Update on bipolar disorder biomarker candidates

Distinguishing functional and structural MRI abnormalities between bipolar and unipolar depression

Background

This study aims to investigate the underlying characteristics of spontaneous brain activity by analyzing the volumes of the hippocampus and parahippocampal gyrus, as well as the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), in order to differentiate between bipolar disorder (BD) and unipolar depressive disorder.

Methods

A total of 46 healthy controls, 58 patients with major depressive disorder (MDD), and 61 patients with BD participated in the study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. The researchers calculated the differences in volume, fALFF, and ReHo values among the three groups. Additionally, they conducted correlation analyses to examine the relationships between clinical variables and the aforementioned brain measures.

Results

The results showed that the BD group exhibited increased fALFF in the hippocampus compared to the healthy control (HC) and MDD groups. Furthermore, the ReHo values in the hippocampus and parahippocampal gyrus were significantly higher in the BD group compared to the HC group. The findings from the person correlation analysis indicated a positive relationship between ReHo values in the hippocampus and both HAMD and HAMA scores. Moreover, there was no correlation between the volumes, fALFF, and ReHo values in the hippocampus and parahippocampal gyrus, and cognitive function levels (RBANS).

Conclusion

Taken together, these aberrant patterns of intrinsic brain activity in the hippocampus and parahippocampal gyrus may serve as quantitative indicators for distinguishing between BD and unipolar depression.

Reward and punishment learning deficits among bipolar disorder subtypes

BACKGROUND

Reward sensitivity is an essential dimension related to mood fluctuations in bipolar disorder (BD), but there is currently a debate around hypersensitivity or hyposensitivity hypotheses to reward in BD during remission, probably related to a heterogeneous population within the BD spectrum and a lack of reward bias evaluation. Here, we examine reward maximization vs. punishment avoidance learning within the BD spectrum during remission.

METHODS

Patients with BD-I (n = 45), BD-II (n = 34) and matched (n = 30) healthy controls (HC) were included. They performed an instrumental learning task designed to dissociate reward-based from punishment-based reinforcement learning. Computational modeling was used to identify the mechanisms underlying reinforcement learning performances.

RESULTS

Behavioral results showed a significant reward learning deficit across BD subtypes compared to HC, captured at the computational level by a lower sensitivity to rewards compared to punishments in both BD subtypes. Computational modeling also revealed a higher choice randomness in BD-II compared to BD-I that reflected a tendency of BD-I to perform better during punishment avoidance learning than BD-II.

LIMITATIONS

Our patients were not naive to antipsychotic treatment and were not euthymic (but in syndromic remission) according to the International Society for Bipolar Disorder definition.

CONCLUSIONS

Our results are consistent with the reward hyposensitivity theory in BD. Computational modeling suggests distinct underlying mechanisms that produce similar observable behaviors, making it a useful tool for distinguishing how symptoms interact in BD versus other disorders. In the long run, a better understanding of these processes could contribute to better prevention and management of BD.

Endocan: A novel biomarker of endothelial dysfunction in depression?

Endocan is a proteoglycan secreted from endothelium upon endothelial damage. Since depression is associated with higher inflammation and oxidative stress to the vascular endothelium, endothelial dysfunction is prevalent and it is one of the responsible mechanisms for increased cardiovascular morbidity and mortality in depressive disorders. This study aimed to investigate endocan levels in patients with depression (either bipolar or unipolar) and healthy controls to evaluate the projected endothelial injury. We included nonsmoker patients without comorbid inflammatory conditions: 31 with Bipolar Disorder Depression (BDD), 30 with Major Depressive Disorder (MDD) and 25 healthy controls (HC). The severity of depression was assessed with the Hamilton Depression Rating Scale (HDRS). Ultimately, serum endocan levels were significantly higher in patients with BDD than in patients with MDD (p < .000) and HCs (p < .000). Also, patients with MDD had significantly higher endocan levels than HCs (p < .000). The AUC value for the endocan to differentiate patients with depression from controls was 0.990 (95% CI: 0.971-1.000; p < .001) with sensitivity and specificity of 98.4 and 100%, respectively, and an optimal cut-off value of 316.92 ng/L. Serum endocan levels showed a mild positive correlation with HDRS scores (r = 0.372, p = .039) in the BDD group but not in the MDD group (r = -0.242, p = .20). Patients with BDD had higher endocan levels than MDD; this finding, while preliminary, could be an implication of higher endothelial dysfunction in BDD.

