Serum brain-derived neurotrophic factor in bipolar and unipolar depression: a potential adjunctive tool for differential diagnosis

Progress and trends of research on mineral elements for depression

Objective

To explore the research progress and trends on mineral elements and depression.

Methods

After querying the MeSH database and referring to the search rules, the search terms were selected and optimized to obtain the target literature collection. We analyzed the general characteristics of the literature, conducted network clustering and co-occurrence analysis, and carried out a narrative review of crucial literature.

Results

Bipolar disorder was a dominant topic in the retrieved literature, which saw a significant increase in 2010 and 2019-2020. Most studies focused on mineral elements, including lithium, calcium, magnesium, zinc, and copper. The majority of journals and disciplines were in the fields of psychiatry, neuropsychology, neuropharmacology, nutrition, medical informatics, chemistry, and public health. The United States had the highest proportion in terms of paper sources, most-cited articles, high-frequency citations, frontier citations, and high centrality citation. Regarding the influence of academic institutions, the top five were King's College London, the Chinese Academy of Sciences, University of Barcelona, INSERM, and Heidelberg University. Frontier keywords included bipolar disorder, drinking water, (neuro)inflammation, gut microbiota, and systematic analysis. Research on lithium response, magnesium supplementation, and treatment-resistant unipolar depression increased significantly after 2013.

Conclusion

Global adverse events may have indirectly driven the progress in related research. Although the literature from the United States represents an absolute majority, its influence on academic institutions is relatively weaker. Multiple pieces of evidence support the efficacy of lithium in treating bipolar disorder (BD). A series of key discoveries have led to a paradigm shift in research, leading to increasingly detailed studies on the role of magnesium, calcium, zinc, and copper in the treatment of depression. Most studies on mineral elements remain diverse and inconclusive. The potential toxicity and side effects of some elements warrant careful attention.

Chronic REM sleep deprivation leads to manic- and OCD-related behaviors, and decreases hippocampal BDNF expression in female rats

BACKGROUND

Rapid-eye movement (REM) sleep deprivation (SD) can induce manic-like behaviors in rodents. On the other hand, lithium, as one of the oldest drugs used in neuropsychiatric disorders, is still one of the best drugs for the treatment and control of bipolar disorder. In this study, we aimed to investigate the role of chronic short-term REM SD in the induction of manic-like behaviors in female rats.

METHODS

The rats were exposed to REM SD for 14 days (6 hours/day). Lithium was intraperitoneally injected at the doses of 10, 50, and 100 mg/kg.

RESULTS

REM SD induced hyperactivity and OCD-like behavior, and decreased anxiety, depressive-like behavior, and pain subthreshold. REM SD also impaired passive avoidance memory and decreased hippocampal brain-derived neurotrophic factor (BDNF) expression level. Lithium at the doses of 50 and 100 mg/kg partly and completely abolished these effects, respectively. However, lithium (100 mg/kg) increased BDNF expression level in control and sham REM SD rats with no significant changes in behavior.

CONCLUSIONS

Chronic short-term REM SD may induce a mania-like model and lead to OCD-like behavior and irritability. In the present study, we demonstrated a putative rodent model of mania induced by chronic REM SD in female rats. We suggest that future studies should examine behavioral and mood changes following chronic REM SD in both sexes. Furthermore, the relationship between manic-like behaviors and chronic REM SD should be investigated.

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.

Can Brain-Derived Neurotrophic Factor Be Considered a Biomarker for Bipolar Disorder? An Analysis of the Current Evidence

Brain-derived neurotrophic factor (BDNF) plays a key role in brain development, contributing to neuronal survival and neuroplasticity. Previous works have found that BDNF is involved in several neurological or psychiatric diseases. In this review, we aimed to collect all available data on BDNF and bipolar disorder (BD) and assess if BDNF could be considered a biomarker for BD. We searched the most relevant medical databases and included studies reporting original data on BDNF circulating levels or Val66Met polymorphism. Only articles including a direct comparison with healthy controls (HC) and patients diagnosed with BD according to international classification systems were included. Of the 2430 identified articles, 29 were included in the present review. Results of the present review show a reduction in BDNF circulating levels during acute phases of BD compared to HC, which increase after effective therapy of the disorders. The Val66Met polymorphism was related to features usually associated with worse outcomes. High heterogeneity has been observed regarding sample size, clinical differences of included patients, and data analysis approaches, reducing comparisons among studies. Although more studies are needed, BDNF seems to be a promising biomarker for BD.

A review of new insights into existing major depressive disorder biomarkers

As major depressive disorder (MDD) is such a diverse condition, there are currently no clear ways for determining its severity, endophenotype, or therapy response. The distinctive nature of depression, the variability of analysis in literature and the large number of conceptually complicated biomarkers are some of the many reasons for the lack of progress. Markers are involved in the process of neurotrophic, metabolic, and inflammation as well as neuroendocrine and neurotransmitter systems' components. Some clinical indicators are strong enough so that can be measured using assessments of proteomic, genetic, metabolomics, neuroimaging, epigenetic and transcriptomic. Markers of oxidative stress, endocrine, inflammatory, proteomic, and growth indicators are currently among the promising biologic systems/markers identified in this analysis. This narrative review examines succinct studies which investigated cytokines of inflammatory factors, peripheral factors of development, metabolic and endocrine markers as pathophysiological biomarkers of MDD, and treatment responses. Endocrine and metabolic alterations have also been linked to MDD in various studies. So, this study summarizes all of the numerous biomarkers that are significant in the detection or treatment of MDD patients. The paper also provides an overview of various biomarkers which are important for the regulation and its effects on MDD.

Brain-derived Neurotrophic Factor and High Sensitive C-reactive Protein in Bipolar Depression and Unipolar Depression: The Practical Usage as a Discriminatory Tool

Objective

Brain-derived neurotrophic factor (BDNF) and high sensitive C-reactive protein (hs-CRP) have been reported to play roles in depression and bipolar disorder (BD). However, the probable discriminatory properties of these biologic markers are less investigated. We aimed to assess the serum BDNF and hs-CRP levels among Iranian patients with major depressive disorder (MDD) and BD during a depressive episode and investigate the optimum cut-off point for differential diagnosis of BD and MDD.

Methods

We recruited 30 patients with MDD, 30 with BD in depressive mood and 30 healthy comparators. Blood sample was taken from each participant to measure BDNF and hs-CRP levels. We also used receiver operating characteristic (ROC) curve analysis to find an optimal cut-off point for differentiating MDD from BD according to pre-defined variables.

Results

The mean age of total study population was 37.3 ± 5.0 years (males: 49%). BDNF was significantly lower in patients with BD, followed by MDD subjects and healthy controls 541.0 ± 601.0 pg/ml vs. 809.5 ± 433.3 pg/ml vs. 1,482.1 ± 519.8, respectively, p < 0.001). The area under curve of ROC curve analysis for BD versus MDD was 0.704 (95% confidence interval: 0.564-0.844, p = 0.007). We also found that the BDNF cut-off value of 504 could appropriately distinguished BD from MDD (sensitivity: 73%, specificity: 70%). No significant association were identified in terms of hs-CRP levels.

Conclusion

Patients suffering from BD had lowest BDNF levels compared to MDD or healthy adults and this biomarker could play a practical role differentiating MDD from BD. Several studies are required confirming our outcomes.

