Putative transcriptomic biomarkers in the inflammatory cytokine pathway differentiate major depressive disorder patients from control subjects and bipolar disorder patients

Common changes in rat cortical gene expression after valproate or lithium treatment particularly affect pre- and post-synaptic pathways that regulate four neurotransmitters systems

OBJECTIVES

We have postulated that common changes in gene expression after treatment with different therapeutic classes of psychotropic drugs contribute to their common therapeutic mechanisms of action.

METHODS

To test this hypothesis, we measured levels of cortical coding and non-coding RNA using GeneChip® Rat Exon 1.0 ST Array after treatment with vehicle (chow only), chow containing 1.8 g lithium carbonate/kg (n = 10) or chow containing 12 g sodium valproate/kg (n = 10) for 28 days. Differences in levels of RNA were identified using JMP Genomics 13 and the Panther Gene Ontology Classification System was used to identify potential consequences of RNA.

RESULTS

Compared to vehicle treatment, levels of cortical RNA for 543 and 583 coding and non-coding RNAs were different after treatment with valproate and lithium, respectively. Moreover, levels of 323 coding and non-coding RNAs were altered in a highly correlated way by treatment with valproate and lithium, changes that would impact on cholinergic, glutamatergic, serotonergic and dopaminergic neurotransmission as well as on voltage gated ion channels.

CONCLUSIONS

Our study suggests that treating with mood stabilisers cause many common changes in levels of RNA which will impact on CNS function, particularly affecting post-synaptic muscarinic receptor functioning and the release of multiple neurotransmitters.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Serum CC Chemokines as Potential Biomarkers for the Diagnosis of Major Depressive Disorder

Objective

Evidence indicates a potential role of chemokines in depression-like behavior and depression-related pathophysiological processes. In the present study, we examined the serum levels of multiple chemokines, focusing on CC chemokines, in patients with major depressive disorder (MDD), with the aim to discover and identify serum chemokines-based biomarkers for MDD diagnosis.

Methods

Participants included 24 patients with MDD and 24 healthy controls. The 24-item Hamilton Depression Rating Scale (HAMD-24) was administered to assess the disease severity of patients with MDD. A total of 9 serum CC chemokines including MCP-1 (CCL-2), MIP-1α (CCL-3), MIP-1β (CCL-4), eotaxin-1 (CCL-11), MCP-4 (CCL-13), TARC (CCL-17), MIP-3α (CCL-20), MDC (CCL-22), and Eotaxin-3 (CCL-26) were measured using electrochemiluminescence immunoassays. The levels of serum CC chemokines between MDD group and control group were compared, and diagnostic values of different CC chemokines were evaluated using the receiver operating characteristic (ROC) curve method for discriminating MDD patients from healthy controls. Correlations between the levels of serum CC chemokines and depression severity (HAMD-24 scores) were evaluated using Pearson's correlation test.

Results

Patients with MDD had higher levels of serum MIP-1α and MIP-1β and lower levels of serum MCP-1, MCP-4, TARC, MDC, and Eotaxin-3 compared to controls (all P < 0.05). Moreover, ROC curve analysis showed that the Area Under Curve (AUC) values of MIP-1α, MCP-4, TARC, and Eotaxin-3 were > 0.7 in discriminating patients with MDD from healthy controls. Furthermore, no significant relationship was found between the levels of serum CC chemokines and HAMD-24 scores in MDD group.

Conclusion

These results suggested that circulating CC chemokines may hold promise in the discovery of biomarkers for diagnosing MDD.

Investigating data-driven biological subtypes of psychiatric disorders using specification-curve analysis

BACKGROUND

Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results.

METHODS

Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes.

RESULTS

The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased.

CONCLUSION

SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients.

Classification of Psychoses Based on Immunological Features: A Machine Learning Study in a Large Cohort of First-Episode and Chronic Patients

For several years, the role of immune system in the pathophysiology of psychosis has been well-recognized, showing differences from the onset to chronic phases. Our study aims to implement a biomarker-based classification model suitable for the clinical management of psychotic patients. A machine learning algorithm was used to classify a cohort of 362 subjects, including 160 first-episode psychosis patients (FEP), 70 patients affected by chronic psychiatric disorders (schizophrenia, bipolar disorder, and major depressive disorder) with psychosis (CRO) and 132 health controls (HC), based on mRNA transcript levels of 56 immune genes. Models distinguished between FEP, CRO, and HC and between the subgroup of drug-free FEP and HC with a mean accuracy of 80.8% and 90.4%, respectively. Interestingly, by using the feature importance method, we identified some immune gene transcripts that contribute most to the classification accuracy, possibly giving new insights on the immunopathogenesis of psychosis. Therefore, our results suggest that our classification model has a high translational potential, which may pave the way for a personalized management of psychosis.