Deep neural network to differentiate brain activity between patients with euthymic bipolar disorders and healthy controls during verbal fluency performance: A multichannel near-infrared spectroscopy study

In this study, we aimed to differentiate between euthymic bipolar disorder (BD) patients and healthy controls (HC) based on frontal activity measured by fNIRS that were converted to spectrograms with Convolutional Neural Networks (CNN). And also, we investigated brain regions that cause this distinction. In total, 29 BD patients and 28 HCs were recruited. Their brain cortical activities were measured using fNIRS while performing letter versions of VFT. Each one of the 24 fNIRS channels was converted to a 2D spectrogram on which a CNN architecture was designed and utilized for classification. We found that our CNN algorithm using fNIRS activity during a VFT is able to differentiate subjects with BD from healthy controls with 90% accuracy, 80% sensitivity, and 100% specificity. Moreover, validation performance reached an AUC of 94%. From our individual channel analyses, we observed channels corresponding to the left inferior frontal gyrus (left-IFC), medial frontal cortex (MFC), right dorsolateral prefrontal cortex (DLPFC), Broca area, and right premotor have considerable activity variation to distinguish patients from HC. fNIRS activity during VFT can be used as a potential marker to classify euthymic BD patients from HCs. Activity particularly in the MFC, left-IFC, Broca's area, and DLPFC have a considerable variation to distinguish patients from healthy controls.

The prevalence and associated clinical correlates of hyperuricemia in patients with bipolar disorder

Objective

The prevalence and clinically associated factors of hyperuricemia (HUA) have been widely studied in the general population but rarely in patients with bipolar disorder (BPD) co-morbid with HUA. This study attempted to investigate the prevalence of HUA in BPD patients and analyze the associated correlates of HUA.

Materials and methods

In this study, 182 outpatients with BPD and 182 healthy controls participated. The demographic and clinical information were collected. The body weight, height, waist circumference (WC), hip circumference (HC), and blood pressure (BP) were measured. The levels of serum uric acid (UA), triglyceride (TG), high-density lipoprotein (HDL-C), and fasting blood glucose (FBG) were also determined.

Results

BPD patients had a significantly higher prevalence of HUA (40.7%) compared to healthy controls (30.2%) (χ² = 4.335, P = 0.037). The systolic blood pressure (SBP), pulse pressure (PP), FBG, UA, and body mass index (BMI) were higher in the BPD group compared with those in the control group, while the diastolic blood pressure (DBP) and HDL-C level were lower (P < 0.05) in BPD patients. The prevalence of HUA was higher in BPD patients who used antipsychotics combined with mood stabilizers than that in BPD subjects receiving the mood stabilizers alone (P < 0.001). The prevalence of HUA and increased serum UA levels were higher in the manic group (62.1%) than in the depressive (34.3%) or euthymia group (17.0%) (P < 0.001). Additionally, the severity of mania was positively correlated with the UA level (r = 0.410, P < 0.001). There were significant differences in terms of MetS (29.7% vs. 14.8%), BMI, HC, WC, TG, and HDL-C between the HUA and the non-HUA groups (P < 0.05). The unconditional logistic regression analysis revealed that high BMI (OR = 1.210; 95%CI: 1.100–1.331) and high TG level (OR = 1.652; 95%CI: 1.058–2.580) were the major risk factorids for HUA in BPD patients.

Conclusion

Our study suggests that patients with BPD are prone to metabolic diseases such as HUA. Higher serum levels of TG and high BMI could be associated with HUA development. Clinicians need to regularly monitor and evaluate BPD patients for their serum UA levels, especially for BPD patients with manic/hypomanic episodes and/or under the treatment of antipsychotics combined with mood stabilizers.

Metabolomic Identification of Serum Exosome-Derived Biomarkers for Bipolar Disorder

Background

Exosomes are extracellular vesicles that play important roles in various physiological and pathological functions. Previous studies have demonstrated that exosome-derived contents are promising biomarkers to inform the pathogenesis and diagnosis of major depressive disorder and schizophrenia.

Methods

We used ultraperformance liquid chromatography-tandem mass spectrometry to analyze the differentially expressed metabolites in serum exosomes of patients with bipolar disorder (BD) and evaluated the potential of exosomal metabolites as biomarkers for BD.

Results

Our results showed 26 differentially expressed serum exosomal metabolites in patients with BD (n = 32) when compared with healthy control (HC) subjects (n = 40), and these differentially expressed metabolites were enriched in pathways related to sugar metabolism. We then utilized random forest classifier and identified 15 exosomal metabolites that can be used to classify samples from patients with BD and HC subjects with 0.838 accuracy (95% CI, 0.604–1.00) in the training set of participants. These 15 metabolites showed excellent performance in differentiating between patients with BD and HC subjects in the testing set of participants, with 0.971 accuracy (95% CI, 0.865–1.00). Importantly, the 15 exosomal metabolites also showed good to excellent performance in differentiating between BD patients and other major psychiatric diseases (major depressive disorder and schizophrenia).

Conclusion

Collectively, our findings for the first time revealed a potential role of exosomal metabolite dysregulations in the onset and/or development of BD and suggested that blood exosomal metabolites are strong candidates to inform the diagnosis of BD.