Charting the proteome landscape in major psychiatric disorders: From biomarkers to biological pathways towards drug discovery

Schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) are major mental disorders that affect a significant proportion of the global population. Advancing our knowledge of the pathophysiology of these disorders and identifying biomarkers are urgent needs for developing objective diagnostic tests and new therapeutics. In this study, we performed a systematic review and then extracted, curated, and analyzed proteomics data from published studies, aiming to assess the proteome in peripheral blood of individuals with SZ, BD, or MDD. Then, we performed pathway and network analyses to illuminate the biological themes concatenated by the differentially expressed proteins by systematically interrogating the literature to uncover biological pathways with more robust biological meaning. We identified 486 differentially expressed proteins from 51 studies across the three disorders with 9,423 participants. The great majority of pathways were common to SZ, BD, and MDD. They were related to the immune system, including signaling by interleukins, Toll-like receptor signaling pathway, and complement cascade, and to signal transduction, notably MAPK1/MAPK3 signaling, PI3K-Akt Signaling Pathway, Focal Adhesion-PI3K-Akt-mTOR-signaling, rhodopsin-like receptors, GPCR signaling, and the JAK-STAT signaling pathway. Other shared pathways included advanced glycosylation end-product receptor signaling, Regulation of Insulin-like Growth Factor, cholesterol metabolism, and IL-17 signaling pathway. Pathways shared between SZ and BD were integrin cell-surface interactions, GRB2:SOS provides linkage to MAPK signaling for integrins, and syndecan interactions. Shared between BD and MDD were the NRF2 pathway and signaling by EGFR pathways. Our findings advance our understanding of the protein variations and associations with these disorders, which are useful for accelerating biomarker development and drug discovery.

Low BDNF levels in serum are associated with cognitive impairments in medication-naïve patients with current depressive episode in BD II and MDD

OBJECTIVE

This study aimed to investigate the role of Brain-derived neurotrophic factor (BDNF) in clinical and cognitive outcomes in medication-naïve patients with Bipolar type II disorder (BD II) and Major depressive disorder (MDD).

METHODS

45 outpatients with BD II, 40 outpatients with MDD and 40 healthy controls (HCs) were recruited, and sociodemographic and clinical data were collected. Their BDNF serum levels were measured and analyzed with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).

RESULTS

BDNF levels were significantly lower in BD II patients than in MDD patients and HCs (p = 0.001). BD II and MDD patients had similar cognitive performance deficits shown on Attention (p = 0.001), Delayed memory (p = 0.001), and RBANS total score (p = 0.001). BDNF levels were positively associated with Visuospatial / constructional and Stroop color-word in BD II group, and with language in MDD group. The area under the curve (AUC) of the ROC analysis in BD II vs. MDD was 0.664, therefore, BDNF levels could not distinguish BD II from MDD.

CONCLUSION

Our study showed the decreased serum BDNF in MDD and BD II patients, suggesting BDNF may be involved in the pathophysiology of MDD and BD II. BDNF and cognitive deficits are both of low efficiency in distinguishing BD II from MDD. Decrease of BDNF may potentially indicate cognitive dysfunction in BD II and MDD patients with a current depressive episode.

Serum levels of glial cell line-derived neurotrophic factor as a biomarker for mood disorders and lithium response

Glial cell line-derived neurotrophic factor (GDNF) plays an important role in the pathophysiology of neuropsychiatric disorders. We examined serum GDNF levels in bipolar disorder (BD) patients and major depressive disorder (MDD) patients and their association with response to lithium therapy. We used a multicenter (six sites), exploratory, cross-sectional case-control design and recruited 448 subjects: 143 BD patients, 116 MDD patients, and 158 healthy controls (HCs). We evaluated the patients' clinical severity using the Clinical Global Impression (CGI), and responses to lithium therapy using the Alda scale. The serum GDNF levels were significantly decreased in the BD and MDD groups compared to the HCs, with no significant difference between the BD and MDD groups. After adjustment, the serum GDNF levels in the BD and MDD patients in remission or depressive states were decreased compared to the HC values. Lower serum GDNF levels in BD patients were associated with higher CGI and Alda scores (i.e., severe illness and good response to lithium therapy, respectively). Our findings suggest that the serum GDNF level may be a biomarker for both BD and MDD in remission or depressive states. The serum GDNF level may be associated with the lithium response of BD patients.

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

BACKGROUND

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

METHODS

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

RESULTS

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

LIMITATIONS

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

CONCLUSION

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

Neutrophil-to-Lymphocyte Ratio, a Novel Inflammatory Marker, as a Predictor of Bipolar Type in Depressed Patients: A Quest for Biological Markers

(1) Background: Recent research suggests inflammation as a factor involved in the pathophysiology of mood disorders. Neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), platelet-to-lymphocyte (PLR), and systemic immune-inflammatory (SII) index ratios have been studied as peripheral markers of inflammation in bipolar and major depressive disorders. The purpose of this study is to comparatively analyze these inflammatory ratios among manic episodes of bipolar disorder, bipolar depression and unipolar depression. (2) Methods: 182 patients were retrospectively included in the study and divided into three groups: 65 manic patients, 34 patients with bipolar depression, and 83 unipolar depressive patients. White blood cells, neutrophils, monocytes, lymphocytes, and platelets were retrieved from the patients' database. NLR, MLR, PLR, and SII index were calculated using these parameters. (3) Results: Patients with manic episodes had elevated NLR (p < 0.001), MLR (p < 0.01), PLR (p < 0.05), and SII index (p < 0.001) compared to unipolar depression and increased NLR (p < 0.05) and SII index (p < 0.05) when compared to bipolar depression. NLR (p < 0.01) and SII index (p < 0.05) were higher in the bipolar depression than unipolar depression. NLR is an independent predictor of the bipolar type of depression in depressive patients. (4) Conclusions: The results confirm the role of inflammation in the pathophysiology of mood disorders and suggest the ability of NLR as a marker for the differentiation of bipolar from unipolar depression.

Biomarkers of Major Depressive Disorder: Knowing is Half the Battle

Major depressive disorder (MDD) is a heterogeneous disease which is why there are currently no specific methods to accurately test the severity, endophenotype or therapy response. This lack of progress is partly attributed to the com-plexity and variability of depression, in association with analytical variability of clinical literature and the wide number of theoretically complex biomarkers. The literature accessible, indicates that markers involved in inflammatory, neuro-trophic and metabolic processes and components of neurotransmitters and neuroendocrine systems are rather strong indicators to be considered clinically and can be measured through genetic and epigenetic, transcriptomic and proteomic, metabolomics and neuroimaging assessments. Promising biologic systems/markers found were i.e., growth biomarkers, endocrine markers, oxidant stress markers, proteomic and chronic inflammatory markers, are discussed in this review. Several lines of evidence suggest that a portion of MDD is a dopamine agonist-responsive subtype. This review analyzes concise reports on the pathophysiological biomarkers of MDD and therapeutic reactions via peripheral developmental factors, inflammative cytokines, endocrine factors and metabolic markers. Various literatures also support that endocrine and metabolism changes are associated with MDD. Accumulating evidence suggests that at least a portion of MDD patients show characteristics pathological changes regarding different clinical pathological biomarkers. By this review we sum up all the different biomarkers playing an important role in the detection or treatment of the different patients suffering from MDD. The review also gives an overview of different biomarker's playing a potential role in modulating effect of MDD.

Concepts of Neuroinflammation and Their Relationship With Impaired Mitochondrial Functions in Bipolar Disorder

Bipolar disorder (BD) is a chronic psychiatric disease, characterized by frequent behavioral episodes of depression and mania, and neurologically by dysregulated neurotransmission, neuroplasticity, growth factor signaling, and metabolism, as well as oxidative stress, and neuronal apoptosis, contributing to chronic neuroinflammation. These abnormalities result from complex interactions between multiple susceptibility genes and environmental factors such as stress. The neurocellular abnormalities of BD can result in gross morphological changes, such as reduced prefrontal and hippocampal volume, and circuit reorganization resulting in cognitive and emotional deficits. The term "neuroprogression" is used to denote the progressive changes from early to late stages, as BD severity and loss of treatment response correlate with the number of past episodes. In addition to circuit and cellular abnormalities, BD is associated with dysfunctional mitochondria, leading to severe metabolic disruption in high energy-demanding neurons and glia. Indeed, mitochondrial dysfunction involving electron transport chain (ETC) disruption is considered the primary cause of chronic oxidative stress in BD. The ensuing damage to membrane lipids, proteins, and DNA further perpetuates oxidative stress and neuroinflammation, creating a perpetuating pathogenic cycle. A deeper understanding of BD pathophysiology and identification of associated biomarkers of neuroinflammation are needed to facilitate early diagnosis and treatment of this debilitating disorder.