Neuroinflammation as a Common Denominator of Complex Diseases (Cancer, Diabetes Type 2, and Neuropsychiatric Disorders)

The term neuroinflammation refers to inflammation of the nervous tissue, in general, and in the central nervous system (CNS), in particular. It is a driver of neurotoxicity, it is detrimental, and implies that glial cell activation happens prior to neuronal degeneration and, possibly, even causes it. The inflammation-like glial responses may be initiated in response to a variety of cues such as infection, traumatic brain injury, toxic metabolites, or autoimmunity. The inflammatory response of activated microglia engages the immune system and initiates tissue repair. Through translational research the role played by neuroinflammation has been acknowledged in different disease entities. Intriguingly, these entities include both those directly related to the CNS (commonly designated neuropsychiatric disorders) and those not directly related to the CNS (e.g., cancer and diabetes type 2). Interestingly, all the above-mentioned entities belong to the same group of "complex disorders". This review aims to summarize cumulated data supporting the hypothesis that neuroinflammation is a common denominator of a wide variety of complex diseases. We will concentrate on cancer, type 2 diabetes (T2DM), and neuropsychiatric disorders (focusing on mood disorders).

Serum levels of chemokines in adolescents with major depression treated with fluoxetine

BACKGROUND

Major depressive disorder (MDD) is a global health issue that affects 350 million people of all ages. Although between 2% and 5.6% of affected individuals are adolescents, research on young patients is limited. The inflammatory response contributes to the onset of depression, and in adult MDD patients, symptom severity has been linked to chemokine levels.

AIM

To determine the differences in circulatory levels of chemokines in healthy volunteers (HVs) and adolescents with MDD, and assess the changes induced by fluoxetine consume.

METHODS

The 22 adolescents with MDD were monitored during the first 8 wk of clinical follow-up and clinical psychiatric evaluation was done using the Hamilton depresión rating scale (HDRS). The serum levels of monocyte chemoattractant protein-1 (MCP-1), macrophage inflammatory protein (MIP)-1α, MIP-1β, interleukin (IL)-8, interferon gamma-induced protein (IP)-10, and eotaxin were measured in patients and HVs.

RESULTS

In all cases, significant differences were detected in circulating chemokine levels between patients before treatment and HVs (P < 0.0001). All chemokines decreased at 4 wk, but only MCP-1 and IL-8 significantly differed (P < 0.05) between 0 wk and 4 wk. In the patients, all chemokines rose to their initial concentrations by 8 wk vs 0 wk, but only IP-10 did so significantly (P < 0.05). All patients experienced a significant decrease in HDRS scores at 4 wk (P < 0.0001) and 8 wk (P < 0.0001) compared with 0 wk.

CONCLUSION

Despite the consumption of fluoxetine, patients had significantly higher chemokine levels, even after considering the improvement in HDRS score. The high levels of eotaxin, IP-10, and IL-8 partially explain certain aspects that are affected in MDD such as cognition, memory, and learning.

Low cardiac vagal tone index by heart rate variability differentiates bipolar from major depression

Objectives: Major depressive disorder (MDD) and depression in bipolar disorder (BD) are often difficult to distinguish from each other. Autonomic nervous system (ANS) dysregulation is associated with various depressive symptoms and inflammatory response disinhibition. The beat-to-beat pattern of heart rate (heart rate variability, HRV) offers a non-invasive portal to ANS function and provides a reliable index of resting cardiac vagal tone. We quantified HRV and measured inflammatory biomarkers in MDD and BD patients in an effort to derive potential diagnostic criteria for MDD and BD. Methods: Sixty-four MDD and 37 BD patients were enrolled. HRV was assessed and blood was drawn at baseline after antidepressant washout and prior to study initiation. HRV was quantified and corrected for artefacts. Results: MDD subjects had significantly higher baseline respiratory sinus arrhythmia (P = 0.05) and LF-HRV (P < 0.01) in comparison to BD subjects. Compared to MDD subjects, BD subjects had significantly higher baseline levels of IL-10 (P < 0.01) and MCP-1 (P < 0.01). In the MDD group only, baseline LF-HRV was significantly positively correlated to baseline levels of IL-10 (r = 0.47, P < 0.01). Conclusions: Reduced vagal tone and higher levels of inflammatory biomarkers may distinguish BD from MDD and reveal an underlying pathophysiology of depression involving ANS dysfunction and chronic immune system dysregulation.

Role of inflammation in depression relapse

Major depressive disorder (MDD) is a leading cause of disability worldwide. After the first episode, patients with remitted MDD have a 60% chance of experiencing a second episode. Consideration of therapy continuation should be viewed in terms of the balance between the adverse effects of medication and the need to prevent a possible relapse. Relapse during the early stages of MDD could be prevented more efficiently by conducting individual risk assessments and providing justification for continuing therapy. Our previous work established the neuroimaging markers of relapse by comparing patients with recurrent major depressive disorder (rMDD) in depressive and remitted states. However, it is not known which of these markers are trait markers that present before initial relapse and, consequently, predict disease course. Here, we first describe how inflammation can be translated to subtype-specific clinical features and suggest how this could be used to facilitate clinical diagnosis and treatment. Next, we address the central and peripheral functional state of the immune system in patients with MDD. In addition, we emphasize the important link between the number of depressive episodes and rMDD and use neuroimaging to propose a model for the latter. Last, we address how inflammation can affect brain circuits, providing a possible mechanism for rMDD. Our review suggests a link between inflammatory processes and brain region/circuits in rMDD.

