Peripheral vascular endothelial growth factor as a novel depression biomarker: A meta-analysis

What happens when the lights are left on? Transcriptomic and phenotypic habituation to light pollution

Artificial light at night (ALAN) is a ubiquitous pollutant worldwide. Exposure can induce immediate behavioral and physiological changes in animals, sometimes leading to severe health consequences. Nevertheless, many organisms persist in light-polluted environments and may have mechanisms of habituating, reducing responses to repeated exposure over time, but this has yet to be tested experimentally. Here, we tested whether zebra finches (Taeniopygia guttata) can habituate to dim (0.3 lux) ALAN, measuring behavior, physiology (oxidative stress and telomere attrition), and gene expression in a repeated measures design, over 6 months. We present evidence of tolerance to chronic exposure, persistent behavioral responses lasting 8 weeks post-exposure, and attenuation of responses to re-exposure. Oxidative stress decreased under chronic ALAN. Changes in the blood transcriptome revealed unique responses to past exposure and re-exposure. Results demonstrate organismal resilience to chronic stressors and shed light on the capacity of birds to persist in an increasingly light-polluted world.

Estrogen, progesterone, cortisol, brain-derived neurotrophic factor, and vascular endothelial growth factor during the luteal phase of the menstrual cycle in women with premenstrual dysphoric disorder

The interplay between ovarian hormones, stress, and inflammatory markers in developing premenstrual dysphoric disorder (PMDD) remains inadequately understood. This study investigated the associations of dynamic changes in the levels of estrogen, progesterone, cortisol, brain-derived neurotrophic factor (BDNF), and vascular endothelial growth factor (VEGF) with PMDD during the luteal phase of the menstrual cycle. A total of 58 women with PMDD and 50 healthy women were recruited in this study. These women's estrogen, progesterone, cortisol, BDNF, and VEGF levels were evaluated during the preovulation (PO), mid-luteal (ML), and late-luteal (LL) phases. Furthermore, the severity of P MDD symptoms, depressive symptoms, perceived stress, inattention, craving for sweet foods, and fatigue was assessed. The findings revealed that women with PMDD with higher levels of progesterone during the ML or LL phase or a greater increase (ML-PO) or higher sum (ML + LL) of luteal progesterone level exhibited a greater increase in PMDD symptoms during the luteal phase than did the healthy controls. Furthermore, women with PMDD exhibited higher cortisol levels during the LL phase than did the controls. The BDNF level was negatively correlated with PMDD severity. Furthermore, BDNF and VEGF levels were negatively correlated with inattention and craving for sweet foods among women with PMDD. These results suggest an association between progesterone and the exacerbation of PMDD symptoms during the LL phase. Women with PMDD have relatively high cortisol levels during the LL phase. Future investigations with experimental designs or larger sample sizes are warranted to verify the roles of progesterone and cortisol in the development of PMDD.

Major depressive disorder: biomarkers and biosensors

Depressive disorders belong to highly heterogeneous psychiatric diseases. Loss of in interest in previously enjoyed activities and a depressed mood are the main characteristics of major depressive disorder (MDD). Moreover, due to significant heterogeneity in clinical presentation and lack of applicable biomarkers, diagnosis and treatment remains challenging. Identification of relevant biomarkers would allow for improved disease classification and more personalized treatment strategies. Herein, we review the current state of these biomarkers and then discuss diagnostic techniques of aimed to specifically target these analytes using state of the art biosensor technology.

The effects of ketamine and classic hallucinogens on neurotrophic and inflammatory markers in unipolar treatment-resistant depression: a systematic review of clinical trials

Although results are still preliminary, ketamine and classical hallucinogens have shown promise in recent years as novel, fast-acting antidepressants, especially for the treatment of unipolar treatment-resistant depression (TRD). Depression also seems to be related to abnormal levels of peripheral inflammatory and neurotrophic biomarkers, which may one day help to diagnose of this disorder. In this context, this systematic review of clinical trials evaluated the current evidence that relates the antidepressant effects of ketamine and classical hallucinogens on TRD with changes in inflammatory and neurotrophic biomarkers. Twelve studies were found (n = 587), 2 with oral ayahuasca (1 mL/kg) and 10 with ketamine (mostly intravenous 0.5 mg/kg) administration. Results for all biomarkers assessed were contradictory and thus inconclusive. Randomized controlled trials with bigger samples and higher statistical power are warranted to clarify if peripheral biomarkers can confidently be used to indicate and measure ketamine's and classical hallucinogens' antidepressant effect. The PROSPERO ID for this study is CRD42021249089.

Prediction of depressive symptoms onset and long-term trajectories in home-based older adults using machine learning techniques

OBJECTIVES

Our aim was to explore the possibility of using machine learning (ML) in predicting the onset and trajectories of depressive symptom in home-based older adults over a 7-year period.

METHODS

Depressive symptom data (collected in the year 2011, 2013, 2015 and 2018) of home-based older Chinese (n = 2650) recruited in the China Health and Retirement Longitudinal Study (CHARLS) were included in the current analysis. The latent class growth modeling (LCGM) and growth mixture modeling (GMM) were used to classify different trajectory classes. Based on the identified trajectory patterns, three ML classification algorithms (i.e. gradient boosting decision tree, support vector machine and random forest) were evaluated with a 10-fold cross-validation procedure and a metric of the area under the receiver operating characteristic curve (AUC).

RESULTS

Four trajectories were identified for the depressive symptoms: no symptoms (63.9%), depressive symptoms onset {incident increasing symptoms [new-onset increasing (16.8%)], chronic symptoms [slowly decreasing (12.5%), persistent high (6.8%)]}. Among the analyzed baseline variables, the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) score, cognition, sleep time, self-reported memory were the top five important predictors across all trajectories. The mean AUCs of the three predictive models had a range from 0.661 to 0.892.

CONCLUSIONS

ML techniques can be robust in predicting depressive symptom onset and trajectories over a 7-year period with easily accessible sociodemographic and health information.

Supplemental data for this article is available online at http://dx.doi.org/10.1080/13607863.2022.2031868.

Single dose S-ketamine rescues transcriptional dysregulation of Mtor and Nrp2 in the prefrontal cortex of FSL rats 1 hour but not 14 days post dosing

There is a pressing need to identify biological indicators of major depression to help guide proper diagnosis and optimize treatment. Animal models mimicking aspects of depression constitute essential tools for early-stage exploration of relevant pathways. In this study, we used the Flinders Sensitive and Resistant Line (FSL/FRL) to explore central and peripheral transcriptional changes in vascular endothelial growth factor (VEGF) pathway genes and their temporal regulation after a single dose of S-ketamine (15 mg/kg). We found that S-ketamine induced both rapid (1 hour) and sustained (2 and 14 days) antidepressant-like effects in the FSL rats. Analysis of mRNA expression revealed significant strain effects of Vegf, Vegf164, Vegfr-1, Nrp1, Nrp2, Rictor, and Raptor in the prefrontal cortex (PFC) and of Vegf164, GbetaL, and Tsc1 in the hippocampus (HIP), which indicates suppression of VEGF signaling in the FSL rats compared to FRL rats. This notion was further substantiated by reduced expression of Vegf and Mtor in plasma from FSL rats. In the brain, S-ketamine induced transcriptional changes in the acute phase, not the sustained phase. There were significant treatment effects of S-ketamine on Vegfr-2 in both PFC and HIP and on Vegf and Vegfr-1 in HIP. Moreover, we found that S-ketamine specifically restored reduced levels of Nrp2 and Mtor in the PFC of the FSL rats. In conclusion, this study substantiates the use of the FRL/FSL rats to explore the depressive-like behavior at the transcriptional level of the VEGF pathway genes and study their regulation in response to various treatment paradigms.

Longitudinal assessment of inflammatory markers in the peripartum period by depressive symptom trajectory groups

Objective

Mechanisms driving temporal fluctuations of inflammatory markers during pregnancy, and how these might differ between distinct perinatal depressive trajectories, are not well understood. The aim of this study was to investigate cytokines levels over the course of pregnancy in women with different trajectories of depressive symptoms peripartum, and relate the levels to levels of non-pregnant controls.