Blood Brain-Derived Neurotrophic Factor (BDNF) and Major Depression: Do We Have a Translational Perspective?

Major depressive disorder (MDD) affects millions of people worldwide and is a leading cause of disability. Several theories have been proposed to explain its pathological mechanisms, and the “neurotrophin hypothesis of depression” involves one of the most relevant pathways. Brain-derived neurotrophic factor (BDNF) is an important neurotrophin, and it has been extensively investigated in both experimental models and clinical studies of MDD. Robust empirical findings have indicated an association between increased BDNF gene expression and peripheral concentration with improved neuronal plasticity and neurogenesis. Additionally, several studies have indicated the blunt expression of BDNF in carriers of the Val66Met gene polymorphism and lower blood BDNF (serum or plasma) levels in depressed individuals. Clinical trials have yielded mixed results with different treatment options, peripheral blood BDNF measurement techniques, and time of observation. Previous meta-analyses of MDD treatment have indicated that antidepressants and electroconvulsive therapy showed higher levels of blood BDNF after treatment but not with physical exercise, psychotherapy, or direct current stimulation. Moreover, the rapid-acting antidepressant ketamine has presented an early increase in blood BDNF concentration. Although evidence has pointed to increased levels of BDNF after antidepressant therapy, several factors, such as heterogeneous results, low sample size, publication bias, and different BDNF measurements (serum or plasma), pose a challenge in the interpretation of the relation between peripheral blood BDNF and MDD. These potential gaps in the literature have not been properly addressed in previous narrative reviews. In this review, current evidence regarding BDNF function, genetics and epigenetics, expression, and results from clinical trials is summarized, putting the literature into a translational perspective on MDD. In general, blood BDNF cannot be recommended for use as a biomarker in clinical practice. Moreover, future studies should expand the evidence with larger samples, use the serum or serum: whole blood concentration of BDNF as a more accurate measure of peripheral BDNF, and compare its change upon different treatment modalities of MDD.

Using classification and regression tree modeling to investigate appetite hormones and proinflammatory cytokines as biomarkers to differentiate bipolar I depression from major depressive disorder

BACKGROUND

Altered immunity and metabolic profiles have been compared between bipolar depression (BD) and major depressive disorder (MDD). This study aimed at developing a composite predictor of appetite hormones and proinflammatory cytokines to differentiate BD from MDD.

METHODS

This cross-sectional study enrolled patients with BD and those with MDD aged 20 to 59 years and displaying depressive episodes. Clinical characteristics (age, sex, body mass index, and depression severity), cytokines (C-reactive protein, interleukin [IL]-2, IL-6, tumor necrosis factor [TNF]-α, P-selectin, and monocyte chemoattractant protein), and appetite hormones (leptin, adiponectin, ghrelin, and insulin) were assessed as potential predictors using a classification and regression tree (CRT) model for differentiating BD from MDD.

RESULTS

The predicted probability of a composite predictor of ghrelin and TNF-α was significantly greater (for BD: area under curve = 0.877; for MDD: area under curve = 0.914) than that of any one marker (all P > .05) to distinguish BD from MDD. The most powerful predictors for diagnosing BD were high ghrelin and TNF-α levels, whereas those for MDD were low ghrelin and TNF-α levels.

CONCLUSION

A composite predictor of ghrelin and TNF-α driven by CRT could assist in the differential diagnosis of BD from MDD with high specificity. Further clinical studies are warranted to validate our results and to explore underlying mechanisms.

Präzisionspsychiatrie und der Beitrag von Brain Imaging und anderen Biomarkern

'Precision Psychiatry' as the psychiatric variant of 'Precision Medicine' aims to provide high-level diagnosis and treatment based on robust biomarkers and tailored to the individual clinical, neurobiological, and genetic constitution of the patient. The specific peculiarity of psychiatry, in which disease entities are normatively defined based on clinical experience and are also significantly influenced by contemporary history, society and philosophy, has so far made the search for valid and reliable psychobiological connections difficult. Nevertheless, considerable progress has now been made in all areas of psychiatric research, made possible above all by the critical review and renewal of previous concepts of disease and psychopathology, the increased orientation towards neurobiology and genetics, and in particular the use of machine learning methods. Notably, modern machine learning methods make it possible to integrate high-dimensional and multimodal data sets and generate models which provide new psychobiological insights and offer the possibility of individualized, biomarker-driven single-subject prediction of diagnosis, therapy response and prognosis. The aim of the present review is therefore to introduce the concept of 'Precision Psychiatry' to the interested reader, to concisely present modern, machine learning methods required for this, and to clearly present the current state and future of biomarker-based 'precision psychiatry'.

Mitochondria under the spotlight: On the implications of mitochondrial dysfunction and its connectivity to neuropsychiatric disorders

Neuropsychiatric disorders (NPDs) such as bipolar disorder (BD), schizophrenia (SZ) and mood disorder (MD) are hard to manage due to overlapping symptoms and lack of biomarkers. Risk alleles of BD/SZ/MD are emerging, with evidence suggesting mitochondrial (mt) dysfunction as a critical factor for disease onset and progression. Mood stabilizing treatments for these disorders are scarce, revealing the need for biomarker discovery and artificial intelligence approaches to design synthetically accessible novel therapeutics. Here, we show mt involvement in NPDs by associating 245 mt proteins to BD/SZ/MD, with 7 common players in these disease categories. Analysis of over 650 publications suggests that 245 NPD-linked mt proteins are associated with 800 other mt proteins, with mt impairment likely to rewire these interactions. High dosage of mood stabilizers is known to alleviate manic episodes, but which compounds target mt pathways is another gap in the field that we address through mood stabilizer-gene interaction analysis of 37 prescriptions and over-the-counter psychotropic treatments, which we have refined to 15 mood-stabilizing agents. We show 26 of the 245 NPD-linked mt proteins are uniquely or commonly targeted by one or more of these mood stabilizers. Further, induced pluripotent stem cell-derived patient neurons and three-dimensional human brain organoids as reliable BD/SZ/MD models are outlined, along with multiomics methods and machine learning-based decision making tools for biomarker discovery, which remains a bottleneck for precision psychiatry medicine.

Precision psychiatry with immunological and cognitive biomarkers: a multi-domain prediction for the diagnosis of bipolar disorder or schizophrenia using machine learning

Precision psychiatry is attracting increasing attention lately as a recognized priority. One of the goals of precision psychiatry is to develop tools capable of aiding a clinically informed psychiatric diagnosis objectively. Cognitive, inflammatory and immunological factors are altered in both bipolar disorder (BD) and schizophrenia (SZ), however, most of these alterations do not respect diagnostic boundaries from a phenomenological perspective and possess great variability in different individuals with the same phenotypic diagnosis and, consequently, none so far has proven to have the ability of reliably aiding in the differential diagnosis of BD and SZ. We developed a probabilistic multi-domain data integration model consisting of immune and inflammatory biomarkers in peripheral blood and cognitive biomarkers using machine learning to predict diagnosis of BD and SZ. A total of 416 participants, being 323, 372, and 279 subjects for blood, cognition and combined biomarkers analysis, respectively. Our multi-domain model performances for the BD vs. control (sensitivity 80% and specificity 71%) and for the SZ vs. control (sensitivity 84% and specificity 81%) pairs were high in general, however, our multi-domain model had only moderate performance for the differential diagnosis of BD and SZ (sensitivity 71% and specificity 73%). In conclusion, our results show that the diagnosis of BD and of SZ, and that the differential diagnosis of BD and SZ can be predicted with possible clinical utility by a computational machine learning algorithm employing blood and cognitive biomarkers, and that their integration in a multi-domain outperforms algorithms based in only one domain. Independent studies are needed to validate these findings.

Differential biomarker signatures in unipolar and bipolar depression: A machine learning approach

OBJECTIVE

This study used machine learning techniques combined with peripheral biomarker measurements to build signatures to help differentiating (1) patients with bipolar depression from patients with unipolar depression, and (2) patients with bipolar depression or unipolar depression from healthy controls.