Reduced CXCL1/GRO chemokine plasma levels are a possible biomarker of elderly depression

BACKGROUND

Depression is the single largest contributor to non-fatal health loss worldwide. A role of inflammation in major depressive disorder (MDD) was suggested, and we sought to determine if cytokine levels predict the severity of depressive symptomatology or distinguish MDD patients from healthy controls (HCs).

METHODS

The severity of depressive symptoms and cognitive impairment were assessed by the Korean version of the Geriatric Depression Scale (GDS-K) and Mini-Mental State Examination (MMSE-KC) in 152 elderly subjects (76 with MDD). Plasma levels of 28 cytokines were measured and analysed as continuous predictors or dichotomized using the median value. The association between individual cytokines, MDD risk and depressive symptoms severity was investigated using multiple logistic and linear regressions that included the relevant covariates. A Cytokine Weighted Score (CWS) was calculated by weighting cytokines according to previously reported effect sizes on MDD risk. Sensitivity analyses were performed excluding subjects with significant cognitive impairment.

RESULTS

CXCL10/IP-10 levels were higher in subjects with MDD vs. HCs while the opposite was observed for CXCL1/GRO. Only the second association survived after adjusting for possible confounders and excluding subjects with severe cognitive impairment. Using dichotomized cytokine levels, CXCL1/GRO and TNF-α were negatively associated with MDD. The CWS was also negatively associated with MDD. Cytokine levels did not predict the severity of depressive symptoms.

LIMITATIONS

Our cross-sectional approach was not able to longitudinally evaluate any temporal fluctuations in the considered cytokine levels.

CONCLUSIONS

This study found significantly lower CXCL1/GRO chemokine plasma levels in elderly subjects with MDD compared to HCs.

Genetic biomarkers for differential diagnosis of major depressive disorder and bipolar disorder: A systematic and critical review

Depressive symptoms are present in the depressive mood state of bipolar disorder (BPD) and major depression disorder (MDD). Often, in clinical practice, BPD patients are misdiagnosed with MDD. Therefore, genetic biomarkers could contribute to the improvement of differential diagnosis between BPD and MDD. This systematic and critical review aimed to find in literature reliable genetic biomarkers that may show differences between BPD and MDD. This systematic review followed the PRISMA-P method. The terms used to search PubMed, Scopus, PsycINFO, and Web of Science were depress*, bipolar, diagnos*, genetic*, biomark*. After applying the selection criteria, N = 27 studies were selected, being n = 9 about biomarkers for BPD; n = 15, about MDD; and n = 3 for distinguishing MDD from BPD. A total of N = 3086 subjects were assessed in the selected studies (n = 486 in BPD group; n = 1212 in MDD group; and n = 1388, healthy control group). The articles were dated up to June 2017. Of the N = 27 studies, n = 16 assessed gene, n = 1 miRNA, n = 2 lcnRNA and n = 3 protein expressions, n = 4 methylation, and n = 4 polymorphisms. Some studies applied more than one of these genetic analyses. To find reliable genetic biomarkers we have taken into account the methodological care during the studies development and their validity. The genetic biomarkers selected are related to genes that play a fundamental role in synaptic plasticity, neurogenesis, mood control, brain ageing, immune-inflammatory processes and mitochondrial respiratory chain. BDNF gene expression was one of the genetic biomarkers that highlighted because of its capacity of distinguishing BPD and MDD groups, and being adequately reproduced by more than one selected study.

Blood-based dynamic genomic signature for obsessive-compulsive disorder

No biologically based diagnostic criteria are in clinical use today for obsessive-compulsive disorder (OCD), schizophrenia, and major depressive disorder (MDD), which are defined with reference to Diagnostic and Statistical Manual clinical symptoms alone. However, these disorders cannot always be well distinguished on clinical grounds and may also be comorbid. A biological blood-based dynamic genomic signature that can differentiate among OCD, MDD, and schizophrenia would therefore be of great utility. This study enrolled 77 patients with OCD, 67 controls with no psychiatric illness, 39 patients with MDD, and 40 with schizophrenia. An OCD-specific gene signature was identified using blood gene expression analysis to construct a predictive model of OCD that can differentiate this disorder from healthy controls, MDD, and schizophrenia using a logistic regression algorithm. To verify that the genes selected were not derived as a result of chance, the algorithm was tested twice. First, the algorithm was used to predict the cohort with true disease/control status and second, the algorithm predicted the cohort with disease/control status randomly reassigned (null set). A six-gene panel (COPS7A, FKBP1A, FIBP, TP73-AS1, SDF4, and GOLGA8A) discriminated patients with OCD from healthy controls, MDD, and schizophrenia in the training set (with an area under the receiver-operating-characteristic curve of 0.938; accuracy, 86%; sensitivity, 88%; and specificity, 85%). Our findings indicate that a blood transcriptomic signature can distinguish OCD from healthy controls, MDD, and schizophrenia. This finding further confirms the feasibility of using dynamic blood-based genomic signatures in psychiatric disorders and may provide a useful tool for clinical staff engaged in OCD diagnosis and decision making.

