Apart from clinical efficacy defined as the change in Hamilton Depression Rating Scale (HAMD)-17 score, secondary outcomes include changes in pathophysiological mechanisms related to depression as well as changes in local brain activity (functional Magnetic Resonance Imaging, fMRI) and white matter integrity (Diffusion Tensor Imaging, DTI). Importantly, sole patients with CRP levels with values between 0.85 and 10 mg/L will be included.

DISCUSSION

This is the first clinical trial taking both TRD and increased inflammatory activity as inclusion criteria. This study will provide reliable evidence for the efficacy of NAC in patients with TRD displaying increased inflammatory activity. And this study also will help explore further the roles of inflammation and oxidative stress involved in the alleged pathophysiological processes of TRD.

TRIAL REGISTRATION

The trial protocol has been registered on "ClinicalTrials.gov"with protocol ID "NAC-2015-TJAH" and ClinicalTrials.gov ID " NCT02972398 ".

Elevated hippocampal choline level is associated with altered functional connectivity in females with major depressive disorder: A pilot study

Metabolic and functional alterations in hippocampus have been associated with the pathophysiology of major depressive disorder (MDD). However, how the hippocampal biochemical disruptions lead to dysfunction of limbic-cortical circuit remains unclear. The present pilot study combined magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (rs-fMRI) to investigate the hippocampal metabolic alteration and its relationship with the intrinsic functional connectivity (FC) changes in MDD. Both MRS and fMRI data were obtained from twelve women with MDD and twelve age-matched, healthy women. Bilateral hippocampi were chosen as regions of interest, in which metabolite concentrations of total choline (tCho), N-acetylaspartate and creatine were quantified. Bilateral hippocampal FC to the whole brain and its correlations with hippocampal metabolite concentrations were conducted. Females with MDD showed significantly elevated left hippocampal tCho level, and decreased anti-correlations between the left hippocampus and bilateral superior frontal gyrus (SFG), left inferior frontal gyrus, and right superior temporal gyrus. More importantly, the left hippocampal tCho level was associated with FC to the right SFG and right fusiform gyrus in healthy women, whereas it was significantly associated with FC to the right lingual gyrus in women with MDD. Our findings suggested that regional metabolic alterations in the left hippocampus might be related to the network-level dysfunction.

Interleukin, tumor necrosis factor-α and C-reactive protein profiles in melancholic and non-melancholic depression: A systematic review

OBJECTIVE

The current diagnostic criteria for major depressive disorder (MDD) do not allow prediction of prognosis and therapeutic response. A possible strategy to improve this situation is the identification of depression subtypes on the bases of biomarkers reflecting underlying pathological processes such as neuro-inflammation.

METHODS

The PubMed/Medline database was searched until Apr 25th, 2017. In the initial search 1018 articles were retrieved, which were subsequently screened and only selected when the inclusion and exclusion criteria were fulfilled.

RESULTS

Eight eligible studies were found. Overall, serum interleukin-6 and 1β values were increased in the melancholic MDD subtype compared to controls and the non-melancholic MDD subtype. C-reactive protein was increased in non-melancholic MDD in 2 out of 4 studies, while there was no difference for tumor necrosis factor-α and interleukin-2 and 10.

CONCLUSION

Given the paucity of eligible studies the tentative conclusion must be drawn that peripheral inflammation markers have limited added value thus far to distinguish between melancholic and non-melancholic depression. To allow for a more definitive conclusion, further research is warranted using a broader panel of inflammatory markers in MDD subtypes, preferably based on a general consensus regarding diagnostic criteria and subtype definitions.