Distinguish bipolar and major depressive disorder in adolescents based on multimodal neuroimaging: Results from the Adolescent Brain Cognitive Development study®

Background

Major depressive disorder and bipolar disorder in adolescents are prevalent and are associated with cognitive impairment, executive dysfunction, and increased mortality. Early intervention in the initial stages of major depressive disorder and bipolar disorder can significantly improve personal health.

Methods

We collected 309 samples from the Adolescent Brain Cognitive Development study, including 116 adolescents with bipolar disorder, 64 adolescents with major depressive disorder, and 129 healthy adolescents, and employed a support vector machine to develop classification models for identification. We developed a multimodal model, which combined functional connectivity of resting-state functional magnetic resonance imaging and four anatomical measures of structural magnetic resonance imaging (cortical thickness, area, volume, and sulcal depth). We measured the performances of both multimodal and single modality classifiers.

Results

The multimodal classifiers showed outstanding performance compared with all five single modalities, and they are 100% for major depressive disorder versus healthy controls, 100% for bipolar disorder versus healthy control, 98.5% (95% CI: 95.4–100%) for major depressive disorder versus bipolar disorder, 100% for major depressive disorder versus depressed bipolar disorder and the leave-one-site-out analysis results are 77.4%, 63.3%, 79.4%, and 81.7%, separately.

Conclusions

The study shows that multimodal classifiers show high classification performances. Moreover, cuneus may be a potential biomarker to differentiate major depressive disorder, bipolar disorder, and healthy adolescents. Overall, this study can form multimodal diagnostic prediction workflows for clinically feasible to make more precise diagnose at the early stage and potentially reduce loss of personal pain and public society.

Therapeutic approaches employing natural compounds and derivatives for treating bipolar disorder: emphasis on experimental models of the manic phase

Bipolar disorder (BD) is a complex psychiatric disease characterized by mood swings that include episodes of mania and depression. Given its cyclical nature, BD is especially hard to model; however, the standard practice has been to mimic manic episodes in animal models. Despite scientific advances, the pathophysiology of BD is not fully understood, and treatment remains limited. In the last years, natural products have emerged as potential neuroprotective agents for the treatment of psychiatric diseases. Thus, the aim of this review was to explore the therapeutic potential of natural compounds and derivatives against BD, taking into account preclinical and clinical studies. Reliable articles indexed in databases such as PubMed, Web of Science and Science Direct were used. In clinical studies, treatment with herbal plants extracts, omega-3, inositol, n-acetylcysteine and vitamin D has been associated with a clinical improvement in symptoms of mania and depression in BD patients. In animal models, it has been shown that red fruits extracts, curcumin, quercetin, gallic acid, alpha-lipoic acid and carvone can modulate many neurochemical pathways involved in the pathophysiology of manic episodes. Thus, this review appointed the advances in the consumption of natural compounds and derivatives as an important therapeutic strategy to mitigate the symptoms of BD.

Are Mannan-binding Lectine Serin Protease-2 and Alpha-1-microglobulin and Bukinin Precursor the Potential Biomarkers of Manic Episode? A Study via Urinary Proetomic Analysis

Objective

Investigating the molecular basis of bipolar disorder (BD) is crucial in terms of developing effective treatment strategies as well as objective laboratory-based diagnostic tools for the disease.

Methods

We examined the urine samples of BD patients both in manic episode and after remission and compared their urinary protein profiles with the controls. Twelve patients and twelve controls (C group) included to the study. Urinary samples of patients were first collected during manic episode (M group) and then after remission (R group). Two-dimensional gel electrophoresis (2-DE) coupled to MALDI-TOF/TOF massspectrometry approach and Western blot analysis were used.

Results

Alphα-1-microglobulin and bukinin precursor (AMBP), Mannan-binding lectine serin protease-2 (MASP-2), and Ig gamma-1-chain displayed significant increases in their abundance in the urine protein pool of M group in comparison to the C and R groups. Alpha-1B glycoprotein and prostaglandin-H2 D-isomerase (PGD2) levels were significantly higher in the urine protein pool of the M and R groups in comparison to the C group. Annexin A1 was downregulated significantly in the urine protein pool of the M group in comparison to the C group.

Conclusion

Intensities of MASP-2 and AMBP proteins discriminated manic episode from remission period and healthy controls indicating that these proteins may be candidate biomarkers for manic episode. The decrease in Annexin A1 and increase in Ig gamma-1 chain levels appeared to be associated with “Manic Episode” while the increase in PGD2 and alpha-1B glycoprotein levels appeared to be associated with “Bipolar Disorder”.