Methods

Based on the Edinburgh Postnatal Depression Scale and/or selective serotonin reuptake inhibitors use, 131 women were categorized into: no (n = 65); antepartum (APD, n = 19), postpartum (PPD, n = 17) and persistent (n = 30) depressive symptoms. Plasma samples (n = 386) were analyzed for levels of interleukin (IL)-8, IL-18, Tumor necrosis factor-α, macrophage colony-stimulating factor (M-CSF), vascular endothelial growth factor A (VEGF-A) and fractalkine, at four different time-points (twice during pregnancy, during childbirth, and postpartum) using Bio-Plex Pro Human Cytokine Assays. Generalized linear mixed models were applied to analyze the associations between cytokine levels, time-point, perinatal depressive symptom trajectory group and their interaction.

Results

For all markers but VEGF-A, pregnancy was associated with higher cytokine levels compared to the non-pregnant controls, with delivery being the most prominent time-point. For M-CSF, IL-18 and VEGF-A, levels were back to the non-pregnant status at postpartum week 8. An effect of perinatal depressive symptom trajectory groups on cytokine levels was found for VEGF-A. Women with PPD and women with APD had lower levels of VEGF-A throughout the study period compared to women with persistent depression, and women with PPD had lower levels compared to non-depressed women.

Conclusions

Lower levels of VEGF-A were noted among women in some trajectories of depressive symptoms peripartum. The peripartum period is a time of tremendous immune system adaptations. Standardization of time-points for cytokine measurements in studies of perinatal depression are important in order to draw valid conclusions on the role of the immune system in perinatal depression.

Neurobiological Highlights of Cognitive Impairment in Psychiatric Disorders

This review is focused on several psychiatric disorders in which cognitive impairment is a major component of the disease, influencing life quality. There are plenty of data proving that cognitive impairment accompanies and even underlies some psychiatric disorders. In addition, sources provide information on the biological background of cognitive problems associated with mental illness. This scientific review aims to summarize the current knowledge about neurobiological mechanisms of cognitive impairment in people with schizophrenia, depression, mild cognitive impairment and dementia (including Alzheimer's disease).The review provides data about the prevalence of cognitive impairment in people with mental illness and associated biological markers.

Associations of Serum Cytokines, Growth Factors, and High-Sensitivity C-Reactive Protein Levels in Patients with Major Depression with and without Type 2 Diabetes Mellitus: An Explanatory Investigation

PURPOSE

We investigated the serum levels of cytokines, including interleukin 1β (IL-β), IL-6, IL-8, IL-10, tumor necrosis factor-alpha (TNF-α), and growth factors, including brain-derived neurotrophic factor, vascular endothelial growth factor, and insulin-like growth factor 1, and their association with major depression in patients with and without type 2 diabetes mellitus. We also investigated the response to antidepressant treatment in both groups.

PATIENTS AND METHODS

Forty-one patients with major depression were recruited at the University Hospital of Occupational and Environmental Health. All patients were diagnosed with major depression using the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition. Type 2 diabetes mellitus was diagnosed according to the criteria of the Japan Diabetes Society. Six healthy controls with no history of psychiatric or physical diseases were also enrolled. Serum levels of several cytokines, growth factors, and high-sensitivity C-reactive protein (hs-CRP) were measured. The clinical symptoms of patients with major depression were assessed using the Montgomery-Asberg Depression Rating Scale.

RESULTS

Significant differences in cytokines, growth factors, and hs-CRP were observed between the major depression and healthy control groups. Serum TNF-α levels were significantly higher in patients with major depression and type 2 diabetes mellitus than in those without type 2 diabetes mellitus. In the major depression group, serum IL-6 and hs-CRP levels tended to be higher in patients with type 2 diabetes mellitus than in those without. Several correlations among cytokines, growth factors, and hs-CRP were observed in patients with major depression with and without type 2 diabetes mellitus. Responses to pharmacological interventions for major depression did not differ between patients with and without type 2 diabetes mellitus.

CONCLUSION

Serum levels of TNF-α, hs-CRP, and IL-6 were different between patients with major depression with and without type 2 diabetes mellitus. Also, correlations were found between serum levels of cytokines, growth factors, and hs-CRP in patients with major depression. Inflammatory factors, which may be associated with growth factors, may be involved in the pathophysiology of major depression, particularly among patients with comorbid type 2 diabetes mellitus.

Pathomechanisms of Vascular Depression in Older Adults

Depression in older individuals is a common complex mood disorder with high comorbidity of both psychiatric and physical diseases, associated with high disability, cognitive decline, and increased mortality The factors predicting the risk of late-life depression (LLD) are incompletely understood. The reciprocal relationship of depressive disorder and age- and disease-related processes has generated pathogenic hypotheses and provided various treatment options. The heterogeneity of depression complicates research into the underlying pathogenic cascade, and factors involved in LLD considerably differ from those involved in early life depression. Evidence suggests that a variety of vascular mechanisms, in particular cerebral small vessel disease, generalized microvascular, and endothelial dysfunction, as well as metabolic risk factors, including diabetes, and inflammation that may induce subcortical white and gray matter lesions by compromising fronto-limbic and other important neuronal networks, may contribute to the development of LLD. The "vascular depression" hypothesis postulates that cerebrovascular disease or vascular risk factors can predispose, precipitate, and perpetuate geriatric depression syndromes, based on their comorbidity with cerebrovascular lesions and the frequent development of depression after stroke. Vascular burden is associated with cognitive deficits and a specific form of LLD, vascular depression, which is marked by decreased white matter integrity, executive dysfunction, functional disability, and poorer response to antidepressive therapy than major depressive disorder without vascular risk factors. Other pathogenic factors of LLD, such as neurodegeneration or neuroimmune regulatory dysmechanisms, are briefly discussed. Treatment planning should consider a modest response of LLD to antidepressants, while vascular and metabolic factors may provide promising targets for its successful prevention and treatment. However, their effectiveness needs further investigation, and intervention studies are needed to assess which interventions are appropriate and effective in clinical practice.

Effects of Training with Different Modes of Strength Intervention on Psychosocial Disorders in Adolescents: A Systematic Review and Meta-Analysis

Physical exercise has a positive impact on anxiety and depression. However, the evidence that associates strength training with a decrease in adolescents' psychosocial disorders is scarce. Consequently, the objective was to analyze the effects of training with different modes of strength intervention on anxiety, stress, and depression in adolescents. The search was designed according to PRISMA^®. We searched WoS, Scopus, SPORTDiscus, PubMed, and MEDLINE (2010-2020). Methodological quality and risk of bias were assessed with the Cochrane Collaboration. The analysis was carried out with a standardized mean difference (SMD) pooled using the Hedges g test (95% CI). The Main Outcome Measures were: anxiety, stress, and depression in adolescents post strength training. Nine studies were included in the systematic review and seven in the meta-analysis. These studies showed a large and significant effect of strength training on anxiety (SMD = -1.75; CI = 95%: -3.03, -0.48; p = 0.007) and depression (SMD = -1.61; CI = 95%: -2.54, -0.67, p = 0.0007). In conclusion, training with different modes of strength intervention have shown control over anxiety and depression in adolescents. However, conventional strength training seems to have better results than other modes of strength intervention.