METHODS

We assessed serum levels of interleukin-2, interleukin-4, interleukin-6, interleukin-10, tumor necrosis factor-α, interferon-γ, interleukin-17A, brain-derived neurotrophic factor, lipid peroxidation and oxidative protein damage in 54 outpatients with bipolar depression, 54 outpatients with unipolar depression and 54 healthy controls, matched by sex and age. Depressive symptoms were assessed using the Hamilton Depression Rating Scale. Variable selection was performed with recursive feature elimination with a linear support vector machine kernel, and the leave-one-out cross-validation method was used to test and validate our model.

RESULTS

Bipolar vs unipolar depression classification achieved an area under the receiver operating characteristics (ROC) curve (AUC) of 0.69, with 0.62 sensitivity and 0.66 specificity using three selected biomarkers (interleukin-4, thiobarbituric acid reactive substances and interleukin-10). For the comparison of bipolar depression vs healthy controls, the model retained five variables (interleukin-6, interleukin-4, thiobarbituric acid reactive substances, carbonyl and interleukin-17A), with an AUC of 0.70, 0.62 sensitivity and 0.7 specificity. Finally, unipolar depression vs healthy controls comparison retained seven variables (interleukin-6, Carbonyl, brain-derived neurotrophic factor, interleukin-10, interleukin-17A, interleukin-4 and tumor necrosis factor-α), with an AUC of 0.74, a sensitivity of 0.68 and 0.70 specificity.

CONCLUSION

Our findings show the potential of machine learning models to aid in clinical practice, leading to more objective assessment. Future studies will examine the possibility of combining peripheral blood biomarker data with other biological data to develop more accurate signatures.

Homocysteine as a peripheral biomarker in bipolar disorder: A meta-analysis

Background:

Bipolar disorder (BD) is a psychiatric disorder with an uncertain aetiology. Recently, special attention has been given to homocysteine (Hcy), as it has been suggested that alterations in 1-carbon metabolism might be implicated in diverse psychiatric disorders. However, there is uncertainty regarding possible alterations in peripheral Hcy levels in BD.

Methods:

This study comprises a meta-analysis comparing serum and plasma Hcy levels in persons with BD and healthy controls. We conducted a systematic search for all eligible English and non-English peer-reviewed articles.

Results:

Nine cross-sectional studies were included in the meta-analyses, providing data on 1547 participants. Random-effects meta-analysis showed that serum and plasma levels of Hcy were increased in subjects with BD in either mania or euthymia when compared to healthy controls, with a large effect size in the mania group (g= 0.98, 95% CI: 0.8–1.17,P< 0.001,n= 495) and a small effect in the euthymia group (g= 0.3, 95% CI: 0.11–0.48,P= 0.002,n= 1052).

Conclusions:

Our meta-analysis provides evidence that Hcy levels are elevated in persons with BD during mania and euthymia. Peripheral Hcy could be considered as a potential biomarker in BD, both of trait (since it is increased in euthymia), and also of state (since its increase is more accentuated in mania). Longitudinal studies are needed to clarify the relationship between bipolar disorder and Hcy, as well as the usefulness of peripheral Hcy as both a trait and state biomarker in BD.

Longitudinal multi-level biomarker analysis of BDNF in major depression and bipolar disorder

Preliminary evidence suggests that BDNF (brain derived neurotrophic factor) rs6265 genetic polymorphism, BDNF gene promotor methylation and BDNF serum levels might play an important role in the pathogenesis of affective disorders. As studies testing the BDNF system across molecular levels are sparse, this study aimed at investigating the BDNF val66met genotype, BDNF DNA methylation changes and peripheral BDNF serum levels in acute and remitted phases of MDD (major depressive disorder) and BD (bipolar disorder) and healthy controls. We found a significant difference of methylation levels at CpG site 1-1-1 and 3-1-1 between MDD and healthy controls (p < 0.003) with MDD patients showing significantly higher methylation levels. CpG 5-2-1 revealed a statistically significant difference between MDD and healthy controls and MDD and BD (p = 0.00003). Similar to the results of the methylation analysis a significant difference between MDD and healthy controls was found in BDNF serum levels (p = 0.002) with significantly lower BDNF serum levels in MDD compared to healthy controls. A difference between the samples from admission and discharge from hospital of both BDNF gene methylation and serum levels could not be detected in the present study and no influence of the BDNF val66met genotype on neither methylation nor BDNF serum level.

RNA sequencing of bipolar disorder lymphoblastoid cell lines implicates the neurotrophic factor HRP-3 in lithium's clinical efficacy

Objectives: Lithium remains the oldest and most effective treatment for mood stabilisation in bipolar disorder (BD), even though at least half of patients are only partially responsive or do not respond. This study aimed to identify biomarkers associated with lithium response in BD, based on comparing RNA sequencing information derived from lymphoblastoid cell lines (LCLs) of lithium-responsive (LR) versus lithium non-responsive (LNR) BD patients, to assess gene expression variations that might bear on treatment outcome. Methods: RNA sequencing was carried out on 24 LCLs from female BD patients (12 LR and 12 LNR) followed by qPCR validation in two additional independent cohorts (41 and 17 BD patients, respectively). Results: Fifty-six genes showed nominal differential expression comparing LR and LNR (FC ≥ |1.3|, P ≤ 0.01). The differential expression of HDGFRP3 and ID2 was validated by qPCR in the independent cohorts. Conclusions: We observed higher expression levels of HDGFRP3 and ID2 in BD patients who favourably respond to lithium. Both of these genes are involved in neurogenesis, and HDGFRP3 has been suggested to be a neurotrophic factor. Additional studies in larger BD cohorts are needed to confirm the potential of HDGFRP3 and ID2 expression levels in blood cells as tentative favourable lithium response biomarkers.

Brain-derived neurotrophic factor as a possible predictor of electroconvulsive therapy outcome

While brain-derived neurotrophic factor (BDNF) has been shown to predict response to pharmacotherapy in depression, studies in electroconvulsive therapy (ECT) are small and report conflicting results. This study assesses the association between pre-treatment BDNF levels and ECT outcome in severe late-life unipolar depression (LLD). The potential of BDNF as a clinical predictor of ECT outcome was subsequently evaluated. Characteristics associated with low and high BDNF subgroups were determined as well. Ninety-four patients diagnosed with LDD referred for ECT were included. Fasting serum BDNF levels were determined before ECT. Remission and response, measured with the Montgomery-Åsberg Depression Rating Scale, were the outcomes. The association between BDNF and ECT outcome was analysed with logistic regression and Cox regression. The clinical usefulness of BDNF was evaluated using the receiver operating characteristic (ROC) curve. Associations between clinical characteristics and low versus high BDNF levels were examined with T tests, chi-squared tests and Mann-Whitney tests. The odds of remission decreased with 33% for every five units increase of BDNF levels (OR 0.67, 95% confidence interval 0.47-0.96; p = 0.03); however, neither the association with time to remission nor the associations with response nor the adjusted models were significant. The area under the ROC (0.66) implied a poor accuracy of BDNF as a clinical test. Clinical characteristics associated with BDNF were inclusion site, physical comorbidities and duration of the index episode. To conclude, although there is an association between pre-treatment BDNF levels and ECT outcome, BDNF cannot be considered an eligible biomarker for ECT outcome in clinical practice.

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.

Brain-derived neurotrophic factor (BDNF) and bipolar disorder

Brain-derived neurotrophic factor (BDNF) is deemed to be associated with the psychopathology of bipolar I disorder (BD). However, studies focusing on accuracy of BDNF levels to differentiate these patients from healthy controls (HCs) are scarce. Over a discrete twelve-year period, we investigated serum BDNF levels in patients with BD and compared them to age-, sex- and body mass index (BMI)-matched HCs. There were lower serum BDNF levels in 83 samples with BD than in 222 HCs samples (5.7 ± 4.2 ng/ml vs. 12.2 ± 7.5 ng/ml, F = 46.784). Pearson's correlation test showed significant positive correlations between Young Mania Rating Scale scores and the BDNF levels among 61 manic patients (γ = 0.339). The receiver operating characteristic curve analysis showed BDNF levels demonstrated a moderate accuracy of being able to differentiate BD patients from HCs (AUC = 0.801). The most adequate cut-off points of the BDNF level were 6.74 ng/ml (sensitivity = 82.0%, specificity = 63.9%). Our results support that BDNF demonstrated moderate accuracy to distinguish BD patients from HCs. In the future, greater samples would be required to prove these results.