Identification of potential plasma protein biomarkers for bipolar II disorder: a preliminary/exploratory study

The diagnostic peripheral biomarkers are still lacking for the bipolar II disorder (BD-II). We used isobaric tags for relative and absolute quantification technology to identify five upregulated candidate proteins [matrix metallopeptidase 9 (MMP9), phenylalanyl-tRNA synthetase subunit beta (FARSB), peroxiredoxin 2 (PRDX2), carbonic anhydrase 1 (CA-1), and proprotein convertase subtilisin/kexin type 9 (PCSK9)] for the diagnosis of BD-II. We analysed the differences in the plasma levels of these candidate proteins between BD-II patients and controls (BD-II, n = 185; Controls, n = 186) using ELISA. To establish a diagnostic model for the prediction of BD-II, the participants were divided randomly into a training group (BD-II, n = 149; Controls, n = 150) and a testing group (BD-II, n = 36; Controls, n = 36). Significant increases were found in all five protein levels between BD-II and controls in the training group. Logistic regression was analysed to form the composite probability score of the five proteins in the training group. Receiver-operating characteristic curve analysis revealed the diagnostic validity of the probability score [area under curve (AUC) = 0.89, P < 0.001]. The composite probability score of the testing group also showed good diagnostic validity (AUC = 0.86, P < 0.001). We propose that plasma levels of PRDX2, CA-1, FARSB, MMP9, and PCSK9 may be associated with BD-II as potential biomarkers.

Neuroinflammation in Mood Disorders: Role of Regulatory Immune Cells

Mood disorders are associated with chronic low-grade systemic (sterile) inflammation, with increased plasma levels of pro-inflammatory mediators targeting all tissues including the brain. Importantly, pro-inflammatory cytokines (ex., tumor-necrosis factor alpha [TNF-α], interleukin [IL]-6) regulate mood behavior and cognition by influencing neurotransmitter levels, activating stress-responsive endocrine axes, among other effects. However, the mechanisms underlying this enhanced inflammation are not well understood. There is increasing evidence indicating that impaired immunoregulatory mechanisms may play a role in this context. Patients with mood disorders (major depression [MDD] and bipolar disorder [BD]) have reduced numbers of major regulatory cells of both innate (natural killer regulatory cells and myeloid-derived suppressor cells [MDSCs]) and adaptive immune responses (CD4+CD25+FoxP3+, B regulatory cells). Dysfunctional regulatory immune cells might contribute to systemic and neuroinflammation observed in mood disorders via different mechanisms, such as: (i) failure to develop adequate stress-related responses, (ii) indirectly through microglial activation, (iii) lack of trophic support and pro-cognitive functions of T cells in the brain, and (iv) dysbiosis. In conclusion, maladaptive immunoregulatory mechanisms seem to be involved with both onset and progression of mood disorders. A deeper understanding of these mechanisms may lead to the development of new therapeutic strategies.

The Renin Angiotensin System and Bipolar Disorder: A Systematic Review

Bipolar Disorder (BD) is a chronic a multifactorial psychiatric illness that affects mood, cognition, and functioning. BD is associated with several psychiatric conditions as well clinical comorbidities, particularly cardiovascular diseases. The neurobiology of BD is complex and multifactorial and several systems have been implicated. Considering that the Renin Angiotensin System (RAS) plays an important role in cardiovascular diseases and that recently evidence has suggested its role in psychiatric disorders, the aim of the present study is to summarize and to discuss recent findings related to the modulation of RAS components in BD. A systematic search of the literature using the electronic databases MEDLINE and LILACS was conducted through March 2019. The search terms were: "Bipolar Disorder"; "Renin Angiotensin System"; "Angiotensin 2"; "Angiotensin receptors"; "Angiotensin 1-7"; "ACE"; "ACE2"; "Mas Receptor". We included original studies assessing RAS in BD patients. Two hundred twenty-two citations were initially retrieved. Eleven studies were included in our systematic review. In the majority of studies (6 of 8), the ACE insertion/deletion (I/D) polymorphism did not differ between BD patients and controls. BD patients presented higher plasma renin activity in comparison with controls. The studies evaluating the RAS molecules in BD are very scarce and heterogeneous. The literature suggests a potential role of RAS in BD. Further studies are necessary to investigate this relationship.