Role of the IL-6-Receptor expression in CD14+ monocytes in modulating sleep in patients with bipolar disorder

OBJECTIVE

Bipolar disorder is a severe mental disorder associated with persistent sleep disturbances and elevated levels of mRNA coding for pro-inflammatory cytokines within peripheral monocytes. The mechanisms causing and sustaining a reduced sleep quality remain elusive. The pro-inflammatory cytokine receptor IL-6R is known to negatively affect sleep quality and architecture. Since elevations in IL-6R have repeatedly been demonstrated in bipolar disorder the association of sleep quality and architecture with levels of mRNA coding for IL-6R in monocytes was to be tested.

METHODS

Euthymic patients with bipolar disorder (n = 24) and healthy control subjects (n = 25) were assessed using all night polysomnography (PSG) and six day actigraphy. CD14+ monocytes were isolated on the evening of PSG assessment and levels of mRNA coding for IL-6R and other cytokines were determined using hybridization based assays. Interactions between IL-6R and sleep measures were calculated using linear regression models, adjusting for potential confounders.

RESULTS

Patients with bipolar disorder were found to have a reduced subjective sleep quality as assessed by the Pittsburgh Sleep Quality Index (PSQI) and more frequent arousals and short changes to wake during sleep. Both PSQI and the frequency of arousals were significantly predicted by levels of IL-6R. Contrary to previous publications, elevated levels of mRNA coding for pro-inflammatory cytokines in peripheral CD14+ monocytes of patients with bipolar disorder could not be replicated.

LIMITATIONS

Participants were only investigated with one night of PSG which may have given rise to first night effects.

CONCLUSIONS

Reduced sleep quality in euthymic patients with bipolar disorder may be related to an increased expression of IL-6R by peripheral monocytes.

Approaching to the Essence of Major Depressive Disorder

Major Depressive Disorder (MDD) is a serious neuropsychic disease. It destroys person’s family relationship and social connections seriously. Latest WHO investigation disclosed nearly 4.4% of the population worldwide (approximately 322 million people) were being affected by MDD extensively [1]. While in China, Dong M, et al. reported the occurrence rate of suicide attempt during hospitalization and after the onset of MDD were 17.3% (95% CI: 12.4-23.7%) and 42.1% (95% CI: 26.1-60.0%) respectively [2]. Another research made by Grupta S, et al. announced MDD in urban China might be under-diagnosed and untreated [3].

Distinct characteristics of hippocampal pathogenic TH17 cells in a mouse model of depression

Increasing evidence indicates that multiple actions of the immune system are closely intertwined with the development of depression and subsequent recovery processes. One of these interactions is substantial evidence that the TH17 subtype of CD4+ T cells promotes susceptibility to depression-like behaviors in mice. Comparing subtypes of CD4+ T cells, we found that administration of TH17 cells, but not TH1 cells or TREGS, promoted susceptibility to learned-helplessness depressive-like behavior and accumulated in the hippocampus of learned helpless mice. Adoptively transferred TH17 cells into Rag2-/- mice that are devoid of endogenous T cells increased susceptibility to learned helplessness, demonstrating that increased peripheral TH17 cells are capable of modulating depression-like behavior. Moreover, in wild-type mice, adoptively transferred TH17 cells accumulated in the hippocampus of learned-helpless mice and induced endogenous TH17 cell differentiation. Hippocampal TH17 cells from learned-helpless mice expressed markers of pathogenic TH17 cells (CCR6, IL-23R) and of follicular cells (CXCR5, PD-1), indicating that the hippocampal cells are TFH-17-like cells. Knockout of CCR6 blocked TH17 cells from promoting learned helplessness, which was associated with increased expression of PD-1 in CCR6-deficient TH17 cells. In summary, these results reinforce the conclusion that depression-like behaviors are selectively facilitated by TH17 cells, and revealed that these cells in the hippocampus of learned helpless mice display characteristics of TFH17-like cells, which may contribute to their pathogenic actions in promoting depression.

Differentially expressed genes related to major depressive disorder and antidepressant response: genome-wide gene expression analysis

Treatment response to antidepressants is limited and varies among patients with major depressive disorder (MDD). To discover genes and mechanisms related to the pathophysiology of MDD and antidepressant treatment response, we performed gene expression analyses using peripheral blood specimens from 38 MDD patients and 14 healthy individuals at baseline and at 6 weeks after the initiation of either selective serotonin reuptake inhibitor (SSRI) or mirtazapine treatment. The results were compared with results from public microarray data. Seven differentially expressed genes (DEGs) between MDD patients and controls were identified in our study and in the public microarray data: CD58, CXCL8, EGF, TARP, TNFSF4, ZNF583, and ZNF587. CXCL8 was among the top 10 downregulated genes in both studies. Eight genes related to SSRI responsiveness, including BTNL8, showed alterations in gene expression in MDD. The expression of the FCRL6 gene differed between SSRI responders and nonresponders and changed after SSRI treatment compared to baseline. In evaluating the response to mirtazapine, 21 DEGs were identified when comparing MDD patients and controls and responders and nonresponders. These findings suggest that the pathophysiology of MDD and treatment response to antidepressants are associated with a number of processes, including DNA damage and apoptosis, that can be induced by immune activation and inflammation.