Increased levels of plasma IL-1b and BDNF can predict resistant depression patients

SUMMARY BACKGROUND: There is no strong evidence on the link between inflammatory profile and pattern of drug treatment response in depressive patients that could result in Coronary Artery Disease occurrence. OBJECTIVE: This study aimed to compare the subclinical atherosclerosis markers, inflammatory profile, and BDNF production in Resistant Depression (RD) or Bipolar Affective Disorder (BAD) patients under conventional treatment. METHODS: The population evaluated was comprised of 34 RD, 43 BAD, and 41 controls. Subclinical atherosclerosis markers were evaluated using ultrasonography, tomography, and exercise stress test. Plasma concentrations of TNFα, IL-1β, IL-6, and BDNF were measured using Luminex100™. The usCRP concentration was measured using turbidimetric immunoassay. IL1B, IL6, and TNFA expression were determined using TaqMan®. For the statistical analysis, the significance level was established at p<0.05. RESULTS: Concerning subclinical atherosclerosis markers, only O2 consumption was reduced in the BAD group (p = 0.001). Although no differences were found in gene expression, BDNF and IL-1β plasma concentration was increased in the RD group (p = 0.002 and p = 0.005, respectively) even with an antidepressant treatment, which suggests that these drugs have no effect in IL-1β secretion and that the inflammasome may play a role in therapy response. CONCLUSION: Taken together, both BDNF and IL-1β plasma concentrations could be used to the early identification of RD patients.

Acute and subsequent continuation electroconvulsive therapy elevates serum BDNF levels in patients with major depression

INTRODUCTION

The induction of brain-derived neurotrophic factor (BDNF) release and subsequent restoration of neuroplastic homeostasis may underlie the effects of electroconvulsive therapy (ECT).

OBJECTIVES

We aimed to assess serum and plasma BDNF levels during the course of acute ECT, as well as before and after subsequent continuation ECT, in patients with depression.

METHODS

We included 24 patients with major depressive disorder (mean age ± SD: 54.5 ± 13.7; f/m: 17/7; baseline 17-item Hamilton Depression Rating Scale score of 26.79 ± 4.01). Serum and plasma BDNF (sBDNF, pBDNF) levels were assessed at nine time-points before, during, and after acute ECT series. Data were analysed using linear regression and linear mixed models, which were adjusted for multiple comparisons via Bonferroni correction. Five patients received continuation ECT subsequent to the acute ECT series. In these patients, BDNF levels were assessed before and after each two continuation ECT sessions using Wilcoxon signed-rank tests.

RESULTS

Relative to baseline (mean ng/ml ±SD: 24.68 ± 14.40), sBDNF levels were significantly higher 1 day (33.04 ± 14.11, p = 0.013, corrected), 1 week (37.03 ± 10.29, p < 0.001, corrected), and 1 month (41.05 ± 10.67, p = 0.008, corrected) after the final ECT session, while pBDNF levels did not significantly differ (p > 0.1). Furthermore, our results indicated that sBDNF levels increased after each continuation ECT session. There was no significant association between sBDNF levels and clinical parameters or treatment response.

CONCLUSION

The absence of an association between changes in sBDNF levels and depressive symptoms challenges the proposed concept of sBDNF/pBDNF as key markers of the effects of ECT.

Accuracy of brain-derived neurotrophic factor levels for differentiating between Taiwanese patients with major depressive disorder or schizophrenia and healthy controls

Objectives

Brain-derived neurotrophic factor (BDNF) has been associated with the psychopathology of both major depressive disorder (MDD) and schizophrenia (SZ). However, studies focusing on the accuracy of BDNF levels to differentiate between these patients and healthy controls (HCs) have been rare.

Methods

Over a discrete ten-year period, we investigated serum BDNF levels in patients with MDD or SZ and compared them to HCs.

Results

We found serum BDNF levels in 224 samples with SZ to be lower than those in 390 HCs samples (p = 0.007), but not lower than those in the 273 samples with MDD. Male MDD patients tended to have lower BDNF levels compared to male HCs (p = 0.083). The receiver operating characteristic curve analysis demonstrated that BDNF levels were moderately accurate in differentiating male MDD patients and female patients with SZ from HCs (AUC = 0.652 and 0.623, respectively). The most adequate cut-off points for BDNF level were 5.11 ng/ml (sensitivity = 81.1%, specificity = 48.5%) and 5.88 ng/ml (sensitivity = 74.1%, specificity = 57.4%), respectively.

Conclusions

Our results support that BDNF demonstrated moderate accuracy in distinguishing male patients with MDD and female patients with SZ from HCs. In the future, greater samples would be required to further confirm these results.

Objective and biological markers in bipolar spectrum presentations

INTRODUCTION

Subthreshold presentations of bipolarity (BSPs) pose a diagnostic conundrum, in terms of whether they should be conceptualized and treated similarly as traditionally defined bipolar disorders (BD). While it has been argued that BSPs are on a pathophysiologic continuum with traditionally defined BDs, there has been limited examination of biological and objective markers in these presentations to validate this assertion. Areas covered: The authors review studies examining genetic, neurobiological, cognitive and peripheral markers in BSPs, encompassing clinical and non-clinical populations with subthreshold hypo/manic symptoms. Results are placed in the context of previously identified markers in traditionally defined BDs. Expert commentary: There have been few studies of objective and biological markers in subthreshold presentations of BD, and results are mixed. While abnormalities in brain structure/functioning, peripheral inflammatory, and cognitive markers have been reported, it is unclear whether these findings are specific to BD or indicative of broad affective pathology. However, some studies suggest that increased sensitivity to reward and positive stimuli are shared between subthreshold and traditionally defined BDs, and may represent a point of departure from unipolar major depression. Further examination of such markers may improve understanding of subthreshold bipolar presentations, and provide guidance in terms of therapeutic strategies.

Can P300 aid in the differential diagnosis of unipolar disorder versus bipolar disorder depression? A meta-analysis of comparative studies

BACKGROUND

It is difficult to distinguish between bipolar disorder (BD) and unipolar disorder (UD) depression. Given the different pattern of cognitive impairments between BD and UD, P300 is potentially useful for the differential diagnosis. This meta-analysis was performed to estimate the extent of difference in P300 in patients with BD versus UD depression.

METHODS

Studies comparing P300 between depressed BD and UD patients with or without healthy controls (HCs) were retrieved from major English and Chinese databases. Studies with BD and UD samples that were comparable in terms of age, gender, and depression severity, were rated as having high quality. Standardized mean differences (SMDs) of P300 latency and amplitude were calculated.

RESULTS

In total, eight studies with a total of 397 depressed BD patients, 390 depressed UD patients, and 497 HCs, were included. Among included studies, six were rated as having good quality and three followed BD (n = 146) and UD (n = 144) patients during remission. BD patients had significantly longer P300 latency than UD patients during major depressive episode [SMD (95%CI): 0.580 (0.309, 0.850)] and remission [SMD (95%CI): 1.583 (1.322, 1.844)]. Compared to HCs, remitted BD patients still had significantly longer P300 latency [SMD (95%CI): 0.857 (0.059, 1.656)] but P300 latency of remitted UD patients had decreased to normal [SMD (95%CI): 0.536 (-0.272, 1.343)].

LIMITATIONS

Sample sizes of depressed and remitted patients with BD and UD of included studies are small.

CONCLUSIONS

P300 latency can be used as an auxiliary diagnostic marker for differentiating BD from UD depression.