Isoforms of soluble vascular endothelial growth factor in stress-related mental disorders: a cross-sectional study

Vascular endothelial growth factor (VEGF) has been implicated in the pathophysiology of stress-related mental disorders. However, VEGF levels have seldom been compared across mental disorders and never by isoforms. Pathophysiological processes involving leakage of astrocyte-derived extracellular vesicles (EVs) across the blood–brain barrier could be associated with VEGF levels in patients with stress-related mental disorders. This cross-sectional study compared plasma levels of VEGF₁₂₁, VEGF₁₆₅, and VEGF₁₂₁ + VEGF₁₆₅ (VEGF_total) in patients with stress-induced exhaustion disorder (SED) (n = 31), patients with major depressive disorder (MDD) (n = 31), and healthy controls (n = 61). It also analyzed the correlation between VEGF and astrocyte-derived EVs in plasma. An enzyme-linked immunosorbent assay (ELISA) was used to measure VEGF₁₂₁ and VEGF₁₆₅ in citrate plasma, and flow cytometry was used to measure astrocyte-derived EVs in plasma. The mean concentration of soluble VEGF₁₂₁ (sVEGF₁₂₁) was significantly higher in patients with SED than healthy controls (P = 0.043). Mean sVEGF₁₆₅ was significantly lower in patients with MDD than patients with SED (P = 0.004) or healthy controls (P = 0.037). Mean sVEGF_total was significantly higher in patients with SED than in patients with MDD (P = 0.021) and also higher in patients with SED than healthy controls (P = 0.040). Levels of sVEGF₁₂₁ were positively correlated with levels of astrocyte-derived EVs only in patients with SED (P = 0.0128). The same was true of levels of sVEGF_total and astrocyte-derived EVs (P = 0.0046). Differing levels of VEGF isoforms may reflect different pathophysiological mechanisms in SED and MDD. Further research is needed to better understand the potential roles of VEGF isoforms and astrocyte-derived EVs in mental disorders.

Predicting Depression in Community Dwellers Using a Machine Learning Algorithm

Depression is one of the leading causes of disability worldwide. Given the socioeconomic burden of depression, appropriate depression screening for community dwellers is necessary. We used data from the 2014 and 2016 Korea National Health and Nutrition Examination Surveys. The 2014 dataset was used as a training set, whereas the 2016 dataset was used as the hold-out test set. The synthetic minority oversampling technique (SMOTE) was used to control for class imbalances between the depression and non-depression groups in the 2014 dataset. The least absolute shrinkage and selection operator (LASSO) was used for feature reduction and classifiers in the final model. Data obtained from 9488 participants were used for the machine learning process. The depression group had poorer socioeconomic, health, functional, and biological measures than the non-depression group. From the initial 37 variables, 13 were selected using LASSO. All performance measures were calculated based on the raw 2016 dataset without the SMOTE. The area under the receiver operating characteristic curve and overall accuracy in the hold-out test set were 0.903 and 0.828, respectively. Perceived stress had the strongest influence on the classifying model for depression. LASSO can be practically applied for depression screening of community dwellers with a few variables. Future studies are needed to develop a more efficient and accurate classification model for depression.

Can Molecular Biology Propose Reliable Biomarkers for Diagnosing Major Depression?

BACKGROUND

Modern medicine has provided considerable knowledge of the pathophysiology of mental disorders at the body, systemic, organ and neurochemical levels of the biological organization of the body. Modern clinical diagnostics of depression have some problems, that is why psychiatric society makes use of diagnostics and taxonomy of different types of depression by implemention of modern molecular biomarkers in diagnostic procedures. But up to now, there are no reliable biomarkers of major depressive disorder (MDD) and other types of depression.

OBJECTIVE

The purpose of this review is to find fundamentals in pathological mechanisms of depression, which could be a basis for development of molecular and genetic biomarkers, being the most feasible for clinical use.

METHOD

This review summarizes the published data using PubMed, Science Direct, Google Scholar and Scopus.

RESULTS

In this review, we summarized and discussed findings in molecular biology, genetics, neuroplasticity, neurotransmitters, and neuroimaging that could increase our understanding of the biological foundations of depression and show new directions for the development of reliable biomarkers. We did not find any molecular and genetic biomarker approved for the clinic. But the Genome-Wide Association Study method promises some progress in the development of biomarkers based on SNP in the future. Epigenetic factors also are a promising target for biomarkers. We have found some differences in the etiology of different types of atypical and melancholic depression. This knowledge could be the basis for development of biomarkers for clinical practice in diagnosis, prognosis and selection of treatment.

CONCLUSION

Depression is not a monoetiological disease. Many pathological mechanisms are involved in depression, thus up to now, there is no approved and reliable biomarker for diagnosis, prognosis and correction of treatment of depression. The structural and functional complexity of the brain, the lack of invasive technology, poor correlations between genetic and clinical manifestation of depression, imperfect psychiatric classification and taxonomy of subtypes of disease are the main causes of this situation. One of the possible ways to come over this situation can be to pay attention to the trigger mechanism of disease and its subtypes. Researchers and clinicians should focus their efforts on searching the trigger mechanism of depression and different types of it . HPA axis can be a candidate for such trigger in depression caused by stress, because it influences the main branches of disease: neuroinflammation, activity of biogenic amines, oxidative and nitrosative stress, epigenetic factors, metabolomics, etc. But before we shall find any trigger mechanism, we need to create complex biomarkers reflecting genetic, epigenetic, metabolomics and other pathological changes in different types of depression. Recently the most encouraging results have been obtained from genetics and neuroimaging. Continuing research in these areas should be forced by using computational, statistical and systems biology approaches, which can allow to obtain more knowledge about the neurobiology of depression. In order to obtain clinically useful tests, search for biomarkers should use appropriate research methodologies with increasing samples and identifying more homogeneous groups of depressed patients.

The Role of Neurotrophic Factors in Pathophysiology of Major Depressive Disorder

According to the neurotrophic hypothesis of major depressive disorder (MDD), impairment in growth factor signaling might be associated with the pathology of this illness. Current evidence demonstrates that impaired neuroplasticity induced by alterations of neurotrophic growth factors and related signaling pathways may be underlying to the pathophysiology of MDD. Brain-derived neurotrophic factor (BDNF) is the most studied neurotrophic factor involved in the neurobiology of MDD. Nevertheless, developing evidence has implicated other neurotrophic factors, including neurotrophin-3 (NT-3), neurotrophin-4 (NT-4), nerve growth factor (NGF), vascular endothelial growth factor (VEGF), insulin-like growth factor (IGF), glial cell-derived neurotrophic factor (GDNF), and fibroblast growth factor (FGF) in the MDD pathophysiology. Here, we summarize the current literature on the involvement of neurotrophic factors and related signaling pathways in the pathophysiology of MDD.

Comparison of Regression and Machine Learning Methods in Depression Forecasting Among Home-Based Elderly Chinese: A Community Based Study

BACKGROUND

Depression is highly prevalent and considered as the most common psychiatric disorder in home-based elderly, while study on forecasting depression risk in the elderly is still limited. In an endeavor to improve accuracy of depression forecasting, machine learning (ML) approaches have been recommended, in addition to the application of more traditional regression approaches.

METHODS

A prospective study was employed in home-based elderly Chinese, using baseline (2011) and follow-up (2013) data of the China Health and Retirement Longitudinal Study (CHARLS), a nationally representative cohort study. We compared four algorithms, including the regression-based models (logistic regression, lasso, ridge) and ML method (random forest). Model performance was assessed using repeated nested 10-fold cross-validation. As the main measure of predictive performance, we used the area under the receiver operating characteristic curve (AUC).

RESULTS

The mean AUCs of the four predictive models, logistic regression, lasso, ridge, and random forest, were 0.795, 0.794, 0.794, and 0.769, respectively. The main determinants were life satisfaction, self-reported memory, cognitive ability, ADL (activities of daily living) impairment, CESD-10 score. Life satisfaction increased the odds ratio of a future depression by 128.6% (logistic), 13.8% (lasso), and 13.2% (ridge), and cognitive ability was the most important predictor in random forest.

CONCLUSIONS

The three regression-based models and one ML algorithm performed equally well in differentiating between a future depression case and a non-depression case in home-based elderly. When choosing a model, different considerations, however, such as easy operating, might in some instances lead to one model being prioritized over another.