The Discovery of Clinically Applicable Biomarkers for Bipolar Disorder: A Review of Candidate and Proteomic Approaches

Bipolar disorder (BD) is a severe psychiatric condition which affects innumerable people across the globe. The etiopathogenesis of BD is multi-faceted with genetic, environmental and psychosocial factors playing a role. Hitherto, the diagnosis and management of BD are purely on empirical grounds as we lack confirmed biomarkers for this condition. In this regard, hypothesis-driven investigations have been unable to identify clinically applicable biomarkers, steering the field towards newer technologies. Innovative, state-of-the-art techniques like multiplex immunoassays and mass spectrometry can potentially investigate the entire proteome. By detecting up or down regulated proteins, novel biomarkers are identified and new postulates about the etiopathogenesis of BD are specified. Hence, biological pathways are uncovered which are involved in the initiation and advancement of the disease and new therapeutic targets are identified. In this manuscript, the extant literature is thoroughly reviewed and the latest findings on candidate BD biomarkers are provided, followed by an overview of the proteomic approaches. It was found that due to the heterogeneous nature of BD no single biomarker is feasible, instead a panel of tests is more likely to be useful. With the application of latest technologies, it is expected that validated biomarkers will be discovered which will be useful as diagnostic tools and help in the delivery of individually tailored therapies to the patients.

Glial and neuronal markers in bipolar disorder: A meta-analysis testing S100B and NSE peripheral blood levels

S100 calcium-binding protein B (S100B) and neuron-specific enolase (NSE) might be peripheral markers reflecting glia and neuronal abnormalities in subjects with bipolar disorder. We carried out a systematic review and meta-analysis, searching for studies indexed in main electronic databases, to clarify whether S100B and NSE blood levels might be increased in bipolar disorder. Eleven studies met eligibility criteria, with data on S100B levels and/or NSE levels in subjects with bipolar disorder and healthy controls, respectively. Random-effects meta-analysis estimated higher levels of S100B in bipolar disorder (standardized mean difference [SMD] = 0.81; p < .001), with some inconsistency across studies (I² = 81.7%). Findings were confirmed by relevant sensitivity analyses. Meta-regression analyses did not estimate any effect for tested covariates. On the other hand, no differences in NSE levels between individuals with bipolar disorder and healthy controls were estimated (SMD = -0.32; p = .374), with high heterogeneity across studies (I² = 89.9%). Meta-regression analyses showed that the effect size was influenced by both mean age (p < .001) and illness duration (p = .001) of subjects with bipolar disorders. Our findings support the hypothesis of a possible role of glial abnormalities in the pathophysiology of bipolar disorder.

Increased inflammatory biomarkers and changes in biological rhythms in bipolar disorder: A case-control study

BACKGROUND

Bipolar Disorder (BD) is a chronic psychiatric disorder characterized by mood disturbances that include depressive, manic, and hypomanic episodes. Despite the severity of the symptoms, there is still a gap in the literature on the precise neurobiology and treatment of BD. The investigations of inflammatory changes in BD has increased in the last decade, evincing the importance of its role in the pathophysiology of the disorder. The present study aimed to investigate the inflammatory role in BD, through the evaluation of biomarkers and their relation to biological rhythms.

METHODS

It was conducted a case-control study that included 36 BD and 46 healthy controls (HC). The Cyclooxygenase 2 (COX-2) enzyme, Arachidonic Acid (AA), interleukins (IL) IL-4, IL-5, IL-6, IL-10, IL-33, and Tumor Necrosis Factor Alpha (TNF-α) in the serum of individuals. It also was administered the Biological Rhythm Interview of Assessment in Neuropsychiatry (BRIAN) to the BD and healthy control groups.

RESULTS

The results indicated that the individuals with BD showed increased COX-2, AA, IL-6, and TNF-α levels in comparison to the HC without psychiatric disorders, as well as significant commitments in all domains evaluated by BRIAN.

LIMITATIONS

Uncontrolled pharmacotherapy used by the included bipolar participants, which had important effects on participants' inflammatory systems and the lack of cases with bipolar manic episodes.

CONCLUSIONS

The results of the present study reaffirm that inflammation has an important role in BD, as well as the significant changes in biological rhythms. It is still necessary to better characterize the inflammatory pathway of AA.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder

BACKGROUND

Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomarker in Alzheimer's dementia. However, such an approach has not been examined to differentiate healthy individuals from Bipolar disorder. In this study, we examined the utility of support vector machine (SVM) technique to differentiate bipolar disorder patients and healthy using structural, functional and diffusion tensor images of brain and neurocognitive measures.

METHODS

30 patients with Bipolar disorder-I and 30 age, sex matched individuals participated in the study. Structural MRI, resting state functional MRI and diffusion tensor images were obtained using a 1.5 T scanner. All participants were administered neuropsychological tests to measure executive functions. SVM, a supervised machine learning technique was applied to differentiate patients and healthy individuals with k-fold cross validation over 10 trials.

RESULTS

The composite marker consisting of both neuroimaging and neuropsychological measures, had an accuracy of 87.60 %, sensitivity of 82.3 % and specificity of 92.7 %. The performance of composite marker was better compared to that of individual markers on classificatory.

CONCLUSIONS

We were able to achieve a high accuracy for machine learning technique in distinguishing BD from HV using a combination of multimodal neuroimaging and neurocognitive measures. Findings of this proof of concept study, if replicated in larger samples, could have potential clinical applications.