Insight into the roles of hepatoma derived growth factor related protein-3 under physiological and pathological conditions

Hepatoma derived growth factor related protein-3 (HRP-3) is a HDGF growth factor family member that is expressed mainly in nervous tissues. It shares structural similarities with HDGF but differs in its expression and scope of action. It has recently attracted more attention due to its variable roles. HRP-3 was originally reported as a mitogenic factor. However, over the last decade, additional functions for this growth factor have been uncovered. In addition to its mitogenic activity, other physiological functions were discovered including those related to proliferation, differentiation, and maintenance of neurons, presenting it as a neurotrophic and neuroprotective growth factor. Interestingly, HRP-3 was also shown to be involved in the pathogenesis of certain tumors via its mitogenic, angiogenic, and antiapoptotic effects. Based on this, HRP-3 represents a molecule that can be targeted for the treatment of cancer and various neurodegenerative diseases.

Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach

Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown translational value. This study evaluated the prognostic value of a wide range of clinical, psychological, and biological characteristics for predicting the course of depression and aimed to identify the best set of predictors. Eight hundred four unipolar depressed patients (major depressive disorder or dysthymia) patients were assessed on a set involving 81 demographic, clinical, psychological, and biological measures and were clinically followed-up for 2 years. Subjects were grouped according to (i) the presence of a depression diagnosis at 2-year follow-up (yes n = 397, no n = 407), and (ii) three disease course trajectory groups (rapid remission, n = 356, gradual improvement n = 273, and chronic n = 175) identified by a latent class growth analysis. A penalized logistic regression, followed by tight control over type I error, was used to predict depression course and to evaluate the prognostic value of individual variables. Based on the inventory of depressive symptomatology (IDS), we could predict a rapid remission course of depression with an AUROC of 0.69 and 62% accuracy, and the presence of an MDD diagnosis at follow-up with an AUROC of 0.66 and 66% accuracy. Other clinical, psychological, or biological variables did not significantly improve the prediction. Among the large set of variables considered, only the IDS provided predictive value for course prediction on an individual level, although this analysis represents only one possible methodological approach. However, accuracy of course prediction was moderate at best and further improvement is required for these findings to be clinically useful.

Neurotrophins, cytokines, oxidative stress mediators and mood state in bipolar disorder: systematic review and meta-analyses

BACKGROUND

A reliable biomarker signature for bipolar disorder sensitive to illness phase would be of considerable clinical benefit. Among circulating blood-derived markers there has been a significant amount of research into inflammatory markers, neurotrophins and oxidative stress markers.AimsTo synthesise and interpret existing evidence of inflammatory markers, neurotrophins and oxidative stress markers in bipolar disorder focusing on the mood phase of illness.

METHOD

Following PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analyses) guidelines, a systematic review was conducted for studies investigating peripheral biomarkers in bipolar disorder compared with healthy controls. We searched Medline, Embase, PsycINFO, SciELO and Web of Science, and separated studies by bipolar mood phase (mania, depression and euthymia). Extracted data on each biomarker in separate mood phases were synthesised using random-effects model meta-analyses.

RESULTS

In total, 53 studies were included, comprising 2467 cases and 2360 controls. Fourteen biomarkers were identified from meta-analyses of three or more studies. No biomarker differentiated mood phase in bipolar disorder individually. Biomarker meta-analyses suggest a combination of high-sensitivity C-reactive protein/interleukin-6, brain derived neurotrophic factor/tumour necrosis factor (TNF)-α and soluble TNF-α receptor 1 can differentiate specific mood phase in bipolar disorder. Several other biomarkers of interest were identified.

CONCLUSIONS

Combining biomarker results could differentiate individuals with bipolar disorder from healthy controls and indicate a specific mood-phase signature. Future research should seek to test these combinations of biomarkers in longitudinal studies.Declaration of interestNone.

The Staging of Major Mood Disorders: Clinical and Neurobiological Correlates

OBJECTIVE

Staging of psychiatric disorders is gaining momentum and the purpose of this review is to examine whether major mood disorders can be defined according to stages.

METHODS

In April 2018 the PubMed electronic data base was scrutinized by a combination of various search terms like "major depressive disorder and staging," "bipolar disorder and neuroprogression," etc. To incorporate the latest findings the search was limited to the last 10 years. Both original and review articles were examined by reading the abstracts, and papers which were found to be particularly applicable were read in full and their reference lists were also consulted.

RESULTS

A significant increase occurred in the number of papers published on the topic of staging of mood disorders. Staging formats were found for both major mood disorders, with the caveat that many more articles were discovered for bipolar disorder. Current evidence points to allostatic load and neuroprogression as the basis for staging of mood disorders.

CONCLUSION

Principal affective illnesses may be characterized by distinct stages, for instance early, intermediate and late. These phases inform the management so that clinicians should incorporate the staging schema into everyday practice and implement treatment strategies according to the phase of the illness.

Suggested Biomarkers for Major Depressive Disorder

Currently, the diagnosis of major depressive disorder (MDD) mainly relies on clinical examination and subjective evaluation of depressive symptoms. There is no non-invasive, quantitative test available today for the diagnosis of MDD. In MDD, exploration of biomarkers will be helpful in diagnosing the disorder as well as in choosing a treatment, and predicting the treatment response. In this article, it is aimed to review the findings of suggested biomarkers such as growth factors, cytokines and other inflammatory markers, oxidative stress markers, endocrine markers, energy balance hormones, genetic and epigenetic features, and neuroimaging in MDD and to evaluate how these findings contribute to the pathophysiology of MDD, the prediction of treatment response, severity of the disorder, and identification of subtypes. Among these, the findings related to the brain-derived neurotrophic factor, the hypothalamo-pituitary-adrenal axis, cytokines, and neuroimaging may be strong candidates for being biomarkers MDD, and may provide critical information in understanding biological etiology of depression. Although the findings are not sufficient yet, we think that the results of epigenetic studies will also provide very important contributions to the biomarker research in MDD. The availability of biomarkers in MDD will be an advancement that will facilitate the diagnosis of the disorder, treatment choices in the early stages, and prediction of the course of the disorder.

Potential biomarkers for bipolar disorder: Where do we stand?

Bipolar disorder (BD) is a severe, recurrent mood disorder, associated with a significant morbidity and mortality, with high rates of suicides and medical comorbidities. There is a high risk of mood disorders among the first-degree relatives of patients with BD. In the current clinical practice, the diagnosis of BD is made by history taking, interview and behavioural observations, thereby lacking an objective, biological validation. This approach may result in underdiagnosis, misdiagnosis and eventually poorer outcomes. Due to the heterogeneity of BD, the possibility of developing a single, specific biomarker is still remote; however, there is a set of promising biomarkers which may serve as predictive, prognostic or treatment markers in the future. The review presents a critical appraisal and update on some of the most promising candidates for biomarkers, namely, neuroimaging markers, peripheral biomarkers and genetic markers, including a brief discussion on cognitive endophenotypes as indicative of genetic risk. The lessons learnt from other fields and specialties in medicine need to be applied to psychiatry to translate the knowledge from ‘bench to bedside’ by means of clinically useful biomarkers. Overall, the biomarkers may help in pushing the shift towards personalized medicine for psychiatric patients.

Toward Precision Psychiatry in Bipolar Disorder: Staging 2.0

Personalized treatment is defined as choosing the "right treatment for the right person at the right time." Although psychiatry has not yet reached this level of precision, we are on the way thanks to recent technological developments that may aid to detect plausible molecular and genetic markers. At the moment there are some models that are contributing to precision psychiatry through the concept of staging. While staging was initially presented as a way to categorize patients according to clinical presentation, course, and illness severity, current staging models integrate multiple levels of information that can help to define each patient's characteristics, severity, and prognosis in a more precise and individualized way. Moreover, staging might serve as the foundation to create a clinical decision-making algorithm on the basis of the patient's stage. In this review we will summarize the evolution of the bipolar disorder staging model in relation to the new discoveries on the neurobiology of bipolar disorder. Furthermore, we will discuss how the latest and future progress in psychiatry might transform current staging models into precision staging models.

