Metabolomics in Schizophrenia and Major Depressive Disorder

Defining pathophenotype, a systems level consequence of a disease genotype, together with environmental and stochastic influences, is an arduous task in psychiatry. It is also an appealing goal, given growing need for appreciation of brain disorders biological complexity, aspiration for diagnostic tests development and ambition to identify novel drug targets. Here, we focus on the Schizophrenia and Major Depressive Disorder and highlight recent advances in metabolomics research. As a systems biology tool, metabolomics holds a promise to take part in elucidating interactions between genes and environment, in complex behavioral traits and psychopathology risk translational research.     

The Potential Biomarker Panels for Identification of Major Depressive Disorder (MDD) Patients with and without Early Life Stress (ELS) by Metabonomic Analysis

Objective

The lack of the disease biomarker to support objective laboratory tests still constitutes a bottleneck in the clinical diagnosis and evaluation of major depressive disorder (MDD) and its subtypes. We used metabonomic techniques to screen the diagnostic biomarker panels from the plasma of MDD patients with and without early life stress (ELS) experience.

Methods

Plasma samples were collected from 25 healthy adults and 46 patients with MDD, including 23 patients with ELS and 23 patients without ELS. Furthermore, gas chromatography/mass spectrometry (GC/MS) coupled with multivariate statistical analysis was used to identify the differences in global plasma metabolites among the 3 groups.

Results

The distinctive metabolic profiles exist either between healthy subjects and MDD patients or between the MDD patients with ELS experience (ELS/MDD patients) and the MDD patients without it (non-ELS/MDD patients), and some diagnostic panels of feature metabolites'' combination have higher predictive potential than the diagnostic panels of differential metabolites.

Conclusions

These findings in this study have high potential of being used as novel laboratory diagnostic tool for MDD patients and it with ELS or not in clinical application.     

Potential hormonal mechanisms of Attention-Deficit/Hyperactivity Disorder and Major Depressive Disorder: A new perspective

Hormonal influences on the organization of behavior are apparent to neuroendocrinologists but under-examined in relation to childhood and adolescent mental disorders. A central mystery in the field of developmental psychopathology is the preferential male vulnerability to behavior disorders in childhood and female vulnerability to emotional disorders in adolescence. Relative neglect of a hormonal explanation may be due to lack of simple or unifying conceptual paradigms to guide studies. This paper seeks to stimulate research in this area by drawing upon clinical psychology and neuroscience literatures to offer a heuristic paradigm for clinical research. Two syndromes are selected here for illustration: Attention-Deficit/Hyperactivity Disorder (ADHD) and Major Depressive Disorder (MDD), because they have opposite gender risk profiles. Two guiding theories are evaluated. First, prenatal organizational effects of testosterone may modulate striatally-based dopaminergic circuits in such a way as to place boys at greater risk for early developing inattention and disruptive behavioral disorders. Second, activational effects of estradiol at puberty may modulate amygdalar and other circuitry, with particular effects on serotonergic pathways, in such a way as to place girls at greater risk for internalizing and mood disorders. Hypotheses from these theories are evaluated based on the current available literature, and limitations of, and future directions for, this literature are discussed.     

Smoking and Major Depressive Disorder in Chinese Women

Objective

To investigate the risk factors that contribute to smoking in female patients with major depressive disorder (MDD) and the clinical features in depressed smokers.

Methods

We examined the smoking status and clinical features in 6120 Han Chinese women with MDD (DSM-IV) between 30 and 60 years of age across China. Logistic regression was used to determine the association between clinical features of MDD and smoking status and between risk factors for MDD and smoking status.

Results

Among the recurrent MDD patients there were 216(3.6%) current smokers, 117 (2.0%) former smokers and 333(5.6%) lifetime smokers. Lifetime smokers had a slightly more severe illness, characterized by more episodes, longer duration, more comorbid illness (panic and phobias), with more DSM-IV A criteria and reported more symptoms of fatigue and suicidal ideation or attempts than never smokers. Some known risk factors for MDD were also differentially represented among smokers compared to non-smokers. Smokers reported more stressful life events, were more likely to report childhood sexual abuse, had higher levels of neuroticism and an increased rate of familial MDD. Only neuroticism was significantly related to nicotine dependence.