Clinical, genetic, and brain imaging predictors of risk for bipolar disorder in high-risk individuals

Introduction: Early detection and intervention in bipolar disorder (BD) might reduce illness severity, slow its progression, and, in specific cases, even ward off the full-blown disorder. Therefore, identifying at-risk individuals and targeting them promptly before the illness onset is of the utmost importance. In the last decades, there has been a significant effort aimed at identifying genetic and molecular factors able to modulate risk and pharmacological outcomes.Areas covered: We performed a narrative review of articles aimed at identifying clinical, genetics, molecular, and brain imaging markers of BD specifically focusing on samples of individuals at high-risk for BD. Special emphasis was put on studies applying an integrative design, e.g. studies combining different markers such as genetic and brain imaging.Expert opinion: Findings from studies in risk individuals are still too sparse to allow drawing definite conclusions. However, the high potentiality of longitudinal studies in individuals considered at risk to develop BD supports the need for more efforts. Future investigations should focus on more homogeneous subpopulations and evaluate the cross-linking between clinical, genetic, and brain morphostructural/functional neuroimaging characteristics as predictors of risk for BD.

Coadministration of lithium and celecoxib reverses manic-like behavior and decreases oxidative stress in a dopaminergic model of mania induced in rats

The present study intends to investigate the effect of lithium (Li) and celecoxib (Cel) coadministration on the behavioral status and oxidative stress parameters in a rat model of mania induced by dextroamphetamine (d-AMPH). Male Wistar rats were treated with d-AMPH or saline (Sal) for 14 days; on the 8th day of treatment, rats received lithium (Li), celecoxib (Cel), Li plus Cel, or water until day 14. Levels of oxidative stress parameters were evaluated in the serum, frontal cortex, and hippocampus. d-AMPH administration induced hyperlocomotion in rats, which was significantly reversed by Li and Cel coadministration. In addition, d-AMPH administration induced damage to proteins and lipids in the frontal cortex and hippocampus of rats. All these impairments were reversed by treatment with Li and/or Cel, in a way dependent on cerebral area and biochemical analysis. Li and Cel coadministration reversed the d-AMPH-induced decrease in catalase activity in cerebral structures. The activity of glutathione peroxidase was decreased in the frontal cortex of animals receiving d-AMPH, and treatment with Li, Cel, or a combination thereof reversed this alteration in this structure. Overall, data indicate hyperlocomotion and alteration in oxidative stress biomarkers in the cerebral structures of rats receiving d-AMPH. Li and Cel coadministration can mitigate these modifications, comprising a potential novel approach for BD therapy.

Resveratrol protects the brain against oxidative damage in a dopaminergic animal model of mania

The present study aimed to evaluate the effects of resveratrol on behavior and oxidative stress parameters in the brain of rats submitted to the animal model of mania induced by m-AMPH. In the first model (reversal treatment), rats received intraperitoneal (i.p.) injection of saline or m-AMPH (1 mg/kg body weight) once a day for 14 days, and from the 8th to the 14th day, they were orally treated with water or resveratrol (15 mg/kg), once a day. In the second model (maintenance treatment), rats were orally pretreated with water or resveratrol (15 mg/kg) once a day, and from the 8th to the 14th day, they received saline or m-AMPH i.p., once a day. Locomotor and exploratory activities were assessed in the open-field test. Oxidative and nitrosative damage parameters to lipid and proteins were evaluated by TBARS, 4-HNE, carbonyl, and 3-nitrotyrosine in the brain submitted to the experimental models. m-AMPH administration increased the locomotor and exploratory activities; resveratrol was not able to reverse or prevent these manic-like behaviors. Additionally, m-AMPH increased the lipid and protein oxidation and nitrosylation in the frontal cortex, hippocampus, and striatum of rats. However, resveratrol prevented and reversed the oxidative and nitrosative damage to proteins and lipids in all cerebral areas assessed. Since oxidative stress plays an important role in BD pathophysiology, supplementation of resveratrol in BD patients could be regarded as a possible adjunctive treatment with mood stabilizers.

Serum uric acid as a predictor of bipolarity in individuals with a major depressive episode

OBJECTIVES

There are no well-established biomarkers to predict the risk of conversion to bipolar disorder (BD) in patients with depression. Given the putative role of purinergic neurotransmission dysfunction in BD, the purpose of our study was to evaluate if higher serum uric acid (UA) levels could predict BD conversion in depressed inpatients.

METHODS

We reviewed retrospectively the records of subjects hospitalized between June 2007 and June 2010 with a diagnosis of major depressive disorder (MDD) who had undergone routine UA levels testing at admission. At an approximate 10-year follow-up we identified subjects with a subsequent diagnosis of BD. We compared UA levels between the BD-converter and non-BD converter groups, performed Receiver operating characteristic curve analysis to evaluate the prognostic accuracy of serum UA levels and calculated the clinical utility index (CUI) as a risk biomarker for conversion to BD.