Differences in the expression of several genes before and after different antidepressant treatments were found in patients with major depressive disorder (MDD), and may help identify patients most likely to benefit from specific drugs. Researchers in South Korea led by Doh Kwan Kim and Soo-Youn Lee at Samsung Medical Center, Seoul, examined gene expression across the 28,869 genes in 38 patients with MDD and 14 healthy individuals. They also validated their findings using existing databases of gene expression in patients with MDD and healthy controls. The research suggests that genes involved in the immune response and inflammation are significantly alternated in MDD and are predictable in which patients respond well to antidepressants. These findings may help develop new approaches to antidepressant therapies, and assist tailoring of treatment to the specific needs of different patients.

T Cell Phenotype and T Cell Receptor Repertoire in Patients with Major Depressive Disorder

While a link between inflammation and the development of neuropsychiatric disorders, including major depressive disorder (MDD) is supported by a growing body of evidence, little is known about the contribution of aberrant adaptive immunity in this context. Here, we conducted in-depth characterization of T cell phenotype and T cell receptor (TCR) repertoire in MDD. For this cross-sectional case–control study, we recruited antidepressant-free patients with MDD without any somatic or psychiatric comorbidities (n = 20), who were individually matched for sex, age, body mass index, and smoking status to a non-depressed control subject (n = 20). T cell phenotype and repertoire were interrogated using a combination of flow cytometry, gene expression analysis, and next generation sequencing. T cells from MDD patients showed significantly lower surface expression of the chemokine receptors CXCR3 and CCR6, which are known to be central to T cell differentiation and trafficking. In addition, we observed a shift within the CD4⁺ T cell compartment characterized by a higher frequency of CD4⁺CD25^highCD127^low/− cells and higher FOXP3 mRNA expression in purified CD4⁺ T cells obtained from patients with MDD. Finally, flow cytometry-based TCR Vβ repertoire analysis indicated a less diverse CD4⁺ T cell repertoire in MDD, which was corroborated by next generation sequencing of the TCR β chain CDR3 region. Overall, these results suggest that T cell phenotype and TCR utilization are skewed on several levels in patients with MDD. Our study identifies putative cellular and molecular signatures of dysregulated adaptive immunity and reinforces the notion that T cells are a pathophysiologically relevant cell population in this disorder.

Metabolomics of Major Depressive Disorder and Bipolar Disorder: Overview and Future Perspective

Major depressive disorder (MDD) and bipolar disorder (BD) are the most common mood disorders. They are etiologically related, but clinically distinct psychiatric illnesses. Their shared clinical features result in high rates of misdiagnosis due to a lack of biomarkers that allow their differentiation. BD is more frequently misdiagnosed as MDD because of overlapping symptomology, often later onset of mania, and frequent occurrence of depressive episodes in patients with BD. Misdiagnosis is also increased when patients with BD present symptoms indicative of a clinically significant depressive episode, but are premorbid for manic symptoms, or previous manic states not recognized. Therefore, the development of specific biomarkers for these disorders would be invaluable for establishing the correct diagnosis and treatment of MDD and BD. This chapter presents an overview and future perspective of the identification of biomarkers for mood disorders using metabolomics.

A multispecies approach for understanding neuroimmune mechanisms of stress

The relationship between stress challenges and adverse health outcomes, particularly for the development of affective disorders, is now well established. The highly conserved neuroimmune mechanisms through which responses to stressors are transcribed into effects on males and females have recently garnered much attention from researchers and clinicians alike. The use of animal models, from mice to guinea pigs to primates, has greatly increased our understanding of these mechanisms on the molecular, cellular, and behavioral levels, and research in humans has identified particular brain regions and connections of interest, as well as associations between stress-induced inflammation and psychiatric disorders. This review brings together findings from multiple species in order to better understand how the mechanisms of the neuroimmune response to stress contribute to stress-related psychopathologies, such as major depressive disorder, schizophrenia, and bipolar disorder.

A systematic review of evidence for the role of inflammatory biomarkers in bipolar patients

Bipolar disorder (BD) is a neuropsychiatric disorder that is characterized by a phasic course of affective episodes interspersed with a euthymic state. Epidemiological, clinical, genetic, post-mortem and preclinical studies have shown that inflammatory reactions and immune modulation play a pivotal role in the pathophysiology of BD. It is conceptualized that biomarkers of inflammation and immune responses should be employed to monitor the disease process in bipolar patients. The objective of this systematic review is to analyse the inflammatory markers involved in human studies and to explore each individual marker for its potential clinical application and summarize evidence regarding their role in BD. A systematic review of human studies to measure inflammatory markers was conducted, and the studies were identified by searching PubMed/MEDLINE, PsycINFO, EMBASE, and Web of Science databases for peer-reviewed journals that were published until September 2015. In this review, we included peripheral markers, genetic, post-mortem and cell studies with inflammatory biomarker analysis in BD. One hundred and two (102) papers met the inclusion criteria. The pro-inflammatory cytokines were elevated and the anti-inflammatory cytokines were reduced in BD patients, particularly during manic and depressive phases when compared to the controls. These changes tend to disappear in euthymia, indicating that inflammation may be associated with acute phases of BD. Even though there are promising findings in this field, further clinical studies using more established detection techniques are needed to clearly show the benefit of using inflammatory markers in the diagnosis, follow-up and prognosis of patients with BD.