Translational Shifts in Preclinical Models of Depression: Implications for Biomarkers for Improved Treatments

Understanding the neurobiology of major depressive disorder (MDD) remains one of the major challenges in neuroscience. The disease is heterogeneous in nature, and patients present with a varied symptom profile. Studies seeking to identify biomarkers for MDD diagnosis and treatment have not yet found any one candidate which achieves sufficient sensitivity and specificity. In this article, we consider whether neuropsychological impairments, specifically affective biases, could provide a behavioural biomarker. Affective biases are observed when emotional states influence cognitive function. These biases have been shown to influence a number of different cognitive domains with some specific deficits observed in MDD. It has also been possible to use these neuropsychological tests to inform the development of translational tasks for non-human species. The results from studies in rodents suggest that quantification of affective biases is feasible and may provide a reliable method to predict antidepressant efficacy as well as pro-depressant risk. Animal studies suggest that affective state-induced biases in learning and memory operate over a different time course to biases influencing decision-making. The implications for these differences in terms of task validity and future ideas relating to affective biases and MDD are discussed. We also describe our most recent studies which have shown that depression-like phenotypes share a common deficit in reward-related learning and memory which we refer to as a reward-induced positive bias. This deficit is dissociable from more typical measures of hedonic behaviour and motivation for reward and may represent an important and distinct form of reward deficit linked to MDD.

From Serotonin to Neuroplasticity: Evolvement of Theories for Major Depressive Disorder

The serotonin (5-HT) hypothesis of depression has played an important role in the history of psychiatry, yet it has also been criticized for the delayed onset and inadequate efficacy of selective serotonin reuptake inhibitors (SSRIs). With evolvement of neuroscience, the neuroplasticity hypothesis of major depressive disorder (MDD) has been proposed and may provide a better framework for clarification the pathogenesis of MDD and antidepressant efficacy. In this article, we first summarized the evidence challenging the monoamine hypothesis and proposed that the antidepressant efficacy of SSRIs is not derived from elevated monoamine (5-HT, noradrenaline (NE), or dopamine (DA)) concentration or monoamine neurotransmission. Second, we reviewed the role of stress in the pathogenesis of MDD and gave a brief introduction to the neuroplasticity hypothesis of MDD. Third, we explored the possible mechanisms underlying the antidepressant efficacy of typical antidepressants in the context of neuroplasticity theory. Fourth, we tried to provide an explanatory framework for the significant difference in onset of efficacy between typical antidepressants and ketamine. Finally, we provided a brief summarization about this review article and some perspectives for future studies.

Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response

Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD.

Inherent vulnerabilities in monoaminergic pathways predict the emergence of depressive impairments in an animal model of chronic epilepsy

The objective was to determine whether the depression comorbid with epilepsy could be predicted based on inherent premorbid patterns of monoaminergic transmission. In male Wistar rats, despair-like and anhedonia-like behaviors were examined using forced swimming and taste preference tests, respectively. Serotonergic raphe nucleus (RN)-prefrontal cortex (PFC) and dopaminergic ventral tegmental area (VTA)-nucleus accumbens (NAcc) pathways were interrogated by fast scan cyclic voltammetry (FSCV). The assays were performed before and 2 months after pilocarpine status epilepticus. In a subset of naive rats, FSCV, coupled with the intensity-dependent stimulation paradigm, detected specific deviations in each pathway (six rats for RN-PFC and seven rats for VTA-NAcc, with overlap in two, of 19 total subjects) in the absence of behavioral impairments. During epilepsy, animals with preexisting deviations in RN-PFC invariably developed despair, and rats with deviations in VTA-NAcc developed anhedonia. Serotonergic and dopaminergic pathways, respectively, showed signs of explicit deterioration. We suggest that epilepsy triggers decompensations in the already vulnerable depression-relevant neuronal circuits, which culminate in depression. The established connection between the identified specific signatures in monoamine transmission in naive rats and specific symptoms of epilepsy-associated depression may help in understanding causes of comorbidity and in developing its early biomarkers.