RESULTS

The study included 250 subjects (55 "BD-converters" and 195 "No BD-converters"). "BD-converters" had significantly higher plasma UA levels compared to "No BD-converters" in their index hospitalization irrespective of gender (males: 403.84 ± 91.76 vs 270.81 ± 53.58 µmol/L; U = 94.5, P < 0.001 and females 302.19 ± 52.64 vs 202.69 ± 48.93 µmol/L; t = 10.75, P < 0.001). Serum UA levels showed a very good to excellent accuracy for predicting conversion to BD in inpatients with MDD (area under the curve [AUC]: 0.90; 95% CI: 0.86, 0.94) and had a good to excellent CUI- and a moderate to good CUI+ grading for discriminating BD-converter cases from non-BD converters.

CONCLUSIONS

Our study suggests that depressed patients with higher levels of serum UA are at greater risk of a subsequent manic or hypomanic episode. The purinergic system could prove a promising path for the search of biomarkers in BD.

Meta-analyses of cavum septum pellucidum in mood disorders in comparison with healthy controls or schizophrenia

The cavum septum pellucidum (CSP) is a neurodevelopmental abnormality significantly more prevalent in subjects with schizophrenia (SCZ) than in healthy controls (HC). Using meta-analyses, we tested the hypotheses whether CSP would be more frequent in subjects with mood disorders when compared with HC or SCZ. We performed a search in MEDLINE and EMBASE followed by 10 meta-analyses of magnetic resonance imaging studies which examined the association of CSP in bipolar disorders (BD), major depressive disorder (MDD) or mood disorders (MD; considering MDD and BD combined) with either HC or SCZ. Nine studies were included, comprising 692 cases (363 with BD, 182 with MDD and 147 with MD), 463 with SCZ and 630 HC. CSP of any size was significantly associated with BD (OR = 2.07, 95% CI: 1.48-2.90) when compared with HC. Large CSP showed a trend to be associated with BD when compared with HC, but the association was not statistically significant (OR = 1.92, 95% CI 0.64-5.78). Large CSP was significantly associated with subjects with SCZ when compared with subjects with MD (OR = 0.57, 95% CI: 0.36-0.92). There was no association between CSP and MDD in comparison to HC or subjects with SCZ. Cortical structures are known to be altered in mood disorders. The present metanalysis found that certain midline brain abnormalities, such as CSP, are also associated with BD.

Biomarkers for bipolar disorder: current status and challenges ahead

INTRODUCTION

Bipolar disorder (BD) is a chronic psychiatric disorder marked by clinical and pathophysiological heterogeneity. There is a high expectation that personalized approaches can improve the management of patients with BD. For that, identification and validation of potential biomarkers are fundamental. Areas covered: This manuscript will critically review the current status of different biomarkers for BD, including peripheral, genetic, neuroimaging, and neurophysiological candidates, discussing the challenges to move the field forward. Expert commentary: There are no lab or complementary tests currently recommended for the diagnosis or management of patients with BD. Panels composed by multiple biomarkers will probably contribute to stratifying patients according to their clinical stage, therapeutic response, and prognosis.

The identification of biomarkers predicting acute and maintenance lithium treatment response in bipolar disorder: A plea for further research attention

The prediction of acute and maintenance lithium treatment response carries major clinical and neurobiological implications, warranting systematic review. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) compliant review searched major electronic databases from inception until December 2017 for studies documenting a clinical diagnosis of bipolar disorder (BD) made according to the mainstream diagnostic manuals and confirmed by a structured interview. Eligible studies allowed a quantitative comparison of endpoint vs baseline mean values of a given biomarker, regardless of the mood phase of patients with BD, and the disorder was assessed for severity using validated rating tool(s). Owing to the purposely applied stringent selection criteria, 16 acute and 12 maintenance studies could be included. The anticipated publication bias limited the chances of reportable generalizable findings, hindering a side-by-side comparison of different records across varying biomarkers and subsequent meta-analyses. The PRISMA approach was nonetheless preferred; it aimed at enhancing the homogeneity of the included results and minimizing the chances of "apples and oranges" with respect to the present research theme. The present critical review confirms the need for future research to specifically assess either pretreatment and/or posttreatment putative biomarkers of patients with BD and treated with lithium.