Peripheral Markers of Depression

Major Depressive Disorder (MDD) is a leading cause of disability worldwide, creating a high medical and socioeconomic burden. There is a growing interest in the biological underpinnings of depression, which are reflected by altered levels of biological markers. Among others, enhanced inflammation has been reported in MDD, as reflected by increased concentrations of inflammatory markers-C-reactive protein, interleukin-6, tumor necrosis factor-α and soluble interleukin-2 receptor. Oxidative and nitrosative stress also plays a role in the pathophysiology of MDD. Notably, increased levels of lipid peroxidation markers are characteristic of MDD. Dysregulation of the stress axis, along with increased cortisol levels, have also been reported in MDD. Alterations in growth factors, with a significant decrease in brain-derived neurotrophic factor and an increase in fibroblast growth factor-2 and insulin-like growth factor-1 concentrations have also been found in MDD. Finally, kynurenine metabolites, increased glutamate and decreased total cholesterol also hold promise as reliable biomarkers for MDD. Research in the field of MDD biomarkers is hindered by insufficient understanding of MDD etiopathogenesis, substantial heterogeneity of the disorder, common co-morbidities and low specificity of biomarkers. The construction of biomarker panels and their evaluation with use of new technologies may have the potential to overcome the above mentioned obstacles.

Peripheral vascular endothelial growth factor changes after transcranial magnetic stimulation in treatment-resistant depression

OBJECTIVES

To determine if vascular endothelial growth factor (VEGF) changes with transcranial magnetic stimulation (TMS) in treatment-resistant major depressive disorder (MDD).

METHODS

Serum from a naturalistic population of 15 patients with MDD was collected at baseline and after standard TMS treatment. VEGF concentration was determined via ELISA. Inventory of Depressive Symptomatology Self Report and Patient Health Questionnaire were used as a measure of depression symptom severity, clinical response and remission. Mann-Whitney U and Kendall's Tau Correlation were used for continuous variables.

RESULTS

VEGF increased from pre- to post-TMS (+30.3%) in remitters whereas VEGF decreased in non-remitters (-9.87%) (P < 0.05). This same pattern was observed when comparing mean %change in VEGF between responders (+14.7%) and non-responders (-14.9%) (P = 0.054). Correlation was present between change in VEGF concentration (baseline to post) and change in Inventory of Depressive Symptomatology-Self Report at Tx30 (r = -0.371, P < 0.054), reflecting greater increases in VEGF linked to greater improvement in depressive symptoms following the standard 6-week course of TMS.

CONCLUSION

Patients with a successful treatment with TMS had significantly greater increase in VEGF from baseline to after treatment compared to non-responders/non-remitters and a larger increase in VEGF was associated with greater improvement in depressive symptoms after TMS. This is the first report examining VEGF levels in depressed patients receiving TMS. This study provides correlative data supporting further investigation into VEGF's role as an important mediator in the processes underpinning TMS' antidepressant effects and as a potential biomarker of clinical outcomes.

Dissecting major depression: The role of blood biomarkers and adverse childhood experiences in distinguishing clinical subgroups

BACKGROUND

The syndromic diagnosis of major depressive disorder (MDD) is associated with individual differences in prognosis, course, treatment response, and outcome. There is evidence that patients with a history to adverse childhood experiences (ACEs) may belong to a distinct clinical subgroup. The combination of data on ACEs and blood biomarkers could allow the identification of diagnostic MDD subgroups.

METHODS

We selected several blood markers (global DNA methylation, and VEGF-a, TOLLIP, SIRT1, miR-34a genes) among factors that contribute to the pathogenetic mechanisms of MDD. We examined their level in 37 MDD patients and 30 healthy subjects. ACEs were measured by the Parental Bonding Instrument and the Childhood Trauma Questionnaire.

RESULTS

We found significant differences between patients and healthy subjects in three biomarkers (TOLLIP, VEGF-a, and global DNA methylation), independently from the confounding effect of parental care received. By contrast, SIRT1 differences were modulated by quality of parental care. The lowest levels of SIRT1 were recorded in patients with active symptoms and low maternal/paternal care. miR-34a and SIRT1 levels were associated with MDD symptoms especially in early-life stressed patients.

LIMITATIONS

Small sample size, no information on personality comorbidity and suicidal history, cross-sectional definition of remission, and lack of follow-up.

CONCLUSIONS

Our findings suggest that the levels of global DNA methylation, TOLLIP, and VEGF-a reflect pathophysiological changes associated with MDD that are independent from the long-term effects of low parental care. This study also suggests that SIRT1 may be an additional variable distinguishing the ecophenotype that includes MDD patients with exposure to ACEs.

Vascular endothelial growth factor in major depressive disorder, schizophrenia, and bipolar disorder: A network meta-analysis

The peripheral levels of vascular endothelial growth factor (VEGF) have been studied in major psychiatric diseases compared with healthy controls (HCs), but the results were inconsistent. Moreover, few studies have compared VEGF levels between these psychiatric diseases. The aim of the present study was to compare blood VEGF levels in major depressive disorder (MDD), schizophrenia (SCZ), bipolar disorder either in a manic episode, a depressive episode, or a euthymic state, and HC. We supposed that VEGF levels may be elevated in some of these diseases as a potential biomarker. In this study, forty-four studies with 6343 participants were included, and network meta-analysis was used to synthesize evidence from both direct and indirect comparisons. The main analysis showed that no significant differences were found between these groups. Subgroup analysis found that patients with MDD may have higher blood VEGF levels than patients with SCZ when the levels were measured through ELISA, and VEGF levels were increased in medication-treated MDD patients compared with HCs. Taken together, blood VEGF levels may be unaltered in these psychiatric disorders, while detection of VEGF in blood by ELISA may a feasible way to distinguish MDD and SCZ. Further replicated studies with larger samples are needed.

Major depression accompanied with inflammation and multiple cytokines alterations: Evidences from clinical patients to macaca fascicularis and LPS-induced depressive mice model

BACKGROUND

Inflammation progress has been consistently implicated in the pathophysiology of major depressive disorder (MDD). However, the underlying mechanism of inflammation and depressive symptoms still far from being fully elucidated. In addition, studies on emotional disorders could also benefit from model of the non-human primates. To explore the difference of serum multi-cytokines levels among the MDD patients and depressed macaca fascicularis as well as LPS-treated mice, thus may find the reliable potential biomarkers for MDD.

METHODS

Serum multi-cytokines levels among MDD patients (n = 44) and depressed macaca fascicularis (n = 6) together with controls (n = 22 for human, n = 6 for macaques) were detected by the Bio-Plex cytokines panel. Then five of these serum cytokines in LPS-treated mice were measured via ELISA. Furthermore, these cytokines protein expressions were validated by western blotting in three depression-related regions of LPS-treated mice.

RESULTS

Here, we found that MDD patients displayed increased concentration of 13 proinflammatory and anti-inflammatory cytokines accompanied with one decreased cytokine in peripheral serum. Meanwhile, the naturally occurring depression (NOD) macaca fascicularis merely exhibited elevated concentration of 4 peripheral cytokines (IL-6, IL-8, MCP-1, VEGF), which were in accordance with the outcomes of MDD patients. Importantly, the serum and brain tissues of LPS-treated mice also emerged similar cytokines alterations.

CONCLUSION

In summary, our findings strengthen the evidence that cytokines were associated with the depression, and the IL-6 and VEGF may as predictive biomarkers for novel diagnostic as well as therapeutic of depression. The hypothalamus may as a key brain region involve in the inflammatory related depressive-like behaviors.