[Nutrition and mental diseases : Focus depressive disorders]

Dietary interventions are currently being discussed as additional treatment options for mental disorders. The pathological mechanisms are not yet fully understood. It is hypothesized that certain nutrients and dietary pattern influence immune and inflammatory processes, the microbiome, the leptin-melanocortinergic axis and hypothalamic-pituitary axis, as well as neurotransmitters of the cholinergic, noradrenergic, dopaminergic and serotonergic signaling cascades and neurotrophins. Observational studies have shown that traditional dietary patterns, such as the Mediterranean diet have a protective effect on mental health. Supplementation with long-chain polyunsaturated omega-3 fatty acids showed small to medium but significant effect sizes in meta-analyses from depression trials. The evidence with respect to the antidepressive effect of vitamin D supplementation is currently inconclusive.

A multispecies approach for understanding neuroimmune mechanisms of stress

The relationship between stress challenges and adverse health outcomes, particularly for the development of affective disorders, is now well established. The highly conserved neuroimmune mechanisms through which responses to stressors are transcribed into effects on males and females have recently garnered much attention from researchers and clinicians alike. The use of animal models, from mice to guinea pigs to primates, has greatly increased our understanding of these mechanisms on the molecular, cellular, and behavioral levels, and research in humans has identified particular brain regions and connections of interest, as well as associations between stress-induced inflammation and psychiatric disorders. This review brings together findings from multiple species in order to better understand how the mechanisms of the neuroimmune response to stress contribute to stress-related psychopathologies, such as major depressive disorder, schizophrenia, and bipolar disorder.

Blood-based immune-endocrine biomarkers of treatment response in depression

Antidepressant treatment for major depressive disorder remains suboptimal with response rates of just over 50%. Although treatment guidelines, algorithms and clinical keys are available to assist the clinician, the process of finding an effective pharmacotherapy to maximise benefit for the individual patient is largely by "trial and error" and remains challenging. This highlights a clear need to identify biomarkers of treatment response to help guide personalised treatment strategies. We have carried out the largest multiplex immunoassay based longitudinal study to date, examining up to 258 serum markers involved in immune, endocrine and metabolic processes as potential biomarkers associated with treatment response in 332 depression patients recruited from four independent clinical centres. We demonstrated for the first time that circulating Apolipoprotein A-IV, Endoglin, Intercellular Adhesion Molecule 1, Tissue Inhibitor of Metalloproteinases 1, Plasminogen Activator Inhibitor 1, Thrombopoietin, Complement C3, Hepatocyte Growth Factor and Insulin-like Growth Factor-Binding Protein 2 were associated with response to different antidepressants. In addition, we showed that specific sets of immune-endocrine proteins were associated with response to Venlafaxine (serotonin-norepinephrine reuptake inhibitor), Imipramine (tricyclic antidepressant) and other antidepressant drugs. However, we were not able to reproduce the literature findings on BDNF and TNF-α, two of the most commonly reported candidate treatment response markers. Despite the need for extensive validation studies, our preliminary findings suggest that a pre-treatment immune-endocrine profile may help to determine a patient's likelihood to respond to specific antidepressant and/or alternative treatments such as anti-inflammatory drugs, providing hope for future personalised treatment approaches.

Immune signatures and disorder-specific patterns in a cross-disorder gene expression analysis

BACKGROUND

Recent studies point to overlap between neuropsychiatric disorders in symptomatology and genetic aetiology.

AIMS

To systematically investigate genomics overlap between childhood and adult attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and major depressive disorder (MDD).

METHOD

Analysis of whole-genome blood gene expression and genetic risk scores of 318 individuals. Participants included individuals affected with adult ADHD (n = 93), childhood ADHD (n = 17), MDD (n = 63), ASD (n = 51), childhood dual diagnosis of ADHD-ASD (n = 16) and healthy controls (n = 78).

RESULTS

Weighted gene co-expression analysis results reveal disorder-specific signatures for childhood ADHD and MDD, and also highlight two immune-related gene co-expression modules correlating inversely with MDD and adult ADHD disease status. We find no significant relationship between polygenic risk scores and gene expression signatures.

CONCLUSIONS

Our results reveal disorder overlap and specificity at the genetic and gene expression level. They suggest new pathways contributing to distinct pathophysiology in psychiatric disorders and shed light on potential shared genomic risk factors.

Role of neuro-immunological factors in the pathophysiology of mood disorders

Mood disorders, despite the widespread availability of monoamine-based antidepressant treatments, are associated with persistently high rates of disability, together with elevated rates of mortality due to suicide, cardiovascular disease, and other causes. The development of more effective treatments has been hindered by the lack of knowledge about the etiology and pathogenesis of mood disorders. An emerging area of science that promises novel pathways to antidepressant and mood stabilizing therapies surrounds evidence that immune cells and their signaling play a major role in the pathophysiology of major depressive disorder (MDD) and bipolar disorder (BD). Here, we review evidence that the release of neuroactive cytokines, particularly interleukins such as IL-1β, IL-6, and TNF-α, is altered in these disorders and discuss mechanisms such as the ATP-gated ion channel P2X7, through which cytokine signaling can influence neuro-glial interactions. Brain P2X7, an emerging target and antagonism of P2X7 holds promise as a novel mechanism for targeting treatment-resistant depression. We further discuss the role of microglia and astroglia in central neuroinflammation and their interaction with the peripheral immune system We present extant clinical evidence that bolsters the role of neuroinflammation and neuroactive cytokines in mood disorders. To that end, the role of clinical imaging by probing neuroinflammatory markers is also discussed briefly. Finally, we present data using preclinical neuroinflammation models that produce depression-like behaviors in experimental animals to identify neuroinflammatory mechanisms which may aid in novel neuroimmune target identification for the development of exciting pharmacological interventions in mood disorders.