Rhythmicity of Mood Symptoms in Individuals at Risk for Psychiatric Disorders

Despite emerging evidence that disruption in circadian rhythms may contribute to the pathophysiology of psychiatric disorders, there is a significant knowledge gap on the rhythmicity of psychological symptoms. Here, we aimed at investigating the rhythmicity of mood symptoms in individuals at risk for psychiatric disorders. 391 Brazilian and 317 Spanish participants completed the Self-Reporting Questionnaire-20 for non-psychotic mental disorders; the Mood Rhythm Instrument was used to assess rhythmicity of mood symptoms and the Munich ChronoType Questionnaire to assess sleep patterns. We found that the rhythmicity of specific mood-related symptoms and behaviors, particularly pessimism and motivation to exercise, were associated with being at risk for psychiatric disorders, even after controlling for sleep timing, sleep deficit, and season of data collection. We also found that the peak of some mood symptoms and behaviors were different between individuals at high vs. low risk for psychiatric disorders, with specific differences between countries. These results are consistent with previous research showing that circadian misalignment is associated with higher risk for mental health conditions. These findings also suggest that lifestyle changes preventing circadian misalignment might be useful to reduce the risk of psychiatric disorders, where cultural differences must be taken into account.

Inhibition of the dopamine transporter as an animal model of bipolar disorder mania: Locomotor response, neuroimmunological profile and pharmacological modulation

Inhibition of dopamine transporter (DAT) by GBR12909 has been proposed as a pharmacological model of mania related to bipolar disorder (BD). Here we tested the hypothesis that GBR12909 injection impairs habituation and induces hyperlocomotion in mice, along with changes in cytokines and neurotrophic factors levels, as observed in BD patients. We also tested if lithium carbonate, sodium valproate and aripiprazole prevent GBR12909-induced locomotion. Male Swiss mice received GBR12909 (15 mg/kg) injections and locomotor responses were quantified in an open field. Cytokines and neurotrophic factors levels were assessed in the prefrontal cortex, striatum and hippocampus 30 min and 24 h after injections. Pre-treatments with lithium, valproate or aripiprazole were performed with single and repeated injection protocols. GBR12909 prevented motoric habituation and increased basal locomotion in habituated mice in the open field. This compound also induced changes in IL-2 and BDNF levels in prefrontal cortex; IL-2, IL-4 and IL-10 in striatum; and IL-10, IL-4, IFN-γ and NGF in hippocampus. GBR12909-induced hyperlocomotion was attenuated by lithium (12.5-100 mg/kg), but not valproate (75-300 mg/kg), and prevented by aripiprazole (0.1-10 mg/kg). Repeated injections of these drugs (twice a day for 3 days), however, failed to inhibit hyperlocomotion. The main limitations of the protocols in this study are the analysis of locomotion as the only behavioral parameter, changes in immune factors that may overlap with other psychiatric disorders and the lack chronic drug injections. Despite of these limitations, this study adds to previous literature suggesting DAT inhibition as a potential animal model of mania related to BD.

Further Evidence of Accelerated Aging in Bipolar Disorder: Focus on GDF-15

Background

Bipolar disorder (BD) is a mood disorder associated with cardiovascular and metabolic diseases and premature aging. Growth differentiation factor 15 (GDF-15) has emerged as a biomarker for cardiovascular risk and aging. Our aim was to compare plasma levels of GDF-15 between BD patients and controls, and to evaluate whether they were associated with clinical parameters.

Methods

Forty-six patients with type I BD (23 in euthymia and 23 in mania) and 33 healthy controls were recruited for this study. Plasma levels of GDF-15 were measured by immunoassay.

Results

The levels of GDF-15 were significantly higher (p < 0.001) in patients with BD in comparison with controls. In patients, GDF-15 levels correlated with age (rho = 0.434; p = 0.003) and illness duration (rho = 0.502; p = 0.001).

Conclusion

Our findings corroborate the view that BD is an illness associated with accelerated aging.

Revisiting the Role of Eotaxin-1/CCL11 in Psychiatric Disorders

Eotaxin-1/CCL11 is a chemokine originally implicated in the selective recruitment of eosinophils into inflammatory sites during allergic reactions, being thoroughly investigated in asthma, allergic rhinitis, and other eosinophil-related conditions. Eotaxin-1/CCL11 is also involved with a skewed immune response toward a type-2 (Th2) profile. In addition to its role in immune response, recent studies have shown that eotaxin-1/CCL11 is associated with aging, neurogenesis and neurodegeneration, being able to influence neural progenitor cells, and microglia. Increased circulating levels of eotaxin-1/CCL11 have been described in major psychiatric disorders (schizophrenia, bipolar disorder, major depression), sometimes correlating with the severity of psychopathological and cognitive parameters. As similar findings have been reported in neurodegenerative conditions such as Alzheimer's disease, it has been hypothesized that mechanisms involving eotaxin-1/CCL11 signaling may underlie the "accelerated aging" profile commonly linked to psychiatric disorders. Future studies must determine whether eotaxin-1/CCL11 can be regarded as a prognostic biomarker and/or as therapeutic target for resistant/progressive cases.