Acute exposure to low-level light at night is sufficient to induce neurological changes and depressive-like behavior

The advent and wide-spread adoption of electric lighting over the past century has profoundly affected the circadian organization of physiology and behavior for many individuals in industrialized nations; electric lighting in homes, work environments, and public areas have extended daytime activities into the evening, thus, increasing night-time exposure to light. Although initially assumed to be innocuous, chronic exposure to light at night (LAN) is now associated with increased incidence of cancer, metabolic disorders, and affective problems in humans. However, little is known about potential acute effects of LAN. To determine whether acute exposure to low-level LAN alters brain function, adult male, and female mice were housed in either light days and dark nights (LD; 14 h of 150 lux:10 h of 0 lux) or light days and low level light at night (LAN; 14 h of 150 lux:10 h of 5 lux). Mice exposed to LAN on three consecutive nights increased depressive-like responses compared to mice housed in dark nights. In addition, female mice exposed to LAN increased central tendency in the open field. LAN was associated with reduced hippocampal vascular endothelial growth factor-A (VEGF-A) in both male and female mice, as well as increased VEGFR1 and interleukin-1β mRNA expression in females, and reduced brain derived neurotrophic factor mRNA in males. Further, LAN significantly altered circadian rhythms (activity and temperature) and circadian gene expression in female and male mice, respectively. Altogether, this study demonstrates that acute exposure to LAN alters brain physiology and can be detrimental to well-being in otherwise healthy individuals.

Lower plasma vascular endothelial growth factor A in major depressive disorder not normalized after antidepressant treatment: A case control study

OBJECTIVE

Vascular endothelial growth factor A is a growth factor with pro-angiogenic and neurotrophic properties. Anti-vascular endothelial growth factor A treatments, used to treat cancers and opthalmic diseases, are known to induce depressive symptoms. Thus, we hypothesized that vascular endothelial growth factor A plasma levels are low in patients experiencing a major depressive episode in the context of major depressive disorder, which consequently increase after antidepressant treatment. The aim of this study was to compare plasma vascular endothelial growth factor A levels in patients with major depressive episode-major depressive disorder before and after antidepressant treatment.

METHODS

Vascular endothelial growth factor A fasting plasma levels of 469 major depressive episode-major depressive disorder patients were compared with healthy controls. Depressed patients were assessed for remission after 3 and 6 months of antidepressant treatment. Bivariate and multivariate analyses adjusted for sex, age, body mass index and tobacco use were performed.

RESULTS

As compared to healthy controls, major depressive episode patients had lower vascular endothelial growth factor A, 66.0 (38.3) pg/mL (standard deviation) vs 83.2 (49.2) pg/mL, p < 0.0001. Plasma vascular endothelial growth factor A levels did not change after antidepressant treatment, even in remitters, and remained lower than those of healthy controls, 64.9 (39.3) pg/mL vs 83.2 (49.2) pg/mL, p < 0.0001.

CONCLUSION

Depressed patients with major depressive disorder have lower plasma vascular endothelial growth factor A levels than healthy controls during their major depressive episode and after remission following antidepressant treatment. New strategies targeting enhancement of plasma vascular endothelial growth factor A could be promising for the prevention and treatment of major depressive disorder.

Daytime melatonin levels in saliva are associated with inflammatory markers and anxiety disorders

BACKGROUND

The bidirectional interaction between melatonin and the immune system has largely gone unexplored in a clinical context and especially in a psychiatric population. This study explored the association between melatonin during the day and inflammatory cytokines in young adult patients seeking psychiatric care.

METHODS

Samples and data were collected from 108 young adults (mean age 21, SD = 2) at an outpatient clinic for affective disorders. Daytime saliva melatonin levels were analyzed with enzyme-linked immunosorbent assay (ELISA) in relation to normalized serum expression levels of 72 inflammatory markers in a proximity extension assay (PEA). In a post hoc analysis the markers associated with melatonin were tested in a generalized linear model to see whether there is a relationship to anxiety disorder or depression.

RESULTS

After Bonferroni correction for multiple testing, melatonin levels at 11:00 were positively correlated with CD5 (p = 4.2e-4). Melatonin levels after lunch were correlated with CCL2/MCP-1 (p = 4.2e-4), CCL3/MPI-1α (p = 6.5e-4) and VEGF-A (p = 5.3e-6). In the generalized linear model, positive associations were found for the presence of any anxiety disorder with melatonin after lunch (p = 0.046), VEGF-A (p = 0.001) and CCL3/MPI-1α (p = 0.001).

CONCLUSION

Daytime saliva levels of melatonin were related to several inflammatory markers in young adults with psychiatric disorders. This observation likely reflects the bidirectional relationship between melatonin production and the immune system. These findings may have relevance for the understanding of psychiatric disorders and other conditions associated with low-grade inflammation.

Predicting future onset of depression among community dwelling adults in the Republic of Korea using a machine learning algorithm

Because depression has high prevalence and cause enduring disability, it is important to predict onset of depression among community dwelling adults. In this study, we aimed to build a machine learning-based predictive model for future onset of depression. We used nationwide survey data to construct training and hold-out test set. The class imbalance was dealt with the Synthetic Minority Over-sampling Technique. A tree-based ensemble method, random forest, was used to build a predictive model. Depression was defined by 9 or more on the Center for Epidemiologic Studies - Depression Scale 11 items version. Hyperparameters were tuned throughout the 10-fold cross-validation. A total of 6,588 (6,067 of non-depression and 521 of depression) participants were included in the study. The area under receiver operating characteristics curve was 0.870. The overall accuracy, sensitivity, and specificity were 0.862, 0.730, and 0.866, respectively. Satisfactions for leisure, familial relationship, general, social relationship, and familial income had importance in building predictive model for the onset of future depression. Our study demonstrated that predicting future onset of depression by using survey data could be possible. This predictive model is expected to be used for early identification of individuals at risk for depression and secure time to intervention.

Association between ideal cardiovascular health and depression incidence: a longitudinal analysis of ELSA-Brasil

OBJECTIVE

We investigated whether ideal cardiovascular health (ICH), a metric proposed by the American Heart Association, predicts depression development.

METHODS

Cohort analysis from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Adults with no current depression and other common mental disorders, cardiovascular diseases, and antidepressant drug use at baseline had their ICH (composite score of smoking, dietary habits, body mass index, blood pressure, fasting glucose, cholesterol, and physical activity) assessed and classified into poor, intermediate, and optimal. Depression was assessed using the Clinical Interview Schedule-Revised (CIS-R). Poisson regression models, adjusted for sociodemographic factors and alcohol consumption, were employed. Stratified analyses were performed for age and sex.

RESULTS

We included 9214 participants (mean age 52 ± 9 years, 48.6% women). Overall depression incidence at 3.8-year follow-up was 1.5%. Intermediate and poor ICH significantly increased the risk rate (RR) of developing depression (2.48 [95%CI 1.06-5.78] and 3 [1.28-7.03], respectively) at a 3.8-year follow-up. Higher ICH scores decreased the rate of depression development (RR = 0.84 [0.73-0.96] per metric). Stratified analyses were significant for women and adults < 55 years old.

CONCLUSIONS

Poor cardiovascular health tripled depression risk at follow-up in otherwise healthy adults. Ameliorating cardiovascular health might decrease depression risk development.

Growth factors and neurotrophins in patients with stress-related exhaustion disorder

Growth factors, such as vascular endothelial growth factor (VEGF) and epidermal growth factor (EGF), and neurotrophic factors, including brain-derived neurotophic factor (BDNF), have attracted attention in studies of the biological effects of long-term stress exposure due to their neuroprotective roles. This study investigated whether circulating levels of EGF, VEGF and BDNF were altered in individuals with stress-related exhaustion disorder. Forty patients diagnosed with exhaustion disorder and 40 healthy subjects (50% women) provided fasting blood samples for analysis of EGF, VEGF, and BDNF in plasma. We found significantly lower levels of EGF, VEGF, and BDNF in patients with ED compared to healthy controls. This pattern was seen in both male and female patients. Given the important roles of BDNF and VEGF for brain plasticity and neurogenesis, decreased levels after long-term stress exposure could indicate increased risk of neuronal damage and cognitive impairments in this patient group.