Circuits Regulating Pleasure and Happiness in Bipolar Disorder

According to our model, the motivation for appetitive-searching vs. distress-avoiding behaviors is regulated by two parallel cortico-striato-thalamo-cortical (CSTC) re-entry circuits that include the core and the shell parts of the nucleus accumbens, respectively. An entire series of basal ganglia, running from the caudate nucleus on one side to the centromedial amygdala on the other side, control the intensity of these reward-seeking and misery-fleeing behaviors by stimulating the activity of the (pre)frontal and limbic cortices. Hyperactive motivation to display behavior that potentially results in reward induces feelings of hankering (relief leads to pleasure); while, hyperactive motivation to exhibit behavior related to avoidance of aversive states results in dysphoria (relief leads to happiness). These two systems collaborate in a reciprocal fashion. We hypothesized that the mechanism inducing the switch from bipolar depression to mania is the most essential characteristic of bipolar disorder. This switch is attributed to a dysfunction of the lateral habenula, which regulates the activity of midbrain centers, including the dopaminergic ventral tegmental area (VTA). From an evolutionary perspective, the activity of the lateral habenula should be regulated by the human homolog of the habenula-projecting globus pallidus, which in turn might be directed by the amygdaloid complex and the phylogenetically old part of the limbic cortex. In bipolar disorder, it is possible that the system regulating the activity of this reward-driven behavior is damaged or the interaction between the medial and lateral habenula may be dysfunctional. This may lead to an adverse coupling between the activities of the misery-fleeing and reward-seeking circuits, which results in independently varying activities.

Biological profiling of prospective antidepressant response in major depressive disorder: Associations with (neuro)inflammation, fatty acid metabolism, and amygdala-reactivity

BACKGROUND

A better understanding of factors underlying antidepressant non-response may improve the prediction of which patients will respond to what treatment. Major depressive disorder (MDD) is associated with alterations in fatty acid metabolism, (neuro)inflammation and amygdala-reactivity. However, their mutual relations, and the extent to which they are associated with prospective antidepressant-response, remain unknown.

PURPOSE

To test (I) alterations in (neuro)inflammation and its associations with fatty acid metabolism and amygdala-reactivity in MDD-patients compared to controls, and (II) whether these alterations are associated with prospective paroxetine response.

METHODS

We compared 70 unmedicated MDD-patients with 51 matched healthy controls at baseline, regarding erythrocyte membrane omega-6 arachidonic acid (AA), inflammation [serum (high-sensitivity) C-reactive protein (CRP)], and in a subgroup amygdala-reactivity to emotional faces using functional magnetic resonance imaging (fMRI) (N=42). Subsequently, we treated patients with 12 weeks paroxetine, and repeated baseline measures after 6 and 12 weeks to compare non-responders, early-responders (response at 6 weeks), and late-responders (response at 12 weeks).

RESULTS

Compared to controls, MDD-patients showed higher CRP (p=0.016) and AA (p=0.019) after adjustment for confounders at baseline. AA and CRP were mutually correlated (p=0.043). In addition, patients showed a more negative relation between AA and left amygdala-reactivity (p=0.014). Moreover, AA and CRP were associated with antidepressant-response: early responders showed lower AA (p=0.018) and higher CRP-concentrations (p=0.008) than non-responders throughout the study.

CONCLUSION

Higher observed CRP and AA, their mutual association, and relation with amygdala-reactivity, are corroborative with a role for (neuro)inflammation in MDD. In addition, observed associations of these factors with prospective antidepressant-response suggest a potential role as biomarkers. Future studies in independent samples are needed to replicate and test the clinical applicability of these biological predictors for treatment response to result in a precision/personalized medicine approach for treatment.

Treatment of depression with low-strength transcranial pulsed electromagnetic fields: A mechanistic point of view

BACKGROUND

Mood disorders constitute a high burden for both patients and society. Notwithstanding the large arsenal of available treatment options, a considerable group of patients does not remit on current antidepressant treatment. There is an urgent need to develop alternative treatment strategies. Recently, low-strength transcranial pulsed electromagnetic field (tPEMF) stimulation has been purported as a promising strategy for such treatment-resistant depression (TRD). The mode of action of this new technique is however largely unknown.

METHODS

We searched PubMed for literature reports on the effects of tPEMF and for information regarding its working mechanism and biological substrate.

RESULTS

Most studies more or less connect with the major hypotheses of depression and concern the effects of tPEMF on brain metabolism, neuronal connectivity, brain plasticity, and the immune system. Relatively few studies paid attention to the possible chronobiologic effects of electromagnetic fields.

LIMITATIONS

We reviewed the literature of a new and still developing field. Some of the reports involved translational studies, which inevitably limits the reach of the conclusions.