An altered peripheral IL6 response in major depressive disorder

Major depressive disorder (MDD) is one of the most prevalent major psychiatric disorders with a lifetime prevalence of 17%. Recent evidence suggests MDD is not only a brain dysfunction, but a systemic disease affecting the whole body. Central and peripheral inflammatory changes seem to be a centerpiece of MDD pathology: a subset of patients show elevated blood cytokine and chemokine levels that partially normalize with symptom improvement over the course of anti-depressant treatment. As this inflammatory process in MDD is poorly understood, we hypothesized that the peripheral tissues of MDD patients will respond differently to inflammatory stimuli, resulting in an aberrant transcriptional response to elevated pro-inflammatory cytokines. To test this, we used MDD patient- and control-derived dermal fibroblast cultures to investigate their response to an acute treatment with IL6, IL1β, TNFα, or vehicle. Following RNA isolation and subsequent cDNA synthesis, quantitative PCR was used to determine the relative expression level of several families of inflammation-responsive genes. Our results showed comparable expression of the tested genes between MDD patients and controls at baseline. In contrast, MDD patient fibroblasts had a diminished transcriptional response to IL6 in all the gene sets tested (oxidative stress response, mitochondrial function, and lipid metabolism). We also found a significant increase in baseline and IL6 stimulated transcript levels of the IL6 receptor gene. This IL6 receptor transcript increase in MDD fibroblasts was accompanied by an IL6 stimulated increase in induction of SOCS3, which dampens IL6 receptor signaling. Altogether our results demonstrate that there is an altered transcriptional response to IL6 in MDD, which may represent one of the molecular mechanisms contributing to disease pathophysiology. Ultimately we hope that these studies will lead to validation of novel MDD drug targets focused on normalizing the altered IL6 response in patients.

Role of Neuro-Immunological Factors in the Pathophysiology of Mood Disorders: Implications for Novel Therapeutics for Treatment Resistant Depression

Mood disorders are associated with persistently high rates of morbidity and mortality, despite the widespread availability of antidepressant treatments. One limitation to extant therapeutic options has been that nearly all approved antidepressant pharmacotherapies exert a similar primary action of blocking monoamine transporters, and few options exist for transitioning treatment resistant patients to alternatives with distinct mechanisms. An emerging area of science that promises novel pathways to antidepressant and mood-stabilizing therapies has followed from evidence that immunological factors play major roles in the pathophysiology of at least some mood disorder subtypes. Here we review evidence that the compounds that reduce the release or signaling of neuroactive cytokines, particularly IL-1β, IL-6, and TNF-α, can exert antidepressant effects in subgroups of depressed patients who are identified by blood-based biomarkers associated with inflammation. Within this context we discuss the role of microglia in central neuroinflammation, and the interaction between the peripheral immune system and the central synaptic microenvironment during and after neuroinflammation. Finally we review data using preclinical neuroinflammation models that produce depression-like behaviors in experimental animals to guide the discovery of novel neuro-immune drug targets.

A Potential Contribution of Chemokine Network Dysfunction to the Depressive Disorders

In spite of many years of research, the pathomechanism of depression has not yet been elucidated. Among many hypotheses, the immune theory has generated a substantial interest. Up till now, it has been thought that depression is accompanied by the activation of inflammatory response and increase in pro-inflammatory cytokine levels. However, recently this view has become controversial, mainly due to the family of small proteins called chemokines. They play a key role in the modulation of peripheral function of the immune system by controlling immune reactions, mediating immune cell communication, and regulating chemotaxis and cell adhesion. Last studies underline significance of chemokines in the central nervous system, not only in the neuromodulation but also in the regulation of neurodevelopmental processes, neuroendocrine functions and in mediating the action of classical neurotransmitters. Moreover, it was demonstrated that these proteins are responsible for maintaining interactions between neuronal and glial cells both in the developing and adult brain also in the course of diseases. This review outlines the role of chemokine in the central nervous system under physiological and pathological conditions and their involvement in processes underlying depressive disorder. It summarizes the most important data from experimental and clinical studies.

Multiplex immunoassay analysis of plasma shows differences in biomarkers related to manic or mixed mood states in bipolar disorder patients

BACKGROUND

The molecular understanding of bipolar disorder (BD) aetiology has advanced over the last years through the identification of peripheral disease biomarkers. Here, we have attempted to identify plasma biomarkers associated with distinct BD mood states.

METHODS

Plasma from BD patients with either a current manic (n=29) or mixed (n=17) mood state and healthy controls (n=53) were analysed using a multiplex immunoassay platform. A total of 145 hormones, growth factors, transport proteins and inflammatory factors were measured.