On the transdiagnostic nature of peripheral biomarkers in major psychiatric disorders: A systematic review

The search for biomarkers has been a leading endeavor in biological psychiatry. To analyze its evolution over the years, we performed a systematic review to evaluate (a) the most studied peripheral molecular markers in major psychiatric disorders, (b) the main features of studies proposing them as biomarkers and (c) whether their patterns of variation are similar across disorders. Of the six molecules most commonly studied as plasmatic markers of schizophrenia, major depressive disorder or bipolar disorder, five (BDNF, TNF-alpha, IL-6, C-reactive protein and cortisol) were the same across diagnoses. An analysis of this literature showed that, while 66% of studies compared patients and controls, only 34% were longitudinal, and only 10% presented a measure of diagnostic or prognostic efficacy. Meta-analyses showed variation in the levels of these molecules to be robust across studies, but similar among disorders, suggesting them to reflect transdiagnostic systemic consequences of psychiatric illness. Based on this, we discuss how current publication practices have led to research fragmentation across diagnoses, and suggest approaches to face this issue.

Serum concentrations of brain-derived neurotrophic factor in patients diagnosed with gender dysphoria undergoing sex reassignment surgery

Introduction:

Transsexualism (ICD-10) is a condition characterized by a strong and persistent dissociation with one's assigned gender. Sex reassignment surgery (SRS) and hormone therapy provide a means of allowing transsexual individuals to feel more congruent with their gender and have played a major role in treatment over the past 70 years. Brain-derived neurotrophic factor (BDNF) appears to play a key role in recovery from acute surgical trauma and environmentally mediated vulnerability to psychopathology. We hypothesize that BDNF may be a biomarker of alleviation of gender incongruence suffering.

Objectives:

To measure preoperative and postoperative serum BDNF levels in transsexual individuals as a biomarker of alleviation of stress related to gender incongruence after SRS.

Methods:

Thirty-two male-to-female transsexual people who underwent both surgery and hormonal treatment were selected from our initial sample. BDNF serum levels were assessed before and after SRS with sandwich enzyme linked immunosorbent assay (ELISA). The time elapsed between the pre-SRS and post-SRS blood collections was also measured.

Results:

No significant difference was found in pre-SRS or post-SRS BDNF levels or with relation to the time elapsed after SRS when BDNF levels were measured.

Conclusion:

Alleviation of the suffering related to gender incongruence after SRS cannot be assessed by BDNF alone. Surgical solutions may not provide a quick fix for psychological distress associated with transsexualism and SRS may serve as one step toward, rather than as the conclusion of, construction of a person's gender identity.

The new field of 'precision psychiatry'

BACKGROUND

Precision medicine is a new and important topic in psychiatry. Psychiatry has not yet benefited from the advanced diagnostic and therapeutic technologies that form an integral part of other clinical specialties. Thus, the vision of precision medicine as applied to psychiatry - 'precision psychiatry' - promises to be even more transformative than in other fields of medicine, which have already lessened the translational gap.

DISCUSSION

Herein, we describe 'precision psychiatry' and how its several implications promise to transform the psychiatric landscape. We pay particular attention to biomarkers and to how the development of new technologies now makes their discovery possible and timely. The adoption of the term 'precision psychiatry' will help propel the field, since the current term 'precision medicine', as applied to psychiatry, is impractical and does not appropriately distinguish the field. Naming the field 'precision psychiatry' will help establish a stronger, unique identity to what promises to be the most important area in psychiatry in years to come.

CONCLUSION

In summary, we provide a wide-angle lens overview of what this new field is, suggest how to propel the field forward, and provide a vision of the near future, with 'precision psychiatry' representing a paradigm shift that promises to change the landscape of how psychiatry is currently conceived.

Biological hypotheses and biomarkers of bipolar disorder

The most common mood disorders are major depressive disorders and bipolar disorders (BD). The pathophysiology of BD is complex, multifactorial, and not fully understood. Creation of new hypotheses in the field gives impetus for studies and for finding new biomarkers for BD. Conversely, new biomarkers facilitate not only diagnosis of a disorder and monitoring of biological effects of treatment, but also formulation of new hypotheses about the causes and pathophysiology of the BD. BD is characterized by multiple associations between disturbed brain development, neuroplasticity, and chronobiology, caused by: genetic and environmental factors; defects in apoptotic, immune-inflammatory, neurotransmitter, neurotrophin, and calcium-signaling pathways; oxidative and nitrosative stress; cellular bioenergetics; and membrane or vesicular transport. Current biological hypotheses of BD are summarized, including related pathophysiological processes and key biomarkers, which have been associated with changes in genetics, systems of neurotransmitter and neurotrophic factors, neuroinflammation, autoimmunity, cytokines, stress axis activity, chronobiology, oxidative stress, and mitochondrial dysfunctions. Here we also discuss the therapeutic hypotheses and mechanisms of the switch between depressive and manic state.

Beyond the therapeutic shackles of the monoamines: New mechanisms in bipolar disorder biology

Multiple novel biological mechanisms putatively involved in the etiology of bipolar disorders are being explored. These include oxidative stress, altered glutamatergic neurotransmission, mitochondrial dysfunction, inflammation, cell signaling, apoptosis and impaired neurogenesis. Important clinical translational potential exists for such mechanisms to help underpin development of novel therapeutics - much needed given limitations of current therapies. These new mechanisms also help improve our understanding of how current therapeutics might exert their effects. Lithium, for example, appears to have antioxidant, immunomodulatory, signaling, anti-apoptotic and neuroprotective properties. Similar properties have been attributed to other mood stabilizers such as valproate, lamotrigine, and quetiapine. Perhaps of greatest translational value has been the recognition of such mechanisms leading to the emergence of novel therapeutics for bipolar disorders. These include the antioxidant N-acetylcysteine, the anti-inflammatory celecoxib, and ketamine - with effects on the glutamatergic system and microglial inhibition. We review these novel mechanisms and emerging therapeutics, and comment on next steps in this space.

The correlation between plasma brain-derived neurotrophic factor and cognitive function in bipolar disorder is modulated by the BDNF Val66Met polymorphism

We explored the effect of the Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism (rs6265) on correlation between changes in plasma BDNF levels with cognitive function and quality of life (QoL) after 12 weeks of treatment in bipolar disorder (BD). Symptom severity and plasma BDNF levels were assessed upon recruitment and during weeks 1, 2, 4, 8 and 12. QoL, the Wisconsin Card Sorting Test (WCST), and the Conners’ Continuous Performance Test (CPT) were assessed at baseline and endpoint. The BDNF Val66Met polymorphism was genotyped. Changes in cognitive function and QoL over 12 weeks were reduced using factor analysis for the evaluation of their correlations with changes in plasma BDNF. Five hundred forty-one BD patients were recruited and 65.6% of them completed the 12-week follow-up. Changes in plasma BDNF levels with factor 1 (WCST) were significantly negatively correlated (r = −0.25, p = 0.00037). After stratification of BD subtypes and BDNF genotypes, this correlation was significant only in BP-I and the Val/Met genotype (r = −0.54, p = 0.008). We concluded that changes in plasma BDNF levels significantly correlated with changes in WCST scores in BD and is moderated by the BDNF Val66Met polymorphism and the subtype of BD.