CONCLUSION

Weak magnetic fields influence divergent neurobiological processes. The antidepressant effect of tPEMF may be specifically attributable to its effects on local brain activity and connectivity.

Frequency-specific alterations in functional connectivity in treatment-resistant and -sensitive major depressive disorder

Major depressive disorder (MDD) may involve alterations in brain functional connectivity in multiple neural circuits and present large-scale network dysfunction. Patients with treatment-resistant depression (TRD) and treatment-sensitive depression (TSD) show different responses to antidepressants and aberrant brain functions. This study aims to investigate functional connectivity patterns of TRD and TSD at the whole brain resting state. Seventeen patients with TRD, 17 patients with TSD, and 17 healthy controls matched with age, gender, and years of education were recruited in this study. The brain was divided using an automated anatomical labeling atlas into 90 regions of interest, which were used to construct the entire brain functional networks. An analysis method called network-based statistic was used to explore the dysconnected subnetworks of TRD and TSD at different frequency bands. At resting state, TSD and TRD present characteristic patterns of network dysfunction at special frequency bands. The dysconnected subnetwork of TSD mainly lies in the fronto-parietal top-down control network. Moreover, the abnormal neural circuits of TRD are extensive and complex. These circuits not only depend on the abnormal affective network but also involve other networks, including salience network, auditory network, visual network, and language processing cortex. Our findings reflect that the pathological mechanism of TSD may refer to impairment in cognitive control, whereas TRD mainly triggers the dysfunction of emotion processing and affective cognition. This study reveals that differences in brain functional connectivity at resting state reflect distinct pathophysiological mechanisms in TSD and TRD. These findings may be helpful in differentiating two types of MDD and predicting treatment responses.

Altered neuronal spontaneous activity correlates with glutamate concentration in medial prefrontal cortex of major depressed females: An fMRI-MRS study

BACKGROUND

Major depressive disorder (MDD) is twice more prevalent in females than in males. Yet, there have only been a few studies on the functional brain activity in female MDD patients and the detailed mechanisms underlying their neurobiology merit further investigations. In the present work, we used combined fMRI-MRS methods to investigate the altered intrinsic neuronal activity and its association with neurotransmitter concentration in female MDD patients.

METHODS

The whole brain amplitude of low frequency fluctuation (ALFF) analysis using resting state functional magnetic resonance imaging (fMRI) was performed to explore the alteration of intrinsic neuronal signals in MDD females (n=11) compared with female healthy controls (n=11). With a specific interest in the medial prefrontal cortex (mPFC) area, we quantified the concentration of amino acid neurotransmitters including GABA ((r-aminobutyric acid)), Glu (Glutamate), and Glx (Glutamate + Glutamine) using (1)H-MRS technology. Moreover, we conducted Pearson correlation analysis between the ALFF value and neurotransmitter concentration to find out the functional-biochemical relation in mPFC area. The relationship between the metabolites concentration and MDD symptomatology was also examined through Spearman correlation analysis.

RESULTS

We found that the female MDD patients showed increased neuronal spontaneous activity in left medial prefrontal cortex (mPFC) and left middle frontal cortex, with decreased ALFF level in right putamen and right middle temporal cortex (p<0.01, Alphasim corrected). The ALFF in mPFC was shown positively correlated with Glu concentration in female MDD patients (r=0.67, p=0.023). The Glu concentration in mPFC was positively correlated with patients HAMA scores (r=0.641, p=0.033).

LIMITATIONS

The relatively small sample size, metabolite information acquired only in mPFC and not all patients were unmedicated are the major limitations of our study.

CONCLUSIONS

Using combined fMRI-MRS methods, we found increased spontaneous neuronal activity was correlated with Glu concentration in mPFC of female MDD patients. Other regions including left middle frontal gyrus, right putamen and middle temporal gyrus also showed altered spontaneous neuronal activities. The abnormal intrinsic neuronal activities in fronto-cortical regions shed light on the pathogenesis underlying MDD females. The multimodal resting-state neuroimaging technique served as a useful tool for functional-biochemical investigation of MDD pathophysiology.