RESULTS

Plasma levels of the hormones C-peptide, progesterone and insulin, and the inflammatory protein cancer antigen 125 were altered in both mood states. The hormone peptide YY and the growth factor trafficking protein sortilin were changed only in mania patients. Finally, the inflammatory factors haptoglobin, chemokine CC4 and matrix metalloproteinase 7 were altered specifically in mixed mood patients.

LIMITATIONS

This study was limited by a small sample size, potential confounding effects of multiple drug treatments in the patient groups, and lack of dietary restrictions at sampling.

CONCLUSIONS

Plasma from mania and mixed mood BD patients revealed similar changes in proteins related to insulin signalling, suggesting that these could be trait biomarkers. However, mania patients showed specific changes in hormonal and growth factor functions and mixed mood patients had a higher number of changes in inflammation-related molecules. Further studies of these and other biomarker candidates will increase our understanding of the systemic biological pathways affected in different BD mood states. This could lead to the identification of differential surrogate readouts and potential new drug targets for improved treatment outcomes.

The promise of biomarkers in diagnosing major depression in primary care: the present and future

Major depressive disorder (MDD) is the most prevalent psychiatric disorder, but it can be underdiagnosed or misdiagnosed. Most people with depression are seen in primary care settings, where there are limited resources to diagnose and treat the patient. There is a lack of clinically validated objective laboratory-based diagnostic tests to diagnose MDD; however, it is clear that these tests could greatly improve the correct and timely diagnosis. This review aims to give a cross-sectional view of current efforts of DNA methylomic, transcriptomic, and proteomic approaches to identify biomarkers. We outline our view of the biomarker developmental steps from discovery to clinical application. We then propose that better cooperation will lead us closer to the common goal of identifying biological biomarkers for major depression. "The important thing is not to stop questioning. Curiosity has its own reason for existing." Albert Einstein.

Serum proteomic profiling of major depressive disorder

Much has still to be learned about the molecular mechanisms of depression. This study aims to gain insight into contributing mechanisms by identifying serum proteins related to major depressive disorder (MDD) in a large psychiatric cohort study. Our sample consisted of 1589 participants of the Netherlands Study of Depression and Anxiety, comprising 687 individuals with current MDD (cMDD), 482 individuals with remitted MDD (rMDD) and 420 controls. We studied the relationship between MDD status and the levels of 171 serum proteins detected on a multi-analyte profiling platform using adjusted linear regression models. Pooled analyses of two independent validation cohorts (totaling 78 MDD cases and 156 controls) was carried out to validate our top markers. Twenty-eight analytes differed significantly between cMDD cases and controls (P < 0.05), whereas 10 partly overlapping markers differed significantly between rMDD cases and controls. Antidepressant medication use and comorbid anxiety status did not substantially impact on these findings. Sixteen of the cMDD-related markers had been assayed in the pooled validation cohorts, of which seven were associated with MDD. The analytes prominently associated with cMDD related to diverse cell communication and signal transduction processes (pancreatic polypeptide, macrophage migration inhibitory factor, ENRAGE, interleukin-1 receptor antagonist and tenascin-C), immune response (growth-regulated alpha protein) and protein metabolism (von Willebrand factor). Several proteins were implicated in depression. Changes were more prominent in cMDD, suggesting that molecular alterations in serum are associated with acute depression symptomatology. These findings may help to establish serum-based biomarkers of depression and could improve our understanding of its pathophysiology.

A critical review of the efficacy of non-steroidal anti-inflammatory drugs in depression

Non-steroidal anti-inflammatory drugs (NSAIDs) require further investigation given mixed results regarding efficacy. We critically and systematically reviewed the literature to determine whether selective COX-2 and non-selective COX inhibitor NSAIDs as adjuncts or monotherapy affect depressive symptoms. Electronic databases including Embase, PsycINFO, Ovid Medline, ScienceDirect, Google Scholar and the Cochrane Central Register of Controlled Trials database were searched up to September 2013. We utilised randomised controlled trials (RCTs), cohort studies and an open label study examining the efficacy of NSAIDs as adjuncts or monotherapy on depressive symptoms in subjects without major comorbidities. There were a total of 6 studies exploring the efficacy of selective COX-2 inhibitor NSAIDs on depressive symptoms with a total of 2706 subjects from 6 RCTs. 4 of the RCTs showed a significant effect of NSAIDs; 2 demonstrated no effect. There were a total of 5 studies exploring the efficacy of non-selective COX inhibitor NSAIDs on depressive symptoms with a total of 7978 subjects. There was 1 RCT, 3 cohort studies and 1 open label pilot study. The RCT failed to show a significant result. 1 of the retrospective cohort studies showed a positive result, with the other 2 showing no effect. The pilot study showed a positive result for NSAIDs. These studies demonstrated significant methodological heterogeneity (i.e. age range, sex, presence of antidepressant use, method of depression measure, severity of depressive symptoms, duration and study design (RCT vs. cohort)). The efficacy of NSAIDs on depressive symptoms appears negligible, however firm conclusions are difficult given the inconsistent findings and substantial methodological heterogeneity. Further high quality research is needed to explore NSAID efficacy in clinical and biological subtypes of depression, as monotherapy and adjunct with various antidepressants, and across various ages.