Plasma brain-derived neurotrophic factor (pBDNF) and executive dysfunctions in patients with major depressive disorder

Objectives: Executive dysfunctions are frequently seen in patients with major depressive disorder (MDD) and normalise in many cases during effective antidepressant therapy. This study investigated whether a normalisation of executive dysfunctions during antidepressant treatment correlates with or can be predicted by clinical parameters or levels of brain-derived neurotrophic factor (BDNF).Methods: In 110 MDD patients with executive dysfunctions (percentile <16), executive functions and plasma BDNF levels were analysed at baseline, and days 14 and 56 of an antidepressant treatment. BDNF exon IV and P11 methylation status was studied at baseline.Results: Eighty patients (73%) experienced a normalisation of executive dysfunctions, while 30 (27%) suffered from persistent dysfunctions until day 56. Patients with persistent dysfunctions had significantly higher HAMD scores at days 14 and 56, and lower plasma BDNF levels at each time point than patients with a normalisation of dysfunctions (F₁= 10.18; P = 0.002). This was seen for verbal fluency, but not processing speed. BDNF exon IV and p11 promoter methylation was not associated with test performance.Conclusions: Our results corroborate a concomitant amelioration of executive dysfunctions with successful antidepressant therapy and support a role of BDNF in the neural mechanisms underlying the normalisation of executive dysfunctions in MDD.ClinicalTrials.gov number: NCT00974155; EudraCT: 2008-008280-96.

Peroxisome proliferator-activated receptor gamma co-activator-1 alpha in depression and the response to electroconvulsive therapy

BACKGROUND

The transcriptional coactivator peroxisome proliferator-activated receptor-γ coactivator (PGC-1α), termed the 'master regulator of mitochondrial biogenesis', has been implicated in stress and resilience to stress-induced depressive-like behaviours in animal models. However, there has been no study conducted to date to examine PGC-1α levels in patients with depression or in response to antidepressant treatment. Our aim was to assess PGC-1α mRNA levels in blood from healthy controls and patients with depression pre-/post-electroconvulsive therapy (ECT), and to examine the relationship between blood PGC-1α mRNA levels and clinical symptoms and outcomes with ECT.

METHODS

Whole blood PGC-1α mRNA levels were analysed in samples from 67 patients with a major depressive episode and 70 healthy controls, and in patient samples following a course of ECT using quantitative real-time polymerase chain reaction (qRT-PCR). Exploratory subgroup correlational analyses were carried out to determine the relationship between PGC-1α and mood scores.

RESULTS

PGC-1α levels were lower in patients with depression compared with healthy controls (p = 0.03). This lower level was predominantly accounted for by patients with psychotic unipolar depression (p = 0.004). ECT did not alter PGC-1α levels in the depressed group as a whole, though exploratory analyses revealed a significant increase in PGC-1α in patients with psychotic unipolar depression post-ECT (p = 0.045). We found no relationship between PGC-1α mRNA levels and depression severity or the clinical response to ECT.

CONCLUSIONS

PGC-1α may represent a novel therapeutic target for the treatment of depression, and be a common link between various pathophysiological processes implicated in depression.

Reduced vascular endothelial growth factor levels in the cerebrospinal fluid in patients with treatment resistant major depression and the effects of electroconvulsive therapy-A pilot study

BACKGROUND

Several lines of evidence are pointing towards an involvement of the vascular endothelial growth factor (VEGF) in the pathophysiology of depression. There are studies analyzing blood levels of VEGF in patients with depression compared to controls, but a data on cerebrospinal fluid (CSF) levels of VEGF in patients with depression are lacking.

METHOD

CSF VEGF levels were measured in patients (n = 12) with a severe, treatment-resistant depressive episode before and after the antidepressant treatment by a course of electroconvulsive therapy (ECT) and compared to age- and sex-matched controls (n = 20).

RESULTS

The patients with depression showed lower mean VEGF levels in the CSF prior to ECT than the controls (p = 0.041). Regarding the patients, CSF VEGF concentration at baseline and after the complete ECT treatment did not differ from each other (p = 0.78).

LIMITATIONS

Major limitations of this study are the small sample size and that data from corresponding serum levels cannot be provided. Another limitation is that the controls were not completely healthy, as they were recruited from a memory clinic with subjective complaints. The timing of the second sample might have been suboptimal, when taking into account that there might be an on-going phase of re-equilibrating after ECT.

CONCLUSIONS

CSF VEGF concentrations were lower in a clinical sample of patients with treatment-resistant depression compared with matched controls. Additionally, no change in CSF VEGF levels during a course of ECT could be detected.

Using heart rate profiles during sleep as a biomarker of depression

BACKGROUND

Abnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may provide new information about physiological sleep signatures of depression. This study assessed the validity of an algorithm using patterns of heart rate changes during sleep to discriminate between individuals with depression and healthy controls.

METHODS

A heart rate profiling algorithm was modeled using machine-learning based on 1203 polysomnograms from individuals with depression referred to a sleep clinic for the assessment of sleep abnormalities, including insomnia, excessive daytime fatigue, and sleep-related breathing disturbances (n = 664) and mentally healthy controls (n = 529). The final algorithm was tested on a distinct sample (n = 174) to categorize each individual as depressed or not depressed. The resulting categorizations were compared to medical record diagnoses.

RESULTS

The algorithm had an overall classification accuracy of 79.9% [sensitivity: 82.8, 95% CI (0.73-0.89), specificity: 77.0, 95% CI (0.67-0.85)]. The algorithm remained highly sensitive across subgroups stratified by age, sex, depression severity, comorbid psychiatric illness, cardiovascular disease, and smoking status.

CONCLUSIONS

Sleep-derived heart rate patterns could act as an objective biomarker of depression, at least when it co-occurs with sleep disturbances, and may serve as a complimentary objective diagnostic tool. These findings highlight the extent to which some autonomic functions are impaired in individuals with depression, which warrants further investigation about potential underlying mechanisms.

The role of hormonal, metabolic and inflammatory biomarkers on sleep and appetite in drug free patients with major depression: A systematic review

BACKGROUND

Major depressive disorder (MDD) is a complex and heterogeneous disorder in which clinical symptoms can widely differ among patients. Neurovegetative symptoms, i.e. decreased or increased appetite, changes in body weight and sleep disturbances, described as 'melancholic' or 'atypical' features of a depressive episode, are the most variable symptoms among patients with MDD. We hypothesized biomarkers differences underlying this neurovegetative variability in major depression.

METHODS

We systematically reviewed, according to the PRISMA guidelines, the role of specific metabolic, hormonal and inflammatory biomarkers in drug-free MDD patients, that could have neurobiological effects on appetite, weight regulation and circadian rhythms, influencing eating behaviour and sleep patterns. All studies regarding the co-occurrence of disturbed sleep and appetite were examined.

RESULTS

Besides the well-known leptin and ghrelin, other biomarkers such as BDNF, VEGF, NPY, orexin, and the recent discovered nesfatin-1 seem to be involved in neurovegetative changes in depressive disorders playing a role in the regulation of affective states, stress reactions and sleep patterns. Interestingly, based on the existing evidence, ghrelin, orexin and nesfatin-1 could be linked both to sleep and appetite regulation in depressed patients.

LIMITATIONS

Heterogeneous studies with low sample size.

CONCLUSIONS

Despite the wide heterogeneity of results, studies on biomarkers of appetite and sleep in MDD are an interesting field of research to explain the neurobiological substrates of depressive symptoms that deserve further investigation.