Conclusions

Although depressed women smokers experience more severe illness, smoking rates remain low in MDD patients. Family history of MDD and environmental factors contribute to lifetime smoking in Chinese women, consistent with the hypothesis that the association of smoking and depression may be caused by common underlying factors.     

Epidemiology of Major Depressive Disorder in Mainland China: A Systematic Review

Background

Major depressive disorder (MDD) is one of the important causes of disease burden in the general population. Given the experiencing rapid economic and social changes since the early 1990s and the internationally recognized diagnostic criteria and interview instruments across the surveys during 2001–2010 in china, the epidemiological studies on MDD got varied results. We performed this meta-analysis to investigate current, 12-month and lifetime prevalence rates of MDD in mainland China.

Methods

PubMed, Embase, Chinese Biological Medical Literature database (CBM), Chinese National Knowledge Infrastructure database (CNKI), and the Chinese Wanfang and Chongqing VIP database were searched for associated studies. We estimated the overall prevalence of MDD using meta-analysis.

Conclusions

Seventeen eligible studies were included. Our study showed that the overall estimation of current, 12-month and lifetime prevalence of MDD was 1.6, 2.3, 3.3%, respectively. The current prevalence was 2.0 and 1.7% in rural and urban areas, respectively; between female and male, it was 2.1 and 1.3%, respectively. In addition, the current prevalence of MDD diagnosed with SCID (Structured Clinical Interview for DSM-IV) was 1.8% and that diagnosed with CIDI (Composite International Diagnostic Interview) was 1.1%. In conclusion, our study revealed a relatively high prevalence rate in the lifetime prevalence of MDD. For current prevalence, MDD diagnosed with SCID had a higher prevalence rate than with CIDI; males showed a lower rate than females, rural residents seemed to have a greater risk of MDD than urban residents.     

Identification and Validation of Urinary Metabolite Biomarkers for Major Depressive Disorder

Major depressive disorder (MDD) is a widespread and debilitating mental disorder. However, there are no biomarkers available to aid in the diagnosis of this disorder. In this study, a nuclear magnetic resonance spectroscopy–based metabonomic approach was employed to profile urine samples from 82 first-episode drug-naïve depressed subjects and 82 healthy controls (the training set) in order to identify urinary metabolite biomarkers for MDD. Then, 44 unselected depressed subjects and 52 healthy controls (the test set) were used to independently validate the diagnostic generalizability of these biomarkers. A panel of five urinary metabolite biomarkers—malonate, formate, N-methylnicotinamide, m-hydroxyphenylacetate, and alanine—was identified. This panel was capable of distinguishing depressed subjects from healthy controls with an area under the receiver operating characteristic curve (AUC) of 0.81 in the training set. Moreover, this panel could classify blinded samples from the test set with an AUC of 0.89. These findings demonstrate that this urinary metabolite biomarker panel can aid in the future development of a urine-based diagnostic test for MDD.Major depressive disorder (MDD)¹ is a debilitating mental disorder affecting up to 15% of the general population and accounting for 12.3% of the global burden of disease (1, 2). Currently, the diagnosis of MDD still relies on the subjective identification of symptom clusters rather than empirical laboratory tests. The current diagnostic modality results in a considerable error rate (3), as the clinical presentation of MDD is highly heterogeneous and the current symptom-based method is not capable of adequately characterizing this heterogeneity (4). An approach that can be used to circumvent these limitations is to identify disease biomarkers to support objective diagnostic laboratory tests for MDD.Metabonomics, which can measure the small molecules in given biosamples such as plasma and urine without bias (5), has been extensively used to characterize the metabolic changes of diseases and thus facilitate the identification of novel disease-specific signatures as putative biomarkers (6–10). Nuclear magnetic resonance (NMR) spectroscopy–based metabonomic approaches characterized by sensitive, high-throughput molecular screening have been employed previously in identifying novel biomarkers for a variety of neuropsychiatric disorders, including stroke, bipolar disorder, and schizophrenia (11–13).Specifically with regard to MDD, several animal studies have already characterized the metabolic changes in the blood and urine (14–19). These studies provide valuable clues as to the pathophysiological mechanism of MDD. However, no study has been designed with the aim of diagnosing this disease. Recently, using an NMR-based metabonomic approach, this research group identified a unique plasma metabolic signature that enables the discrimination of MDD from healthy controls with both high sensitivity and specificity (20). These findings motivated further study on urinary diagnostic metabolite biomarkers for MDD, which would be more valuable from a clinical applicability standpoint, as urine can be more non-invasively collected. Moreover, previous studies have also demonstrated the feasibility of identifying diagnostic metabolite biomarkers of psychiatric disorders in the urine. For example, using an NMR-based metabonomics approach, Yap et al. (21) identified a unique urinary metabolite signature that clearly discriminated autism patients from healthy controls. As systemic metabolic disturbances have been observed in the urine of a depressed animal model, it is likely that diagnostic metabolite markers for MDD can be detected in human urine.Therefore, in this study, NMR spectroscopy combined with multivariate pattern recognition techniques were used to profile 82 first-episode drug-naïve MDD subjects and 82 healthy controls (the training set) in order to identify potential metabolite biomarkers for MDD. Furthermore, 44 unselected MDD subjects and 52 healthy controls (the test set) were employed to independently validate the diagnostic performance of these urinary metabolite biomarkers.     

MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder

Here we outline the protocol for magnetic resonance imaging (MRI) guided repetitive transcranial magnetic stimulation (rTMS) to the dorsal medial prefrontal cortex (dmPFC) in patients with major depressive disorder (MDD). Technicians used a neuronavigation system to process patient MRIs to generate a 3-dimensional head model. The head model was subsequently used to identify patient-specific stimulatory targets. The dmPFC was stimulated daily for 20 sessions. Stimulation intensity was titrated to address scalp pain associated with rTMS. Weekly assessments were conducted on the patients using the Hamilton Rating Scale for Depression (HamD₁₇) and Beck Depression Index II (BDI-II). Treatment-resistant MDD patients achieved significant improvements on both HAMD and BDI-II. Of note, angled, double-cone coil rTMS at 120% resting motor threshold allows for optimal stimulation of deeper midline prefrontal regions, which results in a possible therapeutic application for MDD. One major limitation of the rTMS field is the heterogeneity of treatment parameters across studies, including duty cycle, number of pulses per session and intensity. Further work should be done to clarify the effect of stimulation parameters on outcome. Future dmPFC-rTMS work should include sham-controlled studies to confirm its clinical efficacy in MDD.     

Changes of Functional Brain Networks in Major Depressive Disorder: A Graph Theoretical Analysis of Resting-State fMRI

Recent developments in graph theory have heightened the need for investigating the disruptions in the topological structure of functional brain network in major depressive disorder (MDD). In this study, we employed resting-state functional magnetic resonance imaging (fMRI) and graph theory to examine the whole-brain functional networks among 42 MDD patients and 42 healthy controls. Our results showed that compared with healthy controls, MDD patients showed higher local efficiency and modularity. Furthermore, MDD patients showed altered nodal centralities of many brain regions, including hippocampus, temporal cortex, anterior cingulate gyrus and dorsolateral prefrontal gyrus, mainly located in default mode network and cognitive control network. Together, our results suggested that MDD was associated with disruptions in the topological structure of functional brain networks, and provided new insights concerning the pathophysiological mechanisms of MDD.     

Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis

BackgroundChronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study.ConclusionsGenetic factors, as well as chronic pain in a partner or spouse, contribute substantially to the risk of chronic pain for an individual. Chronic pain is genetically correlated with MDD, has a polygenic architecture, and is associated with polygenic risk of MDD.     

Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia,Bipolar Disorder,and Major Depressive Disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.     

Major Depressive Disorder and Stroke Risks: A 9-Year Follow-Up Population-Based,Matched Cohort Study

Background and Purpose

Major depressive disorder (MDD) is characterized by recurrent depressive episodes and one of the treatment choices is antidepressants. Patients with MDD are at greater risk of developing major metabolic diseases that may in turn lead to stroke. Moreover, both depressive symptoms and taking antidepressant medications are associated with higher risk of stroke. However, whether and how clinical depression increases stroke risk remains an unanswered question. Our aim was to provide answers to this question.