Ratio of mBDNF to proBDNF for Differential Diagnosis of Major Depressive Disorder and Bipolar Depression

There is a high rate of misdiagnosis between major depressive disorder (MDD) and bipolar disorder (BD) in clinical practice. Our previous work provided suggestive evidence for brain-derived neurotrophic factor (BDNF) in differentiating BD from MDD. In this study, we aimed to investigate the role of mature BDNF (mBDNF) and its precursor (proBDNF) in distinguishing bipolar depression (BP) from MDD during acute depressive episode. A total of 105 participants, including 44 healthy controls, 37 MDD patients and 24 BP patients, were recruited. Enzyme-linked immunosorbent assay kits were applied to measure plasma mBDNF levels and proBDNF levels of all participants. Plasma mBDNF levels were significantly decreased in BP group than those in MDD group (P = 0.001) and healthy controls (P = 0.002). Significantly higher ratio of mBDNF to proBDNF (M/P) at baseline was showed in MDD group than those in BP group as well as in healthy controls (P = 0.000 and P = 0.000, respectively). The optimal model for discriminating BP was the M/P ratio (area under the ROC curve = 0.858, 95 % CI 0.753-0.963). Furthermore, the M/P ratio was restored to normal levels after antidepressants treatment in MDD group. In summary, our data demonstrated that both plasma mBDNF levels and M/P ratio were lower in BP compared with MDD. These findings further support M/P ratio as a potential differential diagnostic biomarker for BP among patients in depressive episodes.

The Differential Levels of Inflammatory Cytokines and BDNF among Bipolar Spectrum Disorders

OBJECTIVE

Emerging evidence suggests that inflammation and neurodegeneration underlies bipolar disorder. To investigate biological markers of cytokines and brain-derived neurotrophic factor between bipolar I, bipolar II, and other specified bipolar disorder with short duration hypomania may support the association with inflammatory dysregulation and bipolar disorder and, more specifically, provide evidence for other specified bipolar disorder with short duration hypomania patients were similar to bipolar II disorder patients from a biological marker perspective.

METHODS

We enrolled patients with bipolar I disorder (n=234), bipolar II disorder (n=260), other specified bipolar disorder with short duration hypomania (n=243), and healthy controls (n=140). Their clinical symptoms were rated using the Hamilton Depression Rating Scale and Young Mania Rating Scale. Inflammatory cytokine (tumor necrosis factor-α, C-reactive protein, transforming growth factor-β1, and interleukin-8) and brain-derived neurotrophic factor levels were measured in each group. Multivariate analysis of covariance and linear regression controlled for possible confounders were used to compare cytokine and brain-derived neurotrophic factor levels among the groups.

RESULTS

Multivariate analysis of covariance adjusted for age and sex and a main effect of diagnosis was significant (P<.001). Three of the 5 measured biomarkers (tumor necrosis factor-α, transforming growth factor-β1, and interleukin-8) were significantly (P=.006, .01, and <.001) higher in all bipolar disorder patients than in controls. Moreover, covarying for multiple associated confounders showed that bipolar I disorder patients had significantly higher IL-8 levels than did bipolar II disorder and other specified bipolar disorder with short duration hypomania patients in multivariate analysis of covariance (P=.03) and linear regression (P=.02) analyses. Biomarkers differences between bipolar II disorder and other specified bipolar disorder with short duration hypomania patients were nonsignificant.

CONCLUSION

The immunological disturbance along the bipolar spectrum was most severe in bipolar I disorder patients. Other specified bipolar disorder with short duration hypomania patients and bipolar II disorder patients did not differ in these biological markers.

Rapamycin blocks the antidepressant effect of ketamine in task-dependent manner

OBJECTIVE

The aim of our study was to test whether ketamine produces an antidepressant effect in animal model of olfactory bulbectomy and assess the role of mammalian target of rapamycin (mTOR) pathway in ketamine's antidepressant effect.

METHODS

Bulbectomized (OBX) rats and sham controls were assigned to four subgroups according to the treatment they received (ketamine, saline, ketamine + rapamycin, and saline + rapamycin). The animals were subjected to open field (OF), elevated plus maze (EPM), passive avoidance (PA), Morris water maze (MWM), and Carousel maze (CM) tests. Blood samples were collected before and after drug administration for analysis of phosphorylated mTOR level. After behavioral testing, brains were removed for evaluation of brain-derived neurotrophic factor (BDNF) in prefrontal cortex (PFC) and hippocampus.

RESULTS

Ketamine normalized hyperactivity of OBX animals in EPM and increased the time spent in open arms. Rapamycin pretreatment resulted in elimination of ketamine effect in EPM test. In CM test, ketamine + rapamycin administration led to cognitive impairment not observed in saline-, ketamine-, or saline + rapamycin-treated OBX rats. Prefrontal BDNF content was significantly decreased, and level of mTOR was significantly elevated in OBX groups.

CONCLUSIONS

OBX animals significantly differed from sham controls in most of the tests used. Treatment had more profound effect on OBX phenotype than controls. Pretreatment with rapamycin eliminated the anxiolytic and antidepressant effects of ketamine in task-dependent manner. The results indicate that ketamine + rapamycin application resulted in impaired stress responses manifested by cognitive deficits in active place avoidance (CM) test. Intensity of stressor (mild vs. severe) used in the behavioral tests had opposite effect on controls and on OBX animals.

Staging Models in Bipolar Disorder: A Systematic Review of the Literature

Bipolar disorder is manifested as severe dysregulation of mood with recurrent manic and major depressive episodes. It is associated with psychiatric and medical comorbidities, inadequate response to currently available pharmacological agents and a progressively deteriorating course in many patients. The index episode is often depressive in nature, while the first manic or hypomanic episode may occur several years later in the course of the disorder causing delay in diagnosis and use of inappropriate treatment strategies. Staging has been used to great advantage in other branches of medicine like cardiology and oncology. There is growing realization that major mental disorders are fundamentally progressive, with simpler treatment requirements and better prognosis during initial stages of the illness. Defining these conditions into clinically applicable stages not only helps in better understanding the trajectory of a particular disorder, but also assists in management. Patients with a chronic, recalcitrant condition like bipolar disorder are likely to greatly benefit from this approach. If the illness is correctly identified early in its course, proper treatment can be instigated arresting progression to latter phases which are associated with myriad complications in the biopsychosocial realm. With these considerations, a search of the MEDLINE data base was conducted to seek out literature pertaining to staging models in bipolar disorder. A thorough scrutiny of the existing research work revealed that a number of investigators have endeavored to stage define bipolar disorder. This paper outlines staging proposals for bipolar disorder which have the greatest supporting evidence in the literature.

C-reactive protein is increased in schizophrenia but is not altered by antipsychotics: meta-analysis and implications

The inflammatory hypothesis of schizophrenia (SZ) posits that inflammatory processes and neural-immune interactions are involved in its pathogenesis, and may underpin some of its neurobiological correlates. SZ is the psychiatric disorder causing the most severe burden of illness, not just owing to its psychiatric impairment, but also owing to its significant medical comorbidity. C-reactive protein (CRP) is a commonly used biomarker of systemic inflammation worldwide. There are some conflicting results regarding the behaviour of CRP in SZ. The aims of this study were to verify whether peripheral CRP levels are indeed increased in SZ, whether different classes of antipsychotics divergently modulate CRP levels and whether its levels are correlated with positive and negative symptomatology. With that in mind, we performed a meta-analysis of all cross-sectional studies of serum and plasma CRP levels in SZ compared to healthy subjects. In addition, we evaluated longitudinal studies on CRP levels before and after antipsychotic use. Our meta-analyses of CRP in SZ included a total of 26 cross-sectional or longitudinal studies comprising 85 000 participants. CRP levels were moderately increased in persons with SZ regardless of the use of antipsychotics and did not change between the first episode of psychosis and with progression of SZ (g=0.66, 95% confidence interval (95% CI) 0.43 to 0.88, P<0.001, 24 between-group comparisons, n=82 962). The extent of the increase in peripheral CRP levels paralleled the increase in severity of positive symptoms, but was unrelated to the severity of negative symptoms. CRP levels were also aligned with an increased body mass index. Conversely, higher age correlated with a smaller difference in CRP levels between persons with SZ and controls. Furthermore, CRP levels did not increase after initiation of antipsychotic medication notwithstanding whether these were typical or atypical antipsychotics (g=0.01, 95% CI -0.20 to 0.22, P=0.803, 8 within-group comparisons, n=713). In summary, our study provides further evidence of the inflammatory hypothesis of SZ. Whether there is a causal relationship between higher CRP levels and the development of SZ and aggravation of psychotic symptoms, or whether they are solely a marker of systemic low-grade inflammation in SZ, remains to be clarified.