Epistatic Interaction Between 5-HT1A and Vascular Endothelial Growth Factor Gene Polymorphisms in the Northern Chinese Han Population With Major Depressive Disorder

Aims: Serotonin 1A receptor (5-HT1A) and vascular endothelial growth factor (VEGF) are widely expressed in the neurons of the hippocampus and have significant roles in the pathophysiological processes of major depressive disorders (MDDs). The present study was designed to examine 5-HT1A and VEGF gene polymorphisms and whether the gene-gene interaction of 5-HT1A and VEGF gene variants was associated with MDD. Methods: A total of 264 MDD patients and 264 healthy controls were included in the present genetic study. The rs6295, rs1364043, and rs878567 single-nucleotide polymorphisms (SNPs) in the 5-HT1A gene and the rs699947, rs833061, and rs2010963 SNPs in the VEGF gene were selected for genotypic analyses. The generalized multifactor dimensionality reduction method was employed to assess their interactions. Results: The genotype distributions of the two genes' respective SNPs were significantly different between patients and controls for 5-HT1A rs6295 (p = 0.041) and VEGF rs2010963 (p = 0.035); however, no significant allelic variation in 5-HT1A (rs6295, rs1364043, and rs878567) and VEGF (rs699947, rs833061, and rs2010963) was found. The interactions between 5-HT1A (rs6295, rs1364043, and rs878567) and VEGF (rs699947, rs833061, and rs2010963) had a cross-validation (CV) consistency of 10/10 and a p value of 0.0107, which was considered as the best generalized multifactor dimensionality reduction (GMDR) model. Conclusions: The interactions between 5-HT1A and VEGF gene polymorphisms may play a key role in the development of MDD in the Northern Chinese Han population.

Vascular endothelial growth factor plasma levels in depression and following electroconvulsive therapy

Both animal and human studies have implicated the neurotrophic and angiogenic mediator vascular endothelial growth factor (VEGF) in depression, with meta-analyses, indicating that protein levels are raised in patients with depression. In line with this, we have previously shown that VEGFA mRNA levels are higher in whole blood from patients with depression compared to controls, in particular in patients with psychotic unipolar depression, and that treatment with electroconvulsive therapy (ECT) alters VEGFA mRNA levels. The aim of the present study was, therefore, to extend this previous work by assessing plasma VEGF protein levels in patients with depression compared to healthy controls, and in patients following treatment with ECT. We found that there was no difference between controls and patients with depression with regard to plasma VEGF (p = 0.59), and that VEGF levels were unaltered by ECT (p = 0.09) after correction for potential covariates. We found no correlation between VEGF protein and mRNA levels. Within the subgroup of patients receiving treatment with bitemporal ECT (n = 34), we identified a moderate negative correlation (ρ = - 0.54, p = 0.001) between the change in VEGF and the change in depression severity following treatment; however, no other association between VEGF and mood, responder/remitter status, polarity of depression, or presence of psychosis were found. Overall, our results indicate that the measurement of VEGF protein is not a useful marker for depression or response to treatment, and suggest that the measurement of VEGFA mRNA may prove more useful.

Cross-species evidence from human and rat brain transcriptome for growth factor signaling pathway dysregulation in major depression

An enhanced understanding of the pathophysiology of depression would facilitate the discovery of new efficacious medications. To this end, we examined hippocampal transcriptional changes in rat models of disease and in humans to identify common disease signatures by using a new algorithm for signature-based clustering of expression profiles. The tool identified a transcriptomic signature comprising 70 probesets able to discriminate depression models from controls in both Flinders Sensitive Line and Learned Helplessness animals. To identify disease-relevant pathways, we constructed an expanded protein network based on signature gene products and performed functional annotation analysis. We applied the same workflow to transcriptomic profiles of depressed patients. Remarkably, a 171-probesets transcriptional signature which discriminated depressed from healthy subjects was identified. Rat and human signatures shared the SCARA5 gene, while the respective networks derived from protein-based significant interactions with signature genes contained 25 overlapping genes. The comparison between the most enriched pathways in the rat and human signature networks identified a highly significant overlap (p-value: 3.85 × 10-6) of 67 terms including ErbB, neurotrophin, FGF, IGF, and VEGF signaling, immune responses and insulin and leptin signaling. In conclusion, this study allowed the identification of a hippocampal transcriptional signature of resilient or susceptible responses in rat MDD models which overlapped with gene expression alterations observed in depressed patients. These findings are consistent with a loss of hippocampal neural plasticity mediated by altered levels of growth factors and increased inflammatory responses causing metabolic impairments as crucial factors in the pathophysiology of MDD.

Blood-brain barrier regulation in psychiatric disorders

The blood-brain barrier (BBB) is a dynamic interface between the peripheral blood supply and the cerebral parenchyma, controlling the transport of material to and from the brain. Tight junctions between the endothelial cells of the cerebral microvasculature limit the passage of large, negatively charged molecules via paracellular diffusion whereas transcellular transportation across the endothelial cell is controlled by a number of mechanisms including transporter proteins, endocytosis, and diffusion. Here, we review the evidence that perturbation of these processes may underlie the development of psychiatric disorders including schizophrenia, autism spectrum disorder (ASD), and affective disorders. Increased permeability of the BBB appears to be a common factor in these disorders, leading to increased infiltration of peripheral material into the brain culminating in neuroinflammation and oxidative stress. However, although there is no common mechanism underpinning BBB dysfunction even within each particular disorder, the tight junction protein claudin-5 may be a clinically relevant target given that both clinical and pre-clinical research has linked it to schizophrenia, ASD, and depression. Additionally, we discuss the clinical significance of the BBB in diagnosis (genetic markers, dynamic contrast-enhanced-magnetic resonance imaging, and blood biomarkers) and in treatment (drug delivery).

Baseline serum vascular endothelial growth factor levels predict treatment response to antipsychotic medication in patients with schizophrenia

Vascular endothelial growth factor (VEGF) is implicated in angiogenesis, blood flow, and neuroplasticity, which have previously been shown to contribute to schizophrenia and the mechanisms of action of antipsychotic medication. The aim of the present study was to investigate whether baseline serum VEGF levels predict treatment responses to antipsychotic medication. Drug-free adults with schizophrenia were administered monotherapy with atypical antipsychotic drugs for 6 weeks. Participants' psychiatric symptoms were assessed using the positive and negative symptom scale (PANSS) before and after treatment. Blood samples for VEGF measurements were collected from 201 participants comprising 83 healthy controls and 118 patients (i.e. only on admission). Baseline VEGF levels in adults with schizophrenia were significantly lower than those in the control group (t = 3.656, df = 199, P < 0.001). In particular, pretreatment VEGF levels were significantly higher in patients responding to drug treatment at follow-up (≥ 50% reduction in initial PANSS total) (t = 4.743, df = 116, P < 0.001). The predictive power of serum VEGF levels was investigated using receiver operating characteristic curves. The area under the curve was 0.774 (95% confidence interval 0.688-0.846); for fixed specificity of 78.8%, the corresponding sensitivity was 63.5%. Results from this preliminary experiment suggest high baseline serum concentrations of VEGF may predict a better response to antipsychotic medications in adults with schizophrenia. Further studies using larger sample sizes are needed to verify the findings.

Exploring the sortilin related receptor, SorLA, in depression

BACKGROUND

Studies of individual biomarkers for depression have shown insufficient sensitivity and specificity for clinical use, and most likely combinations of biomarkers may provide a better signature. The sorting-related receptor with A-type repeats (SorLA) is a well-studied pathogenic factor for Alzheimer's. SorLA belongs to the Vps10p domain receptor family, which also encompasses sortilin and SorCS1-3. All family members have been implicated in neurological and mental disorders. Notably, the SORCS3 gene is genome-wide significantly associated with depression and serum protein levels of sortilin are reduced in depressed individuals. SorLA regulates the activity of neurotrophic factors and cytokines and we hence speculated that SorLA might be implicated in depression.

METHODS

Serum SorLA levels were measured in two well-defined clinical samples using ELISA. Generalized linear models were used in the statistical analyses.

RESULTS

We identified a multivariate model to discriminate depressed individuals from healthy controls. Interestingly, the model consisted of serum SorLA levels and additional four predictors: previous depressive episode, stressful life events, serum levels of sortilin and VEGF. However, as an isolated factor, we observed no significant difference in SorLA levels between 140 depressed individuals and 140 healthy controls. Nevertheless, we observed a significant increase in SorLA levels following 12 weeks of treatment with nortriptyline, but not escitalopram.

LIMITATIONS

The number of biomarkers included in the multivariate model for depression and lack of replication limit our study.