Methods

A matched cohort study of 5015 subjects (1003 MDD patients and 4012 control subjects) was conducted using a nationwide database. Subjects were followed to a maximum of 9 years to determine rates of newly-developed strokes, and controls and MDD groups with different levels of antidepressant refractoriness were compared to determine the temporal relation between stroke and three major metabolic comorbidities (i.e., diabetes mellitus, hypertension and hyperlipidemia). The levels of depressive symptoms and the antidepressant medications before stroke onset were investigated.

Results

Patients with MDD had significantly higher rates of stroke (4.3% vs. 2.8%, p<0.05) during the follow-up. Mediation regression analyses revealed that the occurrence of stroke in the MDD subjects was significantly mediated by the development of major metabolic diseases. Greater severity of depression, but not greater use of antidepressants, preceded the occurrence of stroke.

Conclusions

A clinical diagnosis of major depression leads to stroke indirectly through more intense depressive symptoms and the development of major comorbidities.     

Resequencing Three Candidate Genes for Major Depressive Disorder in a Dutch Cohort

Major depressive disorder (MDD) is a psychiatric disorder, characterized by periods of low mood of more than two weeks, loss of interest in normally enjoyable activities and behavioral changes. MDD is a complex disorder and does not have a single genetic cause. In 2009 a genome wide association study (GWAS) was performed on the Dutch GAIN-MDD cohort. Many of the top signals of this GWAS mapped to a region spanning the gene PCLO, and the non-synonymous coding single nucleotide polymorphism (SNP) rs2522833 in the PCLO gene became genome wide significant after post-hoc analysis. We performed resequencing of PCLO, GRM7, and SLC6A4 in 50 control samples from the GAIN-MDD cohort, to detect new genomic variants. Subsequently, we genotyped these variants in the entire GAIN-MDD cohort and performed association analysis to investigate if rs2522833 is the causal variant or simply in linkage disequilibrium with a more associated variant. GRM7 and SLC6A4 are both candidate genes for MDD from literature. We aimed to gather more evidence that rs2522833 is indeed the causal variant in the GAIN-MDD cohort or to find a previously undetected common variant in either PCLO, GRM7, or SLC6A4 with a higher association in this cohort. After next generation sequencing and association analysis we excluded the possibility of an undetected common variant to be more associated. For neither PCLO nor GRM7 we found a more associated variant. For SLC6A4, we found a new SNP that showed a lower P-value (P = 0.07) than in the GAIN-MDD GWAS (P = 0.09). However, no evidence for genome-wide significance was found. Although we did not take into account rare variants, we conclude that our results provide further support for the hypothesis that the non-synonymous coding SNP rs2522833 in the PCLO gene is indeed likely to be the causal variant in the GAIN-MDD cohort.     

Fear Extinction as a Model for Synaptic Plasticity in Major Depressive Disorder

Background

The neuroplasticity hypothesis of major depressive disorder proposes that a dysfunction of synaptic plasticity represents a basic pathomechanism of the disorder. Animal models of depression indicate enhanced plasticity in a ventral emotional network, comprising the amygdala. Here, we investigated fear extinction learning as a non-invasive probe for amygdala-dependent synaptic plasticity in patients with major depressive disorder and healthy controls.

Methods

Differential fear conditioning was measured in 37 inpatients with severe unipolar depression (International Classification of Diseases, 10^th revision, criteria) and 40 healthy controls. The eye-blink startle response, a subcortical output signal that is modulated by local synaptic plasticity in the amygdala in fear acquisition and extinction learning, was recorded as the primary outcome parameter.

Results

After robust and similar fear acquisition in both groups, patients with major depressive disorder showed significantly enhanced fear extinction learning in comparison to healthy controls, as indicated by startle responses to conditioned stimuli. The strength of extinction learning was positively correlated with the total illness duration.

Conclusions

The finding of enhanced fear extinction learning in major depressive disorder is consistent with the concept that the disorder is characterized by enhanced synaptic plasticity in the amygdala and the ventral emotional network. Clinically, the observation emphasizes the potential of successful extinction learning, the basis of exposure therapy, in anxiety-related disorders despite the frequent comorbidity of major depressive disorder.     