CONCLUSIONS

Our results suggest SorLA as one of five factors that in combination may support the depression diagnosis, but not as an individual biomarker for depression or treatment response.

Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression

Previous studies suggest that neurotrophic factors participate in the development of stroke and depression. So we investigated the utility of these biomarkers as predictive and distinguish model for post stroke depression (PSD). 159 individuals including PSD, stroke without depression (Non-PSD), major depressive disorder (MDD) and normal control groups were recruited and examined the protein and mRNA expression levels of vascular endothelial growth factor (VEGF), vascular endothelial growth factor receptors (VEGFR2), placental growth factor (PIGF), insulin-like growth factor (IGF-1) and insulin-like growth factor receptors (IGF-1R). The chi-square test was used to evaluate categorical variable, while nonparametric test and one-way analysis of variance were applied to continuous variables of general characteristics, clinical and biological changes. In order to explore the predictive and distinguish role of these factors in PSD, discriminant analysis and receiver operating characteristic curve were calculated. The four groups had statistical differences in these neurotrophic factors (all P < 0.05) except VEGF concentration and IGF-1R mRNA (P = 0.776, P = 0.102 respectively). We identified these mRNA expression and protein analytes with general predictive performance for PSD and Non-PSD groups [area under the curve (AUC): 0.805, 95% CI, 0.704-0.907, P < 0.001]. Importantly, there is an excellent predictive performance (AUC: 0.984, 95% CI, 0.964-1.000, P < 0.001) to differentiate PSD patients from MDD patients. This was the first study to explore the changes of neurotrophic factors family in PSD patients, the results intriguingly demonstrated that the combination of protein and mRNA expression of biological factors could use as a predictive and discriminant model for PSD.

Growth Factor Proteins and Treatment-Resistant Depression: A Place on the Path to Precision

Background: Since the neurotrophic hypothesis of depression was formulated, conflicting results have been reported regarding the role of growth factor proteins in depressed patients, including whether there are state or trait alterations found in patients compared to controls and whether they represent predictors of treatment response. Recently it has been hypothesized that heterogeneity of findings within this literature might be partly explained by participants' history of treatment-resistant depression. This study aimed to investigate the role of growth factor proteins in patients with treatment-resistant depression (TRD) undergoing an inpatient intervention. Methods: Blood samples were collected from 36 patients with TRD and 36 matched controls. Patients were assessed both at admission and discharge from a specialist inpatient program. We examined serum biomarker differences between patients and non-depressed matched controls, longitudinal changes after inpatient treatment and relationship to clinical outcomes. Additionally, the influence of potential covariates on biomarker levels were assessed. Results: Patients displayed lower serum levels of brain-derived neurotrophic factor (OR = 0.025; 95% CI = 0.001, 0.500) and vascular endothelial growth factor-C (VEGFC; OR = 0.083, 95% CI = 0.008, 0.839) as well as higher angiopoietin-1 receptor (Tie2; OR = 2.651, 95% CI = 1.325, 5.303) compared to controls. Patients were stratified into responders (56%) and non-responders (44%). Lower VEGFD levels at admission predicted subsequent non-response (OR = 4.817, 95% CI = 1.247, 11.674). During treatment, non-responders showed a decrease in VEGF and VEGFC levels, while responders showed no significant changes. Conclusion: TRD patients demonstrate a deficit of peripheral growth factors and our results suggest that markers of the VEGF family might decline over time in chronically depressed patients in spite of multidisciplinary treatment. The action of angiogenic proteins may play an important role in the pathophysiology of TRD, and pending comprehensive investigation may provide important insights for the future of precision psychiatry.

Developing a deeper insight into reproductive biomarkers

The development of biomarkers of reproductive medicine is still in its infancy because many black boxes are still present in reproductive medicine. Novel approaches to human infertility diagnostics and treatment must be developed because reproductive medicine has lagged behind in the implementation of biomarkers in clinical medicine. Despite the dearth of the available literature, the current rapid pace of publications suggests that this gap will soon be filled therefore; this review is a précis of the research that has been done so far and will provide a basis for the development of biomarkers in reproductive medicine.

Effective litmus gene test for monitoring the quality of blood samples: Application to Alzheimer's disease diagnostics

Gene expression profiles reflect the biologically diverse activities of cells under specific cell environments. Using the transcriptional response of cultured cells to blood composition, we developed a litmus gene assay to discriminate blood samples reflecting different sample qualities or disease conditions. This cell-based litmus gene assay identified six genes (CCL20, CEMIP, IL1B, IL8, PRG2, PTGS2) as potential biomarkers of plasma quality control and the SPC25 gene as a diagnostic biomarker of Alzheimer’s disease (AD). In addition, the SPC25 gene expression level was significantly increased in the cell-based assay using serum samples from patients with mild cognitive impairment (MCI). In conclusion, we demonstrated the effectiveness and potential of a litmus gene assay to detect the orchestrated effects of circulating systemic factors, leading to the successful diagnosis of AD and MCI. This method is broadly applicable to the diagnosis of disease subtypes or patho-physiological stages of complex diseases and tumors.

Peripheral blood microRNA and VEGFA mRNA changes following electroconvulsive therapy: implications for psychotic depression

OBJECTIVE

MicroRNAs are short, non-coding molecules that regulate gene expression. Here, we investigate the role of microRNAs in depression and electroconvulsive therapy (ECT).

METHODS

We performed three studies: a deep sequencing discovery-phase study of miRNA changes in whole blood following ECT (n = 16), followed by a validation study in a separate cohort of patients pre-/post-ECT (n = 37) and matched healthy controls (n = 34). Changes in an experimentally validated gene target (VEGFA) were then analysed in patients pre-/post-ECT (n = 97) and in matched healthy controls (n = 53).

RESULTS

In the discovery-phase study, we found no statistically significant differences in miRNA expression from baseline to end of treatment in the group as a whole, but post hoc analysis indicated a difference in patients with psychotic depression (n = 3). In a follow-up validation study, patients with psychotic depression (n = 7) had elevated baseline levels of miR-126-3p (t = 3.015, P = 0.006) and miR-106a-5p (t = 2.598, P = 0.025) compared to healthy controls. Following ECT, these differences disappeared. Baseline VEGFA levels were significantly higher in depressed patients compared to healthy controls (F(1,144) = 27.688, P = <0.001). Following ECT, there was a significant change in VEGFA levels in the psychotic group only (t = 2.915, P = 0.010).

CONCLUSION

Molecular differences (miRNA and VEGFA) may exist between psychotic and non-psychotic depression treated with ECT.

Primary Blast Causes Delayed Effects without Cell Death in Shell-Encased Brain Cell Aggregates

Previous work in this laboratory used underwater explosive exposures to isolate the effects of shock-induced principle stress without shear on rat brain aggregate cultures. The current study has utilized simulated air blast to expose aggregates in suspension and enclosed within a spherical shell, enabling the examination of a much more complex biomechanical insult. Culture medium-filled spheres were exposed to single pulse overpressures of 15-30 psi (∼6-7 msec duration) and measurements within the sphere at defined sites showed complex and spatially dependent pressure changes. When brain aggregates were exposed to similar conditions, no cell death was observed and no changes in several commonly used biomarkers of traumatic brain injury (TBI) were noted. However, similarly to underwater blast, immediate and transient increases in the protein kinase B signaling pathway were observed at early time-points (3 days). In contrast, the oligodendrocyte marker 2',3'-cyclic nucleotide 3'-phosphodiesterase, as well as vascular endothelial growth factor, both displayed markedly delayed (14-28 days) and pressure-dependent responses. The imposition of a spherical shell between the single pulse shock wave and the target brain tissue introduces greatly increased complexity to the insult. This work shows that brain tissue can not only discriminate the nature of the pressure changes it experiences, but that a portion of its response is significantly delayed. These results have mechanistic implications for the study of primary blast-induced TBI and also highlight the importance of rigorously characterizing the actual pressure variations experienced by target tissue in primary blast studies.