Near Infrared Spectroscopy Study of the Frontopolar Hemodynamic Response and Depressive Mood in Children with Major Depressive Disorder: A Pilot Study

AIM

The aim of this study was to evaluate the frontopolar hemodynamic response and depressive mood in children with mild or moderate major depressive disorder during six weeks treatment without medication.

METHODS

The subjects were 10 patients with mild or moderate depression. They were depressive drug-naive children and adolescents. The scores of Depression Self Rating Scale (DSRS), the results of the Verbal Fluency Test (VFT), and the concentrations of oxy-hemoglobin (Oxy-Hb) of frontal pole brain assessed by two-channel near infrared spectroscopy (NIRS) after six weeks of treatment was compared with those of initial treatment.

RESULTS

The score of DSRS was significantly reduced after six weeks of initial treatment (p<0.001, t-test). The word number of VFT was not significantly changed after six weeks of treatment. The oxy-Hb concentration significantly increased after six weeks of treatment (p<0.001, t-test).

CONCLUSIONS

This study demonstrated that the concentration of oxy-Hb of frontopolar cortex in children with mild and moderate depression improved along with their depressive mood. These results suggested that concentration of oxy-Hb using NIRS may be used as the state maker for change in depressive mood of children having depression, similar to that in adults.     

Perceived Impeding Factors for Return-to-Work after Long-Term Sickness Absence Due to Major Depressive Disorder: A Concept Mapping Approach

Objective

The purpose of the present study was to explore various stakeholder perspectives regarding factors that impede return-to-work (RTW) after long-term sickness absence related to major depressive disorder (MDD).

Methods

Concept mapping was used to explore employees'', supervisors'' and occupational physicians'' perspectives on these impeding factors.

Results

Nine perceived themes, grouped in three meta-clusters were found that might impede RTW: Person, (personality / coping problems, symptoms of depression and comorbid (health) problems, employee feels misunderstood, and resuming work too soon), Work (troublesome work situation, too little support at work, and too little guidance at work) and Healthcare (insufficient mental healthcare and insufficient care from occupational physician). All stakeholders regarded personality/coping problems and symptoms of depression as the most important impeding theme. In addition, supervisors emphasized the importance of mental healthcare underestimating the importance of the work environment, while occupational physicians stressed the importance of the lack of safety and support in the work environment.

Conclusions

In addition to the reduction of symptoms, more attention is needed on coping with depressive symptoms and personality problems in the work environment support in the work environment and for RTW in mental healthcare, to prevent long term sickness absence.     

Association between Glucocorticoid Receptor Methylation and Hippocampal Subfields in Major Depressive Disorder

Background

DNA methylation in the promoter region of the glucocorticoid receptor gene (NR3C1) is closely associated with childhood adversity and suicide. However, few studies have examined NR3C1 methylation in relation to major depressive disorder (MDD) and hippocampal subfield volumes. We investigated the possible association between NR3C1 methylation and structural brain alterations in MDD in comparison with healthy controls.

Methods

We compared the degree of NR3C1 promoter methylation in the peripheral blood of non-psychotic outpatients with MDD and that of healthy controls. Correlations among NR3C1 promoter methylation, structural abnormalities in hippocampal subfield volumes and whole-brain cortical thickness, and clinical variables were also analyzed.

Results

In total, 117 participants (45 with MDD and 72 healthy controls) were recruited. Patients with MDD had significantly lower methylation than healthy controls at 2 CpG sites. In MDD, methylations had positive correlations with the bilateral cornu ammonis (CA) 2–3 and CA4-dentate gyrus (DG) subfields. However, in healthy controls, methylations had positive correlation with the subiculum and presubiculum. There were no differences in total and subfield volumes of the hippocampus between patients with MDD and healthy controls. Compared with healthy controls, patients with MDD had a significantly thinner cortex in the left rostromiddle frontal, right lateral orbitofrontal, and right pars triangularis areas.

Conclusions

Lower methylation in the NR3C1 promoter, which might have compensatory effects relating to CA2-3 and CA4-DG, is a distinct epigenetic characteristic in non-psychotic outpatients with MDD. Future studies with a longitudinal design and a comprehensive neurobiological approach are warranted in order to elucidate the effects of NR3C1 methylation.